Environmental Accounting 

Using Emergy: Evaluation of Minnesota

United States 

Environmental Protection 

Agency 

Fuels and 

Minerals

Goods and 

Services

Environment

Exports

Goods and Services w/o Iron 

E20 sej/yr 1041

4714

191

Exported Ores and 

Concentrates

6342

1290

Imports

Minnesota

 EPA/600/R-09/002 

 January 2009 

Environmental Accounting Using Emergy: 

Evaluation of Minnesota 

By 

Daniel E. Campbell

USEPA, Office of Research and Development 

National Health and Environmental Effects Research Laboratory 

Atlantic Ecology Division, Narragansett, RI 02882 

Andrew Ohrt 

Arcadis U.S., Inc. 

2300 Eastlake Avenue East, Suite 200 

Seattle, Washington 98102

US Environmental Protection Agency 

Office of Research and Development 

National Health and Environmental Effects Research Laboratory 

 Atlantic Ecology Division 

Narragansett, RI 02882 
Environmental Accounting Using Emergy: Minnesota 

ii 

NOTICE

This report is contribution number AED-08-006 of the Atlantic Ecology Division (AED), National Health and 

Environmental Effects Research Laboratory (NHEERL), Office of Research and Development (ORD). The research 

described here has been funded wholly (or in part) by the U.S. Environmental Protection Agency and the document 

has been subjected to the USEPA’s peer review process and has been approved for publication. However, we note 

that the opinions expressed in this report are those of the authors and they are not necessarily those of the U.S. 

Environmental Protection Agency. In addition, the methodology used in this report is not completely developed and 

the approach itself is not accepted by everyone in the scientific community. Therefore, caution should be employed 

in using the data and conclusions provided here. The data, calculations and conclusions reported herein have not been 

subjected to formal analyses of their uncertainties, and therefore should be viewed with extreme caution; no claims to 

their accuracy and veracity can be made at this time. Technical issues preventing the complete application of these 

methods include better methods to document far-field environmental liabilities such as disturbance to natural carbon, 

nitrogen, and sulfur budgets of regions. Finally, the mention of trade names or commercial products does not 

constitute endorsement or a recommendation for use. 

ABSTRACT

Often questions related to environmental policy are difficult to resolve successfully, because robust solutions 

depend on accurately balancing the needs of both human and natural systems. To accomplish this end the 

socioeconomic and environmental effects of policies must be expressed in common terms so that both the 

contributions of the environment and the contributions of the economy to human well-being are valued fairly. 

Emergy is an accounting quantity that has the property of expressing all forms of energy in terms of their equivalent 

ability to do work when used in the system of which they are a part. Based on past studies and a previous report in 

this series, environmental accounting using emergy has proved to be a method that can be used to objectively value 

the work of the environment, economy and society by using an energy-based unit, the solar emjoule (sej) and a 

combined emergy-monetary unit the emdollar (Em$). Emergy tabulates the available energy of one kind required for 

the production of a product or service i.e., the solar joules used up both directly and indirectly in the past to make the 

product or service. The unit of emergy is the emjoule, which denotes that the energy has been used in the past in 

contrast to a joule of available energy that is an energy potential that can be used in the present. What something can 

do when used within its network is represented by its emergy and not its energy. Thus, energy alone is not a 

sufficient basis for making policy decisions. 

This USEPA Project Report contains an emergy evaluation of the State of Minnesota and it includes a guide to the 

Emergy Analysis methods used to characterize a state within the larger context of its region and nation. A summary 

of the results of this analysis based on the values of emergy indices calculated for the State and their interpretation 

follows: (1) Twenty-one percent of the emergy used in the State in 1997 was derived from home sources, which 

indicates a moderate potential for self-sufficiency. (2) The emergy use per person was 1.53E+17 sej/person. This 

index showed that Minnesotans have a high overall standard of living compared to the national average. (3) The 

import/export emergy ratio showed 1.33 times as much emergy leaving the State in exports as is received in imports, 

which indicates a slight imbalance in the exchange of real wealth with the Nation. However, when iron ore (taconite) 

is removed from the import-export balance, the emergy of exports is only 10% larger than that of the imports. (4) The 

emergy used per square meter (3.23E+12 sej/m2

) indicates that an average location in the State is developed relative 

to an average place in the Nation. (5) The emergy to dollar ratio was 4.66 E+12 sej/$, thus the purchasing power of a 

dollar in Minnesota in 1997 was 1.82 times that of an average place in the United States. This ratio had fallen to 1.69 

times the national purchasing power of a dollar by 2000. (6) The investment ratio was 3.81:1, which indicates a 

relatively low intensity of matching between purchased economic emergy invested from outside the State and the 

emergy of renewable and nonrenewable environmental resources within the State. This index suggests that 

Minnesota is still an attractive place for further economic investment. (7) The environmental loading ratio was 
Environmental Accounting Using Emergy: Minnesota 

iii 

37.1:1, indicating a more intense matching of purchased inputs with renewable energy from the environment than 

was found for West Virginia (20.4:1) or the Nation as a whole (19.6:1). Higher environmental loading ratios 

potentially result in higher stress on ecosystems and a heavier “load” on the waste processing capacity of the 

environment. (8) Minnesota can support 2.6% of the present population at the 1997 standard of living using its 

renewable resources alone in their current state of development compared to 3.0% for West Virginia and 4.9% for the 

Nation. 

Minnesota is a state with large regional differences. The Northeastern region appears to be a hinterland exporting 

vast quantities of emergy in its natural resources. For example, the iron mining sector has a balanced monetary 

exchange but the emergy exchange shows a 42:1 advantage in favor of the buyer. The agricultural and industrial 

regions in the remainder of the State export value added products that command a premium over the average skill 

level used to produce the products imported. This premium paid for the services of Minnesota workers is the main 

reason for the State’s high standard of living relative to other states. Minnesota’s pool of highly educated and skilled 

labor can be attributed to an early and continuing interest in and support for education in the State. Based on this 

evidence the best thing that the State can do to ensure a prosperous future is to continue to educate forward-thinking, 

highly-skilled individuals through further developing and maintaining its school systems. 

Keywords: emergy analysis, environmental accounting, Minnesota, renewable resources, nonrenewable resources, 

sustainability, quality of life, import-export balance 

ACKNOWLEDGMENTS 

We are most grateful to the U.S. Forest Service North Central Research Station and to Pam Jakes of that 

institution for hosting University of Minnesota graduate student, Andrew Ohrt during the time required to complete 

this research. Dr. Jakes participated in research planning and supported the research activities reported here. The 

North Central Research Station and Dr. Jakes provided all logistical support needed by Mr. Ohrt during his stay 

there. In addition, David Bengston provided assistance and consultation on forest resources, as well as on the 

availability of data. The Mid-Continent Ecology Division (MED) of the National Health and Environmental Effects 

Research Laboratory (NHEERL), Office of Research and Development, USEPA provided a venue for discussion of 

this work, insights on the State and half of the funds for its publication. Denis White of the Western Ecology 

Division (WED) of the National Health and Environmental Effects Research Laboratory (NHEERL) performed the 

analysis of the emergy stored in soils. This manuscript was reviewed by Philip Cook of MED, Naomi Detenbeck of 

AED, and Gilman Veith of the Natural Resources Research Institute, University of Minnesota-Duluth. 
Environmental Accounting Using Emergy: Minnesota 

iv 

Preface 

PURPOSE OF THE REPORT 

This USEPA Project Report has several purposes. 

The first purpose is to provide a second peer-reviewed 

report on a state for comparison with the results of our 

original report on West Virginia. The Minnesota and 

West Virginia reports are two analyses in a 

comparative analysis of eight states that were 

evaluated for the years 1997 and 2000. In addition, 

this report serves as a further guide to Emergy 

Analysis with particular emphasis on those methods 

used to characterize a state within the United States 

and the data needs for performing emergy analyses on 

all scales, including an expanded section on 

transformities with many new calculations. This report 

also provides emergy indices for the State of 

Minnesota that are needed to perform a proposed 

regional analysis of sustainability of the Arrowhead 

Region of Northern Minnesota. In this report we 

applied the results of our study to gain an energy 

systems perspective on some current policy questions 

facing the people of Minnesota. 

SIGNIFICANCE OF THE REPORT 

Many people struggle to understand the concept of 

emergy and why we go to so much trouble to 

document economic and ecological flows and storages 

in these terms. The practical answer is that the 

accounts for environmental systems cannot be kept in 

dollars alone, because environmental systems are 

based on both the work of humanity, which is paid for 

by a counter flow of dollars, and the work of 

ecosystems, for which no money is paid. An accurate 

picture of environmental systems requires that we 

account for the flows and storages of energy, matter, 

and information that are responsible for supporting 

economic and social activities and that may not be 

accompanied by flows of money. Energy can be used 

as a common denominator for quantifying all these 

flows. Converting flows of energy to emergy puts the 

work done by the economy and the environment on 

the same basis, so that economic and environmental 

flows are directly comparable. While it is true that 

dollar values are directly comparable, it is also true 

that economic markets only value a subset of the 

products and processes that are important in 

environmental systems. The key synthesis produced 

by Emergy Analysis is an accounting of social, 

economic and environmental flows in common terms 

on an objective basis. Thus, for the first time, what is 

removed from Minnesota is shown in true relationship 

to what is received in return. For example, it is true 

that everyone in Minnesota realizes that farming, 

mining, manufacturing, and timber are important 

sectors in the economy, but this is the first time the 

numbers have been calculated to show the relationship 

of the real wealth (emergy) in natural and human 

capital that supports the flows of emergy and the 

counter current of money moving through these 

sectors annually. The exchange of real wealth between 

Minnesota and the Nation is quantified for the first 

time and contrasted with those of another resource 

rich state, West Virginia. The importance of 

recognizing the true nature of value in exchanges is 

easily illustrated by the inequitable barter between 

Europeans and Native Americans in which ecological 

resources, e.g., animal skins and land of great value, 

were exchanged for relatively less valuable items of 

industrial society. Emergy accounting can potentially 

give environmental managers tools similar to those 

regularly used by financial analysts to make business 

decisions. However, we are far from this point at 

present and there is much work left to be done by 

those who thoughtfully read this report. Further 

development of the emergy analysis methods and 

tools presented in this report and closer coordination 

with existing methods of environmental impact 

assessment, e.g., life cycle assessment, will make it 

possible for managers to first examine complete and 

commensurate economic and environmental 

accounting data before making policy decisions about 

environmental systems. 

The State of Minnesota and its relationships with 

its region and the Nation are characterized in the case 

study presented in this report. Insights from this study 

may be useful in establishing a context for 

determining policies for the State as a whole, but finer 

scale analyses must be performed to address more 

specific environmental management problems, such as 

what is sustainable for a region within the State. In 

addition, the analysis methods described here can be 

used as a guide to creating emergy accounts for any 

state in the United States. 
Environmental Accounting Using Emergy: Minnesota 

v 

STRUCTURE OF THE REPORT 

This technical report gives an overview of the 

emergy accounting and analysis methodology, which 

can be used to evaluate environmental systems on any 

scale of organization (Odum 1996). However, it is 

impossible to condense the methods and insights of a 

comprehensive methodology in a single, relatively 

short document. For this reason, Section 2 (Methods) 

of this paper focuses on methods, calculations and 

data sources needed to evaluate a state within the 

United States of America. Even with this restriction, 

the task is daunting because there are 50 states and 

each one will present the researcher with new 

problems to solve. So far we have begun work on 10 

of the 50 states, and as expected, almost without 

exception each one has presented a new theoretical or 

technical challenge. In Campbell et al. (2005) we 

made the task somewhat easier through the 

development of a method for determining the imports 

to and exports from any state using readily available 

data from the U.S. Census Bureau’s Commodity Flow 

Survey that is performed every 5 years, most recently 

in 1997, 2002, and 2007. Application of the emergy 

analysis method is demonstrated through reporting a 

case study of the State of Minnesota (Section 3), 

which is presented in lieu of a Results section. This 

section of the report is written so that it can stand 

alone as a final report on the Emergy Analysis of 

Minnesota. Those readers who are primarily interested 

in the results of this study can go directly to Section 3. 

The emergy analysis and environmental accounts 

for the State of Minnesota given in the case study 

include the following eight elements that we used to 

characterize any state: (1) a narrative history, (2) a 

detailed energy systems diagram of the state as an 

environmental system with supporting tables, (3) the 

Emergy Income Statement showing annual emergy 

and dollar flows of renewable and nonrenewable 

resources, production, consumption, imports and 

exports, (4) the Emergy Balance Sheet showing some 

of the stored assets in the state, (5) an aggregate 

diagram giving a macroscopic overview of the energy 

resource base for the state’s economy and a summary 

table from which indices were calculated, (6) emergy 

indices of system structure and function, (7) the 

emergy signature for the state, and (8) the examination 

of several issues of concern for the well-being of 

Minnesota and its people in the future. 

Following the Emergy Analysis of Minnesota, 

there is a Discussion (Section 4) which examines (1) 

some unique problems in the analysis of Minnesota 

and the solutions employed, (2) quality assurance, the 

reliability of the data, and areas of uncertainty in the 

analysis, and (3) the use of emergy accounting data 

for environmental decision-making and planning for 

the future. References are given in Section 5 and the 

data sources used along with their Worldwide Web 

addresses can be found in Section 6. Extensive data 

and documentation to support the method and the case 

study are given in the appendices found in Section 7. 

These appendices are as follows: the Energy Systems 

Language (Appendix A), information on the 

transformities used in this report (Appendix B), notes 

documenting the energy and emergy calculations 

(Appendix C), import-export calculation methods 

(Appendix D), and emergy analysis tables for 

Minnesota in 2000 (Appendix E). Supplemental 

information on this analysis and errata are posted at 

http://www.epa.gov/aed/research/desupp5.html.
Environmental Accounting Using Emergy: Minnesota 

vi 

TABLE OF CONTENTS 

Notice ..........................................................................................................................................................ii 

Abstract .......................................................................................................................................................ii 

Acknowledgments......................................................................................................................................iii 

Preface........................................................................................................................................................iv 

Purpose of the Report.............................................................................................................................iv 

Significance of the Report......................................................................................................................iv 

Structure of the Report ............................................................................................................................ v 

Section 1

Introduction ................................................................................................................................................. 1 

Section 2

Methods....................................................................................................................................................... 3 

2.1 Understanding the System................................................................................................................. 3 

2.2 Overview of Emergy Analysis Methods ........................................................................................... 3 

2.2.1 Diagramming and Models.......................................................................................................... 3 

2.2.1.1 The Energy Systems Language ........................................................................................... 4

2.2.1.2 Simulation Models .............................................................................................................. 5 

2.2.2 Emergy Tables............................................................................................................................ 6 

2.2.3 Data Sources and Model Evaluation .......................................................................................... 6 

2.2.4 Transformities ............................................................................................................................ 7 

2.2.5 Flow Summary and the Calculation of Indices .......................................................................... 8 

2.3 Creating the Emergy Income Statement............................................................................................ 8 

2.3.1. Evaluating Renewable Resources ............................................................................................. 8 

2.3.2. Evaluating Nonrenewable Resources........................................................................................ 9 

2.3.3 Evaluating Exports and Imports ................................................................................................. 9 

2.3.3.1 Determining the Emergy in Materials............................................................................... 10 

2.3.3.2 Determining the Emergy in Services ................................................................................ 11 

2.4 Creating the Emergy Balance Sheet................................................................................................ 12 

2.5 Constructing the Emergy-Economic Overview .............................................................................. 13 

2.5.1 Summary Emergy and Dollar Flows ........................................................................................ 13

2.5.2 Determining the Renewable Emergy Base for a System ......................................................... 13 

2.6 Emergy Indices................................................................................................................................ 14 

2.6.1 The Emergy/Money Ratio........................................................................................................ 15 

2.6.2 The Emergy Exchange Ratio.................................................................................................... 15 

2.6.3 The Investment Ratio ............................................................................................................... 15 

2.6.4 The Environmental Loading Ratio........................................................................................... 15 

2.6.5 Indices of Self-Sufficiency and Dependence ......................................................................... 156 

2.6.6 Indices of Sustainable Use ....................................................................................................... 16 

2.6.7 Indices of Quality of Life ......................................................................................................... 16 

2.7 Energy and Emergy Signatures....................................................................................................... 16 

Section 3

An Emergy Evaluation of Minnesota........................................................................................................ 17 
Table of Contents 

vii 

3.1 Introduction ..................................................................................................................................... 17 

3.2 The Efficacy of Emergy Accounting in Answering Management Questions................................. 18 

3.3 Narrative History of the Land, People and Natural Resources of Minnesota................................. 18 

3.3.1 Timber ...................................................................................................................................... 23 

3.3.2 Flour ......................................................................................................................................... 23 

3.3.3 Surface Water........................................................................................................................... 23 

3.3.4 Iron Ore .................................................................................................................................... 23 

3.3.5 Taconite.................................................................................................................................... 24 

3.3.6 Other Minerals.......................................................................................................................... 24 

3.3.7 Peat ........................................................................................................................................... 24 

3.3.8 Agriculture................................................................................................................................ 24 

3.3.9 Education.................................................................................................................................. 24 

3.4 An Energy Systems Model of Minnesota ....................................................................................... 25 

3.5 The Emergy Income Statement for Minnesota ............................................................................... 32 

3.6 The Emergy Balance Sheet for Minnesota...................................................................................... 34 

3.7 Overview Models and Flow Summary............................................................................................ 38 

3.8 Emergy Indices................................................................................................................................ 40 

3.9 The Emergy Signature for the State ................................................................................................ 41 

3.10 Analysis of Minnesota and Comparison with other States ........................................................... 41 

3.10.1 Characteristics of Minnesota Based on Emergy Analysis...................................................... 43 

3.10.2 Comparison with other States................................................................................................. 46 

3.11 Summary of Findings as Related to the Management Questions.................................................. 50 

3.12 Recommendations to Managers .................................................................................................... 53 

3.13 Minnesota and the Future.............................................................................................................. 53 

Section 4

Discussion ................................................................................................................................................. 54 

4.1 Standard Methods versus Intellectual Creativity ............................................................................ 54 

4.2 Methods Developed and Refined in this Study............................................................................... 55 

4.3 Quality Assurance: Reliability of the Data and Uncertainty........................................................... 55 

4.4 Future Research and Reports........................................................................................................... 58 

Section 5

References ................................................................................................................................................. 59 

Section 6

Data Sources............................................................................................................................................ 644 

Section 7

Appendix A Primary Symbols of the Energy Systems Language ............................................................ 68 

Appendix B Sources, Adjustments, and Calculation of Transformities ................................................... 70 

B1. Information Sources for the Emergy per Unit Values.................................................................... 71 

B2. Estimation of Transformities for the SCTG Commodity Classes .................................................. 72 

B3. Calculation of New or Revised Transformities .............................................................................. 74 

Appendix C Calculation of Energy and Economic Values ..................................................................... 100 

C1 Notes for Table 4 Renewable ........................................................................................................ 101 

C2 Notes for Table 5 Nonrenewable................................................................................................... 111 
Environmental Accounting Using Emergy: Minnesota 

viii 

C4. Notes for Table 7 Exports............................................................................................................. 118 

C5. Notes for Table 8 Storaged Assets ............................................................................................... 120 

C6. Notes for Table 9 Summary Flows.............................................................................................. 123 

C7. Notes for Table 10 Calculation of Emergy Indices ...................................................................... 124 

Appendix D Calculating the Import and Export of Materials................................................................. 126 

D1. Creating Export/Import Spreadsheets for Materials..................................................................... 127 

Appendix E Minnesota Emergy Accounts for 2000 ............................................................................... 134

FIGURES 

Figure 1. A detailed energy systems model of Minnesota ....................................................................... 26 

Figure 2. Aggregated diagram of Minnesota’s economy and emergy resource base............................... 38 

Figure 3. Summary of Minnesota’s environmental and economic emergy flows.................................... 40 

Figure 4. The emergy signature of the State of Minnesota in 1997 ......................................................... 42 

Figure A1 Primary symbols of the Emergy Systems Language .............................................................. 69 

LIST OF TABLES 

Table 1. Tabular format for an Emergy Evaluation ................................................................................... 6 

Table 2. Definition of pathway flows for the systems model of Minnesota’s environment ................... 27 

Table 3. Definitions of the components for the systems model of Minnesota’s environment................. 31 

Table 4. Annual renewable resources and production for Minnesota in 1997......................................... 35 

Table 5. Annual production and use of nonrenewable resources in 1997................................................ 36 

Table 6. Annual imports to the Minnesota economy in 1997 .................................................................. 36 

Table 7. Annual exports from the Minnesota economy in 1997.............................................................. 37 

Table 8. Assets of Minnesota in 1997 ...................................................................................................... 37 

Table 9. Summary of flows for Minnesota in 1997 ................................................................................. 39 

Table 10. Minnesota emergy indicators and indices for 1997 ................................................................. 42 

Table 11. Analysis of Federal outlay and tax relationships ..................................................................... 45 
Table of Contents 

ix 

Table 12. Comparison of emergy flows and indices for Minnesota ........................................................ 47 

Table B1.1 The values and sources for transformities and specific emergies used in this report............ 71 

Table B2.1 Transformities and specific emergies for the SCTG commodity classes.............................. 72 

Table B3.1 Transformity of snow ............................................................................................................ 74 

Table B4.1 The factors needed to convert one planetary baseline to another.......................................... 99 

Table B4.2 Emergy to Money Ratio of the United States for 1997 and 2000 ......................................... 99 

Table C1.1 Data used to determine the geopotential energy of rainfall................................................. 104 

Table C2.1 Detailed account of the emergy imported in material inflows. ........................................... 115 

Table C2.2 Export and import of services between Minnesota and the Nation..................................... 116 

Table C2.3 Determination of imported and exported services .............................................................. 117 

Table C3.1 Emergy in the materials exported from Minnesota ............................................................. 118 

Table C4.1 Services in imported fuels and minerals.............................................................................. 123 

Table C4.2 Services in exported minerals.............................................................................................. 124 

Table D1 Approximate conversion for SCTG, SIC and NAICS industry classification codes. ............ 128 

Table D2 Calculation of Minnesota exports from the state to state commodity shipments................... 129 

Table D3 Our original example of estimating missing import data from Alabama to West Virginia. .. 132 

Table E1 Annual renewable resources and production in 2000............................................................. 135 

Table E2 Annual production and use of nonrenewable resources in 2000 ............................................ 136 

Table E3 Annual imports to the Minnesota economy in 2000............................................................... 136 

Table E4 Annual exports from the Minnesota economy in 2000 .......................................................... 137 

Table E5 Assets of Minnesota in 2000................................................................................................... 137 

Table E6 Summary of flows for Minnesota in 2000.............................................................................. 138 

Table E7 Minnesota emergy indicators and indices for 2000................................................................ 139 
Environmental Accounting Using Emergy: Minnesota 

x 
Introduction 

1 

Section 1 

Introduction 

Accurate accounting of the inflows, outflows and 

storages of energy, materials, and information is 

necessary to understand and manage environmental 

systems at all levels of hierarchical organization. The 

accounting tools, i.e., the emergy income statement, 

emergy balance sheet, and emergy indices described in 

this document can be used to analyze and understand 

systems defined for any arbitrary set of boundaries. 

Boundaries of concern to us define an environmental 

system containing both ecological and socioeconomic 

components. The research or management questions 

asked at each level of organization will be somewhat 

different but the most important questions that are 

concerned with the overall condition of the system will 

be illuminated by information and indices related to the 

system’s inflows, outflows and to the storages of 

energy, matter, and information in the system. In this 

report we present the methods of environmental 

accounting using emergy and apply them to analyze the 

State of Minnesota. Therefore, the particular sources of 

data and methods presented here will relate to the 

calculation of the important flows and storages for states 

within the United States. 

At present, records for the environment are kept in 

terms of physical units such as pounds of chemical 

pollutants discharged, miles of degraded streams, or the 

number of endangered species present in a given area, 

while the accounts of human activities are for the most 

part kept in dollars. Neither accounting mechanism is 

able to address the credits and debits of the other, thus 

there is often a gap in the scientific assessment 

information given to managers faced with solving 

complex environmental problems that have social, 

economic and ecological consequences. To keep 

accurate accounts for the environment, the economy, 

and for society we need a system capable of expressing 

the debits and credits (costs and benefits) that accrue to 

each in common terms. For more than 100 years, 

physical and social scientists have struggled with this 

problem, i.e., how to incorporate resource limitations 

and contributions into the formulations of economics 

(Martinez-Alier, 1987). Land, labor, energy and other 

physical quantities have been tried without much 

success. Often these efforts centered on available 

energy, i.e., energy with the potential to do work, as a 

potentially unifying common denominator for 

accounting purposes, because it is both required for all 

production processes and incorporated in all products of 

production. These early efforts failed largely because 

none of the proposed energy-based accounting methods 

considered differences in the ability to do work among 

energies of different kinds (Odum 1996). 

In the 1980s, H.T. Odum and his colleagues solved 

this problem through the development of the concepts of 

emergy and transformity (Odum 1986, 1988, Scienceman 1987). Emergy is the available energy of one kind 

previously used up directly and indirectly to make a 

product or service. The unit of emergy is the emjoule, 

which connotes the past use of energy that was required 

to create the present product or service. Transformity is 

the emergy required to make a unit of available energy 

of the product or service. Most often, emergy accounts 

for the environment and the economy are kept using the 

solar joule as a base unit. In this case solar 

transformities are expressed as solar emjoules (sej) per 

joule (J). Empower is the flow of emergy (sej) per unit 

time. Emergy is related to the system of economic value 

through the emergy to money ratio. The emdollar (Em$) 

value of a flow or storage is its emergy divided by the 

emergy to money ratio for an economy in that year 

(Odum 1996). Odum’s innovative definition of emergy 

established a medium for environmental accounting that 

for the first time made it possible to express economic 

commodities, services, and environmental work of all 

kinds on a common basis as solar emjoules. In this 

report we use the methods of emergy accounting to 

demonstrate how keeping the books on environmental 

systems can help us identify problems and seek 

solutions at the macroscopic level of a state economy. 

In our previous study of West Virginia (Campbell et al.

2005a); we began to adapt two standard accounting 

tools, the income statement and the balance sheet for use 

with emergy. Respectively, these tools allowed us to 

characterize state annual activities and long-term assets. 

We propose that creating combined emergy and 

monetary accounts for environmental, economic, and 
Environmental Accounting Using Emergy: Minnesota 

2 

social systems is a method that will allow us to bridge 

the gap between economic and ecological analyses of 

natural capital and processes in a plausible and 

integrated manner, thereby leading to more accurate and 

comprehensive evaluations of the effects of 

environmental policies. 
Methods 

3 

Section 2 

Methods 

Emergy evaluations of the macroscopic features of 

an environmental system such as a state, region, or 

nation are carried out in the same manner for each 

system regardless of its size or level in the hierarchy of 

organization, e.g., county, state, nation, 1st, 2nd, ... 6th

order watersheds, etc. Emergy analyses like other 

assessment methods are guided by research or 

management questions. In general, the hierarchical 

organization of ecological and economic systems 

requires that emergy accounts be created for more than 

one level of organization to obtain accurate answers to 

questions about a system at any particular level of 

organization. Multiple levels of organization are 

examined because large-scale patterns within a system 

are often determined by energy inflows from the next 

larger system, whereas, internal system dynamics may 

be affected by policy changes in the management of 

important subsystems. The examination of multiple 

levels of organization is also recommended because 

environmental policies often have different 

consequences at different levels of system organization 

(Odum and Arding 1991). The general rule is that 

analyses at three levels of organization (the system, its 

subsystems, and the next larger system) are the 

minimum required for a thorough understanding of a 

particular system. Because of time and labor constraints 

the emergy analysis presented in this report varies from 

this standard because (1) it does not include an 

examination of important subsystems within the state, 

e.g., the rapidly growing corn ethanol industry, and (2) 

international trade between the United States and 

Canada is not explicitly considered; therefore, it is only 

the first step in a complete emergy analysis of the state. 

2.1 Understanding the System 

Effective models and analyses depend on the degree 

to which the investigators understand the system that 

they have chosen to analyze. For this reason, a thorough 

study of the system to be analyzed and its relationship to 

the next larger system, which determines long-term 

trends, is a prerequisite for successful analysis. Before 

performing emergy analyses of states or other systems, 

we recommend that investigators review existing studies 

containing current and historic information on the state 

with a view toward characterizing it as an environmental 

system. Environmental systems include the economic 

and social infrastructure and activities of humanity as 

well as the storages, flows and processes of ecosystems. 

In the method presented here and illustrated in the 

Results section, the knowledge gained through this 

review is captured in the narrative history of the state. 

The narrative history is a vehicle for understanding how 

renewable and nonrenewable resources have shaped the 

current economy in the state. Setting down the history of 

the state helps trace causal pathways from the past to the 

present and establishes the historical context of 

changing relationships between the state and the nation. 

The knowledge gained through this review serves as a 

basis for creating a detailed energy systems diagram of 

the state as discussed below. 

2.2 Overview of Emergy Analysis Methods 

There are five main steps required to complete an 

emergy evaluation. First, a detailed systems diagram is 

completed. The second step is to translate this 

knowledge into an aggregated diagram of the system 

addressing specific questions. Third, descriptions of the 

pathways in the aggregated diagram are transferred to 

emergy analysis tables where the calculations needed to 

quantitatively evaluate these pathways are compiled. 

The fourth step in the method is to gather the raw data 

needed to complete the emergy analysis tables along 

with the conversion factors (energy contents, 

transformities, etc.) needed to change the raw data into 

emergy units. Finally, after the raw data has been 

converted into emergy units, indices are defined using 

an aggregate diagram (Odum 1996, Lu et al. 2007) and 

calculated using the appropriate data. These five steps 

are discussed in more detail in the following sections. 

2.2.1 Diagramming and Models 

First, a detailed energy system diagram is 

constructed representing all interactions between human 

and natural components of the system that have been 

identified as relevant (Fig. 1). The Energy Systems 

Language symbols and their intrinsic mathematics (see 
 Environmental Accounting Using Emergy: Minnesota 

4 

Appendix A, Fig A1 and Odum 1994) are used to 

develop models of ecological and socio-economic 

interactions and components representative of the 

functions and structures within the system or process of 

interest. In an energy systems diagram, structure 

encompasses the system components and their 

arrangement, and function includes pathways of energy 

flow and interactions. Components can be both physical 

entities and properties such as information or aesthetics 

that are usually considered as intangible, but require 

small energies for their storage and operation. The 

pathways and interactions can be both physical flows 

such as electricity or raw materials as well as control 

mechanisms, e.g., logic programs controlling animal 

migrations or management decisions. 

It is important to include all known connections 

between system components in the draft diagram to 

ensure completeness of the evaluation. A diagram like 

this is a useful tool for defining data needs. Once the 

exercise of defining all known interactions that affect 

the system components is completed, there is usually 

enough information to construct working hypotheses 

about the mathematical expressions that govern these 

processes. This in turn points to the appropriate factors 

that need to be measured when field work is required. 

Variables in the detailed model are then aggregated, 

according to similarity of function, into variables 

considered important in controlling the system behavior 

that is relevant to specific research or management 

questions. Preliminary evaluations of the emergy in 

system storages and flows helps in determining the 

dominant components and processes of the system that 

should be included in the aggregate diagram. 

Aggregating does not mean removing any component 

from the system. It refers to combining components and 

using either averaged data or data from the dominant 

entity to evaluate the component or process. For 

example, data on a biological component can be 

weighted for population percentages. The goal of 

aggregation is to obtain the simplest possible system 

that still allows the original research or management 

question to be answered. 

Committing our understanding of the energy and 

material flows, storages and connections within an 

ecosystem to paper invites review of the completeness 

and accuracy of the conceptual thinking. It is not 

necessary to include all known details in a diagram. In 

the emergy accounting procedure presented in this 

document, the pathways of primary interest are those 

crossing the boundaries, both as inputs and as outputs. 

At this scale, the focus is on the external flows 

supporting the environmental system. The only internal 

interactions of interest are the extractions of natural 

resource storages for economic use, e.g., minerals or soil 

erosion. Other internal pathways are drawn, but much of 

the detail concerning the workings of each component 

can be omitted. 

2.2.1.1 The Energy Systems Language 

The tools and methods for constructing an energy 

systems diagram are discussed extensively in Ecological 

and General Systems (Odum, 1994). The Energy 

Systems Language is a visual mathematics because each 

symbol is mathematically defined. A network of these 

symbols translates directly into a set of simultaneous 1st 

order differential equations. Energy Systems diagrams 

represent both kinetics and energetics in a single 

diagram and they demonstrate and obey the 1st and 2nd

laws of thermodynamics in their structure (Odum 1994). 

The commonly used symbols and conventions of the 

language are briefly described below to assist the reader 

in understanding the energy systems diagrams used in 

this document (Figure A1). 

System boundary A rectangular box represents the 

system boundaries. This is an arbitrary decision and 

boundaries are often chosen to address an issue or 

question being evaluated. Determining the boundary 

requires specifying the spatial and temporal scale of the 

analysis. 

Forcing functions Any input that crosses the 

boundary is an energy source for the system. Such 

inflows include energy flows, materials, information, 

genes of living organisms, services, as well as inputs 

that are destructive, such as wastes and toxicants. 

External inputs are represented with a circular symbol 

and are arranged around the outside border from left to 

right in order of increasing transformity with sunlight on 

the left and information and human services on the right. 

Pathway lines Flows are represented by lines and 

include energy, materials, and information. Money is 

shown with dashed lines and always flows in the 

opposite direction to the material or energy flow with 

which it is coupled. Lines without arrowheads flow in 

proportion to the difference between two forces and 
Methods 

5 

represent a reversible flow that follows the 

concentration gradients. 

Outflows Any outflow that still has available energy, 

e.g., materials more concentrated than the environment 

or usable information, is shown as a pathway exiting 

from any of the three upper system borders, but not from 

the lower border. Degraded or dispersed energy, with 

insufficient ability to do work in the system, is shown 

with gray lines leaving at the bottom of the diagram 

through a single arrow going to the heat sink. 

Adding pathways Pathways add their flows when 

they join and when they enter the same storage. Every 

flow in or out of a storage must be of the same type and 

is measured in the same units. 

State variables Storages of material, energy and 

information are shown as tanks, which may occur alone 

or within system compartments. Changes in the system 

can be recorded as fluctuating accumulations within 

each tank. In system diagrams using group symbols, the 

actual simulation details, such as tanks and complex 

interactions flowing into and out of each tank, are not 

presented. However, a state variable is always implied 

for every compartment within the diagram whether it is 

shown or not. 

Intersection/interaction Two or more flows that are 

different, but required for a process, are drawn entering 

an intersection symbol. The flows to an intersection are 

connected from left to right in order of their 

transformity, the lowest quality one connecting to the 

notched left margin and the higher quality flows 

connecting to the top of the interaction symbol. 

Photosynthesis is an example of a multiplicative 

interaction in which light, plant biomass, and nutrients 

are the inputs required to produce organic matter. 

However, any mathematical relationship can be used to 

define an interaction by making the appropriate symbol 

or notation on the interaction symbol. A flow of one 

entity cannot go from its tank to a tank with a different 

entity without passing through some interaction, e.g., 

sunlight cannot flow into a tank containing 

phytoplankton carbon without first interacting with 

nutrients, phytoplankton biomass and other inputs to 

produce a flow of carbon in gross primary production. If 

hierarchical symbols are being used, e.g., the producer, 

consumer or a rectangular box for a sub-system (Figure 

A1), disparate flows can enter the symbol without 

showing the interactions. However, the interactions are 

implied and are shown explicitly when the hierarchical 

symbol is completely specified (Odum and Odum 

2000). 

Counter-clockwise feedbacks High-quality outputs 

from consumers, such as information, controls, and 

scarce materials, are fed back from right to left in the 

diagram. Feedback from right to left also represents 

recycle or a loss of concentration, because of 

divergence, with the service usually being spread out to 

a larger area. Feedback control or recycle paths go from 

right to left over the top of all other components and 

pathways. 

Sensor If the quantity of a component in some way 

affects a flow without using up the component, a small 

box (sensor) is placed at the top of the storage tank and 

information on the stored quantity is drawn from this 

point for use by another symbol, e.g. an interaction or 

logic program. For example, the emergy stored in the 

biodiversity of a National Park may attract tourists to 

visit the park, but it is not ordinarily diminished as a 

consequence. 

Material balances Since all inflowing materials 

accumulate in system storages or flow out, each 

inflowing material such as water or money needs to 

have a budget determined. 

2.2.1.2 Simulation Models 

The characterizations of Minnesota given in this 

report are based on data from 1997 and 2000 and as 

such they are snapshots of a dynamically changing 

system. The dynamic system processes of the State are 

constantly changing under the influence of both external 

forcing functions, e.g., climate change, fuel availability, 

etc., as well as variations in the internal structure of the 

system, e.g., the growth and development of alternative 

energy industries such as wind power and ethanol. 

Microcomputer simulation is the standard Energy 

Systems Analysis tool used to examine system 

dynamics. Simulation models are not used in this report, 

but they will be important in future studies of the 

sustainability of the State and its regions and in 

predicting the development and behavior of important 

subsystems such as the ethanol industry within the State. 

Simulation models are often helpful in considering 

alternative futures, investigating dynamic properties, 
 Environmental Accounting Using Emergy: Minnesota 

6 

Table 1. Tabular Format for an Emergy Evaluation 

Col. 1 Column 2 Col. 3 Column 4 Column 5 Column 6 

Note Item Data Solar Emergy/Unit Solar Emergy Em$ 

 J, g, $ sej/J, sej/g, sej/$ sej, sej/y U.S. Em$ 

and making predictions. They act as a controlled 

experiment and allow the investigator to adjust one 

variable at a time and note the resulting changes to the 

system. In creating a simulation model, an evaluated 

diagram showing the initial conditions for all state 

variables and pathway flows is made. Storages and 

flows are determined from the literature or from field 

measurements of biomass, production rates, etc. The 

simulation model is translated into a set of simultaneous 

first order differential equations containing the 

mathematical functions governing rates and interactions 

that result in changes in the state variables under a given 

set of forcing functions. These differential equations are 

written as difference equations in a programming 

language and solved on the computer to predict the 

changes in each state variable as a function of time or 

space. More detail on the use of models and simulation 

in energy systems analysis can be found in Odum and 

Odum (2000). 

2.2.2 Emergy Tables 

Emergy analysis tables provide a template for the 

calculation of the emergy values for energy storages and 

flows. In the emergy tables, raw data on the mass of 

flows and storage reserves are converted to energy and 

then to emergy units and emdollars to aid in 

comparisons and to provide information for public 

policy decision-making. Emergy tables are used to 

create the accounts for the emergy income statement and 

emergy balance sheet. 

The common format used to set up emergy tables is 

illustrated above. Each emergy evaluation table has six 

columns as shown in Table 1.The columns are defined 

as follows: Column 1: Note. The line number for the 

item evaluated is listed. Each line number corresponds 

to a footnote where raw data sources are cited and 

calculations shown. The footnotes referenced in this 

paper may be found in the appendices. Column 2: Item. 

The name of the item is listed. Column 3: Data. For each 

line item the raw data is given in joules, grams, dollars 

or some other appropriate unit. The source, derivation 

and characteristics of the data should be shown in the 

footnotes. Column 4: Solar Emergy per Unit. For many 

items the solar emergy per unit (transformity where the 

unit is energy) has already been calculated in previous 

studies. If it has not, the solar emjoules per unit can be 

calculated using one of the methods listed in Odum 

(1996). Transformities and other emergy per unit ratios 

including some new values, e.g., snow, taconite, 

dolomite, are listed in Appendix B. Column 5: Solar 

Emergy. The solar emergy is given here and it is the 

product of columns three and four. It can be an emergy 

flow (sej y-1) or emergy storage (sej). Column 6: 

Emdollars (Em$). This number is obtained by dividing 

the emergy in column 5 by the emergy/dollar ratio for 

the country in the selected year. 

2.2.3 Data Sources and Model Evaluation 

In general, government sources are the first priority 

for environmental and economic data acquisition. For 

the emergy analysis of a state, U.S. government sources 

are preferred. Government sources are most likely to 

provide detailed descriptions of assumptions and 

methods, and they often provide a quantitative estimate 

of error. Recorded data specific to the system both in 

time and space are preferred. However, data are rarely 

collected in a manner that can be directly inserted into 

an emergy evaluation table. For example, international 

trade exchanges are recorded annually by several 

Federal agencies, but domestic trade is evaluated only 

through surveys conducted five years apart. 

Furthermore, a great deal of economic information is 

recorded in terms of currency exchange, but because 

unit prices vary substantially, it is difficult to estimate 

the actual resource or environmental use involved. In 

these cases, broader based assumptions and accepted 

models, many of them models employed by economists, 

are used to convert the recorded data into estimates for a 

particular area or system. 

The information needed for the emergy income 

statement is most often reported as annual flows of mass 

and/or dollars. Usually mass can be easily converted to 

energy because the energy content of many objects has 

been widely tabulated (1). Numbers in italics follow 
Methods 

7 

data sources mentioned in the text and refer to entries in 

the Data Sources section of this report. The energy 

contents of many materials evaluated in this study are 

given in Appendix C. The specific emergy or the emergy 

per unit mass has also been calculated for many items 

and can be used to convert mass flows to emergy when 

it is convenient (see Appendix B). Dollar flows can be 

converted to the average emergy in the human services 

associated with the good or service purchased by 

multiplying the dollar amount by the appropriate emergy 

to dollar ratio (Odum 1996). However, the dollar value 

of something does not give an accurate estimate of its 

emergy except when the work of humans accounts for 

all but a small part of the emergy required to make the 

item. 

2.2.4 Transformities 

The energy content of many items has been 

tabulated; however, the information available on the 

solar transformities of those items is often more limited. 

Thus, the availability of data on solar transformities 

often determines the ease and accuracy with which 

emergy accounting studies can be performed. Many 

solar transformities have been calculated (see Appendix 

C in Odum, 1996 and Appendix B below, Brown and 

Bardi 2001, Odum 2002), but most studies require the 

calculation of new transformities or the updating of old 

transformities, when the average or general value for the 

transformity of an item is not appropriate to answer the 

management or research question. Although several 

methods for calculating transformities exist (Odum 

1996), transformity calculations are commonly based on 

an analysis of the production process for a particular 

item, e.g., see Bastianoni et al. (2005). Global 

production processes are used to determine the 

transformity of planetary products like the wind, rain, 

snow, and waves (Odum 1996, Odum 2000). The 

relevant production processes of environmental and 

economic subsystems are analyzed to determine the 

transformities for particular economic or ecological 

products and services. For example, the inputs to Florida 

agricultural production processes for different crops 

were evaluated to obtain transformities for soybeans, 

grain corn, potatoes, etc. (Brandt-Williams 2001). The 

transformities calculated for agricultural products by 

Brandt-Williams (2001) were updated in this study and 

several crops commonly grown in Minnesota (grain 

corn, spring wheat, and soybeans) were evaluated. 

Transformities for Minnesota crops were used in this 

study where appropriate. 

Transformities are determined through the analysis 

of a production process or by other empirical means. All 

energy inputs required for the production of an item are 

documented and converted to solar joules (the available 

energy inputs are multiplied by the appropriate 

transformity). These emergy inputs to the process are 

summed and divided by the available energy in the 

product to obtain the transformity of that item in sej/J. 

When many production processes are evaluated, a 

distribution of values can be obtained for the 

transformity of any item. The thermodynamic limits on 

the efficiency of all production processes lead to the 

hypothesis that there will be a minimum attainable 

transformity, which results when the production process 

is operating at maximum power. This minimum 

transformity may approach an asymptote for a given 

product or service and this minimum value indicates the 

location of that item in the hierarchy of all natural 

processes. In practice, when a general value for a 

transformity is to be determined, a well-adapted (fast 

and efficient) production process is evaluated on the 

scale and in the setting under which the product is 

commonly formed (Bastianoni et al. 2005). For 

example, rain and wind are products of the global 

atmospheric heat engine and thus their transformities are 

determined through an analysis of their global 

production processes (Odum 2000). In any emergy 

analysis it is important to consider whether the energy 

and material inputs to the system can be considered to 

be of average transformity for that item. If so, the 

general value for the transformity for these items can be 

used. For example, electricity can be generated by many 

processes (using wood, water, coal, gas, tide, or solar 

voltaic cells, etc.) each with a different transformity 

(Odum 1996). An average value of 1.7 E5 sej/J was 

determined by Odum (1996), which is close to the 

transformity of electricity generated from coal-fired 

power plants. The use of a general transformity for an 

item is appropriate when (1) the item is representative of 

the mix of production processes that determine the 

mean, (2) the general value reflects the specific input, 

and (3) the transformity of the particular item is 

unknown or is undeterminable. It would not be 

reasonable to use the general transformity for an item 

when the system or process under evaluation is known 

to be dependent on an inflow of higher or lower 

transformity energy. 
 Environmental Accounting Using Emergy: Minnesota 

8 

The earth receives energy from three primary energy 

sources, i.e., solar radiation, the deep heat from the 

earth, and the gravitational attraction of the sun and 

moon. Odum (1996) and Campbell (2000a) developed 

methods to equate these three independent sources in 

terms of solar emergy resulting in the determination of a 

set of planetary solar emergy baselines that depend on 

how the equivalences between the independent sources 

are determined. All transformities are measured relative 

to a planetary solar emergy baseline and care should be 

taken to ensure that the transformities used in any 

particular analysis are all relative to the same baseline. 

However, all the past baselines can be easily related 

through multiplication by an appropriate factor and the 

results of an emergy analysis do not change by shifting 

the baseline (Odum et al. 2000). The baseline used in 

this study is from Campbell and Odum (1998) and 

Campbell (2000a), who calculated a revised solar 

transformity for tidal energy that resulted in a correction 

to the planetary baseline in Odum (1996) giving a new 

value of 9.26 E+24 solar emjoules per year. The 

transformities used in this report have either been 

calculated using the 9.26 baseline or multiplied by the 

appropriate factor to express them relative to this 

baseline. These factors and information on baselines are 

provided in Appendix B, Table B1.1, where 

transformities are also given relative to the 15.83 E+24 

sej/y baseline calculated in Odum et al. (2000). 

2.2.5 Flow Summary and the Calculation of Indices 

The final step in creation and analysis of emergy 

accounts for a system is to combine the information 

from the income statement into summary variables that 

are used in the calculation of emergy indices. These 

summary variables are shown on the aggregate diagram 

discussed above and provide a macroscopic overview of 

emergy and dollar flows of the system. Other analysis 

methods and tools are used in Emergy Analysis (Odum 

1996, Odum 1994) but they cannot be adequately 

discussed in a short report. Using the emergy analysis 

tables and the aggregated figures, emergy indices are 

calculated to compare systems, predict trends, and to 

suggest alternatives that deliver more emergy, reduce 

stress on the environment, are more efficient or more 

equitable. 

2.3 Creating the Emergy Income Statement 

The income statement includes the following tabular 

accounts: (1) renewable resources received and used 

within the system and the production based primarily on 

the use of those resources, (2) production and 

consumption of nonrenewable resources within the 

system, (3) imports into the system, and (4) exports 

from the system. 

2.3.1. Evaluating Renewable Resources 

Renewable resources are replenished on a regular 

basis as a result of the use of planetary emergy inflows 

in solar radiation, the deep heat of the earth and 

gravitational attraction of the sun and moon. These 

primary planetary emergy inflows and the continuously 

generated co-products of their interactions in the 

geobiosphere comprise the renewable resources of the 

earth. All renewable resources known to be important 

inputs to a system are evaluated and the emergy 

contributed to the system by each is determined. While 

all renewable energies known to be important are 

calculated and included in the table, not all of them are 

included in the emergy base for a system. If all the coproducts of a single interconnected planetary system are 

counted, some of the emergy inflow will be counted 

twice; therefore, a general rule is that only the largest of 

any set of co-products is counted in the emergy base. 

This rule may be modified in certain cases by adjusting 

the base used for transformities of two or more inputs 

(Odum et al. 1987, Lu et al. 2007). 

Rain delivers two kinds of energy to systems, the 

chemical potential energy that rainwater has by virtue of 

its purity relative to seawater and the geopotential 

energy of the rain at the elevation at which it falls, and 

both must be accounted for in an emergy analysis. 

Renewable energy also enters the state or other system 

through cross-border flows of energy and materials in 

rivers. Renewable energy inflows to the system can be 

determined at two points, (1) the point of entry and (2) 

the point of use. The first of these two flow 

measurements gives the emergy received by the system 

and the second gives the emergy absorbed or used in the 

system. For example, the incident solar radiation is 

received by the system and the incident solar radiation 

minus the surface albedo is absorbed. The geopotential 

energy of rain on land at the elevation it falls is the 
Methods 

9 

geopotential energy received by the system, whereas the 

geopotential energy of the runoff relative to the 

elevation at which it leaves the state is used on the 

landscape to create landforms. The chemical potential 

energy of the rain that falls on the land is received, but 

the water transpired is actually used by the vegetation to 

create living structures on the landscape. In some cases 

almost all the emergy received by the system is 

absorbed, e.g., almost all tidal energy received is 

dissipated in estuaries and on the continental shelf. 

Long-term averages are used for the environmental 

inputs to the system. An economy develops over many 

years in response to the environmental energies 

available to support human activities in the system; 

therefore, a long-term average of environmental 

variables, i.e., 10 to 50 years depending on the available 

data, is used to calculate the average energy supplied to 

the system from renewable sources. Long-term averages 

for environmental data smooth temporal variations in 

the inputs of renewable energy, which might otherwise 

lead to variability in the emergy indices based on 

renewable inflows. Environmental data should be 

collected with comparable technologies. Sometimes, 

with long environmental data sets, the technology used 

to obtain the data will have changed during the period of 

record. In this case, we may try to reconcile the two data 

sets, or if this fails, we may use only the data recorded 

using the most recent instruments, since they are 

comparable. Representative averages in space and time 

are also important to characterize inputs accurately. 

Where there are substantial differences in environmental 

inputs in different regions of a state, the differences 

should be prorated by area to ensure that the most 

accurate estimate of the energy input to the state as a 

whole is obtained for any particular variable. For 

example, mountainous areas often have a different 

climate and rate of surface heat flux compared to coastal 

areas. More specific methods for determining the 

emergy of renewable resources are provided in 

Appendix C. 

2.3.2. Evaluating Nonrenewable Resources 

Nonrenewable resources are storages of raw 

materials that have been built-up over a long period of 

time by environmental processes, but that are being used 

by human activities at a rate much faster than they can 

be renewed. Iron ore mined from the Mesabi Range or 

ground water in the Southwestern United States, which 

is being withdrawn in excess of the recharge rate, are 

respectively, examples of flows of a nonrenewable 

resource and of a renewable resource that is being used 

in a nonrenewable manner. An emergy evaluation does 

not determine the contribution of a nonrenewable 

resource by the price paid for the raw material – a ton of 

iron for instance – because this is not the value of the 

iron itself. It is the price someone is willing to pay for 

the labor, machinery, and materials required to mine the 

iron. When evaluating iron as an emergy input to steel 

making, for example, it is important to evaluate or 

estimate the energy required by nature to make the iron 

as well as the human work done in its extraction and 

processing (Appendix B3.4 gives an emergy evaluation 

of taconite). The solar emergy required to make a joule 

of iron is its solar transformity measured in solar 

emjoules per joule. Material flows are multiplied by the 

specific emergy (sej/g) of the item or converted to 

energy and then multiplied by the transformity (sej/J) to 

obtain an emergy flow. All storages in the system that 

are being used faster than they are being replaced 

contribute to the nonrenewable emergy supporting the 

system. This includes storages that can be used 

renewably, e.g., soil, groundwater, timber. 

2.3.3 Evaluating Exports and Imports 

The data sources and methods used to evaluate 

imports and exports will vary depending on the system. 

The following methods are specific for the evaluation of 

imports and exports to and from a state in the United 

States. Emergy is imported and exported in three forms: 

(1) emergy in services separate from any material flows 

(consulting, data analysis, financial services, etc.), (2) 

emergy in materials entering and leaving the state, and 

(3) emergy in the human service associated with the 

material inflows and outflows (collecting, refining, 

manufacturing, distributing, shipping, and handling). 

Most of the data on the shipment of commodities 

between states is collected in terms of both the dollar 

value and tonnage shipped. Both kinds of data are 

needed to make estimates of emergy movements 

because goods have energy and emergy associated with 

their creation and concentration in nature that is separate 

from the contributions of human services that are 

measured in the economic value of the good. Generally 

for steady state conditions, the value, or the money paid 

for a material at the point of use reflects the service 

associated with that commodity. This dollar value can 

be multiplied by the national emergy to dollar ratio for 
 Environmental Accounting Using Emergy: Minnesota 

10 

the year of analysis to give a 1st order estimate of the 

average emergy of the human services accompanying 

the flow of imported goods. The fluxes of energy or 

mass in each material flow can be multiplied by the 

appropriate emergy per unit (excluding services) and the 

results summed to determine the total emergy in the 

import and export of the materials in goods. 

Determining the emergy in goods and services 

imported to and exported from a state is a difficult 

problem because data on the exchange of goods and 

services is collected at different points, by different 

government agencies, using different methods of 

aggregation and estimation. Furthermore, while imports 

and exports are tracked at the national level using 

shipping labels that have explicit information, the 

domestic distribution of goods is determined by the 

statistical analysis of survey data and other economic 

modeling methods. Domestic energy shipments are the 

only commodities tracked on the basis of a nearly 

complete accounting of actual state-to-state movements 

of the commodity. Petroleum is an exception to this 

level of detailed accounting because its movements are 

only tracked among regions. 

The detailed export profile estimates and the overall 

information on state-to-state movements of goods in the 

Commodity Flow Survey (CFS) (2) and it was the 

primary source used to determine both the exports from 

and the imports to a state by product category. In 

addition, other sources were consulted to get a more 

complete accounting of goods crossing the boundary 

and to check the CFS numbers wherever possible. All of 

these data are available on government websites (see 

Data Sources). 

2.3.3.1 Determining the Emergy in Materials 

Theoretically, determining the emergy in material 

inflows should be straightforward; however, the data 

reported are not complete. Although total dollar and 

tonnage values are given for inbound and outbound 

shipments in the CFS for each commodity class, some 

commodity classes are missing an estimate for tonnage, 

dollar value, or both. This situation occurs most 

commonly because shipments are too variable to make 

the average a useful parameter or because a value, if 

given, would reveal information about an individual 

firm. A price per ton can be estimated from the data 

wherever the dollar value and tonnage are provided. 

Often both dollar value and tonnage for commodities are 

available for the total shipments out of a state. If the 

tonnage data was missing for a commodity in the 

shipments to a particular state, the price (dollars per ton) 

from the total shipments was used to calculate the 

unknown tonnage. Where flows are present but both 

tonnages and dollar values are unreported a tonnageweighted export profile of commodities based on their 

respective fraction of total shipments was used to 

estimate the missing tonnage and to bring the total for 

all commodities exported to the total reported in the 

CFS (see Appendix D). 

The Energy Information Administration (EIA) data 

on energy movements of coal and natural gas were 

estimated using all sources larger than a certain 

minimum size; and therefore, these data were 

considered to be more accurate and complete than the 

CFS data, which are estimated from the results of a 

survey of shippers. The EIA data were used to check 

and replace, if needed, entries in the CFS. In addition, a 

category for natural gas data was added. Natural gas 

movements through existing pipelines can be 

determined as well as natural gas exports or imports 

from or to the state. 

All materials that are prepared for shipment from a 

state are reported as exported in the CFS. However, 

some of these materials end up within the state of origin. 

The materials actually exported from a state are 

determined by subtracting the tonnage of shipments that 

begin and end in the state of origin from the total 

tonnage of shipments in each commodity class. 

While the amount of goods imported into a state are 

not directly tracked in the 1997 CFS, the destination 

state for exports is reported, and consequently, the 

goods imported to a state can be determined by adding 

up the tonnage within each commodity class exported 

from the other 49 states to the state under analysis 

(Minnesota). If a state has a customs entry point, the 

U.S. Customs data on imports are tabulated for each 

commodity class. The interstate shipment of goods 

tracked by the CFS includes all the goods shipped from 

a state regardless of origin, therefore international 

imports need not be included separately even for states 

with ports of entry. Most of the goods coming in from 

abroad are passed on directly to other states and 

contribute to the nation as a whole and to the states of 

destination, but they contribute little to the state where 

entry occurs, if they are not used there. A preliminary 
Methods 

11 

analysis of the State of Maryland including the port of 

Baltimore showed that emergy inflows through a major 

international port may be an order of magnitude larger 

than the state-to-state emergy shipments. Thus, 

including these pass-through flows from the next larger 

system alters the emergy indices of the state to such a 

degree that they are no longer comparable to states 

without major ports of entry. 

The 1997 Commodity Flow Survey reported 

commodities using a two-digit Standard Classification 

of Transported Goods (SCTG) code. This code is 

different from the Standard Industrial Classification 

(SIC) and the North American Industry Classification 

System (NAICS), both of which are used in U.S. 

economic data reports. Both import and export data are 

included in the CFS, but conversion is not necessary 

unless the state has a foreign customs entry point 

(Minnesota has customs entries at Duluth and along its 

northern border with Canada). Imports listed by NAICS 

categories were converted to SCTG categories using an 

approximate conversion scheme that we developed for 

several different industry classification codes (see 

Appendix D, Table D1.1). Foreign trade entering the 

State of Minnesota was not considered separate from the 

CFS survey of total shipments, because of the problems 

observed in the Maryland study. 

The emergy in materials exported from or imported 

to a state is then determined by multiplying the mass or 

energy flow in each commodity class by the appropriate 

emergy per mass or transformity, respectively, based on 

an average of these ratios for the major material items 

moving in the class (Appendix B, Table B2.1). Outflows 

or inflows are then summed across all commodities to 

get the total emergy exported or imported. 

Three key data sources for export/import calculations 

are the 1997 Commodity Flow Survey (2), the 

Department of Energy’s Energy Information 

Administration (3) and import data from the US 

Customs Office and the Office of International Trade 

(4). In addition, data for natural gas and coal shipments 

came from Department of Energy (DOE) documents (5, 

6). A step-by-step method for completing tables to 

calculate exports and imports is given in Appendix D. 

2.3.3.2 Determining the Emergy in Services 

Services per se can be tracked along with goods and 

the services required for their production using total 

receipts for the different industry sectors along with 

sector employment. These numbers are recorded for 

both the United States as a whole and for each 

individual state using the same methods, but there is no 

distinction between goods and services that remain 

within the state and services that are transferred to other 

states. A variation of the economic base-nonbase 

method was used to estimate the emergy imported and 

exported in services. The information on the basenonbase method used in this report can be found at the 

web address (7) given in Data Sources. 

Economic base theory is usually employed to 

analyze the growth potential and stability of an economy 

in terms of its export industries (7). In this method, 

economic sectors are designated as basic (exporting 

sectors that are largely dependent on areas external to 

the state or region for marketing their goods and 

services) or non-basic (sectors whose products and 

services are mainly used within the state or local region 

of analysis). Once the industry data have been gathered 

and the assumptions about sector behavior have been 

recorded, an estimation of exported and imported 

services can be made. 

The underlying assumption behind the base-nonbase 

method of estimation is that the aggregate demand of the 

people in a nation will be satisfied by the total 

production of goods and services in all sectors of the 

national economy. Thus the ratio of workers in any 

sector to total employment for the nation indicates the 

level of economic production necessary to satisfy the 

average needs of the people. The number of workers in 

any given economic sector in a state as a fraction of the 

total workers in that state compared to a similar ratio for 

the nation is an indicator of the excess or deficit 

production capacity that may exist within that sector in 

the state’s economy. This ratio is the location quotient 

(LQ) and it can be used to determine whether a given 

industry sector produces exports. If LQ is greater than 

one, at least some of the sector is basic (exporting). If it 

is equal to one, the sector production is assumed to just 

meet local demand and there is no excess to export. If 

the LQ is less than one, the local economic sector cannot 

satisfy the average demand and thus it is assumed that 

no net export will occur. In this study we view sectors 

with location quotients less than one as potential 

importers of goods and services. The formula to 

calculate the LQ for employment, S, in industry sector, 

i, within the economy of a state with total employment, 
 Environmental Accounting Using Emergy: Minnesota 

12 

St, referenced to employment in the same industry sector 

of the national economy, Ni, with total employment, Nt, 

is given below. 

t

i

t

i

N

N

S

S

LQ = (1) 

 The following equation was used to determine the 

number of basic jobs, B, in the export portion of an 

industry: 

i

t

t

i

i N

N

S

N

S B ⎥ ×

⎦

⎤ ⎢

⎣

⎡

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ −⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ = (2) 

The number of basic sector workers, B, times the 

productivity per worker in the state industry gives an 

estimate of the dollar value of exported services. 

Multiplication of this number by the emergy to dollar 

ratio for the nation gives an estimate of the average 

emergy exported from a sector. If both goods and 

services are exported from the sector, the dollar value of 

the goods exported must be subtracted from total sector 

exports to estimate services. Alternatively for sectors 

that export both goods and services, the above method 

can be applied to more detailed data from sub-sectors 

that are almost entirely services and the export 

determined based on these sector divisions. 

An estimate of the potential import of services to a 

region can be obtained in a similar manner. Under the 

assumptions given above, the deficit in employment in 

an industry sector should indicate the amount of service 

that would need to be imported for the residents of a 

region to enjoy the same level of service from these 

sectors experienced by an average person in the nation. 

To estimate imported services from the calculated 

potential, states above the average per capita income in 

the nation are assumed to be able to fill all their need for 

services, whereas states below this level were assumed 

to be able to fill only part of their needs. For example, 

West Virginia is a state shown to be impoverished by 

many social and economic indicators, e.g., in 1997 West 

Virginia ranked 49th among the 50 states in per capita 

income (8). Following the assumption given above, we 

assumed that West Virginians could purchase services in 

proportion to the ratio of West Virginia’s 1997 per 

capita income to the 1997 national average per capita 

income. In contrast, Minnesota ranked 10th in per capita 

income in 2000 and it is assumed to import all services 

needed to fill any deficit. This number is only an 

estimate and the actual value of services entering the 

state is unknown. Assumptions governing the export and 

import of services from different industry sectors might 

be expected to vary somewhat based on the particular 

economic circumstances of individual states. In using 

this method, it is important to ascertain the facts about a 

given state’s economy and to make supportable 

assumptions about service import-export relationships 

based on those facts. Steps in the method to calculate 

services are given in Appendix C. 

2.4 Creating the Emergy Balance Sheet 

The emergy balance sheet is a table containing the 

evaluation of the emergy stored in the natural and 

economic assets of the system. A partial list of assets for 

Minnesota that emphasizes the storages of natural 

capital is presented in this paper. The determination of 

some stored assets on the balance sheet of a state or 

region requires knowledge of the emergy input over the 

average turnover time of the storage. For example, to 

determine the emergy required for a forest of trees that 

are on average 80 years-old, the average annual energy 

used to support an area of forest (chemical potential 

energy of the water evapotranspired) would be 

multiplied by its transformity and then that number 

multiplied by 80 to determine the emergy required to 

develop the standing crop of trees comprising the forest. 

In evaluating an economic production process, start-up 

or capital costs are prorated over the average lifetime of 

the facility carrying out a production process. If the 

energy or mass of storage present in the system is 

known, this quantity can be multiplied by its 

transformity or specific emergy to obtain the emergy of 

the stored asset. For example, the estimated recoverable 

iron reserves in grams could be multiplied by the Gibb’s 

free energy J/g to get energy and then by the 

transformity of iron (sej/J) to find the emergy of the 

stored capital asset. In this study environmental 

liabilities (Campbell 2005) are only partially accounted 

for on the emergy income statement and thus are not 

placed on the balance sheet; however, methods to better 

document them are under development and we plan to 

include these accounts fully in future studies. Also, the 

data to quantify the economic infrastructure of a state in 

physical units is not commonly tabulated, and thus, we 
Methods 

13 

are looking for data sources and methods to easily 

quantify the economic infrastructure and assets of 

society present within state borders. 

2.5 Constructing the Emergy-Economic 

Overview 

Information from the completed emergy income 

statement tables is combined to create a Table of 

Summary Flows, which provides the quantities needed 

for the calculation of the emergy indices. These 

summary flows are also placed on the aggregated 

overview diagram of the system. The item name often is 

sufficient to identify a quantity, but where it is not, 

additional explanation is given in the Table notes along 

with how the quantity was derived. The evaluated 

energy systems diagram of the macroscopic economic 

and ecological features of the system shows important 

classes of flows, the details of emergy and money 

movements across system boundaries, and a limited 

number of flows within the state. The inflows of 

renewable and purchased emergy and the outflows of 

emergy in products and services are summarized in an 

even simpler “3-arm diagram” that shows only the 

inputs and outflows from the system. 

2.5.1 Summary Emergy and Dollar Flows 

The summary table includes information on all the 

important emergy and dollar flows of the system 

designated with a letter for each category of flow. 

Numerical subscripts after a letter or symbol denote a 

particular flow of a given type. The renewable energy 

inflow to the system is designated with the letter “R”. 

The letter “N” indicates nonrenewable energy sources 

and it includes “N0”, which designates ordinarily 

renewable sources that are being used faster than they 

are replaced, e.g., soil, timber, or groundwater. The 

letter “F” designates flows of fuels and minerals 

imported to and/or used within the state. The gross 

economic product of the state (GSP) is designated with 

the letter “X”. The letter “G” designates imported goods 

excluding fuels and minerals. The dollars paid for all 

imports are shown with the letter “I”, and subdivisions 

of this sum are given by subscripts. The dollars brought 

into the state as Federal transfer payments are listed with 

other dollar inflows. The letters “PI” designate the 

emergy flows in human service that have been 

purchased by the dollars paid for imported goods and 

services. Exported products are represented with the 

letter “B”. The dollars paid for exports are shown with 

the letter “E” whereas the emergy of the human service 

required to produce these exports is shown as “PE”. 

Other flows can be added, e.g., immigration, when they 

represent major inflows of emergy in the annual budget. 

Money entering the state does not bring emergy into 

the state unless it is spent on goods, fuels, or minerals 

from outside sources. However, when money from 

outside is spent in the state, this money generates 

internal emergy flows. For example, the emergy flows 

generated when tourist dollars are spent in the state are 

included as emergy exports. Campbell (1998) argued 

that tourists receive value from their recreational 

experience and that these experiences are virtual emergy 

exports, which require that unique emergy storages and 

flows exist within the system to attract tourists and their 

expenditures. Tourist’s expenditures within the state are 

taken as a first order estimator of the value of the 

recreational experience that they take home with them. 

Recreational experiences are classified as exports, 

because they would not be possible without the unique 

opportunities provided by the emergy stores and flows 

that are present in a given area. 

One research question of interest is, “Are Federal 

transfer payments linked to the overall emergy received 

by the nation from a state?” If so, Federal transfer 

payments might be larger if the real value received by 

the Nation exceeds that expected from the monetary 

exchange, i.e., the monetary exchange balances but the 

emergy exchange does not. This relationship has not 

been proven, but Federal outlays add emergy flows to 

the state when these monies are spent within the state, 

i.e., at the state’s emergy to dollar ratio. In this latter 

view Federal outlays are imports and Federal taxes are 

exports because they represent a foregone opportunity to 

generate emergy flows within the state. In this paper we 

examine the question of Federal outlays and taxes more 

closely by analyzing the structure of Federal outlays and 

taxes in Minnesota and by comparing Minnesota to 

West Virginia. 

2.5.2 Determining the Renewable Emergy Base for a 

System 

The objective in determining the renewable emergy 

base for a given area of the earth is to evaluate the 

degree to which the earth’s renewable emergy sources 
 Environmental Accounting Using Emergy: Minnesota 

14 

have been concentrated in a given area. All significant 

inflows are identified and evaluated, but the items 

included in the renewable emergy base for the system 

are determined in a manner that avoids double counting, 

i.e., the base includes only the largest of the emergy 

sources entering the area when they are co-products of 

the same generating process. For example, rain and 

wind are co-products of the work done by the planetary 

heat engine (the latitudinal gradient of temperature over 

the world oceans); therefore, only the largest would be 

counted toward the renewable emergy base for a given 

area. If a system includes land and sea areas, the 

renewable emergy base can be determined for each area 

and the two inputs summed to obtain the renewable 

emergy base for the entire area. 

Planetary processes are considered to be one 

interconnected system for the purpose of determining 

the transformities of global products, thus the entire 

emergy input to the earth is necessary for the formation 

of all global co-products, regardless of the baseline. As a 

result the rules to minimize double counting in 

determining the natural emergy base for a given area of 

the earth will be the same for all baselines. A simple 

rule to avoid double counting when using the 15.83 or 

the 9.26 baseline is to only count the largest inflowing 

emergy of all the co-products of the planetary system 

(including tide) as the emergy base for any given area of 

the earth. Under this rule different areas in the same 

system may count different single emergies as the direct 

base, e.g., tide for a state’s area of coastal ocean and the 

chemical potential energy of rain for the land area of the 

coastal state can be added together to get the renewable 

emergy received by the entire area of the state. The 

same spatial resolution for determining the emergy 

inflows must be used to ensure that bases are 

comparable. Where emergy inflows are concentrated in 

space, higher resolution of the inputs will result in a 

greater emergy base for the system. For example, at a 

resolution of 100 m, the zone of breaking waves would 

be resolved for a coastal system and the wave emergy 

absorbed might be added to the emergy base for the 

system after adjustment of the area of the other inputs, 

and if it is the largest input received over the area of the 

100 m coastal strip. This dependence on spatial 

resolution requires that the emergy analyst consider 

differences in the emergy signature across the landscape 

where they exist, thus areas of different biogeographic 

characteristics are considered separately and the largest 

emergy inflows to each are combined to represent the 

total system (Campbell 2000a). 

With regard to determining the emergy base for a 

system, the main purpose of the emergy accounting is to 

include all the emergy required for a system without 

double counting any input. The rule to only count the 

largest input among co-products is a crude way of 

ensuring that no double counting occurs; however, this 

method gives a conservative estimate of the emergy 

required for the system. In fact, co-products may have 

only partial dependencies and where the relationship 

between these inputs is known other solutions can be 

used (Odum et al. 1987, Lu et al. 2007). How to handle 

partial dependencies among system inputs is being 

investigated in current research on emergy methods. 

(A) Renewable emergy received. For any area, use 

the largest of the energy sources supplied by the 

planetary processes (rain, wind, waves, earth cycle, 

tides, etc.) at the point that they enter the system and 

sum over the entire area to determine the renewable 

emergy received. For rivers that cross into a state or 

flow along its borders, the emergy received at the point 

the river enters the state is included in the emergy base. 

If the river flows along the border between two states, 

1⁄2 of the emergy received is given to each state. 

(B) Renewable emergy absorbed. Both the emergy in 

chemical potential energy (evapotranspiration) and the 

geopotential energy (runoff) of water doing work in the 

system are counted, because these two forms of energy 

carried by water interact across the elevation gradient 

from mountains to the sea to maximize empower on the 

landscape (Romitelli 1997). All tidal energy received is 

assumed to be used within the estuarine and continental 

shelf area and all wave energy is assumed to be used 

when waves break on the shore. The chemical potential 

and the geopotential energy of rivers used in the state is 

found by determining the chemical and geopotential 

energy at the point where the river leaves the state and 

subtracting this from the respective potentials at the 

point of entry. For example, a river enters the state 500 

m above sea level and leaves at an elevation of 250 m, 

the difference in geopotential energy of the annual water 

flows at these two points is the geopotential energy used 

within the state. 

2.6 Emergy Indices 

Emergy indices are often helpful in characterizing 

the condition of a region and in determining the 

relationship between the region and its larger system. 
Methods 

15 

The emergy indices are calculated by performing 

various mathematical operations with the quantities 

given in the Flow Summary Table. The indices used in 

the emergy evaluation of Minnesota are identified and 

explained below. 

2.6.1 The Emergy/Money Ratio 

The ratio of annual emergy flow to money flow is a 

useful index because it connects economic activity to 

the emergy flows that support the economy in a given 

year. An emergy to money ratio is obtained by dividing 

the total emergy used by a state or country in a given 

year by the gross economic product for that year. The 

result gives the average amount of emergy that is 

purchased by spending a dollar in a certain place (sej/$) 

at a given time. In other words the emergy/dollar ratio 

tells us the purchasing power of a dollar in terms of the 

real wealth (emergy) that it can buy. Money is used to 

purchase products such as food, fuels, clothing, housing, 

electricity, information, etc. according to their market 

price. Each of these products also has an emergy value. 

In addition, many products of nature contribute to these 

economic products but are not traded in the market and 

thus have no market value. Dividing the emergy of a 

product or service by the emergy to dollar ratio for its 

system gives the emdollar value of the item. The 

emdollar value of a product or service represents the 

portion of the total purchasing power in the system that 

is due to a particular product or service from the 

economy or from nature. The emergy to dollar ratio has 

another useful property. Since dollars are only paid to 

people for their services, the emergy to dollar ratio for a 

system can be used as an estimate of the average value 

of human services in that system. Thus, multiplying a 

dollar value of a product or service by the emergy to 

dollar ratio gives, on average, the emergy equivalent of 

human service required for an item. 

2.6.2 The Emergy Exchange Ratio 

The emergy exchange ratio (EER) is the ratio of 

emergy received to the emergy given in any economic 

transaction, i.e., a trade or sale. The trading partner that 

receives more emergy will receive greater real wealth, 

and therefore, greater economic stimulation due to the 

trade. Indices of equity in exchange between states and 

nations are determined by comparing the emergy in 

imports and exports. The difference between imports 

and exports indicates whether the state or region is a 

support area for other regions and/or the larger system. 

The ratio of exports to imports indicates the degree to 

which a system contributes emergy to or receives it from 

a trading partner or its larger system. When applied to 

individual products, the EER gives the emergy 

advantage to the buyer by determining the emergy of the 

exported product relative to the emergy that could be 

purchased with the buying power of the money received 

in exchange. 

2.6.3 The Investment Ratio 

The investment ratio is the ratio of the solar emergy 

purchased from outside the system to the solar emergy 

supplied by the renewable and nonrenewable energy 

sources from within the system. It shows the matching 

of economic investment to the indigenous resources of a 

state or region. Lower values of this ratio indicate that 

more of the indigenous environmental resources are 

available per unit of economic activity than the average, 

and therefore, environmental resources may be available 

locally and capable of stimulating investment and 

additional economic use. The ratio of purchased to free 

emergy is a variation of the investment ratio, which 

compares purchased emergy with the free contributions 

of renewable emergy (e.g., rain) and renewable emergy 

used in a nonrenewable manner (e.g., soil erosion). 

Empower density or the emergy flow per unit area is a 

related measure that indicates the spatial concentration 

of economic activity or the intensity of development in 

any unit area of a state or nation. 

2.6.4 The Environmental Loading Ratio 

The environmental loading ratio is the ratio of the 

emergy used from nonrenewable sources (including 

renewable sources being used in a nonrenewable 

manner) and the emergy imported in goods and services 

to the renewable emergy used (Odum 1996, Brown and 

Ulgiati 2001). It indicates the expected intensity of 

impacts that must be carried by the renewable emergy 

base of the system, and therefore, the probability that the 

system will have incurred significant environmental 

liabilities on the balance sheet. 
 Environmental Accounting Using Emergy: Minnesota 

16 

2.6.5 Indices of Self-Sufficiency and Dependence

The emergy used from home sources as a fraction of 

total emergy use is a measure of the relative selfsufficiency of a state or region. Conversely, the fraction 

of total emergy use purchased from outside shows the 

dependence of a state or region on the larger economy 

of which it is a part. The fraction of use that enters as 

imported services indicates the relative dependence of 

the state on the service economy of the nation. 

2.6.6 Indices of Sustainable Use

The fraction of use that is free and the fraction of use 

that is renewable are indicators of what is sustainable in 

the long run. If the difference between these two 

indicators is large, it shows that the long-term capacity 

of the renewable emergy sources to support life is being 

degraded. Truly sustainable use is based on renewable 

resources alone used in a renewable manner. A quick 

estimate of the renewable carrying capacity of a state at 

the current standard of living is obtained by multiplying 

the fraction of use that is renewable by the present 

population of the state. Sometimes the developed 

carrying capacity at the current standard of living is also 

estimated by multiplying the above number by 8, an 

average ratio of purchased to renewable emergy in 

developed countries from past studies (Odum 1996). 

Eventually, this number will be modified based on the 

current set of state studies. 

2.6.7 Indices of Quality of Life

The annual emergy flow per person is hypothesized 

to be an index of the overall standard of living that 

includes environmental and economic contributions to 

the quality of life. This assumes that the people living in 

the system actually benefit from the energy used there. 

Quality of life is also indicated by the emergy in 

electricity use as a fraction of total use. This ratio is a 

measure of the relative importance of the higher 

transformity activities of people, and therefore, it should 

be correlated with the contributions of technology to 

higher standards of living. Other emergy indices of 

quality of life need to be developed that better capture 

the human-information aspect of well-being. 

2.7 Energy and Emergy Signatures 

Energy and emergy signatures of a system show the 

magnitude of environmental and economic processes as 

a synoptic plot that is useful in characterizing and 

classifying systems. The energy signature is a bar graph 

of energy flows with the magnitude and direction of the 

flow (in or out of the system) in joules per year shown 

on the ordinate and the type of energy flow identified on 

the abscissa listed in order of increasing transformity. A 

bar graph of the same flows converted to empower 

(sej/y) is the emergy signature of the system. 

Conversion of energy flows to empower shows the 

relative contributions of the various energy inputs in 

terms of equivalent ability to do work. If functionally 

distinct areas have different emergy signatures 

(Campbell 2000b) and similar areas exhibit similarities 

in their emergy signature, the emergy signature may be 

useful in classifying different environmental systems 

based on differences in their inputs (Odum et al. 1977). 
An Emergy Evaluation of Minnesota 

17 

Section 3 

An Emergy Evaluation of Minnesota 

An emergy analysis of the State of Minnesota is 

given in this section of the report. The application of 

emergy analysis methods in this state study shows 

how each of the techniques given in the methods 

section is performed. The assumptions, calculations 

and data sources used in each part of the analysis are 

documented and given in the Appendices. This section 

is written as a stand alone report that can be used by 

scientists and managers who are interested in the 

results and conclusions of this case study, “Emergy 

Evaluation of Minnesota.” 

3.1 Introduction 

The economic productivity and well-being of 

Minnesotans are dependent on the health and vitality 

of their environment as well as the wealth of their 

stored natural resources. However, the environmental 

contributions to Minnesota’s economy cannot be 

evaluated using market values alone. This is true 

because there is an inverse relationship between the 

contribution that a resource makes to the economy and 

its price (Odum 1996). For example, when timber is 

abundant, prices are lowest but the contribution of 

timber to society is greatest because it is used in great 

quantity and for many purposes. On the other hand, 

after extreme logging of a region, timber becomes 

scarce and the cost increases; timber contributes less 

to the economy, because it is no longer commonly 

used (Odum 1996). Economic studies evaluate wealth 

by what people are willing to pay for a commodity or 

service, but because money is not paid to the 

environment for its work, market values do not 

effectively assess environmental contributions to 

society (Odum, 1996). Emergy includes nature’s 

work contributions to economic products and services. 

Emergy accounts can provide directly comparable 

estimates of the environmental, social and economic 

costs and benefits of alternative actions. Therefore, the 

creation and analysis of such accounts is needed to 

ensure that managers have all the information that 

they need to make decisions in the best interest of 

society. 

At present, Minnesota is faced with the conflicting 

needs of its people and the nation. There is a national 

energy policy initiative for the United States to reduce 

its dependence on foreign sources of energy (National 

Energy Policy Development 2001). At the same time, 

there is a growing recognition of the need to establish 

a sustainable relationship between society, resource 

use, and the environment (National Research Council 

1999). If a constant standard of living is to be 

maintained in the United States as global petroleum 

production declines, fuel autonomy implies an 

expansion of national energy production and 

economic growth for Minnesota and other states with 

a rich abundance of natural resources. However, there 

are thought to be large environmental and social 

impacts associated with the use of Minnesota 

farmland to produce biofuels such as corn-based 

ethanol (Pimentel 2003). Minnesota is currently 

subject to national legislation calling for the increase 

of ethanol production. The need to increase corn 

production to make ethanol will compete for arable 

land with other food crops and prices for both corn 

and the displaced crops will increase. Emergy 

analyses of ethanol production from various feed 

stocks and technologies will help clarify the 

consequences of greatly increasing ethanol production 

in Minnesota and in the Nation as a whole. Minnesota 

is also under internal pressures to increase economic 

prosperity through further developing its human and 

natural capital resources while also confronting the 

daunting task of preventing agricultural and industrial 

development from further damaging the health of 

human beings and the environment. 

Human economic activities such as mining, 

timbering, farming, and changing patterns of urban 

and industrial growth are the primary forces causing 

environmental change in the State. Major 

environmental problems in Minnesota include point 

and non-point pollution from agricultural activities 

and urban development, e.g., effluents from 

agricultural and industrial manufacturing facilities, 

sediment accumulation in streams, nitrogen in runoff 

from farm lands, as well as invasion of exotic species, 
 Environmental Accounting Using Emergy: Minnesota 

18 

forest fragmentation, and habitat loss that accompany 

these and other human activities (9). Because of its 

many lakes and wetlands, the aquatic environment is 

of special concern to Minnesotans, especially the 

deposition of mercury and its accumulation in game 

fish (M. Bourdaghs, pers. com.). In this report, we 

examine the larger system that controls the 

environmental and socioeconomic characteristics of 

local systems within Minnesota. The results of this 

study can serve as the context for the analysis of the 

sustainability of regional and local systems. In 

addition, the emergy analysis methods used in this 

state-wide study can be applied to characterize 

environmental and socioeconomic problems at the 

local and regional scale and to evaluate alternative 

solutions for watershed restoration. 

3.2 The Efficacy of Emergy Accounting in 

Answering Management Questions 

People need accurate and complete financial 

information to answer questions about their fiscal 

condition, so that they can make better decisions. The 

kinds of questions that can be answered by keeping 

accurate financial accounts are many and depend on 

the particular system for which the accounts are being 

kept. For example, people ask and answer practical 

questions about their individual finances every day. 

Some of these questions relate to the amount of assets 

or income, e.g., “How much money do I have in the 

bank?” or “Are my monthly expenditures within my 

budget?” Other questions relate to the equity of 

exchange, e.g., “Is that used car really worth the 

money?” or “How much will the schools improve if 

my property taxes go up?” Still other questions are 

social in nature and relate to how we are doing 

compared to others, e.g., “Do we have a higher or 

lower standard of living than the neighbors?” When 

the questions relate to financial condition, dollars are 

sufficient to provide the answer. However, where 

resources in the public domain are being used, 

degraded, or developed, questions about 

environmental systems cannot be answered by 

considering monetary value alone. Yet the health of 

society depends on accurate answers to questions 

about the condition and use of environmental 

resources as surely as individual financial health 

depends on assessing personal savings and income. 

Standard accounting tools, such as the income 

statement and balance sheet, are used to document the 

financial health of a firm. It is no less important that 

we develop similar tools to assess the condition of 

environmental systems. Emergy accounting provides 

the means to keep the accounts for the economy, 

society, and the environment on a single income 

statement and balance sheet. The questions that we 

can answer after performing an emergy analysis of a 

system are similar to those that we can answer as a 

result of doing a financial analysis of a business or of 

our own individual accounts. The following key 

questions to be answered from information on 

Minnesota’s environmental accounts were derived 

from discussions with environmental managers from 

Region 3 and they are the same questions used in the 

West Virginia study: (1) “What is the current level of 

economic investment in relation to Minnesota’s 

resource base, and is this level of investment 

sustainable?” (2) “What is the net exchange of real 

wealth between Minnesota and the nation?” (3) “What 

are the major causes for any observed imbalances?” 

(4) “What actions can be taken to address an 

imbalance, if it exists?” (5) “How does Minnesota’s 

standard of living compare to other states and the 

Nation?” (6) “Who benefits most from the productive 

use of the state’s resources?” (7) “How self-sufficient 

is the state based on its renewable and nonrenewable 

resources?” (8) “How can we manage the environment 

and economy of Minnesota to maximize the wellbeing of humanity and nature in the State and in the 

Nation?” The emergy accounts for Minnesota 

presented below will provide information and 

indicators that will help answer these questions. 

3.3 Narrative History of the Land, People and 

Natural Resources of Minnesota 

Before considering in detail the condition of the 

State of Minnesota in 1997 and 2000, we briefly 

review the history of the State. Environmental systems 

like Minnesota are composed of the land, the people, 

and natural resources and it is our understanding of 

the development of all aspects of the system that 

allows us to accurately interpret the present and plan 

for the future. The following section presents a brief 

narrative history of the land, people, and natural 

resources of Minnesota, which is manifested today in 

the structure of environmental, economic and social 

systems in the State. 
An Emergy Evaluation of Minnesota 

19 

The real wealth of Minnesota can be found in the 

hard work and ingenuity of its people and in the 

emergy stored in its abundant natural resources. We 

first consider the geological history of the State and 

the development of its landforms and mineral 

deposits. The entire geologic history of Minnesota is 

not entirely clear but it is apparent that Minnesota has 

not always been prairies, rolling hills, and vast forests. 

Many of the physical features of Minnesota as seen 

today took millions of years to form and the land that 

makes up Minnesota has gone through billions of 

years of change. At times it rested on the equator; it 

has been the host to great inland seas, and it has been 

subjected to several periods of glaciation. In the last 

150 years geologists have pieced together a great deal 

of the State’s past (Ojakangas and Matsch 1982). 

Some of the oldest rocks in the world are found in 

Minnesota. Called gneisses, they are approximately 

3.6 billion years old. The oldest gneisses on Earth are 

found in Greenland and Labrador and these were 

formed in the pre-Cambrian era only 200 million 

years before those of Minnesota. Mountains and 

volcanoes are not something that Minnesota is known 

for today, but there were several periods of volcanism 

in Minnesota’s geologic history. All that is known of 

the ancient volcanism is found in gneissic super belts 

that formed around 2.7 billion years ago. Minnesota 

was covered with large mountains due to volcanism at 

two points, 2.7 and 1.8 billion years ago. There was 

another period of volcanism in the State around 1.1 

billion years ago, but this did not have a dramatic 

effect on the landscape. After the volcanism the 

terrain was subject to a great deal of folding. Next, 

large bodies of granitic magma intruded into and 

metamorphosed the volcanic and sedimentary rocks. 

Upon solidification of the granite, faulting began, 

creating rifts in the old sheets of rock. This 

combination of folding, intrusion, and faulting was 

responsible for forming the mountains in northern 

Minnesota. Since then, the land of Minnesota has been 

stable and free of violent geologic events. Erosion 

wore down the land and the mountains in the Lake 

Superior region over millions of years. The State lies 

on the Laurentian Upland and Interior Lowland of 

North America, which are two stable areas of low 

relief that are perhaps responsible for this long period 

of stability and erosion in Minnesota (Ojakangas and 

Matsch 1982). Within the last billion years, the State 

has been repeatedly covered with oceans; proof of this 

lies in the many layers of sandstone, shale and 

limestone within the State and the marine fossils that 

are found in some deposits. 

The large iron deposits found in the State are from 

the pre-Cambrian era and they were formed from 

sediment deposition in an ocean that covered the land 

around two billion years ago. The middle-preCambrian was a time when massive iron deposits 

were laid down in many shallow seas around the 

world, presumably by the action of iron-fixing 

bacteria (Ojakangas and Matsch 1982). The great 

prevalence of iron deposition at this time has been 

attributed to the low oxygen atmosphere that is 

presumed to have existed, before photosynthetic 

organisms came to dominate the earth. 

Around 250-550 million years ago during the 

Paleozoic era, a transcontinental arch ran through 

Minnesota creating an area that could not be 

submerged by most of the subsequent invading 

oceans. Therefore there was very little deposition in 

Minnesota during this time and none at all through the 

center of the State. Also, during the Mississippian and 

Pennsylvanian periods the equator ran through the 

area that is now Minnesota. About 100 million years 

ago, an ocean invaded western North America and its 

eastern shoreline passed through Minnesota. Life 

flourished through the State in the Cretaceous period 

and led to small deposits of coal, but nothing that can 

be mined economically today. 

From 75,000 to 10,000 years ago, glaciers covered 

Minnesota with ice that was several kilometers thick 

in some places. These glaciers were responsible for 

creating much of Minnesota’s current landscape. 

During one stage, the glaciers extended south as far as 

Kansas, which is evidenced by glacial, erratic 

boulders found there that match Minnesota’s bedrock. 

As the glaciers finally receded, several glacial lakes 

formed over Minnesota with the largest being Lake 

Agassiz. This lake formed on the western edge of 

Minnesota and extended into the Dakotas and Canada. 

Before the glaciers melted enough for the lakes to 

drain to the north, the water had to flow south and 

eventually spilled over the moraine which formed the 

southern boundary of Lake Agassiz. This draining 

action wore away a valley creating the Glacial River 

Warren, while at the same time depositing sediment. 

Eventually the glaciers melted enough to allow water 

to drain to the north into Hudson Bay. As this 

happened, the Glacial River Warren ceased to flow 
 Environmental Accounting Using Emergy: Minnesota 

20 

south and the Minnesota River began to flow in the 

glacial river’s broad valley. Because the Minnesota 

River is many times smaller than its predecessor, it 

was able to wear away a deep valley in the loose 

sediment that the Glacial River Warren had deposited. 

The Mississippi River formed in much the same 

manner from smaller glacial lakes draining south. The 

resulting feature is that both rivers have wide flood 

plains and fertile river valleys. In the north, oxygen 

poor water and cool temperatures allowed peat to 

form easily on the poorly drained lands that had been 

covered by Lake Agassiz and other glacial lakes until 

around 5,000 years ago. 

Even though the land had been subject to geologic 

forces for billions of years, one of the greatest forces 

that would alter the landscape had yet to arrive. For 

several thousand years before the present time, people 

inhabited the area that became Minnesota; however, 

they lived a low impact existence relative to today’s 

industrial civilization. Ever since white Americans 

and Europeans began to settle in Minnesota in large 

numbers during the mid-1800s, the land has been in 

constant change. Nearly all of Minnesota’s forests 

have been clear-cut at least once, and less than one 

percent of the original prairie remains (Tester 1995). 

 

The history of the people of the State is complex, 

but it behooves us to consider it, if we are to 

understand the basis for present social structures and 

mores. The following account of the history of the 

people of Minnesota draws heavily on Theodore C. 

Blegen’s “Minnesota, A History of the State” written 

in 1963. 

The northern and southern halves of the State were 

separated by a vast expanse of wilderness, and as a 

result, they have notably different histories. Europeans 

arrived by boat from the south, coming up the 

Mississippi River and from the north, they found their 

way to Minnesota by canoe crossing Lake Superior. 

The Europeans and white Americans who arrived 

using these different access routes had very different 

resource exploitation goals, and these goals 

determined the different course of development in the 

north and south. 

For centuries prior to European settlement, Native 

American tribes lived in Minnesota. In the north, the 

Sioux and Chippewa constantly battled, contesting the 

boundaries of their lands. Then in the mid-1600s, the 

French arrived in the northern region in search of furs. 

The French sided with the Chippewa and aided them 

in their battle against the Sioux. Eventually, with guns 

and new tactics learned from the French, the 

Chippewa drove the Sioux out of the forests of 

northern Minnesota and onto the Great Plains of 

southwestern Minnesota and the Dakotas. The French 

entrenched themselves in the region when they 

annexed the entire Lake Superior region, including 

part of Minnesota. The French presence lasted until 

1763 when northeastern Minnesota was given to the 

British through the Treaty of Paris at the end of the 

French and Indian War. During the American 

Revolution, British soldiers made a brief show of 

force in the region by arriving at Grand Portage in 

1778. This was the only involvement of the region in 

any part of that war. After the war, Britain ceded 

control of all land south of the Boundary Waters Area. 

Despite the cession of this territory to the United 

States, the British maintained control until after the 

War of 1812. 

The displacement of the Sioux in the north 

eventually created conflict with the advancing settlers 

as they began to occupy land in southern Minnesota. 

This desirable area included good farmland that lay 

along the Mississippi and Minnesota Rivers. In 1851, 

thirty-five Sioux Chiefs signed a contract with the 

Territorial Governor, Alexander Ramsey, giving a 

large portion of their land along the Minnesota River 

to the Americans but retaining small portions of land 

for themselves in the upper reaches of the Mississippi. 

The Americans were supposed to pay the Sioux a cash 

settlement, but that was given to investors assuming 

they would make money on their investments and 

with that buy food, medicine, and other necessities for 

the tribes. In 1861 and 1862, conditions on the 

reservations deteriorated because of the failure to 

deliver the promised food and supplies and conflict 

between the tribes broke out. As the situation 

worsened, Chief Little Crow, whom both Sioux and 

Americans respected, approached the agent in charge 

of the reservation to negotiate food and supplies. 

When the Chief was rebuffed by a trader, the tribes 

retaliated by murdering five white settlers and 

declaring war the next day. The Sioux Uprising of 

1862 lasted for five weeks and was eventually put 

down by a force led by Henry Sibley from the Twin 

Cities. As many as 800 settlers and soldiers died in the 

uprising along with an uncounted number of Sioux. 

In the wake of the uprising, 300 Indians were 
An Emergy Evaluation of Minnesota 

21 

sentenced to death. President Lincoln intervened and 

he pardoned all but 38 Sioux who were eventually 

hanged. As a result of this uprising, Minnesota exiled 

all remaining Sioux from the territory and forbade 

their return. 

Exploration of the southern part of the State began 

in 1680 when Father Hennepin, a Franciscan priest 

entered Minnesota from the south. He was the first 

European on record to arrive at and name the Falls of 

St. Anthony, which are at the heart of Minneapolis. In 

1805, Zebulon Pike on orders from the United States 

Government purchased land from the NativeAmerican tribes around the falls of St. Anthony. 

Settlement in the territory by white men began in 1820 

with the completion of Fort St. Anthony, now known 

as Fort Snelling. The settlement around Fort Snelling 

offered an oasis of American civilization in the 

wilderness to travelers and St. Anthony Falls became 

one of the best-known tourist attractions in the 

northern United States. The first mills were built along 

the banks of the Mississippi at the St. Anthony Falls 

from 1821 to 1823. This was the beginning of a long 

history of exploiting the waterfall for its power. This 

event also marked the beginning of grain and lumber 

milling industries that would form the basis of a 

thriving economy in Minnesota for the next hundred 

years. 

Initially, the falls and the land surrounding them 

were in the hands of the military, but by the 1830s the 

potential for private use of the land was realized and 

the military used its right of ownership to expel the 

nearly 200 squatters that had made their home on land 

belonging to the Fort. The displaced squatters left the 

“Falls” area and made their home eight miles down 

stream on Pig’s Eye Island, named after a well known 

whiskey seller of the time. This island eventually 

became the city of St. Paul. In 1837, the government 

negotiated a deal with the Chippewa and Sioux that 

opened up the entire area of land between the 

Mississippi and the St. Croix Rivers to settlement. As 

soon as the treaty had been ratified by Congress, 

Minnesota’s first land rush began. One of the people 

awaiting the news of ratification was Franklin Steele. 

He was determined to gain control of the eastern half 

of St. Anthony Falls so he could claim half of the 

river’s water power for himself. Along with his 

business partners he already owned a large portion of 

the St. Croix Falls. At this point, timber was being cut 

quickly along the St. Croix River; however, logging 

had not made its way to the rich stands of trees along 

the Mississippi. Steel knew that since he owned the 

land and half of the falls, he could make a fortune if 

he built mills. To do that he needed capital, so he 

found several wealthy politicians from Massachusetts 

to fund his venture. This led to the first civilian dam 

on the river and resulted in the construction of mills at 

the Falls of St. Anthony. 

In 1848 President Polk initiated the first land sale 

in the Minnesota Territory. Steele purchased another 

332 acres of land around the falls and strengthened his 

claim. Once people started moving to the area, Steele 

was able to establish the township he had been 

envisioning from the beginning. Because St. Anthony 

Falls was too long of a name to fit on a map, the 

settlement on the east bank of the Mississippi became 

St. Anthony. 

The early 1850s ushered in the era of forest clearcutting in the Mississippi watershed, creating a steady 

flow of timber down the river to the booming milling 

industry at St. Anthony Falls. Eighteen fifty-one also 

brought a glimpse of the future when the first grist and 

flour mill was built in the settlement. The era of 

commercial flour milling began with the erection of a 

commercial grinding mill in 1854. 

At the same time, Minneapolis was becoming a 

city across the falls. For many years, the western side 

of the falls was the property of Fort Snelling and the 

potential of the western half of St. Anthony Falls was 

not realized. This changed when Robert Smith, a 

congressman from Illinois, petitioned the Department 

of War to lease the lumber and grist mills and the 

house that had been built in the 1820s to supply Fort 

Snelling. Despite never actually moving to Minnesota, 

Smith kept up the façade that he was living there and 

the Secretary of War believed him. Steele was also 

attempting to gain a foothold on the western side of 

the river. He managed this by constructing a ferry at 

the falls and having one of his former employees settle 

on the western shore. This became the first residence 

on the land that would become Minneapolis. In 1852 

Congress passed a bill that would open up over 2/3 of 

the 34,000 acres included in Fort Snelling to private 

auction. Several years after the auction, the city of 

Minneapolis was born. The two cities of Minneapolis 

and St. Anthony worked together on many things 

including building the first suspension bridge across 

the river at the falls in 1855 and competing with 
 Environmental Accounting Using Emergy: Minnesota 

22 

St. Paul, which had become a formidable rival as the 

head of navigation for the Mississippi. The rivalry can 

clearly be seen as early as 1850 when a resident of St. 

Anthony, Paul R. George quoted, “man made Saint 

Paul, but God made Saint Anthony.” Because all three 

cities relied on the river for their livelihood to a 

similar degree, their future was to be decided by the 

people who controlled the businesses of the area. 

In the mid-1850s several corporations were formed 

around the falls. The first was the St. Anthony Falls 

Water Power Company, which was formed by Steele 

in St. Anthony. Another corporation was formed on 

the opposite bank by Smith, and was called the 

Minneapolis Mill Company. Working together these 

companies headed up the construction of the second 

dam over the falls. At over 2,200 feet long, this was a 

major project that changed the face of the falls 

forever. After the construction of the dam, mills were 

able to more efficiently harness the power of the water 

and businesses around the falls grew quickly. Over the 

next two decades, as Minnesota became a state, the 

area around the falls changed dramatically. The cities 

grew rapidly as did the number of mills that relied on 

waterpower. Until around 1870 lumber milling was 

Minneapolis and St. Anthony’s main industry, but 

second was flour milling and it was rapidly catching 

up. Between 1860 and 1869 flour production rose 

from 30,000 barrels to 256,100 barrels. It was 

bolstered by the increase in grain being grown in the 

southern and western parts of the State. At the same 

time, residents of the two cities began to realize that 

one city around the falls was ideal and Minneapolis 

and St. Anthony became one in 1872. 

Minneapolis was quickly becoming one of the 

largest producers of flour in the world and in 1880 it 

surpassed St. Louis as the largest flour milling center 

in the country. The two main reasons for this were its 

abundant waterpower and newly constructed railroads 

that opened some of the finest land in the country for 

farmers to produce wheat. The largest of the mills that 

were built in Minneapolis was the Pillsbury A mill; 

this was also the largest mill in the world at the time. 

Though sawmilling fell behind as the leading industry 

in the city around this time, Minneapolis remained 

third in the Nation in total lumber production. To 

bolster flour production, the lawmakers began to pass 

laws giving flour millers an unfair advantage. 

Eventually this forced lumber mills out of the falls 

area and into north Minneapolis where they utilized 

steam instead of water for power. Minneapolis would 

hold on to the top flour production ranking for the 

next fifty years. 

In the late 1800s, the waterpower of the falls began 

to be converted to hydroelectric power generation. 

This metamorphosis would last until 1960 when the 

last water wheel was taken down. Through this time, 

the resource of the falls was managed by an engineer 

named William De La Barre. He was primarily 

responsible for transitioning the use of waterpower 

from era to era as technology improved and needs 

changed. Before 1960, flour milling fell by the 

wayside and total production was a fraction of what it 

had been in its heyday. As milling moved away from 

the falls, the Hennepin Island hydroelectric power 

plant took over the newly opened waterway. Today, 

only the Pillsbury A Mill remains as a working mill. 

In 1963 the Army Corps of Engineers finished a lock 

and dam by-passing the Falls and opening the river 

above the falls to the sea for the first time. Since this 

time, Minneapolis has held its place as the largest city 

in Minnesota and as the cultural and commercial 

center for the upper Midwest. 

In the late 1800s Minnesota began to transform 

through rapid development of agriculture, industry, 

and education. The emphasis on wheat growing 

shifted toward other crops such as barley, oats, and 

corn. Dairy farming increased along with milk, butter, 

and cheese production under the organizing influence 

of cooperative creameries. Livestock production 

increased in the State and St. Paul became an 

important terminal for shipping livestock and later a 

center for meat packing. During this time Minnesota 

society began to create supporting institutions such as 

the cooperative mutual insurance companies for 

farmers and dairy men that formed as early as 1867. 

The cooperatives began to take on other tasks such as 

advertising, and by the 1920s Land O’ Lakes Inc. had 

made the Minnesota Co-operative Dairies Association 

the largest marketer of butter in the world. The 

cooperative idea spread further extending into 

cooperatively run grain elevators and as far as 

consumer cooperatives. From its beginning the 

cooperative movement in Minnesota was allied with 

the interests of the working person (Blegen 1963). 

Cooperatives spread into many businesses including 

cooperative wholesalers, insurance companies, 

telephone, farm supplies, and credit unions. 

 
An Emergy Evaluation of Minnesota 

23 

Education played an important role in the 

transformation of Minnesota agriculture. County 

agents working within agricultural extension programs 

that were mandated by Federal law in 1914 publically 

disseminated new information to farmers that 

promoted modern farming methods and technological 

advances. As Minnesota farms became some of the 

most productive in the Nation, the food processing 

industry located canneries and freezing facilities 

throughout the agricultural regions of the State. In the 

years since 2000 the use of Minnesota corn for 

industrial production of ethanol has gained 

prominence and as of October 2007, Minnesota had 

17 operating ethanol facilities with a production 

capacity of 675 million gallons per year (10). 

3.3.1 Timber 

Initially, timber was the main resource that drew 

people to Minnesota in the 19th century. With the 

Mississippi and St. Croix rivers capable of floating 

large amounts of wood to mills in Minneapolis and 

Stillwater, the forests were soon clear-cut. By the 

1870s the great coniferous forests of the north were 

being cut and Minnesota was supplying more timber 

to America than was any other state (Borchert 1959). 

The vast scale and wealth of Minnesota’s timber 

resources elevated the social importance of the 

lumberjack and generated stories of a mythical hero of 

giant proportions, Paul Bunyan and his blue ox, Babe. 

Nevertheless, by the 1920s, large-scale logging was 

finished in Minnesota and the great forest of the North 

Country was called the “cutover” (Borchert 1959). 

Beginning in 1895, logging began in the boundary 

waters area. At that time, the target resource was 

lumber and mine supports for the booming mining 

industry in that the northeastern part of the State. 

Once all of the big pine had been cut, the industry 

shifted to logging for pulpwood. This lasted until 1978 

when a state law was passed ending logging in the 

Boundary Waters Canoe Area. From 1870 to 1900 

Minnesota timber built cities, towns and farms all 

across the treeless plains to the south and west as the 

prairie lands were settled and developed. 

3.3.2 Flour 

Flour milling was established to use the 

waterpower of St. Anthony’s falls to grind wheat, 

which was the dominant crop, produced from 

Minnesota’s rich farmland from the 1850s through the 

1880s. Beginning in 1880, and for the next fifty years, 

Minneapolis was the largest flour producer in the 

United States and second in the world only to 

Budapest. Great innovations were made in the wheat 

milling industry during this time and Minnesota’s 

patented spring wheat flour was generally 

acknowledged as the best bread-making flour in the 

world. The conglomeration of milling companies in 

Minneapolis centered on St. Anthony Falls until the 

advent of steam and electric power became more 

efficient and less expensive to use than water power. 

3.3.3 Surface Water 

Minnesota has an abundance of surface waters 

including over 15,000 lakes, ponds, and wetlands and 

several large rivers such as the Mississippi, the 

Minnesota and the St. Croix. Minnesota’s rivers have 

been used for transportation and waterpower since the 

1800s and today its lakes are host to many forms of 

recreation in all seasons. Lake Itasca, the headwaters 

of the Mississippi, is located in Minnesota. The 

Boundary Waters Canoe Area (BWCA) lies within the 

State and it has been protected since 1978. The 

BWCA along with its sister park, Quetico Provincial 

Park across the border in Canada and Voyageurs 

National Park contain more land area together than 

Yellowstone National Park, which is the largest U.S. 

National Park. This land contains the largest area of 

unlogged virgin forest in the eastern United States. 

3.3.4 Iron Ore 

Iron was first found in Minnesota as early as 1848; 

however, production did not start until 1884. At first, 

explorers assumed that all the iron in the State was 

low-grade magnetite due to the effect of the rock on 

their compasses. However, high-grade hematite was 

later found in pockets within the magnetite. There are 

three main iron ranges in the State: Vermillion, 

Mesabi, and Cuyuna. The Vermillion range no longer 

produces ore, but the Mesabi and Cuyuna still produce 

two-thirds of the Nation’s iron ore. Up to 1980, 

Minnesota mines had produced over three billion 

metric tons of iron ore. At current rates of production, 

Minnesota has over two hundred years worth of 

economically retrievable reserves with the potential 
 Environmental Accounting Using Emergy: Minnesota 

24 

for more if lower grade taconite rock can be 

economically beneficiated. 

3.3.5 Taconite 

Taconite is one of the hardest minerals known, 

making it very difficult to mine. Mining of taconite 

was not possible until the advent of a drilling 

technique known as jet piercing. Recent advances in 

mining technology through the use of tungstencarbide drill bits, has increased the feasibility of 

mining taconite. The process of beneficiating taconite 

rock was worked out over many years by E.W. Davis, 

a professor at the University of Minnesota, and his 

colleagues. To refine the taconite, large plants had to 

be built at a price of about 250 million dollars each. 

To refine taconite, it must be crushed to a very fine 

powder, then, using powerful magnets the magnetite is 

separated from undesirable byproducts. Next, the 

magnetite is mixed with bentonite clay and fired to 

create pellets of hematite that are around 65% iron. 

Due to the small size of the pellets, it is easy to mix 

them with coke and limestone in a blast furnace to 

produce steel. In the furnace, taconite pellets melt 

quickly increasing the productivity of the furnace by 

roughly doubling the amount of steel that can be 

produced in a given time. This increased efficiency 

keeps taconite mining competitive with lower cost 

sources of ore. 

3.3.6 Other Minerals 

Recently, a large deposit of copper-nickel ore has 

been found in the Duluth Complex in northeastern 

Minnesota. This deposit makes up 25% of U.S. copper 

reserves and 12% of the world’s nickel reserves. In 

addition, due to the geology of Minnesota and high 

radioactivity of wells, reserves of uranium ore are 

thought to exist in the State. Lastly, in 1865 and 1866, 

Minnesota had a small gold rush. Since then, however, 

no deposits have been found. Exploration continues, 

but has yielded nothing but trace amounts of gold and 

silver. 

3.3.7 Peat 

Peat was created in the glacial lakes that covered a 

large portion of the State thousands of years ago. It 

lies under nearly one million acres within the State. 

Peat contains half of the thermal potential of 

anthracite coal and may become an important fuel 

source in the future. 

3.3.8 Agriculture 

Minnesota can be divided into four agricultural 

zones: the dairy region covering the lake and hill 

region in the center of the State, the corn belt on the 

rich prairie lands of the southwestern portion of the 

State, the cash crop region covering the bed of glacial 

Lake Agassiz in the northwestern portion of the State 

and the North country, which is primarily forested but 

contains a few farms (Borchert 1959). The primary 

crops and growing conditions vary across the State. 

Corn, soybeans and livestock are the primary crops of 

the Corn Belt. Crops like wheat, sugar beets, and 

canola that will tolerate colder conditions than corn 

are grown on large tracts of land in the cash crop 

region. Dairy cattle and corn are grown in the Dairy 

Region, which is interspersed with many lakes and 

wetlands and includes many small hills where plowing 

is difficult, but which are ideally suited for pasture. 

The soils in the North Country region are young and 

poor in most places and therefore they are not suitable 

for large scale agriculture. Agriculture occupies over 

40% of the land area of the State and it is one of 

Minnesota’s largest industries. In 2000, it employed 

over 100,000 people and had sales over eight billion 

dollars (11). The largest crops are corn, soybeans, and 

wheat and the largest livestock sales come from 

turkeys, hogs, and cattle. The State is the number one 

producer of turkeys in the country. 

3.3.9 Education 

Minnesotans had an early interest in promoting 

education within the State and as a result the State has 

become known for its many fine institutions of higher 

learning. For example, the University of Minnesota 

was founded in 1851 before Minnesota achieved 

statehood and it was ranked 20th on a list of the top 

research universities the U.S. for 2004 (88). Many of 

the early settlers came to Minnesota from the 

northeastern United States bringing with them their 

knowledge and experience with long-established 

schools and colleges. In addition, the State received 

many immigrants from northern Europe, who brought 
An Emergy Evaluation of Minnesota 

25 

with them a belief in the value of a good education 

and hard work. Minnesota has several private schools 

that are ranked among the top educational institutions 

of the Nation. Minnesota’s emphasis on education is 

reflected in the knowledge and skill level of the labor 

force. This abundance of “know-how” is shown by the 

fact that Minnesotans have been innovators in many 

fields from flour milling and iron mining to 

manufacturing and medicine. 

3.4 An Energy Systems Model of Minnesota 

An energy systems model of Minnesota that shows 

the major economic and environmental forcing 

functions, components, and connections is presented 

in Fig. 1. It offers a conceptual guide to thinking about 

the State and provides the basis for developing 

emergy accounts. The environmental energy sources, 

as well as the fuels, goods, and services that help 

make Minnesota’s economy productive, are shown as 

circles around the edge of the system boundary, i.e., 

the box labeled “Minnesota, 2000”. Purchased imports 

and exports generate monetary flows that cross the 

State borders in exchange for products and services. 

Tourists bring money into the State to spend on 

recreation and the Federal government generates both 

monetary inflow as outlay and outflows as taxes. The 

flows of energy, material, and information into, 

through, and out of the State are identified by the 

various pathways, each labeled with a subscripted k. 

The k’s are listed and defined in Table 2, but in this 

paper they only identify the various pathways. In a 

simulation model, each k has a numerical value that 

determines the rate of flow of energy or materials 

along the pathway. The system components, e.g., 

economic sectors, shown within the diagram are 

defined in Table 3. The external forcing functions for 

the State are listed below and they are used in 

developing the emergy income statement for 

Minnesota. External forcing functions are arranged 

around the edge of the box indicating the system’s 

boundaries from left to right in order of increasing 

transformity. In the left hand corner, solar radiation 

enters the system followed by other natural energies, 

in the form of wind, rain and snow, rivers, and 

geologic processes such as uplift, subsidence and 

volcanism. Next, the energy of fossil fuel and 

minerals enters, followed by material goods and 

services, people, and higher social structures, such as 

government, markets and tourism. 

 The model components in Fig. 1 include aggregated 

systems for coniferous forests, deciduous forests, and 

agriculture, which together represent the natural 

production systems in the State. The lakes and rivers, 

soils, and ground water of the State are subdivided 

into the region in which they are found. In addition, 

special systems are assigned within their appropriate 

regions, such as “Bogs and Fens”, which reside within 

the coniferous forest region (Fig. 1). Timber is 

distributed between the coniferous and deciduous 

forests regions, which would be reflected in the 

harvest of softwood and hard wood logs in the State. 

The agricultural region is further subdivided into cash 

crops and food crops with a storage of soil assigned to 

each area. In addition, livestock production is 

designated as a separate system. Reserves of 

nonrenewable environmental resources are important 

to Minnesota. They include iron, sand, gravel 

limestone, dolomite, peat, and a recently discovered 

large copper and nickel ore body that includes some 

platinum. Renewable resources are abundant and also 

of primary importance to the economy of the State. 

Renewable resources include soil, surface and ground 

water, timber and agricultural production. When a 

renewable resource is used faster than it is replaced by 

natural processes, it makes a nonrenewable emergy 

contribution to the State. The mining of nonrenewable 

resources supports a large industry to process, upgrade 

and ship these raw materials, especially iron to the 

steel mills outside the State. Electric power generation 

is carried out mostly using fuel and mineral resources 

shipped into the State. Agriculture is one of the most 

important sectors of Minnesota’s economy and, as a 

result food processing has become a leading industry 

there. Minnesota food processing companies 

accounted for 20% of all shipments in 2001 and did 

over 30 billion dollars worth of business in 2003 (11). 

In addition to food operations, Minnesota is a leader 

in manufacturing with prominence nationally and/or 

internationally in ethanol and biodiesel, plant 

polymers and fibers, paper and packaging, computer 

and electronic equipment, industrial equipment, 

medical and dental devices, and printing and 

publishing. 
 Environmental Accounting Using Emergy: Minnesota 

26 

Figure 1. A detailed energy systems model of Minnesota is shown (see Appendix A for symbol definitions and 

Tables 2 and 3 for the definition of sources, components and pathways). The large capital letters 

imply connections between sectors without using connecting lines.

Wind

Federal 

Gov.

Markets

People

Coniferous 

Forest

Timber

Production 

Manufacturing

Food Crops

Rivers

Solar

People & 

Households

Power 

Plants

Geologic

Processes

Minnesota, 2000

Tourists

Mining &

Processing

Service & 

Commerce

Transportation

Recreation & 

Tourism

Goods & 

Services

Education 

Systems

Lakes & 

Rivers

Ground 

water

Peaty

Soils

Nuclear 

Waste

Waste

GSP

Soil

Cash Crops

Livestock

Soil

Deciduous 

Forest

W

P

Land

Iron Gravel

Cu-Ni-Pt

Ore

Sand

Limestone 

Dolomite

Lakes & 

Rivers

Soil

Bogs & Fens

Timber

Ground 

water

Ground 

water

ET

Soil Lakes & 

Rivers

Food 

Processing

O

O

Fuels

State & Local 

Government

Know-How

W

W

W

O

S

S

S

k0

k1

k2

k3

k5

k6

R0

R1

k7

k8

k9

k13

k14

k10

k15

k17

k18

k11

k12

k16

k4

Rain &

Snow

k19

k20

k21

k22

k23

k24

k25

k28

k27

k29

k26

k30

k31

k33

k34

k32

k35

k36

k37

k38

k39

k40

k44

k43

k42 

k41

k45 k46

k47

k48 k49

k50 k51

k54

k59

k68

k67

k58

k69

k57

k60

k65

k55

k k61 62

k63

k64

k66

k71

k70

k52

k53

k56

k72

k78

k77

k76

k73

k94

k74 k79

k81

k80

k82

k83

k75

k93

k86

k87 k88 k90 k89

k91

k92

k84

k85

k95 k96

k97

k98

k99

k100

k101

k102 k103

k106

k105

k104

k120

k108

k107

k109

k110

k111

k112

k113

k114

k115

k116

k117

k118

k119

k121

k122

k123

k124 k127

k126

k128

k125

k129

k130

k133

k131 k132

k134

k135

k136 k137 k138

k139

k140

k141 k142

k143

k144 k145 k146 k147

k148

k149

k152

k151

k150

k153

k156

k155

k154

k157

k158

k23'

k36'

k54′

k61′

Wind

Federal 

Gov.

Markets

People

Coniferous 

Forest

Timber

Production 

Manufacturing

Food Crops

Rivers

Solar

People & 

Households

Power 

Plants

Geologic

Processes

Minnesota, 2000

Tourists

Mining &

Processing

Service & 

Commerce

Transportation

Recreation & 

Tourism

Goods & 

Services

Education 

Systems

Lakes & 

Rivers

Ground 

water

Peaty

Soils

Nuclear 

Waste

Waste

GSP

Soil

Cash Crops

Livestock

Soil

Deciduous 

Forest

W

P

Land

Iron Gravel

Cu-Ni-Pt

Ore

Sand

Limestone 

Dolomite

Lakes & 

Rivers

Soil

Bogs & Fens

Timber

Ground 

water

Ground 

water

ET

Soil Lakes & 

Rivers

Food 

Processing

O

O

Fuels

State & Local 

Government

Know-How

W

W

W

O

S

S

S

k0

k1

k2

k3

k5

k6

R0

R1

k7

k8

k9

k13

k14

k10

k15

k17

k18

k11

k12

k16

k4

Rain &

Snow

k19

k20

k21

k22

k23

k24

k25

k28

k27

k29

k26

k30

k31

k33

k34

k32

k35

k36

k37

k38

k39

k40

k44

k43

k42 

k41

k45 k46

k47

k48 k49

k50 k51

k54

k59

k68

k67

k58

k69

k57

k60

k65

k55

k k61 62

k63

k64

k66

k71

k70

k52

k53

k56

k72

k78

k77

k76

k73

k94

k74 k79

k81

k80

k82

k83

k75

k93

k86

k87 k88 k90 k89

k91

k92

k84

k85

k95 k96

k97

k98

k99

k100

k101

k102 k103

k106

k105

k104

k120

k108

k107

k109

k110

k111

k112

k113

k114

k115

k116

k117

k118

k119

k121

k122

k123

k124 k127

k126

k128

k125

k129

k130

k133

k131 k132

k134

k135

k136 k137 k138

k139

k140

k141 k142

k143

k144 k145 k146 k147

k148

k149

k152

k151

k150

k153

k156

k155

k154

k157

k158

k23'

k36'

k54′

k61′
An Emergy Evaluation of Minnesota 

27 

Table 2. Definition of pathway flows for the systems model of Minnesota’s environment and 

 economy shown in Figure 1. 

Pathway Definition of Flow 

R0 Albedo 

R1 Wind passing through the State 

k0 Solar radiation absorbed by the State 

k1 Solar radiation absorbed by food crops 

k2 Solar radiation absorbed by cash crops 

k3 Solar radiation absorbed by deciduous forests 

k4 Solar radiation absorbed by lakes and streams 

k5 Solar radiation absorbed by coniferous forests 

k6 Solar radiation absorbed by bogs and fens 

k7 Wind energy absorbed by food crops 

k8 Wind energy absorbed by cash crops 

k9 Wind energy absorbed by deciduous forests 

k10 Wind energy absorbed by lakes and streams 

k11 Wind energy absorbed by coniferous forests 

k12 Wind energy absorbed by bogs and fens 

k13 Rain and snow absorbed by food crops 

k14 Rain and snow absorbed by cash crops 

k15 Rain and snow absorbed by deciduous forests 

k16 Rain and snow absorbed by lakes and streams 

k17 Rain and snow absorbed by coniferous forests 

k18 Rain and snow absorbed by bogs and fens 

k19 River water flowing into the State 

k20 River water flowing out of the State 

k21 Runoff to lakes and rivers from the coniferous forest 

k22 Infiltration to ground water in the coniferous forest 

k23 Nutrient and water uptake by the coniferous forest 

k23' Evapotranspiration by coniferous forest 

k25 Ground water supplied to bogs and fens 

k26 Evapotranspiration by vegetation in bogs and fens 

k27 Runoff to lakes and rivers from bogs and fens 

k28 Base flow to lakes and streams in the coniferous forest 

k29 Infiltration to ground water from lakes and rivers 

k30 Ground water outflow to regions outside the coniferous forest 

k31 Evaporation from lakes and rivers in the coniferous forest 

k32 Water use by the mining industry 

k33 Net production of peat 

k34 Net production of coniferous forest biomass 

k35 Net production of deciduous forest biomass 

k36 Nutrient and water uptake by deciduous forest 

k36' Evapotranspiration by deciduous forest 

k38 Runoff to lakes and rivers from the deciduous forest 

k39 Infiltration to ground water from lakes and rivers 
 Environmental Accounting Using Emergy: Minnesota 

28 

Table 2 continued 

Pathway Definition of Flow 

k40 Base flow from ground water to lakes and streams 

k41 Evaporation from lakes and rivers in the deciduous forest 

k42 Water use by power plants 

k43 Water use by production manufacturing 

k44 Surface water use in food processing 

k45 Ground water use in food processing 

k46 Ground water outflow to regions outside the deciduous forest 

k47 Soft and hard wood timber harvested for manufacturing 

k48 Cash crops processed 

k49 Livestock processed 

k50 Waste produced by livestock 

k51 Food crops used as livestock feed 

k52 Food crops used in production manufacturing 

k53 Cash crops used in production manufacturing 

k54 Water and nutrients taken up by food crops 

k54 Evapotranspiration by food crops 

k56 Ground water used for irrigation of food crops 

k57 Waste produced by food crops 

k58 Infiltration from food crop soil to ground water 

k59 Ground water resupply of soil water 

k60 Movement of ground water out of the cash and food crop regions 

k61 Water and nutrients taken up by cash crops 

k61 Evapotranspiration by cash crops 

k63 Runoff to lakes and rivers from cash crop soil 

k64 Runoff to lakes and rivers from food crop soil 

k65 Surface water used for irrigation of cash crops 

k66 Ground water used for irrigation of cash crops 

k67 Evaporation from lakes and rivers 

k68 Infiltration from lakes and rivers to ground water 

k69 Base flow of ground water to lakes and rivers 

k70 Waste produced by cash crops 

k71 Waste produced by livestock 

k72 Geologic processes building landform and mineral deposits 

k73 Iron ore mined and processed 

k74 Sand and gravel mined and processed 

k75 Dolomite and limestone mined and processed 

k76 Water used by the mining industry 

k77 Electricity used by the mining industry 

k78 Fuels used by the mining industry 

k79 Goods and services used by the mining industry 

k80 Government control of mining 

k81 Mining industry inputs to production and manufacturing 

k82 Waste produced by mining and processing ores 
An Emergy Evaluation of Minnesota 

29 

Table 2 continued 

Pathway Definition of Flow 

k83 Human knowledge and labor used in the mining sector 

k84 Transport of fuels into the State 

k85 Transport of goods and services into the State 

k86 Government regulation of transportation 

k87 Human knowledge and labor used in the transportation sector 

k88 Electricity used by the transportation sector 

k89 Goods and services input to the transportation sector 

k 90 Fuels input to the transportation sector 

k91 Mining inputs to the transportation sector 

k92 Electricity use by the government sector 

k93 Fuels input to the government sector 

k94 Goods and services input to the government sector 

k95 Human knowledge and labor used in the government sector 

k96 Federal government regulations 

k97 Federal taxes 

k98 Federal outlays 

k99 Money spent on fuels 

k100 Money spent on goods and services 

k101 Electricity use by the food processing sector 

k102 Fuels input to the power plants 

k103 Goods and services input to power plants 

k104 Government regulation of power plants 

k105 Human knowledge and labor used by power plants 

k106 Electricity use by education systems 

k107 Electricity use by production and manufacturing 

k108 Waste produced by power plants (conventional and nuclear) 

k109 Electricity use by service and commerce 

k110 Electricity use by households 

k111 Fuels input to education systems 

k112 Goods and services input to education systems 

k113 Government regulation of education 

k114 Human knowledge and labor used in the schools 

k115 Teaching 

k116 Learning 

k117 Increase in human knowledge and skills 

k118 Loss of information (knowledge and skills) 

k119 Gain of knowledge and skills with immigrants 

k120 Loss of knowledge and skills with emigrants 

k121 Government regulation of people 

k122 Goods and services used by people and households 

k123 Fuels used by people and households 

k124 Water used by people and households 

k125 Waste produced by people and households 

k126 Immigration 
 Environmental Accounting Using Emergy: Minnesota 

30 

Table 2 continued 

Pathway Definition of Flow 

k127 Emigration 

k128 Raw and processed ores exported 

k129 Manufactured products exported 

k130 Raw and processed food exported 

k131 Fuels used by production and manufacturing 

k132 Goods and services used by production and manufacturing 

k133 Government regulation of industry 

k134 Human knowledge and labor used in manufacturing 

k135 Waste produced by industry 

k136 Fuels used by food processing 

k137 Goods and services used by food processing 

k138 Government regulation of food processing industry 

k139 Human knowledge and labor used in food processing 

k140 Food processing inputs to manufacturing 

k141 Waste produced by food processing 

k142 Production and manufacturing inputs to service and commerce 

k143 Food processing inputs to service and commerce 

k144 Fuels used by service and commerce 

k145 Goods and services used by service and commerce 

k146 Government regulation of service and commerce 

k147 Human knowledge and labor used in service and commerce 

k148 Service and commerce used by tourists 

k149 Exports from the service and commerce sector 

k150 Tourists entering the State 

k151 Tourists leaving the State 

k152 Money gained from the sale of products and services 

k153 Money spent by tourists 

k154 Effects of wastes on coniferous 

k155 Effects of wastes on deciduous forests 

k156 Effects of wastes on agricultural lands 

k157 Wastes leaving the State 

k158 Minnesotans using recreation and cultural resources 
An Emergy Evaluation of Minnesota 

31 

Table 3 Definitions of the components for the systems model of Minnesota’s environment 

 and economy shown in Figure 1.

Component Definition 

Coniferous Forest Land covered by coniferous forest. 

Deciduous Forest Land covered by deciduous forests. 

Bogs and Fens Peat forming wetland in the Coniferous Forest region. 

Agriculture Land devoted to food crops, cash crops, or livestock 

Ground Water The quantity of water held in aquifers in the State. 

Divided into ground water in the coniferous, deciduous 

and agricultural regions. 

Lakes and Rivers All surface water in the State including lakes, rivers, and 

Lake Superior divided into surface waters in coniferous, 

deciduous, and agricultural areas. 

Soil The storage of topsoil divided into soil underlying the 

coniferous and deciduous forests and cash crop and food 

crop agricultural lands. 

Peaty Soils Peat stored in the bogs and fens. 

Timber Tree biomass associated with the coniferous and 

deciduous forest lands. 

Cash Crops Sugar beets, wheat, rapeseed, etc. generally grown in the 

Red River Valley Region. 

Food Crops Corn, Soybeans, etc. usually grown in the southwest and 

central regions of the State. 

Livestock Cattle, hogs, turkeys, etc. 

Land Bedrock and surface materials. 

Sand and Gravel The reserves of sand and gravel within the State. 

Limestone/Dolomite The reserves of limestone and dolomite. 

Iron Reserves of iron ore in Minnesota. 

Cu-Ni-Pt Reserves of copper, nickel, and platinum. 

Mining & Processing All mining industries in the State including iron ore, 

taconite processing, copper, nickel, platinum, sand, gravel, 

peat, limestone, and dolomite. 

Production and Manufacturing All manufacturing of durable and non-durable goods 

including chemicals, pharmaceuticals, plastics, fabricated 

and primary metals, and glass, stone and clay products, 

Including the industrial use of farm products such as corn 

processed to ethanol. 

Food Processing Canning, freezing, meat packing and other processing of 

food crops, cash crops, and livestock. 

Transportation, All elements of transportation, including movement by 

truck, train, and river. 

Power Plants All fossil fuel, nuclear, and hydroelectric power plants. 

Government State and local government. 
 Environmental Accounting Using Emergy: Minnesota 

32 

 

Table 3. continued 

Component Definition 

Service and Commerce, S Wholesale and retail trade, hotels, restaurants, 

banking, real estate, insurance and construction 

companies, repair shops; the transportation industry, 

communication and utilities; health, legal, social, 

personal, and repair services; waste treatment, 

hospitals, schools and other government services. 

The “S” leaving Service and Commerce connects to 

all the other sectors. 

People and Households, P The population of Minnesota and their assets 

(households). 

Education Systems Primary schools, secondary schools, colleges and 

universities. 

Know-how The knowledge and skill base of the people. 

Recreation and Tourism All cultural and recreational activities in the State, 

including sports, festivals, canoeing, boating, hiking, 

camping, and historical sites. 

Waste, W All solid, liquid, and gaseous waste created by 

people, industry, and agriculture and stored in the 

State. 

GSP Gross State Product 

 The mix of four nonrenewable energy sources used to 

generate electricity is primarily made up of coal, 

uranium, and natural gas. The use of wind power is 

increasing in the State and some electric power is also 

generated from water, oil, and wood. Waste is a byproduct of all human activity and it most significantly 

affects the aquatic ecosystems of the State as drainage 

from agricultural lands, animal waste, human sewage, 

and industrial effluents. The service and commerce 

sector supports recreation and tourism, which generates 

a significant part of the gross state product, GSP. 

People and households in combination with their 

knowledge and skills (termed Know-how in the model) 

supply the labor that carries out and controls all the 

human activities in the State. The state population has 

been increasing linearly since 1850, but the rate of 

growth has shown signs of slowing during the past few 

years (1990-2006). The transportation sector is critical 

for the movement of goods and services into, out of, and 

within Minnesota. It connects Minnesota to the rest of 

the world through an international port at Duluth and 

through barge traffic down the Mississippi from the 

Twin Cities to New Orleans, LA. Good road and rail 

systems complete the linkages for the transport of goods 

and services within Minnesota and with Canada to the 

north and the contiguous states of Iowa to the south, 

North and South Dakota to the west and Wisconsin to 

the east. 

3.5 The Emergy Income Statement for 

Minnesota 

The emergy income statement summarizes the major 

annual flows of emergy for the State. It consists of four 

accounts, renewable resources (Table 4), nonrenewable 

resources (Table 5), imports (Table 6), and exports 

(Table 7). Each account or table in the emergy income 

statement has six columns as defined in Table 1. The 

numbers in column one (labeled Note) refer to the 
An Emergy Evaluation of Minnesota 

33 

listing of calculations and assumptions in Appendix C 

that document the values given in column three (Data). 

The annual renewable resources and production for 

Minnesota in 1997 are shown in Table 4. There is a 

corresponding table of renewable natural resources and 

products for 2000 in Appendix E, Table E1. The wind 

energy absorbed is the largest renewable emergy source 

received by the State. The chemical potential energy of 

rain received by the State is the second largest emergy 

source entering the State, followed by the geopotential 

energy of rain and snow (the energy of water by virtue 

of its elevation relative to sea level). The largest source 

of renewable production in Minnesota is crop 

production, followed by livestock production, and 

timber harvested. The emergy of renewable crops 

produced in the State in 1997 was 157% of the emergy 

of iron ore mined in that year. The production and use of 

nonrenewable resources in Minnesota was evaluated for 

1997 in Table 5 with a corresponding evaluation for 

2000 in Appendix E, Table E2. Iron ore mined was the 

largest emergy from nonrenewable resources produced 

in the State followed by sand and gravel and then 

dolomite. Petroleum is the second largest nonrenewable 

emergy used in the State and it supplies 57% of the 

emergy of fossil fuels used, followed by coal (23%), and 

natural gas (20%). 

In this study we took a small step toward a broader 

documentation of environmental liabilities by 

quantifying the emergy of some atmospheric pollutants 

deposited upon the ecosystems of the State. Nitrogen 

and the chloride ion were small compared to the 

renewable emergy of the State, 2.7 and 0.6%, 

respectively. However, the emergy of sulfur deposited 

was 43.7% of the renewable emergy base of the State, 

indicating that a substantial environmental liability is 

associated with this flow. We determined the 

transformity for sulfur using several methods and the 

calculations are given in Appendix B. 

Minnesota’s imports and exports for 1997 are shown 

in Tables 6 and 7. There are tables with the 2000 

numbers in Appendix E, Tables E3 and E4. The largest 

emergy imported to Minnesota in 1997 was in the 

materials in goods entering the State. The second largest 

emergy inflow was in the services associated with those 

goods, followed by the emergy in petroleum. Federal 

government outlays may be spent outside the State to 

bring emergy into the State; however, these emergy 

inflows would be counted in our estimates of imported 

goods and services. In addition, Federal outlays will 

generate emergy flows in the State economy when they 

are spent there. Total outlays must be decreased by the 

amount of taxes paid to get the net effect of government 

expenditures on the State. If all Federal outlays are used 

to buy goods and services outside the State, the emergy 

purchased would be slightly more than the emergy 

imported in petroleum. However; if they are spent 

entirely in Minnesota, the emergy flow generated would 

be 1.88 times larger than the emergy imported in 

petroleum. 

The value and pattern of imports by category in 2000 

was similar to that observed in 1997. Differences 

between the two years are seen in a 33% decline in the 

amount of electricity imported accompanied by an 8.6% 

increase in coal emergy imported. Twenty-two percent 

of the decline in electricity imports was made up by a 

35% increase in electricity from renewable sources. 

Natural gas imports increased by 2.3% and petroleum 

decreased by 3.3% in 2000 compared to 1997. Other 

notable changes are that tourist expenditures in the State 

increased by 25% and Federal government outlays by 

13% during this time. 

The dollars that tourists bring into the State are not 

accompanied by emergy per se; however, they generate 

flows of emergy in proportion to the State’s emergy to 

dollar ratio when they are used to purchase products and 

services within the state economy. We hypothesize that 

the natural, historical, and aesthetic assets of the State 

deliver an experience to tourists that can be measured 

roughly by the emergy purchased through the dollars 

spent on tourism. This approximation gives a 

conservative value and the method is similar to the 

travel cost method used in economics. A more complete 

estimate might be obtained from a detailed analysis of 

the emergy required to support the assets that allow 

tourists to receive particular experiences. However, this 

work would require an evaluation of all aspects of 

tourism in the State, which is beyond the scope of this 

study. If all 1997 tourist dollars are spent at the 

Minnesota emergy to money ratio, they comprise 182% 

of the emergy that those dollars could purchase when 

spent at an average location in the United States. 

Taconite pellets account for the largest amount 

(17%) of emergy exported from the State in a single 

product. Manufactured value-added products and the 

services required to produce them account for 82% of 

Minnesota exports. The overall pattern of emergy 
 Environmental Accounting Using Emergy: Minnesota 

34 

exports was similar in 1997 and 2000, primarily because 

we relied on the 1997 Commodity Flow Survey (2) for 

both estimates. However, there was a 25% increase in 

the emergy of the experiences tourists carried home with 

them as measured by the expenditure approximation and 

a 9.6% increase in Federal taxes between the two years. 

3.6 The Emergy Balance Sheet for Minnesota 

The emergy balance sheet, when fully developed, 

will provide the information needed to determine 

whether a human activity, institution, or system is 

sustainable (Campbell 2005). The balance sheets given 

in Table 8 and Appendix E, Table E5 summarize the 

important environmental assets of the State and they 

give a rough estimate of the skill and knowledge base of 

Minnesota’s people. The balance sheet has the same six 

columns described for the income statement. The 

difference between the income tables and the balance 

sheet table is in the units of the items recorded. The 

balance sheet contains stored quantities of mass (g), 

energy (J), or emergy (sej), etc., whereas, the income 

statement contains annual flows of matter (g/y), energy 

(J/y), emergy (sej/y) and dollars ($/y). 

Separate estimates for natural capital were not 

performed for 1997 and 2000 since these assets change 

relatively slowly. The social capital in the stored 

knowledge of people was determined in 1997 based on 

population estimates and using the methods in Odum 

(1996). A similar calculation was made for 2000 using 

census data. Many of the major storages of natural 

capital were estimated, but socioeconomic capital was 

not quantified in this study. Storages of natural, social, 

and economic capital that need to be evaluated to 

complete the balance sheet for this state are as follows: 

(1) the emergy in additional stores of natural capital 

including biodiversity, (2) the assets of society and 

culture, and (3) the economic infrastructure. In addition, 

the debts incurred through the loss of natural lands to 

urban and agricultural uses and the resulting 

diminishment of natural processes over the landscape 

need to be quantified and placed on the balance sheet, 

respectively, as environmental liabilities and as interest 

on the existing environmental debt. Campbell (2005) 

presented a theoretical basis for the definition and 

measurement of environmental liabilities and the use of 

emergy-monetary balance sheets to determine the true 

solvency of human endeavors and institutions. 

Currently, we are focused on developing the methods to 

document environmental liabilities through the 

completion of several example balance sheets. 

The cumulative extent of the State of Minnesota’s 

environmental liabilities is unknown; nevertheless, a 

partial balance sheet that includes its major natural 

capital assets (Table 8) contains useful information that 

documents the stored wealth available to the system. In 

Minnesota, the emergy of natural capital stored in 

accessible iron reserves is the largest actively used 

storage of natural wealth followed closely by sand and 

gravel aggregate. The large reserves of copper and 

nickel ore in Table 8 are in one ore body, which is not 

actively exploited at present. This ore body is not as 

well-known as the iron reserves, but permits to mine 

these resources have been submitted. The iron and 

gravel reserves are almost 7 times larger than soil, 

which is the third largest actively used storage of natural 

capital. The estimate of the amount of sand and gravel in 

the State was based on our extrapolation of Minnesota 

Department of Natural Resources estimates of the 

reserves for the 7 county region around Minneapolis and 

St. Paul and other assessed areas in the State. Complete 

coverage for the entire state was not available; therefore, 

it is more uncertain than the iron reserve estimate. The 

emergy in recently discovered reserves of copper and 

nickel ore may be, respectively, 11.1 and 2.3 times 

greater than the remaining iron reserves, but these 

numbers are highly uncertain. The rough estimates for 

the quantity of ore for both nickel and copper are the 

same, but copper is the richer deposit based on 

assessments available to us. Also, a small reserve of 

platinum, associated with the copper and nickel ore, is 

estimated to be about 0.2% of the mass and 6.7% of the 

emergy of the remaining iron ore. 

The social capital stored in the education of 

Minnesota’s people is the tenth largest storage of capital 

on the balance sheet. The emergy of the knowledge and 

skills of people is slightly less that that stored in peat 

and dolomite. This measure of social capital is about 2% 

of the emergy in iron ore reserves, but it is almost 700% 

of the storage of emergy in forest biomass. The 

population of Minnesota has continued to grow in a 

linear manner since about 1850, continuously adding to 

the knowledge and skills residing within the State. 
An Emergy Evaluation of Minnesota 

35 

Table 4 Annual Renewable Resources and Production for Minnesota in 1997. 

Note* Item 

Data 

J, g, $, 

ind/yr Units 

Emergy/ 

Unit 

sej/unit 

Emergy 

E+20 sej 

1997 

Emdollars 

E+6 Em$ 

Renewable Resources Within Minnesota 

1 Sun, Incident 1.07E+21 J 1 10.7 419.4 

1 Sun, Absorbed 8.84E+20 J 1.21 10.7 419.4 

2 Wind Kinetic Energy 1.26E+19 J 1467 185.5 7244.9 

3 Earth Cycle Energy 2.80E+17 J 33700 94.3 3683.2 

4 Rain, Chemical Potential Energy Received 7.07E+17 J 18100 127.9 4998.0 

5 Evapotranspiration, Chemical Potential 

Absorbed 

3.14E+17 J 28100 88.3 

3449.3 

6 Rain, Geo-Potential On Land 4.58E+17 J 10100 46.2 1805.7 

6 Snow, Geopotential On Land 7.22E+16 J 101100 73 2852.4 

7 Rain, Geo-Potential Of Runoff 2.55E+16 J 27200 6.9 270.7 

7 Snow, Geo-Potential Of Runoff 4.67E+16 J 101100 47.2 1842.8 

8 Wave Energy (Lake Superior) 1.55E+16 J 30000 4.7 181.9 

9 Rivers Chemical Potential Received 9.15E+15 J 50100 4.6 179.1 

9 Rivers Chemical Potential Absorbed 6.44E+12 J 50100 0.0 0.1 

10 Rivers, Geo-Potential Energy Received 5.09E+15 J 27200 1.4 54.1 

10 Rivers, Geo-Potential Energy Absorbed 1.51E+15 J 27200 0.4 16.0 

11 NH4-N In Dry/Wet Deposition 1.55E+11 g 1.4E+09 2.2 84.1 

11 NO3-N In Dry/Wet Deposition 4.44E+10 g 6.8E+09 3.0 118.6 

11 Total N In Dry/Wet Deposition 2.00E+11 g variable 5.2 202.7 

12 S In Dry/Wet Deposition 5.26E+10 g 1.58E+11 83.2 3249.2 

13 Cl In Dry/Wet Deposition 8.81E+09 g 1.31E+10 1.2 45.1 

 

Renewable Production Within Minnesota 

14 Agricultural Products 7.00E+17 J variable 2632.5 102833.7

15 Livestock 3.49E+16 J variable 584.31 22824.5

16 Fish Production 1.32E+11 J 1961800 0.003 0.1

17 Hydroelectricity And Other Renewable 7.95E+15 J 1.20E+05 9.56 548.2

18 Net Timber Growth 1.28E+17 J 20600 26.43 1032.3

19 Timber Harvest 6.47E+16 J 68700 44.47 1737.2

20 Groundwater, Chemical Potential 4.61E+15 J 159100 7.33 286.4

21 Solid Waste, Recycled Or Recovered 4.55E+12 g 6.28E+09 286.10 140263.4
 Environmental Accounting Using Emergy: Minnesota 

36 

Table 5. Annual Production and Use of Nonrenewable Resources in 1997.

Note* Item 

Data 

J, g, $, 

ind/yr Units 

Emergy/ 

Unit 

sej/unit 

Emergy 

E+20 sej 

1997 

Emdollars 

E+6 Em$ 

Fuels and Renewable Resources Used In A Nonrenewable Manner 

22 Coal Used In The State 5.09E+17 J 37800 192.5 16041.7 

23 Natural Gas Used In The 

State 

3.89E+17 J 43500 169.4 

14115.8 

24 Petroleum Used In The State 7.45E+17 J 64800 482.7 40228.6 

25 Electricity Production 1.48E+17 J 170400 251.5 20958.3 

26 Electricity Used In The State 2.00E+17 J 170400 341.3 28437.9 

27 Nuclear Electricity 3.89E+16 J 170400 66.4 5530.8 

28 Iron Ore Mined 4.79E+13 g 3.51E+09 1681.1 140094.6 

29 Sand And Gravel 3.45E+13 g 1.31E+09 452.0 37662.5 

30 Limestone 7.35E+12 g 9.81E+08 72.1 6008.0 

31 Dolomite 3.08E+12 g 1.08E+10 332.1 27671.5 

32 Peat 2.90E+10 g 3.53E+08 0.102 8.5 

33 Soil Erosion 9.79E+16 J 72600 71.1 5921.1 

* The notes for Table 5 can be found in Appendix C, Section C.2. 

Table 6. Annual Imports to the Minnesota Economy in 1997.

Note* Item 

Data 

J, g, $, ind/yr Units 

Emergy/ 

Unit 

sej/unit 

Emergy 

E+20 sej 

1997 

Emdollars 

E+6 Em$ 

34 Tourism (Money Imported) 7.20E+09 $ 2.56E+12 184.3 7200.0 

35 Electricity 4.48E+16 J 1.70E+05 76.3 2979.5 

36 Uranium 2.94E+09 g 4.66E+11 13.7 535.5 

37 Coal 5.09E+17 J 3.78E+04 192.5 7519.5 

38 Petroleum 7.45E+17 J 6.48E+04 482.7 18857.2 

39 Natural Gas 3.89E+17 J 4.35E+04 169.4 6616.8 

40 Minerals 1.06E+13 g Variable 106.0 4142.5 

41 Goods (Materials) 3.92E+13 g Variable 2747.9 107338.1 

42 Goods (Services) 6.63E+10 $ 2.56E+12 1698.0 66326.8 

43 Fuels (Services) 5.51E+09 $ 2.56E+12 141.0 5509.2 

44 Minerals including Uranium 

(Services) 

1.27E+08 $ 

2.56E+12 3.3 127.0 

45 Electricity (Services) 6.22E+08 $ 2.56E+12 15.9 621.7 

46 Services 4.22E+09 $ 2.56E+12 108.1 4221.5 

47 Immigration 8.23E+03 ind. variable 11.3 441.0 

48 Federal Government Outlays 1.98E+10 $ 2.56E+12 506.6 19789.3 

 (If Spent In US) 

* The notes for Table 6 can be found in Appendix C, Section C.3. 
An Emergy Evaluation of Minnesota 

37 

Table 7. Annual Exports from the Minnesota Economy in 1997.

Note* Item 

Data 

J, g, $, ind/yr 

Units 

Emergy/

Unit 

sej/unit

Emergy 

E+20 sej 

1997 

Emdollars 

E+6 Em$ 

49 Material Goods w/o Iron Ore and Fuels 7.37E+13 g Variable 3854.9 150581.3

50 Iron Ore as Taconite 3.57E+13 g 3.61E+0 1290.4 50404.9

51 Services in Goods 9.46E+10 $ 2.56E+1 2421.7 94597.0

52 Services 1.36E+09 $ 2.56E+1 34.7 1356.7

53 Federal Government (Taxes) 2.60E+10 $ 2.56E+1 665.7 26002.8

54 Tourists (Experiences Taken Home) 7.20E+09 $ 4.66E+1 335.4 13100.2

* The notes for Table 7 can be found in Appendix C, Section C.4. 

Table 8 Assets of Minnesota in 1997.

Note* Item 

Data 

J, g, $, ind/yr Units 

Emergy/ 

Unit 

sej/unit 

Emergy 

E+20 sej 

1997 

Emdollars 

E+6 Em$ 

55 Forest Biomass Storage 6.26E+18 J 28200 1765.1 68949.7

56 Water (Lakes) 6.76E+17 J 18100 122.3 4778.9

57 Water (Lake Superior, MN share) 3.30E+17 J 240300 791.8 30928.5

58 Soils 9.42E+19 J 72600 68375.0 2670897.9

59 Iron 1.40E+16 g 3.51E+09 490324.4 19153297.6

60 Sand & Gravel 3.19E+16 g 1.31E+09 417826.0 16321326.7

61 Limestone 2.82E+15 g 9.81E+08 27661.4 1080522.7

62 Dolomite 1.32E+14 g 1.08E+10 14231.1 555900.5

63 Copper 4.50E+15 g 1.14E+11 5115002.3 199804775.6

64 Nickel 4.50E+15 g 2.55E+10 1147664.2 44830631.0

65 Peat 7.57E+19 J 1.86E+04 14100.0 550780.8

66 Platinum 2.90E+13 g 1.13E+11 32728.4 1278454.3

67 People 4.74E+06 Ind. Various 12265.8 479134.7

 Preschool 317301 Ind. 3.34E+16 105.8 4134.1

 School 2312528 Ind. 9.22E+16 2132.3 83294.0

 College Grad 1812350 Ind. 2.75E+17 4977.8 194446.2

 Post-College 246293 Ind. 1.28E+18 3165.1 123638.3

 Public Status 47358 Ind. 3.85E+18 1875.8 71321.0

 Legacy 765 Ind. 7.70E+18 58.9 2301.0

* The notes for Table 8 can be found in Appendix C, Section C.5. 
 Environmental Accounting Using Emergy: Minnesota 

38 

Finally, relatively small amounts of emergy are stored in 

forest biomass and surface waters. 

3.7 Overview Models and Flow Summary 

Figure 2 shows an aggregated model of the 

environment and economy of Minnesota in 1997. It 

provides an overview of the emergy and dollar flows 

across state boundaries and gives the various natural and 

economic sources of the flows. The pathways on the 

diagram show the interaction of renewable and 

 nonrenewable resources within the system and the 

exchanges of emergy and dollars that drive the State’s 

economy. Table 9 identifies the flows of emergy and 

dollars shown on Figure 2. The table that summarizes 

the flows of emergy and dollars for 2000 is found in 

Appendix E, Table E6. The pathway symbols and values 

in Table 9 are used in Table 10 to calculate indices. The 

number indicated in column one directs the reader to a 

description of the calculations used to obtain the 

summary flows, which are found in Appendix C6. 

Fuels Goods

Sun 

Wind 

Rivers 

Rain

Environment

Soil

Minerals 

Iron

Used Nonrenewably

E20 sej/yr 

E9 $/yr

GSP

Markets

Tourists

Services

Federal 

Gov’t

U.S. & World 

Economies

X

RA

N0

N1'

F1

F G

P2I

B

P2E3

Economy

Minnesota 1997

191

156

71

2537

1041 2748

I 76.8

1290

N2

2288

I1

6.3

I2

66.3

I3

4.2

I4

7.2

I5 19.8

1966

P2I3

108

P2I2

1698

P2I1 160

3855

E194.6

P2E2 31.0

34.7

E2

1.2

E3

E4

26

1.4

2422

P2E1

R1

9.6

Figure 2: Aggregated diagram of Minnesota’s economy and emergy resource base used for the calculation of 

indices. Symbols are identified in Table 9. Emergy flows times E+20 sej/y; dollar flows times E+9 $/y. 
An Emergy Evaluation of Minnesota 

39 

Table 9. Summary of Flows for Minnesota in 1997.

Note 

Letter in 

Fig. 2 Item 

Emergy 

E+20 sej 

Dollars 

E+9 $/y 

1997 

Emdollars 

E+9 Em$/y

68 RA Renewable Sources Used 191 7.4

69 R1 Renewable Electricity 9.6 0.4

70 N Nonrenewable Source Flows 2608 104.9

71 N1 Extracted Fuels and Minerals 2537

72 N0 Dispersed Rural Source 71 2.8

73 N1 Conc. Use (Fuels, Minerals, Elec.) 1323 51.7

74 N2 Exported without Full Use 1290 50.4

75 F Imported Fuels (Fuels) 1041 40.7

76 F1 Fuels, Minerals Used (F+F2) 2288 89.4

77 F2 In State Minerals Used (N1'- N2) 1247 48.7

78 G Imported Goods (Materials) 2748 107.3

79 I Dollars Paid for All Imports 76.8 

80 I1 Dollars Paid for Service In Fuels 6.3 

81 I2 Dollars Paid for Service In Goods 66.3 

82 I3 Dollars Paid for Services 4.2 

83 I4 Dollars Spent by Tourists 7.2 

84 I5 Federal Transfer Payments 19.8 

85 P2I Imported Services, Total 1966 76.8

86 P2I1 Imported Services in Fuels 160 6.3

87 P2I2 Imported Services in Goods 1698 66.3

88 P2I3 Imported Services 108 4.2

89 P1I4 Emergy Purchased by Tourists 335 13.1

90 P1I5 Net Emergy Purchased by Fed. $ -289 -11.3

91 B Exported Products w/o Taconite 3855 150.6

92 E Dollars Paid for All Exports 97.1 

93 E1 Dollars Paid for Goods 94.6 

94 E2 Dollars Paid for Mineral Exports 1.2 

95 E3 Dollars Paid for Services 1.4 

96 E4 Federal Taxes Paid 26.0 

97 P2E Total Exported Services 2487 97.1

98 P2E1 Exported Services, Goods 2422 94.6

99 P2E2 Exported Services in Iron 31 1.2

100 P2E3 Exported Services 35 1.4

101 X Gross State Product 155.9 

102 P2 U.S. Emergy/ $ Ratio 1997 sej/$ 2.56E+12 

103 P1 MN Emergy/ $ Ratio 1997 sej/$ 4.66E+12 
 Environmental Accounting Using Emergy: Minnesota 

40 

Figure 3. Summary of Minnesota’s environmental and economic emergy flows. 

The state system was further simplified using a 

“three-armed diagram” (Fig. 3). This diagram gives an 

overview of the renewable and nonrenewable emergy 

entering and leaving the State. Purchased imports and 

exports are shown with a single, simple visual image. 

Several key facts can be easily determined from this 

diagram: (1) in 1997, exported emergy was 1.33 times 

greater than the emergy imported (7632/5755); (2) the 

ratio of purchased to renewable environmental emergy 

was 30:1 (5755/191); (3) seventeen percent (1290/7632) 

of the emergy in exports was derived from the export of 

taconite pellets; (4) when the emergy of taconite pellets 

is removed from Minnesota exports, the emergy 

exported exceeds imported emergy by 10.2%. 

3.8 Emergy Indices 

Table 10 presents several emergy indices that help us 

gain a better understanding of the State of Minnesota in 

1997. Similar indices for 2000 are shown in Appendix 

E, Table E7. The values of some important indices and 

their meaning follow: (1) Twenty-one percent of the 

emergy used in the State in 1997 was derived from 

home sources, which indicates a low potential for selfsufficiency compared to other states (see the comparison 

of states in Campbell et al. 2005a); (2) The emergy use 

per person was 1.53E+17 sej/ind., which shows that 

Minnesotans have a high overall standard of living (see 

Table 12 and Campbell et al. 2005a); (3) The 

import/export emergy ratio shows 1.33 times as much 

emergy leaving the State in exports as is received in 

imports, which indicates an imbalance in the exchange 

of real wealth with the Nation. (4) The emergy used per 

square meter (3.23E+12 sej/m2

) indicates that an 

average location in the State is developed relative to an 

average place in the Nation (Table 12); (5) The emergy 

to dollar ratio was 4.66 E+12 sej/$, thus the purchasing 

power of a dollar in Minnesota in 1997 was 1.82 times 

that of an average place in the United States. This ratio 

had fallen to 1.69 times the national purchasing power 

of a dollar by 2000; (6) The investment ratio was 3.81, 

which indicates a relatively low intensity of matching 

(Odum 1996) between purchased economic emergy 

invested from outside the State and the emergy of 

renewable and nonrenewable environmental resources 

within the State. This index suggests that Minnesota is 

still an attractive place for further economic investment; 

(7) The environmental loading ratio was 37.1:1, 

indicating a more intense matching of purchased inputs 

with renewable energy from the environment than found 

for West Virginia (20.4:1) or the Nation as a whole 

(19.6:1). Higher environmental loading ratios potentially 

result in higher stress on local ecosystems and a heavier 

“load” on the waste processing capacity of the 

environment. 

Fuels and 

Minerals

Goods and 

Services

Imports

Environment

Exports

Goods and Services w/o Iron 

Minnesota

E20 sej/yr 1041

4714

191

Exported Ores and 

Concentrates

6342

1290
An Emergy Evaluation of Minnesota 

41 

3.9 The Emergy Signature for the State 

The emergy signature for Minnesota in 1997 is 

shown in Fig. 4, which charts the significant emergy 

flows within the State as well as the major imports and 

exports. The large quantities of iron ore mined in 

Minnesota, and the taconite pellets exported indicate the 

strength of the connection between Minnesota’s 

economy and the larger regional economies of the East 

coast, the Mid-West, and the world. The large emergy 

flows of materials in both exported and imported goods 

and services also show Minnesota’s role in the larger 

system of the Nation and the strength of the State‘s 

economy in agriculture and manufacturing. The second 

largest pair of flows is also associated with import and 

export. These bars present on the right of the graph 

represent the services required for the production and 

transport of imported and exported goods. A second tier 

of smaller though still important flows includes energy 

and mineral, use, import, and export. Social emergy 

flows of comparable magnitude to petroleum use are 

generated by Federal outlays and expenditures for 

tourism. The emergy of Federal government outlays is 

fairly large, but once taxes are removed there is a net 

outflow of emergy from the State. Petroleum is the 

largest component in the energy consumption signature 

of the State, but overall the energy use pattern is fairly 

well-balanced with substantial inputs from natural gas, 

coal, and nuclear electricity balancing petroleum use. 

The generation of electricity from renewable sources 

was small in 1997, but has grown since then. 

3.10 Analysis of Minnesota and Comparison 

with other States 

The construction of emergy indices from the 

accounting data on storages and flows led to insights on 

the development and use of the State’s natural resources. 

A comparison of these results with emergy analyses of 

other states and of the Nation will help put the 

Minnesota numbers in perspective. In this study, we 

compared Minnesota indices to West Virginia indices 

and selected national indices; all calculated using similar 

methods for documenting imports and exports. Many 

emergy analyses of states have been done in the past 

(Campbell et al. 2005a) and while the analysis method 

has not varied the accuracy with which imports have 

been determined has varied. Therefore, the results of 

many older analyses are only roughly comparable to 

those reported here. Comparisons can be made, but the 

investigator should be aware that the estimates of 

imported goods and services in older studies may be 

somewhat lower than the values that would be expected 

using the revised method first presented in Campbell et 

al. (2005a). The values of indices that include imported 

goods and services in there formulations should be 

compared with this caveat in mind. 
 Environmental Accounting Using Emergy: Minnesota 

42 

0

500

1000

1500

2000

2500

3000

3500

4000

4500

Solar Energy (absorbed)

Wind (absorbed)

Geo-Potential of Rain (run-off)

Evapotranspiration

Wave Energy (Lake Superior)

Earth Cycle Energy

Coal Used

Natural Gas Used

Petroleum Used

Soil Erosion

Geopotential of snow as runoff

Electricity Production

Electricity Used

Electricity imported

Limestone

Sand and Gravel

Iron mined

Iron exported as taconite pellets

Goods imported (materials)

Goods exported (materials)

Dolomite

Electricity imported (services)

Federal Government Outlays

Fuels imported (services)

Goods imported (services)

Services imported

Tourism (buying power in US)

Taxes buying power in the US

Goods exported (services)

Services exported

Category

Emergy Flow Solar Emjoules/Year X E +20

Exported

Imported 

Produced

Renewables

Figure 4. The emergy signature of the State of Minnesota in 1997 is shown. Items are arranged in order of 

increasing emergy per unit. Emergy flows shown to the right of dolomite are determined based on 

the emergy to dollar ratio (sej/$) for the U.S. in 1997. Items from solar energy through electricity 

imported are arranged by transformity (sej/J) and those from limestone through dolomite are 

ordered according to their specific emergy (sej/g). 

Table 10. Minnesota Emergy Indicators and Indices for 1997.

 Item Name of Index Expression Quantity Units 

104 Renewable Use RA 1.91E+22 sej y-1

105 In State Non-Renewable Use N0+N1 1.32E+23 sej y-1

106 Imported Emergy F+G+P2I 5.75E+23 sej y-1

107 Total Emergy Inflows R+F+G+P2I 5.95E+23 sej y-1

108 Total Emergy Used U=(RA+N0+F1+G+P2I) 7.26E+23 sej y-1

109 Total Exported Emergy B+P2E+N2 7.63E+23 sej y-1

110 Emergy From Home Sources (N0+F2+R)/U 0.21 

111 Imports-Exports (F+G+P2I)-B+P2E+N2) -1.88.E+23 sej y-1

112 Ratio Of Export To Imports (B+P1E+N2)/ F+G+P2I) 1.33 

113 Fraction Used, Locally Renewable R/U 0.026 

114 Fraction Of Use Purchased Outside (F+G+P2I)/U 0.792 

115 Fraction Used, Imported Service P2I/U 0.271 

116 Fraction Of Use That Is Free (R+N0)/U 0.036 

117 Ratio Of Purchased To Free (F1+G+P2I)/(R+N0) 26.77 
An Emergy Evaluation of Minnesota 

43 

Table 10 continued. Minnesota Emergy Indicators and Indices for 1997.

 Item Name of Index Expression Quantity Units 

118 Environmental Loading Ratio (F1+N0+G+P2I)/R 37.12 

119 Investment Ratio (F+G+P2I)/(RA+N0+F2) 3.81 

120 Use Per Unit Area U/Area 3.23E+12 sej m-2

121 Use Per Person U/Population 1.53E+17 sej/ind. 

122 Renewable Carrying Capacity (R/U)*Population 124,235 people 

123 Developed Carrying Capacity 8*(R/U)*Population 993,882 people 

124 State Economic Product GSP 1.6E+11 $/yr 

125 MN Emergy Use To GSP U/GSP 4.66E+12 sej/$ 

126 U.S. Emergy Use To GNP U/GNP 2.56E+12 sej/$ 

127 Electricity Used/Emergy Use El/U 0.047 

128 Electricity Produced/Emergy Use Elp/U 0.035 

129 Emergy of Fuel Use per Person Fuels/Population 1.78E+16 sej/ind. 

130 Population 4.74E+06 people 

131 Area 2.25E+11 m2

132 Renewable Empower Density RA/Area 8.46E+10 sej m-2

3.10.1 Characteristics of Minnesota Based on Emergy 

Analysis 

The geopotential energy available in the State of 

Minnesota is governed by the fact that most of the State 

is covered by landforms that were deposited during the 

last glacial period (Tester 1995). The elevation of the 

land varies from the lowest point on the Lake Superior 

shore (183 m) to the highest point on Eagle Mountain 

(701 m). Minnesota is fairly unusual among the states 

that we have examined, because the largest emergy 

inflow to the State is in the wind energy absorbed, rather 

than the chemical potential energy of rainfall. The wind 

accounts for more than 97% of the largest emergy base 

for the State and waves on Lake Superior make up 

2.44% with the remainder supplied by the chemical and 

geopotential energy of the St. Croix River that enters 

from Wisconsin and flows along the border. 

Nonetheless, the renewable emergy supplied by 

water is the basis for many ecological processes in the 

State, i.e., transpiration of forests and crops, and the 

emergy of these flows was also examined. The water 

budget of Minnesota is unique among the states that we 

have examined in that snow is a prominent feature of the 

annual geopotential energy flows. A new transformity 

for the geopotential energy of snow was determined in 

this study (Appendix B), and based on the global 

distribution of rain and snow fall, it was found to be 

about an order of magnitude greater than that of the 

geopotential energy of rain. In light of this fact, it is 

understandable that 32% of the renewable emergy of 

water used in the State is supplied by the geopotential 

energy of runoff generated by snow. Most of the 

remaining emergy of water (59%) is attributed to the 

chemical potential energy of rain transpired by 

vegetation. The geopotential of rain as runoff, waves on 

Lake Superior and the chemical and geopotential of the 

St. Croix River make up the remainder. The high 

transformity of the geopotential energy of snow relative 

to rain means that it should have special organizing 

powers not possessed by rainfall, i.e., snow accumulates 

over many months and this stored geopotential energy is 

released in a pulse over a relatively short period of time 

during snowmelt in the spring. This highly concentrated 

delivery of geological work that is a property of the 

snow pack is consistent with the higher transformity of 

snow calculated on the basis of its global annual 

production. 

Minnesota is richly endowed with mineral resources 

(principally iron, but see Table 8). The emergy density 

of actively exploited underground fuel and mineral 

resources in Minnesota is 4.28E+14 sej m-2. This is 

about half of the emergy density of underground mineral 

reserves in West Virginia. However, if the vast reserves 

of copper and nickel predicted to be available in 

Minnesota are proven, the emergy density of minerals 

beneath Minnesota would be 3.6 times that of the coal 

beneath West Virginia. From this analysis we might 
 Environmental Accounting Using Emergy: Minnesota 

44 

predict that iron mining, beneficiation, and transport will 

dominate the emergy flows, and ostensibly the 

economic activities and environmental impacts in the 

northeastern region of the State; however a complete 

regional analysis needs to be performed to confirm this 

prediction. The emergy of iron produced in Minnesota 

in 1997 was equal to 23% of the total emergy used in 

the State. Most (75% or more) of the iron mined in 

Minnesota is exported (2). 

Emergy measures the power to create useful products 

and services in a system. The taconite produced in 

Minnesota provides a tremendous subsidy (1.29E+23 

sej/y) of organizing power to the larger economies of the 

United States and the world. However, the actual 

subsidy would be 3 times greater, if geological 

processes did all the work of concentration. The 

transformity of taconite pellets was calculated as part of 

this study (Appendix B3.4). This transformity is based 

on the work of nature in creating iron ore (taconite rock, 

20% Fe) and the energy and human service required to 

beneficiate low grade ores. E.W. Davis’s technology to 

concentrate low grade ores results in a 22:1 emergy 

yield for every sej used in beneficiation (Appendix 

B3.4). However, when compared to the work that nature 

does in creating an ore of 63% iron, the magnification 

factor is 47:1. The taconite exported to steel mills in the 

east would require three times more emergy, if it was a 

natural iron ore with the same iron concentration. This 

calculation demonstrates how technology can increase 

the production efficiency of materials used by society, 

i.e., taconite is like an ore containing 63% iron, which 

would take three times as much emergy to produce 

through the work of natural geological processes. Given 

the high net emergy yield of Minnesota’s original rich 

iron deposits, it is not surprising that the mining of this 

ore during the 1890s led to the rapid expansion of the 

iron and steel industry in the United States and 

subsequent dominance of the U.S. in manufactured 

exports (Irwin 2003). 

The emergy to money ratio for Minnesota in 1997 

was 4.66E+12 sej/$ compared to 2.56E+12 sej/$ in the 

United States as a whole. This index means that in 1997, 

the power of a dollar to purchase emergy was 1.82 times 

greater at an average place in Minnesota than in an 

average place in the Nation. The consequences of this 

relationship can be better understood by considering an 

example such as Federal outlays and taxes. The United 

States contributed $19.8 billion dollars in Federal 

outlays to individuals and to state and local governments 

in Minnesota in 1997. Multiplying this value by the 

emergy to dollar ratio for Minnesota in 1997 shows that 

the combined expenditures of the Federal government 

could have generated an emergy flow of 9.22E+22 sej/y, 

if all the tax money had been spent in the State. This is 

71% of the emergy in taconite pellets exported. 

However, if the money was spent at an average location 

in the United States it would only generate a flow of 

5.07E+22 sej (45% less). Federal taxes amounting to 

$26 billion were collected from Minnesotans in 1997. 

Similarly, if this tax money had been spent in Minnesota 

it would have generated an emergy flow that was 1.82 

times the flow when spent at an average location in the 

U.S. The difference between taxes and outlays in this 

year was 6.21 billion dollars or 23.9% of taxes and the 

emergy deficit assuming all money was spent in the 

Nation was also 23.9%. Table 11 analyzes several 

Federal outlay and tax scenarios for Minnesota 

depending on where tax dollars and Federal outlays are 

spent. As indicated by the relative values of the emergy 

to money ratio in Minnesota and the United States, more 

emergy flows when Federal dollars are spent in 

Minnesota. This fact is balanced by the need for tax 

dollars to support national structure and function that all 

the states rely upon for their well-being and the wellbeing of the Nation. 

Emergy parity like monetary parity can be used as a 

benchmark to show relative advantage and disadvantage 

in a relationship. Scenarios B and C in Table 11, 

respectively, show the emergy balance when all Federal 

outlays are spent either in an average place in the United 

States or in Minnesota. At the same time tax dollars are 

removed to support the Nation; and therefore, they 

probably are not spent in Minnesota. The results for 

Scenario B, in which outlays are spent out-of-state, 

show that parity in emergy flows can be obtained by 

either increasing outlays or decreasing taxes with a 

much larger change in the dollar flow required, if 

outlays must be increased rather than taxes cut. Scenario 

C, in which outlays are spent in MN, gives the same 

result for decreasing taxes that would be found by 

seeking monetary parity in the tax-outlay relationship. 

However, a larger percentage increase (31% vs. 24%) in 

the dollar outlay is required compared to the tax dollar 

decrease to achieve both dollar and emdollar parity. 

Emergy or dollar parity per se may not result in the 

optimum relationship to promote maximum mutual 

benefit between a state and the nation of which it is a 

part. Energy Systems Theory (Odum 1994) postulates 

that maximizing empower at all levels of organization
An Emergy Evaluation of Minnesota 

45 

Table 11. Analysis of Federal Outlay and Tax Relationships 

sej y-1 X 1020 1997 Em$ $ % Change 

Scenario A (Current) 

All Federal outlays spent in MN 921.8 3.60E+10 1.98E+10 

All Minnesota taxes spent in US 665.7 2.60E+10 2.60E+10 

Surplus for the US 256.1 1.00E+09 -6.21E+09 

Minnesota surplus over outlays spent in U.S. 415.2 1.62E+10 

Scenario B 

All Federal outlays spent in the US 506.6 1.98E+10 1.98E+10 

Federal taxes not spent in Minnesota 1211.2 4.73E+10 2.60E+10 

Emergy Deficit for Minnesota -704.6 -2.75E+10 -6.21E+09 

Emergy Parity 704.6 2.75E+10 

Increase Federal outlays for parity 2.75E+10 139% 

Decrease Minnesota taxes for parity 1.51E+10 58% 

Scenario C 

Federal outlays spent in Minnesota 921.8 3.59E+10 1.98E+10 

Federal taxes not spent in Minnesota 1211.3 4.75E+10 2.60E+10 

Emergy Deficit for Minnesota -289.4 -1.13E+10 -6.21E+09 

Emergy Parity 289.4 1.13E+10 

Increase Federal outlays for parity 6.21E+09 31% 

Decrease Minnesota taxes for parity 6.21E+09 24% 

simultaneously (Campbell 2000) is the goal function for 

successful systems. The current Federal outlay and tax 

situation for Minnesota is shown as Scenario A. 

Although we do not know that this scenario is 

maximizing empower in both systems, it has some 

interesting emergy flow advantages for both the state 

and nation. Using the extreme conditions that all Federal 

outlays are spent in Minnesota and that all taxes are 

spent elsewhere in the Nation, we found that the nation 

has an emergy surplus of 1.00E+10 Em$ which is 61% 

larger than the monetary surplus ($6.21E+9) under these 

conditions. This surplus emergy flow is derived 

primarily from the additional empower generated by 

spending outlays in Minnesota. In addition, Minnesota 

realizes a surplus under these conditions compared to 

what it would have if all Federal outlays had been spent 

out of the State. Determining the balance of taxes and 

outlays between states and the Nation is, of course, a 

political decision, but it is apparent that the Federal 

government gets good value for its tax dollars spent in 

Minnesota. Federal outlays increased 13.1% between 

1997 and 2000, while taxes increased 9.6% during this 

time (Appendix E). These increases actually result in a 

lower Federal stimulus and tax burden for Minnesota, 

since the emergy to dollar ratio of the United States 

(Appendix B4.2) declined by about 15% over these 

years. State emergy flows appear to be more sensitive to 

tax decreases, whereas, the Federal surplus may be more 

closely tied to an increase in outlays spent in Minnesota. 

Spending more of Minnesota’s tax dollars to support 

Federal functions located in the State or locating new 

Federal functions in the State may be win-win situations 

for both Minnesota and the Nation. 

The largest storage of biological natural capital in the 

State is found in Minnesota’s soils. The real wealth in 

Minnesota soils is 14% of the real wealth in its 

remaining iron ore reserves. With this large source of 

available energy, it should not be a surprise that 

Minnesota was 5th in the Nation in both agricultural 

receipts and exports in 2005 (12). We used an emergy 

analysis of Florida agricultural crops (Brandt-Williams 

2001) as a template to evaluate several Minnesota crops. 

The evaluations for Minnesota dairy, spring wheat, grain 
 Environmental Accounting Using Emergy: Minnesota 

46 

corn, and soybeans are reported in Appendix B3.7.2 and 

compared to similar crops grown in Florida and 

Arkansas (Appendix B3.7.1). The relative difference 

between transformities for the same or similar items is a 

measure of the relative efficiencies of the two 

production processes. Using this indicator we found that 

production of the three crops was much more efficient in 

Minnesota than in Florida or Arkansas. For grain corn 

almost all the inputs were lower and the yield was 3.76 

times higher in MN than in FL. The transformity of 

grain corn grown in Minnesota was only 0.082 to 0.126 

of that grown in Florida with and without services, 

respectively. A similar pattern was seen for soybeans for 

which yield was 2.32 times higher and most inputs were 

lower giving a ratio of transformities (MN/FL) that was 

0.28 and 0.42 with and without services. Fertilizer 

inputs were markedly less in Minnesota compared to 

Florida as might be expected based on Minnesota’s 

fertile soils. Energy and labor inputs varied by crop and 

location, but in general lower amounts of these inputs 

were required in Minnesota compared to Florida. One 

negative factor was soil erosion which was much greater 

in Minnesota. Soil erosion diminishes natural capital 

assets and would appear as a credit on the environmental 

liability account for agriculture in the State. The 

comparison of Minnesota spring wheat to wheat grown 

in Arkansas was less favorable. The yield per hectare 

was lower (82%), but required inputs were also lower, 

especially fertilizer and fuel. This resulted in a ratio of 

transformities (0.38 and 0.41) with and without services 

that made Minnesota the more efficient producer of 

wheat. Dairy production was also more efficient in 

Minnesota compared to Florida, but a full analysis of 

Minnesota inputs was not available so the exact 

difference is not known with confidence. 

Since the time of these analyses, Minnesota has 

rapidly built up the capacity to exploit its endowment of 

renewable emergy and natural capital to meet the State’s 

and the Nation’s need for energy. The use of wind 

power in Minnesota increased from 1997 to 2000 and it 

has continued to increase up to the present. Renewable 

energy production in Minnesota other than from 

hydropower doubled from 2000 to 2006 (3) and most of 

this was wind power. Even with this increase the 

generation of electricity from renewable sources only 

accounted for 6.8% of the electric power generated in 

Minnesota in 2006. In 2008 the large natural capital 

stored in the deep, rich alluvial soils of Minnesota was 

not only being used to produce food, but also energy in 

the form of corn ethanol. We have seen earlier that 

Minnesota is a very efficient producer of corn, but 

emergy studies (Odum and Odum 1984, Lanzotti et al.

2000, Ortega et al. 2003, Felix and Tilley 2008) have 

shown that ethanol from both agricultural crops and 

biomass crops yields little net emergy (Emergy Yield 

Ratio, EYR, = 1.1-1.3). The energy sources that were 

economic from 1980 until 1994 had an EYR from 3 to 

12 (Odum 1996) and in earlier times the Emergy Yield 

Ratios were even higher (Odum 1996). Thus, we can not 

expect ethanol to replace petroleum as an engine of 

growth for the United States, because growth requires a 

large net emergy yield. An emergy analysis of the corn 

ethanol industry in Minnesota should be performed 

evaluating its net emergy yield including any negative 

effects on the environment and food production in the 

assessment of costs and benefits. 

3.10.2 Comparison with other States 

Minnesota’s status relative to other states and the 

Nation can be shown by comparing emergy indicators 

and indices. Indices that are related to system 

characteristics such as self-sufficiency, sustainability, 

and equity in the exchange of real wealth (emergy) are 

of particular interest to society because they are related 

to the well-being of environmental systems. Table 12 

contains comparisons of indices calculated for 

Minnesota in 1997 and 2000 with those of West 

Virginia in the same two years and for the United States 

in 1997. The results reported in Table 12 are calculated 

using the same method that incorporated improvements 

presented in Campbell et al. (2005a). In addition, 

Campbell and Lu (manuscript) have recently 

recalculated the emergy to dollar ratio for the U.S. from 

1900 to 2004, which allowed us to calculate the partial 

set of indices for the United States shown in Table 12. 

We will have a stronger basis for comparative analysis 

when studies of 6 additional states (VA, MD, PA, DE, 

NJ, and RI) for the base years 1997 and 2000 are 

completed. 

The import/export balance of emergy flows shows 

the relationship between trading partners. In a system 

where trade is equitable, the emergy exchanged would 

be approximately equal, i.e., there would be parity in 

emergy exchange. 
An Emergy Evaluation of Minnesota 

47 

Table 12. Comparison of Emergy Flows and Indices for Minnesota and West Virginia in 1997 and 2000 

with selected indices for the United States in 1997. All flows times 1021 sej y-1 unless otherwise 

noted or expressed as ratios.

Index Minnesota1 Minnesota1 W. Virginia2 W. Virginia2 US1

1997 2000 1997 2000 1997 

Renewable Absorbed 19.1 19.1 6.6 6.6 1031 

In State Non-renewable use 132 146 206 196 

Imported Emergy 575 570 159 157 

Total Emergy Inflows 595 589 169 169 

Total Emergy used 726 735 221 230 21240 

Emergy used from home sources 0.21 0.21 0.28 0.31 

Exported emergy including fuels 763 759 305 288 

Imports-Exports -188 -189 -147 -129 

Ratio of export to imports 1.33 1.33 1.92 1.81 

Fraction used, locally renewable 0.026 0.026 0.030 0.030 0.049 

Fraction of use purchased outside 0.79 0.78 0.72 0.68 

Fraction of use that is imported services 0.27 0.27 0.17 0.15 

Fraction of use that is free 0.036 0.036 0.031 0.029 0.057 

Ratio of purchased to free 26.8 26.7 19.7 20.6 3.5 

Environmental Loading Ratio 37.1 37.1 20.4 21.3 19.6 

Investment Ratio 3.81 3.67 2.39 2.11 

Area m2 2.25E+11 2.25E+11 6.24E+10 6.24E+10 9.82E+12 

Population, individuals 4,735,830 4,919,479 1,815,481 1,808,344 272,912,000 

Use per unit area, sej m-2 

y

-1 3.23E+12 3.26E+12 3.54E+12 3.70E+12 2.16E+12 

Use per person, sej ind.-1 

y

-1 1.53E+17 1.49E+17 1.22E+17 1.27E+17 7.78E+16 

Renewable Carrying Capacity, 

individuals 

124,235 127,574 86,805 82,702 13,247,282 

Developed Carrying Capacity, 

individuals 

993,884 1,020,589 694,443 661,619 108,978,256 

Gross State Product $ 1.55E+11 1.85E+11 3.83E+10 3.97E+10 8.30E+12 

Emergy to Money Ratio sej/$ 4.66E+12 3.97E+12 5.76E+12 5.79E+12 2.56E+12 

Ratio of Electricity to Emergy Use 0.047 0.047 0.073 0.073 0.095 

Fuel Use per Person, sej/individual 1.78E+16 1.73E+16 4.50E+16 3.41E+16 1.65E+16 

Renewable Empower Density sej m-2 

y

-1 8.46E+10 8.46E+10 1.06E+11 1.06E+11 1.04 E+11 

1

This study, 2Campbell et al. 2005). 
 Environmental Accounting Using Emergy: Minnesota 

48 

However, a definitive determination of an equitable 

balance between partners would have to consider all 

aspects of their relationship, including factors that are 

difficult to evaluate such as the exchange of technical 

and cultural information and the provision of security. 

What is equitable in trade is also determined by the 

resource reserves and needs of the various states or 

regions and the needs of the Nation of which they are a 

part. Often a monetary balance does not mean that the 

emergy exchange is balanced and this leads to distinct 

advantages in the exchange of real wealth for either the 

buyer or seller (Brown 2003, Campbell et al. 2005a). 

The Energy Systems approach calls for analysis of 

systems on multiple scales to determine the net result of 

trade at several different levels of hierarchical 

organization, e.g., county, state, nation. 

The results in Table 12 show that the emergy of 

exports exceeds imports for both Minnesota and West 

Virginia. In Minnesota the emergy deficit is caused 

primarily by the shipment of iron ores and concentrates 

out of the State, whereas in West Virginia the shipment 

of coal accounts for almost the entire emergy deficit. 

Strategic materials and energy are invariably 

concentrated in particular locations in a nation and the 

national system could not survive and prosper without 

using them broadly. Emergy accounting shows the real 

wealth in these resources in terms that are directly 

comparable to the real wealth in the purchasing power 

of the money received for them. The question that 

resource rich states, like West Virginia and Minnesota, 

and the Nation must answer is, “What is an equitable 

emergy feedback to compensate for the vast quantities 

of the work of nature that were required to generate 

nonrenewable fuels and minerals?” This question is 

complicated by the additional question, “Who owns the 

products of nature’s work?” and “Who has the right to 

benefit from this work?” In the case of Minnesota and 

West Virginia the whole nation benefits greatly from the 

imbalance in emergy exchange between these two states 

and the nation at-large. However, the social 

consequences of these deficits have been very different 

(13). Minnesota is one of the richest states in the Nation 

(8th in per capita income in 2004), whereas West 

Virginia is one of the poorest (48th in per capita income 

in 2004). It is interesting that the poorest region of 

Minnesota, i.e., the Arrowhead Region, supplies the 

Nation with a rich emergy subsidy in ores and timber. 

The emergy gain to the Nation from trade with 

Minnesota and West Virginia is evidenced by the 

emergy exchange ratio (EER) for iron and coal. 

Minnesota exported 1290E+20 sej of iron ores and 

concentrates in 1997 for which it received 1.2 billion 

dollars and West Virginia exported 1497 E+20 sej of 

coal in the same year, for which it received 3.92 billion 

dollars. The Emergy Exchange Ratios (EER) for 

Minnesota iron and West Virginia coal are as follows: 

Minnesota Iron; 

(1290 E+20 sej/y)/ [($1.2 E+9) (2.56 E+12 sej/$)] = 

(1290 E+20 sej/y)/ (30.7 E+20 sej/y) = 42:1 

West Virginia Coal; 

(1497 E+20 sej/y)/ [($3.92 E+9) (2.56 E+12 sej/$)] = 

(1497 E+20 sej/y)/ (100 E+20 sej/y) = 15:1 

Thus, the buyer of Minnesota iron receives 42 times the 

benefit in real wealth compared to the emergy buying 

power of the money paid for the concentrates, if the 

money paid for the concentrates is then spent at an 

average location in the United States. In the case of WV 

coal, the net benefit is 15 times the buying power of the 

money received. If the money received for taconite 

pellets was spent in Minnesota, the advantage to the 

buyer would be 22:1. In either case, Minnesota iron and 

West Virginia coal provide large fluxes of real wealth to 

support growth in the regional, national and global 

economies that receive these raw materials. 

 The recent increase in oil prices on the international 

market provides and example of the limits to growth 

imposed when rising prices eliminate the emergy 

advantage to the buyer of natural resources. For 

example, Saudi Arabian oil at $100 per barrel when 

exchanged for 2004 US dollars has an emergy yield of 

1.647:1 {(6.1E+9 joules per barrel) (54000 sej/J)/ 

[(2.0E+12 sej/$) ($100 per barrel]}. In 2004, $20 per 

barrel oil would have yielded 8.2:1 and oil at $164.70 

per barrel oil would have no net yield to the United 

States. From this preliminary analysis we might guess 

that the long term equilibrium price for oil based on 

emergy parity of the exchange and the emergy to money 

ratio in the U.S. economy in 2004 would be around 

$165 per barrel. Above this price the U.S. infrastructure 

and functions that depend on oil for their maintenance 

would be forced to decline or find substitutes for 

petroleum. Of course, the parity price would rise in the 

future if the emergy to dollar ratio declines as a result of 

inflation, i.e., more dollars and/or less emergy flowing 

in the U.S. economy. 
An Emergy Evaluation of Minnesota 

49 

The empower density or the emergy use per unit area 

is indicative of the average intensity of development in a 

state. In 1997, the annual emergy use per square meter 

in Minnesota was 0.91 of that in West Virginia and 1.5 

times that of the U.S. as a whole. Twenty-nine percent 

of the State’s land area is covered by forests and 39% is 

used for agriculture. High empower densities are found 

in areas with emergy intensive activities, e.g., iron 

mining. Also, major urban areas, such as MinneapolisSt. Paul, which is a metropolitan regional center with a 

diverse manufacturing base, and the port city of Duluth, 

which is the center of commerce in the resource rich 

northeast. The diverse economic base for Minnesota, 

which includes agriculture, mining, manufacturing, 

forestry and commerce, illustrates why its emergy flow 

density is 50% greater than the Nation as a whole. In the 

case of West Virginia, the intense industrial utilization 

of coal to generate electrical power for consumption 

outside the state and to support chemical manufacturing, 

steel production, and other export industries results in 

very high empower densities in certain areas within a 

state that is 79% forested. This tendency to spatially 

concentrate the industrial use of coal power is further 

magnified by the relatively small area of flat land in 

West Virginia. Thus industry is found to be heavily 

concentrated in narrow valleys, as in the Kanawha 

Valley and along the Ohio River, and the overall result 

is an average empower density 1.64 times that of the 

Nation. 

The renewable emergy base for a state sets limits on 

the level of economic activity that is sustainable without 

subsidies from outside. Minnesota can support 2.6% of 

the present population at the 1997 standard of living 

using its renewable resources alone in their current state 

of development compared to 3.0% for West Virginia 

and 4.9% for the Nation. If the 1997 standard of living 

in West Virginia is adjusted by removing exported 

electricity from total emergy use, 5.8% of the population 

could be supported. By this measure, the sustainability 

of Minnesota at its 1997 standard of living was 47% 

lower than the national average and 55% lower than 

West Virginia. Minnesota’s large storage of wealth in 

iron and mineral reserves will not help its energy 

sustainability except through trade for needed fuels. 

However, its large endowment of wind energy and 

waves and the stored wealth in soils and peat along with 

sustainable rotations for the management of forest 

biomass will provide a renewable energy base for 

Minnesotans, when fossil fuel energy sources decline. 

 

The investment ratio is an indicator of the 

competitiveness of a state in attracting additional 

investments. Lower ratios are more attractive for future 

development. The investment ratio in Minnesota in 1997 

was 3.73:1 compared to an average ratio of 2.39:1 for 

West Virginia and 7.0:1 for the United States as a whole 

(Odum 1996). In contrast, the environmental loading 

ratio, ELR, was 37.3:1, which is 86% higher than West 

Virginia (20.4) and the Nation (19.6). This ratio 

indicates that economic activities may be putting a large 

stress or load on the environment of Minnesota. These 

results may mean that the heavy nonpoint loads from 

agriculture in Minnesota are at least as important as 

intense point loads from mining and chemical 

manufacturing found in West Virginia, which of course 

are also present in parts of Minnesota. 

The fraction of use from home sources for Minnesota 

was 0.21 in 1997. West Virginia was less dependent on 

the national economy with 28% of its emergy coming 

from sources within the State. Since the two numbers 

are complements, this fact was also evident from the 

fraction of total use that was purchased outside the 

State, 0.79, compared to 0.72 for West Virginia. 

The emergy use per person is considered to be an 

indicator of the overall quality of life experienced by the 

people of a nation or state. The emergy use per person 

in Minnesota was 25% to 53% higher than in West 

Virginia depending on whether exported electricity is 

counted in the State’s emergy use and 97% higher than 

for an average place in the Nation. This index shows 

that the quality of life experienced by Minnesotans is 

high. This includes not only their economic welfare, but 

also the wealth of their natural resources and society. At 

present social welfare is captured implicitly in overall 

emergy use. In the future we will develop methods to 

fully assess the social systems of the State, so that these 

values can be captured explicitly in our overall estimates 

of welfare. 

In 1997, the emergy to dollar ratio for Minnesota 

was 81% of that for West Virginia and 182% that of the 

United States. This indicates that in 1997, a dollar spent 

in Minnesota purchased about 1.8 times the real wealth 

(emergy) in Minnesota products and services compared 

to a dollar spent at an average location in the United 

States. The emergy to dollar ratio indicates how much 

Minnesota loses or gains on average when it trades with 

various partners (see the emergy exchange ratio 

discussion above). Areas with a high emergy to dollar 
 Environmental Accounting Using Emergy: Minnesota 

50 

ratio can attract tourists and new businesses. The 

emergy to dollar ratio of Minnesota indicates that it is an 

attractive destination for tourists as indicated by the 

increase in tourist dollars spent in the State from 7.2 

billion in 1997 to 9 billion in 2000. States with a high 

emergy to money ratio, e.g., Maine (Campbell 1998) 

and West Virginia (Campbell et al. 2004), often have 

tourism as a major part of their economies. The 

difference between the emergy to money ratios in West 

Virginia and Minnesota indicates that Minnesotans 

would gain from vacationing in West Virginia, because 

a dollar spent in West Virginia buys more real wealth 

(emergy) than it does when spent in Minnesota. This is 

true because the free work of the environment 

contributes more to local products and services in states 

with a high emergy to money ratio. Brown and Ulgiati 

(2001) showed that problems can arise when tourists’ 

dollars compete for limited natural resources in 

developing economies. Therefore, where the support 

capacity of the system is limited the effects of tourism 

on the price of local products consumed by residents 

should be carefully monitored. 

The ratio of the emergy in the electricity and fuel 

used to total emergy use is an indicator of the high 

quality energy in people’s lives. This indicator of the 

standard of living was 36% lower in Minnesota than in 

West Virginia and 50% lower than the national average. 

We are not sure why Minnesota’s use of electricity is a 

lower fraction of total use than in West Virginia, but the 

emergy of electricity used per capita there is 81% of that 

used in West Virginia. This lower electricity use in a 

state with a high quality of life might be explained by a 

lower fraction of electricity being used for low quality 

purposes, e.g., heating, in Minnesota. Fuel use per 

person in MN was about the same as in the Nation and 

about half of that used in West Virginia, where some 

coal mined in-state is used to produce electricity for 

export (Campbell et al. 2005a). 

3.11 Summary of Findings as Related to the 

Management Questions 

The findings of the Minnesota emergy evaluation 

provide understanding and data to shed light on the 

management questions presented above. Here each 

question is repeated and then relevant information from 

the analysis is presented. 

(1) “What is the current level of economic investment in 

relation to Minnesota’s resource base, and is this level 

of investment sustainable?” Minnesota’s relatively low 

investment ratio 3.81:1 in 1997 and 3.67:1 in 2000 and 

relatively high environmental loading ratio (37.1:1) 

show that it is a state with enough renewable and 

nonrenewable resources to attract further economic 

development, while currently experiencing some 

degradation of its renewable resource base due to past 

and present economic activities. Even though 

environmental resources are being exploited by intense 

economic development in parts of the State, e.g., the 

iron ranges, some agricultural and forest areas, and most 

industrial areas, Minnesota’s stored wealth is so great 

that development pressures can be expected to continue 

and increase in the future. The pressure to further 

develop Minnesota’s resources, as well as current point 

and nonpoint pollution produced by agriculture, industry 

and mining imply that Minnesota will need to continue 

to protect and restore the environment to ensure that the 

present high quality of life experienced by Minnesotans 

continues into the future. 

Our estimate of carrying capacity indicates that only 

2.6% of the Minnesota population in 2000 can be 

sustained at the 2000 standard of living using the 

emergy of renewable resources alone. If the intensity of 

resource use needed to support an average developed 

state in the world during the 1980s was to be maintained 

in the future in Minnesota, only one fifth of the 2000 

population could be supported at their 2000 standard of 

living. These are conservative levels of support and 

technological change to harvest a greater fraction of 

renewable emergy inputs for human use may result in 

raising these low estimates somewhat. Today, 

Minnesotans and the people of the United States as a 

whole face serious challenges with regard to our choices 

about energy and the environment that will determine 

our future prosperity. This fact has become evident to 

many people and government and private entities are 

beginning to search for solutions. 

(2) “What is the net exchange of real wealth (emergy) 

between Minnesota and the Nation?” Emergy 

accounting shows that Minnesota is a state with great 

real wealth in natural resources that supplies a large 

emergy subsidy to the Nation. Minnesota exports 33% 

more emergy than it receives in return. In 1997, this 

resulted in an imbalance of 1.88E+23 sej y-1, which is 

about one-fourth of the annual emergy used in the State. 

If exported ores and concentrates are removed from the 

balance, exports exceed imports by about 10%. In 
An Emergy Evaluation of Minnesota 

51 

contrast, the monetary exchange between Minnesota and 

its trading partners shows a $20 billion surplus in 1997. 

The import (+) and export (-) of the emergy in materials 

(without considering taconite) is nearly balanced 

(-1.7%), but the exported services exceed imported 

services by 26.5%. The surplus in value added services 

goes directly to the bottom line in its effect on personal 

income and the welfare of the population. In contrast, 

imported services were slightly larger than exported 

services in West Virginia and personal income 

apparently suffered as a result. Both states are resource 

suppliers for the Nation, exporting large emergy 

surpluses in the environmental work used to create fuels 

and minerals. 

(3) “What are the major causes for any observed 

imbalances?” The emergy of iron ores and concentrates 

exported without full use accounts for about two-thirds 

of the difference between emergy imports and exports in 

the State. Most of the remaining imbalance is accounted 

for by the work of human services incorporated in 

Minnesota agricultural, industrial, and informational 

products for export. The large emergy imbalance related 

to iron export indicates that the costs and benefits of 

iron mining to Minnesota and to the Nation should be 

considered as an issue for discussion. For example, one 

trade-off is that the economic benefits derived from 

taconite used in the steel mills of the mid-west and east 

primarily accrue outside of Minnesota, whereas, the 

environmental cost of extraction and processing is born 

primarily by the State. The environmental damage done 

in the State as a result of iron mining was not evaluated 

in this study, and it should be addressed in future 

research. 

(4) “What actions might be taken to address an 

imbalance, if it exists?” Federal outlays and taxes are an 

obvious way to address trade inequities between a state 

and the Nation. The current situation with regard to 

taxes and outlays in Minnesota has been explored above. 

However, the questions that arise from noting the nature 

of the emergy imbalance in trade between Minnesota 

and the Nation are more profound than those related to 

tax policy. Such questions must consider how we should 

count the presently unaccounted for subsidies from 

nature’s work upon which the existence of all industrial 

societies depend. Questions related to the ownership of 

these environmental resources arise followed by a 

consideration of who should benefit from the millions of 

years of environmental work that were required for the 

creation of mineral and fossil energy resources. The 

heterogeneous distribution of natural wealth and human 

occupation of the land raises questions related to the 

equity of resource distribution among people, states, and 

nations. These questions can not be resolved in this 

short report, however, it is apparent that there should be 

a national and perhaps a global debate on the 

implications of modern society’s debt accrued as a result 

of its reliance on the renewable and nonrenewable 

resources of the environment. This debate and the 

questions mentioned above might be elucidated by using 

environmental accounting methods and emergy 

valuation to systematically consider all the benefits and 

costs accruing as consequences of the various policy 

choices that arise. 

(5) “How does Minnesota’s standard of living compare 

to other states and the Nation?” The quality of life in 

MN as measured by the emergy use per capita is twice 

the national average. This index is also high in West 

Virginia where it is 1.57 times that of the Nation, but in 

this case many social indicators are depressed (CVI 

2002). This paradoxical condition can occur if the 

benefits of high emergy use are not accurately 

transmitted to people by the economic system, but also 

see Campbell et al. (2005). Comparison of the situations 

in Minnesota and West Virginia revealed that West 

Virginia does not maintain a value-added surplus in the 

products it provides to the Nation over those it receives. 

As a result the emergy that can be purchased with the 

dollars West Virginians receive for their work is just 

enough to maintain an emergy balance in imported and 

exported goods and services but not enough to gain a 

comparative advantage in real wealth. The high emergy 

use per capita comes in large part from coal mined and 

used within the State and much of the emergy value of 

this coal is not included in the dollar flows received for 

it that people depend on to purchase emergy outside the 

State. Thus, in West Virginia there is a paradoxical 

situation where the emergy per capita is high but the 

quality of life is low. If dollars were flowing into West 

Virginia to pay for the uncounted work of nature and if 

this money was spent to benefit the people of the State, 

West Virginians would have the high quality of life 

indicated by their emergy use per capita. In contrast, 

Minnesotans use the dollar surplus received for their 

value-added manufactured goods compared to imported 

goods purchased, to purchase both inside and outside the 

State what they need for a high quality life. In this case 

the economy is diverse enough so that the imbalance in 

real wealth that results from the exchange of iron ore 

does not overwhelm the entire economy. This situation 
 Environmental Accounting Using Emergy: Minnesota 

52 

might be different, if regions within the State of 

Minnesota were examined. 

(6) “Who benefits most from the productive use of the 

State’s resources?” The 1997 CFS shows that over 53% 

of the tonnage of shipments remains within the State. 

About 25% of shipments or half of the tonnage exported 

goes to the North Central states (OH, MI, IN, WI, and 

IL). Louisiana (3.7%), Iowa (3.2%), North Dakota 

(3.1%), and Pennsylvania (2.1%) account for another 

12% of the tonnage or almost 80% of exports. 

Minnesota ships large tonnages (short tons) of 

agricultural products (77,391,000), metal ores and 

concentrates (47,367,000), gravel, sand, and crushed 

stone (45,201,000), and petroleum products 

(28,432,000). For the most part, the people of Minnesota 

benefit from the productive use of their resources. 

Minnesota maintains a favorable trade balance in the 

exchange of manufactured products and the skilled work 

force commands a premium in the value of exported 

goods and services compared to imports. Minnesota’s 

long history of supporting and promoting education is 

undoubtedly a factor in training and maintaining a high 

skill level in their population. For example, in 1997 the 

average emergy of a person in Minnesota based on their 

education level (2.59E+17 sej/ind) was 22% higher than 

in West Virginia. Despite Minnesota’s favorable 

position on the whole, the results of this analysis 

indicate that there may be some concern about the 

equity of the current terms of trade for taconite. This 

question and other questions related to accurately 

accounting for environmental work in the economy 

might be examined in more detail as a part of a regional 

study of Northern Minnesota. 

(7) “How self-sufficient is the State based on its 

renewable and nonrenewable resources?” The emergy 

indices of self-sufficiency (emergy from home sources) 

and dependence (fraction of use purchased outside and 

fraction of use that is purchased service) presented 

above show Minnesota is dependent on outside sources 

for 79% of its emergy use. For West Virginia 

dependence on outside sources was only 72% of total 

use, primarily because West Virginia coal is used as the 

primary energy source for the State. Perhaps more 

telling is the fraction of use that is imported services, 

which was 27% for Minnesota but only 17% for West 

Virginia. All indicators demonstrate that Minnesota is 

better integrated with and more dependent on the 

economy of the Nation, than is West Virginia. A more 

complete understanding of the meaning of this index 

and of the other indices in this study will only be gained 

as more states are analyzed using these methods and the 

results added to the comparison. Minnesota’s potential 

for self-sufficiency in a lower energy future (Odum and 

Odum 2001) may be more accurately shown by the fact 

that considerable wind and wave energies are available 

to be harnessed on a renewable basis. Also, there is a 

large storage of biomass in peat and a smaller but 

potentially renewable storage in forest biomass. The 

greatest natural biological resource in Minnesota is its 

fertile soil (Table 8); therefore, agriculture can be 

expected to remain a pillar of the Minnesota economy in 

a lower energy world. The large iron, copper, and nickel 

deposits in Minnesota may provide the capacity to trade 

for the fossil fuels and other items that it lacks far into 

the future; however, the considerable environmental 

impacts of these activities would need to be mitigated. 

The eighth question “How can we manage the 

environment and economy to maximize the well-being 

of humanity and nature?” relates directly to the 

decision-making criteria for environmental managers. 

Financial managers have a clear criterion for overseeing 

the operations of a business, which is to maximize 

profits and shareholder value. Energy Systems Theory 

provides a parallel maximal principle related to the 

overall well-being of both mankind and nature, which 

managers should consider in making decisions on 

environmental policy. In this method, policy outcomes 

are compared based on the total environmental, 

economic, and social emergy flows realized under each 

alternative. The maximum power (empower) principle 

(Lotka 1922, Odum 1996) indicates that those systems 

which maximize empower in their networks will be the 

ones that prevail in evolutionary competition among 

alternatives. Campbell (2001) gives a theoretical 

argument and some practical examples of how 

maximizing empower in ecosystems is a mechanism for 

determining what is valuable, in the sense that it 

promotes system survival and well-being. 

Environmental accounting using emergy and energy 

systems model simulations allow managers to quantify 

the empower relations among environmental systems 

with alternative designs. Maximizing empower for the 

entire system gives a clear unified criterion for decision 

making and provides an answer to the eighth 

management question given above. The use of this 

criterion in environmental decision-making may help 

society avoid the expense of costly trials and errors, 

which are often required under present decision-making 

paradigms such as adaptive management. 
An Emergy Evaluation of Minnesota 

53 

3.12 Recommendations to Managers 

 Constructing emergy accounts for the State of 

Minnesota gave us quantitative and comparable 

information to judge the condition of the economy and 

environment in the State and to provide preliminary 

answers to some management questions. Emergy indices 

helped us understand the current condition of the State 

and how we might set policies to improve conditions 

there. Based on past emergy analyses (Odum 1996, 

Campbell et al. 2005a) and the insights gained from this 

study, we recommend that the methods and principles of 

emergy accounting presented in this report and in Odum 

(1996) be used to keep consistent and accurate books for 

all human enterprises, including businesses, counties, 

states, regions and nations. We recommend that 

managers’ call for further development of these methods 

using the existing and tested methods of bookkeeping 

and accounting (Campbell 2005). If emergy accounting 

methods continue to be developed and tested so that 

they become generally accepted, managers will be able 

to use independent emergy audits of their 

environmental, economic, and social systems as a 

regular part of a system of checks and balances 

governing the relationship between economies, societies 

and the environment. 

3.13 Minnesota and the Future 

No system on earth exists alone. According to the 

maximum empower principle (Lotka 1922, Odum 

1996), they all have developed interactions with the net 

result that empower (emergy per unit time) moves 

toward a maximum under a given set of external forcing 

energies (emergy signature). The maximum empower 

principle implies that human and natural systems will 

become coupled in ways that increase emergy flow. 

Therefore, we can expect Minnesota to follow this path 

in the future constrained by the changing emergy 

signature of the Earth. Present Minnesota connections 

include sediments, nutrients that move from this north 

central state to the Louisiana coast via the Mississippi 

River and cargo that is transported to and from 

Minnesota on the river. Also, goods from Minnesota and 

the hinterland states to the west, e.g., the Dakotas and 

Montana, are shipped to the Atlantic Ocean through the 

Port of Duluth via the Great Lakes and the St. Lawrence 

Seaway and other goods are returned to the hinterlands 

via this route. Railways and highways carry Minnesota 

exports and imports coupling the State’s economy most 

closely with the surrounding states of the North Central 

Region and Canada, but also to a lesser degree with 

states throughout the Nation as shown by data form the 

CFS (2). Energies of many kinds are exchanged within 

and among these state systems and both the state and 

national systems should be better off in the long run as a 

result of this process. However, when the external 

emergy sources to a system are changing, it often takes 

some time for emergy flows to be maximized under the 

new or changing conditions (Campbell 2000b). If 

maximizing empower in a system network is the 

decision criteria in evolutionary competition as 

proposed by Lotka (1922) and Odum 1996), then 

emergy analysis can help discern where the patterns of 

interaction may be improved (by elucidating conditions 

that increase emergy flow) toward the end of attaining 

greater benefits (empower) for the environmental 

system as a whole including all its ecological, economic, 

and social components. 

In the future if not now, world oil production will 

reach its peak and then decline (Campbell and Laherrere 

1998) and the United States will become more 

dependent on the remaining deposits of fossil fuels 

within its borders and on the renewable energies that 

flow into it each year. West Virginia coal and Minnesota 

iron, copper and nickel will be important nonrenewable 

resources for the Nation in the future. Since 

nonrenewable resource supplies of energy and materials 

are limited, it is now and will continue to be important 

to continuously restructure societal systems to fit the 

global resource base. Minnesota can prepare for the 

challenge of meeting larger demands on its natural 

resources by using its education system to carry-out 

needed research on energy and the environment. In 

addition, emergy accounting methods may be widely 

taught and used to evaluate the environmental and 

socio-economic costs and benefits associated with 

current economic production systems, energy 

technologies, and development plans. Such analyses will 

help determine what alternative system designs lead to 

social and economic prosperity and which ones will 

maintain a healthy environment and be sustainable, i.e., 

supported by the capacities of the existing emergy 

signature. The emergy accounts and indices presented 

above are a beginning to help Minnesota move toward a 

prosperous and sustainable future. 
 Environmental Accounting Using Emergy: Minnesota 

54 

Section 4 

Discussion 

The publication of “Environmental Accounting: 

Emergy and Environmental Decision Making” by H.T. 

Odum in 1996 made the methods of Emergy Analysis 

easily available to the broader scientific community for 

the first time. These methods make it possible to keep 

“the accounting books” for an environmental system, 

including accounts for the economic, ecological, and 

social components of these systems, in common units of 

solar emjoules (sejs). Despite the promise that some 

scientists see in emergy methods, the scientific 

community as a whole has been slow to recognize this 

potential. Tests of the method and comparison of results 

to other methods have been infrequent; and therefore, 

the potential benefits of adding emergy accounting to 

the tools commonly used by environmental managers 

have been foregone. One purpose of this series of 

technical reports (Campbell et al. 2005a) is to make 

emergy methods and data sources easily accessible to 

ecologists, economists, and managers within and outside 

the EPA in a peer reviewed government document, so 

that they might be more widely tested and applied in 

finding solutions for practical problems encountered in 

managing the complex systems of humanity and nature. 

A second purpose was to present the results of an 

emergy evaluation of Minnesota and to test the efficacy 

of these methods by addressing questions that 

environmental managers have about economic and 

environmental conditions and policies relevant to 

managing a whole state. 

The methods of emergy accounting are still 

developing, but we believe that they possess great 

potential as a tool to aid environmental decisionmaking. Several advances in the method have been 

incorporated into this series of reports: (1) we made the 

analogy between emergy accounting and financial 

accounting and bookkeeping explicit by proposing the 

use of emergy income statements and balance sheets as 

the standard tools of environmental accounting 

(Campbell 2005, Campbell et al. 2004). (2) We found 

formerly unused data sources and revised the method for 

evaluating imports and exports to and from states in the 

United States, making it possible to construct accurate 

accounts for these important fluxes. (3) We calculated 

new transformities for snow, taconite, dolomite, sulfur, 

and the chloride ion (Appendix B), and estimated rough 

transformities for commodity classes in the Standard 

Classification of Transported Goods (SCTG). In 

Appendix B we also included revised calculations of the 

emergy and transformity of agricultural products using 

updated numbers for the emergy to dollar ratio and for 

the transformity of evapotranspiration. Three Minnesota 

crops and milk production were also analyzed. The new 

transformities section includes an update of the 

calculation of the transformity of electricity generated 

from nuclear power first presented in Campbell et al.

(2005). The transformities of minerals used in this report 

reflect the new method proposed by Cohen et al. (2007). 

This method is not perfect and it may be adjusted in the 

future, but we believe that it gives more accurate 

estimates of the emergy required to produce 

economically viable concentrations of the elements than 

those found by methods currently in use. To apply this 

method, the emergy of a mineral deposit needs to be 

adjusted by taking into account its ore grade. 

4.1 Standard Methods versus Intellectual 

Creativity 

The methods of emergy analysis have evolved over 

the past 37 years (Odum 1971, 1983, 1996) and the 

vitality and creativity of new insights and ideas have 

played an important role by creating the present 

generality and flexibility of the method. This has caused 

the accuracy with which the various flows have been 

determined to vary over time. For example, previous 

emergy analyses for the states of Florida (Odum, et al.

1986, Odum et al. 1998b), Texas (Odum, et al. 1987), 

Alaska (Brown et al. 1993), North Carolina (Tilley 

1999), Arkansas (Odum et al. 1998a), and Maine 

(Campbell 1998) have each added new insights and 

ideas to the method for analyzing states, but differences 

in the quantification of inputs make the results of these 

analyses, done over many years, only good for first 

order comparisons. Comparisons are still possible 
Discussion 

55 

because emergy analyses report relative results and thus 

the conclusions of a study rarely change unless there are 

large changes in the inputs. It is not our intent to limit 

the future development of emergy analysis methods; 

however, standards for the emergy analysis of states and 

other systems are needed to make results comparable 

and to ensure that anyone can use the proposed tools to 

reproduce results. We hope that the material presented 

here makes the method for constructing the emergy 

accounts for states transparent and reproducible to all 

those who choose to use and improve it. To this end we 

included extensive notes in the appendices that 

document the calculations of the entries on the emergy 

tables. Appendix D is devoted to a detailed description 

of the method that Campbell et al. (2005a) used to 

determine the emergy of imports and exports. We also 

include Appendix B that documents the sources for all 

the transformities used and the calculations for the new 

transformities that were determined in this study. 

4.2 Methods Developed and Refined in this 

Study 

The renewable emergy base for a system is an 

important characteristic that has been determined using 

various rules over the years. The objective in calculating 

this quantity is to determine the degree to which the 

renewable energy sources of the earth have been 

concentrated in a particular area without double 

counting any of the inputs. The renewable emergy 

delivered to the system boundaries is received by the 

system. The part of the renewable emergy received that 

is absorbed is most important because it is the emergy 

actually used within the system to make products and 

services. The mutually supporting role of the various 

kinds of energy transformed in the system has been 

clearly demonstrated by the complementary interactions 

of the geopotential energy of runoff and the chemical 

potential energy of evapotranspiration working together 

to structure landscapes (Romitelli 1997, Odum et al.

1998a, Brandt-Williams 1999). In this study, the 

renewable emergy received (RR) and the renewable 

emergy absorbed (RA) were clearly distinguished in 

definitions and in the calculation of indices. We think 

that it is important to distinguish these two quantities 

because the transformity of the system and its products 

are a direct consequence of the energy used in that 

system, whereas, the energy received by the system 

indicates the potential of the system for development. 

That is, the amount of emergy received may determine 

the attractiveness of an area for investment and future 

development. For example, all the river water entering a 

state could be used to support economic activities within 

that state, but invariably only a small portion will be 

used. If the boundaries are wide enough, almost all the 

emergy received can be used in the system, 

nevertheless, we believe that these two quantities should 

be distinguished in future calculations of emergy indices 

that use the renewable emergy base for the system. For 

Minnesota this distinction was not very important, 

because wind energy was the largest renewable input to 

the State and its calculation is only for what is absorbed. 

Similarly the second largest input was from waves and 

this calculation also is only what is absorbed. Water 

more often has chemical and geopotential energies that 

enter and then leave a region with only a part of the 

delivered available energy absorbed by the system. In 

this case, only the St. Croix River contributes to the 

emergy base of the State and its contribution is less than 

1% of the total. 

The method for calculating the imports and exports 

to and from a state in the United States was revised to 

use data from the U.S. Census Bureau’s Commodity 

Flow Survey for 1997 (this survey was updated in 2002 

but this data was not available at the time this study was 

performed). This revised method and new data sources 

represented a major improvement in accuracy over the 

first method used to determine the imports and exports 

to and from the State’s economy (Campbell et al.

2005a). In this study, we further revised this method and 

used new calculations of the emergy base for the United 

States to put the national indices on the same basis as 

those calculated for the states. To reconcile all studies 

West Virginia was updated to use the new number for 

the emergy to money ratio of the United States in 1997 

and 2000 (Campbell and Lu, manuscript). 

4.3 Quality Assurance: Reliability of the Data 

and Uncertainty 

One question that should be asked of any scientific 

analysis is, “How do we know that the results reported 

are correct and accurate?” This question is particularly 

relevant for extensive and/or complex analyses that 

draw upon many sources of data. In common usage, the 

word “uncertain” means that something is unknown or 

doubtful; however, in scientific language “uncertainty” 

pertains to the probability structure of the data. For, 

example, a relevant variable such as rainfall can be 
 Environmental Accounting Using Emergy: Minnesota 

56 

expressed as the mean of a normal distribution plus or 

minus its standard deviation. Reporting the probability 

structure of the data always provides more information 

and may in some cases (e.g. risk analysis) allow better 

decisions to be made. However, the time and effort 

required to obtain probability distributions for all data in 

an extensive analysis may not be worth it, if the 

variation is small or for some other reason not 

important. In emergy analysis there is often a great 

diversity in the amount and kind of information 

available on the various numbers used in the analysis. 

For this reason, emergy accounting provides 1st order 

answers to questions on the scale of the analysis. If more 

exact answers are needed to particular questions, the 

scale of the analysis can be reduced by using a smaller 

window in space and time to set the system boundaries. 

As a rule of thumb, emergy analysts aim to achieve 

estimates that are within 10-15% of the actual value of 

the variable used in the analysis. Some numbers will be 

determined with a higher degree of accuracy, but others 

may be less accurate. Because many systems are 

characterized by dominant energy flows that exceed the 

less important flows by an order of magnitude or more, 

a first order estimate of quantities is usually sufficient to 

produce a robust analysis. Many emergy analyses have 

been performed over the past 20 years and numerous 

errors have been found and corrected in these analyses, 

but the results of an emergy analysis are rarely changed 

by subsequent corrections. 

For example, during the development of the West 

Virginia emergy evaluation process many errors were 

found and corrected and the methodology was 

improved. Additional improvements have been made in 

the process of evaluating Minnesota. The history of 

changes in values and indices in these reports is used to 

illustrate the sensitivity of emergy analysis to error 

correction and improvements in methodology (e.g., 

model uncertainty). In addition, the relevant 

characteristics of the different types of data are reported 

and an explanation of the techniques used to check and 

ensure the accuracy of the numbers used in this analysis 

is given. 

 

Two sources of uncertainty are considered (1) 

uncertainty in the numerical values of the quantities 

used and (2) uncertainty in the methods and models used 

to make determinations. Uncertainty in the numerical 

values arises from imprecision of the measuring device, 

scanty or unrepresentative data, and systematic flaws in 

the measuring process (Finkel 1990). Model uncertainty 

arises from difficulties in determining which quantities 

are relevant to the analysis, from the technical methods 

used to determine those quantities, and from the choice 

of surrogates when the needed information is not 

directly available. 

Both environmental and economic data are key 

inputs to emergy analyses. The broad data quality 

objective for these data is that values be determined to 

within 10-15% of the actual value with a high degree of 

confidence. Environmental data is generally determined 

to within 10-15% and meets our data quality objectives 

(Campbell 2003a). For example, pyroheliometers 

measure incident solar radiation with 2-5% accuracy, 

anemometers measure wind speed within about 5% and 

rain gauges record precipitation within about 10%, but 

newer electronic instruments claim ±3% accuracy. 

The Energy Information Administration (EIA) 

provided key data on energy production, consumption 

and movements. The EIA obtains data from survey 

forms, some of which are statistical samples, as well as 

from many additional information sources (14). They 

report both sampling and non-sampling errors in their 

surveys, and have extensive procedures in place to 

guarantee data quality. In some cases, almost all 

participants in a process are counted. In 1997, for 

example, EIA documented 1,850 coal producers who 

reported production, which included all U.S. coal 

mining companies with production of 10,000 short tons 

per year or more. Thus, almost all coal production in the 

U.S. is counted in the EIA estimate and therefore in 

most cases, EIA data would fall within our data quality 

objective of 10-15% accuracy. 

Commodity Flow Survey (CFS) data was critical in 

the development of a revised method for calculating the 

import and export of emergy to and from a state. The 

CFS is a survey conducted every five years by the U.S. 

Census Bureau. Both sampling and non-sampling errors 

are considered, and the reliability of the data is reported 

as the coefficient of variation with its standard error (2). 

The CFS data meets or exceeds our data quality 

objectives for total commodity movements. For 

example, the total dollar value of inbound shipments to 

Minnesota was determined within 3.1% and the tonnage 

value within 6.7%, whereas, the dollar value of 

shipments leaving the State was determined within 4.3% 

and tonnage leaving within 8.9%. Some of the estimated 

movements of individual commodities have higher 

uncertainties, which exceed our 10-15% criteria. Major 
Discussion 

57 

energy or mineral flows are checked using EIA and 

USGS data as well as data from the CFS. In summary, 

we have a high degree of confidence that the material, 

energy, and monetary flows upon which the energy and 

emergy calculations of bulk imports and exports depend 

have been determined within 10 - 15% of their actual 

values. 

The effect of the propagation of errors in the 

estimation of emergy can be estimated as follows. In 

general emergy is the product of two independent 

numbers the estimate of the available energy or exergy 

and the estimate of transformity. If we assume that the 

data quantity objectives specify that these two numbers 

be estimated to within ± 10% of the actual value, the 

propagation of error for two independent variables 

multiplied together would increase the error of the 

estimates from ± 10% to ± 14.1% (89). 

Whenever the opportunity has arisen, we have used 

duplicate data and different calculation methods to 

check the accuracy of estimates. For example, the EIA 

information on coal imports and exports was used to 

check the CFS estimates of these quantities. Petroleum 

imports from the CFS were checked against the 

petroleum imports that were required to meet the 

difference between in-state production and consumption 

obtained from the EIA data. Potential temporal 

anomalies in the economic data were assessed through 

collecting and comparing socioeconomic data for two 

years. Long term averages (10-50 years) were used for 

environmental variables. In this case, the variation is not 

reported because most socioeconomic systems depend 

on the long term average environmental conditions for 

support and development. Trends or variations in the 

long term data would be considered as a part of a 

dynamic energy systems model analysis of the State (not 

performed in this study). The effect of our 

improvements in the methodology for estimating 

imports and exports was discussed in Campbell et al.

(2005). In general, everything that is known to be of 

importance in the system under analysis is included. The 

emergy associated with each item is an indicator of its 

relative importance and determines whether an item is 

included in the analysis. 

The effect of correcting an error in the determination 

of the energy associated with an input is illustrated by 

the recalculation of the geopotential energy of runoff 

absorbed by the West Virginia system. In Campbell et 

al. (2004), this number was incorrectly calculated, 

because the energy used was determined relative to sea 

level rather than the minimum elevation of rivers 

leaving the State. When this number was corrected, the 

energy absorbed changed from 6.59 E+16 J/y to 6.02 

E+16 J/y, a difference of 8.6%. This resulted in a 

change of 2 E+20 sej/y or 2.9% in the emergy absorbed 

by the system and a change of 0.0008 or 2.9% in the 

fraction of use that is locally renewable, which is an 

important index calculated using the renewable emergy 

absorbed. Other calculations that have been refined have 

resulted in a similar or smaller percentage change in the 

energy, emergy, and emdollar values. Even the large 

change in the ratio of imports to exports was based on a 

30% decrease in the difference between emergy 

imported and emergy exported. The major conclusion 

that West Virginia was a net exporter of emergy was 

unchanged by methodological improvements and the 

correction of errors in calculations. 

A second example showing the effect of model 

uncertainty in determining the emergy associated with 

an input can be seen in the evaluation of the 

transformity of electricity from nuclear power which 

appears in this study and in Campbell et al. (2005). 

Cohen et al. (2007) was used to determine the 

transformity of elemental uranium adjusting it using the 

ore grade of uranium mined in the United States. The 

former method had used the determination of the 

transformity of uranium ore from Odum (1996) to 

estimate the emergy of the uranium used in generating 

nuclear electricity. The calculation using the mass of 

uranium oxide, U3O8, to estimate the emergy of uranium 

required was 45% of the original estimate based on the 

ore required. This resulted in the transformity of 

electricity generated from nuclear power declining from 

51,900 sej/J to 48,100 sej/J or 7.3%. The conclusion that 

nuclear power is one of the most efficient processes for 

generating electricity was reinforced by these 

calculations, e.g., electricity from coal requires 162,000 

sej/J, (Odum 1996). 

The transformities and specific emergies by which 

the energy or mass flows are multiplied, respectively, to 

obtain emergy are critical numbers in the analysis. 

Campbell (2003) analyzed five global water budgets, 

and determined that the transformities of global 

hydrological flows, such as rain, evapotranspiration, and 

river flow, were determined within an average standard 

deviation of 5.9± 2.5% of the mean value of the 5 

estimates. These global transformities meet our data 

quality criteria for emergy analysis. Multiple 
 Environmental Accounting Using Emergy: Minnesota 

58 

determinations of transformities are not often available, 

and an accurate estimate of the differences that arise 

from different sources of data and different estimation 

techniques is not available for most items. In a few 

cases, multiple determinations of transformities using 

different methods have been carried out. Odum (1996) 

determined the transformity of coal from its relative 

efficiency in producing electricity and from its 

geological production process. The former method gave 

an estimate of 4.3E+4 sej/J and the latter 3.4 E+4 sej/J. 

The two values are within 12 % of the mean value, 

which may be a rough estimate of the model uncertainty 

in determining transformities. In a similar example, 

Bastianoni et al. (2005) estimated the transformity of 

petroleum from its geological process of formation and 

found it to be 55,400 sej/J compared to 53,000 sej/J 

determined by Odum (1996) by the method of relative 

efficiencies. These two estimates are within 2.5% of the 

mean value. 

We estimated the transformity for each SGTG 

commodity class to determine the emergy in the tonnage 

of each commodity imported. These transformities are 

approximated by averaging known transformities of 

items within the class (without services); however, all 

items in a class are not included in the determination of 

the transformity. In some cases, when a transformity 

was not known for an item in a class, the parent material 

was used as a surrogate for the item’s transformity. The 

use of parent materials results in a minimum estimate of 

the emergy imported and exported in these commodity 

classes. For example, we updated the transformity for 

goods in which steel is the major component by using 

the new transformity for iron determined in this study 

(Cohen et al. 2007). More work is needed to calculate 

additional transformities and to obtain better estimates 

for known transformities using detailed production 

processes, multiple data sets and different calculation 

methods to determine the distribution of values. 

4.4 Future Research and Reports 

The methods described in this report represent a 

significant step forward in our ability to perform 

accurate and comparable emergy analyses of states 

within the United States. Comparable state analyses 

provide the raw material for the analysis of regions, 

which is of particular concern to the USEPA and other 

government agencies that are responsible for the 

management of environmental, social, and economic 

conditions within regional areas, e.g. EPA Region 3, the 

Mid-Atlantic Highlands, The Chesapeake Bay 

watershed. There are emergy analyses for eight 

additional states in various stages of completion as this 

report is being written. The five states of the MidAtlantic region (WV, VA, PA, MD, and DE) are among 

the eight states analyzed and an emergy analysis of this 

region is planned in the future. In addition, the emergy 

accounts for the nine states (MN, WV, MD, VA, PA, 

NJ, DE, RI, CO) are in progress and when completed 

will allow a robust comparative analysis of emergy 

indices. Our current research is focused on the 

development of methods to evaluate environmental 

liabilities, which are needed to complete the emergy 

balance sheet for any enterprise, e.g., nation, state, 

county, business, or institution. Once this work is 

complete, we will have an accounting method to 

determine directly whether any human endeavor is 

sustainable. 
References 

59 

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Campbell, D.E., 2005. Financial Accounting Methods to 

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Campbell, D.E., Lu. H.F. (manuscript). Historical 

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Section 6 

Data Sources 

1) USDA Nutrient Data Laboratory, Food Composition 

and Nutrition. http://www.nal.usda.gov/fnic/cgibin/nut_search.pl 

2) U.S. Census, Commodity Flow Survey for 1997. 

http://www.census.gov/econ/www/cdstate.html 

3) Energy Information Administration: 

http://www.eia.doe.gov 

4) International Trade: 

http://dataweb.usitc.gov/scripts/user_set.asp 

5) Energy Information Administration (EIA) natural 

gas: 

http://www.eia.doe.gov/pub/oil_gas/natural_gas/data_pu

blications/natural_gas_annual/historical/1997/nga_1997.

html 

6) Energy Information Administration coal: 

http://tonto.eia.doe.gov/FTPROOT/coal/058497.pdf 

7)http://garnet.acns.fsu.edu/~tchapin/urp5261/topics/eco

nbase.htm 

8)http://www.nylovesbiz.com/nysdc/Personalincome/stp

cpi9702.pdf 

9) Minnesota Pollution Control Agency, 

http://www.pca.state.mn.us/index.cfm 

10) MN ethanol production, 

http://blogs.citypages.com/blotter/2007/10/boom_boom

_bust.php, http://www.nass.usda.gov/mn/ 

11) http://www.deed.state.mn.us/facts/PDFs/food.pdf 

12) http://www.allbusiness.com/government/3754093-

1.html, 

http://www.netstate.com/economy/mn_economy.htm 

13) http://www.census.gov/statab/ranks/rank29.html 

14) http://www.eia.doe.gov/oss/forms.html#eia-7a 

15) Snow: 

http://www.windows.ucar.edu/tour/link=/earth/Water/w

ater_cycle_climate_change.html 

16) Electricity from uranium, 

http://www.ems.psu.edu/~elsworth/courses/cause2003/e

ngineofindustry/teamnuclear.ppt 

17) Uranium Industry Annual report 2002, DOE/EIA0478(20020) http://www.eia.doe.gov/fuelnuclear.html 

18) U.S. uranium mining 

http://www.eia.doe.gov/cneaf/nuclear/uia/table03.html 

19)http://minerals.usgs.gov/minerals/pubs/commodity/ir

on_ore/stat/ 

20)http://www1.eere.energy.gov/industry/mining/pdfs/c

over.pdf 

21)http://www.epa.gov/ttnecas1/regdata/IPs/Taconite_I

P.pdf 

22)http://minerals.usgs.gov/minerals/pubs/commodity/ir

on_ore/stat/ 

23) http://www.the-innovationgroup.com/ChemProfiles/Sulfur.htm 

24)http://www.netstate.com/states/geography/mn_geogr

aphy.htm 

25) http://www.dnr.state.mn.us/faq/mnfacts/water.html 

26) NASA Surface Meteorology and Solar Energy 

Website. http://eosweb.larc.nasa.gov/cgibin/sse/register.cgi?task=login&next_url=/cgibin/sse/ion-p&page=globe_main.ion&app=sse 

27) National Renewable Energy Laboratory, Renewable 

Resource Data Center. 

http://rredc.nrel.gov/wind/pubs/atlas/tables/1-1T.html 

http://www.met.utah.edu/jhorel/html/wx/climate/windav

g.html 
Data Sources 

65 

28) Global Heat Flow Database of the International Heat 

Flow Commission, 

http://www.heatflow.und.edu/index2.html 

29) Western Regional Climate Center, Average 

precipitation (1900-2000) 

http://www.wrcc.dri.edu/cgi-bin/divplot1_form.pl?2102 

30) MN temperatures. 

http://www.dnr.state.mn.us/faq/mnfacts/climate.html 

31) Center for Natural Resources, UM- Duluth 

http://www.cnr.umn.edu/FR/research/centcoop/mfric/tab

le3a.htm 

32) Evapotranspiration Data, 

http://walkerbranch.ornl.gov/ Estimated from graphs. 

http://www.esd.ornl.gov/programs/WBW/NASA.htm 

33) Net-State.com 

http://www.netstate.com/states/tables/st_size.htm 

34)http://www.grow.arizona.edu/water/temperature/eva

poration.shtml 

35) Precipitation 

http://www.wcc.nrcs.usda.gov/climate/climate-map.html 

36) MN County Areas 

http://www.mnplan.state.mn.us/cgi-bin/datanetweb/ 

landuse?map=n&stats=y&topic=P&area=C 

37) http://www.crh.noaa.gov/ncrfc/?n=2007outlook 

38) Drainage Basin Information 

http://www.pca.state.mn.us/water/basins/index.html 

39) Runoff data 

http://mn.water.usgs.gov/ann-repts/annrpt01/index.htm 

40) Lake Superior Wave Statistics: 

http://www.meds-sdmm.dfoo.gc.ca/alphapro/WAVE/TDCAtlas/TDCProducts.htm 

41) Coastline 

http://www.dnr.state.mn.us/waters/lakesuperior/feis/part

3.html 

42) Flow of the St. Croix River 

http://mn.water.usgs.gov/annrepts/annrpt00/05340500.2000.sw.pdf 

43) Elevation at Danbury, WI., 

http://water.usgs.gov/pubs/wri/wri934076/stations/0533

3500.html 

44) Elevation at Reno, MN 

http://download.geocomm.com/download.php 

45) National Atmospheric Deposition Program/NTN 

http://nadp.sws.uiuc.edu/ 

46) Ag Census 1997, Crop amounts. Table #1, #42. 

http://www.nass.usda.gov/census/census97/volume1/ac9

7-mn.pdf 

47) Ag Census 1997. Pounds/bushel for various crops. 

Appendix F. 

http://www.nass.usda.gov/census/census97/volume1/ac9

7-mn.pdf 

48) Nutrient Data Laboratory 

http://www.nal.usda.gov/fnic/foodcomp/index.html 

49) http://www.nass.usda.gov/census/index1997.htm 

50) http://www.unicamp.br/fea/ortega/creta/emergy.htm 

51) Ag Census 2001 http://www.nass.usda.gov/mn/ 

52)http://jan.mannlib.cornell.edu/reports/nassr/livestock/

pls-bb/2000/lstk1200.pdf 

53) Energy Information Administration, Total 

Electricity Production (1997) 

http://www.eia.doe.gov/cneaf/electricity/epa/generation

_state.xls 

54) http://www.engineeringtoolbox.com/wood-biomasscombustion-heat-9_440.html 

http://mb-soft.com/juca/print/311.html 

55) Forest growth 

http://files.dnr.state.mn.us/forestry/um/2004mn_forest_r

esources.pdf 

http://www.dnr.state.mn.us/forestry/um/index.html 

56) U.S. Geological Survey, Ground Water Used (1995) 

http://water.usgs.gov/watuse/pdf1995/pdf/summary.pdf 

57)Water Quality http://mn.water.usgs.gov/annrepts/annrpt00/40000001.2000.wq.pdf 
 Environmental Accounting Using Emergy: Minnesota 

66 

58) Municipal Solid Waste Generation and Disposal 

http://www.pca.state.mn.us/programs/indicators/iom0201.html 

59) EIA, Coal Consumption, 

http://www.eia.doe.gov/cneaf/coal/cia/html/t67p01p1.ht

ml 

60) EIA, Natural Gas, 

http://www.eia.doe.gov/pub/oil_gas/natural_gas/data_pu

blications/natural_gas_annual/current/pdf/table_049.pdf 

61) EIA, Petroleum 

http://www.eia.doe.gov/emeu/states/sep_use/pet/use_pet

_mn.html 

62) EIA, Electricity Production 

http://www.eia.doe.gov/cneaf/electricity/epa/generation

_state.xls 

63) EIA, Electricity Consumption. 

http://www.eia.doe.gov/cneaf/electricity/st_profiles/sept

05mn.xls 

64) http://www.eia.doe.gov/cneaf/nuclear/ 

page/at_a_glance/states/statesmn.html 

65) U.S.G.S. Mineral Yearbook 

http://minerals.usgs.gov/minerals/pubs/state/mn.html 

66) Wind Erosion, 

http://www.nrcs.usda.gov/technical/NRI/1997/summary

_report/table11.html 

67)Water Erosion, 

http://www.nrcs.usda.gov/technical/NRI/1997/summary

_report/table10.html 

68) Natural Resources Conservation Service, 

http://www.mn.nrcs.usda.gov/technical/nri/tables/82-

97lcu_basin.htm 

69) http://server.admin.state.mn.us/mm/ 

indicator.html?Id=60&G=39&CI=60 

70) Minnesota Department of Trade and Economic 

Development, http://www.dted.state.mn.us/04x00f.asp 

71) Uranium price 

http://www.uranium.info/prices/longterm.html 

72) 1997 Economic Census: Summary Statistics for 

Minnesota, 

http://www.census.gov/epcd/ec97/mn/MN000.HTM 

73) U.S. Statistical Abstract 2002, 

http://www.census.gov/compendia/statab/past_years.ht

ml 

74) IRS, http://www.irs.gov/pub/irs-soi/00db06co.xls, 

http://www.census.gov/population/censusdata/90den_stc

o.txt 

75) 1997 Economic Census: Summary General Statistics 

http://www.census.gov/epcd/ec97/wv/WV000.HTM 

Summary Statistics for the U.S., 

http://www.census.gov/epcd/ec97/us/US000.HTM 

By industry, 

http://www.census.gov/epcd/ec97/industry/E3331.HTM 

Tables for Minnesota, 

http://www.census.gov/govs/apes/96fedst.txt, 

http://www.census.gov/govs/apes/97stlmn.txt 

76) IRS, http://www.irs.gov/pub/irs-soi/00db06co.xls 

77) Estimate from Minnesota DNR. 

78) Water Quality for Minnesota's Water Basins, 

http://www.pca.state.mn.us/water/groundwater/gwmap/

basins2.pdf 

79) Lake Superior Volume/Shoreline, 

http://www.glerl.noaa.gov/pr/ourlakes/lakes.html 

80) Electrical Conductivity, Lake Superior, 

http://wow.nrri.umn.edu/wow/under/parameters/conduct

ivity.html 

81) Taconite Reserves, 

http://www.taconite.org/pdfs/factsheet4.pdf 

82) Twin cities Aggregate Resources 

http://www.dnr.state.mn.us/lands_minerals/metroaggreg

ate.html 

83) Aggregate maps 

http://www.dnr.state.mn.us/lands_minerals/aggregate_m

aps/index.html 

84) Cu, NI, Pt, Assay 

http://www.prnewswire.co.uk/cgi/news/release?id=9435

2 
Data Sources 

67 

85) Peat 

http://www.lmic.state.mn.us/chouse/metadata/peatmaps.

html 

86) U.S. Census Bureau, Population Statistics, 

http://quickfacts.census.gov/qfd/states/27000.html 

87) Bureau of Economic Analysis, State GSP, 

http://www.bea.gov/bea/regional/gsp/ 

88) http://mup.asu.edu/research2006.pdf 

89) Propagation of error. 

http://www.chem.usu.edu/~sbialkow/Classes/3600/Over

heads/Propagation/Prop.html 
 Environmental Accounting Using Emergy: Minnesota 

68 

Section 7 

Appendix A

Primary Symbols of the Energy Systems Language 
Appendix A 

69 

Energy circuit A pathway whose flow is proportional to the storage or source

upstream.

Source A forcing function or outside source of energy delivering forces 

according to a program controlled from outside.

Tank A compartment or state variable within the system storing a quantity 

as the balance of inflows and outflows.

Heat sink Dispersion of potential energy into heat accompanies all real 

transformation processes and storages. This energy is no longer usable by

the system.

Interaction Interactive intersection of two pathways coupled to produce an 

outflow in proportion to a function of both; a work gate.

Consumer An autocatalyticunit that transforms energy, stores it and feeds 

it back to improve inflow.

Producer Unit that collects and transforms low-quality energy under the control 

of high quality flows.

Box Miscellaneous symbol to use for whatever unit or function is needed.

Switching Action A symbol that indicates one or more switching actions controlled

by a logic program.

Figure A1. Primary symbols of the Energy Systems Language.
 Environmental Accounting Using Emergy: Minnesota 

70 

Appendix B 

Sources, Adjustment, and Calculation of Transformities 
Appendix B 

71 

B1. Information Sources For The Emergy Per Unit Values Used In This Report. 

The note number links the emergy per unit values listed in this table to the values used in Tables 4-8. The emergy 

per unit values used in Table B1.1 are given to three significant figures and shown for the 9.26 and 15.83 E+24 sej/y 

baselines. Values are transformities with units of sej/J except where other units are noted. For example where emergy 

per unit mass is given a (g) for mass is noted next to the item and the units are sej/g. The emergy per unit of 

education level is sej per individual and the emergy to dollar ratio (sej/$) is used for services. Table B3.1 gives the 

factors used to convert one baseline to another. The 9.44 baseline was used by Odum (1996) and was revised to the 

9.26 baseline by Campbell (2000a). The 9.44 values are not reported, because this baseline should no longer be used. 

The 15.83 baseline values are reported because some emergy researchers have been using this baseline, which was 

reported in Folio #2 (Odum 2000). All numbers given in the text of this report have been converted to the 9.26E+24 

sej/y baseline by multiplying the number reported in the original source by the appropriate factor. 

Table B1.1 The values and sources for transformities and specific emergies used in this report. 

Note Item (per J unless noted) 

Source of transformity or specific 

emergy calculation 

Emergy/unit 

9.26 

Emergy/unit

 15.83 

1 Incident solar radiation (by definition) 1 1

2 Wind - Odum (1996), p. 309 1470 2.51E+03

3 Earth Cycle Odum (1996), p. 309 33700 5.76E+04

4 Rain, chemical potential Odum (1996) Campbell (2003a) 18100 3.12E+04

5 Evapotranspiration, Odum (1996) Campbell (2003a) 28100 4.80E+04

6 Rain, geo-potential, land Odum (1996), p. 309 10300 1.76E+04

7 Snow, geo-potential, land This study 101000 1.73E+05

8 Rain, geo-potential runoff Odum (1996) (errata) 27200 4.66E+04

9 Snow, geo-potential runoff This study 101000 1.73E+05

10 Rivers, chemical pot. Odum (1996), Campbell (2003a) 50100 8.13E+04

11 Rivers, geo-potential Odum (1996), p. 43 27200 4.66E+04

12 Evapotranspiration Campbell (2003a) 28100 4.81E+04

13 Ammonia fertilizer (g) Odum (1996) 3.73E+09 6.37E+09

13 Ammonia, global (g) Campbell (2003a) 1.39E+09 2.37E+9

13 NO, NO2, NO3 (g) Campbell (2003b) 6.84E+09 1.17E+10

14 Sulfur, S (g) This study 1.58E+11 2.70E+11

15 Chlorine, Cl ̄ (g) This study 1.31E+10 2.24E+10

16 Agricultural Products 

A weighted average of: 

Brandt-Williams (2002) 

See B3 #7. 

variable variable

17 Livestock Odum et al. (1998) 3.36E+06 

 Beef cattle See B3 #7. 9.48E+05 

18 Hydroelectricity Odum (1996), p. 186 120258 2.06E+05

19 Net Timber Growth Tilley (1999), p.150 20600 3.52E+04

20 Timber Harvest Tilley (1999) 68700 1.17E+05

21 Ground Water Odum et al. (1998a) 159000 2.72E+05

22 Solid Waste (g) Brown & Buranakarn (2000) 6.28E+09 1.07E+10

23 Coal Odum (1996), p. 310 39200 6.71E+04

24 Natural Gas Bastianoni et al. (2005) 43500 7.44E+04

25 Crude Oil Bastianoni et al. (2005) 54200 9.27E+04

26 Electricity Odum (1996), p. 305& 311 170400 2.91E+05
 Environmental Accounting Using Emergy: Minnesota 

72 

Note Item (per J unless noted) 

Source of transformity or specific 

emergy calculation 

Emergy/unit 

9.26 

Emergy/unit

 15.83 

27 Iron Ore (g) This study, 20% Fe 3.51E+9 6.00E+09

28 Sand and Gravel (g) Campbell et al. (2005a) 1.31E+09 2.24E+09

32 Limestone (g) Odum (1996) 9.81E+08 1.68E+09

33 Dolomite This Study 1.98E+07 3.38E+07

33 Dolomite (g) This Study 1.08E+10 1.85E+10

34 Peat (g) Odum (1996) Tab. 5.4 3.89E+08 6.65E+08

34 Peat Odum (1996) Tab. 5.4 1.86E+04 3.19E+04

35 Erosion, topsoil Odum (1996) 72600 1.24E+0

37 Nuclear Electricity This Study. 4.81E+04 8.22E+4

37 Uranium (g) Cohen et al. (2007) 5.49E+11 9.39E+11

38 Petroleum fuels Odum (1996) 64100 1.10E+05

39 Aluminum ore, bauxite, Odum (1996) 1.47E+07 2.52E+07

40 Steel (g) This Study 1.47E+10 2.52E+10

49 Forest Biomass Campbell et al. (2005a) 28200 4.82E+04

53 People (per individual) Odum (1988, 1996) 

 Preschool (ind.) 3.E+16 5.70E+16

 School (ind.) 9.E+16 1.58E+17

 College Grad (ind.) 3.E+17 4.70E+17

 Post-College (ind.) 1.E+18 2.20E+18

 Elderly (65+) (ind.) Campbell et al. (2005a) 1.69E+17 2.89E+17

 Public Status (ind.) 4.E+18 6.59E+18

 Legacy (ind.) 8.E+18 1.32E+19

NA Net Prod. Tilley (1999) p.150 10800 1.84E+04

NA Aluminum (g) Brown & Buranakarn (2000) 1.23E+10 2.10E+10

B2. Estimation of Transformities for the SCTG Commodity Classes. Transformities and specific 

emergies for each SCTG commodity classes were determined by averaging items within the class, for which 

transformities were known. For classes where no transformities were available the transformity of the raw 

materials was used as a first order estimate. Transformities for the SCTG commodity class codes are given 

below as estimated from the transformities of the items listed. See Appendix D Table D1.1 for a definition of 

the items represented by the SCTG Class Code numbers. Emergy per unit is relative to the 9.26 baseline. 

Table B2.1 Transformities and Specific Emergies for the SCTG Commodity Classes. 

 Transformity Spec. Em.

Code Items in Class Average se/J sej/g 

1 Avg. poultry and cattle, Odum et al. (1987) Brandt-Williams (2001) 439,300 

2 Avg. wheat, grain corn, rice, oats, sorghum, Odum et al. (1987) Brandt 

Williams (2001) 181,800 

3 Avg. soybeans, cotton, pecans, cabbages, oranges, etc. Odum et al. (1987) 

Brandt-Williams (2001) 233,400 

4 Forage Ulgiati et al. (1994) Cornstalks & wool Odum (1996), eggs BrandtWilliams (2001) 1.22 E6 

5 Meat ,veal, mutton, shrimp, Odum (1996). 3.27 E6 

 
Appendix B 

73 

Transformity Spec. Em.

Code Items in Class Average sej/J sej/g 

6 use flour (wheat + energy to process) 18,1800 

7 Sugar, palm oil and cacao from Odum et al. (1986b), milk Brandt-Williams 

(2001). 1.12 E6 

8 Use ethanol and avg. 10% alcohol by volume for beer and wine,, Odum 

(1996). 58,900 

9 Use tobacco, Scatena et al. (2002). 650,000 

10 Use limestone Odum (1996). 9.81 E8

11 Use sand, this study. 1.31 E9 

12 Use granite rocks Odum (1996). 4.91 E8

13 Use clay, Odum (1996). 1.96 E9 

14 Use ore rocks, iron, alumina, copper, nickel, zinc Odum (1996). 2.71 E9 

15 Use coal Odum (1996). 39,200 

17 Use crude oil, petroleum fuels Odum (1996). 64,700 

18 Use petroleum fuels Odum (1996). 64,700 

19 Use fuel oil Odum (1996) 64,700 

20 Use hydrated lime, caustic soda, diatomite, and sulfuric acid Odum et al.

(2000b) 

 2.75 E9 

21 Pharmaceutical and biological products (use chemicals as feedstock) 2.75 E9

22 Fertilizer from Brandt-Williams (2001) and Odum (1996). 2.99 E9 

23 Insecticide, paint and glue (Brown and Arding 1991cited in Buranakarn 

(1998). 

 9.90 E9 

24 (plastic, tires, etc.,) Odum et al. (1987) 2.71 E9 

25 Use avg. Softwood and hardwood logs Odum (1996). 19,600 

26 Use wood chips, lumber, particle board, plywood, Buranakarn (1998). 1.49 E 9 

27 (Use avg. Wood pulp, paper, paper board), Tilley (1999) 139,800 

28 Bags, packing, toilet paper, envelopes, wallpaper, Tilley (1999) 167,400 

29 Paper from Tilley (1999) Ink assumed similar to other chemical preparations. 4.95 E9 

30 Use avg. Of textiles and leather Odum et al. (1987) 7.18 E6 

31 Use avg. Ceramics, glass flat and float, brick, concrete, Buranakarn (1998) 3.09 E9 

32 Avg. Iron , steel, copper, aluminum Buranakarn (1998), Al 1/2 weight in avg. 5.91 E9 

33 Assume articles of metal have similar transformities to the unformed metal. 5.91 E9

34 Machinery non electrical, Odum et. al. (1987), updated Cohen et al. (2007. 1.47E+10

35 Assume the transformity for machinery applies Odum et. al. (1987), updated 

Cohen et al. (2007). 

 1.47E+10

36 Assume the transformity for machinery applies Odum et. al. (1987), updated 

Cohen et al. (2007). 

 1.47E+10

37 Assume the transformity for machinery applies Odum et. al. (1987), updated 

Cohen et al. (2007). 

 1.47E+10

38 Assume the transformity for machinery applies Odum et. al. (1987), updated 

Cohen et al. (2007). 

 1.47E+10

39 Household furniture, lamps, mattresses use hardwood, Buranakarn (1998) 2.89 E9 

40 Miscellaneous manufactured goods 1.61 E9

41 Tire waste, wood waste, slag. Buranakarn (1998) 2.16 E9 

43 Corn and steel for groceries and hardware 6.32 E9
 Environmental Accounting Using Emergy: Minnesota 

74 

B3. Calculation of New or Revised Transformities. In all cases transformity is determined by dividing 

the emergy (sej or sej/y) required for product or service by the energy (J or J/y) in the product or service. 

Table. B3.1 Transformity of Snow 

Average precipitation on land from 5 global water budgets in Campbell (2003a) was : 

 m3 y

-1 

1 Oki (1999) 1.15E+14 

2 Peixoto (1993) 9.90E+13 

3 Baumgartner and Reichel (1975) 1.11E+14 

4 L'vovich (1974) 1.10E+14 

5 Odum 1996) 1.05E+14 

Average precipitation on land from the 5 global water budgets 1.08E+14 

The transformity of snow was estimated from the mass fraction of total 

precipitation assuming that all global precipitation is required for the ann

snowfall. 

Average snow fall in a year 1.10E+13 

Average residence time of snow (15) 120 days 

Snow as a fraction of total precipitation (15) 1.02E-01 

 

Transformity of geopotential energy of precipitation on land is 10,300 sej/J 

Transformity of geopotential energy delivered as snow 1.01E+05 sej/J 

The dynamics of snow pack formation and its residence time could be used to make an alternate 

determination of the transformity of snow, but this was not done in this study. 

B3.2 Transformity of Dolomite 

(1)Assume the production rate of dolomite is proportional to abundance. 

(2) The production ratio of limestone to dolomite in the U.S. is 10/1, we assume this rate holds for the entire 

world, and therefore, we can estimate the crustal abundance of dolomite. We also assumed that despite the 

fact that dolomite production has not been observed, that it has been produced in the global sedimentary 

cycle over the last cycle of mineral formation (Odum 1996). 

Global Sedimentary Cycle Material Flux 9.36E+15 g/yr 

The proportion of the continental area that is limestone is 18%, therefore, under the assumption stated

proportion of continental area of dolomite is 1.8%. 

Limestone flux 1.68E+15 g/yr 

Dolomite flux 1.68E+14 g/yr 

Fraction mass flux 1.80E-02 

Gibbs free energy of the weathered limestone (Odum 1996) 50 J/g 

Calculation #1:

Solar transformity (sej/J)=(fraction*baseline)/(Gibbs free energy/g*flux in g/yr) Odum (1996) p. 46 

Solar Transformity of Dolomite 1.98E+07 sej/J 
Appendix B 

75 

Calculation #2:

Specific emergy of dolomite =(0.981E9 sej/g) / (Gibbs Free 

Energy) Odum (1996) p. 46 

1.96E+07 sej/J 

0.981E+9 sej/g is the emergy/mass of global sedimentary cycle on the 9.26 baseline 

(Campbell 2000a) 

Calculation #3: 

sej/g based on limestone as 9.81E+08 sej/g 

Mass ratio limestone/dolomite 

Fraction total limestone dolomite 0.09090909

Specific emergy dolomite 1.08E+10 sej/g 

 

B3.3 Updated Transformity for Electricity from Nuclear Power 

Cohen et al. (2007) gives the specific emergy of uranium as 1.6E+11sej/g = 9.36E+10 sej/g 

on the 9.26 baseline. Items in the table are from Lapp (1991) quoted in Odum (1996) on p.154. 

 Item sej/y 

Emergy from the economy 9.128E+23 

Emergy from the environment 4.90E+22 

Emergy from uranium 6.37E+22 

Total Emergy 1.03E+24 

On 9.26 baseline 1.01E+24 

Joules of electricity generated 2.09E+19 

 

Transformity of nuclear electricity 4.81E+04 sej/J 

Parameters 

kWh per kg U fuel (16) 50000 

kWh per year generated, Lapp (1991) 5.80E+12 

tons U in fuel used (calculated) 1.16E+05 

tons ore used (calculated) 7.63E+07 

Specific Emergy U.S. Uranium* 5.49E+11 

* Specific Emergy from Cohen et al. (2007) is 1.6E+11 sej/g U adjusted to the 9.26 baseline is 9.36E+10 sej/g 

U., adjusting for stoichiometry the average transformity of U3O8 is 7.94E+10 sej/g. Cohen’s Ore Grade Cutoff 

(OGC) is 0.026 % U and the percent U in U.S. mined ore is 0.152 giving an enrichment of 4.974. 

Average uranium produced in the U.S. Mine n=10 Data Source (17)

Million lbs U3O8 3.49 

1000 MT U 1.35 

 
 Environmental Accounting Using Emergy: Minnesota 

76 

 

Concentrate n=10 Data Source (17)

Million lbs U3O8 4.26 

1000 MT U 1.64 

Fraction U in U3O8 from data above 0.850703226 calculated 

Stochiometry 0.847980998 calculated 

Oxygen, MW 16 128 

Uranium, MW 238 714 

For $30 per pound U, all sources (mining + leaching) 

Average ore grade percent U3O8 0.17928 Data source (18)

 

B3.4 Transformity for Taconite 

Energy use for Iron Extraction (20). 

 1992 1997 Transformity 1992 1997 

Year 1992 1997 Joules Joules sej/J sej sej 

Iron Ore Produced (1000 tons) 61288.5 69255.1 

Energy Requirements for Extraction 

Fuel Oil (1000 bbl.) 669.6 910.7 4.30E+15 5.85E+15 64100 2.76E+20 .75E+20

Natural Gas (billion cu. Ft.) 29.7 34.3 3.27E+16 3.77E+16 40000 1.31E+21 .51E+21

Gasoline (1000 bbl.) 26.2 33.3 1.51E+11 5.03E+12 64100 9.67E+15 

Electricity Purchased (million kWh) 7300 6200 2.63E+16 2.23E+16 170400 4.48E+21 

Total 6.06E+21 .69E+21

Specific Emergy Added (sej/g) 1.09E+08 .05E+07

Average Specific Emergy Added (sej/g) 
Appendix B 

77 

Production Costs 1997 (21) 

 $ sej/y 

Total $ Costs and Emergy of Service 1.68E+09 4.13E+21

 

Total Capital Expenditures 9.10E+07 

Buildings 8.14E+07 2.08E+20

Mineral Exploration 9.42E+06 2.41E+19

Mineral Land Rights 1.06E+05 2.71E+17

 

Total Labor 5.42E+08 

Payroll 3.94E+08 1.01E+21

Fringe 1.48E+08 3.78E+20

 

Total Cost of Supplies 1.04E+09 

Minerals and Machinery 6.04E+08 1.55E+21

Fuels 1.17E+08 3.00E+20

Electricity 2.59E+08 6.63E+20

 

Avg. service (sej /g) 6.56E+07 

1997 emergy/$ (sej/$) 2.56E+12 

Specific Emergy of Taconite Production 

sej/g 

Sedimentary Iron Ore (22) Cohen et al. (2007) (20% Fe) 3.51E+09

Emergy for Extraction and Processing 9.97E+07

Emergy in Services 6.56E+07

Emergy Per Gram of Taconite without Services 3.61E+09

Emergy per Gram Taconite with Services 3.68E+09

Emergy Magnification Factor For Extraction And Beneficiation 22.23

Emergy Magnification Factor Compared to 63% Fe Iron Ore 47.07

Specific Emergy of Taconite Production for Comparison 

 sej/g 

Sedimentary Iron Ore Odum (1996) 9.81E+08

Emergy for Extraction and Processing 9.97E+07

Emergy in Services 6.56E+07

Emergy per Gram Taconite 1.15E+09

Emergy Magnification Factor For Extraction And Beneficiation 6.93

Emergy Magnification Factor Compared to 63% Fe Iron Ore 13.15

Nature’s work in making ores with high iron concentration equivalent to that in taconite 

pellets can be estimated as follows: The ratio of the fraction of iron in beneficiated pellets 

to ore mined was 3.217 (0.6328/0.1967). Adjusting the specific emergy of iron (Cohen et 

al. 2007) to an ore grade cut-off (OGC) of 63% iron gives a specific emergy of 1.13E+10 

sej/g. The emergy magnification factors for the extraction and beneficiation technologies 

using ore that is 20% iron are given above based on this number. 
 Environmental Accounting Using Emergy: Minnesota 

78 

B3.5 Specific Emergy of Sulfur 

 

Specific Emergy of Sulfur Estimated For Petroleum Refining (23)

Recovered Sulfur in the U.S. in 1999 (1000 Mt) 8220 

76% is from Petroleum Refining (1000 Mt) 6247.2 

Sulfur Recovered from Petroleum Refining (G) 6.25E+12 

Sulfur Production Capacity, U.S. Refineries 1999 (Long Tons) 12125 

Production Capacity (G) 1.23E+13 

Capacity Utilization 50.66% 

Emergy of Refining Average 1993-2004* (Sej/Y) 1.95E+24 

Specific Emergy of Recovered Sulfur (Sej/G) 3.12E+11 

Specific Emergy, if Process Was Run at Capacity (Sej/G) 1.58E+11 

* Bastianoni et al. manuscript, Campbell unpublished data 

Alternative Estimate for the Specific Emergy of Sulfur 

 g/y 

Sulfur Emissions, Volcanoes (Andreas & Kasgnoc 1998) 1.04E+13

Volcanic Extrusion at Surface (Odum 1996) 2.10E+15

Estimate of Sulfur Extruded 1.30E+12

 

Sulfur as a Fraction of Extruded Mass 0.006

Average Upper Crust Conc. S ppm (Rudnick & Gao 

2003) 620

 sej/g 

Specific Emergy of Volcanic Extrusions (Odum 1996) 4.41E+09

Specific Emergy Sulfur Based on Mass Concentration 7.92E+11
Appendix B 

79 

B3.6 Specific Emergy of the Chlorine Ion. 

Adapted from the Calculation for Caustic Soda in Odum et al. (2000b) p. 263. All numbers converted to the 

9.26 E+24 sej/y baseline 

 Solar Emergy Raw Units Emergy/Mass 

Note Item (sej/g) (J, g, $) (sej/g) 

1 Salt (NaCl) 1.43E+09 g 

2 Water in Steam 7.91E+05 g 

3 Fuel 3.69E+09 J 

4 Capital and Labor 5.39E+08 $ 

5 50% Caustic Soda 5.66E+09 g 5.67E+09 

Notes: 

1 Salt. Amount necessary from stochiometric relation = 1.46 g/g NaOH. 

 Emergy/gram NaCl = 9.81 E8 sej/g (Odum 1996) 

 Emergy = (1.46 g/g NaOH)*(9.81 E8 sej/g) = 1.43 E9 sej/g NaOH 

2 Water in steam. 8.85 g/g NaOH produced (Wehle, 1974, p. 197). Gibbs free 

 energy of water = 4.94 J/g. Transformity (rain) = 1.81 E4 sej/J (Odum 1996) 

 Emergy = (8.85 g)*(4.94 J/g)*(1.81 E4 sej/J) = 791313.9 

3 Fuel for Electrolysis. 7.29 E7 BTU/ton NaOH (Wehle, 1974, p. 197) 

 Transformity of fuel (natural gas) = 43500 sej/J 

 Emergy = (7.29 E7 BTU/ton)*(1 ton/9.07 E5 g)*(1054.8 J/BTU)*(43500 sej/J) 

4 Labor & Service Purchased Goods. Price of Caustic Soda: $208/ton (4th quarter 2000) 

 Emergy to money ratio in 2000: 2.35E12 sej/$ 

 Emergy = ($208/ton)*(1 ton/9.07 E5 g)*(2.35 E12) = 5.39 E8 

5 50% Caustic Soda. Sum of Inputs 1-4. 

 

 Molar Conversion from NaOH to Cl2: 

 1g NaOH = 0.02439 mol 

 .02439 mol Cl ---> 0.0122 mol Cl2 Specific emergy for Cl2: 

 .0122 mol Cl2 = 0.8662 g Cl2 6.55E+09 sej/g 

Transformity for Cl ̄: Use the reaction in water, assuming deposition is due to rain: 

2H2O+Cl2 → HClO+H3O+

+ Cl ̄ 

0.0122 mol Cl2 → 0.0122 mol Cl ̄ 

0.0122 mol Cl ̄ → 0.4331 g Cl ̄ Specific Emergy for Cl ̄: 

 1.31E+10 sej/g 
 Environmental Accounting Using Emergy: Minnesota 

80 

B3.7 Revised Transformities for Agricultural Products Including Some New Determinations for Minnesota.

Transformities for the agricultural products given in Brandt-Williams (2002) and Odum et al. (1998) were 

recalculated with and without services using the 28100 sej/J as the transformity for evapotranspiration as in 

Campbell et al. (2005) and using new values for the emergy to money ratio of the United States (Campbell and Lu 

manuscript). The transformities without services included were used to determine the emergy of agricultural 

commodity flows. All transformities are on the 9.26 E+24 sej/y planetary baseline. Table numbers and year of 

study refer to Brandt-Williams (2001, revised 2002). 

Key to Transformities Used 

Item Source 

Evapotranspiration Campbell (2003a) 

Topsoil loss Odum 1996 * 0.981 

Fuel Odum 1996 * 0.981 

Electricity Odum 1996 * 0.981 

Potash Odum 1996 * 0.981 

Lime Odum 1996 * 0.981 

Phosphorus 

Brandt-Williams (2001 revised 2002) 

*0.981 

Nitrogen 

Brandt-Williams (2001 revised 2002) 

*0.981 

Pesticides Brown and Arding (1991) 

Labor Unskilled, Odum 1996 * 0.981 

Services Campbell and Lu (manuscript) 

 

B3.7.1 Revised Transformities for Florida and Arkansas Crops and Livestock. 

Modified from Brandt-Williams (2002) 

Beef cattle (2 per ha) 

Table 2 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit

sej/(J, g, $)

1981 Evapotranspiration 1.15E+11 J 28,100 

 Topsoil loss 6.33E+07 J 72,398 

 Fuel 1.20E+10 J 64,746 

 Potash 6.84E+04 g 1.707E+09 

 Lime 5.52E+05 g 9.81E+08 

 Phosphorus 7.63E+03 g 2.158E+10 

 Nitrogen 3.09E+04 g 2.364E+10 

 Pesticides 1.08E+04 g 1.452E+10 

 Labor 8.40E+07 J 4.41E+06 

 Services 3.68E+02 $ 4.97E+12 

 Total w/o services 5.72E+15 sej 

 Total w services 7.92E+15 sej 

 

 Yield dry wt. 1.84E+05 g 

 Yield energy 1.04E+10 J 

 Specific emergy 3.11E+10 sej/g 

 Transformity w/o services 5.50E+05 sej/J 

 Transformity with services 7.62E+05 sej/J 
Appendix B 

81 

Modified from Brandt-Williams (2002) 

Eggs per 100 hens per year 

Table 4 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit

sej/(J, g, $)

1988 Evapotranspiration 6.05E+10 J 28,100

 Topsoil loss 4.25E+09 J 72,398

 Fuel 4.89E+10 J 64,746

 Electricity 3.06E+09 J 170,694

 Potash 1.57E+05 g 1.71E+09

 Lime 5.25E+05 g 9.81E+08

 Phosphorus 2.95E+04 g 2.16E+10

 Nitrogen 7.99E+04 g 2.36E+10

 Pesticides 0.00E+00 g 1.45E+10

 Labor 1.56E+10 J 4.41E+06

 Services 1.21E+03 $ 3.17E+12

 Total w/o services 9.00E+15 sej 

 Total w services 8.17E+16 sej 

 

 Yield dry wt. 8.55E+05 g 

 Yield energy 2.08E+10 J 

 Specific emergy 1.05E+10 sej/g 

 Transformity w/o services 4.33E+05 sej/J 

 Transformity with services 3.93E+06 sej/J 

 

Modified from Brandt-Williams (2002) 

Milk per cow per year 

Table 16 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit

sej/(J, g, $)

1980 Evapotranspiration 1.51E+11 J 28,100

 Topsoil loss 7.69E+09 J 72,398

 Fuel 1.75E+10 J 64,746

 Electricity 5.02E+09 J 170,694

 Potash 1.49E+05 g 1.71E+09

 Lime 9.28E+05 g 9.81E+08

 Phosphorus 3.35E+04 g 2.16E+10

 Nitrogen 5.07E+04 g 2.36E+10

 Pesticides 2.33E+03 g 1.45E+10

 Labor 1.28E+08 J 4.41E+06

 Services 2.19E+03 $ 5.54E+12

 Total w/o services 9.91E+15 sej 

 Total w services 2.26E+16 sej 

 

 Yield dry wt. 7.63E+05 g 

 Yield energy 1.98E+10 J 

 Specific emergy 1.30E+10 sej/g 

 Transformity w/o services 5.01E+05 sej/J 

 Transformity with services 1.14E+06 sej/J 

 
 Environmental Accounting Using Emergy: Minnesota 

82 

Odum et al. (1998) Arkansas 

Poultry (50,000 per ha, 3 months) 

1977 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

 Evapotranspiration 1.48E+10 J 28,100

 Topsoil loss 9.95E+08 J 72,398

 Fuel 2.66E+11 J 64,746

 Machinery (oil equivalent) 1.64E+10 J 64,746

 Ration corn 1.35E+12 J 66,123

 Ration soybeans 5.82E+11 J 2.54E+05

 Electricity 2.70E+10 J 1.71E+05

 Groundwater 1.79E+10 J 1.67E+05

 Buildings (oil equivalent) 2.98E+11 J 6.47E+04

 Services 1977$ 8.02E+04 $ 7.23E+12

 Total w/o services 2.63E+17 sej 

 Total w services 8.63E+17 sej 

 

 Yield dry wt. 9.00E+07 g 

 Yield energy 8.02E+11 J 

 Specific emergy 2.93E+09 sej/g 

 Transformity w/o services 3.28E+05 sej/J 

 Transformity with services 1.08E+06 sej/J 

 

Odum et al. (1998) Arkansas 

Wheat 

 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

 Evapotranspiration 1.48E+10 J 28,100

 topsoil loss 9.92E+08 J 72,398

 fuel 4.98E+10 J 64,746

 Machinery (oil equivalent) 1.32E+09 J 64,746

 Pesticide (oil equivalent) 1.79E+08 J 64,746

 Phosphate 3.90E+05 J 1.00E+07

 Nitrogen 1.95E+08 J 1.90E+06

 seed (oil equivalent) 9.11E+08 J 6.47E+04

 electricity 1.79E+09 J 1.71E+05

 groundwater 1.76E+10 J 1.67E+05

 services 1977$ 2.60E+02 $ 7.23E+12

 Total w/o services 7.48E+15 sej 

 Total w services 9.36E+15 sej 

 

 Yield dry wt. 2.60E+06 g 

 Yield energy 3.81E+10 J 

 Specific emergy 2.88E+09 sej/g 

 Transformity w/o services 1.96E+05 sej/J 

 Transformity with services 2.46E+05 sej/J 

 
Appendix B 

83 

Odum et al. (1998) 

Rice 

 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit

sej/(J, g, $)

 Evapotranspiration 1.48E+10 J 28,100

 topsoil loss 9.92E+08 J 72,398

 fuel 1.35E+10 J 64,746

 Machinery (oil equivalent) 2.87E+08 J 64,746

 Pesticide (oil equivalent) 3.97E+09 J 64,746

 Nitrogen 2.92E+08 J 1.86E+06

 Potassium 2.36E+07 J 2.94E+06

 seed (oil equivalent) 2.63E+09 J 6.47E+04

 electricity 3.78E+09 J 1.71E+05

 groundwater 3.72E+10 J 1.57E+05

 services 1977$ 7.30E+02 $ 7.23E+12

 Total w/o services 8.91E+15 sej 

 Total w services 1.42E+16 sej 

 

 Yield dry wt. 4.72E+06 g 

 Yield energy 6.95E+10 J 

 Specific emergy 1.89E+09 sej/g 

 Transformity w/o services 1.28E+05 sej/J 

 Transformity with services 2.04E+05 sej/J 

 

Odum et al. (1998) 

Corn 

 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit

sej/(J, g, $)

 Evapotranspiration 1.48E+10 J 28,100

 topsoil loss 9.92E+08 J 72,398

 fuel 6.82E+09 J 64,746

 Machinery (oil equivalent) 4.14E+09 J 64,746

 Pesticide (oil equivalent) 9.28E+08 J 64,746

 Nitrogen 2.68E+08 J 1.86E+06

 Potassium 4.00E+07 J 2.94E+06

 seed (oil equivalent) 1.29E+09 J 6.47E+04

 electricity 6.85E+07 J 1.71E+05

 Phosphate 1.81E+07 J 7.70E+06

 services 1977$ 3.53E+02 $ 7.23E+12

 Total w/o services 2.11E+15 sej 

 Total w services 4.66E+15 sej 

 

 Yield dry wt. 3.90E+06 g 

 Yield energy 6.95E+10 J 

 Specific emergy 5.72E+10 sej/g 

 Transformity w/o services 3.03E+04 sej/J 

 Transformity with services 6.71E+04 sej/J 

 
 Environmental Accounting Using Emergy: Minnesota 

84 

Odum et al. (1998) 

Sorghum 

 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit

sej/(J, g, $)

 Evapotranspiration 1.48E+10 J 28,100

 Topsoil loss 9.92E+08 J 72,398

 Fuel 2.99E+09 J 64,746

 Machinery (oil equivalent) 5.27E+08 J 64,746

 Pesticide (oil equivalent) 5.78E+08 J 64,746

 Phosphate 1.18E+06 J 1.00E+07

 Nitrogen 8.20E+07 J 1.90E+06

 Seed (oil equivalent) 1.97E+08 J 6.47E+04

 Potassium 6.31E+05 J 3.00E+06

 Groundwater 1.76E+10 J 1.67E+05

 Services 1977$ 1.47E+02 $ 7.23E+12

 Total w/o services 3.87E+15 sej 

 Total w services 4.93E+15 sej 

 

Yield dry wt. 1.82E+06 g 

Yield energy 3.87E+10 J 

Specific emergy 2.13E+09 sej/g 

Transformity w/o services 1.00E+05 sej/J 

Transformity with services 1.27E+05 sej/J 

 

Modified from Brandt-Williams (2002) 

Corn (grain) 

Table 15 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit

sej/(J, g, $)

1987 Evapotranspiration 6.05E+10 J 28,100

 topsoil loss 4.25E+10 J 72,398

 fuel 8.12E+09 J 64,746

 electricity 7.85E+08 J 170,694

 potash 1.12E+05 g 1.71E+09

 lime 3.73E+05 g 9.81E+08

 phosphorus 2.11E+04 g 2.16E+10

 nitrogen 5.71E+04 g 2.36E+10

 pesticides 1.69E+03 g 1.45E+10

 labor 1.32E+07 J 4.41E+06

 services 4.39E+02 $ 3.17E+12

 Total w/o services 7.82E+15 sej 

 Total w services 9.28E+15 sej 

 

 Yield dry wt. 9.17E+05 g 

 Yield energy 1.81E+10 J 

 Specific emergy 8.53E+09 sej/g 

 Transformity w/o services 4.32E+05 sej/J 

 Transformity with services 5.12E+05 sej/J 

 
Appendix B 

85 

Modified from Brandt-Williams (2002) 

Corn (sweet) 

Table 7 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit

sej/(J, g, $)

1990 Evapotranspiration 6.05E+10 J 28,100

 topsoil loss 2.44E+10 J 72,398

 fuel 1.25E+10 J 64,746

 potash 1.39E+05 g 1.71E+09

 lime 0.00E+00 g 9.81E+08

 phosphorus 3.95E+04 g 2.16E+10

 nitrogen 5.71E+04 g 2.36E+10

 pesticides 1.11E+04 g 1.45E+10

 labor 2.54E+08 J 4.41E+06

 services 7.76E+02 $ 2.88E+12

 Total w/o services 6.88E+15 sej 

 Total w services 1.02E+16 sej 

 

 Yield dry wt. 5.29E+06 g 

 Yield energy 1.04E+11 J 

 Specific emergy 1.30E+09 sej/g 

 Transformity w/o services 6.61E+04 sej/J 

 Transformity with services 9.84E+04 sej/J 

 

Modified from Brandt-Williams (2002) 

Soybeans 

Table 18 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit

sej/(J, g, $)

1989 Evapotranspiration 6.15E+10 J 28,100

 topsoil loss 1.81E+07 J 72,398

 fuel 7.01E+06 J 64,746

 electricity 2.97E+08 J 170,694

 potash 3.73E+04 g 1.71E+09

 lime 3.72E+05 g 9.81E+08

 phosphorus 1.05E+04 g 2.16E+10

 nitrogen 2.38E+03 g 2.36E+10

 pesticides 7.07E+02 g 1.45E+10

 labor 7.34E+06 J 4.41E+06

 services 1.48E+02 $ 2.99E+12

 Total w/o services 2.50E+15 sej 

 Total w services 2.98E+15 sej 

 

 Yield dry wt. 4.04E+05 g 

 Yield energy 9.86E+09 J 

 Specific emergy 6.19E+09 sej/g 

 Transformity w/o services 2.54E+05 sej/J 

 Transformity with services 3.02E+05 sej/J 

 
 Environmental Accounting Using Emergy: Minnesota 

86 

Modified from Brandt-Williams (2002) 

Oats 

Table 17 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1985 Evapotranspiration 6.05E+10 J 28,100 

 topsoil loss 7.69E+09 J 72,398 

 fuel 2.59E+09 J 64,746 

 electricity 0.00E+00 J 170,694 

 potash 9.29E+05 g 1.71E+09 

 lime 0.00E+00 g 9.81E+08 

 phosphorus 1.32E+04 g 2.16E+10

 nitrogen 5.11E+04 g 2.36E+10

 pesticides 0.00E+00 g 1.45E+10

 labor 4.79E+06 J 4.41E+06

 services 1.30E+02 $ 3.51E+12

 Total w/o services 5.50E+15 sej 

 Total w services 5.98E+15 sej 

 

 Yield dry wt. 1.36E+06 g 

 Yield energy 2.72E+10 J 

 Specific emergy 4.05E+09 sej/g 

 Transformity w/o services 2.02E+05 sej/J 

 Transformity with services 2.20E+05 sej/J 

 

Modified from Brandt-Williams (2002) 

Peanuts 

Table 11 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $) 

1987 Evapotranspiration 5.27E+10 J 28,100 

 topsoil loss 7.69E+09 J 72,398 

 fuel 1.01E+10 J 64,746 

 electricity 2.05E+09 J 170,694 

 potash 8.38E+04 g 1.71E+09 

 lime 9.04E+05 g 9.81E+08 

 phosphorus 1.19E+04 g 2.16E+10 

 nitrogen 3.56E+03 g 2.36E+10 

 pesticides 1.52E+03 g 1.45E+10 

 labor 3.00E+07 J 4.41E+06 

 services 6.67E+02 $ 3.17E+12 

 Total w/o services 4.43E+15 sej 

 Total w services 6.68E+15 sej 

 

 Yield dry wt. 2.95E+05 g 

 Yield energy 9.50E+09 J 

 Specific emergy 1.50E+10 sej/g 

 Transformity w/o services 4.67E+05 sej/J 

 Transformity with services 7.04E+05 sej/J 

 
Appendix B 

87 

Modified from Brandt-Williams (2002) 

Cabbages 

 

Table 6 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1989 Evapotranspiration 6.30E+10 J 28,100

 topsoil loss 7.69E+09 J 72,398

 fuel 1.74E+10 J 64,746

 electricity 1.36E+09 J 170,694

 potash 1.86E+05 g 1.71E+09

 lime 5.65E+05 g 9.81E+08

 phosphorus 4.60E+04 g 2.16E+10

 nitrogen 4.75E+04 g 2.36E+10

 pesticides 6.60E+03 g 1.45E+10

 labor 2.05E+08 J 4.41E+06

 services 4.43E+02 $ 2.99E+12

 Total w/o services 6.77E+15 sej 

 Total w services 9.00E+15 sej 

 

 Yield dry wt. 2.31E+06 g 

 Yield energy 4.47E+10 J 

 Specific emergy 2.93E+09 sej/g 

 Transformity w/o services 1.51E+05 sej/J 

 Transformity with services 2.01E+05 sej/J 

 

Modified from Brandt-Williams (2002) 

Potatoes 

Table 12 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1990 Evapotranspiration 5.77E+10 J 28,100

 topsoil loss 7.69E+09 J 72,398

 fuel 1.75E+10 J 64,746

 electricity 1.36E+09 J 170,694

 potash 1.63E+05 g 1.71E+09

 lime 5.65E+05 g 9.81E+08

 phosphorus 3.95E+04 g 2.16E+10

 nitrogen 4.75E+04 g 2.36E+10

 pesticides 3.45E+04 g 1.45E+10

 labor 1.37E+08 J 4.41E+06

 services 1.59E+03 $ 2.88E+12

 Total w/o services 6.85E+15 sej 

 Total w services 1.20E+16 sej 

 

 Yield dry wt. 5.43E+06 g 

 Yield energy 8.55E+10 J 

 Specific emergy 1.26E+09 sej/g 2.22E+09

 Transformity w/o services 8.01E+04 sej/J 

 Transformity with services 1.41E+05 sej/J 
 Environmental Accounting Using Emergy: Minnesota 

88 

Modified from Brandt-Williams (2002) 

Cucumbers 

Table 8 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1990 Evapotranspiration 6.02E+10 J 28,100

 topsoil loss 7.69E+09 J 72,398

 fuel 2.19E+10 J 64,746

 electricity 0.00E+00 J 170,694

 potash 1.49E+05 g 1.71E+09

 lime 5.65E+05 g 9.81E+08

 phosphorus 4.20E+04 g 2.16E+10

 nitrogen 4.75E+04 g 2.36E+10

 pesticides 4.90E+04 g 1.45E+10

 labor 6.41E+08 J 4.41E+06

 services 1.50E+03 $ 2.88E+12

 Total w/o services 7.22E+15 sej 

 Total w services 1.44E+16 sej 

 

 Yield dry wt. 1.33E+07 g 

 Yield energy 2.61E+11 J 

 Specific emergy 5.43E+08 sej/g 

 Transformity w/o services 2.76E+04 sej/J 

 Transformity with services 5.50E+04 sej/J 

 

Modified from Brandt-Williams (2002) 

Green Beans 

Table 9 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1990 Evapotranspiration 5.65E+10 J 28,100

 topsoil loss 7.69E+09 J 72,398

 fuel 1.94E+10 J 64,746

 electricity 1.65E+09 J 170,694

 potash 6.98E+04 g 1.71E+09

 lime 5.65E+05 g 9.81E+08

 phosphorus 1.98E+04 g 2.16E+10

 nitrogen 2.38E+04 g 2.36E+10

 pesticides 1.22E+04 g 1.45E+10

 labor 6.23E+07 J 4.41E+06

 services 1.87E+03 $ 2.88E+12

 Total w/o services 5.52E+15 sej 

 Total w services 1.12E+16 sej 

 

 Yield dry wt. 5.55E+05 g 

 Yield energy 1.12E+10 J 

 Specific emergy 9.95E+09 sej/g 

 Transformity w/o services 4.93E+05 sej/J 

 Transformity with services 9.98E+05 sej/J 

 
Appendix B 

89 

Modified from Brandt-Williams (2002) 

Lettuce (Romaine) 

Table 10 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1990 Evapotranspiration 5.27E+10 J 28,100

 topsoil loss 7.69E+09 J 72,398

 fuel 2.63E+10 J 64,746

 electricity 0.00E+00 J 170,694

 potash 1.86E+05 g 1.71E+09

 lime 0.00E+00 g 9.81E+08

 phosphorus 2.63E+04 g 2.16E+10

 nitrogen 4.75E+04 g 2.36E+10

 pesticides 4.43E+04 g 1.45E+10

 labor 3.87E+08 J 4.41E+06

 services 1.65E+03 $ 2.88E+12

 Total w/o services 6.39E+15 sej 

 Total w services 1.28E+16 sej 

 

 Yield dry wt. 8.08E+05 g 

 Yield energy 1.87E+10 J 

 Specific emergy 7.91E+09 sej/g 

 Transformity w/o services 3.42E+05 sej/J 

 Transformity with services 6.87E+05 sej/J 

 

Modified from Brandt-Williams (2002) 

Bell Peppers 

Table 3 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1981 Evapotranspiration 5.43E+10 J 28,100

 topsoil loss 7.69E+09 J 72,398

 fuel 5.57E+10 J 64,746

 electricity 7.49E+08 J 170,694

 potash 1.72E+05 g 1.71E+09

 lime 0.00E+00 g 9.81E+08

 phosphorus 5.27E+04 g 2.16E+10

 nitrogen 4.40E+04 g 2.36E+10

 pesticides 1.31E+05 g 1.45E+10

 labor 1.64E+09 J 4.41E+06

 services 2.11E+03 $ 4.97E+12

 Total w/o services 1.02E+16 sej 

 Total w services 2.79E+16 sej 

 

 Yield dry wt. 1.82E+06 g 

 Yield energy 3.87E+10 J 

 Specific emergy 5.60E+09 sej/g 

 Transformity w/o services 2.63E+05 sej/J 

 Transformity with services 7.22E+05 sej/J 

 
 Environmental Accounting Using Emergy: Minnesota 

90 

Modified from Brandt-Williams (2002) 

Tomatoes 

Table 13 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1990 Evapotranspiration 6.02E+10 J 28,100

 topsoil loss 6.33E+07 J 72,398

 fuel 7.37E+10 J 64,746

 electricity 0.00E+00 J 170,694

 potash 1.39E+05 g 1.71E+09

 lime 3.29E+06 g 9.81E+08

 phosphorus 4.60E+04 g 2.16E+10

 nitrogen 4.75E+04 g 2.36E+10

 pesticides 1.59E+05 g 1.45E+10

 labor 8.56E+08 J 4.41E+06

 services 4.38E+03 $ 2.88E+12

 Total w/o services 1.44E+16 sej 

 Total w services 3.07E+16 sej 

 

 Yield dry wt. 2.43E+06 g 

 Yield energy 4.54E+10 J 

 Specific emergy 5.91E+09 sej/g 

 Transformity w/o services 3.16E+05 sej/J 

 Transformity with services 6.77E+05 sej/J 

 

Modified from Brandt-Williams (2002) 

Watermelons 

Table 14 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1981 Evapotranspiration 5.43E+10 J 28,100

 topsoil loss 7.69E+09 J 72,398

 fuel 2.07E+10 J 64,746

 electricity 0.00E+00 J 170,694

 potash 7.44E+04 g 1.71E+09

 lime 0.00E+00 g 9.81E+08

 phosphorus 2.63E+04 g 2.16E+10

 nitrogen 2.86E+04 g 2.36E+10

 pesticides 3.79E+04 g 1.45E+10

 labor 4.00E+08 J 4.41E+06

 services 1.05E+03 $ 4.97E+12

 Total w/o services 5.34E+15 sej 

 Total w services 1.23E+16 sej 

 

 Yield dry wt. 1.88E+07 g 

 Yield energy 3.29E+11 J 

 Specific emergy 2.84E+08 sej/g 

 Transformity w/o services 1.62E+04 sej/J 

 Transformity with services 3.75E+04 sej/J 

 
Appendix B 

91 

Modified from Brandt-Williams (2002) 

Oranges 

Table 5 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1983 Evapotranspiration 6.51E+10 J 28,100

 topsoil loss 6.33E+08 J 72,398

 fuel 1.99E+10 J 64,746

 electricity 4.68E+08 J 170,694

 potash 2.36E+05 g K 1.71E+09

 lime 2.40E+05 g 9.81E+08

 phosphorus 1.12E+04 g P 2.16E+10

 nitrogen 3.01E+04 g N 2.36E+10

 pesticides 1.79E+04 g 1.45E+10

 labor 2.71E+08 J 4.41E+06

 services 3.01E+02 $ 3.79E+12

 Total w/o services 5.09E+15 sej 

 Total w services 7.43E+15 sej 

 

 Yield dry wt. 4.91E+06 g 

 Yield energy 8.65E+10 J 

 Specific emergy 1.04E+09 sej/g 

 Transformity w/o services 5.89E+04 sej/J 

 Transformity with services 8.59E+04 sej/J 

 

Modified from Brandt-Williams (2002) 

Pecans 

Table 22 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1989 Evapotranspiration 6.50E+10 J 28,100

 topsoil loss 6.33E+08 J 72,398

 fuel 1.32E+10 J 64,746

 electricity 2.96E+08 J 170,694

 potash 7.54E+04 g 1.71E+09

 lime 3.73E+05 g 9.81E+08

 phosphorus 2.11E+04 g 2.16E+10

 nitrogen 4.88E+04 g 2.36E+10

 pesticides 7.20E+03 g 1.45E+10

 labor 4.53E+07 J 4.41E+06

 services 2.11E+03 $ 2.99E+12

 Total w/o services 4.99E+15 sej 

 Total w services 1.15E+16 sej 

 

 Yield dry wt. 8.00E+05 g 

 Yield energy 2.30E+10 J 

 Specific emergy 6.23E+09 sej/g 

 Transformity w/o services 2.17E+05 sej/J 

 Transformity with services 5.00E+05 sej/J 

 
 Environmental Accounting Using Emergy: Minnesota 

92 

Modified from Brandt-Williams (2002) 

Sugarcane 

Table 19 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1985 Evapotranspiration 6.83E+10 J 28,100

 topsoil loss 7.69E+09 J 72,398

 fuel 5.46E+09 J 64,746

 electricity 0.00E+00 J 170,694

 potash 1.49E+05 g 1.71E+09

 lime 0.00E+00 g 9.81E+08

 phosphorus 1.05E+04 g 2.16E+10

 nitrogen 0.00E+00 g 2.36E+10

 pesticides 1.96E+03 g 1.45E+10

 labor 1.37E+07 J 4.41E+06

 services 1.35E+03 $ 1.99E+03

 Total w/o services 3.34E+15 sej 

 Total w services 3.40E+15 sej 

 

 Yield dry wt. 2.27E+07 g 

 Yield energy 4.12E+11 J 

 Specific emergy 1.47E+08 sej/g 

 Transformity w/o services 8.10E+03 sej/J 

 Transformity with services 8.25E+03 sej/J 

 

Modified from Brandt-Williams (2002) 

Cotton 

Table 20 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1987 Evapotranspiration 5.80E+10 J 28,100

 topsoil loss 8.23E+10 J 72,398

 fuel 9.70E+09 J 64,746

 electricity 3.15E+08 J 170,694

 potash 7.44E+04 g 1.71E+09

 lime 5.65E+05 g 9.81E+08

 phosphorus 1.58E+04 g 2.16E+10

 nitrogen 1.90E+04 g 2.36E+10

 pesticides 4.97E+03 g 1.45E+10

 labor 8.90E+07 J 4.41E+06

 services 4.07E+02 $ 3.17E+12

 Total w/o services 9.81E+15 sej 

 Total w services 1.15E+16 sej 

 

 Yield dry wt. 7.38E+05 g 

 Yield energy 1.25E+10 J 

 Specific emergy 1.33E+10 sej/g 

 Transformity w/o services 7.85E+05 sej/J 

 Transformity with services 9.20E+05 sej/J 

 
Appendix B 

93 

Modified from Brandt-Williams (2002)

Pasture (Bahia Grass) 

Table 21 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1985 Evapotranspiration 5.43E+10 J 28,100

 topsoil loss 6.33E+07 J 72,398

 fuel 2.46E+09 J 64,746

 electricity 2.22E+08 J 170,694

 potash 3.63E+04 g 1.71E+09

 lime 3.73E+05 g 9.81E+08

 phosphorus 7.38E+03 g 2.16E+10

 nitrogen 1.55E+04 g 2.36E+10

 pesticides 0.00E+00 g 1.45E+10

 labor 4.85E+06 J 4.41E+06

 services 2.24E+01 $ 3.51E+12

 Total w/o services 2.68E+15 sej 

 Total w services 2.78E+15 sej 

 

 Yield dry wt. 3.63E+06 g 

 Yield energy 6.88E+10 J 

 Specific emergy 7.39E+08 sej/g 

 Transformity w/o services 3.90E+04 sej/J 

 Transformity with services 4.04E+04 sej/J 

B3.7.2. Minnesota Agriculture 

New transformities calculated for a study to determine the empower density of Minnesota agriculture. 

Dairy (Minnesota) 

Milk per cow per year 

Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1980 Evapotranspiration 1.51E+11 J 28,100

 Topsoil loss 7.69E+09 J 72,398

 Fuel 2.26E+09 J 64,746

 Electricity 1.00E+09 170,694

 Potash 1.49E+05 g 1.71E+09

 Lime 9.28E+05 g 9.81E+08

 Phosphorus 3.35E+04 g 2.16E+10

 Nitrogen 5.07E+04 g 2.36E+10

 Pesticides 2.33E+03 g 1.45E+10

 Labor 1.28E+08 J 4414500

 Services 2.19E+03 $ 5.54E+12

 Total w services 8.24E+15 sej 

 Total w/o services 2.09E+16 sej 

 

 Yield dry wt. 7.63E+05 g 

 Yield energy 1.98E+10 J 

 Specific emergy 1.08E+10 sej/g 

 Transformity w/o services 4.16E+05 sej/J 

 Transformity with services 1.06E+06 sej/J 

 
 Environmental Accounting Using Emergy: Minnesota 

94 

Spring Wheat (Minnesota)

 

 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

 Evapotranspiration 1.29E+10 J 28,100

 Topsoil loss 1.91E+10 J 72,398

 Fuel 5.06E+08 J 64,746

 Potash 4.00E+03 g 1.71E+09

 Pesticide and herbicide 5.66E+02 g 1.45E+10

 Phosphate 5.95E+03 g 2.16E+10

 Nitrogen 1.37E+04 g 2.36E+10

 Labor 3.88E+06 J 4.41E+06

 Electricity 4.35E+07 J 1.71E+05

 Groundwater 0.00E+00 J 1.67E+05

 Services 2003$ 4.09E+02 $ 2.00E+12

 Total w services 2.27E+15 sej 

 Total w/o services 3.09E+15 sej 

 

 Yield dry wt. 2.14E+06 g 

 Yield energy 3.04E+10 J 

 Specific emergy 1.06E+09 sej/g 

 Transformity w/o services 7.48E+04 sej/J 

 Transformity with services 1.02E+05 sej/J 

Grain Corn (Minnesota) 

 

 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1987 Evapotranspiration 2.55E+10 J 28,100

 Topsoil loss 1.11E+10 J 72,398

 Fuel 9.96E+08 J 64,746

 Electricity 5.19E+07 J 170,694

 Potash 9.98E+03 g 1.71E+09

 Herbicide 2.84E+03 g 1.4519E+10

 Phosphorus 7.83E+03 g 2.1582E+10

 Nitrogen 2.49E+04 g 2.3642E+10

 Pesticides 6.16E+02 g 1.4519E+10

 Labor 3.88E+06 J 4.41E+06

 Operator 7.75E+06 J 7.19E+07

 Services 6.27E+02 $ 3.17E+12

 Total w/o services 2.42E+15 sej 

 Total w services 4.43E+15 sej 

 

 Yield dry wt. 3.46E+06 g 

 Yield energy 6.81E+10 J 

 Specific emergy 7.00E+08 sej/g 

 Transformity w/o services 3.55E+04 sej/J 

Transformity with services 6.50E+04 sej/J 
Appendix B 

95 

Soybeans (Minnesota) 

 

 Item 

Inputs 

ha-1

 y

-1 Units 

Emergy per Unit 

sej/(J, g, $)

1989 Evapotranspiration 2.55E+10 J 28,100

 Topsoil loss 1.11E+10 J 72,398

 Fuel 5.15E+08 J 64,746

 Electricity 4.95E+05 J 170,694

 Potash 1.63E+03 g 1706940000

 Herbicide 1.61E+03 g 1.4519E+10

 Phosphorus 1.27E+03 g 2.1582E+10

 Nitrogen 1.01E+03 g 2.3642E+10

 Pesticides 8.63E+02 g 1.4519E+10

 Labor 3.88E+06 J 4.41E+06

 Operator 7.75E+06 J 7.19E+07

 Services 4.20E+02 $ 2.99E+12

 Total w/o services 1.64E+15 sej 

 Total w services 2.92E+15 sej 

 

 Yield dry wt. 9.41E+05 g 

 Yield energy 2.30E+10 J 

 Specific emergy 1.75E+09 sej/g 

 Transformity w/o services 7.16E+04 sej/J 

transformity with services 1.27E+05 sej/J 

B3.7.2.1 Inputs for Minnesota Dairy per cwt Milk and assuming 172 cwt/cow 

Prices 1995 $/gal, cents/kWh 

Diesel 0.77 

Gasoline 1.11 

LPG 0.73 

Electricity 0.05 

Note: 1995 Prices are used to estimate fuel and electricity inputs to all Minnesota crops. 

Milk Production 

 Fuel type 

$ Cost/acre gal. per acre kWh/ ac. J/m2/cwt/y J/cow/y 

0.10 Diesel 0.13 7.60E+06 1.31E+09 

0.02 Gasoline 0.02 1.11E+06 1.91E+08 

0.08 LPG 0.11 4.41E+06 7.59E+08

 Total Fuels 1.31E+07 2.26E+09

0.20 Electricity 4 5.83E+06 1.00E+09 

0.40 Total Cost 

Fertilizer (lbs per treatment * # treatments *%treated) 

 lbs/acre/y g/ha/y 

Nitrogen 75 13,714 

Phosphorus 32 5,947 

Potash 22 3,996 
 Environmental Accounting Using Emergy: Minnesota 

96 

Pesticide (lbs per treatment * # treatments *%treated) 

 lbs/acre/y g/ha/y 

Chlorpyrifos 0.94 172.71 

Permethrin 0.11 20.21 

Phorate 1.11 203.94 

Terbufos 1.19 218.64 

Total 615.51 

Herbicides: 2,4D, Bromoxynil, Dicamba, Diclofop-methyl, Fenoxaprop-ethyl, 

Imazamethabenz-methy, MCPAC, Thifensulfron, Triallate, Tribenuron-methyl 

 lbs/acre/y g/ha/y 

Total 3.08 565.53 

 

Services 2003 

$/acre $/ha 

165.75 409.40 

 

Labor hours/acre hours/ha J/ha/y Labor expense, $ 

Operator 0.00 0.00 0.00 7.01 

Unskilled 1.00 2.47 3.88E+06 

 

Avg. Yield bu/acre g/acre 

1995-2001 136 3,457,664 

 

B3.7.2.2 Inputs for Minnesota Corn 

Use 1995 prices for fuels. 

 

Corn Production 

$ cost/acre Fuel type gal. per acre kWh/ acre J/ha/y 

7.21 Diesel 9.37 5.48E+08 

1.28 Gasoline 1.15 6.38E+07 

6.99 LPG 9.58 3.84E+08 

 Total Fuels 9.96E+08 

1.78 Electricity 35.63 5.19E+07 

17.27 Total 

 

Fertilizer (lbs per treatment * # treatments *%treated) 

 lbs/acre/y g/ha/y 

Nitrogen 105 19,263 

Phosphorus 43 7,826 

Potash 54 9,983 

 

Pesticide (lbs per treatment * # treatments *%treated) 

 lbs/acre/y g/ha/y lbs/acre/y g/ha/y 

Chlorpyrifos 0.94 172.71 135.36 24870 

Permethrin 0.11 20.21 

Phorate 1.11 203.94 

Terbufos 1.19 218.64 

 615.51 
Appendix B 

97 

Herbicide: 2,4D, Alachlor, Atrazinw, Bromoxynil, Cyanazine, Dicamba, ETC, Metolachlor, 

Nicosulfuron, Pendimethakin, Propaclor 

 lbs/acre/y g/ha/y 

All in order 15.47 2,842.36 

 

Services 2002 $/acre $/ha 

 254 627.38 

Labor hours/acre hours/ha J/ha/y 

Operator 2 4.94 7.75E+06 

Unskilled 1 2.47 3.88E+06 

 

Yield bu/acre g J/g 

 136 3,457,664 19,690 

B3.7.2.3 Inputs for Minnesota Wheat

Transpiration rate 3 mm/d 

Growing season 90 day 

Transpiration 0.27 m 

Energy Wheat 

trans. 1.29E+10 J/y 

Erosion Rate 12.6 short tons/acre/y 

Erosion Rate 28.2338784 MT/ha 

Energy of Erosion 1.91E+10 J/y 

Use 1995 Prices 

Wheat Production 

$ cost/acre Fuel type gal./ acre kWh/ acre J/ha/y 

5.57 Diesel 7.24 4.23E+08 

0.99 Gasoline 0.89 4.94E+07 

0.60 LPG 0.82 3.29E+07 

 Total Fuels 5.06E+08 

1.49 Electricity 29.88 4.35E+07 

8.66 Total Cost 

 

Fertilizer, herbicide and service inputs are assumed similar to dairy above. 

 

Wheat Yield bu/acre lbs dry wt./bu J/g 

 34 56 14,230 

 

B3.7.2.4 Inputs for Minnesota Soybeans 

Use 1995 Prices given above. 

Soybean Production 

$ cost/acre Fuel type gal./acre kWh/ acre J/ha/y 

5.72 Diesel 7.43 4.35E+08 

1.01 Gasoline 0.91 5.05E+07 

0.55 LPG 0.75 3.01E+07 

 Total Fuels 5.15E+08 

0.02 Electricity 

7.30 Total Cost 0.34 4.95E+05 
 Environmental Accounting Using Emergy: Minnesota 

98 

 

Fertilizer (lbs per treatment * # treatments *%treated) 

 lbs/acre/y g/ha/y 

Nitrogen 6 1,011 

Phosphorus 7 1,269 

Potash 9 1,627 

 

Pesticide (lbs per treatment * # treatments *%treated) 

 lbs/acre/y g/ha/y 

Chlorpyrifos No data No data 

Permethrin No data No data 

Phorate No data No data 

Terbufos No data No data 

Total 863.46 

 

Herbicides used: 2,4-D, Aciflourfen, Alachlor, Bentazon, Ethalfluralin, Fluazifop-p 

butyl, Glphosate, Imazethapyr, Metolachlor, Metribuzin, Pendimethalin, 

Quizalofop ethyl, Sethoxydim, Thifensulfuron, Trifluralin, Propachlor 

 

 lbs/acre/y g/ha/y 

All herbicides 8.76 1,610 

 

Services 2002 $/acre $/ha 

 170 419.9 

Labor hours/acre hours/ha J/ha/y 

Operator 2 4.94 7.75E+06 

Unskilled 1 2.47 3.88E+06 

 

Yield bu/acre g/ha J/g 

 37 940,688 24,420 

B3.8 Revised Transformities for Fossil Fuels 

There are two major ways to determine the transformities of fossil fuels. The first 

method is based on back calculation from solar based electricity using relative quality 

factors. This was the original way that the fossil fuel transformities were determined 

by Odum (1996), The second method is to calculate the transformity based on the 

geological process of formation of the mineral. Odum used both the first and second 

methods for coal in Odum (1996). The transformities for oil and natural gas were 

determined by the first method only in 1996, but coal was determined using both 

methods. Bastianoni et al. (2005) calculated the transformity for oil and petroleum 

natural gas by the second method. Their results closely conformed to Odum's original 

numbers determined by the first method. The transformity of oil being slightly and 

higher and the transformity of natural gas slightly lower than the original numbers. 

Odum (1996) used an average of the two methods to determine a transformity for coal. 

If a similar average is used for oil and natural gas we obtain the following numbers. 

All numbers are expressed relative to the 9.26E+24 sej/y planetary baseline, which is 

the corrected version of Odum's 9.44 line used in Odum (1996). 
Appendix B 

99 

Fossil Fuel Transformities sej J-1 

 Relative Efficiency Geologic Processes Average 3 sig. figs. 

Coal 42,180 33,350 37,770 37,800 

Natural gas 47,080 40,000 43,540 43,500 

Oil 52,640 55,400 54,020 54,000 

Table B4.1 The factors needed to convert one planetary baseline to another.

To convert, 

Baseline X To baseline, Y 

Multiply 

by 

9.44 9.26 0.981 

9.44 15.83 1.677 

9.26 9.44 1.019 

9.26 15.83 1.710 

15.83 9.26 0.585 

15.83 9.44 0.596 

Table B4.2 Emergy to Money Ratio of the United States for 1997 and 2000 

These numbers are different from those used in the West Virginia Report (Campbell et al.

2005a). These preliminary values are taken from a new study of the Emergy to Money 

Ratio for the United States from 1900 to 2004, which is a manuscript by Campbell and Lu 

to be published later this year. 

Year sej/$ 

1997 2.56E+12 

2000 2.35E+12 
 Environmental Accounting Using Emergy: Minnesota 

100 

Appendix C 

Calculation of Energy and Economic Values 

Used to Determine the 1997 Energy 

and Emergy Accounts for Minnesota 
Appendix C 

101 

C1 Notes for Table 4 – Annual Renewable Resources and Production in 1997.

 The numbers in parentheses and italics refer to data sources given above. The notation E+3 = 103

. 

Note 

Total Area (24) 2.25E+11 m2

Land area 1.72E+11 m2

Water Area (25) 1.55E+10 m2

Area of inland water and wetlands 5.32E+10 m2

Wetlands 2003 3.76E+10 m2

Wetlands 1850 7.53E+10 m2

Surface Waters 1.55E+10 m2

 

1 Solar Energy Received 1.074E+21 J y-1

 Absorbed 8.841E+20 J y-1

 

 Solar energy received (J) = (avg. insolation)(area)(365 day/y)(4186 J/kcal) 

 Solar energy absorbed = (received) (1-albedo) 

 The average insolation and albedo were obtained from the NASA website (26) referenced in sources. Twentysix, one-degree latitude by one-degree longitude, sectors covering the state were averaged.

 

kWh/m2/y J/m2/y 

 Solar energy received over the state 1324 4.77E+09 

 Solar energy absorbed by the state 1091 3.93E+09 

2 Kinetic Energy of Wind Used at the Surface 1.2639+19 J y-1

 

Wind energy = (density)(drag coefficient)(geostrophic wind velocity)3

(area)(sec/year) 

 

 This formula is given in a manuscript by Odum (1999) titled "Evaluating Landscape Use of 

Wind Kinetic Energy". 

 The wind velocity used was taken from the National Renewable Energy Laboratory (NREL) 

web site (59). The common drag coefficient over water is about 1.0E-3 for ordinary winds 

of 10 m/s or less (Miller 1964) 2.0E-3 over land and 3.0E-3 over low mountains Garratt (1977). 

Winds over land are about 0.6 of the wind velocity that the pressure system would generate in 

the absence of friction (Reiter 1969). 

 

Area NREL Class #2 (27)

 Air Density 1.3 kg m-3 

 Geostrophic Wind 7.92 m/s 

 Drag Coefficient 2.00E-03 dimensionless 

 Area of Class 9.5490 E+10 m2

 

 Sec / Year 3.16E+07 

 Energy 3.89E+18 J/yr 

 

Area NREL Class #3 (27) 

 Air Density 1.3 kg m-3 

 Geostrophic Wind 8.92 m/s 

 Drag Coefficient 2.00E-03 dimensionless 
 Environmental Accounting Using Emergy: Minnesota 

102 

 Area 5.3927E+10 m2 

 Sec/Year 3.16E+07 

 Energy 3.14E+18 J/yr 

 

 Area NREL Class #4 (27) 

 Air Density 1.3 kg m-3 

 Geostrophic Wind 9.67 m/s 

 Drag Coefficient 2.00E-03 dimensionless 

 Area 7.5762E+10 m2

 

 Sec/Year 3.16E+07 

 Energy 5.61E+18 J/yr 

 

3 Earth Cycle Energy 2.80E+17 J y-1

 

Earth cycle energy (steady-state uplift balanced by erosion) = 

(land area)(heat flow/area) 

 The heat flow per area is an average of nine wells throughout the state (28). 

 

 Area 2.252E+11 m2

 

 Heat flow/area 39.40 mW m-2 

 1.24E+06 J m2

 yr-1 

 

4 Rain Chemical Potential 7.07E+17 J y-1

 

Chemical potential energy in rain = 

(area)(rainfall)(density water)(Gibbs Free Energy water relative to seawater) 

 Average annual rainfall based on a one hundred year average from the 

 Western Regional Climate Center (29) and temperature of the growing season (30). 

 Area 2.2518 E+11 m2 

 Rainfall 0.658 m/y 

 Gibbs Free Energy (Odum 1996) 4.77 J/g 

 Density 1.00E+06 g/m3 

 

5 Chemical Potential Energy of Evapotranspiration 3.14E+17 J y-1

 

Chemical potential energy in evapotranspiration = 

(Area in land use)(Evapotranspiration for that use)(Density)(Gibbs Free Energy per gram) 

 In general, forest evapotranspiration can be estimated as 0.85 times pan evaporation 

(Odum et al. (1998). Forest area data is from UM-Duluth (31) and forest evapotranspiration 

was estimated using Oak Ridge National Laboratory data from Walker Branch, TN (32). Evapotranspiration 

rates for crops and pasture from Arnold and Williams (1985) and 

Ritter et al. (1985). The area of wetlands is from Net-State data (33) and wetland 

evapotranspiration was estimated using Hussey and Odum (1992) by using the average 

of peak beginning and end from their data, along with Water Resources data from the 

University of Arizona (34). 

 

Deciduous Forest Area 4.80E+10 m2

 

Evapotranspiration 1.83E-01 m y-1 

 1.00E+06 g m-3 

 4.77 J g-1 
Appendix C 

103 

Energy 4.19E+16 J/y 

 

Coniferous Forest Area 1.82E+10 m2

Evapotranspiration 1.83E-01 m y-1

Energy 1.59E+16 J y-1

 

Crop Area 8.70E+10 m2

Evapotranspiration 4.50E-01 m y-1

Energy 1.87E+17 J y-1 

 

Wetlands Area 3.76E+10 m2

 

Evapotranspiration 3.88E-01 m y-1 

Energy 6.97E+16 J y-1 

 

Total Area 1.91E+11 m2

 

Urban & Barren Area 3.43E+10 m2

(by difference)

 

6 Geopotential Energy of Rain and Snow on Land 

 Rain 4.58E+17 J y-1 

 Snow 7.22E+16 J y-1 

Geo-potential energy = (area)(mean elevation)(rainfall)(density)(gravity) 

An area weighted average of rainfall (35) and elevation by county (36) was used 

 to determine the geopotential energy of rain and snow on land. We assumed that 

 on average snow is 7.5% water (37). In the Table below the superscripts have the following meaning: 

*: Estimated Elev. 

T

: Estimated Precipitation and Snow. Averaged from the given values of the bordering 

counties. 

 
 Environmental Accounting Using Emergy: Minnesota 

104 

Table C1.1. Data used to determine the geopotential energy of rainfall. 

County Area m2 Elev. (m) Precip. (m) Snow (m) 

Geopotential 

rain J y-1

Geopotential

snow J y-1

Aitkin 5163064408 384.048 0.721360 1.2573 1.21E+16 1.96E+15 

Anoka 1153730438 277.368 0.796290 1.397 2.15E+15 3.51E+14 

Becker 3743560721 451.104 0.616204 1.03124 8.84E+15 1.37E+15 

Beltrami 7911341260 387.096 0.735076 1.13284 1.94E+16 2.72E+15 

Benton *T 1968803109 347.472 0.721868 1.17602 2.29E+15 3.43E+14 

Big Stone 1368974637 329.184 0.612902 1.01346 2.35E+15 3.58E+14 

Blue Earth *T 1981729403 231.648 0.769366 1.04394 3.09E+15 3.76E+14 

Brown 1600944494 294.132 0.715772 1.09728 2.90E+15 4.06E+14 

Carlton 2265235967 362.712 0.779018 1.3462 5.41E+15 8.68E+14 

Carver 972997830 219.456 0.769874 1.12522 1.42E+15 1.89E+14 

Cass 6248852173 408.432 0.663448 1.20396 1.42E+16 2.41E+15 

Chippewa 1523188195 310.896 0.628396 1.143 2.49E+15 4.25E+14 

Chisago 1145151102 277.368 0.802132 1.21666 2.20E+15 3.03E+14 

Clay 2728649599 271.272 0.564642 0.97028 3.54E+15 5.64E+14 

Clearwater 2666918850 454.152 0.6858 1.21158 7.00E+15 1.15E+15 

Cook 4158606316 185.928 0.626618 1.25476 3.99E+15 7.61E+14 

Cottonwood 1679591102 420.624 0.733552 1.10236 4.47E+15 6.11E+14 

Crow Wing 2993787491 371.856 0.71374 1.14554 6.79E+15 1.00E+15 

Dakota 1517453800 295.656 0.837438 1.14554 3.28E+15 4.03E+14 

Dodge*T 1137712980 335.28 0.81407 1.17602 2.69E+15 3.52E+14 

Douglas*T 1865204219 362.712 0.64897 1.02362 3.76E+15 5.43E+14 

Faribault 1868101768 335.28 0.79502 1.05918 4.36E+15 5.21E+14 

Fillmore 2231752286 329.184 0.864362 1.07188 5.61E+15 6.18E+14 

Freeborn 1869481746 374.904 0.840994 1.0541 5.20E+15 5.80E+14 

Goodhue 2018053986 256.032 0.844804 1.19634 3.80E+15 4.85E+14 

Grant*

 1491505356 298.704 0.591566 0.9525 2.25E+15 3.33E+14 

Hennepin 1570580930 274.32 0.743204 1.2446 2.72E+15 4.21E+14 

Houston 1472687474 381 0.8636 1.13538 4.25E+15 5.00E+14 

Hubbard 2587993010 438.912 0.662686 1.22428 6.29E+15 1.09E+15 

Isanti 1167821592 304.8 0.743204 0.9906 2.32E+15 2.77E+14 

Itasca 7577079013 396.24 0.71501 1.1811 1.83E+16 2.78E+15 

Jackson 1862581856 198.12 0.866902 0.92202 2.87E+15 2.67E+14 

Kanabec 1380767177 301.752 0.723392 1.08712 2.60E+15 3.55E+14 

Kandiyohi 2233225342 362.712 0.771398 1.29032 5.31E+15 8.20E+14 

Kittson 2860888726 356.616 0.637286 1.13284 5.47E+15 9.07E+14 

Koochiching 8162614622 371.856 0.664464 1.30048 1.67E+16 3.10E+15 

Lac Qui Parle 2016645680 316.992 0.619252 1.02362 3.37E+15 5.14E+14 

Lake 5922744342 402.336 0.757682 1.75006 1.44E+16 3.27E+15 

Lake of the Woods 4609203544 329.184 0.568706 1.09474 7.16E+15 1.30E+15 

Le Seuer*

 1226270339 237.744 0.734314 0.86868 1.90E+15 1.99E+14 

Lincoln 1421612099 533.4 0.658622 0.88138 4.37E+15 5.25E+14 

Lyon 1869975463 377.952 0.660146 1.08966 3.97E+15 6.04E+14 

McLeod 1308542930 326.136 0.699008 0.94996 2.61E+15 3.18E+14 
Appendix C 

105 

County Area m2 Elev. (m) Precip. (m) Snow (m) 

Geopotential 

rain J y-1

Geopotential

snow J y-1

Marshall 4698630977 307.848 0.52959 1.00076 6.38E+15 1.14E+15 

Martin 1888303675 362.712 0.796798 1.08966 4.77E+15 5.86E+14 

Meeker 1669194728 277.368 0.747522 1.0287 3.02E+15 3.74E+14 

Mille Lacs 1763207250 332.232 0.706374 1.05918 3.57E+15 4.87E+14 

Morrison 2984896547 341.376 0.668274 1.27 5.66E+15 1.02E+15 

Mower 1841457265 393.192 0.842772 1.11252 5.35E+15 6.32E+14 

Murray 1864220833 509.016 0.694944 1.07442 5.67E+15 8.00E+14 

Nicollet 1208112095 259.08 0.753618 0.75184 2.13E+15 1.85E+14 

Nobles 1872245749 478.536 0.707898 1.01092 5.51E+15 7.11E+14 

Norman 2271144960 268.224 0.55499 0.73914 2.96E+15 3.53E+14 

Olmsted 1693241149 396.24 0.798322 1.30302 4.57E+15 6.86E+14 

Otter Tail 5762399797 371.856 0.622808 1.20904 1.11E+16 2.03E+15 

Pennington 1601025432 344.424 0.518414 0.91694 2.41E+15 3.97E+14 

Pine 3711343697 316.992 0.791464 1.34366 7.89E+15 1.24E+15 

Pipeston 1208059486 521.208 0.657098 0.86106 3.63E+15 4.25E+14 

Polk 5177770684 335.28 0.579628 1.00838 8.50E+15 1.37E+15 

Pope 1857126693 365.76 0.629666 0.93218 3.70E+15 4.97E+14 

Ramsey 440018746 280.416 0.825754 1.32842 8.71E+14 1.29E+14 

Red Lake 1121525555 316.992 0.580644 1.23444 1.68E+15 3.44E+14 

Redwood 2283127128 329.184 0.683514 0.98298 4.46E+15 5.80E+14 

Renville 2556520608 326.136 0.700278 1.10236 5.01E+15 7.21E+14 

Rice 1334689670 286.512 0.80391 1.07442 2.69E+15 3.22E+14 

Rock 1251081616 457.2 0.706628 1.11252 3.47E+15 4.99E+14 

Roseau 4346870123 323.088 0.546354 0.92456 6.51E+15 1.02E+15 

St. Louis 17450352454 432.816 0.736092 1.62814 4.49E+16 9.65E+15 

Scott 953063015 283.464 0.741172 0.63246 1.83E+15 1.34E+14 

Sherburne 1166340443 301.752 0.744982 1.15062 2.25E+15 3.18E+14 

Sibley 1554551332 310.896 0.739394 1.016 3.12E+15 3.85E+14 

Stearns 3598254294 371.856 0.719582 1.17856 8.21E+15 1.24E+15 

Steele 1119117675 350.52 0.80391 1.04394 2.77E+15 3.21E+14 

Stevens 1490663610 347.472 0.646938 1.2065 2.80E+15 4.90E+14 

Swift 1948314509 316.992 0.70739 1.0541 3.77E+15 5.11E+14 

Todd 2536083983 393.192 0.747776 1.30302 6.30E+15 1.02E+15 

Traverse 1518712372 307.848 0.572516 1.05664 2.24E+15 3.88E+14 

Wabasha 1421956082 252.984 0.849884 0.96266 2.73E+15 2.72E+14 

Wadena 1406695386 411.48 0.67183 1.22682 3.26E+15 5.57E+14 

Waseca 1120615012 350.52 0.878332 1.39446 2.95E+15 4.30E+14 

Washington 1095245269 216.408 0.809244 1.02362 1.69E+15 1.90E+14 

Watonwan 1138170275 329.184 0.704342 1.06172 2.28E+15 3.12E+14 

Wilkin*

 1947254233 234.696 0.544322 1.016 2.08E+15 3.64E+14 

Winona 1660409003 201.168 0.837438 0.90424 2.51E+15 2.37E+14 

Wright 1849874727 304.8 0.72009 0.94742 3.56E+15 4.19E+14 

Yellow Medicine 1977544953 377.952 0.65278 1.06426 4.16E+15 6.24E+14 

Total 2.1849E+11 29445.204 61.849254 96.35236 4.58E+17 7.22E+16 
 Environmental Accounting Using Emergy: Minnesota 

106 

7 Geopotential of Runoff Total 7.21E+16 J y-1

Rain 2.55E+16 J y-1

 Snow 4.67E+16 J y-1

Geopotential energy of runoff (physical energy of streams) = (area)(mean elevation)(runoff) 

(density)(gravity) 

The annual runoff is a 100 year average. Drainage basin (38) and runoff data (39) were obtained online from the United States Geological Survey and the State of Minnesota. 

Assume 8% sublimation (Essery et al. 2003) for snow and that all snow melt runs off; thus 65% of 

runoff is from snow melt. 

 

Watershed 

(Scanlon, MN) Area* 1.61E+10 m2

Elevation 335.6 m 

(St. Louis River) Runoff 0.242316 m y-1

Density 1000 kg m-3

Gravity 9.81 m s-2

Energy 1.28E+16 J y-1

* Assumed to be the whole Lake Superior Drainage Basin 

(Crookston, MN) Area 9.61E+10 m2

(Red Lake River) Elevation 254 m 

Runoff 0.078232 m y-1

Density 1000 kg m-3

Gravity 9.81 m s-2

Energy 1.87E+16 J y-1

(Manitou Rapids, MN) Area 2.91E+10 m2

(Rainy River) Elevation 324 m 

Runoff 0.231 m y-1

Density 1000 kg m-3

Gravity 9.81 m s-2

Energy 2.14E+16 J y-1

 

 m2 St. Paul, MN Area (Mississippi River) Elevation 208.4 m 

 Runoff 0.112 m y-1 

 Density 1000 kg m-3 

 Gravity 9.81 m s-2 

 Energy 1.92E+16 J y-1 

 

8 Wave Energy (Lake Superior) 1.55E+16 J y-1

Assuming deep water waves and data from an offshore buoy (40). Calculation method from Pierson et 

al. (1958). 

Length of Coastline (41) 3.30E+05 m 

Density 1.00E+03 kg m-3
Appendix C 

107 

Gravity 9.81 m s-2

Average Wave Height* 0.57 m 

Period, Tmax 4.8 s 

Wave length 35.95 m 

Phase speed 7.49 m s-1

Group speed 3.74 m s-1

9 River Chemical Potential Absorbed 6.44E+12 J y-1

Received 9.15E+15 J y-1

 

River chemical potential energy received = (volume flow)(density)(Gibbs free energy relative to 

seawater) 

 River chemical potential energy absorbed = (volume flow)(density) (Gibbs free energy solutes at river 

entry - Gibbs free energy solutes at river egress) 

 

 The St. Croix River begins outside state boundaries and flows along the border with Wisconsin 

delivering part of the chemical potential energy that it carries to the state. 

Total Dissolved solids concentration from the USGS data (42).

Gibbs Free Energy, G = RT/w ln(C2/C1) = [(8.3143 J/mol/deg)(288 °K)/(18 g/mol H2O)] * ln [(1E6 - 

S)ppm)/965000] 

 

St. Croix* 

 Volume flow 3.87E+09 m3

y

-1

 Density 1000000 g m-3

 Solutes in 106 ppm 

 Solutes out 131 ppm 

 G in 4.73 J g-1

 G out 4.72 J g-1

 Absorbed 1.29E+13 J y-1

 Received 1.83E+16 J y-1

*The river flows along the border the state, so the energy was distributed equally between the states on 

opposite sides of the river. 

 

10 River Geopotential Absorbed 1.51E+15 J y-1

 Received 5.09E+15 J y-1

 

 Geopotential energy = (flow vol.)(density)(height entry - height egress)(gravity) 

 Data on water flow and height of the gauge are from USGS Water Resources Data (42, 43, and 44).

 

 St. Croix 

River* Vol. Flow 3.86E+09 m3

/yr 

 Density 1000 kg/m3

 

 Height In 268.8 m 

 (Height at Danbury, MN) 

 Height Out 189.3 m 

 (Height at Reno, MN) 

 Gravity 9.81 m/s2

 

 Absorbed 3.01E+15 J/y 

 Received 1.02E+16 J/y 

 *If the river borders the state half the calculated energy was used 
 Environmental Accounting Using Emergy: Minnesota 

108 

11 Nitrogen (Atmospheric Deposition) 2.00E+11 g y-1

 Deposition is a 5 year average (77% NH4 and 23% NOx). 1.36E+15 J y-1

Area 2.25E+11 m2 

 Rate (45) 8.8636 kg ha-1 

y

-1

 Conversion 10000 m2 ha-1

 Total Deposition 2.00E+08 kg y-1

 Energy per gram 6789.5 J g-1 (Weast, 1981) 

 Energy 1.36E+15 J y-1

 

12 Sulfur (Atmospheric Deposition) 5.26E+10 g y-1

 Deposition is a 5 year average. 3.91E+14 J y-1 

Area 2.25E+11 J y

 Rate (45) 2.33547 kg ha-1 y

-1

 Conversion 10000 m2 ha-1

 Total Deposition 5.26E+07 kg y-1

 Energy per gram 7429.06 J g-1 (Weast, 1981) 

 Energy 3.91E+14 J y-1

 

13 Chlorine, Cl ̄ (Atmospheric Deposition) 8.81E+09 g y-1

 Deposition is a 5 year average. 3.26E+13 J y-1

Area 2.25E+11 m2

 Rate (45) 0.3913 kg ha-1 

y

-1

 Conversion 10000 m2 ha-1

 Total Deposition 8.81E+06 kg y-1

 Energy per gram 3700 J g-1 (Weast, 1981) 

 Energy 3.26E+13 J y-1

 

14 Agricultural Products 6.99E+17 J y-1

(amount sold)(energy/unit) 

 From the 1997 Census of Agriculture. See Appendix B for energy per unit values except as noted. 

 

 Hay Mass (dry) (46) 4.57E+12 g y-1 

 Energy/unit 18901 J g-1 

 Energy 8.63E+16 J y-1 

 

 Oats Production (46) 1.62E+07 bu y-1 

 Conversion (47) 14515 g bu-1 

 Mass 2.35E+11 g y-1 

 Energy/unit 16280 J g-1 

 Energy 3.82E+15 J y-1

 

 Corn Production (46) 7.84E+08 bu y-1 

 Conversion (47) 25401 g bu-1 

 Mass 1.99079E+13 g y-1 

 Energy/unit 19736 J g-1 

 Energy 3.93E+17 J y-1
Appendix C 

109 

 

 Soybeans Production (46) 2.34E+08 bu y-1 

 Conversion (47) 27216 g bu-1 

 Mass 6.36E+12 g y-1 

 Energy/unit 17410 J g-1 

 Energy 1.11E+17 J y-1

 

 Wheat Production (46) 1.49E+08 bu y-1 

 Conversion (47) 27216 g bu-1 

 Mass 4.06E+12 g y-1 

 Energy/unit (48) 14230 J g-1 

 Energy 5.77E+16 J y-1

 

Barley Production (46) 2.19E+07 bu y-1 

 Conversion (47) 21772 g bu-1 

 Mass 4.77E+11 g y-1 

 Energy/unit (48) 14810 J g-1 

 Energy 7.07E+15 J y-1

 

 Sunflower Production (46) 1.06E+08 lb.y-1 

 Conversion factor 454 g lb. -1 

 Mass 4.83E+10 g y-1 

 Energy/unit (48) 23850 J g-1 

 Energy 1.15E+15 J y-1

 

Wool Production (49) 9.47E+05 lb. y-1 

 Conversion factor 454 g lb.-1 

 Mass 4.29E+08 g y-1

Energy/unit 

Odum et al. (1987) 20934 J g-1

 Energy 8.99E+12 J y-1 

 

Honey Production (49) 9.31E+06 lb. y-1 

 Conversion factor 454 g lb. -1 

 Mass 4.22E+09 g y-1 

 Energy/unit (48) 12720 J g-1 

 Energy 5.37E+13 J y-1

 

Goat's Milk Production (49) 1.37E+05 gal y-1 

 Conversion factor 3904 g gal. -1 

 Mass 5.33E+08 g y-1 

 Energy/unit (48) 2880 J g-1 

 Energy 1.54E+12 J y-1

 

Flaxseed Production (46) 8.17E+04 bu y-1 

 Conversion factor 25401 g bu-1 

 Mass 2.07E+09 g y-1 

 Energy/unit (48) 20590 J g-1 

 Energy 4.27E+13 J y-1

 
 Environmental Accounting Using Emergy: Minnesota 

110 

Potatoes Production (46) 1.89E+07 cwt y-1 

 Conversion factor 45359 g cwt-1 

 Mass 8.55E+11 g y-1 

 Energy/unit (48) 2990 J g-1 

 Energy 2.56E+15 J y-1

 

Sugar Beets Production (46) 8.27E+06 tons y-1

 Conversion factor 907185 g ton-1

 Mass 7.50E+12 g y-1

 Energy/unit (50) 3390 J g-1

 Energy 2.54E+16 J y-1

 

Milk Production (50) 4.75E+06 tons y-1

 Conversion factor 907185 g ton-1

 Mass 4.31E+12 g y-1

 Energy/unit (48) 2680 J g-1

 Energy 1.15E+16 J y--1

 

Eggs Number (49) 3.27E+09 # y-1

 Energy/unit 2010 J g-1

Energy (50g per 

egg) 3.29E+14 J y-1

 

15 Livestock 3.49E+16 J y-1

 (annual production mass)(energy/mass) 

 The amount sold is taken from the 1997 Census of Agriculture (49).

 

 Turkeys # sold (49) 4.72E+07 

 wt (Live) (51) 11063 g animal-1 

 Energy /unit (48) 8200 J g-1 All classes, meat and skin 

 Energy 4.28E+15 J y-1 

 

 Cows # sold (49) 8.25E+05 

 wt (Live) (51) 625050 g animal-1 

 Energy /unit (48) 12225 J g-1 Choice carcass 

 Energy 6.31E+15 J y-1 

 

 Hogs/Pigs # sold (49) 1.29E+07 

 wt (Live) (51) 118388 g animal-1 

 Energy /unit (48) 15742 J g-1 Fresh carcass 

 Energy 2.41E+16 J y-1 

 

 Sheep/Lambs # sold (49) 1.65E+05 

 wt (Live) (52) 48081 g animal-1 

 Energy /unit (48) 27820 J g-1 Raw leg, shoulder, arm 

 Energy 2.20E+14 J y-1 

16 Fish Production 1.32E+11 J y-1

 (mass)(energy/mass) 

Trout, from the 1997 Census of Agriculture. 
Appendix C 

111 

 Mass (49) 47,000 lbs.y-1 

 453.59 g lb-1 

 Energy/mass (48) 6,190 J g-1 

 

17 Hydroelectricity (1999) 4.10E+15 J y-1

 E.I.A. (53) 1,034,697,000 kWh y-1 3.72E+15 J y-1

 Other Renewable (Wind) 1,174,570,000 kWh y-1 4.23E+15 J y-1

 Total Renewable Electricity 2,209,267,000 kWh y-1 7.95E+15 J y-1

 

18 Net Timber Growth (1990) 1.28E+17 J y-1

 See Haugen and Mielke (2002) and web references below. 

(vol. forest growth)(density)(G) 

 G (no moisture, (54))=20086 J g-1

 Forest Growth (55) 4.51E+08 ft3

 

 1.28E+13 cm3

 

 Green wt. 1 g cm-3 

 Forest growth 1.28E+13 g y-1 

 G at 50% moisture 10043 J g-1 

 

19 Timber Harvest (1997) 6.47E+16 J y-1

 Reading and Krantz (2002) give data on harvest and waste.

 (vol forest growth)(density)(organic fraction)(G) 

 G=(4.2 kcal g-1)(4186 J kcal-1) 

Forest Harvest 2.85E+08 ft3

 8.06E+12 cm3

 

 Dry wt. 0.5 g cm-3 

 Forest mass 4.03E+12 g y-1 

 Energy (20% moisture) 16069 J g-1 

 Waste 1.42E+08 ft3

 

20 Groundwater Chemical Potential Energy 4.61E+15 J y-1

 (vol.)(density)(Gibbs free energy) 

 Based on the volume of ground water withdrawn in 1995 (56). 

 G = RT/w ln(C2/C1) = [(8.3143 J/mol/deg)(288 K)/(18 g/mol)] * ln [(1E6 - S)ppm)/965000] 

 Concentration taken as an average of all groundwater quality data given for the year 2000. 

 

 Volume used (56) 9.87E+08 m3

 y

-1

 Density 1000000 g m-3

 Solute conc. (57) 510 ppm 

 G 4.67 J g-1

 

21 Solid Waste Production (1997) 4.55E+12 g y-1

 From the Minnesota Pollution Control Agency (58). 

 

5,019,980 short tons y-1

 907185 g ton-1

 4.55E+12 g y-1

 

C2 Notes for Table 5 – Annual Production and Use of Nonrenewable Resources in 1997.

Note 

 Coal, natural gas and oil are not produced in commercial quantities in the state. 
 Environmental Accounting Using Emergy: Minnesota 

112 

22 Coal Used in the State (59) 5.09E+17 J y-1

 

 Amount 1.91E+07 short tons y-1

 9.07E+05 g ton-1 

 2.94E+04 J g-1 

 

23 Natural Gas Used in the State (60) 3.89E+17 J y-1

 

 Amount 3.54E+08 1000 ft3

 

 1.1E+09 J 1000 ft-3 

 

24 Petroleum Used in the State (61) 7.4E+17 J y-1

 Amount 1.17E+08 Barrels 

25 Electricity Produced (w/o hydroelectric and wind) 1.5E+17 J y-1

 Energy Information Administration (62).

 Amount 4.103E+10 kWh 

 

26 Electricity Used in the State 2.0E+17 J y-1

 Energy Information Administration (63)

 Amount 6.017E+10 kWh 

 

27 Nuclear Electricity Produced in the State

Energy Information Administration (64)

3.89E+16 J y-1

 Amount 1.082E+10 kWh

Mineral Production 

 Taken from the preliminary estimates of production found in the 

 US Geological Survey Minerals Yearbook – 2000 (65). Energy per mass from Odum (1996) 

except dolomite (Rock et al 2001)). 

 

28 Iron 4.79E+07 MT 4.79E+13 g y-1

Energy/Mass 14.2 J g-1 6.80E+14 J y-1

 

29 Sand and Gravel 3.45E+07 MT 3.45E+13 g y-1

Energy/Mass 6.11E+02 J g-1 2.11E+16 J y-1

 

30 Limestone 7.35E+06 MT 7.35E+12 g y-1

Energy/Mass 50 J g-1 3.68E+14 J y-1

 

31 Dolomite 3.08E+06 MT 3.08E+12 g y-1

Energy/Mass 5.00E+01 J g-1 1.54E+14 J y-1

 

32 Peat 2.90E+04 MT 2.90E+10 g y-1

 Energy/Mass 2.15E+04 J g-1 6.24E+14 J y-1

 

33 Soil Erosion Total 9.79E+16 J/y 

Agricultural lands 9.73E+16 J/y 

 (farmed area)(erosion rate)(organic fraction)(energy) 
Appendix C 

113 

The farmed area was taken from the 1997 census of Agriculture (49). 

The organic fraction was taken from Odum (1996). Erosion rates from wind and water (66)

and (67) for cropland and pasture. Energy per gram of soil Campbell (1998). 

 Erosion rate for forests was from personal communication of one of us (Ohrt) with personnel 

of the National Resources Conservation Service (WEPP, 2002). 

 Cropland Area (49) 2.15E+07 acres 

 Erosion rate 7.3 tons acre-1

 y

-1 

 Erosion 1.57E+08 ton y-1 

 Organic fraction 0.03 

 9.07E+05 g ton-1 

 22604 J g-1 

 Energy 9.65E+16 J y-1

 

 Pastureland Area (68) 3.43E+06 acres 

 Erosion rate 0.4 tons acre-1

 y

-1 

 Erosion 1.37E+06 ton y-1 

 Organic fraction 0.03 

 9.07E+05 g ton-1 

 22604 J g-1 

 Energy 8.45E+14 J y-1

 

 Forest Land Area (69) 1.65E+07 acres 

 Erosion rate 0.05 tons acre-1

 y

-1 

 Erosion 8.25E+05 ton y-1 

 Organic fraction 0.03 

 9.07E+05 g ton-1 

 22604 J g-1 

 Energy 5.08E+14 J y-1

 

C3. Notes for Table 6 Imports to the Minnesota economy in 1997

34 Tourism 7.20E+09 $ 

 Estimate for 1997 provided by the Minnesota Department of Trade and Economic Development 

(70).

 

35 Electricity Imported 

 Use - Production 4.48E+16 J y-1

 12,433,998,000 kWh 

 

36 Uranium Imported in 2000 60000000 $ 

2000 price Average (71) 0.0204 $/g 2.94E+09 g y-1

 2.94E+09 g 

 

37 Coal 5.09E+14 J y-1

 Energy Information Association 

 

 Short tons/yr (59) 1.91E+04

 g/short ton 9.07E+05

 J/g 2.94E+04

 
 Environmental Accounting Using Emergy: Minnesota 

114 

38 Petroleum 7.45E+17 J y-1

 Value is the difference between the production and consumption within the state. 

39 Natural Gas 3.89E+17 J y-1

 The difference between the production and consumption within the state (60).

 

40 Imported Minerals 

Data from The 1997 Commodity Flow Survey (2). 

1.06E+22 sej y-1

 

41 Goods (Materials minus Fuels and Minerals) 3.92E+13 g y-1

 1997 Commodity Flow Survey of Minnesota (Table C3.1) 2.75E+23 sej y-1

 

42 Goods (Services) w/o fuels and minerals (Table C3.1) 6.63E+10 $ y-1

42 Emergy of Services in all Imported Goods 1.84E+23 sej y-1

 

Estimated from data on shipments in the 1997 Commodity Flow Survey, US. Census Bureau 

(2). This number includes fuels and minerals, but not electricity. 

 

 Units 

 Total In Bound Shipments 1.31E+11 $ y-1

 Shipments Of Minnesota Origin 5.94E+10 $ y-1

 Dollar Value Of Imported Goods 7.19E+10 $ y-1

 Emergy To Money Ratio For The US In 1997 2.56E+12 sej $-1

 Emergy In The Services Required For Imported Goods 1.84E+23 sej y-1

 

43 5.51E+09 $ y-1 Fuels Services (Table 3.6.1)

 

44 Minerals Services (2) 6.60E+10 $ y-1

 

45 Electricity Services (Table 3.6.1) 6.22E+08 $ y-1

 

46 Pure Services 1.62E+10 $ y-1

 Base-Nonbase Analysis using data from the U.S. Census Bureau’s 

1997 Economic Census (72).(See Table C3.2) 

 

47 Immigration (1997) 8223 Ind. 

 Assume that the skill level of immigrants to Minnesota is similar to 

the skill levels entering the U.S. in 1997 (73). 

1.13E+21 sej y-1

 

48 Federal Government 1.98E+10 $ 

 Total Outlay in 1997 (74). 

 
Appendix C 

115 

Table C2.1 Detailed Account of the Emergy Imported in Material Inflows. 

This table contains detailed data for note 41 above (2).

SCTG 

Code Commodity Class J or g y-1

Emergy 

per unit Units

Emergy 

sej y-1

1 Live animals and live fish. 6.72E+14 4.39E+05 sej/J 2.95E+20 

2 Cereal grains 1.50E+17 1.82E+05 sej/J 2.72E+22 

3 Other agricultural product 7.91E+15 2.33E+05 sej/J 1.87E+21 

4 Animal feed and products of animal origin 2.68E+16 1.22E+06 sej/J 3.26E+22 

5 Meat, fish, seafood, and their preparations 6.30E+15 3.27E+06 sej/J 2.06E+22 

6 Milled grain products and preparations 9.46E+15 1.82E+05 sej/J 1.72E+21 

7 Other prepared foodstuffs , fats and oils 5.98E+16 1.12E+06 sej/J 6.71E+22 

8 Alcoholic beverages 1.24E+16 5.89E+04 sej/J 7.56E+20 

9 Tobacco products 1.31E+14 6.50E+05 sej/J 1.09E+20 

10 Monumental or building stone 2.05E+10 9.81E+08 sej/g 2.01E+19 

11 Natural sands 1.51E+12 1.96E+09 sej/g 2.96E+21 

12 Gravel and crushed stone 7.09E+12 4.91E+08 sej/g 3.48E+21 

13 Nonmetallic minerals 1.70E+12 1.96E+09 sej/g 3.34E+21 

14 Metallic ores and concentrates 2.94E+11 2.71E+09 sej/g 8.07E+20 

15 Coal 4.79E+17 3.92E+04 sej/J 1.88E+22 

17 Gasoline and aviation turbine fuel 1.17E+17 6.47E+04 sej/J 7.58E+21 

18 Fuel oils 7.47E+16 6.47E+04 sej/J 8.19E+21 

19 Coal and petroleum products 1.28E+17 6.47E+04 sej/J 8.32E+21 

20 Basic chemicals 9.90E+11 2.75E+09 sej/g 3.74E+21 

21 Pharmaceutical products 5.19E+10 2.75E+09 sej/g 1.43E+20 

22 Fertilizers 7.31E+11 2.99E+09 sej/g 2.19E+21 

23 Chemical products and preparations 7.61E+11 9.90E+09 sej/g 7.54E+21 

24 Plastics and rubber 1.09E+12 2.71E+09 sej/g 3.09E+21 

25 Logs and other wood in the rough 1.09E+15 1.96E+04 sej/J 2.15E+19 

26 Wood products 1.47E+12 1.49E+09 sej/g 3.99E+21 

27 Pulp, newsprint, paper, and paperboard 2.67E+16 1.40E+05 sej/J 3.75E+21 

28 Paper or paperboard articles 4.98E+15 1.67E+05 sej/J 2.37E+21 

29 Printed products 5.75E+11 4.95E+09 sej/g 2.85E+21 

30 Textiles, leather, and articles 2.35E+15 7.18E+06 sej/J 1.73E+22 

31 Nonmetallic mineral products 4.11E+12 3.09E+09 sej/g 1.29E+22 

32 Base metal in primary or semi-finished form 2.17E+12 5.91E+09 sej/g 1.32E+22 

33 Articles of base metal 8.79E+11 5.91E+09 sej/g 5.35E+21 

34 Machinery 5.01E+11 7.76E+09 sej/g 7.99E+21 

35 Electronic and other electrical equipment 4.20E+11 7.76E+09 sej/g 6.87E+21 

36 Motorized and other vehicles 8.27E+11 7.76E+09 sej/g 1.22E+22 

37 Transportation equipment 3.14E+10 7.76E+09 sej/g 1.09E+21 

38 Precision instruments and apparatus 1.55E+10 7.76E+09 sej/g 2.28E+20 

39 Furniture, mattresses, lamps, lighting 1.64E+11 2.89E+09 sej/g 5.27E+20 

40 Miscellaneous manufactured products 5.26E+11 1.61E+09 sej/g 1.37E+21 

41 Waste and scrap 8.17E+11 2.16E+09 sej/g 1.78E+21 

43 Mixed freight 4.05E+11 6.32E+09 sej/g 2.56E+21 

0 Commodity unknown 1.80E+11 4.26E+09 sej/g 1.31E+21 

 Total sej/y 3.20E+23 

 Total without fuels and minerals sej/y 2.75E+23 
 Environmental Accounting Using Emergy: Minnesota 

116 

Table C2.2 Export and Import of Services Between Minnesota and the Nation 

The emergy of imported and exported services was determined using a variation of the base-nonbase method 

from economic analysis. Data on employment and revenues for economic sectors classified using the North 

American Industry Classification System (NAICS) for MN and the U.S. (75) were used to estimate the services 

exported and imported from the state. The formulae in the text are evaluated using data in the table below. The 

rows in the table below are (1) U.S. employment by sector, (2) Minnesota employment by sector, (3) the fraction 

of total U.S. employment in each sector, (4) the fraction of total state employment in each sector. Row (5) and 

(6) give the money received per paid employee in the nation and state, respectively. Row (7) is the location 

quotient, i.e., row 4 divided by row 3, while (8) is the number of employees, Si, in each state sector (row 2) 

divided by the number of employees, Ni, (row 1) in the corresponding national sector. Row (9) is the sum of 

state employees in all sectors divided by sum of employees in all sectors of the national economy. Row (10) 

calculates basic sector jobs as the difference between rows (8) and (9) times the U.S. employment in each sector, 

and (11) estimates the dollar value of potential exports by multiplying the state dollars generated per employee 

by the number of basic employees (row 10) that could be making products or services for export. We extend this 

calculation to potential imports by multiplying any deficient in employment in row 10 by the dollars generated 

per employee in that sector of the national economy.

Economic Sectors

Parameters Agricult. Mining Utilities Construct. Manufact. Wholesale Retail trade Transport. Informat. 

U.S. Employees 3085992 509006 702703 5664840 16888016 5796557 13991103 2920777 3066167 

MN Employees 101593 7154 13205 103200 382530 131787 282413 53811 58855 

US (sector /total) 0.0249 0.0041 0.0057 0.0457 0.1362 0.0468 0.1128 0.0236 0.0247 

MN (sector/total) 0.0414 0.0029 0.0054 0.0420 0.1558 0.0537 0.1150 0.0219 0.0240 

$/employee US 63793 341840 585899 151563 227502 700357 175889 108959 203255 

$/employee MN 81603 243130 336321 179574 199317 754585 170311 1052356 164138 

Location Quotient 1.6621 0.7096 0.9487 0.9198 1.1436 1.1478 1.0191 0.9301 0.9691 

(Si) ÷ (Ni) 0.0329 0.0141 0.0188 0.0182 0.0227 0.0227 0.0202 0.0184 0.0192 

(St) ÷ (Nt) 0.0231 0.0231 0.0231 0.0231 0.0231 0.0231 0.0231 0.0231 0.0231 

Basic jobs (B) 30246 -4614 -3041 -27769 -7914 -2227 -41056 -13716 -12034 

Potential Imp./Exp. 2.47E+09 -1.58E+09 -1.78E+09 -4.21E+09 -1.58E+09 -1.68E+09 -6.99E+09 -1.49E+09 -2.45E+09

Exp(+) or imp(-) $# 0.00E+00 -1.35E+09 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 -1.22E+09

Services in Sector All goods Imported Local Local All goods Local Local Local Imported 

Assumed type Basic Basic Nonbasic Nonbasic Basic Nonbasic Nonbasic Nonbasic Basic 

# We assume that only basic sectors can export. Some of the potential export and import sectors summed here are 

only part service at this level of sector aggregation. Subtracting the dollar value of the goods exported in the 

sector from total estimated exports may give a better estimate of the services exported. An alternate method 

considers higher resolution sector data where more detailed sectors can be identified as primarily service. 

Considering higher resolution data the fraction of potential service imports was estimated, but a full analysis using 

this method was not used here.

 
Appendix C 

117 

Economic Sectors continued: 

Finance& 

Insurance 

Real Estate/ 

Rental 

Profession. 

Scientific Managem.

Admin. 

Support

Education 

Services

HealthCare 

Social Ser. 

Arts& 

Entertain. 

Accomo.

& Food 

U.S. Employees 5835214 1702420 5361210 2617527 7347366 321073 13561579 1587660 9451226

MN Employees 65996 30172 97818 86754 133839 6064 298312 37343 179487

US (sector /total) 0.0471 0.0137 0.0432 0.0211 0.0593 0.0026 0.1094 0.0128 0.0762

MN (sector/total) 0.0269 0.0123 0.0398 0.0353 0.0545 0.0025 0.1215 0.0152 0.0731

$/employee US 376639 141515 111029 35328 40278 63659 65262 65956 37074

$/employee MN 262568 128809 108001 49107 39132 63249 56416 52030 33062

Location Quotient 0.5710 0.8948 0.9212 1.6733 0.9197 0.9535 1.1106 1.1875 0.9588

(Si) ÷ (Ni) 0.0113 0.0177 0.0182 0.0331 0.0182 0.0189 0.0220 0.0235 0.0190

(St) ÷ (Nt) 0.0231 0.0231 0.0231 0.0231 0.0231 0.0231 0.0231 0.0231 0.0231

Basic jobs (B) -10081 -9187 -26131 26238 -36006 -1359 -15226 637 -39022

Potential 

Imp./Exp. -1.40E+09 -1.30E+09 -2.90E+09 1.29E+09 -1.45E+09 -8.65E+07 -8.59E+08 3.31E+07 -1.45E+09

Exp(+) imp(-) $# -7.00E+08 0.00E+00 -1.45E+09 1.29E+09 0.00E+00 -4.33E+07 0.00E+00 3.31E+07 0.00E+00

Services in Sector Imported Local Imported Exported Local Imported Local Exported Local 

Assumptions Basic Nonbasic Basic Basic Nonbasic Basic Nonbasic Basic Nonbasic

 

Economic Sectors continued:

Other Ser. Auxiliary Govern.

U.S. Employees 3256178 792370 19521000

MN Employees 77235 13734 294388

US (sector /total) 0.0263 0.0064 0.1576

MN (sector/total) 0.0315 0.0056 0.1199

$/employee US 81659 14231 42453

$/employee MN 71947 4650 26899

Location Quotient 1.0194 0.7449 5.1086

(Si) ÷ (Ni) 0.0237 0.0173 0.1189

(St) ÷ (Nt) 0.0231 0.0231 0.0231

Basic jobs (B) 1953 -4585 194895

Potential Imp./Exp. 1.41E+08 -6.53E+07 8.27E+09

Exp(+) imp(-) $# 3.51E+07 -1.63E+07 0.00E+00

Services in Sector Local Imported Local

Assumptions Nonbasic Nonbasic Nonbasic

 

Total Employment U.S 107,274,984

Total Employment Minnesota 2,480,156 

 

Table C2.3 Determination of Imported and Exported Services 

Potential for Importing ($) 8.39E+09 Multiply deficit employment times U.S. worker productivity 

in sectors assumed to be capable of importing services and 

sum over the sectors. 

Estimate of Imported Ser. ($) 4.22E+09 Use detailed NAICS categories; determine a fraction of 

potential imports that is non local service. Assume MN 

imports everything that they need 

Estimate of Exported Ser ($) 1.36E+09 The sum of basic exporting sectors in Table C3.2 above. 
 Environmental Accounting Using Emergy: Minnesota 

118 

Emergy exported services 

(sej y-1) 

3.47E+21 Multiply the exports in dollars by the emergy to dollar ratio 

of the U.S. in 1997 to estimate the emergy exported 

Emergy imported services 

(sej y-1) 

1.08E+22 Multiply the dollar value of the imported services times the 

emergy to dollar ratio of the U.S. in 1997. 

C4. Notes for Table 7 - Exports from the Minnesota Economy in 1997. 

49 Materials in Goods Exported Minus Fuels and Taconite 3.85E+23 sej y-1

Data from Commodity Flow Survey of Minnesota (2).See Table C4.1 for totals. 

 

50 Taconite Exported (2) 3.58E+13 g 

 Total Shipments 4.30E+13 g 

 Instate Shipments 7.25E+12 g 

 Exported 3.58E+13 g 

 

51 Services in Goods Exported. 

Data on shipments from the 1997 Commodity Flow Survey (2). 

 

 Units 

Emergy to dollar ratio for the US in 1997 2.56E+12 sej/$ 

Dollar value of shipments to all destinations 1.55E+11 $/y 

Dollar value final destinations in MN 5.94E+10 $/y 

Dollar value of exported goods w/o iron 9.46E+10 $/y 

Emergy exported in services in goods w/o iron 2.42E+23 sej y-1

 

Value of exported metallic ores 

Total value shipments (2) 1.44E+09 $ 

Fraction leaving the state 0.83 

Dollar value metallic mineral exports 1.20E+09 $/y 

Emergy in services associated with iron export 3.06E+21 sej y-1

Total value of services in exported goods 2.45E+23 sej y-1

Table C3.1 Emergy in the materials exported from Minnesota. Data on material shipments from Minnesota to all 

states by commodity is from The U.S. Census Bureau’s 1997 Commodity Flow Survey (2), Additional State Data, Table 

12. In some cases in Table C4.1 shipment weight was converted to energy. See Appendix B for the calculation of average 

emergy per unit for the commodity classes and a table giving the mass to energy conversions for the commodity class. 

SCTG 

Code Commodity Class J or g 

Emergy 

per unit Units 

Emergy 

sej y-1

1 Live animals and live fish. 0 4.393E+05 sej J-1 0

2 Cereal grains. 2.55E+17 1.818E+05 sej J-1 4.63E+22

3 Other agricultural product. 4.61E+16 2.334E+05 sej J-1 1.08E+22

4 Animal feed and products of animal origin. 2.26E+16 1.217E+06 sej J-1 2.75E+22

5 Meat, fish, seafood, and their preparations. 1.10E+16 3.270E+06 sej J-1 3.61E+22

6 Milled grain products and preparations. 2.62E+16 1.818E+05 sej J-1 4.76E+21

7 Other prepared foodstuffs and fats and oils. 1.05E+17 1.120E+06 sej J-1 1.17E+23

8 Alcoholic beverages. 4.90E+15 5.886E+04 sej J-1 2.88E+20

9 Tobacco products. 1.06E+14 6.500E+05 sej J-1 6.91E+19

10 Monumental or building stone 0 9.810E+08 sej g-1 0

11 Natural sands 1.21E+12 1.962E+09 sej g-1 2.37E+21
Appendix C 

119 

Table C3.1 continued 

12 Gravel and crushed stone 6.14E+12 4.905E+08 sej g-1 3.01E+21

13 Nonmetallic minerals 0 1.962E+09 sej g-1 0

14 Metallic ores and concentrates 3.57E+13 3.61E+09 sej g-1 1.29E+23

15 Coal 1.60E+15 3.78E+04 sej J-1 6.07E+19

17 Gasoline and aviation turbine fuel 8.38E+16 6.475E+04 sej J-1 5.43E+21

18 Fuel oils 6.80E+16 6.475E+04 sej J-1 4.40E+21

19 Coal and petroleum products 2.58E+17 6.475E+04 sej J-1 1.67E+22

20 Basic chemicals 1.04E+12 2.750E+09 sej g-1 2.86E+21

21 Pharmaceutical products 8.71E+10 2.750E+09 sej g-1 2.39E+20

22 Fertilizers 5.72E+11 2.993E+09 sej g-1 1.71E+21

23 Chemical products and preparations 7.72E+11 9.902E+09 sej g-1 7.64E+21

24 Plastics and rubber 6.90E+11 2.709E+09 sej g-1 1.87E+21

25 Logs and other wood in the rough 0 1.962E+04 sej J-1 0

26 Wood products 2.07E+12 1.490E+09 sej g-1 3.08E+21

27 Pulp, newsprint, paper, and paperboard 3.08E+16 1.398E+05 sej J-1 4.31E+21

28 Paper or paperboard articles 5.17E+15 1.674E+05 sej J-1 8.66E+20

29 Printed products 8.99E+11 4.951E+09 sej g-1 4.45E+21

30 Textiles, leather, and articles 3.85E+15 7.177E+06 sej J-1 2.77E+22

31 Nonmetallic mineral products 4.73E+12 3.094E+09 sej g-1 1.46E+22

32 Base metal primary or semi-finished form 3.29E+12 5.906E+09 sej g-1 1.94E+22

33 Articles of base metal 8.24E+11 5.906E+09 sej g-1 4.86E+21

34 Machinery 4.65E+11 1.47E+10 sej g-1 6.84E+21

35 Electronic and other electrical equipment 3.85E+10 1.47E+10 sej g-1 5.65E+21

36 Motorized and other vehicles 7.82E+11 1.47E+10 sej g-1 1.15E+22

37 Transportation equipment 5.26E+10 1.47E+10 sej g-1 7.73E+20

38 Precision instruments and apparatus 6.44E+10 1.47E+10 sej g-1 9.47E+20

39 Furniture, mattresses, lamps, lighting 1.70E+11 2.890E+09 sej g-1 4.90E+20

40 Miscellaneous manufactured products 8.13E+11 1.613E+09 sej g-1 1.31E+21

41 Waste and scrap 3.18E+12 2.161E+09 sej g-1 6.87E+21

43 Mixed freight 1.32E+12 6.316E+09 sej g-1 8.35E+21

0 Commodity unknown 1.38E+11 5.710E+09 sej g-1 7.87E+20

 Natural Gas (joules) 0 4.80E+04 sej/J 0

 Total 5.41E+23

 Total without fuels (15,17,18, natural gas) 5.15E+23

 Exported fuels 2.66E+22

 Total without fuels and iron ore 3.85E+23
 Environmental Accounting Using Emergy: Minnesota 

120 

52 Pure Service Exported at the U.S. Em/$ Ratio 3.47E+21 sej y-1

 1.36E+09 $ 

 

53 Federal Government 2.60E+10 $ 

 Taxes 1997 (76). 

 

54 Tourists (experiences taken home) 

 Money spent 7.2E+09 $ 

Emergy purchased 3.352E+22 sej y-1

 A rough approximation of the experiences taken home by tourists is the dollars spent in 

recreation times the emergy to money ratio of Minnesota in the year of their visit. 

C5. Notes for Table 8 - Value of Minnesota Storages in 1997.

55 Forest Storage 6.26E+18 J 

Based on the forest inventory for Minnesota in Haugen and 

Mielke (2002) 

Timberland Standing Mass 4.29E+6 Tons dry wt. 

 3.895E+15 g 

 16069 J g-1

56 Water (Lakes) 6.76E+17 J 

Total Volume (77) 1.43E+11 m3 

Density 1000000 g/m3 

Concentration (78) 7.9 ppm 

Gibbs 4.74 J/g 

57 Water (Minnesota Part of Lake Superior) 3.30E+17 J 

Chemical Potential 

 

Total Volume (79) 1.22E+13 m3 

% of Shoreline in MN 0.0755 Dimensionless 

Density 1000000 g/m3 

Solute Concentration (80) 63 ppm 

Gibbs 4.73 J/g 

Energy Stored in The Lake 4.37E+18 J 

Turnover Time 191 y 

Net Volume Water per Year 6.41E+10 m3 

Gibbs Free Energy at 5 ppm 4.74 J/g 

Energy Inflow per Year 3.04E+17 J/y 

Transformity Chemical Potential Of Rain 1.81E+04 sej/J 

Emergy Input per Year 5.49E+21 sej/y 

Emergy to Support Storage 1.05E+24 sej 

Transformity Lake Superior Water 2.40E+05 sej/J 

 

58 Soil (Organic Matter)

 Low High Mean Units 

Soil Org M. In The Upper 1m*

 1.88E+15 8.10E+15 4.46E+15 g 

Average Calories In Soil OM 5.04 kcal g-1
Appendix C 

121 

Energy in Soil Organic Matter 21097 J/g 

Energy of Stored OM In Soils 3.96E+19 1.71E+20 9.42E+19 J 

Transformity of Topsoil 7.26E+04 sej/J 

 

Emergy Stored In Soils 2.87E+24 1.24E+25 6.84E+24 sej 

Soil organic matter estimates were made by Denis White of the Office of Research and Development 

Western Ecology Division with the assistance of Jeff Kern of Dynamic Corporation. The formula given 

below was used for the calculation of OM in each horizon (or layer in STATSGO) in each component 

of each map unit (USDA 1994): 

Layer OM = Depth * Bulk Density * Proportion Organic Matter * Proportion Not.Rock 

The variable called “proportion.not.rock” (Tan et al. 2004) was computed from seven STATSGO 

variables. The script used for the mean value computation was written in R by Denis White. The results 

above were derived using the low values of bulk density (bdl) and organic matter (oml) for each layer 

and also the high values (bdh and omh), The mean values are taken as our best estimate for this study. 

Mineral Reserves

59 Iron (81) 1.40E+10 MT 1.40E+16 g 

Energy/Mass 14.2 J/g 1.98E+17 J 

60 Sand & Gravel 

(construction) 3.51E+10

Short tons 3.19E+16 g 

 6.11E+02 J/g 2.15E+19 J 

 Estimate based reserves in a seven county metro area (82) prorated to areas of the state where the 

Minnesota Department of Natural Resources is assessing the sand and gravel resource (83). We 

assume the maximum value for the reserves.

61 Limestone 2.82E+09 MT 2.82E+15 g 

Energy/Mass 50 J/g 1.41E+17 J 

 Based on the projected reserves of Vetter Stone Co. in Kasota, MN and present production rate 

62 Dolomite 1.32E+08 MT 1.32E+14 g 

Energy/Mass 11635.6 J/g 1.54E+18 J 

 Assumes dolomite has the same projected resources as limestone.

 

63 Copper* 4.50E+09 MT 4.50E+15 g 

Energy/Mass 1.00E+06 g/moon 

 

64 Nickel* 4.50E+09 MT 4.50E+15 g 

Energy/Mass 1.00E+06 g/moon 

*There is a Copper/Nickel complex of 4.5 billion tons of ore, according to Ojakangas and Matsch 

1982. Assume that Ni and Cu are by-products. Ore grade is given at (84).
 Environmental Accounting Using Emergy: Minnesota 

122 

 

 Minnesota Nickel, Copper and Platinum ore relative to Cohen et al. (2007) OGC. 

Element Concentration % Ore Grade Cutoff % 

Cohen et al. (2007) 

Transformity 

adjustment 

 Copper 0.694 0.35 1.983 

 Nickel 0.218 1.0 0.218 

 Platinum 5.73E-05 1.1E-04 0.521 

 

65 Peat 3.52E+09 MT 3.52E+15 g 

 Energy/Mass 2.15E+04 J/g 7.57E+19 J 

Estimate based on Minnesota Department of Natural Resources estimate of peat lands (85) and the dry weight 

and area of peat lands in Aiken county, which is about 7% of the total resource.

 

66 Platinum 

 Platinum (PtEq) 3.20E+07 short tons 2.90E+13 g 

 

67 People 1.41E+24 sej 

 Using the population percentages from the 2000 Census (86).

 1997 Population (Estimate) 4735830 people

 

 Number of individuals

 2000 Fraction 1997 sej/ind. sej

 Preschool 329605 6.70% 317301 3.34E+16 1.06E+22

 School 2402204 48.83% 2312528 9.22E+16 2.13E+23

 College Grad 1882631 38.27% 1812350 2.75E+17 4.98E+23

 Post-College 255844 5.20% 246293 1.29E+18 3.17E+23

 Public Status* 49195 1.00% 47358 3.86E+18 3.65E+23

 Legacy# 765 765 7.70E+18 5.89E+21

 Total 4919479 100% 4735830 1.41E+24

*

Public Status is estimated as one per cent of total population. 

#

All individuals listed in the index to Minnesota: A History of the State by Theodore C. Blegen 

are counted as part of Minnesota’s legacy. 

A few of those legacy individuals are: 

 Ignatius Donnelly - Minnesotan congressman 

 F. Scott Fitzgerald – Author 

 Alexander Ramsey – First governor 

 Dr. Archibald Graham – Author, “Shoeless Joe” (Field of Dreams) 

 Walter Mondale – Politician 

 Hubert Humphrey – Presidential Candidate, Vice President 
Appendix C 

123 

C6. Notes for Table 9– Summary Flows for Minnesota in 1997 

68 The largest renewable emergy sources are the wind energy absorbed in the planetary boundary layer, the 

wave energy absorbed on the shore of Lake Superior and the geo- and chemical- potential energy 

delivered to the state in the St. Croix River. 

69 Electricity from renewable sources includes wind, hydropower, and other renewable sources. This 

renewable class of energy was added for this study. It represents the amount of energy for concentrated 

use that has been extracted from the renwebale emergy base o fthe system. 

70 Nonrenewable sources (Table 5) include fuels and minerals coal, natural gas, petroleum, sand and gravel, 

limestone dolomite, iron ore and soil erosion where it exceeds soil building, i.e., in agricultural areas. 

71 Extracted fuels and minerals from within the state. This flow was used in the West Virginia study but it 

was given a symbol that was inconsistent with past usage. Here it has been designated uniquely by adding 

a prime to N1. 

72 Dispersed Rural Source (Table 5) is the soil erosion in agricultural areas. This category includes any 

renewable resource that is being used more rapidly then it is being replaced. 

73 Concentrated Use is the emergy in the mined tonnage of fuels and minerals used within the state plus the 

emergy of electricity, from nuclear, hydropower, wind and other nonfossil fuel and internal renewable 

sources. 

74 Fuels and minerals exported without use are the quantities of iron ore exported directly and as taconite. In 

the case of taconite pellets some value is added to the Minnesota economy before export; however, this 

value is relatively small compared to the wealth generating potential of the ore when used in steel-making. 

75 Imported fuels are coal, petroleum, natural gas and uranium plus some minerals (Table 6). 

76 Fuels and minerals used. Add mineral production and fuel and mineral imports and subtract minerals 

exported without use. 

77 In state minerals used: Subtract minerals exported without use from mineral production. 

78 The material imported in goods was determined from the 1997 Commodity Flow Survey by summing the 

tonnage by commodity class from states with significant exports to Minnesota. (Table C3.1). 

79 Dollars paid for imports is the sum of the dollar value of imported goods including fuels and minerals and 

all other goods and services. 

80 The services in imported fuels and minerals and electricity are determined below. 

Table C4.1 Services in Imported Fuels and Minerals 

Fuel Quantity Unit Price ($/Unit) $ y-1

Coal 1.91E+07 short tons 26.64 5.08E+08 

Petroleum 4.92E+09 gallons 0.8 3.94E+09 

Natural Gas 3.54E+08 1000 cu-ft 3 1.06E+09 

Electricity 1.E+10 kWh 0.05 6.22E+08 

Uranium 6.49E+6 Lb. 9.25 6.00E+07 

The prices of these items can be found in the data sources given in Campbell et al. (2005) 

81 Dollars paid for goods without fuels and minerals is the total dollar value of goods imported from the CFS 

minus the dollar value in fuels and minerals calculated above. 

82 Dollars paid for imported services as determined using the base-nonbase method (Table C3.3). 

83 Dollars spent by tourists in the State of Minnesota. in 1997 or 2000 

84 Federal transfer payments are the total outlay of funds in MN by the Federal government. 

85 Imported Services Total is the sum of the emergy in services associated with imported goods, fuels, and 

minerals, and pure services. 

86 Imported Services in fuels and minerals is the emergy equivalent of the human service represented by the 

money paid for fuels and minerals. Dollars are converted to emergy using the 1997 emergy/$ ratio for US.
 Environmental Accounting Using Emergy: Minnesota 

124 

87 Imported Services in Goods is the emergy equivalent of the money paid for goods minus that paid for 

fuels and minerals. 

88 Imported Service is the emergy equivalent of the money paid for services again assuming an average 

emergy backing a dollar spent for human service in a given year. 

89 Emergy Purchased by Tourists is the emergy purchased when tourists $ are spent in Minnesota, i.e., at 

Minnesota’s emergy to dollar ratio. 

90 Net Emergy purchased by Federal dollars spent in the state. Use Minnesota emergy/$ ratio and the 

difference between outlays and taxes. A negative number shows the emergy flow forgone by failure to 

spend tax dollars in the state. 

91 Exported Products is the emergy in the goods exported including electricity, excluding iron ore. 

92 Dollars Paid For All Exports. This is the sum of the money paid for goods, iron ore and services. 

93 Dollars Paid for Services in Goods. This is the money paid for products listed in 88 above. 

94 Dollars Paid for Services in Iron. This is the money paid for taconite exported.. 

95 Dollars Paid for Services. This is the money paid for pure services supplied by Minnesota to the rest of the 

nation as determined by the Base-Nonbase method.

96 Federal Taxes Paid is the sum of personal income, social security, and business taxes 

97 Total Exported Services is the sum of the emergy equivalents in human service in fuels, goods and 

services exported.

 

Table C4.2 Services in Exported Minerals 

 Amount 1997 prices $/Ton. $ 

Taconite Pellets 3.94E+07 36.50 1.2E+09 

 

98 Exported Services in Goods. This is the emergy equivalent of the dollar value of all exported goods 

excluding taconite. It is determined by multiplying the dollars paid for goods by the emergy to money ratio 

for the U.S. in 1997 or 2000. In using P2 to determine services, our implicit assumption is that the emergy of 

human service in Minnesota is not much different from the average for the U.S. 

99 Exported Services in iron is the emergy equivalent of the human service in the dollars paid for taconite 

pellets exported. Service is determined using the US emergy/$ ratio for 1997 or 2000 under the assumption 

given in 98 above. 

100 Exported service is the emergy equivalent of the dollar value of exported pure services. This number was 

determined as in 98 and 99 above. 

101 Gross State Product (87) for Minnesota in 1997 or 2000. 

102 Emergy-to-dollar ratio for the U.S. in 1997 and in 2000(sej/$). 

103 Emergy-to-dollar ratio for the State of Minnesota in 1997 and in 2000 (sej/$). 

 

C7. Notes for Table 10. Calculation of Emergy Indices 

104 Renewable Emergy Used (see Note 68). 

105 In-State Nonrenewable Use is the sum of dispersed rural sources (N0) and in-state mineral production. 

106 Imported Emergy is the sum of imported fuels and minerals (F), goods (G), and services (PI). 

107 Total Emergy Inflow is the sum of renewable emergy absorbed (RA), and the emergy imported in the 

previous note. 

108 The total emergy used in the state (U) is the sum of the renewable emergy absorbed (RA), the emergy used 

from dispersed rural sources (N0), fuels and minerals used (F1), and the goods (G) and services (PI) 

imported. 
Appendix C 

125 

109 Total exported emergy is the sum of the emergy in the materials of exported goods (B), the emergy of 

services associated with goods and with pure service (PE) and the emergy of fuels and minerals exported 

without use (N2). 

110 The emergy used from home sources is the sum of emergy from dispersed rural sources, in-state minerals 

and fuels used (F2), and renewable emergy absorbed divided by total use (U). 

111 Import minus export is the difference between imported emergy and exported emergy. 

112 Ratio of exports to imports is the quotient of the expression in Note 109 divided by the expression in Note 

106. 

113 Fraction of use that is locally renewable is the ratio of renewable emergy absorbed to total use. 

114 Fraction of use that is purchased is the ratio of imported emergy to total use. 

115 Fraction of use in imported service is PI divided by U. 

116 Fraction of use that is free is the sum of the renewable emergy absorbed and emergy from dispersed rural 

sources divided by total use. 

117 Ratio of purchased to free is the quotient of the sum of imported fuels and minerals (F1), imported goods 

(G) and imported services (PI) divided by the sum of the renewable emergy absorbed (RA) and the emergy 

from dispersed rural sources (N0). 

118 Environmental loading ratio is the quotient of the sum of the emergy from dispersed rural sources (N0), 

imported fuels and minerals (F1), imported goods (G) and imported services (PI) divided by the renewable 

emergy absorbed (RA). 

119 Investment Ratio. There are several possible investment ratios (Odum 1996). This one compares imported 

emergy to the emergy supplied form within the state. The emergy from within the state is the sum of the 

renewable emergy absorbed (RA), the emergy from dispersed rural sources (N0), and the emergy from instate fuels and minerals (F2). 

120 Emergy use per unit area (Empower density) is the total emergy use (U) divided by the area. 

121 Use per person is the total emergy U divided by the population. 

122 Renewable carrying capacity at the present standard of living is found by dividing the renewable emergy 

received by total use and then multiplying this fraction times the present population. 

123 Developed carrying capacity at the present standard of living is approximately eight times the renewable 

carrying capacity. 

124 Minnesota State Economic Product (87) in 1997 or 2000. 

125 Ratio of Minnesota emergy use to GSP. Divide U by X, the GDP. 

126 Ratio of U.S. Emergy use to GNP. See Appendix B4.2. 

127 Ratio of emergy in electricity use to total use (El/U). See Table 5 for electricity use. 

128 Ratio of electricity production to total use (Elp/U). ). See Table 5 for electricity production. 

129 Fuel use per person is the sum of coal, natural gas, and petroleum used in the state divided by population.

130 Population of the State (86) in 1997 and in 2000 

131 Area of the State (24)

132 Renewable Empower Density is the emergy flow of renewable energy per unit area. 
 Environmental Accounting Using Emergy: Minnesota 

126 

Appendix D.

Calculating the Import and Export of Materials 
Appendix D 

127 

D1. Creating Export/Import Spreadsheets for 

Materials 

The method used to determine the emergy exported 

from and imported to a state was further developed in 

this study to take advantage of the extensive data on this 

subject provided by the U.S. Census Bureau’s 

Commodity Flow Survey (2), which is performed every 

five years. This innovation resulted in a marked 

improvement in the accuracy with which imports and to 

a lesser extent exports from a state’s economy can be 

determined. Even though the CFS provides all the 

information needed to document exports and imports it 

is not tabulated in the form that we need and some of the 

information is hidden rather deeply in the data base. To 

make our method transparent and reproducible, we have 

described in detail the characteristics of the database, 

data sources and methods that we used to determine the 

emergy imported and exported from Minnesota. These 

methods should be applicable to the determination of 

imports and exports for any other state and to regions, if 

data at that level can be obtained. To facilitate following 

the method described below the appropriate tables from 

the CFS should be referred to when needed. If the data 

tables or presentation of information change in the 

future these instructions will have to be altered. 

Export Calculations 

Determining material and energy flows for exports is 

straightforward with few extrapolations or assumptions 

needed, because the data are relatively complete as 

provided in the CFS. Data on dollar value and tonnage 

of export shipments between states by commodity class 

comes from the Commodity Flow Survey (CFS), Table 

12 (Additional State Data). This data is also summarized 

in Tables 5, 7, and 8 in the CFS report on each state.

The CFS uses several data codes when a numeric 

measurement is not given and these codes were handled 

in a consistent manner. For example, most states have an 

S or a D in one or more data fields for some commodity 

shipments. These letters indicate variable data (S) or a 

single source of information (D) that would risk 

disclosure of the data source, if reported. In the export 

calculation method, no estimate of exports was made for 

commodity classes with and S or D in both the $ value 

and tonnage columns for instate shipments. When this 

occurs there is often an S or a D in the “all destinations” 

category, as well. In this case there are too many 

unknowns to make an estimate. Materials moving in 

these classes were assumed to remain within the state or 

to constitute a negligible fraction of exports. 

Commodities with a dollar value but no information on 

tonnage were retained in the data because the tonnage 

could be reasonably estimated using the price per ton 

obtained from the dollar value and tonnage of the 

commodity going to all destinations. 

Before transferring data from Table 12 to an interim 

spreadsheet, all dashes (indicating no data) were 

replaced with zeroes. If there was evidence that some 

flows were not actually zero, remain uncounted, or are 

different from the estimates provided, additional 

information was added when the emergy exported in 

each commodity class was determined. For example, 

coal exports were determined using Energy Information 

Administration (EIA) Data (6). The Commodity Flow 

Survey provides a summary table (Table 7) of shipments 

to all states from the state of origin. Note that the top 

row in this table gives the total dollar value and tonnage 

of shipments from the state followed by a set of rows for 

dollar value and tonnage shipments to each state to 

which the state of origin is shipping. This includes a 

row for the state of origin itself, which will be referred 

to as instate shipments from now on.

The commodity classes for Standard classification of 

Transported goods (SCTG), Standard Industrial 

Classification (SIC), and the North America Industry 

Classification System (NAICS) industry classification 

codes and the approximate conversions used in this 

paper are shown in Table D1. An export table (see Table 

D2) with 11 columns was made to use in determining 

the tonnage exported in various commodity classes. The 

column headings for the export table are as follows (1) 

SCTG code, (2) Description of the class, (3) All 

Destinations Value($ mil), (4) All Destinations 

Tons(000), (5) $/Ton, (6) Instate Shipments ($ mil), (7) 

Instate Shipments Tons(000), (8) Known (directly 

measured) exports Tons(000), (9) Instate Tons (000) 

estimated using $/T, (10) Estimated exports tons (000), 

(11) Final Exports (estimated exports are adjusted to 

sum to the total missing tonnage).Table D2 omits 

column 2, the verbal description, because of space 

considerations. 
 Environmental Accounting Using Emergy: Minnesota 

128 

Table D1 Approximate conversion between SCTG , SIC and NAICS industry classification codes developed 

for this study. These conversions are only approximate and better information might be 

developed of used if available.

Class Combined Code SCTG code SIC code NAICS Code 

Agricultural products, grain A 2,3 1 111 

Livestock, seafood, animal products B 1,4 2,9 112 

Logs, rough wood C 25 8 113 

Metallic ores D 14 10 2122 

Coal E 15 12 2121 

Non-metallic minerals, gravel, stone, 

sand 

F 11,12,13 14 2123 

Prepared food products, alcohol, 

tobacco 

G 5,6,7,8,9 20,21 311,312 

Textiles, leather, apparel H 30 22,23,31 313 

Lumber wood product I 26 24 321 

Furniture, fixtures J 39 25 337 

Paper products K 27,28 26 322 

Printed products L 29 27 323 

Chemicals M 20,21,22,23 28 325 

Refined petroleum products N 17,18,19 29 324 

Plastics and rubber O 24 30 326 

Building materials, non-metallic P 10,31 32 327,331 

Primary metal products, semi-finished Q 32 33 331 

Fabricated metal products. Cans etc. R 33 34 332 

Machinery (not electrical) S 34 35 333 

Electrical equipment, precision 

instruments 

T 35.38 36,38 334,335 

Transportation equipment U 36,37 37 336 

Miscellaneous manufactured goods V 40 39 339 

Scrap and waste W 41 49 562 

Unknown, mixed or special classes Y 43 92,98,99 99999 

The steps in estimating exports from a state, e.g., Minnesota, using the data in the spreadsheet columns described 

above are as follows: 

First, copy the Commodity Class code and description from the Commodity Flow Survey Table 12 (Additional 

Data) for the state, for which exports are to be calculated Columns (1 and 2). Remember in following the 

instructions below that column numbers refer to the 11 column headings recommended above. The 10 columns 

shown in Table D2, which is missing column 2, have been numbered to match the verbal description. 

1. Copy the $ value and tons moving from the state to all destinations for all commodities, Columns (3) and (4). 

2. Calculate or otherwise determine the $ per ton. Column (5) 

3. Copy data ($ and Tonnage) for shipments of all commodities with final destination in the state of origin, e.g., 

from MN to MN, Columns (6) and (7). 

4 Calculate known exports by subtracting instate shipments (column 7) from the shipments moving to all 

destinations (column 4) for all commodities for which tonnage has been measured, directly, Column (8). 

5. Sum the tonnage of directly measured export shipments (Column 8) and subtract from the total tonnage moving 

to all destinations. The total tonnage is given at the top of the All Destinations column in Table D2 and in CFS 

Table 12. 
Appendix D 

129 

6. Calculate the tonnage of instate shipments for any commodity for which a $ value of instate shipments is given 

in column 6 by dividing by the $ per ton (column 5). Record in Column 9 the estimated instate shipments. 

7 Estimate the tonnage exported in these commodity classes by subtracting the instate tonnage estimates (column 

9) from tonnage moving to all destinations (column 4). Record these estimates in Column 10. 

8. Sum the estimated export shipments (column 9) and divide into the difference between directly measured 

exports and total exports. If this ratio equals 1 combine directly measured and estimated exports in their 

respective commodity classes into a single column (11) and you are done. If greater or less than 1 multiply each 

estimated commodity by this ratio to adjust the flows so that directly measured and estimated exports will sum 

to the known tonnage of total exports shipped to all destinations. Record these numbers in Column (11), Final 

Adjusted Exports, and fill in column with the directly measured values from Column (8). 

 

Table D2. Calculation of Minnesota Exports from the state to state commodity shipments found in the 

Commodity Flow Survey as Additional Data in Table 12. 

SCTG 

Code 

All 

Destinations 

Value($ mil) 

All 

Destinations 

Tons(000) $/ton 

Instate 

Value 

(mil $)

Instate 

Tons (000)

Directly 

Measured 

Exports 

Estimate 

Instate 

Tons(000) 

Estimate 

State 

Exports 

Final 

Adjusted 

Exports 

Col. 1 Column 3 Column 4 Col. 5 Col. 6 Col. 7 Col.8 Col.9 Col. 10 Col. 11 

Total 35570 233760 8336 66249 167511 167511

1 - - 0 - - 0 0

2 - - 0 - - 0 0

3 S S 356 S S S S 0

4 129 467 276 87 438 29 29

5 609 259 2351 50 21 238 238

6 29 14 2071 20 11 3 3

7 223 S 843 S S S S 0

8 365 351 1040 365 351 0 0

9 440 19 23158 177 7 12 12

10 S S 94 S S S S 0

11 32 793 40 4 347 446 446

12 53 5667 9 51 5484 183 183

13 S S 29 S S S S 0

14 S S 689 S S S S 0

15 4943 187835 26 1107 44488 143347 143347

17 393 S 272 S S S S 0

18 227 964 235 224 954 10 10

19 532 3335 160 78 163 3172 3172

20 3918 5152 760 425 897 4255 4255

21 1996 S 32716 S S S S 0

22 S S 216 S S S S 0

23 1512 946 1598 518 290 656 656

24 2582 1316 1962 485 387 929 929

25 370 5627 66 132 S S 2007 3620 3406

26 900 3869 233 216 1045 2824 2824

27 69 108 639 S S S S 0

28 123 87 1414 58 S S 41 46 43

29 483 S 2499 S S S S 0

30 S S 9097 S S S S 0

31 937 5007 187 263 3658 1349 1349

32 4158 6306 659 449 S S 681 5625 5294

33 860 851 1011 525 465 386 386
 Environmental Accounting Using Emergy: Minnesota 

130 

Table D2 Continued

SCTG 

Code 

All 

Destinations 

Value($ mil) 

All 

Destinations 

Tons(000) $/ton 

Instate 

Value 

(mil $) 

Instate 

Tons (000)

Directly 

Measured 

Exports 

Estimate 

Instate 

Tons(000) 

Estimate 

State 

Exports 

Final 

Adjusted

Exports 

 

34 2109 187 11278 483 48 139 139

35 1326 120 11050 242 S S 22 98 92

 

36 2900 519 5588 212 S S 38 481 453

37 320 S 10622 S S S S 0

38 234 2 117000 S - S S 0

39 159 45 3533 57 12 33 33

40 692 134 5164 140 S S 27 107 101

41 S S 148 S S S S 0

43 794 425 1868 605 314 111 111

-- 99 38 2605 S S S S 0

Class Totals 158122 9977 167511

Difference (Total - Class Total from Column 7 in this Table. 9389 

Fraction (Difference/Class Total (Column 7/Column 9 this 

table) 0.941 

Import Calculations

Table 12 from the CFS web site, “Additional State 

Data”, used in the export calculation, has information on 

the exports by commodity class going from all the other 

states to the state of destination (Minnesota). Data from 

the other 49 states that might be exporting to Minnesota 

were combined to determine imports. Inbound 

shipments by state of origin to the state of destination 

are summarized in Table 8 of the CFS, but commodity 

classes are not shown. For states without a U.S. 

Customs port, state to state commodity shipments will 

capture almost everything entering the state for use or 

transshipment. When one or more U.S. customs ports 

are located in a state the accounting becomes more 

difficult. Should the foreign imports be added, if they 

are destined for other places and are thus immediately 

exported to another state? If the majority of imports 

entering through a major port belong to some other 

place the international flows could greatly exceed the 

interstate flows and lead to large errors in our estimates. 

We assume that most international shipments pass 

through Minnesota and do not pertain to the state’s 

economy, thus our estimate of Minnesota imports will 

be conservative, because some unknown fraction of the 

international flows will be used in Minnesota directly. 

The inbound tonnage shipped in each commodity 

category was used to calculate the emergy imported in 

goods. The five steps used to estimate imported emergy 

to a state are as follows: (1) a quick tally of the total 

tonnage coming into the state from other states was 

obtained by consulting Table 8 in the CFS report. The 

states that had a number entered in the percent of total 

inbound shipments column were identified. The total 

percentage of imports directly measured was determined 

by summing the percentages. The total percent of 

tonnage from the states used to estimate imports should 

be at least 95% of the tonnage of total inbound 

shipments. (2) Once the subset of states exporting to the 

study state was identified, missing values for the 

tonnage for specific commodities coming from each 

state were estimated. (3) If a dollar value of the inbound 

commodity shipments was known and tonnage was not 

listed, the tonnage was estimated based on the cost per 

ton as described above and shown in Table D2. A large 

fraction of total inbound shipments from some states 

had missing values for both dollar value and tonnage (an 

S or D entered into the field). In this case, the missing 

data would have resulted in large errors in the estimate 

of total imports and thus the development of a method to 

handle this situation was warranted. The tonnage fields 

for inbound shipments from a state of origin to 

Minnesota containing and S or a D were handled by 

assuming that a state’s exports to any other state would 

on average follow its overall export profile, i.e., the 

fraction of total shipments accounted for by each 

commodity. Missing tonnage data was distributed 
Appendix D 

131 

among commodity classes by adjusting the overall 

export profile. The missing tonnage is equal to total 

shipments to Minnesota from the state minus 

commodities with numeric entries for tonnage. This 

tonnage was distributed among the commodity classes 

with inbound shipments by adjusting using the state’s 

overall export profile so that the unknown inbound 

shipments made up 100% of the missing inbound 

tonnage. (4) The inbound tonnage in each commodity 

class for a state was transferred as a single column to a 

second worksheet with data from all of the identified 

import states. (5) Then each commodity class was 

summed across the rows for all states to create the 

column of data with imported tonnages in each 

commodity class for the emergy table. 

1. The following steps describe the estimation of the 

unknown tonnage (S and D) as illustrated for 

Alabama’s shipments to West Virginia (our original 

example) shown in Table D3. For all of the states 

importing to the study state, copy the total tonnage in 

each commodity class exported to all destinations 

and the tonnage exported to the state you are 

evaluating (columns 2 and 3 in Table D3), onto a 

spreadsheet.. 

2. Calculate the price per ton for all inbound shipments 

by commodity class from any state exporting to the 

study state according to the instructions given above 

for exports. 

3. Replace all dashes with a zero. Although Table D3 

only presents one state, the same procedure will be 

used for all states sending a significant quantity of 

imports to the study state. 

4. Next, missing tonnage values are estimated for any 

commodity class that reported a dollar value of 

exports to the state but no tonnage. In some cases 

calculating the price per ton for the state of origin is 

not possible, but there is still a dollar value for 

exports. Prices per ton can be quite variable but find 

an adjacent state (or use a better estimation method) 

and substitute this price in the spreadsheet making a 

note on its origin. Fill in all tonnage movements 

possible using this method. Combine the tonnages 

estimated on the basis of average price with the 

tonnages that were directly measured. Sum this 

column and subtract from the total tonnage exported 

to the study state to get the tonnage that will be 

distributed using the export profile (see the number 

in italics at the top of column 4 in Table D3). For 

example, the total export from Alabama to West 

Virginia is 318 thousand tons but the sum of all 

commodities determined directly and estimated 

based on dollar value only adds up to 27 thousand 

tons, the difference is then 291 thousand tons. 

5. Create a fourth column for the export profile, which 

will be used to distribute the missing tonnage across 

the remaining commodities that had either an S or D 

in both the dollar value and tonnage fields. The 

export profile is the fraction of the total tonnage 

accounted for by each commodity as determined 

from the shipments to all destinations. Calculate the 

profile by dividing the tonnage for each commodity 

exported by the total tonnage exported for that state. 

Only those commodities that have an S or D in both 

dollar value and tonnage fields are recorded in 

column 4. Sum the fractions to determine the fraction 

of total tons accounted for by the commodities with 

missing data. 

6. The next step is to adjust these fractions to represent 

the expected fractions of the missing tonnage 

imported to the state in each commodity class with 

missing data. Create a fifth column, the adjusted 

fraction of missing tonnage imported in each class, 

where each fraction of the tons in the export profile 

(individual values in column 4) will be divided by 

the fraction of the total tons that is missing (the sum 

of all fractions in column four). The sum of all 

values in column 5 should equal one, or 100%. 

7. In the last column (column 6), copy over the reported 

and estimated data for tonnage for any commodity 

where it is available from column 3. For all of the 

missing commodities (those with and S or D in both 

the $ value and tonnage fields), multiply the total 

missing tonnage (at the top of Column 4) by the 

corresponding percentage (in Column 5) for each 

commodity class known to have a flow but for which 

tonnage is unknown, and transfer this number to the 

appropriate field in column 6. For example, if data is 

missing for textiles, multiply 291 thousand tons by 

the fraction of textiles or 0.0172, to get 5 thousand 

tons textiles imported. Sum this column to make 

sure it adds up to the total tonnage. 

8. Transfer this tonnage data for each commodity to an 

import table creating a column for each state. 

9. Sum across the states (rows) for each commodity to 

find the total tonnage imported in each commodity 

class and transfer this to the import section of the 

emergy evaluation. 
 Environmental Accounting Using Emergy: Minnesota 

132 

Use Table D1 or better conversion system to convert from NAICS to SCTG code. Create a column for this data and 

include it in the summation of imports described in step 9 above. 

Table D3: Our original example of estimating missing import data. Alabama to West Virginia. 

Description 

Total Tons 

from 

Alabama 

(thousands)

Tons to 

WV 

(thousands)

Fraction 

of total 

tons for 

missing 

data 

Fraction 

of 

missing 

tonnage 

to WV 

Total Tons 

to WV 

(thousands)

 All commodities 256234 318 291 

Live animals and live fish 125 - 0.0 

Cereal grains S - 0.0 

Other agricultural products 1682 - 0.0 

Animal feed and products of animal 

origin 7194 S 0.028 0.059 17.2 

Meat, fish, seafood, and their 

preparations 1836 S 0.007 0.015 4.4 

Milled grain and bakery products 386 S 0.002 0.003 0.9 

Other prepared foodstuffs and fats and 

oils 4408 S 0.017 0.036 10.5 

Alcoholic beverages 482 - 0.000 0.0 

Tobacco products 51 S 0.000 0.000 0.1 

Monumental or building stone S - 0.000 0.0 

Natural sands S - 0.000 0.0 

Gravel and crushed stone 36211 - 0.000 0.0 

Nonmetallic minerals 2905 S 0.011 0.024 6.9 

Metallic ores and concentrates S - 0.000 0.0 

Coal 30993 - 0.000 0.0 

Gasoline and aviation turbine fuel 12659 - 0.000 0.0 

Fuel oils 3605 - 0.000 0.0 

Coal and petroleum products, 4671 S 0.018 0.038 11.1 

Basic chemicals 7460 S 0.029 0.061 17.8 

Pharmaceutical products 33 S 0.000 0.000 0.1 

Fertilizers 2382 S 0.009 0.020 5.7 

Chemical products and preparations 1271 S 0.005 0.010 3.0 

Plastics and rubber 1585 S 0.006 0.013 3.8 

Logs and other wood in the rough 40817 S 0.159 0.334 97.3 

Wood products 12443 S 0.049 0.102 29.7 

Pulp, newsprint, paper, and 

paperboard 8949 S 0.035 0.073 21.3 

Paper or paperboard articles 977 - 0.000 0.0 

Printed products 324 S 0.001 0.003 0.8 

Textiles, leather, and articles of 

textiles or leather 2120 S 0.008 0.017 5.1 

Nonmetallic mineral products 16613 S 0.065 0.136 39.6 

Base metal in primary or semi finished 

forms and in finished basic shapes 11212 17 17.0 

Articles of base metal 4208 S 0.016 0.034 10.0 

Machinery 753 1 0.000 1.0 

Electronic and other electrical 

equipment and components 688 S 0.003 0.006 1.6 
Appendix D 

133 

Motorized and other vehicles 

(including parts) 957 S 0.004 0.008 2.3 

Transportation equipment 251 S 0.001 0.002 0.6 

Precision instruments and apparatus 10 - 0.000 0.0 

Furniture, mattresses and mattress 

supports, lamps, lighting fittings, 

and... 501 S 0.002 0.004 1.2 

Miscellaneous manufactured products 2965 9 9.0 

Waste and scrap 2130 - 0.0 

Mixed freight 2000 - 0.0 

Commodity unknown S - 

subtotals to check 27 0.476 1.000 318 

Custom’s Imports

Our present view on customs data is that the portion 

of these imports that are used within the state is captured 

by the CFS data. Including these flows that really 

pertain to the whole nation in the analysis of an 

individual state alters the indices so they are not longer 

comparable to states without customs facilities. 

Nevertheless, we repeat our original instructions for 

obtaining customs’ data in case it is of interest in a 

particular analysis. If the state has a Customs’ port, 

locate the appropriate data on the USITC data web site 

(37). The Customs’ site requires a password, but 

registration is free. To get the correct data report, a 

series of dialogue boxes must be completed. The 

choices that should be made are as follows: 

• Dialogue 1 – U.S. General Imports; NAICS code; 

current US Trade 

• Dialogue 2 – Customs value; 1997; All import 

commodities; All countries; All country sub-codes; 

create new district list 

 Enter the name, select the districts, then highlight the 

name when you return to original page; 

 In 1,000,000; annual; NAICS 3 digit; aggregate all 

countries together; aggregate import programs; 

display districts separately 

• Dialogue 3 – Arrange in this order: District; NAICS 3 

• Dialogue 4 – District; General customs value; Show 

all; Sort 1997; 5000 records; other display options are 

optional 
 Environmental Accounting Using Emergy: Minnesota 

134 

Appendix E 

Minnesota Emergy Accounts for 2000 
Appendix E 

135 

Table E1. Annual Renewable Resources and Production in 2000. 

Note* Item 

Data 

J, g, $, ind/yr Units 

Emergy/ 

Unit 

sej/unit 

Emergy 

E+20 sej 

2000 

Emdollars 

E+6 Em$ 

Renewable Resources within Minnesota 

1 Sun, Incident 1.07E+21 J 1 10.74 456.9 

1 Sun, Absorbed 8.84E+20 J 1.21 10.74 456.9 

2 Wind Kinetic Energy 1.26E+19 J 1,467 185.47 7892.3 

3 Earth Cycle Energy 2.80E+17 J 33,720 94.35 4014.7 

4 Rain, Chemical Potential Energy Received 7.07E+17 J 18,100 127.95 5444.6 

5 Evapotranspiration, Chemical Potential Absorbed 3.14E+17 J 28,100 88.30 3757.5 

6 Rain, Geo-Potential On Land 4.58E+17 J 10,100 46.23 1967.1 

6 Snow, Geo-Potential On Land 7.22E+16 J 101,100 73.04 3108.1 

7 Rain, Geo-Potential Of Runoff 2.55E+16 J 27,200 6.93 294.9 

7 Snow, Geo-Potential Of Runoff 4.67E+16 J 101,100 47.19 2008.0 

8 Wave Energy (Lake Superior) 1.55E+16 J 30,000 4.66 198.1 

9 Rivers, Chemical Potential Energy Received 9.15E+15 J 50,100 4.58 195.0 

9 Rivers, Chemical Potential Energy Absorbed 6.44E+12 J 50,100 0.003 0.1 

10 Rivers, Geo-Potential Energy Received 5.09E+15 J 27,200 1.39 59.0 

10 Rivers, Geo-Potential Energy Absorbed 1.51E+15 J 27,200 0.41 17.4 

11 NH4-N In Dry/Wet Deposition 1.55E+11 g 1.4E+09 2.15 91.6 

11 NO3-N In Dry/Wet Deposition 4.44E+10 g 6.8E+09 3.04 129.2 

 Total N Deposition 2.00E+11 g Variable 5.19 220.8 

12 S In Dry/Wet Deposition 5.26E+10 g 1.58E+11 83.18 3539.9 

13 Cl In Dry/Wet Deposition 8.81E+09 g 1.31E+10 1.15 49.1 

 

 Minnesota 

14 Agricultural Products 7.00E+17 J Variable 2,632.5 112023.1 

15 Livestock 5.97E+16 J Variable 533.8 22714.9 

16 Fish Production 1.32E+11 J 1,961,800 0.003 0.1 

17 Hydroelectricity and Other Renewable 1.07E+16 J 120,300 12.9 548.2 

18 Net Timber Growth 1.28E+17 J 20,600 26.4 1124.5 

19 Timber Harvest 6.40E+16 J 68,700 43.9 1869.5 

20 Groundwater Chemical Potential 4.61E+15 J 159,100 7.3 311.9 

21 Solid Waste Recycled or Recovered 3.28E+12 g 6.28E+09 206.2 8772.8 

* The notes for Table 4 can be found in Appendix C at C.1. 
 Environmental Accounting Using Emergy: Minnesota 

Table E2. Annual Production and Use of Nonrenewable Resources in 2000. 

Note* Item 

Data 

J, g, $, ind/yr Units 

Emergy/Unit

sej/unit 

Emergy 

E+20 sej 

2000 

Emdollars 

E+6 Em$ 

Fuels and renewables used in a nonrenewable manner 

22 Coal Used In The State 5.53E+17 J 37,800 209.1 8899.7

23 Natural Gas Used In The State 3.98E+17 J 43,500 173.2 7370.9

24 Petroleum Used In The State 7.20E+17 J 64,800 466.8 19865.4

25 Electricity Production 1.74E+17 J 170,400 297.0 12636.6

26 Electricity Used In The State 2.15E+17 J 170,400 366.4 15592.9

27 Nuclear Electricity 4.67E+16 J 170,400 79.5 3383.1

28 Iron Ore Mined 4.67E+13 g 3.51E+9 1639.0 69745.5

29 Sand And Gravel 3.95E+13 g 1.31E+9 517.5 22019.1

30 Limestone 6.40E+12 g 9.81E+8 63.8 2671.4

31 Dolomite 3.37E+12 g 1.08E+10 363.3 15460.6

32 Peat 7.50E+10 g 3.53E+8 0.3 11.3

33 Soil Erosion 9.79E+16 J 72,600 71.1 3023.6

* The notes for Table E2 can be found in Appendix C at C2. 

Table E3. Annual Imports to the Minnesota Economy in 2000.

Note* Item 

Data 

J, g, $, ind/yr Units

Emergy/Unit 

sej/unit 

Emergy 

E+20 sej 

2000 Emdollars

E+6 Em$ 

34 Tourism (Money Imported) 9.00E+09 $ 2.35E+12 211.5 9000.0 

35 Electricity 3.01E+16 J 1.70E+05 51.3 2182.0 

36 Uranium 2.94E+09 g 4.66E+11 13.7 583.1 

37 Coal 5.53E+17 J 3.78E+04 209.1 8899.7 

38 Petroleum 7.20E+17 J 6.48E+04 466.8 19865.4 

39 Natural Gas 3.98E+17 J 4.35E+04 173.2 7370.9 

40 Minerals 1.06E+13 g variable 106.0 4512.6 

41 Goods (Materials) 3.92E+13 g variable 2747.9 116930.0 

42 Goods (Services) 6.60E+10 $ 2.35E+12 1550.5 65977.0 

43 Fuels (Services) 5.51E+09 $ 2.35E+12 129.5 5509.2 

44 Minerals including Uranium (Services) 4.78E+08 $ 2.35E+12 11.2 477.9 

45 Electricity (Services) 6.22E+08 $ 2.35E+12 14.6 621.7 

46 Services 4.22E+09 $ 2.56E+12 108.1 4598.8 

47 Immigration 8.67E+03 Ind. variable 4.2 180.5 

48 Federal Government Outlays 

(If spent in US) 2.24E+10 $ 2.35E+12 526.2 22391.9 
Appendix E 

137 

Table E4. Annual Exports from the Minnesota Economy in 2000.

Note* Item 

Data 

J, g, $, ind/yr Units

Emergy/Unit

sej/unit 

Emergy 

E+20 sej 

2000 Emdollars

E+6 Em$ 

49 Goods w/o Iron Ore and Fuels (Materials) 7.37E+13 g mixed 3855 164037.5 

50 Iron Ore as Taconite 3.57E+13 g 3.61E+09 1290.4 54909.2 

51 Goods (Services) 9.46E+10 $ 2.35E+12 2223.0 94597.0 

52 Services 1.36E+09 $ 2.35E+12 31.9 1356.7 

53 Federal Government Taxes (Spent in the 

US) 2.85E+10 $ 2.35E+12 668.8 28460.0 

54 Tourists (Experiences Taken Home) 9.00E+09 $ 3.97E+12 357.3 15202.9 

* The notes for Table E4 can be found in Appendix C at C4. 

Table E5. Assets of Minnesota in 2000.

Note* Item 

Data 

J, g, $, ind/yr Units 

Emergy/Unit

sej/unit 

Emergy 

E+20 sej 

2000 Emdollars

E+6 Em$ 

55 Forest Biomass Storage 6.26E+18 J 28,200 1767 75,202 

56 Water (Lakes) 6.76E+17 J 18,100 122 5,206 

57 Water (Lake Superior) 3.30E+17 J 2.40E+05 792 33,692 

58 Soils 9.42E+19 J 72,600 68375 2,909,574 

59 Iron 1.40E+16 g 3.51E+09 490324 20,864,869 

60 Sand & Gravel 3.19E+16 g 1.31E+09 417826 16,321,327 

61 Limestone 2.82E+15 g 9.81E+08 27661 1,177,080 

62 Dolomite 1.32E+14 g 1.08E+10 14231 605,577 

63 Copper 4.50E+15 g 1.14E+11 5115002 217,659,670 

64 Nickel 4.50E+15 g 2.55E+10 1147664 48,836,772 

65 Peat 7.57E+19 J 1.86E+04 14100 599,999 

66 Platinum 2.90E+13 g 1.13E+11 32728 1,392,699 

67 People 329605 Ind. Various 12738 542,061 

 Preschool 2402204 Ind. 3.34E+16 110 4678 

 School 1882631 Ind. 9.22E+16 2215 94253 

 College Grad 255844 Ind. 2.75E+17 5171 220029 

 Post-College 49195 Ind. 1.28E+18 3288 139895 

 Public Status 765 Ind. 3.85E+18 1896 80699 

 Legacy 329605 Ind. 7.70E+18 59 2507 

 

* Evaluation notes for Table E5 are given in Appendix C at C5. 
Table E6. Summary of Flows for Minnesota in 2000.

Note 

Letter in 

Fig. 2 Item 

Emergy 

E+20 sej 

2000 

Dollars 

E+9 $/y 

2000 

Emdollars 

E+9 Em$/y 

68 RA Renewable Sources Used 191 8.1 

69 R1 Renewable Electricity 13 0.5 

70 N Nonrenewable Source Flows 2654 112.9 

71 N1' Extracted Fuels and Minerals 2583 109.9 

72 N0 Dispersed Rural Source 71 3.0 

73 N1 Concentrated Use (from state) 1385 58.9 

74 N2 Exported (without full use) 1290 54.9 

75 F Imported Fuels and Minerals) 1020 43.4 

76 F1 Fuels, Minerals Used (F+F2) 2313 98.4 

77 F2 In State Minerals Used (N1'-N2) 1292 55.0 

78 G Imported Goods (Materials) 2748 116.9 

79 I Dollars Paid For All Imports 82.3 

80 I1 Dollars Paid For Service In Fuels 6.9 

81 I2 Dollars Paid For Service In Goods 70.8 

82 I3 Dollars Paid For Services 4.6 

83 I4 Dollars Spent By Tourists 9.0 

84 I5 Federal Transfer Payments 22.4 

85 P2I Imported Services Total 1933 82.3 

86 P2I1 Imported Services In Fuels 161.5 6.9 

87 P2I2 Imported Services In Goods 1664 70.8 

88 P2I3 Imported Services 108 4.6 

89 P1I4 Emergy Purchased By Tourists 357 15.3 

90 P1I5 Net Emergy Purchased By Fed. $ -241 -10.3 

91 B Exported Products w/o Taconite 3855 164.0 

92 E Dollars Paid For All Exports 104.2 

93 E1 Dollars Paid For Goods 101.5 

94 E2 Dollars Paid For Mineral Exports 1.3 

95 E3 Dollars Paid For Services 1.5 

96 E4 Federal Taxes Paid 28.5 

97 P2E Total Exported Services 2449 104.2 

98 P2E1 Exported Services In Goods 2385 101.5 

99 P2E2 Exported Services In Iron 30.1 1.3 

100 P2E3 Exported Services 34.2 1.5 

101 X Gross State Product 185.1 

102 P2 Emergy/ $ Ratio U.S. 2000 sej/$ 2.35E+12 

103 P1 Emergy/ $ Ratio MN 2000 sej/$ 3.97E+12 
Appendix E 

139 

Table E7. Minnesota Emergy Indicators and Indices for 2000.

Item Name of Index Expression Quantity Units 

104 Renewable Use RA 1.91E+22 sej y-1

105 In State Non-Renewable Use N0 + N1 1.46E+23 sej y-1

106 Imported Emergy F + G + P2I 5.70E+23 sej y-1

107 Total Emergy Inflows R + F + G + P2I 5.89E+23 sej y-1

108 Total Emergy Used U = (RA+N0+F1+G+ P2I) 7.35E+23 sej y-1

109 Total Exported Emergy B+ P2E +N2 7.59E+23 sej y-1

110 Emergy Used From Home Sources (N0+F2+ R)/U 0.21 

111 Imports-Exports (F+G+ P2I)-(B+P2 E+N2) -1.89E+23 sej y-1

112 Ratio Of Export To Imports (B+P1E+N2)/(F+G+P2I) 1.33 

113 Fraction Used, Locally Renewable R /U 0.026 

114 Fraction Of Use Purchased Outside (F + G + P2I)/U 0.778 

115 Fraction Used, Imported Service P2I/U 0.271 

116 Fraction Of Use That Is Free (R+N0)/U 0.036 

117 Ratio Of Purchased To Free (F1+G+P2I)/(R+N0) 26.73 

118 Environmental Loading Ratio (F1+N0+G+P2I)/R 37.08 

119 Investment Ratio (F+G+P2I)/(R+N0+F2) 3.67 

120 Use Per Unit Area U/Area 3.26E+12 sej/m2

121 Use Per Person U/Population 1.49E+17 sej/ind. 

122 Renewable Carrying Capacity (R/U)*(Pop.) 127,574 people 

123 Developed Carrying Capacity 8*(R/U)*(Population) 1,020,589 people 

124 MN State Econ. Product GSP 1.9E+11 $/yr 

125 Ratio MN Emergy Use To GSP U/GSP 3.97E+12 sej/$ 

126 Ratio U.S. Emergy Use To GNP U/GNP 2.35E+12 sej/$ 

127 Ratio Electricity Use/Emergy Use El/U 0.047 J/sej 

128 Ratio Elec. Prod./Emergy Use Elp/U 0.034 J/sej 

129 Emergy Fuel Use Per Person F2/Population 1.73E+16 sej/ind 

130 Population 4,919,479 people 

131 Area 2.25E+11 m2

132 Renewable Empower Density 8.46E+10 sej/m-2

EPA/600/R-09/002 Environmental Accounting Using Emergy: Evaluation of Minnesota 


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