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Final Report
EMERGY EVALUATION OF ENERGY POLICIES FOR FLORIDA
Report to the Florida Energy Office
By
M.T. Brown, H.T. Odum, G. McGrane, R.D. Woithe, S. Lopez, and S. Bastianoni
Center for Environmental Policy
Department of Environmental Engineering Sciences
University of Florida
Gainesville, FL 32611
(352) 392-0847
January 31, 1995
Table of Contents
Page
Executive Summary------------------------------------------------------------------- i
1. Concepts and Methods of EMERGY Evaluation of Policies
M.T. Brown and H.T. Odum--------------------------------- ---------------- 1-1
2. Transformity of Alternative Energy Sources
H.T. Odum and M.T. Brown------------------------------------------------- 2-1
3. EMERGY Evaluation of Alternative Fuels for Transportation
H.T. Odum, G.G. McGrane, M.T. Brown, S. Bastianoni-------------------------- 3-1
4. Hurricane Andrew: EMERGY Analysis of Dade County, the
Hurricane Impact Area and Evaluation of Damages and Costs.
M.T. Brown and R.D. Woithe --------------------------------------- --------- 4-1
5. South Dade County: EMergy Analysis of Rebuilding Options
after Hurricane Andrew. M.T. Brown and S. Lopez-------- --------------------- 5-1
Literature Cited------- ------------------------------------------------ Ref-1
Appendix A. EMERGY Evaluation of Ethanol and Biogas-Methane
M.T. Brown and S. Bastianoni--------------------------- ------------------A-1
Appendix B. EMERGY Evaluation of Dade County's Metro Rail
M.T. Brown---------------------------------------- -------------------------- B-1
Appendix C. Notes to EMERGY Evaluation of Dade County and Hurricane Impact Area
R.D. Woithe------------------------------- -----------------------------C-1
Appendix D. Notes to EMERGY Evaluations of Carrying Capacity in South Dade.
S. Lopez------------------------------------- ---------------------------------- D-1
Executive Summary
This is a final report of the findings of EMERGY analysis evaluations of alternatives for
energy use and development in Florida. First, evaluations are given of alternative systems for
supplying fuels for transportation, including hydrogen, fuel cells, electricity, ethanol from sugar
cane, methane, and natural gas. A mass transit alternative, Dade County's Metro Rail, was also
evaluated. Second, EMERGY evaluation was made of alternative plans for the redevelopment of
areas of south Florida devastated by hurricane Andrew.
EMERGY Evaluation Methods
The best uses of resources and environment in a process can be analyzed by calculating the
EMERGY (spelled with an "m") of all the inputs, including those received free from the
environment and those supplied by the economy. EMERGY is the sum of all inputs, expressed as
one form of energy, required directly and indirectly to make a product or service. Its unit is the
emjoule. As a common measure of real wealth, EMERGY measures everything: fuels, materials,
services, information, etc. Based on the concept that successful, prevailing systems maximize
wealth, production and use of real wealth, alternatives can be chosen for maximum EMERGY
flow.
The procedure for evaluating a process has the following steps:
1. Define the boundary and make a systems diagram of sources, components, processes
and products, arranged from left to right in order of transformity.
2. Prepare EMERGY evaluation tables with a line item for each item identified in the
systems diagram. Determine total EMERGY flows, storage, and yields of line
items. Determine emdollar (Em$) equivalents of EMERGY values. An Em$ is the
proportion of gross economic product determined from the proportion of the
national EMERGY budget. Microcomputer simulation models of the system may
be run, which generate trends over time for different assumptions and alternatives.
EMERGY, Em$, and transformity graphs may be generated by these simulations.
3. Compare results using EMERGY indices such as net yield ratios, investment ratios,
exchange ratios, EMERGY/money ratios, etc. Recommend for policy choice those
alternatives which contribute the most real wealth, measured by EMERGY, to the
combined system of environment and economy.
4. For primary energy sources, use the net EMERGY yield ratio to select the ones that
contribute most. For determining what uses are appropriate for an energy type, use
the transformity. For necessary processes that consume the primary sources, use
the EMERGY investment ratio to predict which are likely to be economical.
The transformity is defined as the EMERGY per unit, a measure of the position of
something in the scale of energy hierarchy. In order of increasing transformities are sunlight,
wind, rain, mechanical energy, wood, food, electric power, critical materials, drugs, human
service, information sources, and education. Tables of transformities from previous studies
simplify evaluations. Data on inputs are multiplied by their transformities to obtain EMERGY
flows. For determining which energy processes are most efficient for a desired output, the system
with the smallest transformity is used.
Evaluation of Alternative Fuels for Transportation
Alternative systems of supplying energy for transportation were evaluated for their
EMERGY flows. Pathways of energy transformation were evaluated. Sources were arranged
according to their Net EMERGY yield ratios, measuring their overall ability to contribute to the
economy. The efficiencies of various sources and pathways were evaluated using EMERGY per
unit energy and EMERGY per unit of transportation. The following are the preferred means of
transport, arranged in order of overall efficiency:
Bicycle
Compressed natural gas car
Gasoline car
Methanol fueled car
Metrortail
Hydrogen fueled car
Electric car with nickel-zinc batteries
Ethanol car
Public bus
Fuel cell electric car
The best transportation alternative uses about 1/3rd the resources the worst alternative uses.
Hydrogen
In the short range future, while there are available fossil fuels, hydrogen is not likely to
compete with natural gas or motor fuels made from fossil fuels for transport and general industrial
sources of concentrated heat, because the net EMERGY yield ratio of hydrogen is lower than that
of these other sources. In the long range future, after fossil fuels are scarce and expensive,
hydrogen requires too much EMERGY for a general fuel to be competitive, because too much
energy is required to make electricity first and then hydrogen. A possible exception is nuclear
energy if nuclear fuels are still available after the fossil fuels are gone. These conclusions are
based on emergy evaluations of a few cases and should be regarded as tentative until confirmed by
evaluation of more examples.
Hurricane Andrew
Emergy analysis of Dade county and the hurricane Andrew impact area for conditions prior
to the hurricane were conducted to develop insight into the magnitude of hurricane damage and
rebuilding efforts, and to provide the background for growth scenarios for the south Dade region.
As a result of the vast differences in population density and development status, the two
regions are quite different. Emergy use per unit area (Empower density) in Dade county, as a
whole, is nearly three times that which is characteristic of the hurricane impact area. On the other
hand because of the relatively low population density in south Dade, emergy use per capital is
nearly 20% greater than the average for the entire county. Low emergy empower density and high
per capital emergy use suggest higher than average natural emergy contribution to the economy of
south Dade.
Emergy analysis of the damages and costs resulting from hurricane Andrew revealed that
the damages to structure were equal to about 3 times the annual emergy flux within the impact
region. The clean up and reconstruction emergies (dominated by emergy of human services) were
nearly 60% greater than the damage incurred. By far, the greatest damage was to urban,
agricultural and social systems (about 86% of the total) while environmental systems comprised
about 14% of the total damages.
A macroscopic, simulation model was developed and simulated to test theories of the
relationship between order and disorder, and to evaluate the effects of better quality urban structure
on hurricane losses. With no hurricane input, total structure in both the urban and natural systems
was higher over the 250 year simulation period. Increased frequency of hurricanes, and/or
severity decreased total structure and production, and if post hurricane aid was not given, recovery
took longer and resulted in lower total structure and productivity.
A key question is related to the costs and benefits of increasing the quality of structure built
to withstand hurricanes. Theory would suggest that there should be an optimum quality of
structure for given hurricane forces and frequency. If the frequency of hurricanes is longer than
the life of the structure, it may not pay to build structure capable of withstanding the hurricane. On
the other hand, if the frequency is shorter than the life of structure, it may be beneficial to build less
structure of higher quality. Simulations of the model were conducted to test this optimization
strategy. Optimization suggested that increases of 4% in the total emergy "invested" in structure
yielded positive benefit/cost ratios for most hurricane intensities, 6% increases yielded positive
ratios for only the most intense hurricanes and greater increases in emergy invested in structure did
not yield positive results.
Emergy Analysis of Rebuilding Options After Hurricane Andrew
Rebuilding of south Dade after Hurricane Andrew has drawn much attention. There are
those who believe that it will be many years before the area once again reaches the level of
population and economic activity that it had prior to the storm. Others suggest that rebuilding will
be relatively quick. The ultimate question, however, is not how long will rebuilding take, but to
what level of urban structure and population density should the region be developed? In other
words, what is the carrying capacity of south Dade?
In this analysis the population carrying capacity of south Dade was evaluated under several
different scenarios. The basic driving premise for carrying capacity evaluations was to develop a
sustainable pattern of humanity and nature. To achieve a sustainable level of development, energy
resources obtained from outside the region must be matched with resources from within to provide
a resource base that is both well balanced and competitive. Carrying capacity was evaluated for
three levels of development: (1) a population levels sustainable on resources from within, (2) a
population level based on developing to the average level of empower density of the state of
Florida, and (3) population levels sustainable for full development at the density of northern Dade
county. In each case the resources required to sustain populations are evaluated and a hypothetical
spatial distribution of developed and natural lands based on EMergy principles are given.
1. Concepts and Methods of EMERGY Evaluation of Policies
M.T. Brown and H.T. Odum
EMERGY analysis is a method of energy analysis that accounts for the direct and indirect
use of energy in producing a commodity, resource, fuel, or service, in energy of one type. The
solar EMERGY in a resource, product, or service is the sum of the solar energies required to make
it. EMERGY includes both fossil fuel energies and environmental energies (like sunlight, rain,
tides, etc.) that are necessary inputs to most processes of energy transformation. Thus, the
EMERGY of an alternative fuel, such as alcohol made from sugar cane, includes: (1) the solar
energy "embodied" from natural sources in the sugar cane, (2) the EMERGY spent for goods and
services to grow the sugar cane and process it into alcohol, (3) the EMERGY of the fuel that was
burned by agricultural equipment and alcohol processing, and (4) the EMERGY value of labor.
EMERGY can be conceptualized as energy memory (Scienceman 1987, 1989), since it is a
measure of all of the energy previously required to produce a given product or process. The term
"EMERGY" differs from embodied energy as defined by other schools of thought. For example,
environmental inputs and labor are omitted by IFIAS (1974) and Slesser (1978), energies are
added without using transformities by Hall et al. (1984), and energies are assigned by input-output
data (usually money flows) with different results by Hannon et al. (1976), Herendeen et al.
(1975), and Costanza (1978).
EMERGY, Wealth and Economic Vitality
EMERGY is a quantitative measure of the resources required to develop a product (whether
a mineral resource that results from bio-geologic processes, a renewable resource such as wood, a
fuel source, or an economic product that results from industrial processes) and express the required
resources in units of one type of energy (usually solar). We suggest that evaluations using
EMERGY may help to clarify policy options, because the use of EMERGY as a measure of value
overcomes four important limitations of other methods for evaluating alternative fuels and
technologies. These limitations are as follows: (1) mixing units of measure such as weight,
volume, heat capacity, or economic market price cannot lead to comparative analysis; (2)
evaluations that use the heat value of resources for quantification assume that the only value of a
resource is the heat derived from its combustion. In this way, for example, human services are
evaluated as the calories expended doing work and, when compared to other inputs to a given
process, are several orders of magnitude smaller and often considered irrelevant; (3) unmonied
resources and processes (i.e., those outside the monied economy) are often considered externalities
and not quantified. Most processes, and all economies, are driven by a combination of renewable
and nonrenewable energy; (4) price determines value. The price of a product or service reflects
human preferences, often called "willingness-to-pay." It can also reflect the amount of human
services "embodied" in a product A valuing system based on human preference assigns either
relatively arbitrary values, or no value to necessary resources or environmental services.
EMERGY is a measure of the ability to cause work (Odum 1984; Odum and Arding 1991).
New energy sources are often evaluated based on dollar costs per unit of energy produced, and
suggestions are made that if prices rise, a new source may be economical and thus competitive.
However, price merely suggests what humans are willing to pay for something; the ability of a
resource to cause work--and thus its true value to the public--is determined by the effect it has in
stimulating an economy. For instance, a gallon of gasoline will power a car the same distance no
matter what its price; but its value to the driver is the number of miles (work) that can be driven.
Its price reflects the scarcity of gasoline and how important it is to do the work. Price is often
inverse to a resource's contribution to an economy. When a resource is plentiful, its price is low,
yet it contributes much to the economy. When a resource is scarce, its total contribution to the
economy is small, yet its price is high.
EMERGY may be a measure of the equivalence when one resource is substituted for
another. Sunlight and fossil fuels are very different energies; yet when their heat values are used
the difference is not elucidated. A joule of sunlight is not equivalent to a joule of fossil fuel in any
system other than a heat engine. In the realm of the combined system of humanity and nature,
sunlight and fuels are not equally substitutable joule for joule. However, when a given amount of
fuel energy is expressed as the amount of solar energy required to make it (solar EMERGY), its
equivalence to sunlight energy is defined. Since EMERGY is a measure of the work that goes into
a product expressed in units of one type of energy (sunlight), it is also a measure of what the
product should contribute in useful work in relation to sunlight.
Other methods of energy analysis do not account for different tyes of energy, but assume
that the heat value of energy is a common denominator by which quantification and comparisons
can be made by Slesser (1978, 1987). We believe this to be incorrect. All energy types are not
equivalent in their ability to do work and, without accounting for the differences in what has been
termed the quality of different types of energy, erroneous conclusions can result. Use of
EMERGY to represent all the contributions to any given product or process accounts for
differences in resource quality and expresses different resources in equivalent capacity to do work.
Net EMERGY
In this study, various alternative transportation fuels are evaluated using EMERGY analysis
to shed some light on their potential to contribute positively to the economy. For an alternate fuel
source to contribute, it must yield more energy than it costs to produce. The higher the ratio of
yield to cost the greater its contribution to the economy. Evaluation of net yields of fuel sources
has been called net energy analysis and has been done for some time. Most often, however, net
energies are determined using only the heat values of energies consumed in the production process.
Often not included are the indirect energies--associated with goods and services that are consumed,
labor, and nonrenewable resources such as soils-- which are sometimes greater than direct energy
consumption. Net EMERGY analysis accounts for all energy used, including the so-called "free"
renewable energies like sunlight, wind, or rain, and those associated with goods and services. Net
EMERGY ratios (the ratio of yield to costs) of primary fuels have been found to be on the order of
10/1, while the ratio for secondary sources is lower, about 3/1 (Odum, 1995). If a potential fuel
source has a ratio much below current primary sources, it is not economical, and will not complete.
Under such conditions, fuels are often subsidized through government intervention in the market
or through tax incentives.
We believe that conservation strategies can be evaluated in the same manner, since they
should yield more than they cost. True conservation strategies should have net yield ratios that are
greater than 1/1; the higher the ratio the better the conservation. We estimate that for a conservation
strategy to be economical, it should have a net EMERGY yield ratio of at least 3/1.
Previous studies using EMERGY evaluation of choices include: alternative fuels,
alternative sites for power plants, alternative agriculture, mitigation of wetlands, aquaculture
compared with environmental production, national characteristics, benefits of foreign trade, impact
of wars, allocation of waters, waste disposal alternatives, and importance of historic events.
Definitions
Before presenting detailed descriptions of each step in the methodology, definitions are
given for several key words and concepts.
Energy. Sometimes referred to as the ability to do work. Energy is a property of all things
which can be turned into heat, and is measured in heat units (BTUs, calories, or
joules)
EMERGY. An expression of all the energy used in the work processes that generate a
product or service, in units of one type of energy. Solar EMERGY of a product is
the EMERGY of the product expressed in equivalent solar energy required to
generate it. Sometimes its convenient to think of EMERGY as energy memory.
Emjoule. The unit of measure of EMERGY, or EMERGY joule. It is expressed in the
units of energy previously used to generate the product; for instance the solar
EMERGY of wood is expressed as joules of solar energy that were required to
produce the wood. Solar EMjoules is abbreviated "sej."
Empower. The flow of EMERGY per unit time; expressed as sej/time.
Empower density. Empower per unit area; expressed as sej/time*area.
Macroeconomic dollar (Emdollar or EM$) A measure of the money that circulates in an
economy as the result of some process. In practice, to obtain the macroeconomic
dollar value of an EMERGY flow or storage, the EMERGY is multiplied by the
ratio of total EMERGY to Gross National Product for the national economy.
Nonrenewable Energy. Energy and material storage such as fossil fuels, mineral ores,
and soils that are consumed at rates that far exceed the rates at which they are
produced by geologic processes.
Renewable Energy. Energy flows of the biosphere that are more or less constant and
reoccurring, which ultimately drive the biological and chemical processes of the
earth and contribute to geologic processes.
Resident Energy. Renewable energies that are characteristic of a region.
Transformity. The ratio obtained by dividing the total EMERGY that was used in a process
by the energy yielded by the process. Transformities have the dimensions of
EMERGY/energy (sej/J). A transformity for a product is calculated by summing all
of the EMERGY inflows to the process and dividing by the energy of the product.
Transformities are used to convert energies of different types to EMERGY of the
same type.
METHODS
The general methodology for EMERGY analysis is a "top-down" systems approach. The
first step is to construct systems diagrams that are a means of organizing thinking and relationships
between components and pathways of exchange and resource flow (systems symbols and brief
definitions are given in Figure 1.1). The second step is to construct EMERGY analysis tables
directly from the diagrams. The final step involves calculating EMERGY indices that summarize
and relate EMERGY flows of the economy with those of the environment, and allow the prediction
of economic viability and carrying capacity. Given next is further elaboration on the methods used
for EMERGY analysis.
-'V
0-
S
Pric
Li2X
Energy circuit. A pathway whose flow is proportional to the
quantity in the storage or source upstream.
Source. Outside source of energy delivering forces according to a
program controlled from outside; a forcing function.
Tank. A compartment of energy storage within the system storing a
quantity as the balance of inflows and outflows; a state variable.
Heat sink. Dispersion of potential energy into heat that accompanies
all real transformation processes and storage; loss of potential
energy from further use by the system.
Interaction. Interactive intersection of two pathways coupled to
produce an outflow in proportion to a function of both; control
action of one flow on another; limiting factor action; work gate.
Consumer. Unit that transforms energy quality, stores it, and feeds it
back autocatalytically to improve inflow.
Switching action. A symbol that indicates one or more switching
actions.
Producer. Unit that collects and transforms low-quality energy
under control interactions of high-quality flows.
Self-limiting energy receiver. A unit that has a self-limiting output
when input drives are high because there is a limiting constant
quality of material reacting on a circular pathway within.
Box. Miscellaneous symbol to use for whatever unit or function is
labeled.
Constant-gain amplifier. A unit that delivers an output in
proportion to the input I but changed by a constant factor as long as
the energy source S is sufficient.
Transaction. A unit that indicates a sale of goods or services (solid
line) in exchange for payment of money (dashed line). Price is
shown as an external source.
Figure 1.1. Symbols and definitions of the energy language diagramming used to represent systems
(from Odum 1971, 1983).
Step 1: Overview System Diagrams
A system diagram in "overview" is drawn first to put the system of interest in perspective,
combine information about the system from various sources, and to organize data-gathering
efforts. The process of diagramming the system of interest in overview ensures that all driving
energies and interactions are included. Since the diagram includes both the economy and
environment of the system, it is like an impact diagram which shows all relevant interactions.
Then a second, simplified (or aggregated) diagram is drawn, retaining the most important
essence of the more complex version. This final, aggregated diagram of the system of interest is
used to construct a table of data requirements for the EMERGY analysis. Each pathway that
crosses the system boundary is evaluated.
Step 2: EMERGY Analysis Tables
EMERGY analysis of a system is usually conducted at two scales. First, the larger system
within which the system of interest is embedded is analyzed, and indices necessary for evaluation
and comparative purposes are generated. Second, the system of interest is analyzed. Both
analyses are conducted using an EMERGY Analysis Table organized with the following headings:
1 2 3 4 5 6
Note Item Raw Units Transformity Solar Emdollars
EMERGY
Row 1
Row2
Row...
Each row in the table is an inflow or outflow pathway in the aggregated systems diagram;
pathways are evaluated as fluxes in units per year. Six columns describe each pathway as follows:
Column 1 (Note) The line number for each pathway, and corresponding footnote
number that contains sources and calculations for the item.
Column 2 (Item) The item name that corresponds to the name of the pathway in the
aggregated systems diagram.
Column 3 (Raw Units) The actual units of the flow, usually evaluated as flux per
year. Most often the units are energy (joules/year), but sometimes
are given in grams/year or dollars/year.
Column 4 (Transformity) Transformity of the item, often derived from previous
studies.
Column 5 (Solar EMERGY, sej) The product of the raw units in Column 3 and the
transformity in Column 4.
Column 6 (Emdollars) The result of dividing solar EMERGY in Column 5 by the
EMERGY-to-money ratio (calculated independently) for the
economy of the nation within which the system of interest is
embedded.
Step 3: Calculation of EMERGY Indices
The principle used in judging alternative fuel sources is as follows: when alternative fuel
sources or transportation systems are compared, the system that contributes the most EMERGY
value to the public economy for the least EMERGY invested, in the long run, is most likely to be
successful. Several indices which help in gaining perspective about sources and processes are
calculated from the data in the EMERGY Analysis Tables. These are:
EMERGY-money ratio (EMprice). The ratio of total EMERGY flow of a source or process
to the dollar cost. In addition, a ratio of the total EMERGY in the economy of a
region or nation to the GNP of the region or nation is also calculated, as a means of
evaluating the EMERGY content of services.
EMERGY yield ratio. The ratio of the EMERGY yield from a process to the EMERGY
costs. This ratio is a measure of how much a process will contribute to the
economy. Figure 1.2a shows the method of calculating the net EMERGY yield
ratio. Sources with the highest net EMERGY yield ratios contribute most to the
economy and tend to be used first. This ratio is a useful predictor of the best
contributing source.
Solar transformity. The ratio of the solar EMERGY that is required to generate a product
or service to its energy. The transformity measures the resource contribution per
unit of energy in service or product Solar EMERGY units are solar emjoules per
Joule, abbreviated sej/J. Since products that require more resource input are only
used if they have more effect, there tends to be a correlation between the
transformity of a product and its effects. Figure 1.2b shows the method of
calculating a transformity.
Using Transformity to Select Efficient Pathways
Energy sources can be arranged in a series according to their solar transformities (discussed
in more detail in Part 2). Fuels with higher transformities represent more previous work, and thus
should be used for purposes where the extra inputs are justified. To use a high transformity fuel
for a purpose where a low transformity one is sufficient is a waste of the energy used to generate
the higher quality fuel. Inappropriate uses of high transformity energy are not usually economical,
since they require more inputs for their production and thus cost more for the same effect.
The Principle of Appropriate Transformity
The appropriate uses of energies of different types may provide maximum economic vitality
by accomplishing more useful work. The approach is to match transformity of a source with the
task for which the energy is intended. Energies of higher transformity can interact and control
flows of lower transformity. Control by higher quality energy is shown in systems diagrams as a
pathway entering the top of the transformation process (Figure 1.2). An energy source is well
used either in small quantity to interact and control a larger source of lower transformity, or in
larger quantity to interact and be controlled by a smaller quantity of higher transformity energy.
For example, higher transformity electricity is appropriately used to control lower transformity
heating systems, but may not be as appropriate to substitute for heating with natural gas or wood.
Purchased inflow (F)
Inflow From Renewable or
Non- Renewable Source
Outflow of
Upgraded Energy (Y)
EMergy Yield Ratio= Y/F
Energy D
AL(all in EMergy
Transformity of D = A4-B+C of ome type)
D (energy)
(b)
Figure 1.2. Diagram of energy flows in a typical energy transformation process showing method
for calculating EMERGY yield ratio (a) and transformity (b).
2. Transformity of Alternative Energy Sources
H.T. Odum and M.T. Brown
The productivity of modern societies depends on sources of energy and their
transformation into the products and services of the human economy. Whether it is natural
environmental systems or the market economy systems of human managed technology, self-
organizing pressures tend to eliminate those networks that are wasteful or contribute less. But
procedures are needed to tell in advance what combinations of processes use resources most
efficiently. As world supplies of energy become less available, good planning and policy requires
evaluation of alternative sources and processes. Which are abundant and efficient enough to
operate our systems? What are the best alternatives for such processes as heating, transportation,
and electric power?
Evaluating energy sources and processes in the network of environment and economic
sectors is difficult because there are so many inputs that contribute. Inputs such as human labor
and services may represent as much energy indirectly as the fuels supply directly. A measure that
evaluates various kinds of energy on a common basis is the transformity. The larger the
transformity of an energy type, the more energy was required in its formation. This chapter
explains the transformity measure, its use to evaluate alternative energy sources, and the principle
of appropriate transformity for making energy policy.
The many forms of energy available to do work can be arranged in a series according to the
amounts of one kind of energy required to make another. Many joules of environmental energies
are required to make a tree, many joules of wood energy are required to make electricity, and many
joules of electric energy are required to process information, etc. By expressing all forms of
energy in units of one type that was required to make each of the others, a measure is obtained of
their position in the scale of energy requirement. This measure is the transformity, the energy of
one kind used directly and indirectly to make another kind.
After a century of research, technologies are available to transform most kinds of energy
into most other forms of energy. Given a resource of one kind of energy, humans seeking another
kind of energy can string together one or more transformation processes to generate the desired
product. For example, Figure 2.1 shows strings of energy transformations with various forms of
resultant energy, all derived from natural gas. All these arrangements use well established
processes, but some involve unnecessary extra steps. Some require more special inputs of energy
Transport
Natural gas. Gas wells Transform. L-l- lcar-- Transport
in ground Rockets Transport
Elect. power
Power plant Electric car -- Transport
X I .. T Heat
I Fuel Cell car I .Transport
STransform. ILiq.fuel rRegular car Transport
Figure 2.1. Example of the many possible alternative pathways of energy transformation, in this
case starting with natural gas.
Nat. gas
directly and indirectly than others. First we need to explain energy transformation processes, the
EMERGY concept and how the transformity is defined.
Energy Transformation Processes
Energy is normally used in an energy transformation process, as diagrammed in Figure
2.2. The numbers on the pathways in Figure 2.2a are flows of energy per unit of time. In other
words, energy is conserved; it is neither increased nor destroyed during the transformation.
Normally, there is a large flow of one quality of energy that is required for the transformation,
shown inflowing from the left (I) in Figure 2.2a. According to the first energy law, energy
inflowing from the left is either stored (if there is a storage indicated with a tank symbol) or passed
out of the process. In the transformation this energy flow is normally controlled by one or more
higher quality energy flows of lesser quantity, shown flowing in from the right (F in Figure 2.2).
The output yield of the transformation process (Y in Figure 2.2) is energy shown leaving to the
right.
According to the second energy law, most of the potential of the inflowing energy to do
work (energy availability) is used up during the transformation. In energy systems diagrams
energy whose "availability" is used up is shown leaving the system through the "heat sink" at the
bottom in Figure 2.2. A smaller amount of energy which has been transformed into a new form is
shown in Figure 2.2 leaving the process to the right. In classical energy analysis, efficiency of
energy transformation is the percent the output flow (Y) is of the input energy flow (I).
Sometimes the efficiency is calculated as the percent the output flow is of all energy inflows (the
sum of input energy flows I + F) including the feedback flow (F). Since the output energy flow
(Y) required more available energy of incoming type (I) to be used up (and dispersed through the
heat sink), it can be said to be of higher quality.
It is well known that any energy transformation processes can be operated at different
speeds and efficiencies by changing the output loading. You can arrange a process so that it does
little work and, as a consequence, rapidly and wastefully dumps energy into heat. Or, you can
arrange the process with so much loading that the process, although efficient, stalls or goes so
slowly that it is not very useful. Generally, there is an intermediate loading that transforms energy
with an optimum efficiency that maximizes the rate of conversion (maximizes the power output).
In the following discussions of alternative energy sources and transformations, it is assumed that
the processes are loaded to deliver the maximum power output.
The many forms of energy of the biosphere can be arranged in an energy quality series
illustrated in Figure 2.3. Energy forms are arranged from left to right in order of the energy
1000
Energy flow, Joules/time
Efficiency (energy) #1
=100/1000 .100 =10%
Efficiency (energy) #2 = [100/(1000 + 10)1* 100 = 9.9 %
Solar transformity,
solar emjoules per Joule
Solar transformity of Y
[Emergy I + Emergy F]
Energy Y
1000 -"-'. .
Solar energy Process
Flow of solar Emergy
(empower) 0
solar emjoules/time
Net emergy yield ratio = [Emergy Y]/ [Emergy F]
Emergy Investment ratio = (Emergy F] / [Emergy ]
2000
100 20
100
Figure 2.2. Numerical example of energy, transformity, and EMERGY in a transformation
process; I, main energy inflow; F, controlling feedback from the larger system; Y, yield from the
transformation process. (a) Energy flows and the classical calculation of efficiency of energy
conversion; (b) solar transformity given for each energy inflow and the calculation of the
transformity of the yield as the quotient of solar EMERGY flow (in c) divided by the energy flow
(in a); (c) solar EMERGY of each pathway.
1000
= 2.0
= 1.0
Combined efficiency
= 0.0007 %
(b) Energy per
unit of human
service, Joules
(d) Solar
transformity:
solar emjoules
per joule
1 sej/J 4000 sej/J 40,000 seY/J
200,000 sej/J
30,000,000 sej/J
Increasing transformity
Figure 2.3. Series of energy transformation processes arranged to form an energy hierarchy.
Available energy flowing from the left is transformed at each stage to a smaller flow of energy of
higher quality. (a) Efficiency of the string of processes calculated by multiplying the efficiencies of
each successive transformation together from left to right, ignoring the controlling inputs; (b)
energy of the source required for each unit of yield of the last process obtained by back calculating
(sucessively dividing from right to left by the efficiencies, ignoring the controlling inputs); (c) solar
EMERGY required for the yield of the last process including the controlling inputs; (d) solar
transformity of each energy flow calculated as the sum of solar EMERGY inputs divided by the
enerev vield, as in Fipure 2.2.
_^_^^^_^^^^_^^^_^^^---__^,
required for their formation Many joules of potential energy of one kind on the left are used up
in the work of generating fewer joules of a second form of energy to the right. Where many units
of one type are required to support a unit of higher type, the word hierarchy is appropriate. All
kinds of energy can be located in the energy hierarchy depending on the energy of each kind
required to generate another. Since different quantities of energy are required for different forms
of energy, it is not correct to use energy units (joules, kilocalories, btu's, etc.) as a measure of
work where energies of different forms are compared.
However, one may express various energy flows or storage in units of one form of
energy that was previously used to develop each. The available energy of one form required
directly or indirectly to develop a product or service was defined in Chapter 1 as the EMERGY.
To distinguish the energy previously transformed, a new unit was defined, the emjoule. We
usually use solar energy reaching the earth's surface as the form of energy used to evaluate other
forms. Thus, we evaluate various kinds of available energy in terms of solar EMERGY in units of
solar emjoules. A numerical example of Solar EMERGY in an energy transformation is given in
Figure 2.2c. The solar EMERGY of the output yield is the sum of the solar EMERGY of the two
inputs.
Transformity is defined as the total EMERGY that was used in a process divided by the
energy yielded by the process. Transformities have the dimensions of EMERGY/energy (solar
emjoules per Joule, abbreviated sej/J). A transformity for a product is calculated by summing all
the EMERGY inflows to the process and dividing by the energy of the product. A numerical
example is shown for the energy transformation process in Figure 2.2b.
In Figure 2.3 the solar energy on the left, processed through several transformations,
produces small amounts of the energy types on the right. The more transformation stages there
are, the less energy of the output. The further to the right in the energy hierarchy, the greater the
solar transformity to make a joule of that energy type. The solar transformities increase from left to
right In Figure 2.3d, marking the position in the energy hierarchy series.
Where there are alternative processes for generating the same power outputs, processes
with inputs of lower transformity are the most efficient. Comparing solar transformities of
alternative processes is an easy way to select the best choices. The solar transformity of new
processes for generating an energy type can be compared with the values in tables of transformity
based on previous evaluations (Table 2.1).
Observations suggest that forms of energy with higher transformity have greater effect
when they are used, providing they have other forms of energy with which to interact. Efficient
systems don't disperse more energy than is necessary (that is, they don't unnecessarily use up the
potential for work). Energies are not long transformed to higher transformity unless the product
has effects justifying the greater energy use. In other words, the higher the transformity, the
greater the effect the energy has in its use. Sometimes the phrase "greater energy quality" is used
to describe an energy type that has greater effect per joule. In this sense, it can be said that
transformity measures energy quality.
In diagramming a typical energy transformation (Figure 2.2), the lowest transformity is that
of the larger, low quality energy from the left (I). The highest transformity is that of the high
quality, controlling, (but low energy content) "feedback" (F) from higher levels in the energy
hierarchy. The product outflow has intermediate transformity. As shown in Figure 2.2, there is
apparently a matching of high and low quality energy flows required for any energy
transformation.
By the principle of appropriate transformity, each kind of process has appropriate
transformities for its inputs. An energy use is appropriate if it is efficient in supporting useful
work of a type needed. An energy use is not appropriate if a higher transformity form is used
than is necessary, because this means that more energy was used than necessary. In terms of the
series in Figure 2.3, it would be a waste to transform energy into a high quality form on the right
and then use it do work that a lower form could do. For example, it is wasteful to convert fuels
into electricity and then use that electricity to make heat that the ordinary fuel could generate
without the transformation to electricity.
Fuels with higher transformities represent more previous work and thus should be used for
purposes where the extra inputs are justified. To use a high transformity fuel for a purpose where
a low transformity one is sufficient is a waste of the energy used to generate the higher quality fuel.
Inappropriate uses of high transformity energy are not usually economic since they require more
inputs for their production and thus cost more for the same effect. High transformity flows with
relatively small energy may not have much effect in interactive-control action on energy types with
several orders of magnitude lower transformity. In the opposite direction, an energy type may not
be controlled by an energy form with a transformity several orders of magnitude higher.
Transformities are evaluated for observed operations as an empirical measure of what a
system does. Each EMERGY evaluation of a production system generates additional
transformities. Sometimes we use the least transformity known to indicate what the most efficient
transformation is (most efficient consistent with maximum power). For other purposes we use the
mean of the transformities found from previous studies.
In order to use the appropriate transformity principle to select the best energy alternatives,
the lowest solar transformity which is possible for each fuel must be established. Lower
transformity means greater efficiency. No doubt there is an ultimate thermodynamic lower limit to
the transformity for each kind of energy. Evaluation of many kinds of systems will eventually
determine the least transformities (the most efficient conversions) consistent with delivery of
maximum power. A national agency may be required to make the hundreds of evaluations needed.
Even determining the average transformity will require many duplicate evaluations. In the
meantime, we have assembled the available determinations of transformity such as those for
electric power in Table 2.1 for evaluating processes and recommending policies.
In the last two centuries of expanded use of rich storage of fossil fuels, these energies
were used to interact, control, and stimulate most of the processes of human industry and
civilization. For example, fossil fuels were used to process fertilizers and pesticides to improve
efficiencies of agriculture. In Figure 2.2 these special inputs are examples of high EMERGY,
controlling feedbacks (F). In order to maximize intensive agriculture, these inputs were increased
with diminishing returns. The solar transformity that resulted in these over-stimulated processes
was larger than the minimum observed. There was not a good matching between the inputs. In
other words, the waste of trying to stimulate with too much fuel-based input caused a loss of
overall efficiency and thus a higher transformity. In times of rapid economic development and
open competition, accelerating power and speed of development displaces efficiency temporarily.
Later, when growth is not possible, efficient alternatives may displace the fast, inefficient ones and
the observed transformities will be less. In times like the present which are in transition, we often
have to consider two transformities: the larger (inefficient) one that is competitive and a smaller
(efficient) one that can prevail in non-growth periods. The latter probably has a thermodynamic
lower limit consistent with maximizing power in a real system.
Some of the most basic transformities are used in evaluating other transformities. For
example, the solar transformity of electric power is estimated from various processes in Table 2.1.
The range of values is due to differences in the efficiency of the particular systems evaluated, to
variations and errors in the data used, to omissions of some contributions, and errors in the
assumptions. Pending a national project to more precisely determine the best and the average
transformities, we arbitrarily selected values to use for other evaluations based on studies so far
available. Between 1966 and 1990, transformities were revised every few years as more accurate
basic transformities were found, which caused many others to change. Many transformities
changed when we added geologic energies and tides that had not previously been included in the
earth calculations.
For any study, one set of transformities is used for most purposes so that all evaluations
are comparable. However, small differences in transformities of the main energy sources don't
Table 2.1. Solar Transformities of Electric Power
Note System Solar Empower Electric Power Solar Transformity
sej/yr J/yr sej/J
1 Coal power plant 160,000 1 160,000
2 World stream geopotential 9.44 E24 1.0 E20 94,400
3 Hydroelectric power,Sweden 1.95 E24 2.43 E17 80,246
4 Wood power plant, Jari Brazil 2.38 E20 1.17 E15 203,418
5 Solar voltaic grid,Austin, Tx 7.5 E17 1.8 E12 416,666
6 Hydroelectric,Tucurui, Brazil 1.65 E22 1.0 E17 165,000
7 Wood power plant, Thailand 2.42 E14 3.6 E9 67,222
8 Oil power plant, Thailand 7.14 E14 3.6 E9 197,777
9 Coal power plant, Thailand 6.10 E14 3.6 E9 169,444
10 Lignite power plant, Thai. 5.47 E14 3.6 E9 151,944
11 Lignite Power plant, Texas 5.4 E21 2.65 E16 204,384
12 Geothermal Electric, Calif. 2.13 E20 2.5 E15 84,800
Mean 166,274
*18% added to those EMERGY evaluations that were made before tide was added to global solar EMERGY budget
(items 6 and 11)
1 Assuming 4 coal emjoules per Joule electric power and 40,000 sej/J coal
2 Global calculation made with assumptions about the empower required for the mountain uplift, the carving of
basins, and the construction of dams.
Global solar empower, 9.44 E24 sej/yr, generates average stream flow over land 39.6 E3 km3 runoff (Todd
1970) and maintains an average land elevation, 875 m (Ryabchikov, 1975). Average land and average
streams were taken as by-products of shared empower.
Stream geopotential: (39.6 E12 m3/yr)(875 m)(1000 kg/m3)(9.8 m/sec2) = 3.39 E20 J/yr.
Electric power potential = stream geopotential times efficiency of hydroelectric conversion taken as 80%.
(3.39 E20)(0.8) = 2.7 E20 J/yr electrical.
For a 25% feedback of empower from the economy for dam and operation, the net yield of electricity could
be 3/4 of 2.7 E20 J/yr = 2.0 E20 J/yr.
If stream energy in the long run has to carve a basin half the time to allow generation of electricity the
other half, then the electric output is half or 1 E20 J/yr.
3 Realized electric power 1988:72 Terawatt-hours page 17 in Energy in
Sweden, National Energy Administration 1990 S117 82 Stockholm Sweden. 30 pp.
(72 E9 kilowatt-hrs/yr)(860 kcal/kwhs)(4186 J/kcal) = 2.60 E17 J/yr;
For 80% efficiency, input geopotential is 2.6 E17/0.8 = 3.25 E17 J/yr.
Time for erosion to make a basin may be assumed to be similar to the time for filling with sediment.Thus
the dam in the long run operates for half the time as it fills with sediment, eroding for half using the same
stream energy. Either consider the long range electrical yield as half or consider the short term operation as
receiving the prorated EMERGY of the carved basin as equivalent to the input geopotential (2 times
geopotential in use). (2)*(3.25 E17 J/yr) = 6.5 E17 J/yr input geopotential. For 3rd order streams, solar
transformity from Fig. 4.11 on the Mississippi River is 3 E4 sej/J and therefore the input solar EMERGY
is (3 E4 sej/J)*(6.5 E17 J/yr) = 1.95 E22 sej/yr
Using 1/4 of empower feedback for dam and operation, net electrical yield is
(3.25 E17)*0.75 = 2.43 E17 J/yr.
4 Rainforest logs supplied in a steady state from a 100 year rotation requiring 2.324 E9 m2; Solar EMERGY
from main use of rain by trees and 3 mm transpiration, 4.94 J Gibbs free energy per gram of rain water and
solar transformity of rain, 1.82 E4 sej/J :
(3mm/d)(365 d/yr)(l E-3 m3/mm)(lE6 g/m3)(4.94 J /g water)(2.3 E9 m2)(1.82 E4 sej/J)
= 2.27 E20 sej/yr; plus solar EMERGY from fuels use 0.085 E20 sej/yr and services used 0.025 E20
sej/yr.
Electricity produced, 1.67 E15 J/yr minus electricity used in the processing: 0.032 J/yr debarking &
chipping and 0.46 E15 J/yr in plant operations.
5 Power grid evaluated by R. King (1991). See Table 22.5
6 Modified from Brown(1986) Energy analysis of the hydroelectric dam near Tucurui, Brazil, pp. 82-91 in Energy
Systems O overview of the Amazon Basin, H.T.Odum, M. T. Brown, and R.A. Christianson.
Electricity produced: 1.0 E17 J/yr based on 0.8 capacity factor and 4000 megawatts.
Contribution to dam and operation from economy: = 4.25 E21 sej/yrContribution of geopotential of
inflowing water and also the prorated contribution of the basin that was developed by the same streamflows
earlier. See note #3.
(2.06 E17 J/yr)(2.36 E4 sej/J) = 4.87 E21 sej/yr
Total input includes this factor twice (present inflow + prorated basin EMERGY). In a full cycle of
damming and allowing reerosion of basin, there is no net sediment diversion.
(4.87 + 4.87 + 4.25) E 21 sej/yr = 13.95 E21 sej/yr
(13.95 E21 sej/yr)(1.18 tidal correction) =
7 Wood power plant (25 megawatt generating 173.5 E3 kwh/yr)using eucalyptus plantation wood (S.Doherty and
Bo Hector, 1991). Values estimated per megawatthour electrical
(1 mwh)* (1000 kwh/mwh)* (860 kcal)/kwh*(4186 J/kcal) = 3.59 E9 J/yr
Solar EMERGY inputs in sej per mwh:
Rain, 44 E12; Fertilizer, 6 E12; Labor, 7 E12; plantation capital, 29 E12; plant operational service, 96
E12; power plant capital, 55 E12; transmission, 6 E12; total, 242 E12 sej/mwh
8 Oil fired power plant (S.Doherty and Bo Hector, 1991).
Values estimated per megawatthour electrical
(1 mwh)* (1000 kwh/mwh)* (860 kcal)/kwh*(4186 J/kcal) = 3.59 E9 J/yr
Solar EMERGY inputs in sej per mwh:
2-10
Oil, 402 E12; Oil services, 100 E12; plant operational services, 131 E 12; capital, 40 E 12; transmission,
41 E12;total, 714 E12 sej/mwh,
9 Coal Powered plant (S. Dohery and Bo Hector, 1991)
Values estimated per megawatthour electrical
(1 mwh)* (1000 kwh/mwh)* (860 kcal)/kwh*(4186 J/kcal) = 3.59 E9 J/yr
Solar EMERGY inputs in sej per mwh:
Coal, 380 E12; Oil services, 80 E12; plant operational services, 109 E 12; capital, 58 E 12; transmission,
43 E12; total, 610 E12 sej/mwh.
10 Lignite power plant ( S. Doherty and Bo Hector, 1991)
Values estimated per megawatthour electrical
(1 mwh)* (1000 kwh/mwh)* (860 kcal)/kwh*(4186 J/kcal) = 3.59 E9 J/yr
Solar EMERGY inputs in sej per mwh:
Lignite, 279 E12; mining services, 93 E12; plant operational services, 100 E 12; capital, 44 E12;
transmission, 30 E12; total, 547 E12 sej/mwh
11 Big Brown Lignite power plant, Texas Odum, Odum, and Blissett, 1987)
(7.27 E13 J/dayX365 d/yr)=2.65 E16 J/yr electrical power produced.
Inputs evaluated in solar emjoules/day:
Mining inputs:
Lignite mined for power plant, 73.7 E17; topsoil lost, 3.1 E17; fuel used, 0.032 E17; electric power used,
0.49 E17; equipment maintenance, 0.93 E17; goods and services, 6.2 E17; and total, 84.45 E17 sej/day.
Power Plant inputs: cooling water 0.10 E17; equipment maintenance, 1.24; Goods and services, 40 E17;
total 41.34 E17 sej/day.
Mining and power plant on a year basis: (365)*(84.45 +41.34)E17 = 4.59 E21 sej/yr
Tidal correction to global transformities: 4.59E21 1.18 = 5.4 E21 sej/yr
12 Geothermal electric power conversion in California updated from Gilliland (1975).
Efficiency of 11% generates 2.5 E11 J/yr
Economic feedbacks based on 1972 costs and EMERGY/USem$ for 1972
(9.7 E6$)(7 E12 sej/$) +0.68 E20 sej/yr
Geothermal heat contribution estimated from efficiency of 11% and 6% pipe loss of heat
2.4 E16 J/yr; and solar transformity for deep heat from Appendix table Al,
(2.4E16 J/yr) (6055 sej/J.) = 1.45 E20 sej/J
Geothermal plus economic feedbacks: (1.45+ 0.68)E20 sej/yr= 2.13 E20 sej/yr
make much difference in comparative evaluations because they affect all of the systems similarly.
In the future, after transformities have been calculated for more examples, better estimates for the
average and the most efficient transformity will be found, but such refinements are not expected to
change policy conclusions very much.
In the case of electric power, for many studies during the period 1983-1993 we
standardized on a higher value for solar transformity of electric power (2 E5 sej/J) in order to be
realistically conservative until further studies proved whether electric power could be made with
less. The solar transformity of coal was standardized as 40,000 sej/J.
Using Transformities to Evaluate Energy Transformation Series
Using traditional energy process analysis, the efficiencies of each stage in a series of
processes are combined (multiplied together) to obtain an overall efficiency for a whole series, as
shown in Figure 2.3a. However, this method omits the controlling inputs, which often have a
high transformity (which means that much energy was used previously to make them). A better
evaluation using EMERGY includes all inputs on a common basis as shown in Figure 2.3c. For
each stage, the sum of the input EMERGY divided by the energy flow is the transformity. Solar
transformities for the series are given in Figure 2.3d.
Transformity Tables for EMERGY Evaluations
Transformities are useful for rapid EMERGY calculations, and tables of transformities
from previous studies have been assembled. Transformities are used to convert data on energies of
different types to EMERGY of the same type. Table 2.1 has a selection of solar transformities
from earlier studies.
2-12
3. EMERGY Evaluation of Alternative Fuels for Transportation
H.T. Odum, G.G. McGrane, M.T. Brown, and S. Bastianoni
Good fuel policy is based on a knowledge of which sources are most efficient in supplying
energy to maximize economic vitality. Plans are successful that develop those sources which will
be competitive in free markets. Fuels which will be successful as primary energy sources and
which should be given priority are those with the highest EMERGY yield ratios, and which
generate the needed transportation with the lowest transformity (highest efficiency considering all
inputs). Recommendations in this chapter are based on EMERY yield ratios and transformities,
which were determined from the EMERGY evaluation of alternative fuels and systems for
transportation
Rationale for comparisons and suggestions related to most favorable alternative fuel
sources are based on the assumption that the fuels that contribute most to an economy are the ones
with the greatest net EMERGY yield. These are the ones that contribute the most, compared to
what is required from the economy for fuel processing and distribution. The EMERGY yield ratio
measures the net contribution of a fuel. Figure 3.1 shows recently determined EMERGY yield
ratios for several primary fuels and alternative sources. Fuels with high EMERGY yield ratios also
provide more energy per unit of carbon dioxide released to the atmosphere.
When fuels are abundant and close to the surface so that mining is cheap, EMERGY yield
ratios are high. When primary fuel sources have high EMERGY yield ratios, economies are
prosperous. Before 1973, with prices of oil and gas very low, developed economies were
purchasing fuels from the Middle East with EMERGY yields 40 to 60 times more than the
EMERGY in the buying power of their payments. In other words, 40 to 60 times more wealth
was generated in the economy by the fuels than was required for their processing. Since 1973,
world prices have increased. EMERGY ratios for purchases of foreign oil declined, ranging
between 3/1 and 12/1. Fossil fuels bought on markets in 1993 give the purchasers a EMERGY
yield ratio on the order of 10/1.
The EMERGY yield ratios for the energy sources in Figure 3.1 vary from more than 13/1
for Alaskan north slope oil, to palm oil having a net yield just barely above break-even (1.06/1).
For the most part, energy sources with infra-structure for their distribution and use have yields
between 13/1 and 3/1. With declining ratios, and therefore less available energy to support growth
and luxury consumption, most of the world is exhibiting slower growth (some would say stagnant
growth rates) than was characteristic in the period from 1950 to 1973. For growth rates to resume,
we believe that primary fuel sources must have EMERGY yield ratios much higher than is
Palm Oil i 1.06
Ethanol (sugar cane) 1.14
Jari Pulpwood 2.2
Peat (sun dried) 3
Texas Crude Oil 3.2
Compressed Nat. Gas 111111Iiii ii 3.4
Coal Methanol IIIIII I I1 4.7
Spruce Wood 51111111 111111S-4
Texas Nat. Gas (off shore) I111111 1 11111 11111111
Texas Lignite IIIIIIIIIII IIIII6.8
Mideast Oil (purchase,1992) 8.4111111111111111111111 4
Texas Nat. Gas (on shore) J1|ilII IIiIIIIIIII Il il 10.3
Wyoming Coal llllllllll1 11111110.5
Rainforest Logs 1111111111111111111112
North Slope Oil Iinn13.3
0 2 4 6 8 10 12 14
EMERGY Yield Ratio
Figure 3.1. Net EMERGY evaluation of fuels. Rain forest logs (Odum et al., 1982); north slope
oil (Brown,1993); Wyoming coal (Ballentine, 1976); Texas natural gas onshore, offshore, coal
methanol, compressed natural gas, Texas crude oil (King,1992); oil purchase, Texas lignite (Odum,
Odum, and Blissett, 1987); Jari pulpwood, palm oil (Odum, Brown, and Christianson, 1986);
spruce wood (Doherty, Nilsson and Odum, 1992).
characteristic of most present sources. Alternative fuel sources should have high EMERGY yield
ratios equal to or better than current primary sources, if they are to be net contributors to the
economy.
Evaluating Alternative Fuels and Systems for Transportation
Although determining the best transportation system involves the net EMERGY yield of the
fuel to be used, transportation also requires vehicles, roads or rails, and people as well as fuels.
To evaluate the EMERGY as well as the energy required for alternatives, both direct and indirect
energy consumption were examined. Figure 3.2 is a diagram of the transportation system showing
the inputs to transportation, including environment, fuel processing, vehicles, and infrastructure.
the EMERGY of transportation was determined by evaluating these inputs. All of the energies
were compared on a common basis--EMERGY, in solar emjoules (sej). EMERGY of vehicles
was divided by their lifetime to obtain their yearly contribution. EMERGY of consumed fuel,
services, vehicles modification, and materials were summed and compared between vehicle types.
An overall index of transportation efficiency was the EMERGY required per mile driven, with the
lowest values being best. That is, the best alternatives deliver the desired transport with the least
inputs.
Figure 3.3 summarizes the ways of evaluating transportation fuels and systems. At each
dashed, vertical line in the diagram, a net EMERGY analysis was made and EMERGY yield ratios
were calculated. The EMERGY yield ratio is the ratio of the EMERGY yield at each dashed line
(flow to the right--Y) to the EMERGY of resources, goods, and services consumed (flows to the
left--I). See Chapter 1 for more detail.
Net EMERGY of alternative fuels was first evaluated at the point of production (Y1 in
Figure 3.3), and then a comparative analysis with conventional methods was done based on the
EMERGY required per mile driven (Y2 in figure 3.3). A complete analysis of transportation
systems for comparison with alternative systems (i.e., comparisons of mass transit versus private
automobiles) includes the EMERGY required for infrastructure. However, in these comparisons
of alternative fuels, the EMERGY of infrastructure (roads, bridges, traffic devices, etc.) were
assumed to be the same for each vehicle type driven.
For comparative purposes, the various alternative fuels were compared for a conventional
vehicle (CV). This vehicle was a 4 passenger automobile, with an average fuel consumption of 30
miles per gallon. The electric vehicle (EV) evaluated had a projected range of slightly over 100
miles, and acceptable acceleration to highway speeds. The fuel-cell vehicle (FCV) was one of the
few such vehicles that have actually been road tested, yet much of the data were estimated from
Figure 3.2 Energy systems diagram of a transportation systems showing inputs for
fuels, vehicles, infrastructure, etc. (a) Main components and processes; (b) aggregate
diagram with vertical dashed lines indication positions for calculation of net EMERGY
ratios.
Lines for Calculating I
EMERGY Yield Ratios: Y1 Y2
Figure 3.3 Aggregated systems diagram of transportation systems with vertical dashed lines
indicating positions for calculation of EMERGY yield ratios.
several sources. To evaluate the compressed natural gas vehicle (CNGV), ethanol-fueled vehicle
(E85), methanol-fueled vehicle (M85), and hydrogen-fueled, internal combustion engine vehicle
(H2), it was assumed they all were conventional vehicles that had been retrofitted with a fuel tank
and different carburation as necessary to accommodate the alternative fuel type.
Results of Transportation Evaluations
Results of the EMERGY analyses for the various alternative transportation modes are given
in Appendix Tables A.1 through A.7. Table 3.1 and Figure 3.4 summarize the evaluations, and
compare the various fuel uses for transport on a per car basis. The conventional gasoline vehicle
required 64.2 E15 sej over its lifetime, 64% of which was direct and indirect energy consumed in
manufacturing and propelling the vehicle (46% of total EMERGY costs are gas and oil consumed
directly in propulsion). The next lowest total EMERGY costs were for compressed natural gas and
methanol.
Another way of expressing the input requirements and energy delivered is in terms of the
EMERGY to travel a given distance. Efficiencies change as a result of the energy dispersed in
friction due to the weights of vehicles, batteries and storage vessels. Figure 3.5 graphs the
EMERGY per passenger mile for the different transportation alternatives. Considering all inputs,
Metro Rail is the most efficient, since it uses the least amount of EMERGY per passenger mile.
Transformities of Alternative Transportation Fuels
Table 3.2 summarizes the transformities and EMERGY yield ratios for various fuels. The
lowest transformity (best efficiency) was for natural gas, followed by gasoline and ethanol.
EMERGY yield ratios were highest for oil and natural gas. These indices confirm the trend already
underway to substitute natural gas for other fuels in transportation systems.
Comparing Energy and EMERGY Pathway Analysis
As introduced in Figure 2.3, energy systems involve chains of processes with many
stages. Such diagrams show the pathway of successive energy conversions. With traditional
pathway analysis, overall efficiencies may be estimated from data on the efficiencies of each
transformation (Figure 2.3a). However, this method omits the goods, services, and controlling
inputs whose energy flows are small, but whose embodied energy may be large. EMERGY
evaluation of the same pathway was given in Figure 2.3c. From these numbers an overall
transformity was calculated (Figure 2.3d), the "bottom line" of pathway efficiency.
Table 3.1. Comparison of Solar Emergy Required per Car
E15 solar emjoules/car
Fuel/Vehicle Materials Manufacture & Human Services Total
Type Propulsion
Natural Gas 6.8 27.1 39.1 73
Gasoline 5.3 35.1 36.6 77
Methanol 5.5 30.8 47.8 84.1
Hydrogen 5.7 40.6 42.6 88.9
Electric 25.5 26.5 37.6 89.6
Ethanol 5.5 51.6 42.4 99.5
Fuel Cell 49.9 15.9 38.1 103.9
120
E
100
1
5
80
60 +
Natural Gasoline Methanol Hydrogen Electric
Ethanol Fuel Cell
Vehicle / Fuel Type
Figure 3.4. Comparison of the EMERGY requirements from manufacturing and propulsion,
human services, and materials for alternative transportation systems.
7 --E
40
20
n0
T
r Bicycle
a
n C. Nat. Gas I.C.E.
s Gasoline I.C.E.
o Methanol I.C.E.
r Dade MetroRail
t
a Hydrogen I.C.E
SElectric Ni/Zn Battery
o Pedestrian
Public Bus
M Ethanol I.C.E.
S Electric Fuel Cell
d E------uel-- I I I I
e
0 2 4 6 8 10 12 14
EMERGY/passenger-mile (El sej)
Figure 3.5. EMERGY per passenger-mile for alternative fuel transportation systems.
Table 3.2. Transformities and EMERGY Yield Ratios for Alternative Fuels
Fuel Transformity EMERGY Yield Ratio
(E 4 sej/J)
1 Gasoline
Alaskan North slope 6.4 13.3
Mid-East Oil @ $18/bbl 6.4 8.4
2 Natural Gas 4.8 6.8
3 Hydrogen
from Natural Gas 7.63 4.5
from F. Fuel Elec. Generation 20.4 2.4
from Hydro-electric 11.06 4.9
from Nuclear Electric 20.4 4.7
from Photovoltaic Cells 6.9 0.4
4 Electricity
Coal Power Plant 16.0 2.7
Wood Power Plant 20.3 2.6
From Methane 118.7 2.3
5 Ethanol 10.5 3.2
6 Biogas (Puerto Rico dairy wastes) 24.8 2.4
7 Ethyl Alcohol from Biomass 8.8 1.1
Notes to Table 3.2
1. Alaskan Oil from Brown et.al, 1993, mid east oil based on 6.11 E9 J/bbl,
20% refining and transportation costs, and emergy/money ratio of
1.2 E12 sej/$
2. Average of offshore and onshore Texas Natural Gas (King, 1991)
3. from Barbir, 1992
4. Coal & wood from Table 3.3;
5. This study
6. Methane from Appendix B
7. Odum et al, 1986
3-10
Block (1993) provides an energy pathway analysis of fuel transportation alternative (see
example in Figure 3.6a). In this analysis, efficiencies of energy conversion (given as percentages
along the bottom line of Figure 3.6a) were used to determine the amount of primary energy
required to produce "1000 units" of energy in vehicle propulsion. The energy pathway analysis
shows that it requires 5638 crude oil Joules to produce 1000 Joules of vehicle propulsion.
Pathway evaluation using EMERGY, including all inputs, is compared in Figure 3.5b. The
EMERGY inputs come from two sources, in the fuels consumed (278 E8 sej) and the EMERGY in
goods and services used (688.4 E6 sej). The total EMERGY required per 1000 Joules of vehicle
propulsion is the sum of these two sources (966.4 E6 sej).
Table 3.3 contains the energy requirements for four transportation systems that were
obtained using both energy pathway analysis (Block, 1993) and EMERGY pathway analysis.
Energy pathway analysis expresses the numerator in energy units, treating energies of different
kinds as if they were equal measures of work, while EMERGY analysis expresses the numerator
in joules of one kind of energy required to deliver the transportation energy. Although the
limitation is rarely stated, energy pathway analysis only includes energies of intermediate quality,
those often considered under the group name "Exergy." To facilitate comparison, EMERGY
evaluations in Table 3.3 are expressed in units of two kinds of EMERGY (solar EMERGY and
coal EMERGY).
Energy pathway analysis indicates that the lowest ratio (presumably the most desirable) is
the electric vehicle, followed by gasoline, fuel cell and natural gas. EMERGY analysis indicates
that the lowest ratio is natural gas, followed by gasoline. Both the electric and fuel cell vehicles
were highest, with approximately the same ratio. The two techniques give different results when
vehicle and fuel types are compared with each other because EMERGY analysis includes the
EMERGY costs of materials and services that are consumed indirectly in the production of the
vehicle or fuel type. The evaluation of what is necessary to deliver a set amount of mechanical
energy to the wheels should include all requirements, both direct and indirect (including, for
example, those necessary to modify engines, add batteries, or add storage vessels).
Discussion of Alternative Fuels
Hydrogen
Hydrogen occurs as a gas with a molecule made of two hydrogen atoms (H2). When
burned with atmospheric oxygen, hydrogen gas has the most intense heat of all the fuels with 29.1
Elec.
-I
Generation
Plant
36%
Delivered
Elec.
On-Board
Elec.
Rotary
Power
-,I
W m W- P w
Elec. Trans.
Battery
Storage
70%
Elec. Motor
90%
1000 J
Vehicle
Propulsion
Power
Train
85%
(from Block, 1993)
Crude 011 Units
1000 J of Vehicle Propulsion
5638 C.O. unite
1000 J
688.4E6 sel
Vehicle Propulsion
Total Emergy Input
1000 J of Vehicle Propulsion
966.4E6 eel
1000 J
Figure 3.6. Comparison of methods of pathway analysis. (a) Energy analysis (Block, 1993); (b)
EMERGY evaluation.
5638
Fossil
Fuel
i
VW
" /. /
Table 3.3. Comparison of Methods of Pathway analysis
Ratio of Input Required to Output Delivered*
Note Fuel/Vehicle Type Energy analysis Emergy Analysis
(sej/J) (cej/J)
1. Gasoline 9.7/1 9.9 E5/1 24.8/1
2. Electricity 5.6/1 10.6 E5/1 26.5/1
3. Natural Gas 12.7/1 7.6 E5/1 19/1
4. Fuel Cell 11.9/1 10.6 E5/1 26.5/1
Units of the ratio are as follows:
Energy analysis: (units of primary energy) / (unit of vehicle propulsion)
Emergy analysis: (Solar emjoules) / (Joule of propulsion)
(Coal emjoules) / (Joule of propulsion)
Notes to Table 3.3
1. Energy analysis includes refining and distribution losses, engine efficiency
and power train efficiency from Block (1993)
Emergy analysis includes solar energy cost of producing crude oil,
emergy costs of refining and distribution, and efficiencies of
engine and power train
2 Pathway analysis does not include the efficiencies of fossil fuel production
If the efficiences used in the gasoline engine were used as the
efficiency of producing and transporting fuel to a power plant,
then the ratio would be about 7.0/1
3 In both cases, the engine type is an Internal Combustion engine
4 In both cases, the hydrogen for the fuel cell is derived from reforming
natural gas
3-13
Calories per gram (121, 813 joules/gram). Compared with a gram of sugar ( 4 Calories per gram)
its heat is intense. With an atomic weight of 1, hydrogen is also the lightest of all fuels. For these
reasons, hydrogen is required for weight-dependent processes, such as sending rockets into space.
Hydrogen is the most abundant element in the Universe but in the earth biosphere it is rare
as a gas for two reasons: (1) at the top of the atmosphere molecular collisions give hydrogen
molecules (H2) enough velocity to exceed that required to escape the earth's gravity, and (2) in the
presence of sunlight or lightning, hydrogen combines with oxygen to form water.
Hydrogen is not a vapor at ordinary refrigerated temperatures, and must be compressed
within heavy-walled containers to be stored. With a small, rapidly-moving molecule, hydrogen
leaks from many containers and pipes more than other gases. Hydrogen can be dangerous as
shown by the experience with fire in dirigibles. A compressed gas tank, at pressures of 3000
pounds per square inch or more, can be dangerous if its valve connections are broken, with the
escaping gas driving the tank on an erratic path.
Hydrogen gas is among the alternative energy systems being considered for the future,
when petroleum-based fuels are scarce and more expensive. How competitive would a hydrogen
system be? Would it be energy conserving? Would it be economical? Should research initiatives
and investment be made in hydrogen systems? A hydrogen system, including its sources and
uses, was evaluated and compared with other alternative fuel sources and other uses of hydrogen,
to see if hydrogen is a promising fuel alternative for the future.
At present, in the United States as in much of the world, reserves of natural gas are large.
The net EMERGY contribution of such reserves is as large or larger than liquid petroleum, which
means that natural gas is likely to continue to be economically competitive as a source of
concentrated heat for industry, but locally dependent on the availability and investment in pipelines.
Natural gas is being used increasingly for motor transport with government assisted programs in
New Zealand, California, and Florida, for example. To use natural gas for fuel transportation,
vehicles have to be fitted with compressed gas tanks and a system of gas recharging stations must
be established. When and if natural gas becomes more important to vehicular transportation, as it
already is for home heating and industry, the compressed gas infrastructure is likely to become
more common. This system could be adapted to hydrogen if there is any net EMERGY advantage.
In the long run, proponents suggest that when natural gas supplies become scarce and
expensive, hydrogen could be supplied from electric power sources, provided there are adequate
electric sources. When the high net EMERGY fossil fuels are no longer available and prices are
higher, fuel conservation measures will be greater and demand will be less.
Alternatives for Hydrogen Production and Use
There are several ways in which hydrogen can be concentrated for use as a fuel, including:
separation from natural gas; by chemical processing from methane; and separation from water via
electrolysis. Table 3.4 and Figure 3.7 summarize the EMERGY evaluations of 5 alternative
methods for deriving hydrogen, and for comparison, an evaluation of natural gas as a
transportation fuel source. The EMERGY yield ratios and transformities indicate which systems
will be more important in the future. Evaluations of the 6 alternatives are given below.
Case 1. Natural gas. Natural gas can be drilled and supplied with EMERGY yield ratios in
the range of 6/1 to 10/1, depending on transport distance. Figure 3.7a shows the net EMERGY
yield for natural gas. Natural gas can be used in compressed tanks for vehicles, although this
reduces the net EMERGY contribution by about half (approximately 3.4/1, according, to King's
[1991] evaluation of its use in Texas busses). Since gasoline can currently be supplied to vehicles
at a higher ratio, the natural gas compressed tank alternative will not be competitive until the
general market price of liquid fuels rises. The rise in price reduces the EMERGY yield ratio of
liquid fuels, causing the natural gas system to be more competitive as the net EMERGY of liquid
fuels declines.
Case 2. Hydrogen produced from natural gas. Hydrogen can be produced from steam
reforming of natural gas with a EMERGY yield ratio of 4.5/1 (Figure 3.7b). For general heating
and motor transport, natural gas can suffice without the extra processing and additional costs that
are necessary to derive hydrogen from it. Since natural gas has a higher EMERGY yield ratio than
the hydrogen that is derived from it, it makes little sense to incur the additional energy costs to
make a similar fuel for general heating or transportation.
Case 3. Hydrogen produced from electricity generated from fossil fuels.
Hydrogen can be generated from water (H20) by electrolysis, which separates hydrogen from
oxygen using electric power (Figure 3.7c). If the electric power is generated in a fossil fuel plant,
the EMERGY yield ratio is about 2.4/1. Although this allows electric energy to be transformed
into a form usable for moving vehicles, the EMERGY yield ratio is less than that of current fuels or
natural gas. A better yield can be obtained by converting the coal, oil, or natural gas directly to
motor fuel, with about a 60% or better conversion and a better net EMERGY yield.
Table 3.4. Transformity and Net EMERGY Yield Ratio of Hydrogen
Note System Solar transformity Net EMERGY
solar emjoules/Joule Yield Ratio
1 Natural gas 48,000 6.8
2 Hydrogen from Natural gas 76,300 4.5
3 Hydrogen from fossil fuel
electric power plants 204,000 2.4
4 Hydrogen from hydropower 110,563 4.9
5 Hydrogen from nuclear power 203,956 4.7
6 Hydrogen from photovoltaic cells 69,000 1.007
1 Offshore natural gas in Texas (King 1992)
2 Steam reforming; EMERGY evaluation by Barbir (1992). Given the natural gas, the net
EMERGY yield ratio of the conversion is 11.4, butif the net EMERGY yield ratio of the natural
gas is 6.8, the combined feedbacks make the overall combined process of processing and
transforming gas to be 4.5
3 Hydrogen production from electric power evaluated by Barbir (1992), given the electric power
and using an electrical transformity from a coal power plant (160,000 sej/J). If coal fired net
EMERGY yield ratio is 2.5, then the accumulated net EMERGY yield ratio is 2.4
4 Hydroelectric power evaluated with solar transformity of 85,437 and net EMERGY yield ratio
5.7
5 Requirements for conversion used in item #3 were combined with EMERGY analysis of U.S.
Nuclear Fission power (Lapp, 1992). Transformity of Electric power used as that of fossil fuel
plants, but net EMERGY yield ratio 4.9
6 Hydrogen from solar driven photovoltaic cells evaluated by Barbir (1992)
(a) 1 63 s services
(a)- Water
Fuels
Natural 1
Ga Drilling, 1114 natural Gas
Gas Processing natural Gas
Reserve
E15 solar emjoules
Goods
(b) 163 270 services
NtrlNatural--12 Water
Natural rilg Gas Steam 1221
Gas Processing 1114 Reforming Hydrogen
;D g Hdrocessongge
Reserve
E15 solar emjoules
--- 12Goods
11521 235 /S services
1152
Electricit
(c) 83 \water
Fossil Fuel 4608.1, i 469 ,
Coal Power Pant Electrolysis Hydrogen
S- Goods
"5 514 / Services
(d) Electricit'
83 Water
Geopotential 2460 2543
in IHydroelectric Electrolysis I Hydrogen
i so Plant Electric Hd"
Water Power
E15 solar emjoules
Goods
9 3 1006 S/ services
Electric,
(e) 8, 3 \Water
Nuclear Nuclear 4608 Hd4691
FNuclearl Fiso Ele"ric Electrolysis Hydrogen
Fuel ^ Fission Electric
Power
E15 solar emJoules
Goods
10705 10788 Services
(f( ) Electrici
M 83 Water
.079 Photovoltaic 4608 Electrolysis 4691 hydrogen
Sunlight OGrid --yorogen
Electric
E15 solar emjoules Power
Figure 3.7 Summary diagrams of EMERGY evaluation of natural gas (a) and hydrogen (b-f)
calculated in Table 3.4.
Case 4. Hydrogen produced from hydroelectric power. Hydrogen can be generated
from water by electrolysis using hydroelectric power (Figure 3.7d). The EMERGY yield ratio
(4.9/1) is lower than present fossil fuel alternatives for transport fuel, but has a much better yield
ratio than some alternatives being proposed for fossil fuels that are less available (such as motor
fuels from biomass). If EMERGY evaluations of hydroelectric power include the contributions of
streams and rivers that are lost when a dam is built, a lower EMERGY yield ratio is found.
However, there is little unutilized hydroelectric capacity in rivers of the United States. Because of
its flat terrain, the potential for hydroelectric power in Florida is negligible.
Case 5. Hydrogen produced from nuclear power. Hydrogen can be produced by
electrolysis from electricity generated by nuclear plants, and thus provides a way to harness nuclear
energy to operate moving vehicles (Figure 3.7e). A recent EMERGY evaluation of U.S. nuclear
fission power (Lapp, 1992) showed a EMERGY yield ratio of 4.9/1 and, when combined with the
electrolysis process, yields an overall ratio for hydrogen production of 4.7/1. This could be
competitive for motor transport after the fossil fuel period, for the years when high quality nuclear
fission fuels are still available. However, large expansion of nuclear power in Florida would be
necessary to provide the energy requirements for transportation, as well as household, commercial
and industrial needs.
Case 6. Hydrogen from solar photovoltaic cells. Hydrogen can also be generated from
electrolysis using electricity from photovoltaic cells that use direct sunlight (Figure 3.7f).
However, the EMERGY yield ratio of solar voltaic systems is so low, there is no net EMERGY
contribution to the economy (0.43/1). Making hydrogen from this electricity with additional input
requirements makes the yield ratio even less. The ultimate reason for the poor conversion may be
an inherent thermodynamic limit on converting dilute energy into a very concentrated one in a
single step. After a billion years of evolution, green plants operate a chlorophyll solar voltaic cell
which has higher conversion efficiencies, possibly representing the thermodynamic maximum
conversion possible. This may be the ultimate limit for solar voltaic research. Appropriate
comparison of chlorophyll with silicon cells evaluates the efficiency of both of these cases in the
conversion of photons to displaced electrons.
Transformity of Hydrogen
In order to use the appropriate transformity principle to select the best energy alternatives,
the best (lowest) transformity which is possible for each fuel must be established. The ultimate
thermodynamic limit to the efficiency for generating hydrogen in open systems operating at
maximum power is not yet known. Data on some solar transformities found for hydrogen are
shown in Table 3.4. These include processes where there are unnecessary long sets of
transformations which, as a result, are less efficient (higher than the minimum transformity).
Although more examples need to be evaluated, one may infer from data available so far that the
best possible transformity for hydrogen is higher than fossil fuels and less than electric power. If
this is valid, then the methods that depend on electric power are wasteful and alternatives that can
generate motor fuels more directly are likely to be more competitive economically. Where
hydrogen can be made with a lower transformity than electricity, it can be used for more general
heating purposes and to make electricity. If the solar transformity of hydrogen was higher than
electricity--which is what is obtained when hydrogen is made from electrolysis of water--then it
would not generally make economic or energetic sense to use hydrogen for lower transformity
purposes such as heating and other current uses of electric power.
Since electric power generates hydrogen, the transformity of hydrogen calculated from this
process (Table 3.4) is higher than that of electricity (Table 2.1). And since the reverse process can
also be arranged, electricity can be generated from hydrogen (and oxygen). Barbir (1992) raises
the question as to which has the higher transformity--hydrogen gas or electric power-when the
most efficient chain of processes is used. This is a critical questioning energy conservation. Since
energy is dispersed in each transformation, energy should net be transformed any more times than
is necessary to accomplish a purpose.
In other words, if hydrogen is necessarily higher in the transformity scale than electricity,
then its use can be justified only for very special purposes for which electricity is not adequate. If
the transformity of hydrogen is lower than electricity, then it may be substituted for some
processes, providing the net EMERGY yield is competitive. Tables 2.1 and 3.4 summarize the
solar transformities of hydrogen and electric power as calculated for several processes.
An as yet to be determined effect is the pollution caused by each alternative, and the
resulting energy costs for cleanup and the loss of natural and agricultural productivity. These
effects could alter the results of the analysis. The electric vehicle system would act more as a point
source of pollution (the electric power plant outlet), and may be easier to clean up. On the other
hand, conventional vehicles act as non-point sources of pollution. In either case, the costs of
pollution abatement could be substantial. Their pollution would probably be impossible to clean up
to the same degree as a point source, and environmental impacts would have to be tabulated for
both cases. The general question is whether it is more cost effective to concentrate or dilute
pollution, since the earth must ultimately assimilate the pollution. For a complete analysis,
environmental impacts should be considered as well.
3-20
4. Hurricane Andrew:
EMERGY Analysis of Dade County, The Hurricane Impact Area and
Evaluation of Damages and Costs
by
Mark T. Brown and Robert Woithe
The normal suit of renewable and non-renewable energies driving an economy can be
thought of as "ordering" energies since they act, for the most part, to develop ordered storage,
structures, and work processes. While working economies generate disorder in the form of waste
heat pollutants, and some local disordering of ecological systems, for instance, the net effect in
growing, robust economies is the creation of order that is greater than the disordering influences of
work processes. This net effect is a spatial and temporal concentration of order. If the larger
system is considered, that is, the biosphere as a whole, the net effect according to the 2nd energy
law is an increase in disorder. Thus the balance of order and disorder is spatially and temporally
constrained. Any temporary increase in order at one location is accompanied by disorder in
another location equal to or greater than the ordering influence.
The normal suit of energies driving any system also contains energies whose magnitude,
transformity, and frequiecy are such that the system is not necessarily adjusted to them. Examples
are extreme rainfall events that cause floods, tornadoes, earth quakes, and of course hurricanes.
Because these energies are not constant, but appear from time to time with much force, they often
act in disaster like fashion, since the system is not adapted to them. When this happens there is a
temporary increase in disorder, often followed by a burst of rebuilding activity. Energies are
converged at the point of disaster to rebuild and renovate. The net effect of which may be an
overall increase in ordered structure immediately following the disaster.
Energies that cause disasters have magnitudes, frequencies, and transformities that are
greater than the normal suite of driving energies in any system. They are pulses of energy that
when released can cause momentary disorder. Yet these disordering energies are variable. Their
frequency and magnitude vary from occurrence to occurrence. Lower magnitude events occur
more frequently than higher magnitude events. Thus often areas experience relatively minor
hurricanes every couple of years, while the very large storms occur only once every 50 years or
so.
A hurricane represents a disordering energy to terrestrial systems including those of
humanity when the magnitude is greater than that which the systems are adapted. Adaptation may
be related to the frequency of occurrence, and the turnover time (useful life) of the structure
COLLIER
Marco
Miami
-- _ftftwa
A;C IMP AeCT
-?: "crA~f)A
Florida Bay
Figure 4.1. Map showing the Hurricane Andrew Impact Area
. *Att,-f-.- .
DADE
affected. Theory would suggest that systems organize themselves to withstand pulses of a
frequency that is less than the useful life of their structure. In other words, it becomes more
"efficient' to allow the destruction of easily replaced (and therefore relatively inexpensive and short
life) structure than it is to build it more expensively to withstand larger magnitude events. Another
way of saying this is that if the frequency of a pulse event is longer than the turnover time of the
structure, it does not make energetic sense to build the structure to withstand its forces.
Quite frequently systems respond to disorder with an outburst of ordering process to
rebuild and replace that which is lost. This frenzy of activity is tempered in intensity and duration
only by the availability of energies with which to support it. In this analysis of Dade County, the
ordering energies inflowing on an annual basis and the disordering energies of the hurricane are
evaluated and compared. The response to the hurricane was an inflow of workers, money, and
resources to rebuild and repair the damage. These ordering energies are also evaluated and
compared to the economy and the disordering influences of the hurricane.
EMERGY Evaluations of Dade County and the Impact Area
EMERGY evaluations of Dade County (1991, the latest year for which there is data) and
the area of hurricane impact (Figure 1) were conducted to develop insight into the magnitude of
hurricane damage and rebuilding efforts, and to provide the background for growth scenarios for
the south Dade region. The evaluations were done for both the impact area and Dade County as a
whole to evaluate what effect the hurricane had at different scales. The impact area, the smaller of
the two scales, is that area in south Dade, Monroe, and Collier Counties over which the hurricane
passed. Total EMERGY budget, or driving energies, of the region were evaluated and compared
to the energy in the pulse of hurricane Andrew and the EMERGY in the response and rebuilding
efforts. For purposes of perspective, the same comparisons were made with the economy of Dade
County as a whole.
Tables 4.1 through 4.3 provide the details and indices of the EMERGY evaluation
(footnotes to the tables are found in Appendix C). Total EMERGY use in Dade County was 66.1
E21 sej/yr in 1990 (Table 4.1), while for the impact region, total EMERGY use was 15.4 E21
sej/yr (Table 4.2). By far the largest renewable energy contribution to the Dade County economy
was from rain, followed by tidal energy. These energies were relatively insignificant when
compared to purchased energies. Only 3.4% of the total EMERGY use in Dade County was from
renewable sources (and 96.6% was purchased). The impact area, on the other hand, had a
renewable EMERGY base equal to about 20% of the total EMERGY budget Table 4.3 gives these
summary indices and others for both Dade county and the impact area. As a result of the vast
Table 4.1. Annual EMergy support for Dade County, Florida in 1990,
Note Item Raw Trans- Solar Emdollars
Units formity EMergy (1990US)
(J,$ or g) (sej/unit) (E19 sej) (E8 em$)
RENEWABLE RESOURCES:
1 Sunlight 3.56E+19 J 1 3.56 0.22
2 Wind, kinetic 6.00E+17 J 620 37.20 2.33
3 Rain, geopotential 6.25E+13 J 8900 0.06 0.00
4 Rain, chemical 9.19E+16 J 15000 137.90 8.62
5 Tide 3.89E+16 J 24000 93.43 5.84
6 Waves 8.07E+15 J 26000 20.99 1.31
INDIGENOUS RENEWABLE ENERGY:
7 Agriculture product. 5.50E+12 J 2.00E+05 0.11 0.01
8 Shellfish 2.00E+12 J 8.00E+05 0.16 0.01
9 Finfish 1.90E+12 J 2.00E+06 0.38 0.02
NONRENEWABLE SOURCES FROM WITHIN SYSTEM:
10 Groundwater 1.22E+13 J 41000 0.05 0.00
11 Limestone 4.70E+11 g 6.70E+06 0.31 0.02
IMPORTS AND OUTSIDE SOURCES:
12 Fuel 1.60E+17 J 5.30E+04 848.00 53.00
13 Electicity 2.20E+17 J 1.59E+05 3498.00 218.63
14 Net migration 5.12E+13 J 4.06E+07 207.87 12.99
15 Services in Imports 1.27E+10 $ 1.60E+12 2032.00 127.00
EXPORTS:
16 Agriculture prods. 1.05E+14 J 2.00E+05 2.09 0.13
17 Limestone 4.70E+11 g 6.70E+06 0.31 0.02
18 Services in Exports 3.12E+08 $ 1.60E+12 49.92 3.12
Footnotes to Table 4.1 can be found in Appendix C
Table 4.2. Annual EMergy support for Hurricane Andrew Impact Area in 1990
Note Item Raw Trans- Solar Emdollars
Units formity EMergy (1990US)
(J,$ or g) (sej/unit) (E19 sej) (E8 em$)
RENEWABLE RESOURCES:
1 Sunlight 3.12E+19 J 1 3.12 0.20
2 Wind, kinetic 4.00E+17 J 620 24.80 1.55
3 Rain, geopotential 1.68E+13 J 8900 0.01 0.00
4 Rain, chemical 9.45E+16 J 15000 141.80 8.86
5 Tide 7.79E+16 J 24000 186.87 11.68
6 Waves 5.44E+15 J 26000 14.15 0.88
INDIGENOUS RENEWABLE ENERGY:
7 Agriculture product. 2.48E+12 J 2.00E+05 0.05 0.00
8 Shellfish 5.62E+12 J 8.00E+05 0.45 0.03
9 Finfish 2.07E+12 J 2.00E+06 0.41 0.03
NONRENEWABLE SOURCES FROM WITHIN SYSTEM:
10 Groundwater 2.31E+12 J 41000 0.01 0.00
11 Limestone 1.18E+11 g 6.70E+06 0.08 0.00
IMPORTS AND OUTSIDE SOURCES:
12 Fuel 3.04E+16 J 5.30E+04 161.12 10.07
13 Electicity 4.18E+16 J 1.59E+05 664.62 41.54
14 Net migration 1.28E+13 J 4.06E+07 51.97 3.25
15 Services in Imports 2.41E+09 $ 1.60E+12 386.08 24.13
EXPORTS:
16 Agriculture prods. 4.70E+13 J 2.00E+05 0.94 0.06
17 Shellfish 5.06E+12 J 8.00E+05 0.40 0.03
18 Finfish 1.86E+12 J 2.00E+06 0.37 0.02
19 Limestone 1.18E+11 g 6.70E+06 0.08 0.00
20 Services in Exports 2.70E+08 $ 1.60E+12 43.18 2.70
Footnotes to Table 4.2 can be found in Appendix C
Table 4.3. Dade County and Hurricane Andrew impact area EMergy indicies derived from Tables 4.1
and 4.2.
Name of IndexExpression Impact Area Dade County
Total imported emergy
Total EMergy inflows
Economic component
Total exported emergy
% EMergy Use locally renewable
Ratio of Nonrenewable to renewable
Ratio of imports to exports
Imports minus exports
% of emergy use purchased
Fraction imported service
% of emergy use derived
from home sources
% of use that is free
Use per unit area
Use per person
Renewable carrying capacity
at present living standard
Ratio of use to GDP
Fraction Electric
Fraction Fossil Fuels
Fuel use per person
1211.8 E+19 sej/y
1540.7 E+19 sej/y
1263.1 E+19 sej/y
43.3 E+19 sej/y
20.6 %
3.8
28.0
1168.6 E+19 sej/y
76.1 %
0.2
20.7 %
20.6 %
0.5 E+13 sej/m2-y
4.1 E+16 sejlper-y
79494.2 people
2.4 E+12 sej/$
0.4
0.1
4.2 E+15 sej/per-y
6378.0 E+19 sej/y
6610.0 E+19 sej/y
6584.1 E+19 sej/y
50.2 E+19 sej/y
3.4 %
28.5
127.0
6327.8 E+19 sej/y
93.6 %
0.3
3.4 %
3.4 %
1.2E+13 sej/m^2-y
3.5 E+16 sej/per-y
65846.8 people
2.0E+12 sej/$
0.5
0.1
4.4 E+15 sej/per-y
differences in population density and development status, the two regions are quite different.
EMERGY use per unit area in Dade County is nearly three times the EMERGY use per unit area
characteristic of the impact area. On the other hand, because of the relatively low population in the
impact area EMERGY per capital is 20% greater than in Dade County.
Table 4.4 summarizes the total EMERGY in structure of the various subsystems of the impact
area. The greatest structural components are within the urban systems, many of which are 1 to 2
orders of magnitude greater than the structure in ecological communities. The final column in Table
4.4 gives estimates of EMdollars for each subsystem. EMdollars are the estimated amount of Gross
Domestic Product (GNP) that would be required to replace the structure.
EMERGY Evaluation of Hurricane Andrew
EMERGY evaluations of the damages and costs resulting from Hurricane Andrew are given in
Table 4.5 and summarized in Figure 4.2. The diagram summarizing EMERGY disordering and
ordering shows the hurricane interacting with natural and urban structure (for simplicity, agricultural
systems have been incorporated into the urban systems in the diagram). The interaction is a
disordering stress, pulling from each compartment ordered structure. In natural systems, much of the
disordered parts are recycled and reused in building new structure. Unlike natural systems, the
disordered parts from urban and agricultural systems are not recycled locally, but are shown
accumulating in a storage of wastes and slowly degrading away. A pathway of recycle is shown, but
very little of the disordered urban and agricultural structure is recycled. Some of the disordered urban
and agricultural structure may have been recycled (aluminum, steel, glass, etc) as exported material,
shown leaving the system to the right. No data were found on the magnitude of this pathway.
The diagram shows the exodus of population, in response to the disordering of urban
structure. The loss was estimated at about 50,000 people (Powers, 1993). However, because of
rebuilding efforts, there was also an inflow of population. Newspaper articles suggested that the
inflow of this temporary work force was about 100,000 people; or about twice the number of
residents that moved away after the hurricane. The hurricane disaster caused an outburst of local
activity that was financed by aid and insurance money that flowed into the local economy from
elsewhere. The inflow of money (about 20 billion dollars) was used to purchase goods and services,
as well as to pay the salaries of reconstruction workers.
Table 4.4 summarizes the EMERGY evaluation of hurricane impacts and costs of rebuilding.
First the EMERGY in hurricane winds was estimated as 2.2 E21 sej. This is an estimate of the wind
energy absorbed by the terrestrial ecosystems and urban structure of the impact area. Not included is
Table 4.4. EMergy value of storage of the Hurricane Andrew Impact Area by land use category
Note Item Raw Trans- Solar Emdollars
Units formity EMergy (1990US)
(J,$ or g) (sej/unit) (E19 sej) (E8 em$)
1 Beaches, dunes & salt
flats 9.5E+10 J 3.5E+04 0.003 0.002
2 Emerging systems 3.0E+11 J 3.5E+04 0.01 0.01
3 Scrub mangroves 6.5E+12 J 3.5E+04 0.23 0.14
4 Lakes and ponds 1.3E+12 J 3.5E+04 0.04 0.03
5 Urban parks 6.3E+12 J 3.5E+04 0.22 0.14
6 Wet prairie 3.8E+14 J 3.5E+04 13.4 8.4
7 Scrub cypress 5.2E+13 J 3.5E+04 1.8 1.1
8 Pine uplands 1.5E+13 J 3.5E+04 0.54 0.34
10 Agriculture 5.0E+14 J 3.5E+04 17.4 10.9
11 Mangroves & salt marshes 2.0E+15 J 3.5E+04 71.4 44.6
12 Cypress domes & strands 9.0E+14 J 3.5E+04 31.5 19.7
13 Hardwood hammocks 1.6E+14 J 3.5E+04 5.7 3.6
14 Sawgrass marsh 5.1E+15 J 3.5E+04 177.1 110.7
15a Single-family residential-
wood 4.8E+16 J 3.5E+04 1688.1 1055.0
15b -concrete 8.5E+12 g 7.0E+07 593.6 371.0
16a Transportation-asphalt 6.5E+15 J 5.3E+04 346.0 216.2
16b -subbase rock 4.0E+11 g 6.7E+06 2.7 1.7
17a Multi-family residential-
wood 1.4E+16 J 3.5E+04 484.0 302.5
17b -concrete 2.6E+12 g 7.0E+07 179.2 112.0
18 Commercial & industrial 2.3E+12 g 7.0E+07 161.7 101.1
Footnotes to Table 4.4 can be found in Appendix C
Table 4.5 Emergy Damages and Costs Resulting From Hurricane Andrew
Item Storage or Flow Amount Transformity Emergy Emdollars
(units) (sej/unit) (E+18 sej) (E6 em$)
Damages
Environmental Systems
Structure (biomass)
Productivity
Agricultural Systems
3 Buildings & Equip
4 Structure (biomass)
5 Productivity
Urban Systems
6 Infra-struct. (wood)
Infra-struct. (conc)
Infra-struct (services)
7 Productivity
8 Flectricitv
Social Systems
9 Population
5.16E+14 J 35000
3.07E+16 J 3500
9.65E+08
8.57E+14
2.67E+15
1.9E+12
35000
7000
1.71E+11 g 100000000
5.83E+12 g 92600000
6.97E+09 $ 1.9E+12
6052.50
4.61E+15 J 160000
5.00E+04 p 9.4E+16
Cleanup and Restoration Costs
10 Dollar payments
Federal Sources 9.00E+09
State Sources 5.00E+08
Insurance Co. 1.00E+10
Private Sources 2.30E+07
11 Human pop. inflow
Temporary workers 5.71E+04
12 Productivity Increase
Permanent Jobs 8.00E+04
1.6E+12
1.6E+12
1.6E+12
1.6E+12
9.4E+16
18.05
107.54
1833.50
30.01
18.71
17.12
540.32
13243.00
3185.53
737.60
4700.00
14400.00
800.00
16000.00
36.80
5371.29
9.4E+16 7520.00
Footnotes to Table 4.5 can be found in Appendix C
9.50
56.60
965.00
15.79
9.85
9.01
284.38
6970.00
388.21
2473.68
9000.00
500.00
10000.00
23.00
2826.99
3957.89
Figure 4.2. Systems diagram of the impacts and resulting inflows of ordering energies that
resulted from Hurricane Andrew
4-10
the wave energy resulting from the hurricane that was absorbed along the coast. Second estimates of
damages incurred by ecological, agricultural, and urban systems are given. In each category, both the
losses associated with damaged structure and the loss of productivity are given separately.
Productivity losses were calculated based on estimated recovery times.
Damages to ecological, agricultural, and urban systems were approximately 16.8 E21 sej and
population loss was 4.7 E21 sej, giving a total loss of about 21.5 E21 sej. The costs of cleanup and
rebuilding were 23.4 E21 sej and the gain from temporary population increase was 5.4 E21 sej. A
productivity increase based on the creation of 80,000 new permanent jobs results in an increase of 7.5
E21 sej. In all it appears that the EMERGY value of damages was about equal to the EMERGY in the
rebuilding effort.
The relative impact of the hurricane was evaluated by comparing the total EMERGY budget of
the region (Table 4.2) and the EMERGY value of storage within the impact area (Table 4.4) with the
disordering effect of Andrew. The losses of ecological system structure was about 6% of the total
structure and urban system structural losses were about 18% of total. Combined losses of
productivity from natural, agricultural, and urban systems was 15% of the annual EMERGY budget
of Dade county and about 64% of the annual EMERGY budget of the impact area. The EMERGY
value of total disordered structure (including natural, agricultural, and urban) was about 32% of the
annual EMERGY budget of Dade County and represented about 135% of the annual budget of the
impact area. The EMERGY value of cleanup and rebuilding was about 34% of the annual EMERGY
budget of Dade county and about 147% of the EMERGY budget of the impact area.
In all, the hurricane represented a significant impact to the south Florida region, and as a
result, questions concerning the long term implications of hurricane disordering on economies were
addressed using a simplified simulation model of the south Florida economy and environment.
Simulations of Hurricane Disordering
The effects of hurricane disordering and benefits from increasing the quality of structure to
minimize hurricane damages was tested and evaluated using a simulation model. Given in Figure 4.3
is an aggregated systems diagram of the economy of south Dade county including its environmental
support base, and external trade. Equations for the state variables (natural structure, urban structure,
and money) are given below the diagram. These equations were programmed in a simple simulation
of 250 years of growth of urban structure. Figure 4.4 gives 4 graphs which summarize some of the
simulation results of the model.
In the first graph (Figure 4.4a), the amount of natural structure is shown as it might have
been before any significant human presence in south Florida. Each break in the graph line represents
4-11
HURRICANE
R = o /(1+Ko* Q)
E=K4 *A*Q
d =K *R' Q- K2Q- K3 A Q
dt
dM = Pe E K M
dt
dA= K M / Pg K *A K7 A Q
dt
Figure 4.3 Simulation Model of Hurricane disordering in South Dade
(b)
125
Time (years)
(c)
125
Time (years)
250
250
125 250
Time (years)
(d)
250
125
Time (years)
Figure 4.4. Simulation results of the model in Figure 4.3 showing (a) graph of natural structure
affected by small hurricanes on a 7 year cycle and major storms on a 50 year cycle, with no urban
development; (b) graphs of natural structure, urban development, and money supply with no
hurricane damage; (c) graphs of natural structure, urban development, and money supply with
small hurricanes on a 7 year cycle and major storms on a 50 year cycle; (d) graphs of natural
structure, urban development, and money supply with small hurricanes on a 7 year cycle and major
storms on a 25 year cycle
4-13
Natural Structure
5-0 Year Storm
\/ 5 Year Storm '\
a hurricane event. The smaller events occur on 7 year cycle, while the larger storms occur on a 50
year cycle. The size of the events were programmed to be somewhat random. After each storm
event, the regrowth of natural structure occurs until the region is "hit" by another storm.
In the second graph (Figure 4.4b), the amounts of natural structure, urban structure, and
money over time are shown as they might be if there were no hurricanes. The human presence in
south Florida begins to increase in the first 20 years, and grows significantly over the next 100 years.
Natural structure declines as more and more land is converted to urban uses. There is a leveling of the
economy (ie minor net growth) after the 150th year of the simulation, as a result of the limiting effect
of the reduction of the natural support base.
The third graph (Figure 4.4c) shows the effect of hurricanes on the growth and development
of the region. Hurricane frequency is the same as in Figure 4.4a, that is, small hurricanes every 7
years and larger storms every 50 years. The breaks in the graphs of money and natural and urban
structure result from disordering influence of the hurricanes. Since each hurricane was programmed
to be different, the amount of disorder varies from one storm to the next. The effect of each major
storm is to disorder structure and cause a temporary increase in the money within the region (resulting
from outside aid). The regrowth of urban structure after each major storm is facilitated by the
additional aid.
In the fourth graph (Figure 4.4d) the effect of increased frequency of major hurricane events is
simulated. The frequency was increased to 25 years instead of 50 years. The increased frequency
results in lower levels of urban and natural structure and a smaller local money supply. Since aid is
sent to the region with each hurricane, the regrowth of urban structure is facilitated. Yet the total
amount of urban structure never reaches levels that are characteristic of the region with longer
intervals between hurricanes. Simulations of the model when aid is reduced after a hurricane, slows
down recovery of the urban systems and results in even lower total structure. The aid has a
stimulating effect rebuilding the structure much quicker than would be possible without it.
Benefits of Increased Structural Quality
To address questions related to the relative benefits of increasing the quality of built structure
and thus minimizing damages from future hurricanes, varying levels of increased quality were
programmed and related to damages from hurricanes. A benefit -cost analysis resulted where the
benefit was the difference between damages incurred with the present quality of structure and lower
damages that would result with increased structural quality. The costs in this analysis were the
increased EMERGY costs of the added structural quality. The model was simulated with varying
hurricane strengths, 50 year storm events, and a 250 year time horizon.
4-14
The graph in Figure 4.5 shows the relative benefit-cost ratio (X axis) for hurricanes of varying
damage intensity (Y axis). Each set of symbols represents a different expenditure for increasing
structural quality, and each data point results from a 250 year simulation of the model where the
relative damage by hurricanes during that time varied from those that resulted in 20% of Andrew
damages to those that resulted in about 130% of Hurricane Andrew damages. The highest line
(dashed data points) represents a 2% increase in expenditures for higher quality structure, while the
lowest line (solid square data points) represents a 20% increase in expenditures. A benefit-cost ratio
of 1.0 represents a break even point, thus data points above 1.0 have positive benefit-cost ratios and
those below 1.0 have negative ratios.
The simulation results suggested that, generally, increased expenditures on the order of 2% to
4% of current structural costs resulted in positive benefit-cost ratios across all hurricane damage
intensities, with very high yields for hurricanes of the magnitude of hurricane Andrew. Increased
expenditures on the order of 6% to 8% resulted in positive B-C ratios for hurricanes of the magnitude
of Andrew, but lower for the smaller hurricanes. Increased expenditures in the range of 10% of
current structural costs resulted in positive benefit-cost ratios for only the most intense hurricanes, and
expenditures greater than 12% of current costs resulted in B-C ratios less than 1.0. In other words,
there is a diminishing return on increasing the quality of urban structure as a means of minimizing
hurricane damage. Small incremental increases in costs that increase the quality of structure have
positive B-C ratios, while larger increases can only be justified for for the most sever hurricane
damage intensities.
There is an important assumption built into this analysis that should be considered. It was
assumed that expenditures for increased structural quality would result in a direct saving in damages
proportional to the expenditure. As can often happen, increased construction costs may not
necessarily mean better quality. The assumption, however that increased construction costs provide
increased protection against hurricane damage is valid if taken in the aggregate, that better quality
structure lessens hurricane damage.
4-15
20 40 60 80 100 120
HURRICANE INTENSITY
Figure 4.5. Graphs of EMERGY cost/benefit of increasing the quality of urban structure that
result from repeated simulations of the model in Figure 4.3. Each line represents a 2% increase in
construction costs.
4-16
140
5. South Dade County:
Emergy Analysis of Rebuilding Options After Hurricane Andrew
by
Mark T. Brown and Sergio Lopez
INTRODUCTION
Questions concerning sustainability, carrying capacity, and the welfare of developing
regions center on the role of natural resources, or what economists term "natural capital," in
economies. Economists are beginning to take a hard look at resource depletion and loss of
environmental quality and their effect on economic productivity and net capital formation,
suggesting that when taken into account, many otherwise growing economies may in fact be
declining, since declining levels of natural capital threaten long term economic sustainability.
Increasingly there is a call for factoring into economic production functions the contributions of
environmental systems and the negative consequences of resource depletion. Carrying capacity
and the welfare of growing populations in developing regions may be tied, ultimately, to natural
resources instead of capital formation. This section investigates the resource base of the economy
of south Dade and its relationship to sustainability and carrying capacity.
Sustainable Development
Figure 5.1 is a systems diagram of a region showing the interplay of natural and
agricultural systems and the human economy. The inflow of renewable resources power the
natural and agricultural systems and recycle and feedback pathways provide limited resources and
energies from the larger economy. Resources are "harvested" from natural and agricultural
systems, and either consumed locally, or exported. The proceeds from exported goods are used to
purchase imported fuels, goods, and services. Degraded lands and "waste-by-products" are often
slow to recycle to productive uses.
Sustainability can be defined from at least four different perspectives using the diagram in
Figure 5.1.; (1) sustainable development of natural systems; (2) sustainable yields from
agricultural systems; (3) sustainable use of resources at the regional scale; and (4) sustainable inter-
regional trade. The qualities given below the diagram describe each of these perspectives on
sustainable use of resources.
In a larger sense, since all systems are embedded within bigger systems, and, in some
measure influence lessor systems (i.e. a farm is driven by larger economic forces and in turn
Imports
L w
H. Exports
Sustainability Criteria:
Natural Systems
Agricultural Systems
Regional System
International Trade
A+B+C< R + G+J
-1
D+E< R + C+K
2
F+H+J+K < A+D+i
H
Figure 5.1. Systems diagram of a regional economy that is the interplay of renewable and non-
renewable energies. Shown are three scales for which sustainability should be determined:
ecological scale, regional scale, and intra-regional scale
1
influences what crops and management techniques are used at the field level) truly sustainable
development should satisfy stainability criteria at all levels simultaneously.
Conceptually, the diagram and equations may help to define sustainability. Yet to be truly
useful, the diagram should be evaluated to determine if the outflows exceed inflows at each of the
various compartments and for the regional systems as a whole. Evaluation in several different
units (kg of soil, tons of wood, hours of labor, liters of fuel, etc.) however will only serve to
increase confusion. Common units for all pathways are necessary. A new unit of evaluation
called "emergy" (which is somewhat analogous to embodied energy. .. in other words the energy
used to make something) may offer the potential of evaluating all resources in a regional economy
in the same units so that comparisons and judgements concerning sustainability can be made.
It is absolutely essential that a quantitative method be employed to judge sustainability so
that policy decisions are informed decisions. A systems perspective and the use of emergy
analysis techniques may provide the needed tools.
We have evaluated numerous systems of production, from primitive rice cultivation in
Thailand, to oil palm plantations in Brazil and have related them using several emergy indices to
criteria for sustainability. The basic criteria is simply that all systems of production (agricultural
field, farm, community, or region) should strive to at least balance that which is "harvested" with
the inflows of energy and resources that drive productive processes. If there is net negative
balance, in other words if more outflows than inflows, the enterprise is not sustainable, in the long
run, the greater the deficit, the shorter the time horizon before production ceases.
A Definition of Carrying Capacity
Carrying capacity for human populations is the population size that can be sustained at
some consumptive level for a given period of time. With a given amount of resources the
population level can vary depending on per capital resource consumption. Since resources are not
infinite in their availability (both temporally and spatially), increasing local carrying capacity
becomes an issue of increasing resource availability. In most economies this means increasing the
rates of resource extraction and imports of resources that are in short supply. The rub is that to
increase imports, often exports must be increased and therefore even greater rates of resource
extraction result. Thus the imports on the one hand may increase carrying capacity in the short
run, but the exports, ultimately, decrease carrying capacity in the long run. Clearly the balance
between short run increases in carrying capacity and long term decreases has been tipped in favor
of the short run as populations and "standards of living" have increased in most nations throughout
the developed and developing world. The following question begs to be answered...can these
I
1--
short run increases in carrying capacity be sustained in the long run in light of the fact that natural
capital is being depleted at ever increasing rates?
Determining Carrying Capacity
One theory for determining carrying capacity is that the scale or intensity of development
in relation to existing conditions may be critical in predicting its effect and ultimately its
sustainability (Odum et al. 1980; Odum and Arding 1991). If a development's intensity is much
greater than that which is characteristic of the surrounding landscape, on average, the development
has greater capacity to disrupt existing social, economic, and ecologic patterns (Brown 1980,
Odum 1980). If it is similar in intensity it is more easily integrated into existing patterns. For
example, because of the differences between a heavily urbanized area and an undeveloped
wilderness area, the appropriate intensity of development in each environment is much different
At the regional scale, the appropriate scale of urbanization is the level that is characteristic of the
economy within which the region is embedded.
Large-scale developments and those with greater intensity than the surroundings can be
integrated into the local economy and environment if there is sufficient regional area to balance its
effect. Much like the ecological concept of carrying capacity, where differing environments require
different aerial extent of photosynthetic production for support of a given biomass of animals,
environmental carrying capacity for human populations and their economies depends on the area of
"support" over which development can be integrated. As the intensity of development increases
(and therefore its consumption of resources and environmental impacts increase), the area of
natural undeveloped environment required for its support must increase. All other things being
equal, the more intensely an area is developed, the greater the area of environment necessary to
balance it. Thus, if planned in advance, the spacing between urban centers should increase as their
intensity increases. The methodology described in this section uses EMergy analysis to evaluate
intensity of urban development and the support base of the local environment and then uses a ratio
of purchased, nonrenewable EMergy to the resident renewable EMergy of the environmental
support base as a means of determining carrying capacity.
1Intensity may be measured using any quantity (energy, materials, money, or information) per unit time
per unit area. If one uses energy per unit time, or power, expressed over a unit area, the intensity is power density
(Brown 1980).
Carrying Capacity and Economic Competitiveness: EMERGY INVESTMENT
RATIO
Given in Figure 5.2 is a diagram illustrating the use of nonrenewable and renewable
EMergies in a regional economy. The interaction of indigenous EMergies (both renewable [I] and
nonrenewable [N] with purchased resources from outside [F]) is the primary process by which
humans interface with their environment.
The Investment Ratio (IR) is the ratio of purchased inputs (F) to all EMergies derived from
local sources (the sum of I and N) as follows:
IR = F/(I+N) (1)
The name is derived from the fact that it is a ratio of "invested" EMergy to resident
EMergy. The Investment Ratio is a dimensionless number; the bigger the Investment Ratio the
greater the intensity of development. Regional or state-wide IRs are useful for comparing the
intensity of individual developments or smaller regions embedded within the larger. The
U.S.Investment Ratio is about 8 to 1 and the State of Florida IR is 7.75 to 1, while Dade County's
is about 18 to 1. In this analysis we used both the ratio for Florida (calculated previously) and that
for Dade County
Determining Regional Carrying Capacity
Once the annual flux of renewable EMergy per year per unit area of landscape (renewable
EMergy density) is known and the nonrenewable EMERGY flux for a region is known, the
Investment Ratio can be calculated. Renewable EMergy density is derived from regional a
EMERGY analysis such as that for Dade County in Section 4.. Using the calculated Investment
Ratio for the larger region, the Investment Ratio for a subregion is set equal and then the equation
for IR is solved for the nonrenewable EMERGY flux as follows:
IR() = IR(r) (2)
where:
IR(r) =Investment Ratio of the larger region = known
IR(r) =Investment Ratio of the sub-region = [Fr] / [Ir+ Nr]
since Ir + Nr is known, the equation is solved as follows:
Fr =[IRlr)1[Ir+Nrl (3)
Purchased Inputs (F)
Investment Ratio of Regional Economy: IR=F/I+N
Figure 5.2 Systems diagram illustrating Investment Ratio
Once Fr is known, it is added to the quantity [Ir+Nr] yielding the total EMERGY flux for
the sub- region. Total population at a given per capital EMERGY use is then determined by
dividing total EMERGY flux by EMERGY per capital. EMERGY use per capital is the sum of the
emergy used directly or indirectly by the population. This index is a measure of the quality of life
in a region that accounts not only for the resources provided by the economy, but also for the ones
supplied by the environment. In this sense, it has the advantage of accounting for resources that
improve life quality, but are invisible when the measures of economic income are used. The
population that can be supported at the given EMERGY per capital is calculated as follows;
Population = (F+N)r + Ir / EMERGY per capital (4)
An awareness has recently developed that sustainability is a key factor to consider when
considering issues of regional development. Yet sustainability remains an elusive concept. It can
be argued that sustainable development, in the long run (100 years or more?), is that which can be
supported by the renewable flows of EMergy of a region. Development that depends on purchased
resources may not ultimately be sustainable since purchased EMergy is composed of nonrenewable
flows and subject to fluctuations in world prices. Yet, development that does not allow for the
possibility of using purchased resources to amplify a region's environmental basis cannot give an
economic return and becomes a moot point. Thus sustainability should reflect the current intensity
of development of an economy and match it. In this way, it is no more dependent on limited
supplies of nonrenewable EMergies than the economy as a whole. As the economy's use of
nonrenewable purchased energies may decline, new development under these circumstances does
not draw more of these energies on the average than the rest.
Determinations of sustainability should take into account the relative mix of: (1) an
economy's environmental basis (renewable EMergy sources), (2) its use of nonrenewable storage
from within, and (3) its purchased goods, resources, and services. These flows drive the
economy and ultimately influence what is sustainable by defining an upper boundary to the present
mix of purchased EMergy, resources from within, and renewable EMergy flows. The investment
ratio is a ratio of purchased EMergy to resident EMergy and when the ratios of development
proposals are compared to the ratio for the economy in which they are imbedded, may provide one
means of defining sustainable carrying capacity. Development proposals that have investment
ratios that are higher than the economy require more purchased EMergy per unit of resident
EMergy and therefore are more vulnerable, on the average, to changes in availability of purchased
EMergy. Developments with lower ratios than the local economy are less vulnerable, but also
yield less, on average.
Evaluations of South Dade's Carrying Capacity
In addition to using the Investment Ratio to determine a sustainable EMERGY intensity for
the region, carrying capacity using the sustainable water "crop" was also calculated. For each
method, several alternative scenarios were analyzed in order to produce a range of population
levels.
Water Crop Method
Water crop is a theoretical amount of water that can be harvested from ground water
sources without depleting reserves. Based on best estimates of local recharge, the water crop is
that amount of local rainfall that can be withdrawn from the drinking water aquifer without causing
draw down. We assumed an average annual rainfall in the region of 60 inches, with 75 %
evaporation. The receiving area was considered to comprise all of the study area, about 1.6E+9
square meters (395.4E+3 acres), yielding an average of 2.32E+9 cubic meters of water a year
(612.94E+9 gallons). With an evapotranspiration and a runoff of 75% and 24 % respectively, the
remaining 1 %, 2.32E+7 cubic meters, was assumed as available for human use. Water use per
capital was assumed as 346.8 cubic meters a year (251 gallons a day) (Morin, 1987), including
agriculture.
Two water use regimes were analyzed in order to determine their corresponding water crop
carrying capacity. Under the first, water available from infiltration of rainfall is used and disposed
without any recycling effort. Under the second, the rain water available is reused after treatment in
a wetlands system designed for the purpose, and then released to estuaries. This increases local
infiltration somewhat (0.4% of rainfall) resulting in a higher water crop.
Investment Ratio Scenarios
Investment ratios of Dade County and Florida were used in combination with the renewable
emergy density in the south Dade region and two different energy use per capital levels to calculate
several different population levels. When the IR for Florida (7.75 / 1) was used to calculate
carrying capacity of south Dade, a development intensity that is more rural in character was
obtained. This is the average of the State as a whole, and reflects the average statewide intensity of
land utilization. When the Dade County IR (18 / 1) was used to calculate carrying capacity, a
development intensity resulted that reflects the average for Dade County, more urban in character.
If the influences of Latin America continue to grow, and Miami continues to act as a hub
for business activity with Latin America, development in the south Dade region may continue to
grow. Population levels may eventually match the population densities that are characteristic of
the northern portions of the County. Local commerce will expand to match the population levels,
and international commerce may expand as well, leading to a relatively dense urban economy with
less reliance on production of agricultural products. The Dade county Investment Ratio was used
to calculate the population level that would be characteristic of this scenario.
On the other hand, if the Latin American "connection" is not as influential, and there is no
growth in the south Florida economy, the population level of the south Dade region may be more
sustainable if the region is developed to the intensity if Florida on the average. The economy
would be an agriculturally based economy with some local commerce and some tourism activity.
In fact, much like the present day economy. The State of Florida Investment Ratio was used to
calculate the population level that would be characteristic of this scenario
A third scenario was calculated as well. This is the lower population level sustainable at
current EMERGY per capital consumption, but relying only on the renewable resource base of the
region. This scenario represents a lower limit to population carrying capacity based on current
EMERGY consumption patterns.
Table 5.1 summarize the carrying capacity of south Dade based on the Water Crop and
Investment Ratio calculations. The sustainable water crop assuming no recycle of treated
wastewater locally yielded a population of about 67,000 people. When recycle of treated
wastewater is included the sustainable water crop method yielded a population of almost 94,000
people. Carrying capacity using the Investment Ratios of Florida and Dade County was 718,000
and 1.7 million people respectively. The renewable carrying capacity of the region was 82,000
people using Florida's per capital EMERGY consumption and 94,500 using Dade County's per
capital EMERGY consumption.
In all, the four population carrying capacities represent differing sustainable population
levels under the various scenarios. The lower bound, that which is sustainable on a renewable
basis, was calculated to be between about 70,000 and 95,000 people. At higher levels of
development intensity, and relying on a continued flux of purchased EMERGY from outside the
region, the carrying capacity of south Dade is between 700,000 and 1.7 million people. At these
higher levels, water crop calculations suggested that local rainfall/recharge will not be sufficient to
Table 5.1 Summary of Carrying Capacity for South Dade County
Method Carrying Capacity Total EMERGY Use Area of Dev. Land
(1000 people) (E21 sej/yr) (E3 hectares)
Water Crop
1% of Rainfall 67.0 1.8 19.0
1% rainfall + recycle 93.8 2.5 26.0
1% rainfall + Miami wastewater 342.5 9.2 76.4
Investment Ratio
At Florida's IR 718.0 19.6 85.4
At Dade Co.'s IR 1700.0 40.3 85.4
Renewable EMERGY only 82.0 2.2 18.9
Note: See Appendix B for Tables and Calculations
5-10
supply water needs of the population. Additional outside water sources will need to be transferred
from other areas of south Florida to meet the higher demand.
A Proposal for Increasing Carrying Capacity of South Dade
In this analysis a proposal is made to reuse wastewater more effectively and thus increase
the development potential of the hurricane impact area in south Dade County. If natural
productivity is enhanced and those areas that have been experiencing declines in productivity and
are stressed are restored the entire region benefits through better use of resources. Our concept of
carrying capacity is based on the ability of a natural system to support economic development, thus
if natural areas are restored and enhanced, there is greater support of economic development.
The rebuilding of south Dade County offers a unique opportunity to reestablish wetland
sloughs that once drained through the pine ridge connecting the Everglades with Biscayne Bay.
During the wet season, waters from inland used to flow through broad sloughs called "finger
'glades" southeastward to Biscayne Bay. The map in Figure 5.3 shows historical land cover (c.
1990) of the south Dade region with the pine ridge actually more resembling a series of islands
surrounded by wet prairie. Drainage projects begun in the early part of this century lowered
ground water tables and decreased wet season flooding. The map in Figure 5.4 shows present
land use and the canal network that is now in place.
The objective of this analysis was to develop a wetland slough system that would allow for
effective recycle of reclaimed wastewater and increased flow of Everglades water during the wet
season toward the east. The map in Figure 5.5 shows one wetland slough scheme. Reclaimed
wastewater from greater Miami would be discharged to the system in its upper northwestern
segment and in the wetland area in the vicinity of Homestead. Water flows southwest through the
western segment, then southeast to Biscayne Bay.
Tables 5.2 and 5.3 evaluate the emergy in yearly productivity and the emergy associated
with structure of the various land uses and land cover of the area that would be converted to
wetland slough. The total area is 38,967 hectares (96,287 acres) or about 150 square miles. The
single most affected land cover is the classification called Protected Area, which is primarily
eastern Everglades. Protected area and "Open Land", together, comprise about 62% of the area
affected. When combined with agricultural lands, the area of relatively "undeveloped land"
comprises about 90% of the total.
It is important to note that the land use and land cover was compiled from projected land
use map by Metro-Dade County Planning, and does not represent the as-built condition. It is our
thought that these numbers represent the maximum costs associated with a wetlands slough
valuation of Development-
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Dade
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Florida, Gainesville, FI 32611
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Table 5.2. Productivity loss of land uses within the proposed wetland system
Land Use Area Emergy Density Empower
(acres) (E12sej/ac./yr) (E 18sej/yr)
Open Land 14066 33.49 0.47
Protected Area 45285 45.21 2.05
Agriculture 27171 167.44 4.55
Institutional 676 837.20 0.57
Transportation 26 4186.00 0.11
Low/Med Residential 7476 2093.00 15.65
Med/High Residential 122 4353.44 0.53
Bus/Industrial 1465 13395.20 19.62
Total Land Use 96287 43.54
5-15
Table 5.3. EMERGY loss associated with structure on
proposed wetland system
land uses within the
Land Use Area Structure EMERGY
(acres) (E12sej/ac) (E 18 sej)
Open Land 14066 4.19 0.06
Protected Area 45285 33.49 1.52
Agriculture 27171 837.20 22.75
Institutional 676 8372.00 5.66
Transportation 26 16744.00 0.44
Low/Med Residential 7476 6279.00 46.94
Med/High Residential 122 10465.00 1.28
Bus/Industrial 1465 50232.00 73.59
Total Land Use 96287 152.23
proposal. The map indicates that about 7,476 acres of low/med residential, 122 acres of med/high
residential, and 1,465 acres of business/industrial lands are affected. In addition, about 676 acres
of institutional and 26 acres of transportation are affected by the slough system.
The costs associated with conversion of present land uses to wetland can be divided into
two areas. First there is the loss associated with loss of yearly productivity. Table 5.2
summarizes these losses. The highest losses are in Business and Low/Med. Residential categories
comprising about 81% of the total. The second loss is the structure associated with each land use
and land cover type. Table 5.3 summarizes these losses. The highest losses, again, are from
Business/Industrial and Low/Med. Residential, comprising about 33% of the total. Agricultural
structure, because of the magnitude of area affected is the third largest emergy loss, about 15% of
total losses. If some minor modifications were made to the alignment of the slough system, and
actual viable structure were taken into account, instead of assuming that all structure is in place,
these costs would be substantially reduced. It is quite apparent from the analysis of the hurricane
impacts that much of the structure in the south Dade impact area has been damaged and that a large
percentage (about 30%) has been damaged beyond usefulness. Thus losses associated with
conversion to a wetland slough given in Tables 5.2 and 5.3 are highest losses and when analyzed
in greater detail by determining the actual viability of structure within the slough system alignment,
we can expect them to decrease.
Table 5.4 summarizes an emergy benefit cost analysis for the proposed wetland slough
system. Total costs result from losses of yearly production and structure associated with land uses
and land cover types, that are within the "footprint" of the slough, the sloughs capital costs, and its
yearly operation and maintenance costs. The largest costs are associated with operation and
maintenance (90.7 E18 sej/yr) and capital costs (73.9 E18 sej/yr). Emergy benefits total 1575.9
El8 sej/yr, and the largest of which is the value of the reclaimed wastewater that is used more
effectively through the wetland system. The ratio of value received to costs if the wetland slough
system were constructed is about 7.3/1, if no additional development occurs.
Additional development could be supported as a result of the increases in productivity in the
landscape and good use of reclaimed wastewater. We have estimated that the "multiplier" effect, or
matching effect that natural systems have on the economy is about 8/1, thus if this potential
increased development is included in the analysis, the total benefits are about 8 times as high, or
12.606 E21 sej/yr. In this case, the benefit received for the losses incurred would be almost 60/1.
The effect on the calculated carrying capacity of south Dade should the wetland slough
system be constructed and treated wastewater recycled through it was significant. Assuming
5-17
Table 5.4. EMERGY costs and benefits of reclaimed wastewater wetland
system in south Dade
Flow or Storage (units) Amount Transformity EMERGY
(sej/unit) (E18 sej)
EMERGY Costs
Yearly Production 43.54
Structural losses 7.61
Capital Costs (E6 $/yr) 46.2 1.60E+12 73.92
0 & M (E6 $/yr) 56.7 1.60E+12 90.72
Total Costs 215.80
EMERGY Benefits
Created Wetlands 96878 66.98 6.49
Reclaimed Water (J/yr) 1.57E+15 1.00E+06 1569.41
Total Benefits 1575.90
5-18
345E+6 cubic meters a year (250 MGD), produced by the city is recycled through the system and a
volume of 8.62E+7 (25 %), is available for reuse through recharge of local aquifers the water crop
carrying capacity population would increase to 342,530 people.
A Proposal for Rebuilding South Dade
We carried the analysis of south Dade one step farther. Using theories of the hierarchical
organization of cities in landscapes first enunciated by Chrystaller in 1933 (Brown, 1980), and
found to follow a power law distribution by Zipf (1941) and others, we developed hypothetical
spatial designs of development for south Dade. Using the calculated population levels from the
analysis of carrying capacity to set development density and the wetland slough system as a
backdrop, we designed three urban landscapes that represented low, medium, and high
development intensity.
The hierarchy of urban centers described by Zipf (1941) and found by Brown (1980) in
two regions of Florida, was simulated for south Dade with the simple formula:
p=(P/n)/N (5)
where
p = is the population of each urban center
P = is the population of the region,
n = is the number of towns in each class of city, and
N = is the number of classes of cities used
For all the scenarios calculated the number of classes of cities was set at three, with one central,
two secondary and ten third level cities.
The area for each urban center was assigned based on the emergy required by the
population of that center. Land uses within each city were aggregated in eight categories defined by
their empower density. The categories used were: (1) Business and Industrial; (2) medium -high
density residential; (3) transportation (including streets and highways); (4) low- medium
residential; (5) institutional; (6) agriculture; (7) parks and protected areas; and (8) natural lands.
These land uses are arranged in a decreasing order from high empower levels representing the
central business district to low empower of the outskirts of the cities and the rural and natural
areas.
5-19
Sluatio0
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Dev
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Dade
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Prep
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Area
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environmental Engineering Sciences
d Presentation by Sergio A. Lopez
Florida, Gainesville, FI 32611
ty
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environmental Engineering Sciences
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:lorida, Gainesville, Fl 32611
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Florida, Gainesville, FI 32611
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The percentage of land for each category was adapted from land use distributions found by
Brown (1980) for two regions of Florida, and from Bartholomew (1965)for 53 central cities in the
United States. Smaller cities received a higher proportion of low emergy land categories, like
agriculture, as they are devoted to concentrate resources from the fields around. Large urban
centers concentrate the products from smaller towns, serving as central places, therefore a higher
proportion of high emergy land uses, like industrial, commerce and institutional, were concentrated
in them.
Figures 5.6 through 5.8 are GIS generated maps of the spatial distribution of cities based
on three development intensities. Cities are located along the existing ridge corridor and utilizing
the established highway infrastructure. The largest central place is located in the northern portion
of the study area closest to greater Miami, near the present day city of Kendal. Other cities are
located along the highway infrastructure and at central locations in the surrounding agricultural
regions.
In the first scenario (Figure 5.6), representing the population sustainable on renewable
EMERGY, the population was about 75,000. The area required for this population was calculated
at about 20,000 hectares. The number of city classes was fixed at three, with one central city
(25,000 people), two secondary cities (12,500 people each) and ten third class centers ( 1,250
people each). The medium development scenario (Figure 5.7) represents a sustainable population
based on renewable EMERGIES and recycled wastewater from greater Miami. The population in
this scenario was about 340,000 people distributed in the three classes of cities as follows: one
central city (112,000 people), 2 secondary cities (56,000 people), and 10 third class cities (5,600
people). The final development scenario (Figure 5.8) is based on Investment Ratio calculations
and developing the region to levels equal in intensity to the State as a whole. The total population
was 1.7 million people distributed in three classes of cities as follows: one central city (567,000
people), 2 secondary cities (283,000 people), and 10 third class cities (28,300 people).
5-20
Summary
Questions concerning the impacts of economic development, its costs and benefits and
ultimate sustainability, and the carrying capacity of regions for expanded development are relative
to the economy in which they are imbedded. The carrying capacity of south Dade County was
evaluated using EMergy flows and the EMERGY Investment Ratio and availability of long term
storage of water on a sustainable basis. The carrying capacity of the region, using the Investment
Ratio was based on setting aside sufficient undeveloped "support area" so that the contributions of
environmental resources to the developed economy equaled that which was characteristic of the
State economy. Population levels calculated in this manner were between 700,000 and 1.7 million
people. In addition, several carrying capacity levels were calculated based on sustainable use of
water resources, or "water crop". These suggested that between 70,000 and 90,000 people could
be supported without "mining" water resources of the region, and that if treated wastewater were
imported from greater Miami, and recycled through constructed wetland sloughs, the sustainable
water crop would increase population levels to about 340,000 people.
A range of population levels have been generated using the Investment Ratio and water
crop methods. The range has an almost 30 fold difference between the lowest and highest values.
Our intention was to suggest that carrying capacity is a dynamic concept, depending on resource
availability. With little or no resources available from outside sources, the carrying capacity in
south Dade is probably more on the order of 70,000 people. With moderate availability of outside
resources, the carrying capacity is probably on the order of 350,000 people. And under full
development to intensities characteristic of Dade county, the population level would be over 1.7
million people. Which scenario is appropriate for south Dade, depends on global and national
economies, and the degree to which the area is integrated into them.
The use of EMergy flows as a means of evaluating the carrying capacity of regional
economies may lend insight into the complex questions surrounding the increased integration of
regional economies with outside economies and whether over development is beneficial and
sustainable in the long run. The proposed methods of quantitative evaluation are tendered more as
a means of helping guide public policy decisions than as the means to once and for all predict
ultimate carrying capacity. The intensity to which a region develops, and thus the number of
people that are sustainable within it are serious questions that communities should be wrestling
with. The age of unlimited resource availability is behind us, requiring more accurate awareness of
what over development may mean in the long run.
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Ref-4
Final Report
EMERGY EVALUATION OF ENERGY POLICIES FOR FLORIDA
APPENDICES
Report to the Florida Energy Office
By
M.T. Brown, H.T. Odum, G. McGrane, R.D. Woithe, S. Lopez, and S. Bastianoni
Center for Environmental Policy
Department of Environmental Engineering Sciences
University of Florida
Gainesville, Florida
(904) 392-0847
January 31, 1995
APPENDIX A
Emergy Evaluation of Ethanol and Methane
by
S. Bastianoni and M.T. Brown
Emergy Evaluation of Ethanol and Methane
by
S. Bastianoni and M.T. Brown
Ethanol
Figure A-i is a summary diagram of ethanol production from sugar cane in south Florida.
Cane is harvested, transported and fermented to produce ethanol. Renewable inputs include
sunlight, wind, and rain. Surface water is pumped into and out of the agricultural fields depending
on rainfall patterns and crop needs. An important source for cane production is the storage of soils
that are being depleted. Purchased inputs include fuels, goods, and services.
Table A-I is an emergy evaluation of the ethanol production system. Data for sugar cane
production are from Fluck (1992) while data for ethanol production are from Giampietro and
Piemental (1990). Renewable energy inputs totaled 12.54 E15 sej/ha*yrl, the largest of which
was topsoil loss (9.97 E15 sej/ha*yr-t). Topsoil loss was about 6 times greater than the emergy
inputs of rain and surface water combined.
Purchased inputs to sugar cane production totaled 5.33 E15 sej/ha*yr-l Largest purchased
inputs were labor (1.56 E15 sej/ha*yr-1) and services "embodied" in purchased goods (5.33 E15
sej/ha*yr-l). Total emergy inputs to sugar cane production were 17.87 E 15 of which top soil loss
represents almost 57% of the total.
The inputs to ethanol production include sugar cane and water and the steel and cement
used in construction of fermentation equipment In addition an important input is services
"embodied" in purchased goods. Water and services were the largest of the inputs to ethanol
production totaling 0.99 E15 sej/ha*yr-I and 0.82 E15 sej/ha*yr-t respectively.
Total inputs to ethanol production were 19.84 E15, and the energy content of ethanol
produced was 1.89 El 1 Joules. When expressed as a net emergy yield ratio (the emergy yield
divided by nonrenewable energy consumed in its production), ethanol is relatively low (3.15/1).
Primary energy sources that support the economy have higher ratios and therefore ethanol will not
be competitive until these other sources decline in availability. Such declines will lower their yield
ratios making ethanol more competitive.
Methane
Figure A-2 is a summary diagram of methane production from dairy cow manure. The
methane production is part of an "energy integrated dairy farm system in Puerto Rico" (Sasscer and
Morgan (1986) and is a by-product of the system. Electricity is generated from combustion of the
methane, some of which is used by the farm and some of which is sold during times when on farm
demand is low. Renewable inputs to the farm system include sunlight, wind and rain. In addition,
groundwater is pumped for irrigation. Purchased inputs include fuels, goods and services.
Outputs from the farm system include milk, electricity, and soil loss and pollutants.
Table A-2 is an emergy evaluation of the dairy farm system and its methane production.
Non-purchased emergy inputs totaled 508 E15 sej/yr. Rainfall was the largest of the renewable
inputs totaling 370.97 sej/yr or about 73% of the total, while agricultural water (126.24 sej/yr) was
the largest of the nonrenewable free inputs.
Purchased inputs totaled 388.66 sej/yr, the largest of which were services (117.76 sej/yr),
fuel (102.93 sej/yr) and purchased electricity (115.14 sej/yr). Combined these three inputs
represent about 86% of the purchased inputs.
The net emergy yield ratio for the methane generated by the system is about 2.4/1. While
the operation has a positive net emergy yield ration, it does not compete with richer sources that
have higher yields.
Ethanol from Sugar Cane.
Figure B-1. EMERGY systems diagram of ethanol production from sugarcane.
Table A.1. Emergy analysis of ethanol production from sugarcane for South
Florida (data from UF data base [sugarcane production] and Giampietro
and Piementel, 1990 [ethanol production])
Note Item Unit Units/ha/yr. Transformity Solar Emergy
(sej/unit) (E14 sej/ha/yr)
RENEWABLE FREE RESOURCES
1 Sunlight J 5.40E+13 1.00E+00 0.54
2 Wind J 9.89E+11 1.50E+03 14.80
3 Rain J 2.76E+10 1.54E+04 4.26
NONRENEWABLE FREE RESOURCES
4 Surface water J 2.26E+10 4.85E+04 10.95
5 Loss of Topsoil J 1.59E+11 6.25E+04 99.68
Sum of independent free inputs 125.42
PURCHASED INPUTS FOR SUGARCANE PRODUCTION
6 Phosphate g 4.77E+04 6.88E+09 3.28
7 Potash g 1.91E+05 2.96E+09 5.64
8 Insecticides J 3.06E+06 1.97E+07 0.60
9 Pesticides J 5.98E+06 1.97E+07 1.18
10 Other Chemicals g 2.03E+04 3.00E+09 0.61
11 Diesel J 4.07E+09 6.60E+04 2.69
12 Lubricants J 1.75E+08 6.60E+04 0.12
13 Human Labor hr 3.31E+01 4.70E+13 15.56
14 Services $ 1.57E+03 1.50E+12 23.62
Sum of purchased inputs for sugarcane production 53.29
Sum of inputs for sugarcane production 178.72
INPUTS FOR THE ETHANOL PRODUCTION
15 Sugarcane g 8.80E+07 2.03E+09 178.72
16 Water J 3.88E+09 2.55E+05 9.91
17 Steel g 4.40E+04 2.64E+09 1.16
18 Cement g 5.03E+04 7.48E+08 0.38
19 Services $ 5.47E+02 1.50E+12 8.20
Sum of free inputs for ethanol production 135.33
Sum of purchased inputs for ethanol production 63.03
PRODUCT
20 Ethanol J 1.89E+11 1.05E+05 198.36
Notes to Table A.1
1 Sunlight 1.29 E6 Kcal/m^2/day Ref: Odum et al. (1992)
(1.29 E6 Kcal/m^2/yr)(1 E4 m^2/ha)(4186 J/Kcal)=
5.40E+13 J/ha/yr
2 Wind eddy diffusion 1.7 m3/m2/s; vertical gradient 1.5 E-3 m/s/m Ref: Odum (1992)
(1000 m)(1.23 kg/m3)(1.7 m3/m2/s)(3.154 E7 s/yr)(1.5 E-3 m/s/m)(1 E4 m^2/ha)=
9.89E+11 J/ha/yr
3 Rain 22 in/yr
(22 in/yr)(.0254 m/in)(l E4 mA2/ha)(1000kg/m^3)(4.94 E3 J/kg)=
2.76E+10 J/ha/yr
4 Surface water 18 in/yr Ref: Brown et al. (1991)
(18in/yr)(.0254 m/in)( E4 mA2/ha) (4.94J/g)(1000000g/t)
2.26E+10 J/ha/yr
5 Loss of Topsoil 1 in/yr Ref: Stephens (1984)
(.0254 m/yr)(l E4 mA2/ha)(10% organic matter)(.3 E6 g/m3)(5 kcal/g)(4186 J/kcal)
1.59E+11
6 Phosphate (P205) 42.5 lb/acre/yr Ref: Brown et al. (1991)
(42.5 lb/acre/yr)(2.47 acre/ha)(454 g/lb)
4.77E+04 g/ha/yr
7 Potash (K20) 170 lb/acre/yr Ref: Brown et al. (1991)
(170 lb/acre/yr)(2.47 acre/ha)(454 g/lb)
1.91E+05 g/ha/yr
8 Insecticides .65 Ib/acre/yr Ref: Odum et al. (1992)
(.65 lb/acre/yr)(2.47 acre/ha)(454 g/lb)(4.2 E3 J/g)
3.06E+06 J/ha/yr
9 Pesticides 1.27 lb/acre/yr Ref: Odum et al. (1992)
(1.27 lb/acre/yr)(2.47 acre/ha)(454 g/lb)(4.2 E3 J/g)
5.98E+06 J/ha/yr
10 Other chemicals 18.1 lb/acre/yr
(18.1 lb/acre/yr)(2.47 acre/ha)(454 g/lb)
2.03E+04 J/ha/yr
11 Diesel 15.56 gal/acre/yr Ref: Brown et al. (1991)
(15.56 galacre/yr)(2.47 acre/ha)(3.8 1/gal)(2.79 E7 J/1) =
4.07E+09 J/ha/yr
12 Lubricants 0.67 gal/acre/yr Ref: Brown et al. (1991)
(0.67 gal/acre/yr)(2.47 acre/ha)(3.8 l/gal)(2.79 E7 J/) =
1.75E+08 J/ha/yr.
13 Human Labor 13.4 man-hr/yr/acre Ref: Odum (1988)
(13.4 man-hr/yr/acre)(2.47 acre/ha)
3.31E+01 man-hr/ha/yr
14 Services 637.5 $/acre/yr Ref: Odum et al. (1992)
(637.5$/acre/yr)(2.47 acre/ha)
1.57E+03 $/ha/yr
15 Sugarcane 88000 kg/ha
(88000 kg/ha)(1000 g/kg)=
8.80E+07 g/ha/yr
16 Water 125 E3 1/1000 1 ethanol Ref: Brown et al. (1991)
(6285.7 1/ha)(125 E3 1 water/1000 1 ethanol)=785.7 E3 1/acre/yr
A-4
(785.7 E3 1/acre/yr)(4.94 E3 J/l) =
3.88E+09 J/ha/yr
17 Steel 7 kg/1000 1 of ethanol
(6285.7 l/ha)(7 kg steel/1000 1 ethanol)=44 kg/acre
(44 kg/acre)(1000 g/kg)=
4.40E+04 g/ha/yr
18 Cement 8 kg/1000 1 ethanol
(6285.7 l/ha)(8 kg cement/1000 1 ethanol)=50.3 kg/acre
(50.3 kg/acre)(1000 g/kg)=
5.03E+04 g/ha/yr
19 Services 546.5 $/ha/yr
5.47E+02 J/ha/yr
20 Ethanol 6285.7 I/acre
(6285.7 l/ha)(3 E7 J/l)=
1.89E+11 J/ha/yr
Ref: Brown et al. (1991)
Ref: Brown et al. (1991)
Ref: Brown et al. (1991)
Indexes
Net Emergy Ratio for Sugarcane Production 3.35
Net Emergy Ratio for Ethanol production 3.15
Free/Purchased Ratio 2.15
References
1) Brown M.T. and Arding J., 1991. Transformity Working Paper. Center for Wetlands, University of
Florida, Gainesville, USA.
2) Gianpietro M. and Piementel D., 1990. Alcohol and Biogas Production from Biomass. Critical Reviews
in the Plant Sciences, 9:213-233.
3) Odum H.T., 1988. Self Organization, Transformity, and Information. Science 242: 1132-1139
4) Odum H.T., 1992. Emergy and Public Policy. Environmental Engineering Sciences, University of
Florida, Gainesville, USA.
5) Odum H.T. and Odum E.C.,1987. Ecology and Economy: Emergy Analysis and Public Policy in Texas.
L.B. Johnson School of Public Affairs, Policy Research Project Report 78.
6) Odum H.T., Odum E.C. and Brown M.T.,1992. Environment and Society in Florida. Environmental
Engineering Sciences, University of Florida, Gainesville, USA.
7) Stephens, J.C., 1984. Subsidence of Organic Soil in the Florida Everglades, a Review and Update, in
P.J. Gleason ed., Environments of South Florida: Past and Present II, Miami Geological Society, Coral
Gables, Florida.
roaure X\ / \ I( 00
Crops
Manur
Mixing CH Electric
& /- Oeneratlon
Digestion
Electricity
Soil Loss.
Pollutants
Methane from Dairy Cow Manure
Figure B-2. Methane production from dairy cow manure in Puerto Rico.
Table A.2. Emergy Analysis of Methane Production in Puerto Rico
Note Item Unit Units/Yr. Transformity Solar Emergy 1986 Macroeconomic
(sej/unit) (E15 sej/yr) Value (E4 $)
RENEWABLE RESOURCES
1 Sunlight J
2 Wind J
3 Rain J
2.98E+16
1.89E+ 12
2.40E+13
1.00E+00
1.50E+03
1.54E+04
NONRENEWABLE RESOURCES
4 Ground water J 4.47E+ 10 2.55E+05
5 Agricult. water J 2.61E+12 4.85E+04
Sum of free inputs (sun,wind,waves omitted)
PURCHASED INPUTS
6 Seeds
7 Fertilizer (N)
8 Forage
9 Concrete
10 Machinery
11 Services
12 Fuel
13 Electricity
14 Human Labor
J 1.15E+10
g 6.48E+06
J 4.10E+ 10
g 2.85E+07
g 1.00E+06
$ 3.93E+04
J 1.56E+12
J 5.76E+11
J 8.72E+09
8.60E+04
3.45E+09
6.60E+04
9.26E+07
6.70E+09
3.00E+12
6.60E+04
2.00E+05
2.00E+06
Sum of purchased inputs
Sum of total inputs
PRODUCTS
15 Milk
16 Manure
17 Methane
18 Electricity
1 2.98E+06
g 7.95E+09
J 3.62E+12
J 7.56E+11
3.02E+11
1.13E+08
2.48E+05
1.19E+06
29.84
2.83
370.97
11.41
126.24
508.63
0.99
22.36
2.70
2.64
6.70
117.76
102.93
115.14
17.44
388.66
897.28
897.28
897.28
897.28
897.28
0.99
0.09
12.37
0.38
4.21
16.95
0.03
0.75
0.09
0.09
0.22
3.93
3.43
3.84
0.58
12.96
29.91
29.91
29.91
29.91
29.91
Data from: D.S. Sasscer and T.O. Morgan "Energy Integrated Dairy Farm System in Puerto Rico"
Center for Energy and Environmental Research, University of Porto Rico, 1986.
Notes to Table A.2
1 Sunlight 3.83 E3 Kcal/m^2/day
(3.83 E3 KcaV/m2/day)(365)(1800 acres)
(4047 mA2/acre)(70% albedo )(4186 J/Kcal) =
2.98E+16 J/yr
2 Wind 712 J/m^2/day
(712 J/m^2/day)(365 days/yr)(1800acres)(4047 m^2/acre)=
1.89E+12 J/yr
3 Rain 0.89 m/yr
(0.89 m/yr)(1-.25 runoff)(1800 acre)(4047 m^2/acre)(1000kg/m^3)(4.94 E3 J/kg)
2.40E+13 J/yr.
4 Ground water (22800 I/day for dilution) + (2000 I/day for the cows)
(24800 l/day)(365 days/yr) (4.94 J/g)(1000g/kg)+
4.47E+10 J/yr
5 Agricultural Water 54 in/yr
(54 in/yr)(.0254 m/in)(95 acre)(4047 m^2/acre)(IE6 g/mA3)(4.94 J/g) =
2.61E+12 J/yr
6 Seeds 2.25 g/m^2/yr
(2.25 g/m^2)(90 acres)(4047mA2/acre)(3.345 kcal/g)(4186 J/kcal)=
1.15E+10 J
7 Fertilizer N (purchased) 6.48 E6 g/yr
6.48E+06 g/yr
8 Forage (purchased) 13.5 E5 Kg/yr
(13.5 E5 Kg/yr) (7.25 kcal/kg)(4186 J/kcal)=
4.10E+10 J/yr
9 Concrete 850 m^3 for Loafing Barns + 100 m^3 for the methane production system
(950 m^3)(1.5 E3 kg/m^3)(1000 g/kg) =
2.85E+07 g/yr
10 Machinery 10 E3 kg. (10 years of use)
Assumption: 60% for crops and milk production, 30%
for methane prod. and 10% for electricity prod.
1.00E+06 g/yr
11 Services = {1.45 E5 (for Agriculture) + 5.5 E4 (for Electrical Power) + 2.79 E5
(for Manure Management)}/20years + 4400+6400+4482 (Maintainance)
{(145,000+55,000+279,400)$/20 yr} + (4400+6400+4482 $/yr) =
3.93E+04 $/yr
12 Fuel 55900 1/yr of gasoline
(55.9 E3 1)(2.79 E7 J/1) =
1.56E+12 J/yr
13 Electricity 140,000 for milk production + 19915 for methane production
(159915 kWh)(3.6 E+6 J/kWh) =
5.76E+11 J/yr.
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