v>EPA
United States
Environmental
Protection Agency
EPA/600/R-23/202 | March 2024 | www.epa.gov/research
The Unit Emergy Value (UEV) Library
for Characterizing Environmental
Support in Life Cycle Assessment
Office of Research and Development
Center for Environmental Solutions & Emergency Response
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The Unit Emergy Value (UEV) Library
for Characterizing Environmental
Support in Life Cycle Assessment
Christopher De Vilbiss1, Sam Arden2, Mark T. Brown1, Daniel E. Campbell3,
Xin (Cissy) Ma4' *, and Wesley Ingwersen4
1 Center for Environmental Policy
School of Sustainable Infrastructure and Environment
College of Engineering
University of Florida
Gainesville, FL 32611
2 Eastern Research Group, Inc.
Lexington, MA 02421
3 (Retired) Office of Research and Development
U.S. Environmental Protection Agency
Narragansett, RI 02882
4 Center for Environmental Solutions and Emergency Response
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati, OH 45268
March 22, 2024
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ABSTRACT
In the field of environmental sustainability assessment, there are different integrated metrics used
to quantify the total natural resource use, raw materials (i.e., minerals, water, fuels) and
environmental impacts. In a resource-constrained world, it is essential to quantify the
environmental support that these resources provide to economic activities, that includes the work
provided by Nature such as chemical potential in rain water or in fossil fuel formation. The
integrated measures involving the comparisons of different units or scales require a "common
currency." Life cycle assessment (LCA) has been extensively used to assess the potential
environmental impacts of goods and services over their full life cycles. Traditional
environmental impacts in LCA have been focused on impacts of emissions with limited
information regarding the impacts of resource uses such as fossil fuel, minerals, land, water, and
soil. It is critical to not only quantify the impact of uses of these resources in LCA but also
capture the environmental inputs to these resources in any industrial processes or economic
activities. Therefore, the resource true values and resource scarcity can be captured, and
sustainability can be evaluated. An environmental accounting method that provides a means of
estimating resource value based on the geobiophysical work required to make and sustain those
resources is the Emergy Accounting approach. Emergy is defined as the available energy
(exergy) of one kind used up to make and sustain a resource directly and indirectly. Emergy
values can be provided to estimate the value of renewable and nonrenewable resources in a
common energy unit (solar emjoule, sej). The unit emergy value (UEV) library was developed
for quantification of the environmental support associated with elementary resource use in
emergy accounting and LCA studies. The library provides emergy characterization factors
(EmCFs) for different types of renewable energy sources, minerals and metals, land occupation,
water flows and storages, biomass, soils, fossil fuels and etc. Only elementary resources are
included, while refined commodities and manufactured goods are not and their EmCFs can be
calculated based on the elementary ones and a sufficient knowledge of each production process.
The EmCFs rest on a common set of estimates and assumptions regarding geobiosphere
processes and were calculated in a dynamic model from the ground up according to consistent
algebra, rules, and assumptions. The calculation procedure is constructed in such a way that
changes to an underlying estimate or assumption (such as the value of the global emergy
baseline) will propagate through the library to update all the factors and avoid introducing human
errors. The UEV library will provide a consensus set of emergy values for emergy accounting,
LCA and various other sustainability analyses. This library uses the consensus global emergy
baseline 1.2 E25 seJ/y. The intended audience for UEV library includes emergy practitioners,
LCA practitioners, sustainability practitioners, academics, policy makers, public, consulting
firms, etc.
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Notice
The views expressed in this report are those of the author(s) and do not necessarily represent the
views or policies of the U.S. Environmental Protection Agency (EPA). Although the research in
this document has been partially funded by the United States Environmental Protection Agency
under Contract EP-1 l-C-000197 to University of Florida (Draft Report) and EPA Contract No.
EP-C-15-010 to Pegasus Technical Services, Inc. (Draft Report), any mention of trade names,
manufacturers or products does not imply an endorsement by the United States Government or
the U.S. Environmental Protection Agency.
Technical Advisory Committee
Xin (Cissy) Ma, Ph.D. (chair), US EPA ORD CESER *
Wesley Ingwersen, Ph.D., US EPA ORD CESER
Daniel E. Campbell (retired), Ph.D., US EPA ORD NHEERL
* corresponding contact
Technical Reviewers:
Heriberto Cabezas, Ph.D., Senior Science Advisor, US EPA ORD (retired); University of
Miskolc, Miskolc, Hungary
Jeff Yang, Ph.D., Senior Scientist, US EPA ORD
Smiti Nepal, P.E., Environmental Engineer, UE EPA OWM
Elliot Campbell, Ph.D. Ecological Economist at Maryland Department of Natural Resources
Sergio Ulgiati, Environmental Chemist, Department of Science and Technology, Parthenope
University of Naples, Naples, Italy.
Natalia Andrea Cano Londono, Research Fellow, Department of Green Chemistry and
Technology, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
Contracting Officer Representative
Xin (Cissy) Ma, Ph.D., US EPA ORD CESER
George Moore (retired), Ph.D., US EPA ORD NRMRL
Diana Bless (retired), US EPA ORD CESER
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Table of Contents
Abstract ii
Notice iii
Definitions vii
1.0 Introduction 1
2.0 The EmCF library 3
2.1 Emergy Algebra 5
3.0 Renewable Primary Earth Emergy Inputs 7
4.0 Renewable Secondary Earth Emergy Flows 10
4.1 Wind 10
4.2 Precipitation 12
5.0 Renewable Tertiary Earth Emergy Flows 16
5.1 Ocean Currents 16
5.2 Waves 16
5.3 Continental runoff geopotential transformity 17
5.4 Continental runoff chemical exergy 17
6.0 Water EmCFs 18
6.1 Scaling Water EmCFs by Purity and Turnover Time 19
7.0 Crustal mineral EmCFs 20
7.1 Singular Minerals 20
7.2 Mixed Minerals 24
7.3 Multiple Minerals 25
7.4 Aggregate rock EmCFs 25
7.5 Minerals in seawater 25
8.0 Atmospheric gases 26
9.0 Land, Biomass and Soil EmCFs 27
9.1 Land Occupation 27
9.2 Land Transformation/Volume Occupied 29
9.3 NPP and Biomass 29
9.4 Soil organic carbon 30
9.5 Soil minerals 30
9.5.1 Inorganic matter 30
9.5.2 Soil Nitrogen 30
9.5.3 Sulfur 31
10.0 Wood 31
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11.0 Fossil fuels 32
11.1 Peat 33
11.2 Coal 33
11.3 Oil and natural gas 35
11.4 Helium 36
12.0 Discussion/Future Research 37
12.1 Global emergy baseline 37
12.2 Renewable vs. Non-renewable 37
12.3 Biological EmCFs 38
12.4 Land occupation EmCFs 38
12.5 Minerals 38
12.6 Atmospheric gases 39
12.7 Accounting procedures for land occupation, standing biomass, and lumber
harvest 39
12.8 Accounting procedures for water 40
12.8.1 Water's thermal capacity. 40
12.8.2 Water's chemical potential 41
12.8.3 Water'sgeo-potential 42
13.0 Conclusions 42
14.0 Quality Assurance 43
15.0 References 43
Table of Figures
Figure 1 The major elementary flows in Earth geobiosphere described in this ECF library are
organized in primary, secondary and tertiary flows 7
Figure 2 The Earth system, or geobiosphere, is composed of 4 main subsystems, the Atmosphere,
Hydrosphere, Lithosphere and the Anthroposphere. The geobiosphere is driven by three
main energy sources, solar energy, the gravitation pull of the sun and moon that creates
tidal energy, and the geothermal energy which is largely responsible for geologic
processes. In recent times, the fossil fuel energies released by humans have added
considerably to the total energy budget of the Earth 9
Figure 3 Global hydrologic cycle (a) flows in km3 y"1 from Bengtsson (2010) and (b) in Gibbs
energy 15
Figure 4 The global water cycle showing the hierarchical circulation of water driven by the
tripartite and the main storages of water. ET = evapotr(inspiration, Evap = evaporation,
Prec. = precipitation, and Gd water = ground water 19
Figure 5 Gibbs energy of freshwater with varying TDS concentration at T = 287.25 K 20
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Figure 6 Diagram of the geobiosphere showing the crustal cycle of sediments interconnected
with a much longer cycle of the upper mantle. The productive processes of the
atmosphere, biosphere, and hydrosphere contribute to the cycling of sediments, minerals
Figure 7 Generic ecosystem/biome showing the inputs of emergy driving gross primary
production (GPP) and net primary production (NPP) as the difference between GPP and
respiration (R). The storages of wood, biomass and soil carbon are all products of
primary production. Note that we compute separate EmCFs for biomass, wood and soil
Figure 8 The two phases of coal formation. Phase I: peat production is dominated by ecological
processes that are driven by solar, tidal, and geothermal energies of the geobiosphere.
Phase II: coalification is driven by geothermal energy. PF1-2 are preservation factors
(fraction of carbon that is preserved and passed to the next step): PFi is the preservation
between organic matter production and peat accumulation. Hard coal and soft coal have
two different preservation factors PF2aand PF2b between peat and coal 34
Figure 9 The two phases of petroleum formation. Phase I: organic matter production is
dominated by ecological processes driven by solar, tidal and geothermal energies of the
geobiosphere. Phase II: petroleum production is driven by geothermal energy. PF1-3 are
preservation factors (fraction of carbon that is preserved and passed to the next step):
PFiis the preservation between organic matter production and organic matter
accumulation in basins, PF2is the preservation between accumulated organic matter and
kerogen, and PF3 is the preservation between kerogen and oil/natural gas. (Ki = kerogen
type I; Kn = kerogen type II, Km = kerogen type III) 36
and the fossil fuels.
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carbon because they are on very different time scales
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Table of Tables
Table 1: List of supporting worksheets in the EmCFdb
Table 2: Solar Equivalent Joules for Earth's tripartite (Brown et al., 2016) ..
Table 3. Summary of modeled global wind dissipation rates
Table 4. Emergy heat maps for global biomes using different transformities
Table A-l Summary of EmCFs for LCA Elementary Flows
..4
.. 9
12
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Definitions
Areal empower intensity (AEI): emergy per unit area per year
Biomass: the total mass of living matter within a given habitat (usually expressed in terms of
dry weight per unit area).
Biome: a community of plants and animals that occupy a contiguous area with similar climatic
conditions
Characterization factor: a quantity derived from a life cycle impact assessment method that
represents a unit of a quantity of impact per unit of a resource of consumed or an emission
produced. Depending on the methodology these factors may be equivalent to a resource or
emission based on its impact potential (e.g., C02-eq) or an actual measure of impact on an
endpoint (e.g., disability-adjusted life year).
Co-product: the allocation of total inputs to the system to each output
Coupling: feedback in hierarchically organized open thermodynamic systems
Ecosystem: A spatially explicit unit of the Earth that includes all the organisms, along with
all components of the abiotic environment within its boundaries (Likens, 1992)
Elementary flow: material or energy entering the system being studied that has been drawn
from the environment without previous human transformation, or material or energy leaving
the system being studied that is released into the environment without subsequent human
transformation (ISO 14044:2006)
EmCF: Emergy characterization factor; the emergy per unit exergy or mass of something
EmCFdb: Emergy Characterization Factor database; see accompanying excel workbook
Emergy: the sum of all direct and indirect available energy (exergy), expressed in the same
form of energy required to produce a system or resource; units are solar emjoule (sej)
Empower: emergy per unit time, the emergy unit of power, emjoules per second, is an
emwatt, or emW
Exergy: the portion of the total energy of a system that is available for conversion to useful
work
Ga: Giga-annum; 1E+09 years
GEB: Geobiosphere (or Global) Emergy Baseline
gej: gravitational emjoules. The unit of gravitational emergy. Gravitational emergy defined
as the amount of gravitational exergy required directly or indirectly in the fusion reactions to
resulted in sunlight and the radionuclides.
LCA: Life Cycle Assessment - a framework for assessing the environmental impacts of goods
and services over their life cycle (ISO 14044:2006)
NPP: net primary production, typically refers to photosynthetic plants and algae
OLCA: OpenLCA. Software for sustainability assessment designed by GreenDelta
ppt: parts per thousand.
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ppm: parts per million.
sej: solar emjoules. The unit of solar emergy. Emjoules are not available energy, but instead a
measure of the exergy used in the past to create a storage or flow of exergy in the present.
Emjoules are not joules in the thermodynamic sense of the unit and the "j" should not be
capitalized.
seJ: solar equivalent Joule. This is the unit of solar equivalent exergy or solar equivalent
joules between sunlight and other sources (gravitational energy and Earth geothermal heat)
that comprise global emergy baseline.
SER: solar equivalent ratios. Solar equivalent exergy per unit of exergy (seJ/J). It is neither
transformity nor UEV, rather solar equivalent exergy /joule. It is used to establish the
equivalence between sunlight and other sources of energy.
Specific emergy: the ratio of emergy to mass (sej/g).
Split: as opposed to a co-product a split allocates emergy in proportion to divergent exergy
flows and results in identical transformities of the diverted flows.
TDS: Total dissolved solids in water
Transformity: the ratio of emergy to available energy (sej/J)
Turnover Time: the quantity of a stock (storage) of material or energy present in a particular
system divided by the flux rate into or out of the stock.
Unit Emergy Value (UEV): the ratio of the emergy required to make something to its
available energy or mass. It is equivalent to EmCF for elementary flows.
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1.0 Introduction
Life cycle assessment (LCA) is an internationally-standardized framework for assessing the
potential environmental impacts of goods and services over their full life cycles (U.S. EPA,
2006). A number of environmental impacts have traditionally been characterized in life cycle
assessment, including impacts of emissions from processes to air and water quality, climate, and
human health. The EPA's TRACI 2.1 impact assessment methodology provides characterization
factors for a dozen impact categories (Bare, 2012). Most of these impact categories are related to
impacts from process emissions; only one impact category characterizes impacts to resources
(fossil fuel use). Other impact methodologies, such as ReCiPe, provide methods for impacts to
other specific categories of resources, including waters, metals, and fossil fuels. All resources
from the environment that are used in human-driven processes (the technosphere) can be
considered means of environmental support to enable the sustainability of our economy and
society in a "resource-constrained world" (NRC, 2012). A means of measuring this type of
environmental support underlying the life cycle of a product or process would provide additional
and valuable information to complement traditional LCA results to support sustainable decision
making about the manufacture and use of goods and services.
Measuring the total environmental support from different types of resources in a single metric
presents a challenge, because resources such as land, water, fossils fuels, nutrients, soils, etc. are
not traditionally measured in a single unit. One alternative is to use an integrated sustainability
metric for resource use/environmental support. Integrated metrics draw upon existing scientific
principles and methods to integrate multiple impacts into a single measure based on a system
approach (Ingwersen et al., 2014). An integrated metric proposed and previously used by EPA as
a measure of environmental support is based on the principles and methods of environmental
accounting using emergy, a concept closely related to energy and exergy as well as to
ecosystems dynamics. Emergy is defined as the available energy of any kind previously used
both directly and indirectly to make another form of energy, product, or service (Odum, 1996).
In the emergy method, all direct and indirect sources of material and energy input to a product
system are tracked and quantified in units of a common type of energy. Solar energy is used as
the reference and the common type of energy used in environmental assessments. The unit is
called solar emjoules. Solar emjoules embodied in any resource are based on the use of sunlight
that was directly or indirectly required to make a resource. For instance, solar emjoules of a tree
in an unmanaged forest would include the emergy of the sunlight, wind, and rainfall (chemical
potential and geopotential), all of which resulted either directly or indirectly from inputs of
sunlight or other primary emergy sources. In emergy, models of natural processes on global and
local scales underlying the formation of these basic resources, including renewable and
nonrenewable resources, are used to estimate the amount of emergy in these resources. The
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emergy from these resources is included in the total emergy used to make a product from the
respective quantity of these resources. In this sense, emergy is like the "energy and resource
memory" of a product system.
Some previous research and implementation of emergy in the LCA context has been performed
and the added value of using emergy in the LCA context has been extensively discussed (Rugani
et al., 2011, Raugei et al., 2014). Currently, there is no consensus on a set of impact
characterization factors through which emergy can be integrated into lifecycle databases,
although a methodology and some initial work towards incorporating emergy into LCA datasets
has been done (Baral and Bakshi, 2009; Ingwersen, 2011; Raugei et al., 2006, Rugani et al., 2011
Zhang et al. 2010). Thus, there is a need for a standardized library for using emergy in LCA that
can be used to provide a measure of environmental support to accompany LCA studies.
This report describes the calculations for emergy characterization factors (EmCFs) for the
accompanying excel database called EmCFdb (emergy characterization factor database). The
term characterization factor is derived from Life Cycle Assessment (ISO 14044, 2006). The
library is designed to serve as a Life Cycle Impact Assessment (LCIA) method with multiple
impact categories all related to emergy for use in LCA studies and independent emergy
accounting; however, the EMCFdb is also useful for other methods and models, including
traditional emergy synthesis, for the reasons stated below. We build upon the library of Rugani
et al. (2011) through further compilation of EmCFs from sources and development of several
new EmCF computations. The refinements are detailed progressively to build on each other as
described in the following paragraphs.
First, we discuss fundamental theories and assumptions that underlie EmCF calculations, then we
discuss methods of computing EmCFs in a sequence of resource 'groups' which generally build
in space and time on the previous groups. We close with a discussion of knowledge and
conceptual gaps, which require further research.
The emergy method is fast evolving. Numerous hurdles must be overcome to integrate emergy
with LCA software while minimizing opportunities for ad-hoc decisions by users. Here we have
aimed to avoid tedious case-by-case examination of the rules of emergy algebra (Brown and
Herendeen, 1996) by using a common framework for all EmCF calculations. The framework
consists of updated calculations of the geobiosphere emergy baseline (GEB) (Brown et al., 2016)
and the recalculation of the energy inputs to the geobiosphere according to their available energy
content (exergy) to be consistent with Odum's (1996) definition of emergy. All material and
energy elementary flows are expressed as exergy flows and therefore EmCFs are computed as
emergy divided by exergy. In the cases of localized evaluations, common output units (e.g., m2)
are used to homogenize EmCF calculations. These will all be explained in the following sections.
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2.0 The EmCF library
Because of the size and complexity of the Emergy EmCF database, it is submitted separately
from this written report in electronic form. The Microsoft EXCEL database (Microsoft 365 MSO
Version 2302) is titled "EmCF_database_yyyy_mm_dd" where the yyyy,mm,dd corresponds to
the year, month, and day of the latest version. We refer to this database throughout this report as
EmCFdb. The database is comprised of several worksheets, the third of which, titled EmCF
Library, contains the EmCFs for all elementary flows so far identified, total 203 flows.
Additional supporting worksheets are also included. Table 1 lists and describes each of the
supporting worksheets included in the EmCFdb.
When using emergy as an impact assessment in LCA to capture more complete resource use than
traditional LCA, the emergy used to make a product is calculated to be the sum of all elementary
flow totals used in all life cycle processes in making the product multiplied by the emergy
characterization factor (EmCF) for that specific flow as in Equation 1. The EmCF library
provides characterization factors, equivalent to UEVs in the emergy literature (EmCF = UEV)
(Brown and Ulgiati, 2004) for elementary flows in a life cycle inventory (LCI). This library
provides a complete set of characterization factors for common types of elementary flows in
LCA to provide a full accounting for the emergy of processes and products. Elementary flows
are raw energies or materials (resources) taken in from the environment or emitted by
(emissions) from one or more human activities (a process). Environmental impact assessment in
LCA is a function of the sum of the quantities of each elementary flow for the product system
times its respective characterization factor for the impact of interest.
LCIp x EmCF = UEVp (1)
Where,
LCIp = a vector of all elementary flow totals in the life cycle of product, p
EmCF = a vector of characterization factors for all elementary flows (mostly
resources)
UEVp = unit emergy value of product p
In order to develop a list of elementary flows useful for existing and future life cycle inventory,
the complete list of elementary resource flows from two major commercial databases, Ecoinvent
v2.2 (Weidema and Hischier, 2010) and GaBi v4 (PE International GMBH and University of
Stuttgart, 2007), were extracted and analyzed. From these lists, resource elementary flows were
then categorized by type. Types determined were resources from atmospheric gases, biological
resources, land resources, fossil fuels, minerals and metals, raw renewable resources, rocks and
aggregates, and water resources. The list of resource flows from the two commercial databases
were then used as a reference for the development of a comprehensive list of resources. Due to
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differences and peculiarities in elementary flow nomenclature, an original list of clearly defined
names and resources was developed for which EmCFs are provided.
Table 1: List of supporting worksheets in the EmCFdb.
Worksheet Title
Description
1 Readme and Changinglog
2 Table of Content
3 EmCF Library
4 Renewable Earth flows
Crust element composition
6 Precipitation Matrix
Inversion
7 Water
Singular minerals
Multiple mineral deposits
10 Aggregate mineral s
11 Ocean ions
12 Atmospheric gases
Documentation of what changes were done by who
and when
The list of the worksheets in the database
The summary table of all elementary EmCFs listed
by major category
Summary of the constants and emergy
computations of the annual primary secondary and
tertiary renewable emergy flows driving the
geobiosphere
Table of the abundance and molar mass of
elements used in computation of EmCFs for
minerals
Table of precipitation flows over the terrestrial,
ocean and in the atmosphere using Matrix
Inversion method
Table summarizing the computation of EmCFs of
different freshwater storages and flows based on
Gibbs free energies
Table of the EmCFs for elementary flows of
singular minerals
Tables of mineral EmCFs that are principally
mined from several different parent minerals
Tables of aggregates of minerals that are held
together mechanically, not chemically
Ocean ion fluxes and exergy enrichment ratio
computation of EmCFs
Summary table of the EmCF computations for the
main atmospheric gases using exergy enrichment
ratio
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Worksheet Title
Description
13 Land, biomass & soil
Tables of computations for EmCFs associated with
land, including NPP, biomass and soil organic
matter
Tables of the computation for wood from different
types of ecosystems
Tables leading to the computation of EmCFs for
coal
Tables leading to the computation of EmCFs for
crude oil and natural gas
List of references
14 Wood
15
Coal
16 Oil & NG
17 References
Elementary resources are also categorized as nonrenewable vs. renewable. Renewability is
determined by generation time of the resource compared with a preselected renewable cutoff
threshold, set at 100 years as a first approximation. The renewability threshold, which influences
the category designations, can easily be modified.
Using emergy has also been suggested as a method of tracking use of ecosystem services in LCA
(Zhang et al., 2010). Ecosystem services (e.g., water purification, air quality regulation, wood
fuel, etc.) associated with each of the flows are listed in the database. Information is also
provided for each flow on whether the flow is considered a resource stock or resource flow, and
examples of some technosphere activities commonly associated with the flows are provided to
help guide users to where they might be used in a life cycle inventory.
A summary table of EmCFs for elementary flows is provided at the end of this document (Table
A-l). While it summarizes the list of elementary flows we have evaluated to date, for a full
understanding of the methods, assumptions and calculations employed, we suggest the library
spreadsheet should be used as a reference.
2.1 Emergy Algebra
Calculations performed within the EmCFdb assume steady state and are performed following
standard emergy accounting procedures, which are also referred to as Emergy Algebra (Odum,
1996). Emergy algebra is based on the following set of rules:
Rule 1: Emergy is the available energy (exergy) of one kind that is used up in
transformations directly and indirectly to make a product or service.
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Rule 2: In processes having one output, all independent emergy inputs are assigned to
the processes' output.
Rule 3: When a pathway splits, the emergy is assigned to each branch of the split based
on its percent of the total available energy flow (or mass) on the pathway before the split.
Rule 4: In processes having two or more co-products, all independent input emergy is
assigned to each co-product.
Rule 5: The emergy assigned to by-product flows is proportional to the ratio of the by-
product 's available energy to the available energy of input flows.
Rule 6: Within a system, emergy cannot be counted twice:
a) emergy in feedbacks cannot be double-counted
b) co-products, when reunited cannot be added to equal a sum greater than the
source emergy from which they were derived
Numerous authors have elaborated upon the details, consequences, and applications of the above
emergy algebra rules. As this detail is beyond the scope of this report, the reader is referred to
Odum (1996), Brown and Herendeen (2006), Brown and Ulgiati (2004), Rugani (2010).
The EmCFdb elementary flows are organized hierarchically, which has direct implications for
the calculation of their transformities. Primary flows are the main driving exergies and consist
of solar radiation, tidal dissipation, and deep earth heat. Collectively, the annual sum of these
exergies is referred to as the geobiosphere emergy baseline (GEB) (Odum, 1996). Secondary
flows are directly dependent on the GEB and generally consist of global cycles. For example,
rainfall is part of a global hydrologic cycle that depends on inputs from each part of the GEB.
Likewise, crustal dynamics consist of the continental uplift, subduction and erosion of crustal
material that is driven, both directly and indirectly, by the GEB (Odum, 1996; Brown and
Ulgiati, 2004; Campbell, 2016). Secondary transformities are calculated by parsing the GEB
over the entirety of each energy cycle. Tertiary flows are driven by secondary flows, and the
remaining flows are driven by some combination of secondary and tertiary flows.
Figure 1 is a visual representation of the database. Renewable inputs are circles on the outside of
the system boundary (Figure 1 and 2). It is only a snapshot of the system to highlight the hierarchy
embedded the elementary flows. However, many flows and storages are dynamic and cross spatial
and temporal boundaries. For example, rain and water storages such as lakes and groundwater are
part of the hydrological cycle (
Figure 3Figure 4). Descriptions of the symbols used in the figures, which are part of an energy
system language, can be found in Appendix A of Odum, 1996.
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Primary Secondary Tertiary Other Products
Figure 1 The major elementary flows in Earth geobiosphere described in this ECF library are
organized in primary, secondary and tertiary flows.
3.0 Renewable Primary Earth Emergy Inputs
The geobiosphere is primarily driven by a tripartite of exergy sources (Odum, 1996; Brown and
Ulgiati, 2010) comprised of incoming solar radiation, tidal dissipation, and deep earth heat
(Figure 1, Figure 2). Tides and earth heat are related to the largest and most ubiquitous source,
sunlight, and expressed in solar equivalent Joules (seJ)1. The Earth's planetary emergy baseline
has been estimated many times (Brown and Ulgiati, 2016a; Campbell, 2016). The various
baselines, ranging from 9.26 E24 to 15.2 E24 seJ/yr were based on different methods of
computation and assumptions regarding geobiosphere system organization.
Following the Eighth Biennial Emergy Conference held in January of 2014, the need for
revisiting the procedures and assumptions used to compute the Geobiosphere Emergy Baseline
emerged as a necessity to strengthen the method of Emergy Accounting and remove some
1 We distinguish between solar equivalent Joules (seJ) and solar emjoules (sej). The tide and
deep heat are expressed as solar equivalent Joules because solar processes do not directly
produce them. All other emergy that is produced by the tripartite is expressed as solar emjoules
(sej), using a lowercase "j". An emjoule is not available energy and therefore is not actually a
joule, thus the lowercase "j".
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sources of ambiguity and potential misunderstanding. Three studies (Brown and Ulgiati, 2016a;
Campbell, 2016; and De Vilbiss et al., 2016) were undertaken in an effort to move towards a
single, agreed upon baseline. A synthesis document was published to clarify the baseline issue
and produce a single, agreed upon value. The result of that effort was a synthesis of the methods
into a single baseline equal to 12.0 E24 seJ/yr (Brown et al., 2016), which is the baseline adopted
in this EmCF library. Table 2 lists the solar equivalent joules for the Earth tripartite. In the
future, if there is a need to update the baseline, the change can be easily propagated through the
library to update all the factors.
The resulting GEB is expressed as solar equivalent exergy. whose unit abbreviation is seJ. Solar
equivalent exergy is computed as an equivalence between sunlight and the other sources
comprising the GEB, because Earth geothermal heat, and the gravitational energy absorbed are
not direct transformations of sunlight. We have adopted the convention that solar equivalent
energy uses the abbreviation seJ (note the capital J). Emergy computed for subsequent products
of the Earth's geobiosphere (e.g., rain, wind, waves, etc.) is computed as solar emergy, whose
units are solar emjoules and whose abbreviation is sej (note the lowercase j).
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Figure 2 The Earth system, or geobiosphere, is composed of 4 main subsystems, the Atmosphere,
Hydrosphere, Lithosphere and the Anthroposphere. The geobiosphere is driven by three main
energy sources, solar energy, the gravitational pull of the sun and moon that creates tidal energy,
and the geothermal energy from deep earth heat which is largely responsible for geologic processes.
In recent times, the fossil fuel energies released by humans have added considerably to the total
energy budget of the Earth.
Table 2: Solar Equivalent Joules for Earth's tripartite (Brown et al., 2016)
Solar Equivalent Solar Energy
Inflow Exergya Ratio (SER)b Equivalence0
(seJ/J) (E+24 seJ yr"1)
Solar energy absorbed 3.73E+24 1 3.7
Geothermal Flows 9.52E+20 4,900 4.7
Tidal energy absorbed 1.17E+20 30,900 3.6
Total Global Empower ~ 12.0
9
-------
a. Average of the exergy from Brown & Ulgiati (2016a), Campbell (2016)
b. Average of the solar equivalent energy from Brown & Ulgiati (2016a), Campbell (2016)
c. rounded to two significant figures
4.0 Renewable Secondary Earth Emergy Flows
The primary energy driving the geobiosphere is transformed into secondary global flows that
include, e.g., wind and rainfall. The following sections summarize the methods of computing the
secondary flows. Calculations are included in the EmCFdb - Renewable Earth Flows worksheet.
4.1 Wind
Wind transformity is calculated as the ratio between driving emergy and the amount of wind
energy dissipated. As wind is a global circulation process, its driving emergy is the GEB. Wind
dissipation occurs due to friction associated with upper-level atmospheric turbulence and surface
drag. Global wind dissipation is a complex, nonlinear process, and estimations of its value have
been made using a variety of methods. Here, we follow the approach of Lee and Brown (2019),
as it provides an estimate of global surface dissipation that agrees with estimates made using
alternative approaches and provides a standardized approach to calculating local wind
dissipation, which is useful for emergy analyses that account for wind input.
Surface wind dissipation is calculated using the difference between geostrophic and surface wind
speeds, which assumes the reduction in surface wind speed is indicative of energy dissipation
from surface roughness. Geostrophic wind speed is calculated using Equation 2. For the
estimation of global surface wind dissipation, Lee and Brown (2019) obtained measured wind
speed from NASA's Surface meteorology and Solar Energy (SSE) dataset, which provides
average 50 m wind speed at a one arc degree resolution. Surface roughness is characterized using
data from Chandler et al. (2005) applied to NASA's Moderate Resolution Imaging
Spectroradiometer (MODIS) land cover data.
V = Vref * (/")* (2)
^ref
Where,
V = geostrophic wind velocity
Vref = Reference velocity at 50 m
Zref= Reference height = 50m
Z = height for velocity V = 1000m
a = surface roughness exponent
10
-------
Next wind energy dissipated between the geostrophic wind and ground surface is computed
using Equation 3.
Ewind = 1/2pKGNV3AT (3)
Where,
Ewind= wind energy dissipated
p = Air density = 1.23 kg/m3
Kgn= geostrophic drag coefficient 1.26 E-3 (over sea, N=11) and 1.64 E-3 (over
land, N=7) from Garratt (1992)
A= area of each cell
r = 3.15 E7 s/yr
The resulting energy dissipation rates are provided, by major biome, on the Land, Biomass and
Soil worksheet of the EmCFdb. Summed over the Earth's surface, total dissipation is 2.31 E22
J/yr, which is equivalent to 1.44 W/m2
Wind transformity is the ratio of the GEB to global wind dissipation.
The estimate of surface energy dissipation (2.31 E22 J/yr or 1.44 W/m2) is higher than past
analyses used for wind transformity calculations (e.g., Brown and Ulgiati, 2016b; Campbell and
Urban, 2016) but is in line with past estimates made in the general atmospheric circulation
literature (Table 3). Early estimates (Lorenz, 1967; Ellsaesser, 1969; Gustavson, 1979) were
based on mechanistic, idealized physical models generally based on first principles -
conservation of energy, mass, momentum, etc. and yielded estimates of total dissipation (surface
plus upper atmosphere turbulence) that ranged from 2.35-7.06 W/m2. Peixoto and Oort (1992)
and Winn-Nielsen and Chen (1993) are largely review texts, though they provide useful critiques
of the work that had occurred in the preceding decades. Peixoto and Oort (1992) and Winn-
Nielsen and Chen (1993) estimate total dissipation as 1.65-2.02 W/m2. Beginning in the early
21st century, results from early global circulation models (GCMs) used conservation of energy to
estimate losses due to friction, or wind energy dissipation, in the entire atmosphere. Estimated
dissipation was approximately 2 W/m2, similar to the widely used estimates of Peixoto and Oort
(1992) and Winn-Nielsen and Chen (1993). Also, using the improved resolution of these new
models, Boville and Bretherton (2003) estimated that the surface layer accounts for 83% of total
dissipation, or 1.65 W/m2, which is more than double that estimated by Ellsaesser (1969)
(Campbell and Erban (2016) used Ellsaesser (1969) as the basis for the fraction of dissipation
occurring in the GBL). Boville and Bretherton (2003) also noted that surface heating
(dissipation) was mostly due to surface stress from oceanic storm tracks. The total surface
dissipation calculated using the methods of Lee and Brown (2019) generally aligns with this
11
-------
estimation, as using average wind speeds likely underestimates the dissipative influence of major
storms.
GEB 12.0 £24^
Twind ~ p — j ~ 520 sej/] (4)
£global 2.31 £22 —
yr
Table 3. Summary of modeled global wind dissipation rates
Planetary
Boundary
Layer (-100
mb)
Global
Boundary
Layer (-900
mb)
Fraction of
Total in GBL
Reference
Dissipation in W/m2
Lorenz, 1967
2.35
Ellsaesser, 1969
0.35
Gustavson, 1979
7.06
2.47
Peixoto and Oort, 1992
1.65
Winn-Nielsen and Chen, 1993
2.02
Becker, 2003
1.90
Boville and Bretherton, 2003
2.00
1.65
0.83
Brown and Ulgiati, 2016
0.94
Campbell and Erban, 2016
2.02
0.76
0.38
Lee and Brown, 2019
1.44
NA
4.2 Precipitation
Precipitation is one part of the global hydrologic cycle, as illustrated in
Figure 3. The global hydrologic cycle is an energy cycle, transferring incoming solar radiation
and absorbed thermal radiation across the globe using water as the medium. The transformity of
precipitation is calculated assuming it is a secondary flow, meaning it takes the entire GEB to
drive the entire cycle, similar to the wind global circulation process discussed in Section 4.1.
Although inputs of driving exergies are not uniform across the globe, the cycle is interconnected,
meaning, for example, rain on land cannot occur without transfers of atmospheric moisture that
originate from evaporation over the ocean. Likewise, oceanic processes cannot occur without
regular inputs of runoff from the land.
The chemical quality of precipitation is uniform regardless of where it falls and relative to seawater
as the reference. Chemical quality is measured by total dissolved solids (TDS) content, which for
rain is 10 ppm due to the dilution that results from evapotranspiration processes (
Figure 3). Because of this, rain has an energetic potential relative to runoff (assumed TDS of
100 ppm) and seawater and cellular interstitial fluid, both of which have a solute concentration of
12
-------
around 35,000 ppm. This chemical potential is referred to as Gibbs free energy, which is
calculated using Equation 5. As an example, the Gibbs energy (AGp) between average
precipitation (5 =10 ppm) and ocean or cellular interstitial fluid (S0 =35,000 ppm) is 4.72 J/g,
where R is the universal gas constant, 8.3143 J/mole.K, average Earth surface temperature T =
2Q1.2SK (ncdc.noaa.gov), and molecular weight of water wHz0 = 18.01 g/mole. The
transformity for the terrestrial precipitation is 22,500 sej/J. The Water worksheet of the EmCFdb
provides full calculation inputs and results of the flows in hydrological cycle based on Gibbs free
energy.
Although GEB has been used to derive terrestrial rainfall, there has been argument that the use of
the entire GEB may not accurately reflect the emergy required for rainfalls. One of the
alternative methods to explore different emergy flows for precipitation and other hydrological
flows is the matrix inversion method. It was applied in partitioning flows of available energy in
water between three main compartments/storages - ocean, continents and atmosphere (Brown
and Ulgiati, 2016). The transformity of rainfall is calculated following Brown and Ulgiati
(2016b), where major compartments of the hydrologic cycle are represented as a network and
flows between compartments are calculated using matrix algebra.
Figure 3a shows pathways of water flowing between compartments, given in km3 y"1 (Bengtsson,
2010).
Figure 3b shows the available energy of water flows between compartments, computed using the
difference between chemical potentials (Gibbs free energy, Equation 5) of flows from one
compartment to the next. Application of this method results in unique transformities for
precipitation over land and precipitation over ocean of 7,010 sej/J and 4,230 sej/J, respectively.
The Precipitation Matrix Inversion worksheet of the EmCFdb provides full calculation inputs
and results. T, S and DH in the worksheet mean tide, sun and deep heat emergy. L. Atmos and
O. Atmos. Mean Land Atmosphere and Ocean Atmosphere, respectively.
One of the ways to test this hypothesis is to compare the driving forces for global biomes using
respective transformities because the structure and productivity of world's ecological systems
have been extensively studied (Lee and Brown, 2021). The heat map is shown in Table 4. Table
4a shows the emergy accounting for each biome using transformities for terrestrial precipitation
of 7,010 sej/J. Table 4b shows the ones using 22,500 sej/J. The dominant emergy flows
(highlighted) using matrix inversion indicate wind emergies for majority of the biomes while the
dominant inputs using Gibbs free energy are terrestrial rain for majority of the biomes. It has
been argued that the common classification schemes of global biotic communities rely on two
abiotic elements, water and temperature. Although evapotranspiration is sometimes used, the
(5)
13
-------
most common water parameter in most of the classification schemes is annual precipitation (Lee
and Brown, 2021). Therefore, the most important driving energy sources would be highly
correlated to these two variables. This suggests that rain should be the dominating emergy rather
than wind. In this UEV library, Gibbs free energy derived transformities for precipitation are
adopted, not matrix inversion method. The reason to include the comparison of matrix inversion
method is to document the discussions and the underlying reasoning so others will not repeat the
process.
Table 14. Emergy heat maps for global biomes using different transformities.
(a)
Ocean UEV=4230
Transformities
1
4900
30900
520
7010
7010
21300
3220
EMERGY Table (rainUEV=7010 sej/J)
Biome Type
Solar
Geothermal
Tidal
Wind
Rain Chem
Water Chemical
sej/yr
AET Chem
Runoff Chem
Runoff Geo
MAX BIOME
TVopical & Subtropical Moist Broadleaf Forests
1.48E+23
1.31E+23
1.75E+22
6.00E+23
1.35E+24 r
8.67E+23
7.93E+23
7.35E+22
4.32E+22
8.67E+23
TVopical & Subtropical Dry Broadleaf Forest
2.46E+22
2.21E+22
1.74E+21
1.31E+23
1.20E+23 r
8.28E+22
8.26E+22
2.27E+20
6.18E+20
1.31E+23
TVopical & Subtropical Coniferous Forest
6.25E+21
6.14E+21
3.13E+19
3.75E+22
2.71E+22 r
1.83E+22
1.83E+22
3.64E+18
8.25E+17
3.75E+22
Temperate Broadleaf & Mixed Forests
7.37E+22
7.86E+22
2.77E+22
6.44E+23
3.80E+23 r
2.62E+23
2.53E+23
8.67E+21
3.04E+21
6.44E+23
Temperate Conifer Forests
2.55E+22
3.29E+22
1.92E+21
1.78E+23
1.18E+23 r
7.17E+22
7.13E+22
4.48E+20
1.84E+20
1.78E+23
Boreal Forests/Taiga
6.79E+22
8.53E+22
6.77E+21
5.37E+23
2.64E+23 r
1.90E+23
1.77E+23
1.37E+22
6.21E+21
5.37E+23
TVopical & Subtropical Grasslands, Savannas & Shrublands
1.78E+23
1.28E+23
7.94E+21
9.06E+23
6.33E+23 r
5.16E+23
4.77E+23
3.97E+22
1.42E+22
9.06E+23
Temperate Grasslands, Savannas & Shrublands
6.48E+22
6.22E+22
4.28E+21
3.51E+23
1.55E+23 r
1.28E+23
1.25E+23
3.21E+21
2.00E+22
3.51E+23
Flooded Grasslands & Savannas
8.11E+21
6.52E+21
2.87E+20
5.46E+22
2.66E+22 r
2.38E+22
2.10E+22
2.73E+21
6.18E+20
5.46E+22
Montane Grasslands & Shrublands
4.28E+22
3.77E+22
4.13E+18
2.34E+23
8.40E+22 r
6.30E+22
6.28E+22
1.71E+20
1.03E+21
2.34E+23
Tundra
4.57E+22
8.22E+22
3.52E+22
7.32E+23
1.35E+23 r
6.28E+22
6.10E+22
1.81E+21
1.29E+21
7.32E+23
Mediterranean Forests, Woodlands & Scrub
2.47E+22
2.57E+22
2.11E+20
1.31E+23
5.29E+22 r
4.05E+22
4.04E+22
9.27E+19
6.04E+20
1.31E+23
Deserts & Xeric Shrublands
2.42E+23
1.99E+23
4.90E+21
8.85E+23
1.72E+23 r
1.43E+23
1.32E+23
1.10E+22
2.83E+21
8.85E+23
Mangroves
2.43E+21
2.34E+21
5.05E+21
1.17E+22
1.87E+22 r
8.93E+21
8.92E+21
1.22E+19
6.72E+21
1.17E+22
River
2.32E+22
2.04E+22
1.45E+20
1.01E+23
9.36E+22 r
1.86E+23
6.35E+22
1.23E+23
2.82E+23
2.82E+23
Lake
6.55E+21
5.68E+21
0.00E+00
7.62E+21
2.04E+22 W
1.68E+22
1.51E+22
1.69E+21
3.82E+20
1.68E+22
Rock & Ice
5.69E+22
8.32E+22
1.65E+21
9.75E+23
7.71E+22 r
7.81E+21
7.72E+21
9.02E+19
2.04E+19
9.75E+23
Terrestrial Sub total
1.04E+24
1.01E+24
1.15E+23
6.51E+24
r 3.73E+24
2.69E+24
" 2.41E+24
2.80E+23
3.83E+23
6.97E+24
Estuary 1
2.24E+21
2.52E+21
5.52E+21
1.11E+22
1.23E+22 r
3.58E+24
5.51E+21
3.58E+24
5.40E+23
3.58E+24
Ocean
2.69E+24
3.65E+24
3.47E+24
5.48E+24
1.33E+24
1.32E+24
2.04E+21
4.69E+22
9.81E+24
Total
3.73E+24
4.66E+24
3.60E+24
1.20E+25
1.20E+25 ^
7.60E+24
3.74E+24
3.86E+24
9.71E+23
2.04E+25
(b)
Transformities
1
4900
30900
520
22500
22600
21300
3220
EMERGY Table (rain UEV=22500 sej/J)
Biome Type
Solar
Geothermal
Tidal
Wind
Rain Chem
Water Chemical
sej/yr
AET Chem
Runoff Chem
Runoff Geo
MAX BIOME
TVopical & Subtropical Moist Broadleaf Forests
1.48E+23
1.31E+23
1.75E+22
6.00E+23
4.35E+24
2.63E+24
2.56E+24
7.35E+22
4.32E+22
2.63E+24
TVopical & Subtropical Dry Broadleaf Forest
2.46E+22
2.21E+22
1.74E+21
1.31E+23
3.84E+23
2.67E+23
2.66E+23
2.27E+20
6.18E+20
2.67E+23
TVopical & Subtropical Coniferous Forest
6.25E+21
6.14E+21
3.13E+19
3.75E+22
8.70E+22
5.91E+22
5.91E+22
3.64E+18
8.25E+17
5.91E+22
Temperate Broadleaf & Mixed Forests
7.37E+22
7.86E+22
2.77E+22
6.44E+23
1.22E+24
8.26E+23
8.17E+23
8.67E+21
3.04E+21
8.26E+23
Temperate Conifer Forests
2.55E+22
3.29E+22
1.92E+21
1.78E+23
3.80E+23
2.30E+23
2.30E+23
4.48E+20
1.84E+20
2.30E+23
Boreal Forests/Taiga
6.79E+22
8.53E+22
6.77E+21
5.37E+23
8.47E+23
5.83E+23
5.70E+23
1.37E+22
6.21E+21
5.83E+23
TVopical & Subtropical Grasslands, Savannas & Shrublands
1.78E+23
1.28E+23
7.94E+21
9.06E+23
2.03E+24
1.58E+24
1.54E+24
3.97E+22
1.42E+22
1.58E+24
Temperate Grasslands, Savannas & Shrublands
6.48E+22
6.22E+22
4.28E+21
3.51E+23
4.99E+23
4.05E+23
4.02E+23
3.21E+21
2.00E+22
4.05E+23
Flooded Grasslands & Savannas
8.11E+21
6.52E+21
2.87E+20
5.46E+22
8.52E+22
7.06E+22
6.79E+22
2.73E+21
6.18E+20
7.06E+22
Montane Grasslands & Shrublands
4.28E+22
3.77E+22
4.13E+18
2.34E+23
2.70E+23
2.03E+23
2.02E+23
1.71E+20
1.03E+21
2.34E+23
Tundra
4.57E+22
8.22E+22
3.52E+22
7.32E+23
4.33E+23
1.98E+23
1.97E+23
1.81E+21
1.29E+21
7.32E+23
Mediterranean Forests, Woodlands & Scrub
2.47E+22
2.57E+22
2.11E+20
1.31E+23
1.70E+23
1.30E+23
1.30E+23
9.27E+19
6.04E+20
1.31E+23
Deserts & Xeric Shrublands
2.42E+23
1.99E+23
4.90E+21
8.85E+23
5.52E+23
4.37E+23
4.26E+23
1.10E+22
2.83E+21
8.85E+23
Mangroves
2.43E+21
2.34E+21
5.05E+21
1.17E+22
6.01E+22
2.88E+22
2.88E+22
1.22E+19
6.72E+21
2.88E+22
River
2.32E+22
2.04E+22
1.45E+20
1.01E+23
3.00E+23
3.27E+23
2.05E+23
1.23E+23
2.82E+23
3.27E+23
Lake
6.55E+21
5.68E+21
0.00E+00
7.62E+21
6.54E+22
5.03E+22
4.86E+22
1.69E+21
3.82E+20
5.03E+22
Rock & Ice
5.69E+22
8.32E+22
1.65E+21
9.75E+23 a
^48E+23^S
2.50E+22
2.49E+22
9.02E+19
2.04E+19
9.75E+23
Terrestrial Sub total
1.04E+24
1.01E+24
1.15E+23
6.51E+24 \
1.20E+25
) 8.05E+24
" 7.77E+24
2.80E+23
3.83E+23
1.00E+25
Estuary 1
2.24E+21
2.52E+21
5.52E+21
1.11E+22
3.59E+24
1.78E+22
3.58E+24
5.40E+23
3.59E+24
Ocean
2.69E+24
3.65E+24
3.47E+24
5.48E+24
0.00E+00
1.46E+22
1.26E+22
2.04E+21
4.69E+22
9.81E+24
Total
3.73E+24
4.66E+24
3.60E+24
1.20E+25
1.20E+25
1.17E+25
7.80E+24
3.86E+24
9.71E+23
2.34E+25
14
-------
Global Hydrologic Cycle yp Water Flows = 103 km3 y1
==' Source Energy Flows = xE24 seJ y1
Global Hydrologic Cycle ^ Water Flows = J y^1
Source Energy Flows = xE24 seJ y1
Figure 3 Global hydrologic cycle (a) flows in km3 y"1 from Bengtsson (2010) and (b) in Gibbs
energy.
15
-------
5.0 Renewable Tertiary Earth Emergy Flows
Global available energies of tertiary flows are driven indirectly by the primary flows, but directly
by splits of the biosphere's secondary energies. Tertiary flows include ocean currents, the
available energy in breaking waves on shorelines of continents as well as chemical and
geopotential energy of rivers. The following summarizes methods of computing tertiary flows.
Calculations are included in the Renewable Earth Flows worksheet of EmCFdb.
5.1 Ocean Currents
Surface ocean currents2 are largely wind driven. Accordingly, we can calculate an average ocean
current transformity as the emergy input from wind divided by the amount of energy dissipated
(Equation Error! Reference source not found.Error! Reference source not found.Error! Ref
erence source not found.Error! Reference source not found.6). Emergy input from the wind
is calculated as the surface wind energy dissipated over the ocean (1.1 E22 J/yr) (Lee and Brown,
2019) multiplied by its transformity (520 sej/J) (Section 4.1) and is equal to 5.5 E24 sej/yr. The
amount of energy dissipated by surface ocean currents is obtained from Wang and Huang
(2004a), who estimate total energy input to the Ekman layer of 3 TW (9.5 El9 J/yr). We assume
that this total energy input is equally balanced by dissipative drag forces in the Ekman layer (i.e.,
steady state) and is thus equivalent to total energy dissipation. The resulting transformity is
5.2 Waves
Ocean waves are created as the result of wind dissipation over the ocean surface. The
transformity of ocean waves is therefore calculated as this wind dissipation rate over the energy
dissipated by the waves themselves through turbulence or frictional drag with the ocean bottom
(Equation 7). The driving emergy is the same as that driving surface ocean currents (5.5 E24
sej/yr) while global wave energy dissipation is assumed equivalent to the amount of energy
transferred to waves from wind (i.e., steady state is assumed). The amount of energy transferred
to waves from wind is estimated as 68 TW, or 2.2 E21 J/yr (Rascale et al., 2008).
2 Ocean currents consist of surface currents, which are primarily wind driven, and deep currents,
which are primarily driven by differences in temperature and salinity (also referred to as
thermohaline circulation). The calculation of ocean current transformity only refers to the surface
currents.
58,000 sej/J.
Emwind
Tcurrents ~ ~p
c currents
= 58,000 sej/J
9.SE19 —
yr
(6)
16
-------
Em 5.5 £24^
F = y-r = 2,600 sej/J (7)
^waves 2.2 E21 —
yr
When ocean waves reach shore, the driving wind emergy is dissipated on the shore. Therefore,
the EmCF value above cannot be used when the EmCF is used in terrestrial activities. The
annual wave energy transmitted to surface zone turbulence is believed to be 2.4 TW (equivalent
to 7.57E19 J/yr). The EmCF of wave power on the shore is the ratio of the ocean wind emergy
to the energy dissipated on the shore which is much larger than the wave in the ocean Eq. Error! R
eference source not found.:
ECFwavesonshore = SA9 E24 S6JlyT/7.57£19 J/yr = 72400 sej/J (8)
5.3 Continental runoff geopotential transformity
Average annual global river discharge mg = 3.73 £"19 g/yr (Dai et al., 2009) runs off land
whose average elevation is h = 797m (Eakins and Sharman, 2013). The geopotential energy
dissipated by this runoff is given as Eg = mggh = 2.9 E20 J/yr, where g = gravitational
constant. The mass of yearly continental precipitation which drives continental runoff is mr =
1.13 E20 g/yr (Adler et al., 2003). The emergy of continental rainfall is 1.13 E20 g/yr * 4.72
J/g * 22,500 sej/J =1.2 E25 sej/yr, which is the GEB (see 4.2. Precipitation above). The EmCF
of geopotential energy dissipated by continental runoff is the emergy of terrestrial rain divided
by Eg as follows in Equation 9:
AGrTrmr 120 EM S~0
Tr,g = V = T = 41<180 SeJ/J (9>
n3 2.9 E20 —
5.4 Continental runoff chemical exergy
Dissipation of the chemical exergy of terrestrial precipitation also drives the formation of
chemical exergy in continental runoff. This means that the emergy of runoff chemical exergy is a
co-product with the emergy of runoff geopotential exergy, both of which are produced from
terrestrial precipitation's chemical exergy. Global average chemical exergy in runoff is found
using Equation 10, substituting TDS of S = 100 ppm (Milliman and Farnsworth, 2011; table
2.9).
17
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(10)
The EmCF of chemical exergy of runoff is the emergy of terrestrial precipitation (1.2 E25 sej/yr,
which is the GEB (see 4.2. Precipitation above)) divided by the chemical exergy of runoff (3.7
E19 g/yr * 4.71 J/g =1.8 E20 J/yr) (Equation 11).
Figure 4 is a summary systems diagram of the global water cycle showing aggregated global
storages of surface and ground water as well as ice. Specific emergy e of each global water
storage i (at its global average purity, denoted e) is the ratio of driving emergy, Em, to the
quotient of mass m and turnover time t (Equation 12). The driving emergy for all flows and
storage in hydrological cycle such as rain, vapor, glaciers, ground ice, and ocean, is the GEB
(Em = 12.0 £"24 sej/yr) because they utilize high latitude precipitation which originates from
global transpiration and evaporation from marine and terrestrial waters at global scale.
AGrxrmr
12.0 £"24 ^
— = 68,300 sejU
(11)
6.0 Water EmCFs
Em
£¦ ~
(12)
18
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Figure 4 The global water cycle showing the hierarchical circulation of water driven by the
tripartite and the main storages of water. ET = evapotranspiration, Evap = evaporation, Prec. =
precipitation, and Gd water = ground water
6.1 Scaling Water EmCFs by Purity and Turnover Time
The chemical transformity for freshwater varies by purity according to its Gibb's free energy AG,
also called mixing exergy. The Gibbs free energy equation is given below (Equation 13), where
s0 = 35,000 ppm salt ionized molecules in the oceans, R is the gas constant, T = 287.25K is
surface temperature (http://www.ncdc.noaa.gov/sotc/global/2013/10), w is water's molecular
weight, and q is the concentration of water molecules in freshwater storage i.
AGi = ~ Vln (C7965,OOo) (13)
As water cycles through the geobiosphere, it changes phase from liquid saline water to
comparatively pure atmospheric vapor. This results in a bimodal distribution of water's purity
with local maxima around seawater 35 ppt TDS and vapor with 10 ppm TDS. The average
transformity of a freshwater body i is the ratio of its average specific emergy el to its Gibb's free
energy (Equation 14). Global average TDS, transformity, and specific emergy are given for
several major freshwater storages in the EmCFdb Water worksheet.
19
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(14)
A Gi
As terrestrial precipitation accumulates dissolved solids in route to seawater, its mixing exergy or
Gibbs free energy decreases (Figure 5) according to Equation 15.
Tj = Tj(——)
1 tVA Gi
(15)
The specific emergy of a water storage can be back calculated from its transformity (Equation
15) using Equation 16.
£i = TiAGj
(16)
Equation 15 is an enrichment ratio that approaches zero as water approaches seawater purity
(Figure 5). In the EmCFdb, 'Surface water' and 'Water of unknown origin' are assigned the
minimum value of surface water resources, which are found for rivers/streams, to avoid
unreasonable over-accounting.
O CM —
~i 1 1 1 1 1 r
5000 10000 15000 20000 25000 30000 35000
TDS concentration (ppm)
Figure 5 Gibbs energy of freshwater with varying TDS concentration at T = 287.25 K.
7.0 Crustal mineral EmCFs
7.1 Singular Minerals
Individual crustal minerals and metals (hereafter collectively referred to as minerals) have
different uses within the geobiosphere and technosphere based on their chemical composition. They
20
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can only be effectively utilized, however, when available at biologically or economically sufficient
concentrations. Although the mechanisms for generating these two types of qualities - chemical and
concentration exergy - are different, we assume both are co-products of the GEB. For example,
following the original elemental endowment of the Earth, billions of years of physical, chemical and
biological processes have resulted in the formation of unique chemical properties of crustal
minerals. The same processes are responsible for their non-uniform distribution. Accordingly, we
assume the GEB is responsible for a mineral's chemical composition and its distribution. Mineral
and metals interact with sediment within the larger crustal cycle (
Figure 6)
We calculate singular mineral EmCFs using an adapted version of the methods of De Vilbiss and
Brown (2015), where the chemical specific emergy of mineral k (£kiCh) and the concentration
specific emergy of mineral k (sktC) are calculated separately. Both ek ch and Ekc are calculated
using Equation 17, where individual mineral specific emergies (sej/g) are the product of mineral
exergy (bk in J/g) and average crustal transformity (fcrust m sej/J). If fcrust is thought of as a
global emergy budget divided by a global exergy budget, the implication of this approach is that
the GEB is allocated to individual minerals as a split, where each allocation is made on the basis
of the individual mineral's exergy.
£k ~ crust ^ ^
To calculate fcrUst we first calculate average crustal specific emergy, ecrUst-, which represents
the amount of emergy used to generate a gram of crustal material. Average crustal specific
emergy is the ratio of the GEB to average crustal flux, where the crustal flux rhcrUst is given by
the ratio of the crustal mass (2.17 E25 g, Peterson and Depaolo, 2007) and the average age of the
crust (2.5 E9 yr, Taylor and McLennan, 1995; Veizer and Jansen, 1985): rhcrUst = (2.17IE +
2Sg) / (2.SE + 09yr) = 8.68 £15 g/yr.
The average specific emergy of crust is as follows in Equation 18:
12.0 £24^
(ibtl yr
^crust = = a~ = 138 E + 09 SeHd (18)
lilcrust 8.68 £"15 -S2-
yr
Next, we must calculate the average specific formation exergy of a gram of crustal material.
Note we only use Gibbs formation energy, rather than standard chemical exergy, for this
calculation. Standard chemical exergy is calculated as the sum of an element or compound's
Gibbs formation energy (also called Gibbs free energy of formation, or Gibbs energy) and
chemical exergy (Valero, 2008; Valero et al., 2012), the former representing the interactions
between mineral constituents and the latter representing the presence of the matter itself relative
to a background environment. Because we can only account for the emergy associated with
21
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planetary evolution (i.e., the GEB) and not planetary generation, we only account for matter
evolution and not matter generation.
The average crustal Gibbs energy is calculated by summing the Gibbs energy of each crustal
mineral (A G^k) (Valero et al., 2012) on the basis of that mineral's molar concentration within an
average gram of crust using Equation 19:
crust ~ 1 —ckAGf k = 1.17 EAJ/g
crust (19)
k
where ck is the molar concentration of mineral k (rnolminerai/gcmst) and AG^k is the Gibbs energy
of mineral k (J/molminerai). The average Gibbs transformity of a gram of crust can then be
calculated using Equation 20:
Tcrust ~ A£rTSt = 1A9 ES seJ/J (20)
f, crust
Chemical specific emergy of each mineral can then be calculated as the product of its Gibbs
energy (A6y fcin J/gminerai) and fcrust following the format of Equation 17.
Concentration specific emergy uses a similar approach but replaces Gibbs energy with the
mixing energy required to produce minable concentrations. Mixing energy is calculated as the
difference between free energy at mine concentration and free energy at average crustal
concentration, following the method of De Vilbiss and Brown, 2015.
Free energy for each mineral (AGfc ) makes use of molar fraction x and standard Gibbs energy
AG° k (Valero et al., 2012), where T0 = 298.15K (Equation 21). Please note this standard
temperature was used by Valero et al., (2012) to compute mineral free energy. In the future it
may be appropriate to redo their entire data set using the standard temperature referenced
elsewhere in this document (T = 287.25K )
AGfc = Xfc (AG°fc + RT0lnxk) (21)
Molar fraction (Equation 22) uses molarity a (mol/g) for mineral k at mine concentrations c in
(g/g) and molarity of average crust a, given that average molar mass of the crust is 155.2 g/mol
(Valero et al., 2012).
®k,c
xk,c ~
(®-k.,c (21)
Mineral mixing exergy, b, expresses the difference in free energy between mine concentration c
and average crustal concentration (Equation 23). This is the work available due to geobiospheric
concentration above background concentrations.
22
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b = AGKc - AGk = RTln Xfc'c/^ (23)
The product of mineral mixing exergy (b in J/g) and average crustal transformity (f crust-. m sej/J)
is a mineral's concentration specific emergy at mine conditions.
Following co-product algebra, each mineral's final specific emergy is calculated using the
greater value of its chemical specific emergy and concentration specific emergy, to avoid double-
counting. There are 316 singular minerals included in EmCFdb under Singular Minerals
worksheet.
As pointed out in De Vilbiss and Brown (2015), negative concentration exergy refers the mineral
concentration is below average. However, a negative transformity is not allowed. Due to this
issue, De Vilbiss (2013) used concentration energy rather than concentration exergy to link
crustal mass quality with energy quality. There is no thermodynamic method in the literature to
link crustal specific emergy with its transformity. In this library, only specific emergy (no
transformity) is reported because many mineral uses are mass-based.
23
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1
Figure 6 Diagram of the geobiosphere showing the crustal cycle of sediments interconnected with a
much longer cycle of the upper mantle. The productive processes of the atmosphere, biosphere,
and hydrosphere contribute to the cycling of sediments, minerals and the fossil fuels.
7.2 Mixed Minerals
For mixed minerals, or minerals that are not pure element minerals, element mass ratio is used. A
suitable parent mineral is used for the element. In some cases, multiple minerals are used (see
Multiple minerals worksheet of EmCFdb) and a weighted average taken. The element EmCF is
the ratio of the parent mineral EmCF by the mass fraction / of the desired element within it. For
example, in a lead deposit with cPb = 0.03g/g, lead's EmCF is £Pb = £pb^0 0346 = 3.39£ +
JPb
08 sej/g where fPb = 0.87g/g is the mass fraction of lead in galena (PbS), and 0.0346 =
cPbs = cPb/f = mineral grade. The specific emergy of the element is always greater than the
24
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specific emergy of the parent mineral unless the mineral is a pure element, in which case the
specific emergy of the element and of the parent mineral are identical.
7.3 Multiple Minerals
Some element EmCFs are the weighted average of multiple minerals according to their average
crustal abundance (Multiple minerals worksheet in the EmCFdb). These elements have multiple
important parent minerals (Valero, 2008). The weighted average of multiple minerals was the
chosen method because of the importance of several minerals in the ore extraction process. To
choose only one parent mineral could potentially bias the EmCF of the desired element, as each
mineral would have a different EmCF. Major multiple minerals evaluated (aluminum, iron,
nickel, silver, uranium, magnesium, manganese, titanium, cerium, lanthanum, phosphorus,
smectite) are calculated under Multiple Minerals worksheet.
7.4 Aggregate rock EmCFs
Aggregates like shale, sand, basalt, calcite, granite/gravel, perlite, bentonite and pumice are
agglomerated minerals held together mechanically, not chemically. Almost all the constituent
minerals of these aggregates are known, mostly from DeWulf et al. (2007). The EmCFs for
aggregates are the sum of EmCFs for all n constituent minerals (Equation 24) and are given in
the Aggregate minerals worksheet in the EmCFdb.
n
£ agglomerate ~ I £k,c (24)
k=1
LCA items named 'Aggregate, natural' and 'Rock, unspecified' are assigned the minimum
EmCF from all other aggregate rock types to avoid unnecessary overestimation of their emergy.
7.5 Minerals in seawater
The oceans are the repository for many minerals eroded from the continents. Wind and runoff-
based erosion carries minerals to the oceans where they either settle to the bottom or stay
suspended as dissolved ions. These dissolved ions generally exist as salts and give seawater its
characteristic salinity. Dissolved ions may be taken up by biological processes, splashed into the
atmosphere to form aerosols, or precipitated out of the water column to join the bottom
sediments. Aerosol minerals precipitate out of the atmosphere, mostly on to the marine surface,
but some are transported through precipitation on to the continents where rivers again may
transport them to the seas. Ocean sediments may be stirred up through waves, tides, or ocean
current actions such as in upwelling zones. On longer time scales sediments may be subducted at
plate margins. Over Wilson cycle time scales ocean floor sediments are swallowed during
supercontinent formation. Subducted sediments mostly find their way back into continental crust
as sedimentary rocks because the seafloor spreads away from its interiors. As rivers erode the
25
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continents, the underlying crust is exposed to the surface hydrologic and sedimentary processes
once again through the sedimentary cycle.
We compute the EmCF of seawater ions e0 as the ratio of the GEB to the annual flux cp of
seawater minerals i (Equation 25).
GEB
£O ~ yn ~ (25)
Z.£=l Vi
In this way seawater ions are a co-product to all other global emergy flows. We further split the
GEB among each seawater ion (n = 48) for which residence times, and thus annual fluxes, could
be found (Equation 26).
GEB/n
£o,i = — (26)
-------
For this reason, atmospheric gases have never had EmCFs, except for water vapor. With no
previous method to refer to, we develop a first attempt at computing EmCFs for atmospheric
gases. To be consistent in algebra principles, this first attempt uses the same framework as that
used for crustal minerals, where atmospheric gases are treated as a co-product of the GEB and
the specific emergy of each gas is allocated as a function of its exergy.
The GEB drives atmospheric material exchange within the geobiosphere. The average specific
emergy of the atmosphere (eA) is the ratio of the GEB to annual mass flux of the atmosphere
(Equation 27), where t(- is the turnover time and m is total mass of gas i in the atmosphere.
GEB
Sa = yn tu (27)
Li=i /ruj
Average transformity f of an atmospheric gas, i, is the ratio of average atmospheric specific
emergy (2.0 E4 sej/g) to its chemical exergy j3ch from Szargut et al. (2005) (Equation 28).
(28)
Pch.i
Like in the mineral EmCF method, after specifying an above average concentration c, the
specific emergy e of each gas i is the product of the average atmospheric transformity and its
mixing exergy b (Equation 29). Mixing exergy is the difference in chemical exergy of a
molecule in its concentrated conditions relative to average conditions (Equation 29),
ffb f'-RTl"^ ,29,
£i,c
W W
where w is the gas molar mass (g/mol). Gases with below average concentrations have a
chemical EmCF of zero. The EmCFs of some atmospheric gases are given in the Atmospheric
Gases worksheet of the EmCFdb.
9.0 Land, Biomass and Soil EmCFs
9.1 Land Occupation
The classifications titled "land occupation" in the Ecoinvent and GABI databases are not
geographically specific, allowing allocation of a representative quantity of Earth emergy to a
particular analysis area. It has been suggested to characterize the land use impacts based on net
primary production loss as a proxy (Taelman et al., 2016). As a means of improving on former
practice, which used a global average areal empower intensity, 19 specific biome/ecosystem
types have been characterized based on the work of Lee (2019) and Lee and Brown (2019) and
included in the EmCFdb (Land, Biomass, & Soil worksheet of the EmCFdb). In this way the
land occupied classification has been expanded and now includes the 19 most common global
27
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terrestrial biome/ecosystem types. The driving emergy of each biome type was used to compute
aerial empower intensities (AEI), which is emergy per time per area expressed as sej m"2 yr"1.
Figure 7 is a generalized biome/ecosystem diagram. The AEI is used to compute the EmCF of
gross primary production (GPP), net primary production (NPP), biomass and soil carbon.
Land ErnCFs, while based on the concept of AEI, are computed slightly differently than in the
past. Here we reconsider how emergy algebra is used to characterize AEI. The fourth rule of
emergy algebra (Section 2.1 Emergy Algebra) states that co-generated outputs, when
recombined as inputs, cannot sum to more emergy than the input emergy from which they are
derived (Brown and Herendeen, 1996). While the GEB are all independent emergy flows,
secondary Earth emergy flows are co-products of the GEB.
Tripartite (GEB)
NPP = GPP - Respiration (R)
Figure 7 Generic ecosystem/biome showing the inputs of emergy driving gross primary production
(GPP) and net primary production (NPP) as the difference between GPP and respiration (R). The
storages of wood, biomass and soil carbon are all products of primary production. Note that we
compute separate EmCFs for biomass, wood and soil carbon because they are on very different
time scales.
AEI computation in past evaluations was customarily taken as the largest of the renewable input
emergy. That is, the max of emergy from sun, tide, geothermal, rain, wind, etc. regardless of
whether they were primary flows (the GEB), secondary, or tertiary flows (Odum, 1996).
Evaluations were done in this way to avoid double-counting input emergy because it was
reasoned that all renewable inputs were co-products of the geobiosphere tripartite. To some
extent this is true, but only for the secondary and tertiary renewable sources. The global
tripartite are separate sources and can be added, because emergy inflows of each one is
independent and their equivalencies are not transformations of each other, i.e., they are
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independent. Whereas the emergy of the global tripartite can be added, the emergy of their
"products" cannot, because each of them "embodies" a fraction of the tripartite baseline. For this
reason, we suggest a new computational procedure to assign emergy sources to landscape
systems. This new method sums the tripartite sources and compares this value with the largest of
the secondary and tertiary sources (Equation 30). Areal empower intensity of each
ecosystem/biome type is taken as the largest of these two flows.
AEI = max / (sun, tide, deep heat), secondary emergies, tertiary emergies (30)
Table 2 in the Land, Biomass and Soil worksheet of the EmCFdb lists the major Earth biomes,
their area, and their AEI.
It should be noted that the classifications of 'Occupation, unspecified area' and 'Occupation,
cultivated lands' use the world terrestrial average AEI of 1.14E11 sej m"2 yr"1 (Land, Biomass &
Soil worksheet).
9.2 Land Transformation/Volume Occupied
'Land transformation' and 'volume occupied' have been assigned zero emergy in the EmCFdb.
Instead, we suggest that if lands are transformed from natural forests, swamps, etc., the biomass
or soil organic carbon (see below) lost as a result of land clearing be accounted as elementary
flows. The same rational is applied to volume occupied.
9.3 NPP and Biomass
EmCFs for NPP and biomass are calculated by major biome using data compiled by Lee (2019).
Biomass EmCFs are based on biomass standing mass (in grams of carbon, or gC) and turnover
time which were compiled by Lee (2019) from various literature sources (Whittaker and Likens,
1975; Olson et al., 1985; Gibbs, 2006). Biomass EmCFs are calculated using Equation 31.
NPP EmCFs are calculated in a similar manner from data compiled by Lee (2019) from NASA's
Terra/MODISNPP product (MOD17A3) (Zhao et al., 2005) using Equation 32.
Emergy Input
(31)
biomass (g)
EmCFNPP(—) —
Emergy Input
(32)
g
NPP(gC)
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No EmCF was assigned to biomass from cultivated lands as this is a product of a human activity.
Analyses for land areas where the biome is unknown should use the world average terrestrial
AEI and biomass specific emergy (5.62 E14 sej/ha/yr and 5.18 E8 sej/gC, respectively; Tables 2
and 3, Land, Biomass & Soil worksheet of the EmCFdb). The average transformity and specific
emergy are weighted averages based on areas of terrestrial biomes.
9.4 Soil organic carbon
EmCFs are included for soil organic carbon by biome type (see Table 4 - Land, Biomass & Soil
worksheet of the EmCFdb). The AEI of a biome drives its NPP and soil carbon genesis. NPP and
soil carbon are co-products of biome areal empower, albeit with different time scales. Soil
carbon EmCFs utilize soil turnover time, storage quantity, and AEI for each biome following
Equation 33:
AEI x replacement time
ECFCora = (33)
y energy or mass of storage
While the organic carbon and biomass for cultivated lands are not considered elementary flows
because they are under the influence of anthropogenic inputs (i.e., fertilizer, labor, etc.), we have
included an EmCF for soil carbon in cultivated lands. For the time being, the AEI for cultivated
lands is estimated as the world terrestrial average AEI. Raich and Schlesinger (1992; table 3)
provide the average global quantity and residence time of soil C in cultivated lands. Its EmCF is
found in the same way as other soil C.
We have assigned an EmCF to "Soil, unspecified" by assuming it to be 5% organic carbon and
95% mineral soil (Lee and Brown, 2021). The emergy of the organic portion was taken as the
smallest of the biome soil carbon EmCFs (grassland) while the emergy of the mineral portion
was assumed to be that of shale rock (see discussion of Inorganic Matter below).
9.5 Soil minerals
There are three EmCFs for inorganic soil constituents; inorganic matter in soil, unspecified;
nitrogen (N) in soil; and sulfur (S8) in soil. Methods for their computation are given next.
9.5.1 Inorganic matter
Using the method of Odum (1996; pg. 47) inorganic soil material was assumed to be derived
from shale rock, where half the rock is lost during soil formation. Thus, the EmCF for inorganic
matter in soils is equal to the EmCF of shale multiplied by 2 (because half is lost during soil
formation).
9.5.2 Soil Nitrogen
Soil nitrogen is mostly controlled by biologically driven processes (Berner, 2006). The EmCF
for 'Nitrogen in ground' refers to both organic and inorganic soil N. Watanabe and Ortega
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(2011) used a static steady-state N cycle to compute a nitrogen UEV. We use their data to
compute the EmCF (Equation 34) as the ratio of the GEB to the terrestrial soil N flux mN =
(190 + 140 + 29.4) E9 kg/yr (the sum of organic and inorganic N; Figure 5 in Watanabe and
Ortega, 2011).
GEB
EmCFsoiiN = = 3.34£"13 sej/kg (34)
mN
9.5.3 Sulfur
Sulfur is not included in the minerals section because no ore grade could be found for mined
sulfur. It is predominately produced as a by-product of the refining process of other materials
(primarily oil and natural gas and secondarily as a by-product of ferrous and non-ferrous metal
smelting). Soil sulfur was, however, included as a soil resource. We use the mineral sulfur (S8)
and assume soil content of 0.5% to yield the soil sulfur EmCF (Lee and Brown, 2021). This
concentration and EmCF is easily changed in the EmCFdb should better data become available.
10.0 Wood
Wood EmCF is the ratio of AEI to annualized net wood production for various forested
ecosystems (see Wood worksheet of the EmCFdb). It should be noted that wood and biomass
have different EmCFs. Biomass EmCFs are derived from net community production, which is
greater than the net production of wood. The flows and storages in the database are elementary
flows, which means how nature does the work to produce them. This is not the same as the
timber production from modern timbe industry with added inputs. It should also be noted that
the evaluations for wood use different AEI values than biome biomass and soil carbon (Land,
Biomass and Soil worksheet of the EmCFdb) because the data for wood harvest is from specific
forests whose inputs may be different from aggregated global biomes.
Wood is the marketable lumber produced by forests of different types. Wood grown in
commercial forests would have non-renewable emergy inputs in addition to the wood elementary
flow added as part of the commercial operation. For wood to be an elementary flow we only
account for renewable emergy inputs. Wood EmCFs differ from biomass EmCFs in that
biomass EmCFs are used to account for the emergy of biomass lost in land clearing processes.
The EmCFdb contains several types of wood including wood from specific biomes:
Wood, dry, temperate forests
Wood, dry, boreal forest
Wood, dry, tropical lowland forest
Wood, dry, swamps
Wood, dry, unspecified
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Each of these wood types is assigned a different EmCF based on productivity of the forest
ecosystem from which it is harvested. Usually, rainfall is the defining emergy input to these
wood producing systems except for swamps, temperate forest, and wetland, in which organic
matter deposition, and run-in, characterize the AEI respectively. The "unspecified" classification
uses the minimum wood EmCF to minimize over-estimation.
In addition to the wood types above, the EmCF contains two general wood types:
Hardwood, dry, unspecified, and
Softwood, dry, unspecified
The unspecified hardwood uses the EmCF computed for hardwood harvested from southern
mixed hardwood forest in US, whereas the unspecified softwood uses the EmCF computed for
pine from a Florida Pine Flatwood.
11.0 Fossil fuels
Brown et al. (2011) applied novel concepts to the emergy calculation of coal, oil, and natural gas
such as:
Estimating the emergy of NPP in past geologic eras
Carbon preservation factors at major transformation stages in fossil fuel genesis, and
Geothermal heat absorbed to transform buried organic carbon into fossil fuels
Preservation factors are the proportion of carbon that survives each transformation step (i.e.,
peat formation, digenesis, etc.). Preservation factors are inherently uncertain because their time
scales are too long to directly observe.
Estimation of global NPP from past geologic eons based on oxygen isotope records is potentially
another major source of uncertainty for at least two reasons. First, the GEB of the past 500 Ma or
so was assumed to be equal to today's GEB. Second, the emergy driving terrestrial and marine
NPP was topologically split from the GEB according to the present-day ratio of land to sea
surface area.
Brown et al. (2011) implemented a Monte Carlo simulation to include the uncertainties of
preservation factors for what was essentially modeled as a two (coal) or three (natural gas and
petroleum) tiered transformation process from NPP to crude fossil fuel. Our following
explanations discuss modifications applied to their method but without the use of Monte Carlo
simulation. The resulting values are within 5% of the reported values which, when considering
the inherent uncertainty, seems not to necessitate further sensitivity analysis.
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11.1 Peat
Peat is partially decayed organic matter generally formed in wetlands where anoxic conditions slow
decomposition.
Figure 8 is a summary diagram of the formation of coal, where peat is the first step in the
process. The EmCF of Peat utilizes the EmCF of flooded grasslands and savannas soil C.
Assuming C composes 50% of peat's mass (Brown et al., 2011), and that the units of peat in
LCA databases are kg of peat, rather than only its carbon content, peat's EmCF is found as
follows (Equation 35).
7 30 F1 7
flooded qrasslands and savannas soil C EmCF ka
EmCF Peat = - - = —
50% C in Peat organic material n rn kgC (35)
kgPeat
= 4.61 £"12 sej/kg
Once buried deep enough, geothermal heat cooks peat into coal. The initial accumulation of
organic matter in ecosystems is a biological function driven by surface inputs, such as rain, wind,
and sunlight.
11.2 Coal
The pre-historic terrestrial NPP calculated in Brown et al. (2011) was used in the EmCFdb to
calculate fossil fuel EmCFs. Methods differ, however, in regard to geothermal contributions to
the coalification process.
As shown in
Figure 8, we divide the coal resource into two groups determined by carbon concentration. These
are anthracite/bituminous (A/B) and sub-bituminous/lignite (SB/L). Geothermal exergy at earth's
surface is a function of Carnot efficiency C where TR is reservoir temperature and Ts is source
temperature in Kelvin Equation 36.
Tr
C = l-£ (36)
ls
Coalification for A/B and SB/L occurs at Ts = 237.5 and 97.5 °C respectively (Brown et al.,
2011) and Earth's surface temperature is TR = 14.1 °C. The Carnot efficiency of deep earth heat
contributions are CA/B = 43.7% and CSB/L = 22.5%. These are 82% and 181% larger than what
is used in Brown et al. (2011). Deep heat exergy of coalification is the product of the Carnot
efficiency of coalification with the quantity of deep earth heat F and the mass fraction of organic
carbon at the temperature depth in the lithosphere mc (Equation 37).
Edh = CiFmc (37)
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We update the emergy of deep heat contribution to the coalification process using the deep heat
flow and deep heat SER from Brown et al., (2016), which is 9.52 E20 J/yr and 4,900 seJ/J,
respectively.
Phase I
Peat Production
Phase II
Coalification
Figure 8 The two phases of coal formation. Phase I: peat production is dominated by ecological
processes that are driven by solar, tidal, and geothermal energies of the geobiosphere. Phase II:
coalification is driven by geothermal energy. PF1-2 are preservation factors (fraction of carbon that
is preserved and passed to the next step): PFi is the preservation between organic matter
production and peat accumulation. Hard coal and soft coal have two different preservation factors
PF2a and PF2b between peat and coal.
We only consider the carbon portion of organic matter because that is where the principal
amount of chemical exergy is stored in the resulting fossil fuel. The mass fraction of carbon
receiving deep heat exergy in the lithosphere is the average of initial carbon rrij to final carbon
mF divided by the mass of the lithosphere mL = 2.17 £"25 g (Equation 38).
mj + mF ,
m 2 / (38)
mc — / mL
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In Brown et al. (2011) rrij is the total of carbon in buried organic matter. However, coalification
is the transition from peat to coal, not from organic matter to coal. We make rrij =
carbon in peat and mF = carbon in coal. We assume buried peat has the same density as the
surrounding lithosphere. Our mc = 1 E — 8 g/g crust, reduced from the 2 E — 1 g/g reported
in Brown et al. (2011).
In summary, two steps are performed to account for the emergy of coal, namely calculation of
the emergy of past NPP that is buried as peat, and calculation of the emergy required for
coalification of peat into coal. In this evaluation, the first step is identical to Brown et al. (2011)
whereas the latter has been recalculated to contribute between 0.04 and 0.08% to the EmCF of
coal, less than the former 13.7% contribution (calculated from data in their paper).
11.3 Oil and natural gas
Conventional reserves of crude oil are usually found in association with natural gas. Similar to
coal, the production process can be separated into two distinct phases (Figure 9). The first phase
is dominated by the biological production of organic matter, while geologic processes dominate
the second phase. Biological carbon sources for petroleum are produced in both terrestrial and
marine environments although marine sources dominate total production of reserves (80% vs
20%; Klemme and Ulmishek, 1991). An important distinction occurs during the Oligocene-
Miocene era when the production of natural gas is almost entirely from terrestrial sources.
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Figure 9 The two phases of petroleum formation. Phase I: organic matter production is dominated
by ecological processes driven by solar, tidal, and geothermal energies of the geobiosphere. Phase
II: petroleum production is driven by geothermal energy. PF1-3 are preservation factors (fraction of
carbon that is preserved and passed to the next step): PFiis the preservation between organic
matter production and organic matter accumulation in basins, PF2is the preservation between
accumulated organic matter and kerogen, and PF3 is the preservation between kerogen and
oil/natural gas. (Ki = kerogen type I; Kn = kerogen type II, Km = kerogen type III).
Brown et al. (2011) characterized the emergy of crude oil and natural gas (NG) and computed
UEVs by geologic age and then aggregated with a weighted average to represent a single EmCF
for global crude oil and another for NG, reporting the UEVs per unit carbon in the fuel (Ibid.).
Because approximately 85% of crude oil and natural gas is carbon, the EmCFs of crude oil and
NG in Table 2 of Oil & NG worksheet of the EmCFdb are multiplied by the reciprocal of this
percentage to reflect the emergy of a mass unit of the crude fuel.
11.4 Helium
Most helium on Earth is a result of radioactive decay, known as alpha decay, and is trapped in
the subsurface under conditions that also trap natural gas. Hence the greatest natural
concentrations of helium on the planet are found in natural gas, from which most commercial
helium is extracted. The concentration varies in a broad range from a few ppm up to about 7%.
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For most uses, helium is extracted by fractional distillation from natural gas, and as such is not
an elementary flow but the product of an industrial extraction processes. Until we have a better
way of computing the emergy of helium (the result of natural radioactive decay of thorium and
uranium) we have assigned helium the EmCF of natural gas.
12.0 Discussion/Future Research
12.1 Global emergy baseline
The planet's sources of exergy (sunlight, gravitational attraction, and deep earth heat) are not
constant on geologic timescales (Campbell, 2016). The sun's luminosity increases about 6% per
Ga. The Earth grows farther from Moon and Sun as tidal drag transfers Earth's angular
momentum to orbital geopotential. Earth heat, both isotopic decay and relict heat, diminish
through time. It may be desirable to consider the evolution of the GEB over geologic time, the
implications of which would only apply to the crustal minerals and fossil fuels. Other items in
the EmCFdb are too young to be affected by a dynamic GEB. GEB is mostly based on long-
term average or steady state data. However, the ever-increasing impacts of climate change on
global cycles post higher uncertainties which are trickled down in the elementary flows.
12.2 Renewable vs. Non-renewable
EmCFs in the EmCFdb are classified as either renewable or non-renewable; the slowly
renewable classification has been removed. The differentiation between the renewable and non-
renewable is based on turnover time. We have set the cut-off between renewable and non-
renewable at a turnover time to be 100 years which is set as a first approximation. For most
EmCFs this does not present an issue. However, several flows classified as non-renewable may
be considered renewable if they are "harvested" at renewable rates. For instance, 'water, fresh,
ground' has a very long turnover (1400 years) yet many groundwater sources have much shorter
turnover times and, in some instances, use rate may be considered slow enough that the resource
would be renewable. We mention this point only as a precaution, because under most
circumstances current use rates of all slowly renewable resources are fast enough to warrant
classification as non-renewable.
In emergy accounting, which renewable flows (as well as non-renewable flows) should be
chosen is often determined by the purpose of the research. For example, transformity of wave on
the ocean surface (for wave energy harvesting), wave energy on the shore (for mangrove or coral
reef research), or wave energy in the oceans as a whole (for global studies). Caution should be
taken to ensure proper transformity is used for the intended study.
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12.3 Biological EmCFs
Soil carbon and biome NPP have EmCFs computed from the same spatial boundaries, with
partially overlapping temporal boundaries. This constitutes a definite co-production of at least
some part of the EmCFs for both. LCA software does not have the ability to apply emergy
algebra, pertinent to combining co-products. As such, future improvement to the EmCFdb should
provide EmCFs that can be added without concern for double-counting. The solution may be in
dynamic EmCF calculations, currently being explored. For now, both NPP and soil carbon
EmCFs come from static (tabular) calculations.
Soil organic matter currently does not have an EmCF, but rather is approximated by the EmCF
of soil carbon. Other components of organic material (i.e., Nitrogen, Potassium, Phosphorous,
humus, etc.) should be included to represent the true value of soil fertility. Emergy analyses of
these nutrient cycles are available only as a global static evaluation (Campbell et al., 2014),
which assumes the GEB is embodied on every pathway and in every storage. In essence all
nutrient compartments and flows computed in this static evaluation are co-products and should
not be added. Development of a dynamic and all-inclusive EmCF calculation is a current topic of
research.
12.4 Land occupation EmCFs
Land occupation EmCFs were developed using the areal empower intensities (AEIs) of 17
biome/ecosystems. However, higher resolution EmCFs could be computed by an LCA analyst
for individual enterprises using the approach developed by Lee and Brown (2019) and the
renewable earth EmCFs of the Renewable Earth emergy flows worksheet of the EmCFdb as
inputs to a defined land area in LCA software. Essentially, users can create and input their own
case study sites for which they performed an emergy analysis. Or they can perform the emergy
evaluation outside the LCA framework and input the resulting AEI to a defined land occupation
in the LCA framework. Whichever method is employed it is important not to double-count
emergy.
12.5 Minerals
A crustal genesis of 2.5 gallium is much longer, and more dispersed, than the pulsed production
of some sediment (e.g., colemanite, borates, etc.). Future research aims to include the faster
production of these sediments in a planetary web matrix evaluation.
Precipitate minerals (e.g., trona, halite, etc.) precipitate from drying saline lakes. Many such
minerals still lack EmCFs. Where ore grade information could be found, these minerals would
have EmCFs calculated as if they were part of the crustal cycle. Future research will characterize
the emergy of precipitates according to more localized evaluations.
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Indium, gallium, and rhenium EmCF calculations assume them to be diadochic within a
Sphalerite (ZnS), bauxite, and molybdenite molecule respectively. The EmCFs for these
elements tend to be very high because of their miniscule mass fractions in their parent minerals.
Few minerals have best-guess ore grade concentrations (e.g., uranium). The remaining have
references.
12.6 Atmospheric gases
The annual mass flux of atmosphere is dominated by water vapor (Schneider et al., 2010). By far
the second most fluxed gas is O2. Thus, the average specific emergy of the atmosphere is
approximately that of water vapor. Also, like water vapor, the specific emergy of a unit of gas is
scaled according to its mixing exergy. The rising of global temperature and the intensified
hydrological cycle may present a different mixture and the associated exergy. The dynamic
impacts of climate change to the elementary flows and cascading effects deserve further
comprehensive research.
Uncommon atmospheric gases such as fluorocarbons are generally the product of human
systems, not the natural geo-biosphere. Thus, they are not elementary flows and their emergy
value should be calculated based on the emergy supporting their production process.
12.7 Accounting procedures for land occupation, standing biomass, and lumber
harvest
Land occupation refers to the fact that an enterprise occupies a given portion of land. In land
occupation, emergy is accounted differently depending on the enterprise. Three general types of
enterprise are possible; the first occupies the land, uses the renewable inputs (computed as the
land's AEI), and produces something (i.e., agriculture, commercial forestry). The second is
occupation by an enterprise for a short period of time to harvest standing resources such as virgin
forest wood. The third occupies the land but does not use the renewable inputs directly for its
outputs (industry, buildings, parking lot, etc). In the first case where the enterprise produces
something that incorporates the renewable inputs on a continuing basis, the renewable AEI of the
land is assigned to the product. In the special case where we have computed an EmCF for a
product, such as softwood harvested from a continuing silviculture operation ('softwood, dry,
unspecified') the wood that is harvested on a continuing basis can either be assigned the emergy
of the renewable elementary inputs (the AEI) to the land, if known, or the emergy of the
softwood; but not both. To account for both the AEI and the emergy of the wood would be
double counting.
In the second case where a short-term occupation results in harvesting a resource, the emergy of
the resource is counted, but not the land's renewable AEI.
In the third case, where the enterprise occupies land on a continuing basis but does not utilize the
renewable emergy inputs for its products, the AEI of the land is still assigned to the product. To
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do otherwise would disagree with the general principle that regardless of what is "seen" as being
incorporated in an economic use, the fact that the renewable emergy is inflowing to the process,
it is being incorporated. We have given this considerable thought and debate within the research
group and are reminded that emergy accounting algebra should be consistent at all scales. So,
when accounting for the renewable input to a country, for instance, it is customary to include all
the renewable input, regardless of if it falls on areas not occupied by human enterprise. Thus,
countries like Canada and Australia, have very large renewable inputs because of the large
"uninhabited areas" in each country.
For land occupation that results in the clearing of biomass, the emergy of biomass that had
accumulated before the land was occupied (i.e., using the Biomass UEVs on the EmCF Library
worksheet) should be accounted as a onetime input to the subsequent land occupation. Biomass
EmCFs refer to all biomass (i.e., roots, shoots, leaves, stems, trunks, etc.), which differ from
wood EmCFs. Wood EmCFs consider only the quantity of wood, as lumber, produced and are
meant to represent elementary inputs.
12.8 Accounting procedures for water
Water has several values, each of which humans exploit at different times and for different
purposes. Often, after use, water is returned to the environment with altered quantity and quality,
which may affect downstream systems. Accounting for the emergy of inputs and outputs of
water to and from enterprises needs to be treated consistently within the LCA framework and is
not simple.
Water is often used as a sink for thermal energy because water has the highest specific heat
capacity of any liquid, or as a carrier of by-products from enterprises (Boundless, 2023). The
emergy of water's purity (chemical potential relative to sea water) is used by ecosystems and
economic enterprises alike. The constituents carried by water are sometimes used, such as when
nutrient laden water is discharged to ecosystems; or when toxins carried by water have
detrimental effects downstream. Finally, the gravitational potential of elevated water is used as a
power source in technological applications like the generation of electricity. Accounting
procedures for each of these uses need be addressed carefully and systematically.
12.8.1 Water's thermal capacity
Because cooling water is an input to a process that uses the water's specific heat capacity,
density, and thermal conductivity, rather than its chemical exergy, we must account for its
"thermal service" rather than its chemical service. The main mechanism for water cooling is
convective heat transfer (Boundless, 2023). Cooling water may be recycled through a
recirculating system or used in a single pass once-through cooling (OTC) system. If
recirculating systems are open, then they may have evaporative losses. OTC systems generally
return most of the water at temperatures significantly above the ambient receiving water body.
Water that is not returned might be considered water that is consumed.
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Both the input and output of cooling water need be considered within the LCA framework.
Unless cooling water is used up (i.e., evaporated) it should not be counted as an input. For
example, in a nuclear power plant, make-up water, i.e., which replaced evaporated losses, is
counted. Also blow-down water, water mixed with acids to clean the plant structure, should be
accounted for by using its chemical potential energy EmCF. The emergy of these waters should
be assigned to the product of the process being evaluated, in this case nuclear power. Saltwater
used for cooling would have no chemical potential energy and therefore evaporative losses
would not be counted.
Water that is returned to a water body at higher temperature provides a heat gradient to the
receiving environment. This heat gradient represents an available energy source that can drive
geo-biologic work and post potential environmental impacts.
To compute the emergy of the water, rather than assigning the emergy of the thermal process, we
suggest computing an EmCF based on the method proposed by Odum (1996, pp32-33) that used
an average transformity for heat derived mechanical work, adjusted by Carnot efficiency.
Updating this method to the current GEB yields a new equation where C is the Carnot efficiency
of the hot water and receiving water body (see Equation 39) and 0.7 is the efficiency of 1000°C
power plant relative to average environmental temperature.
Thus, hot water with a temperature of 297.25 K that is discharged to a river having a temperature
of 287.25 K would have an EmCF of 1200 as follows (Equation 40):
12.8.2 Water's chemical potential
In the past, water's available potential energy was computed using its purity relative to seawater
where purity was measured by total dissolved solids (TDS). This method stems from the fact that
living organisms require freshwater to drive cellular osmotic differences for transfer of wastes
from cells. For processes that utilize the available energy in water's chemical potential, the
emergy of the input water is computed using the methods outlined in Section 6. The total net
volume of water used is multiplied by its EmCF and its emergy assigned to a process's output.
Water that is discharged from a process as a by-product may have different TDS from the input
water and thus its transformity may be different. For instance, output water that has lower TDS
may have a higher transformity or vice versa, and higher TDS would result in a lower
transformity. We do not suggest that the other emergy inputs to a process be added to the output
water, unless of course, the output water is the main product of the process.
EmCFi
7h0t water = C(42,000se///) / 0.7
(39)
EmCF = 0.034(42000 sej/J)/0.7 = 1200 sej/J
(40)
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However, water carries other constituents that may be important sources to biological and
technological processes alike. The use of TDS as the indicator for chemical purity may not
capture these other constituents. Common sense need prevail. If an input or output water
contains high levels of some chemical or element, then the emergy of that chemical or element
should be computed using the chemical EmCF methods outlined in Section 7. If the computed
emergy is larger than the chemical potential of the water, it should be used instead of the emergy
of the chemical potential determined using the TDS because mineral emergy is a global co-
product of water emergy.
An emergy signature of water that carries several constituents such as carbon, nitrogen,
phosphorus, pesticide, etc., can be constructed to illustrate the emergy of the various
constituents. However, adding them together to obtain a total emergy of the water should not be
done if those constituents originated from the same place in space and time. They may be added
together if the constituents are independent of each other (i.e., they were not added to the water
as part of the same process). For instance, runoff water from a watershed may have several
constituents whose emergy may be evaluated separately to better visualize the potentials of each
constituent, but they should not be added together because they result from the same watershed's
runoff process. On the other hand, water that has been used in an industrial process may receive
inputs of chemicals manufactured in a different place in both space and time than the
constituents that originated in the watershed. In this case, the emergy of the separate constituents
could be added.
12.8.3 Water's geo-potential
The emergy of the available geo-potential energy in water is related to the height difference
between the inlet and outlet of the process. Thus, computing the emergy of water input to a
hydroelectric dam is the volume of water multiplied by the geo-potential of the height difference
between inlet and outlet times the EmCF of global water geo-potential. Assuming there is no
change in quality or quantity there is no need to compute the emergy of the water outflow from
the dam. Not captured by this analysis is the potential alteration of the pulsing regime of a river
due to the dam, nor the potential change in temperature (colder) of the discharge water taken
from deep reservoirs. For this, calculating the emergy of the chemical change and temperature
change, and comparing with the geo-potential change may be considered. The only the largest
emergy value of these three exergy descriptors is accounted, as they are all global co-products.
13.0 Conclusions
This report and the associated EmCFdb provides equations, data, and rational, for the emergy
characterization of several kinds of elementary flows for inclusion in LCA. EmCFdb also
provides consistent elementary flows for emergy accounting. Primarily resources are
considered, as the emergy method is most developed in accounting for inputs rather than outputs
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or emissions. These resources span natural energies (e.g., wind), land area occupation (e.g.,
biomes), biologic stocks (e.g., soil carbon, biomass, lumber) for several biome varieties, various
kinds of freshwater on a global average basis, many crustal minerals and rocks, some soil
properties (e.g., nitrogen), major air constituents, and fossil fuels. These efforts build on several
prior studies which greatly assisted the aggregation of such information into a common
framework (e.g., Rugani et al., 2011; Sweeney et al., 2006; the emergy Folios, etc.). The library
is expected to be useful for quantifying environmental support in LCA studies. The report and
the associated EmCFdb are also living documents and database as new data, calculations and
methods become available and incorporate into the newer versions.
Among these elementary EmCFs are a few novel calculations. These include updated natural
renewable energies, areal empower of biomes (which effects all biological EmCFs), mineral
EmCFs with varying concentration, and fossil fuel EmCFs. The details of these calculations are
available in the accompanying Excel workbook with the filename EmCF database for LCA.
14.0 Quality Assurance
The EmCF database and this report were prepared under the ORD Quality Assurance Project
Plans: S-17059-QP-1-1 for "Emergy Research Support for Supply Chains", G-STD-0030219-
QP-1-0 and K-WID-0030219 for "Secondary Data Analysis Emergy Research Support for Task
lb", G-WSD-0031214-QP-1-0 for "Resource Recovery from Municipal Wastewater", G-WSD-
0032048-QP-1-0 for "The Development of Smart Water Management Evaluation Database and
Emergy Accounting for the "City of Tomorrow" Analysis", K-WID-0018946 for "Emergy
Research Support".
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50
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Table A-l Summary of EmCFs for LCA Elementary Flows
Flow
Type
Units
sej/unit
Renewable Earth Emergy Flows
Solar energy
Raw renewables
MJ
1.00E+06
Geothermal energy (deep heat)
Raw renewables
MJ
4.90E+09
Tide
Raw renewables
MJ
3.09E+10
Wind energy
Raw renewables
MJ
5.20E+08
Wave energy in the oceans as a whole
Raw renewables
MJ
5.20E+08
Wave energy on the shore
Raw renewables
MJ
7.24E+10
Rain (chemical potential)
Raw renewables
MJ
2.25E+10
Runoff geopotential energy
Raw renewables
MJ
4.12E+10
Ocean Currents
Raw renewables
MJ
5.80E+10
Water
Water, fresh, unspecified; ppmTDS
water
m3
1.28E+12
Water, rivers and streams; ppmTDS
water
m3
3.26E+11
Water, fresh, lake; ppmTDS
water
m3
2.24E+12
Water, fresh, wetland; ppmTDS
water
m3
5.22E+12
Water, fresh, surface; ppmTDS
water
m3
1.28E+12
Water, fresh, ground; ppmTDS
water
m3
1.46E+12
Water, fresh, polar ice; ppmTDS
water
m3
4.83E+12
Water, terrestrial rain; ppmTDS
water
m3
1.06E+11
Water, atmospheric vapor; ppmTDS
water
m3
1.95E+10
Water, runoff geopotential
water
MJ
4.12E+10
Minerals
Aluminum, element mass ratio in Bauxite minerals; {11154517413.4696}; g/g in
ground
minerals and metals
g
1.12E+10
Anhydrite; {8106152969.06314}; g/g in ground
minerals and metals
g
8.11E+09
Antimony; {8089969016.13499}; g/g in ground
minerals and metals
g
8.09E+09
Barite; {3141371127.91076}; g/g in ground
minerals and metals
g
3.14E+09
-------
Bauxite; {11154517413.4696}; g/g in ground
minerals and metals
g
1.12E+10
Borax (Kernite); {6607106595.78549}; g/g in ground
minerals and metals
g
6.61E+09
Cadmium in Greenockite; {12064152593.9228}; g/g in ground
minerals and metals
g
1.21E+10
Cerium; {4536488375.32133}; g/g in ground
minerals and metals
g
4.54E+09
Chromium in Chromite; {9394621509.27478}; g/g in ground
minerals and metals
g
9.39E+09
Sodalite, Chrysotile; {1855023786.62126}; g/g in ground
minerals and metals
g
1.86E+09
Cinnabar; {8241006041.0332}; g/g in ground
minerals and metals
g
8.24E+09
Cobalt; {10390040589.3785}; g/g in ground
minerals and metals
g
1.04E+10
Colemanite; {3320337587.04997}; g/g in ground
minerals and metals
g
3.32E+09
Copper in Chalcopyrite; {13069354716.7953}; g/g in ground
minerals and metals
g
1.31E+10
Copper in Chalcopyrite; {13447698596.6545}; g/g in ground
minerals and metals
g
1.34E+10
Copper in Chalcopyrite; {13846682428.9523}; g/g in ground
minerals and metals
g
1.38E+10
Copper in Chalcopyrite; {14780329117.6962}; g/g in ground
minerals and metals
g
1.48E+10
Diatomite
rock and aggregate
g
Europium; {8258230731.38924}; g/g in ground
minerals and metals
g
8.26E+09
Feldspar; {1598328951.8236}; g/g in ground
minerals and metals
g
1.60E+09
Flourine; {37735915249.4802}; g/g in ground
minerals and metals
g
3.77E+10
Flourine; {44302647816.3473}; g/g in ground
minerals and metals
g
4.43E+10
Fluorspar/Fluorite; {19841711822.2734}; g/g in ground
minerals and metals
g
1.98E+10
Gadolinium; {9918725756.3501}; g/g in ground
minerals and metals
g
9.92E+09
Gallium; {7967512438192.56}; g/g in ground
minerals and metals
g
7.97E+12
Gold; {4700264177.80869}; g/g in ground
minerals and metals
g
4.70E+09
Gold; {4816407585.21258}; g/g in ground
minerals and metals
g
4.82E+09
Gold; {4867930733.65328}; g/g in ground
minerals and metals
g
4.87E+09
Gold; {5149828056.51144}; g/g in ground
minerals and metals
g
5.15E+09
Gold; {5648094158.16104}; g/g in ground
minerals and metals
g
5.65E+09
Gold; {4138047840.01968}; g/g in ground
minerals and metals
g
4.14E+09
Gold; {5956429812.69685}; g/g in ground
minerals and metals
g
5.96E+09
Gold; {5996745125.56752}; g/g in ground
minerals and metals
g
6.00E+09
Gold; {6213682983.82381}; g/g in ground
minerals and metals
g
6.21E+09
Gypsum; {1317975555.53474}; g/g in ground
minerals and metals
g
1.32E+09
-------
Indium; {13538306380011.9}; g/g in ground
minerals and metals
g
1.35E+13
Iron, element mass ratio in Taconite minerals; {2971505078.21115}; g/g in ground
minerals and metals
g
2.97E+09
Kaolinite; {1780555283.21744}; g/g in ground
minerals and metals
g
1.78E+09
Kieserite; {10871827429.0439}; g/g in ground
minerals and metals
g
1.09E+10
Lanthanum; {3613580204.43372}; g/g in ground
minerals and metals
g
3.61E+09
Lead; {5653757622.01115}; g/g in ground
minerals and metals
g
5.65E+09
Lithium; {91802594457.6113}; g/g in ground
minerals and metals
g
9.18E+10
Magnesite; {16076069613.2529}; g/g in ground
minerals and metals
g
1.61E+10
Manganese; {10861965153.3119}; g/g in ground
minerals and metals
g
1.09E+10
Molybdenum; {6162171539.22386}; g/g in ground
minerals and metals
g
6.16E+09
Molybdenum; {6162171539.22386}; g/g in ground
minerals and metals
g
6.16E+09
Molybdenum; {6162171539.22386}; g/g in ground
minerals and metals
g
6.16E+09
Molybdenum; {6162171539.22386}; g/g in ground
minerals and metals
g
6.16E+09
Molybdenum; {8459441651.19405}; g/g in ground
minerals and metals
g
8.46E+09
Nickel; {3251652514.27375}; g/g in ground
minerals and metals
g
3.25E+09
Nickel; {10410349468.3075}; g/g in ground
minerals and metals
g
1.04E+10
Olivine; {7391005661.33716}; g/g in ground
minerals and metals
g
7.39E+09
Palladium; {44174239569.9182}; g/g in ground
minerals and metals
g
4.42E+10
Palladium; {49727797426.6012}; g/g in ground
minerals and metals
g
4.97E+10
Phosphorous in Apatite; {10904197381.1782}; g/g in ground
minerals and metals
g
1.09E+10
Phosphorous in Apatite; {9284926368.37059}; g/g in ground
minerals and metals
g
9.28E+09
Platinum; {29392037460.0736}; g/g in ground
minerals and metals
g
2.94E+10
Platinum; {31284616834.929}; g/g in ground
minerals and metals
g
3.13E+10
Rhenium; {26529241518500.6}; g/g in ground
minerals and metals
g
2.65E+13
Rhodium; {5448880475379370}; g/g in ground
minerals and metals
g
5.45E+15
Rhodium; {4540733729482810}; g/g in ground
minerals and metals
g
4.54E+15
Silver; {3886196578.51713}; g/g in ground
minerals and metals
g
3.89E+09
Silver; {2277868851.45669}; g/g in ground
minerals and metals
g
2.28E+09
Silver; {5850753719.55117}; g/g in ground
minerals and metals
g
5.85E+09
Silver; {9653872313.92939}; g/g in ground
minerals and metals
g
9.65E+09
Silver; {3923042474.79215}; g/g in ground
minerals and metals
g
3.92E+09
-------
Silver; {7793346702.14797}; g/g in ground
minerals and metals
g
7.79E+09
Nitratine, Sodium nitrate; {1385029982.75347}; g/g in ground
minerals and metals
g
1.39E+09
Sodium sulphate; {1659826089.45453}; g/g in ground
minerals and metals
g
1.66E+09
Stibnite; {5800507784.56879}; g/g in ground
minerals and metals
g
5.80E+09
Sylvite, Potassium chloride; {20454345149.1348}; g/g in ground
minerals and metals
g
2.05E+10
Talc; {2609164348.88319}; g/g in ground
minerals and metals
g
2.61E+09
Tantalum; {1009316836.69473}; g/g in ground
minerals and metals
g
1.01E+09
Tellurium; {9487199561.82625}; g/g in ground
minerals and metals
g
9.49E+09
Tin, element mass ratio in Cassiterite; {1354225.64406906}; g/g in ground
minerals and metals
g
1.35E+06
Ti02; {5521393395.0084}; g/g in ground
minerals and metals
g
5.52E+09
Ti02; {4607243856.26256}; g/g in ground
minerals and metals
g
4.61E+09
Ulexite; {3479934132.57111}; g/g in ground
minerals and metals
g
3.48E+09
Uranium, weighted element mass ratio; {4363229331.72704}; g g/g in ground
g
4.36E+09
Verminculite; {1121696152.01091}; g/g in ground
minerals and metals
g
1.12E+09
Zinc; {13985065720.4718}, g/g in ground
minerals and metals
g
1.40E+10
Baddeleyite, Zirconia; {14103675060.1262}; g/g in ground
minerals and metals
g
1.41E+10
Aggregates
Aggregate, natural
rock and aggregate
g
1.62E+09
Basalt
rock and aggregate
g
3.30E+09
Calcite (Limestone)
rock and aggregate
g
5.93E+09
Clay, bentonite
rock and aggregate
g
2.04E+09
Clay, unspecified
rock and aggregate
g
2.04E+09
Dolomite; {5926382251.16802}; in ground
rock and aggregate
g
5.93E+09
Granite
rock and aggregate
g
1.62E+09
Gravel
rock and aggregate
g
1.62E+09
Perlite
rock and aggregate
g
1.65E+09
Pumice
rock and aggregate
g
1.62E+09
Rock, unspecified
rock and aggregate
g
1.62E+09
Sand, quartz
rock and aggregate
g
3.24E+09
Sand, unspecified
rock and aggregate
g
3.24E+09
-------
Shale
rock and aggregate
g
1.63E+09
Ocean Ions
Sodium chloride; {860115312.840238}; g/g in water
minerals and metals
g
8.60E+08
Bromine; {335606441448.866}; g/g in water
minerals and metals
g
3.36E+11
Calcium chloride; {688402240.085752}; g/g in water
minerals and metals
g
6.88E+08
Iodine; {3352284917399.7}; g/g in water
minerals and metals
g
3.35E+12
Magnesium; {1866432551.66494}; g/g in ground
minerals and metals
g
1.87E+09
Atmospheric Gases
Air; {20359.4161501681}; g/g in air
air
g
2.04E+04
Carbon dioxide; {14202.5635391691}; g/g in air
air
g
1.42E+04
Methane; {88626.4796174336}; g/g in air
air
g
8.86E+04
Krypton; {10049.1766253686}; g/g in air
air
g
1.00E+04
Nitrogen; {}; g/g in air
air
g
Oxygen; {4651.95185333505}; g/g in air
air
g
4.65E+03
Xenon; {17560.873018566}; g/g in air
air
g
1.76E+04
Land
Occupation, Tropical & Subtropical Moist Broadleaf Forests
land
m2*a
2.29E+11
Occupation, Tropical & Subtropical Dry Broadleaf Forest
land
m2*a
1.33E+11
Occupation, Tropical & Subtropical Coniferous Forest
land
m2*a
1.24E+11
Occupation, Temperate Broadleaf & Mixed Forests
land
m2*a
9.80E+10
Occupation, Temperate Conifer Forests
land
m2*a
9.49E+10
Occupation, Boreal Forests/Taiga
land
m2*a
5.76E+10
Occupation, Tropical & Subtropical Grasslands, Savannas & Shrublands
land
m2*a
1.04E+11
Occupation, Temperate Grasslands, Savannas & Shrublands
land
m2*a
5.12E+10
Occupation, Flooded Grasslands & Savannas
land
m2*a
8.77E+10
Occupation, Montane Grasslands & Shrublands
land
m2*a
5.25E+10
Occupation, Tundra
land
m2*a
6.34E+10
Occupation, Mediterranean Forests, Woodlands & Scrub
land
m2*a
5.40E+10
Occupation, Deserts & Xeric Shrublands
land
m2*a
3.26E+10
-------
Occupation, Mangroves
land
m2*a
2.90E+11
Occupation, River
land
m2*a
1.16E+12
Occupation, Lake
land
m2*a
6.61E+10
Occupation, Rock and Ice
land
m2*a
8.81E+10
Occupation, Estuary
land
m2*a
3.80E+13
Occupation, Terrestrial Average
land
m2*a
1.14E+11
Occupation, Cultivated Land
land
m2*a
1.14E+11
Occupation, Unspecified Area
land
m2*a
1.14E+11
Biomass
Biomass, Tropical & Subtropical Moist Broadleaf Forests
gC
9.76E+08
Biomass, Tropical & Subtropical Dry Broadleaf Forest
gC
8.24E+08
Biomass, Tropical & Subtropical Coniferous Forest
gC
8.76E+08
Biomass, Temperate Broadleaf & Mixed Forests
gC
6.55E+08
Biomass, Temperate Conifer Forests
gC
8.80E+08
Biomass, Boreal Forests/Taiga
gC
8.31E+08
Biomass, Tropical & Subtropical Grasslands, Savannas & Shrublands
gC
1.27E+09
Biomass, Temperate Grasslands, Savannas & Shrublands
gC
1.04E+09
Biomass, Flooded Grasslands & Savannas
gC
1.13E+09
Biomass, Montane Grasslands & Shrublands
gC
2.57E+09
Biomass, Tundra
gC
3.64E+09
Biomass, Mediterranean Forests, Woodlands & Scrub
gC
8.03E+08
Biomass, Deserts & Xeric Shrublands
gC
4.99E+09
Biomass, Mangroves
gC
2.16E+09
Biomass, River
gC
6.94E+10
Biomass, Lake
gC
3.97E+09
Biomass, Rock and Ice
gC
1.21E+11
Biomass, Estuary
gC
1.76E+11
Biomass, Terrestrial Average
gC
1.01E+09
-------
Soil
Soil Carbon, Tropical & Subtropical Moist Broadleaf Forests
biological
gC
7.41E+08
Soil Carbon, Tropical & Subtropical Dry Broadleaf Forest
biological
gC
4.63E+08
Soil Carbon, Tropical & Subtropical Coniferous Forest
biological
gC
3.62E+08
Soil Carbon, Temperate Broadleaf & Mixed Forests
biological
gC
2.19E+08
Soil Carbon, Temperate Conifer Forests
biological
gC
2.03E+08
Soil Carbon, Boreal Forests/Taiga
biological
gC
2.22E+08
Soil Carbon, Tropical & Subtropical Grasslands, Savannas & Shrublands
biological
gC
1.23E+08
Soil Carbon, Temperate Grasslands, Savannas & Shrublands
biological
gC
2.77E+08
Soil Carbon, Flooded Grasslands & Savannas
biological
gC
3.61E+09
Soil Carbon, Montane Grasslands & Shrublands
biological
gC
3.21E+08
Soil Carbon, Tundra
biological
gC
2.38E+09
Soil Carbon, Mediterranean Forests, Woodlands & Scrub
biological
gC
7.92E+07
Soil Carbon, Deserts & Xeric Shrublands
biological
gC
2.15E+08
Soil Carbon, Mangroves
biological
gC
7.58E+09
Soil Carbon, Terrestrial Average
biological
gC
5.69E+08
Soil Carbon, Cultivated Land
biological
gC
1.09E+08
Soil, Unspecified
biological
kg
3.10E+12
Nitrogen {N}, in soil
minerals and metals
kg
3.34E+13
Inorganic matter, in soil, unspecified
biological
kg
3.25E+12
Sulfur; {4947462077382.01}; g/g in soil
minerals and metals
kg
4.95E+12
Wood
Hardwood, dry, unspecified
biological
kg
3.99E+10
Softwood, dry, unspecified
biological
kg
3.16E+10
Wood, dry, unspecified
biological
kg
3.16E+10
Wood, dry, temperate forests
biological
kg
5.44E+11
Wood, dry, boreal forest
biological
kg
2.35E+11
Wood, dry, tropical lowland forest
biological
kg
4.65E+12
Wood, dry, swamps
biological
kg
1.77E+12
-------
Fossil Fuels
Peat
fossil fuel precursor
kg
7.22E+12
Coal, anthracite
fossil fuel
MJ
3.89E+10
Coal, bituminous
fossil fuel
MJ
3.89E+10
Coal, sub-bituminous
fossil fuel
MJ
3.23E+10
Coal, lignite
fossil fuel
MJ
3.23E+10
Gas, natural
fossil fuel
Nm3
5.36E+12
Oil, crude
fossil fuel
m3
5.09E+15
Helium; {7464230827230.45}; g/g in natural gas
minerals and metals
kg
7.46E+12
Radionuclides
Potassium
minerals and metals
MJ
8.20E+09
Thorium
minerals and metals
MJ
4.20E+09
Uranium 235
minerals and metals
MJ
3.90E+09
Uranium 238
minerals and metals
MJ
3.70E+09
-------
vvEPA
United States
Environmental Protection
Agency
PRESORTED STANDARD
POSTAGE & FEES PAID
EPA
PERMIT NO. G-35
Office of Research and Development (8101R)
Washington, DC 20460
Official Business
Penalty for Private Use
$300
Recycled/Recyclable Printed on paper that contains a minimum of
50% postconsumer fiber content processed chlorine free
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