goessling2013_thermodynamicsandresourceconsumption

7/23/2019 Goessling2013_ThermodynamicsAndResourceConsumption

http://slidepdf.com/reader/full/goessling2013thermodynamicsandresourceconsumption 1/23

65Thermodynamics and ResourceConsumption: Concepts, Methodologies,and the Case of Copper

Stefan Goßling-Reisemann

Abstract

Analysis and minimization of resource consumption is an essential aspect of

sustainability. Engineers in this field need to be equipped with concepts and

methodologies for assessment and sustainable design of products and processes.

Thermodynamics offers these concepts and methodologies. In the current debate

on material flows, the throughput of matter and energy is the primary focus.

Consumption, however, starts when material and energy is transformed and

loses its potential to be useful in further products or processes. On the physical

level, this loss of potential utility is well described by entropy production or

exergy destruction, two related concepts from thermodynamics. Using these

concepts, methodologies for analyzing resource consumption were constructedand have been successfully applied to a large number of processes, products,

and services. Here, a very brief introduction to thermodynamics is given to

enable the interested reader to understand the underlying concepts and help in

the application of thermodynamics to analyze resource consumption. Established

measures for resource consumption can be grouped into those approaches which

are based on the first law of thermodynamics (the conservation of energy

and matter) and those approaches which are based on the second law of

thermodynamics (entropy production and the devaluation of energy and matter).

A brief summary of the currently used approaches is given and how they

relate to the thermodynamic interpretation of resource consumption. Exergy and

entropy analysis are introduced as analytical tools and also briefly explained,

with recommendations for further self-study to get more familiar with the

methodologies. An example, copper making from sulfidic ore concentrates is

presented as a case study for the application of entropy analysis, and the results

S. Goßling-Reisemann

Faculty of Production Engineering, Division of Technological Design and Development, artec jResearch Center for Sustainability Studies, University of Bremen, Bremen, Germany

e-mail: [email protected]

J. Kauffman, K.-M. Lee (eds.), Handbook of Sustainable Engineering,

DOI 10.1007/978-1-4020-8939-8 54,

© Springer Science+Business Media Dordrecht 2013

1263



1264 S. Goßling-Reisemann

are compared to results from other (exergy) analyses. Finally, an interpretation of

entropy production in the context of ecological sustainability and finite resources

is offered, based on the finite entropy disposal rate of the earth, which enables

the reader to evaluate the meaning of the presented results.

1 Introduction

Decreasing resource consumption is a cornerstone of sustainability. Especially

engineers in the field of sustainability need to have a clear concept of how to assess

and how to optimize resource consumption in complex technological settings. Of all

subdisciplines in engineering and the natural sciences, thermodynamics offers the

most suitable set of concepts and methodologies to help the engineer in this respect.As will be shown, entropy production or exergy loss is the concept that delivers the

best physical interpretation of resource consumption and should thus be used as a

measure when assessing resource consumption. The respective methodologies are

well developed in the literature and accessible to everyone with a background in

engineering or the physical sciences.

2 Throughput Versus Change in Quality

When talking about resource consumption, two aspects have to be distinguished:

throughput of matter and energy and the accompanying change in quality of the

material and energy flows. The current discussion around resource consumptionmainly focuses on the quantity of flows, rarely on their quality. Legislation on

closing material loops, for example, is mainly concerned with increasing the amount

of materials circling within the economy, and the success of recycling strategies

is measured by the increase in recovered tons of materials. The quality of the

returned materials is only rarely assessed or included in recycling strategies, and

also the economic or technical importance of the primary and secondary materials

is not (yet) considered in most legislative approaches toward sustainable resource

management. Regarding the importance of primary resources, this seems to be

changing lately, visible by the many studies on critical or strategic materials being

commissioned by governments around the globe (e.g., NRC 2008; Angerer et al.

2009; European Commission 2010). For secondary materials, the discussion of

quality is equally important, especially since it is the quality of the recyclates that

determine the options for reuse. The problem of diminished quality is especially

pronounced for metals: impurities in bulk metals, known as tramp elements, threaten

the goal of a closed loop economy (Janke et al. 2006; von Gleich 2006; Amini

et al. 2007). As long as there are sufficient primary resources available, the focus

on quantities is understandable. The situation changes when there is a need to

significantly increase the amount of circulated material. The natural tendency

of recycling processes is that materials are becoming mixed and the material

dissipation increases. However, dissipation of materials can be avoided by clever



65 Thermodynamics and Resource Consumption 1265

organization of material flows by appropriate dismantling of products and by a

thermodynamically optimized process design. Keeping the quality of recyclates up

is thus a matter of organization, interfaces between members of the recycling chain

and intelligent process design (Castro et al. 2004; Reuter et al. 2005; Hageluken

et al. 2005; Hageluken 2007).

Thermodynamics can offer some help in assessing and designing material

transformation processes, from primary extraction to recycling, for better efficiency

and effectiveness. The main rationale behind the thermodynamic approach is that

the “usefulness” of matter and energy flows depends on their actual physical and

chemical state. The change in thermodynamic states is what constitutes resource

consumption, as is explained in the next sections.

3 Resources and Consumption

The conventional interpretation of physical resources is based on the assumption

that they are delivered by the surroundings, the natural environment in most cases,

and are somehow “used up” in a process called resource consumption. This sounds

like they would be “gone” after they have been used, which is definitely not the

case, as every physicist or chemist would be eager to point out. The laws of physics

dictate that the sum of energy and matter in any given process stays fixed (see any

basic physics textbook, as, e.g., Feynman et al. 2009). For nonnuclear processes

(no fission, no fusion), energy and matter are even conserved individually. So how

can one speak about consumption then? Merriam-Websters dictionary explains(economic) consumption as “the utilization of economic goods in the satisfaction

of wants or in the process of production resulting chiefly in their destruction,

deterioration, or transformation” (Merriam-Webster 2011).

The key message here is that economic goods are destroyed or deteriorated, that

is, they lose some of their functionality or their “potential utility” (cf. Goßling-

Reisemann 2008a). The “potential utility” is a theoretical concept describing the

amount of useful applications of goods or material and energy flows. A given set of

goods or flows have a limited number of potential uses, depending of course on the

ingenuity of the user and the tools available. Once these goods and flows have been

used for a certain product or service, they cannot be used for something else, unless

one invests more goods and flows.

The simplest example is that of a certain amount of wood, water, and energy

(plus the right tools): you can convert them into paper, using up all the material and

energy flows, but then you could not produce any alternative products anymore, like

furniture, for example. You could have chosen to build a boat instead or a wooden

hot tub but either way: once you have decided on one product path, there is no

turning back. Well, almost no turning back: when you are willing to burn some of

the furniture, you could produce enough energy to convert the rest of the furniture

(and the left over water) into paper, but you will not gain as much paper as you

would have by using all of the wood for papermaking in the first place.




The purpose of this little thought exercise is to highlight the importance of the

irreversible nature of consumption. It also shows that consumption is a gradual

concept: goods can be partly consumed and partly remain in the products which have

been produced from them. The degree of consumption obviously has some relation

with the irreversibility of the transformation of the goods. The examples here

were deliberately oversimplified: in reality, you would need many more material

resources to producepaper from wood and water, for example. Also, one should note

that the transformations leading to the loss of potential utility cannot in all cases be

quantitatively linked with the actual loss of potential utility. Small transformations

can have dramatic consequences for the usability of the economic goods involved,

like in the case of dispersing a tiny amount of toxic substances with drinking water.

The main observation remains true, however: consumption is about irreversible

transformations.The irreversibility of the consumption process is a defining characteristic and

thus a good starting point for measuring consumption itself. In economics, it

was Georgescu-Roegen who first drew attention to this (Georgescu-Roegen 1971),

leading to a scientific debate about resources and their finality which still goes on

today (see, e.g., the discussion between Arrow et al. (2004), Daly et al. (2007) and

Arrow et al. (2007)).

This chapter is concerned with physical resources, not economic goods. How-

ever, the meaning of consumption is basically the same: it is about irreversibly

changing the structure and quality of material and energy flows making them

less available for further processing. Taking the above dictionary definition as

a starting point and applying it to physical resources, the key to understanding

(physical) consumption lies in understanding the changes in the physical resourcesby destruction, deterioration, or transformation.

When the above definition of consumption is applied to all process stages from

extraction of resources to disposal and recycling of discards, it becomes clear that

all material and energy flows can be interpreted as resources, although to a different

degree. Thus, consumption is not localized to one defined area of the economic

system (as it might appear from the economically motivated dictionary definition),

but is happening wherever there are material and energy flows transformed and thus

lose potential utility.

In summary of the above paragraphs, the terms resource and consumption can

now be defined in a concise and meaningful way for the following discussion:

Resources in this context are to be understood as reservoirs or flows of matter and energy

that are used to produce products and services. Material resources can appear in the form

of raw materials, semi-products, final products, auxiliary materials, or wastes. Energetic

resources can appear as chemical energy stored in energy raw materials, heat, radiation,

potential energy, or any other form of physical energy.

Consumption is to be understood as the transformation of resources resulting in a loss

of possible further pathways for producing products and services. This loss in potential

utility comes about by chemical and physical processes, like dissipation, dilution, mixing,

chemical reactions, structural changes, heat transfer, and others.

Thermodynamics offers the right concepts to measure these kinds of changes in

physical resources, as it is the discipline of physics that analyzes energy and




material flows with regard to their transformation and conversion (Kondepudi and

Prigogine 1998). The above-mentioned irreversible “loss of potential utility” as a

measure for resource consumption has a more rigorously defined counterpart in

thermodynamics: entropy production. Economic resource consumption can then be

approximated by physical resource consumption, and entropy production can be

introduced as a measure.

4 Thermodynamics Background

Thermodynamics is the discipline of physics dealing with the conversion of energy,

including the transfer of heat and work, and the relation between different state

variables of matter and energy. Its origins lie in the assessment of the consumption of energetic resources and the efficiency of steam machines (Kondepudi and Prigogine

1998). The thermodynamic theory is based on four major laws, which very generally

describe limiting conditions for all physical systems.

The “zeroth” law of thermodynamics describes that any two systems which are

in thermodynamic equilibrium with a given third system are also in equilibrium with

each other (Kondepudi and Prigogine 1998). Thermodynamic equilibrium between

two systems is reached when there are no further driving forces for exchanging

matter or energy. This is equivalent to saying that the corresponding thermodynamic

potential is equal in both systems. For exchanges of heat only, as an example, this is

the case when both systems have the same temperature.

The first law of thermodynamics describes the conservation of energy. In essence,

it says that energy cannot be produced; it can only be converted from one formto another. The energy of a system is usually referred to as the internal energy.

It is given by the sum of all internal kinetic energies (e.g., of the particles

moving with respect to the center of mass) and all internal potential energies (e.g.,

electrostatic energy between charged particles or energy stored in chemical bonds).

For isolated systems, that is, systems with no exchange of matter or energy with

the surroundings, this law implies that the energy of the system stays constant for

all times. For closed systems, that is, systems that have no exchange of matter

with the surroundings, the first law implies that the internal energy can only be

changed by exchanging physical work or heat with the surroundings. For open

systems, additional energy changes can appear by exchanging material flows with

the surroundings. These flows change the internal energy of the system by adding

kinetic energy, gravitational energy, and enthalpy. Enthalpy is formally the sum of

internal energy of the flow and the product of its pressure and volume. Thus, a flow

of matter can add energy to a system by adding, for example, chemically stored

energy or by adding volume at constant pressure.

The second law of thermodynamics describes the devaluation of energy during

material or energetic transformations. In simple terms, it states that, although the

absolute amount of energy in any transformation is always conserved, the “quality”

of the energy decreases. The quality of a given amount of energy is measured by the

amount of physical work one could extract from this energy by ideal (i.e., lossless)

processes. Since the second law states that this quality always decreases, another




interpretation is that every conceivable process will always result in the loss of

potential physical work. The mathematical formulation of the second law uses the

concept of entropy as the measure for the “unavailability” of energy. This physical

quantity was introduced by Clausius (1850) to describe the limited efficiency of

steam engines, and he discovered that entropy is only conserved in a process when

the process is reversible. Reversible processes can be run “backwards,” meaning

that the changes in their state variables and all exchanges of matter and energy

with other systems can be passed though in reversed order. Entropy itself is a state

variable, that is, it is only dependent on the state of the system, not on its path of

evolution. It is an empirical observation that there are no reversible processes, even

if some processes can be made to approach reversibility arbitrarily close. Following

Clausius, the second law can be expressed more elegantly with the help of entropy:

The entropy of the universe can only increase and approaches a maximum.

With regard to a certain observed system and its transformational processes,

the following expression of the second law is more helpful (cf. Kondepudi and

Prigogine 1998):

The sum of the entropies of a given system and its environment cannot decrease. They

remain constant only in the (ideal) case of reversibility.

The meaning of the second law goes beyond energy conversion processes, as

could be inferred from its definition. When pure materials are mixed, for example,

the entropy increases, too. The simple interpretation is that the sum of the energies

stored within the pure material flows is generally less available to further processing

when the flows are mixed. The availability can, in the reversible case, remain

constant, but it cannot increase. The irreversibility of the process is obvious from

the fact that one would have to spend additional energy to de-mix the material flows;

a spontaneous de-mixing will not occur.

One consequence of the second law is that in any real process, the availability

of energy can only decrease. The amount of the loss of availability is directly

proportional to the entropy produced during the process. The entropy increase can

be brought about by all kinds of physical or chemical transformations: mixing,

combustion, chemical reactions, phase changes, heat transfer, etc.

The third law of thermodynamics simply states that as the temperature of a

perfect crystal approaches the absolute zero of temperature (0 K), the entropy of

the crystal also approaches zero (Kondepudi and Prigogine 1998). This then defines

the absolute zero of the entropy scale. Real materials do not necessarily satisfy the

“perfect crystal” condition, that is, they do not have a unique ground state. In gen-eral, quantum mechanics predicts “degenerate” ground states for systems containing

particles with half-integer spins (like electrons). Degenerate means, that for a given

energy, several physical configurations of the constituents are possible. Even if

thus the entropy of many systems does not approach zero for the absolute zero of

temperature, the third law defines an absolute zero for entropy. This is different from

the definition of energy, where there is no “natural” zero level and all comparisons

(and measurements!) have to be made with respect to a chosen baseline.




Especially the first law and the second law have relevancy for assessing resource

consumption. The first law offers a way to close the balance on material and energy

flows entering and leaving a system. It is therefore useful in setting up resource

balances or resource accounts for systems. Balances derived in this way highlight

the throughput of matter and energy as the basis for assessing consumption, without

addressing the change in quality of material and energy flows. The second law,

on the other hand, addresses precisely this defining characteristic of resource

consumption: the devaluation of matter and energy due to transformation of physical

flows.

5 Established Measures for Resource ConsumptionThere have been many attempts to find an adequate measure for resource consump-

tion. These can broadly be distinguished by those measures that are based on the first

law of thermodynamics (conservation of energy or mass) and those that are based

on the second law of thermodynamics (irreversibility and entropy generation).

5.1 Measures Based on the First Law of Thermodynamics

Since the first law of thermodynamics does not address the change in quality of the

materials and energy flows, the methodologiesderived from it cannot really measure

resource consumption as defined above. They rather measure resource throughputor resource use. However, this distinction is rarely made, and, in general, one will

find these methodologies usually being discussed within the context of resource

consumption. The application range of these measures varies from the product or

service level up to the level of nation states and the worldwide economy. A few

typical examples include:

Cumulative energy demand (CED): developed in the 1990s, mainly by the Oko-

Institute in Germany (VDI 1997), it measures the aggregated input of all primary

energy into the production, distribution, use, and disposal of products or services.

Raw material flows are only considered when they are principally suitable as

energy carriers, which include natural gas, crude oil, and rapeseed oil but ex-

cludes, for example, iron ore or freshwater. The CED distinguishes nonrenewable

from renewable energies, like solar, wind, and hydro. The methodology is usually

applied on the product or service level.

Material intensity per service unit (MIPS): developed at the Wuppertal Institute

in Germany and part of the material-intensity-analysis framework (MAIA)

(Schmidt-Bleek and Kluting 1994; Schmidt-Bleek 1998; Ritthoff et al. 2002;

Wuppertal Institut 2011), it measures all material movement associated with

the production, use, and disposal of products or services. The methodology

focuses on the movement of material flows, which are further distinguished into

biotic, abiotic, water, air, and moved soil. Transformation of these flows is not




considered. The methodology has been applied to the product level, to regions,

and whole economies.

Direct material input (DMI) and domestic material consumption (DMC): mea-

sures developed within the framework of material flow accounts (European

Commission 2001), used primarily to measure the input and consumption of ma-

terials in national economies. DMI measures all material flows of economic value

(i.e., which are used for production and/or economic consumption, excluding

water) entering a national economy, aggregated on mass basis. DMC is calculated

from the physical trade balance (direct material input less exports) and domestic

extraction of resources. The methodology is typically applied to nation states, but

other regional scopes are used (the methodology is extensively used for assessing

material flows for the EU as a whole, for example).

5.2 Measures Based on the Second Law of Thermodynamics

The approaches based on mass and energy conservation are merely balancing

inputs and outputs without considering qualitative changes in the material and

energy flows. Methodologies based on the second law of thermodynamics can thus

complement these balances by including an actual reference to the consumption as

defined above: the loss of potential utility.

5.2.1 Exergy Destruction as Resource ConsumptionThe methodologies that do consider the loss of potential utility can broadly be those

using entropy production as a concept and the ones using exergy loss or exergy

destruction. In essence, the two approaches are equivalent, as can be seen from the

definition of exergy (cf. Rant 1956; Szargut et al. 1988; Brodyansky 1994).

The exergy of a flow of matter or energy is the quantity of work which can be extracted

from it by reversible interactions with the environment until complete equilibrium (with the

environment) is reached (based on the definition in Brodyansky 1994).

The exergy of a system is thus dependent on the state of its environment, which must

be individually defined for each system under investigation. Furthermore, exergy has

the same units as energy, but it is not a conserved quantity, very much like entropy.

The difference is that while the entropy of an isolated system is always increasing,

its exergy is constantly decreasing. In an isolated system, exergy can be destroyed,

but never be created. This feature makes exergy destruction a promising candidate

for measuring resource consumption.

The (specific) exergy flow " of a material flow can be partitioned into different

contributions, reflecting the physically independent equilibration processes: poten-

tial, kinetic, thermal, mechanical, and chemical exergy:

" D "pot C "kim C "th C "mech C "chem:




The potential and the kinetic exergy of a flow are equal to its potential and kinetic

energy. The thermal contribution "th is the work rate extractable by reversible

processes when bringing the material flow to thermal equilibrium with the reference

environment without changing either its composition or its other thermodynamic

parameters. The mechanical contribution "mech is defined similarly for the work rate

obtainable from reversible equilibration of pressure differences. The sum of "th and

"mech is also called physical exergy and denoted "ph. It can be derived from the

specific enthalpy h and the specific entropy s of the flow

"ph D "mech C "th D PmŒh h0 T 0.s s0/

where the subscript 0 denotes the values in the reference state of the environment

and Pm is the mass flow rate (mass/time).

The chemical exergy flow rate of a material flow can be obtained from analyzing

the chemical reactions leading from the material flow’s chemical composition to

the chemical composition of the reference environment. This can be achieved by

using the chemical potentials of the flow’s components j at reference temperature

T 0; j 0, the component’s chemical potential in the reference environment,j 00, and

the respective mass fractions xj of the components:

"ch D PmXj

.j 0 j 00/xj :

The reader is referred to the books by Szargut et al. (1988) and Brodyansky (1994)

for a detailed description.

The exergy flow "qs of a heat flow q across a surface area s at temperature T s is

obtained from the Carnot factor:

"qs D

1

T 0

T s

q:

With the above expressions, the exergy flow balance of a steady-state system can be

set up, and the exergy destruction is obtained from

Xi

"ini

Xi

"outi

Xs

"qs PW PI D 0;

with "ini denoting the various incoming exergy flows, "out

i outgoing exergy flows,PW physical work (rate), and PI denoting exergy consumption rate. For nonsteady-

state systems, the 0 on the right hand side has to be replaced by "sys the exergy

change of the system itself. With the help of the Gouy-Stodola theorem, the exergy

consumption rate can be related to the entropy production PS rate of the system:

PI D T 0 PS:




Exergy analyses have been performed on many systems, with the longest and most

successful tradition in analyzing and optimizing energy conversion technologies

and chemical processing (see Brodyansky 1994; Kotas 1995; Szargut 2005; Borel

and Favrat 2010), and are now successfully applied to assess natural resources

and resource consumption in life-cycle assessments (Bosch et al. 2007; Dewulf

et al. 2007) and in natural resource accounting and analysis (see the extensive

bibliography on http://www.exergoecology.com).

5.2.2 Entropy Production as a Measure for Resource ConsumptionAs discussed above, entropy production can serve as a proxy for resource consump-

tion by measuring the decrease in thermodynamically allowed pathways for utilizing

material and energy flows. Entropy is not a conserved quantity, as was also true for

exergy; thus, the balance equation for any real process must include a productionterm for entropy. In general, the change in the entropy of a system can be partitioned

into the entropy being exchanged with the system’s environment, eS sys, and the

internally produced entropy, iS sys (Kondepudi and Prigogine 1998):

S sys D eS sys CiS sys:

In the case of ideal, that is, reversible, processes, the internal production term is

zero. In all real processes, however, entropy is produced. In many cases, the entropy

change of the system itself can be neglected .S sys D 0/. This is especially true for

steady-state processes, where the system state is static, or cyclic processes, where

the system is repeatedly going through the same states such that for an appropriately

chosen time interval, the net change in entropy is zero. The latter definition holds,for example, for batch processes.

A general process can be thought of as a control volume with material flows Pmk(mass/time), heat flows eq (energy/time), and radiation flows es (energy/time) enter-

ing and leaving the system. The thermodynamic measure for resource consumption

is then given by the internally produced entropy. With S sys D 0 (steady-state or

cyclic process after full number of cycles), this quantity can be calculated from the

entropy balance (cf. Goßling 2001):

iS D

Z d iS

dt

dt D

Z 0@eoutq

T 0einq

T 0CXj

4

3

eouts;j

T outs;j

CXj

4

3

eins;j

T ins;j

Xk

sk Pmk

1A dt

where the e in;outq are the heat flows in and out of the system, respectively, e

in;outs;j are

the incoming and outgoing flows of (assumedly black body) radiation

received/emitted at surface area j , with T in;outs;j being the temperature of the

received/emitted radiation, and sk being the specific entropy of material mk.

5.2.3 The Energy BalanceWhen it is assumed that the system at hand does not perform physical work on

the environment (and vice versa), the heat flows in the above formula can be




derived from balancing the enthalpy of the incoming and outgoing flows, including

the incoming and outgoing radiation, and correcting for the internally dissipated

electrical energy eelq :

einq eout

q D eelq ein

s C eouts C

Xk

hk Pmk

with hk being the specific enthalpy of material mk. The emitted radiation flows eouts

can be derived from the temperature of the partial surface areas Aj with uniform

temperature (Kondepudi and Prigogine 1998):

eouts D

Xj

Aj.T outs;j /

4

where sigma is the Stefan-Boltzmann constant. The same formula holds for the

received radiation when the temperature is exchanged accordingly. The radiation

energy balance then becomes

eouts ein

s DXj

Aj h.T outs;j /

4 .T out

s;j /4i:

In many metallurgical and chemical processes, the temperature of the reaction

vessels is comparatively low (e.g., below 100ı

C) so that the radiation losses mightbe omitted. The heat balance is then determined by the electrical energy dissipation

and the enthalpies of the material flows.

The specific enthalpy of a material flow depends on its composition, and for ideal

mixtures, it is simply the weighted sum of the specific enthalpies of the components

of this mixture. For nonideal mixtures, the enthalpy of mixing has to be included.

5.2.4 Material Entropy FlowsAfter having settled the energy balance with the help of the above equations (heat,

radiation, enthalpy), the next step is determining the material entropy flows to

calculate the entropy production within the system under investigation. This can be

done with the help of tabulated values of molar entropies (or molar heat capacities)

found in thermodynamichandbooksand databases (see, e.g., Haynes and Lide 2010;CRCT 2011; Linstrom and Mallard 2010; Barin 1995). The specific entropy sk of a

material flow mk can then be calculated from the molar composition of the flows,

given by the molar amount nk in flow k, the respective molar share ykj of each

component j in this flow, and the molar entropy Nsj of the component j :

sk D1

mk

8<:Xj

nkykj Nsj R

Xj

nkykj ln.yki /

9=;




with R being the universal gas constant (8.314472J/K/mol). The latter sum in the

above formula represents the entropy of mixing and is solely due to the mixing

of components in the material flow. The entropy of mixing can also be used for

assessing the quality of material flow management systems, for example, in waste

incinerators (Rechberger 1999), in recycling processes (Goßling-Reisemann et al.

2011), or on the level of economy-wide substance flows (Rechberger and Graedel

2002).

6 Application Example: Copper Production

6.1 Entropy Production

As an example for the application of using thermodynamics for assessing resource

consumption,the entropy production of copper production is presented (cf. Goßling-

Reisemann 2008b). The analysis is based on a process model describing the

mining and beneficiation of sulfidic copper ores and the metallurgy of these ores

to produce copper cathodes. The metallurgy itself consists of four main stages:

flash smelter, converter, anode furnace, and electrolysis, which are part of this

analysis. Other downstream processes are not considered: the offgas is further used

for the production of sulfuric acid as a by-product, residues from the electrolysis

are further treated to extract valuable metals, and the slag is processed to be used

as a construction material. The material flows most relevant for the calculation of

resource consumption for 1 t of refined copper are given in Table 65.1.The calculation of the entropy production proceeds as outlined in the previous

section: material compositions need to be established, energy flows have to be

calculated (enthalpy, heat, and radiation), and then the entropy balance can be

calculated. Since the system itself is not changing its entropy during the production

of copper, the steady-state condition is met, and the entropy production can be

calculated from the entropy balance.

As an example, consider the composition of the ore concentrate as given in

Table 65.2. The components of the concentrate have specific entropies which can be

looked up in thermochemistry tables (e.g., Barin 1995; Linstrom and Mallard 2010;

CRCT 2011), and the mixing contribution to this material’s entropy is calculated

from the formula given in the previous section.

As with the ore concentrate, all flows are evaluated and can then be analyzed. For

visual inspection, a Sankey diagram is most helpful; see Fig. 65.1 for the entropy

flows of the metallurgical stage. One can see at one glance that the entropy flows

associated with the electricity production are the largest in the system, directly

followed by the offgas flow from the converter. The entropy production due to

electricity production for the metallurgical stage can be read off the labels and is

10.4 MJ/K (per ton of refined copper, which is the functional unit in this case).

The entropy production for the mining and beneficiation stage and the metallurgical

processes is given in Table 65.3.




Table 65.1 Most relevant material flows for mining, beneficiation, and metallurgy of copper

(model description and data sources in Goßling (2001) and Goßling-Reisemann (2008b))

Input Output

Mining and beneficiation

Overburden 76.8 t Overburden 76.8 t

Crude ore 101.2 t Tailings 97.5 t

Final energy 10.7 GJ Ore concentrate 3.8 t

Electricity 8.3 GJ Discarded water 150.0 t

Diesel 2.4 GJ

Fresh water 150.0 t

Lime (CaO) 0.1 t

Metallurgy

Ore concentrate 3.8 t Copper (cathodes) 1.0 tFlux (SiO2) 0.5 t Slag 2.1 t

Final energy 9.1 GJ Offgas (to sulfuric acid plant) 3.9 t

Electricity 1.3 GJ Offgas (to filter/environment) 7.2t

Fossil fuels 7.8 GJ

Electricity production (for mining, beneficiation, and metallurgy)

Primary energy 25.9 GJ Electrical energy 9.6 GJ

Cooling water 618.4 t Cooling water discharge 223.2 t

Steam 395.2 t

Interpreting these results, it seems noteworthy that the resource consumption

of copper making is roughly halfway split between mining and beneficiationand metallurgy. It must further be noted that the upstream process of electricity

production plays an important role, especially for the mining and beneficiation

stage. This is mainly due to the necessary comminution of the raw ore, which is

facilitated by large mechanical crushers and grinders. Another noteworthy fact is

the importance of material transformations for resource consumption: a large part

of the entropy production in the flash smelter and the converter is brought about

by chemical reactions, mixing, and structural changes and not by converting final

energy carriers into heat, as one might assume. This highlights the importance of

looking beyond pure energy and mass balances for assessing resource consumption.

The heat losses in the offgas treatment deserve a closer look, as well. The

resulting entropy production, and thus resource consumption, is due to energy

transformations, that is, the transfer of heat across a finite temperature difference.

However, there are other factors influencing the entropy production associated with

handling the offgas flow: (a) a large amount of cooler ambient air is mixed with the

converter and anode furnace offgas due to the batchwise operation of these furnaces

and (b) the different offgas flows from flash smelter, converter, and anode furnace

have greatly differing temperatures, and the mixing of these flows thus produces

additional entropy. If the mixing with ambient air could be prevented and these

flows would be kept separate, the overall resource consumption could be decreased

by approximately 6 MJ/K or almost 7% of the metallurgical resource consumption.




T a b l e

6 5 . 2

C o m p o s i t i o n o

f t y p i c a l o r e c o n c e n t r a t e , m o l a r e n t r o p i e s o

f t h e c o m p o n e n t s , a n d s p e c i fi c e n t r o p y o f t

h e c o n c e n t r a t e . C o m p o s i t i o n d e r i v e d f r o m

e l e m e n t a l c o m p o s i t i o n ( D a v e n p o r t a n d P a r t e l p o e g 1 9 8 7 ) a n d r e c a l c u l a t e d t o a c c o u n t f o r c h e m i c a l c o m p o u n d s t y p i c a l l y f o u n d i n o r e s ( c f . G ¨ o ß l i n g 2 0 0 1 )

( E n t r o p i e s t a k e n f r o m B a r i n

( 1 9 9 5 ) a n d L i n s t r o m a n d M a l l a r d ( 2 0 1 0 ) )

C o m p o n e n t

C u F e S 2

S i O 2

C

A l 2 O 3

Z n S

P b S

H 2 O

A s 2 S 3

N i

C a O

M a s s f r a c t i o n ( w t % )

8 4 :

4 2

7 :

4 0

2 :

3 0

2 :

2 4

2 :

1 2

0 :

3 5

0 :

3 0

0 :

3 0

0 :

0 5

0 :

5 2

M o l a r e n t r o p y ( J / K / m o l )

1 2 5 :

0

4 1 :

4

5 :

7

5 0 :

9

5 7 :

7

9 1 :

3

7 0 :

0

1 6 4 :

0

2 9 :

8

3 8 :

2

M o l a r w e i g h t ( g / m o l )

1 8 3 :

5 2 1

6 0 :

0 8 4 3

1 2 :

0 1 0 7

1 0 1 :

9 6 1 3

9 7 :

4 4

2 3 9 :

3

1 8 :

0 1

5 3

2 4 6 :

0 3 8

5 8 :

6 9 3 4

5 6 :

0 7 7

S u m o f s p e c i fi c c o m p o n e n t e n t r o p i e s ( J / K / g )

0 . 6 7 9

S p e c i fi c e n t r o p y o f m i x i n g (

J / K / g )

0 . 0 9 1

S p e c i fi c e n t r o p y ( J / K / g )

0 . 7 7 0

E n t r o p y o f 3 . 8 t c o n c e n t r a t e

( M J / K )

2 . 9 2 8




T2:Electricity Mix Germany 428 MJ/K

6.52 MJ/K

29.1 MJ/K

5.05 MJ/K

24.6 MJ/K

10.8 MJ/K

35.3 MJ/K

19.6 MJ/K

5.27 MJ/K

P4:Emissions

P3:Suphuric Acid Plant

P7: Flash smetter slag

P12: Anode slime

P13: Cathodes

P7:Converter slag

51.8 MJ/K

P5:Energy-Resources

P1:MetallurgicalResources

T5:Electrolysis

T4:Anode Furnace

T1:Flash Smelter

T3: Converter

417 MJ/K

P6

Fig. 65.1 Entropy flows of the metallurgy stage for copper production. All arrow widths are

proportional to the respective entropy flow, except for the hatched arrow from electricity mix to

emissions

Table 65.3 Entropy production along the process chain for producing refined copper from

sulfidic copper ore. Basis was the calculation in Goßling-Reisemann (2008b) with improved data

on efficiencies and material compositions. Also the model in Goßling-Reisemann (2008b) has been

updated so that the system border now includes the upstream process of electricity production and

the heat loss from the offgas treatment

Stage Entropy production (per ton of refined copper)

Mining and beneficiation

Direct processes 36.9 MJ/K

Electricity production (upstream) 58.0 MJ/KMetallurgy

Flash smelter 18.2 MJ/K

Converter 15.8 MJ/K

Anode furnace 8.7 MJ/K

Electrolysis 4.4 MJ/K

Electricity production (upstream) 10.4 MJ/K

Offgas treatment (heat loss) 33.0 MJ/K

Sum 185.3 MJ/K




Technically, this is probably not fully feasible, but there are options for optimization:

the temperature difference between the flows and the surroundings could be used

for energy recovery (e.g., by producing steam or electricity), and the anode and

converter furnace can be equipped with more efficient offgas capture systems. Once

the flows have a uniform temperature, their heat content can further be used in heat

recovery systems, as long as their temperature does not fall below the optimum for

the subsequent sulfuric acid plant.

6.2 Comparison with Other Assessments

There have been other attempts at using thermodynamics to assess the resource

consumption of copper making. Most of them have used exergy analysis, but theresults are comparable since the entropy production can be calculated from the

exergy destruction via the Gouy-Stodola equation (see above). One of the earliest

studies was performed by Kolenda et al. (1992), in which three distinct processes

of copper making were analyzed: blast furnace, converter, and anode furnace.

The blast furnace is an outdated technology, which explains the poor results of

the exergetic analysis. A comparison with the entropy analysis above is given in

Table 65.4. Taking into account the distance in time between the two analyses (the

data in Goßling-Reisemann 2008b is from between 1999 and 2006), the agreement

is quite good, and the differences are probably explained by improvements in

process technology (note that the upstream process of electricity production and

the downstream process of offgas treatment are not included).

Another exergy analysis was performed by Ayres et al. (2006) with a technolog-ical setup very close to the one analyzed here and with data from around the same

period (around 1999). A comparison of their results with the one presented here

can be found in Table 65.5. The differences are quite remarkable and can only be

explained with more detailed knowledge of the processes analyzed. It is interesting

to note, however, that the ratio between entropy productions in the metallurgy stage

and the mining stage is between 1.27 and 1.40, respectively, and is thus in fairly good

agreement. This probably indicates a systematic difference between the process

models.

Table 65.4 Comparison of entropy production from an analysis performed by Kolenda et al.

(1992) with the analysis presented in this chapter (updated model of G oßling-Reisemann (2008b))

Kolenda et al. (1992) Goßling-Reisemann (2008b) + model update

Blast furnace 39.2 MJ/K/t Flash smelter 18.2

Converter 17.1 MJ/K/t Converter 15.8 MJ/K/t

Anode furnace 11.0 MJ/K/t Anode furnace 8.7 MJ/K/t

Total 67.3 MJ/K/t 42.7 MJ/K/t




Table 65.5 Comparison of entropy production from an analysis performed by Ayres et al. (2006)

with the analysis presented in this chapter (updated model of Goßling-Reisemann (2008b)). Note

that in the data taken from Ayres et al., upstream and downstream processes (electricity production

and offgas treatment/sulfuric acid production) have not been included to achieve comparable

system boundaries

Process stage Ayres et al. (2006) Goßling-Reisemann (2008b) + model update

Mining and beneficiationa 99.1 MJ/K/t 36.9 MJ/K/t

Metallurgy a 138.6 M J/K/t 47.1 M J/K/taOnly direct entropy production

6.3 Interpretation of Entropy Production

Interpretationof the results from thermodynamicanalyses can be done with different

goals. Historically, thermodynamics was used to optimize processes, most notably

energy conversion processes. This is still the main application also of analyses using

exergy or entropy (see, e.g., the long-standing tradition of the ECOS conferences

– International Conference on Efficiency, Cost, Optimization, Simulation, and

Environmental Impact of Energy Systems). In the paragraphs above, however, the

focus is explicitly on resource consumption of products, processes, and services

under a life-cycle perspective. The goal is to find an answer to the question of

how much resources are going to be destroyed in the satisfaction of a specific

demand. If different products or services are to be compared, the absolute amount

of resource consumption is less important; only the relative differences are relevant

for a decision. Still, the absolute value of the entropy production or exergy loss hasmeaning, too.

As stated above, exergy and entropy are not conserved. The exergy available

for economic processes is limited mainly by the regeneration rates of terrestrial

resources, which again is dependent on the solar irradiation rate. For entropy,

something similar holds. Every living system is dependent on the expulsion of

the internally produced entropy (Ebeling et al. 1990; Glansdorff and Prigogine

1971; Nicolis and Prigogine 1977), or otherwise it collapses under accumulating

entropy waste. This expulsion rate is usually limited, for example, by physical limits

to the exchange of material and energy with the environment. The development

of lakes, amphibian eggs, and humans has been studied in this respect (Aoki

1991, 1995, 2008), and the analysis shows that the entropy production rate of these

biological systems varies with the developmental stage: early in their life, these

systems steadily increase their entropy production rate until it reaches a maximum,

after which the organisms seem to gradually optimize their resource consumption

and the entropy production rate converges toward a much lower stable value. If

this is translated into economic terms, nature seems to favor material growth in

early stages of development, without concern for resource consumption at all. In

later developmental phases, however, efficiency and resource conservation are the

guiding principles.




How does this relate to the global economic system? Firstly, also the entropy

disposal rate of the earth is limited. The disposal of entropy occurs mainly via

the emission of long-wave radiation from the earth atmosphere into space. For

the current biophysical conditions, including the earth’s surface temperature, the

average entropy disposal rate of one square meter of surface area is around 1.2 W/K

(cf. Goßling-Reisemann 2008b). For different conditions, this might change; for

example, a higher surface temperature might change the atmospheric system and

induce currently unknown convective patterns in the atmosphere, leading to a higher

disposal rate of entropy. However, the transition from the current state of the climate

system to the “improved” state probably comes with intermittent turbulence, and the

resulting climatic system might be less favorable to humans than the one us humans

are used to. Precaution thus dictates to preserve the state of the climate system as

much as possible. This implies a limit to the amount of entropy produced globally,which in turn basically fixes the amount of entropy we as humans should be allowed

to produce. There is currently no rigorously defined limit for the sustainable human

entropy production rate, but for the argument of resource conservation, it suffices

to know that there is a limit at all. If there is consensus that the average entropy

production density on earth should not be above 1.2W/K/m2, this “natural” limit can

be used to give the entropy production of economic processes a new meaning, and

it can simultaneously be used as a “yardstick” to compare the entropy production of

all processes.

The above example calculation of the resource consumption for copper making

can be compared to this yardstick. The entropy production of 185.3 MJ/K per ton

of refined copper corresponds to the yearly disposal capacity of approximately

5m2

of earth’s surface. The global annual copper production in 2004 was about10 million tons, according to Graedel et al. (2004). This would imply the permanent

“occupation” of approximately 50 million m2 or 50 km2 of earth surface. For

comparison, the world primary energy consumption rate in 2008 was approximately

15 terawatt (BP 2009). If it is assumed that the primary energy is almost completely

transferred into heat at ambient temperature, the resulting “entropy footprint”

amounts to around 42;000 km2.

In this manner, human activities and economic processes can be evaluated against

a naturally given limit, and the resource side of sustainability can be assessed by

using thermodynamic principles and measures.

7 Further Reading

The application of thermodynamics for process evaluation is not limited to the

question of resource consumption, although there is a current scientific debate

around that topic (Connelly and Koshland 2001a, b; Seager and Theis 2002;

Goßling-Reisemann 2008a, b). As noted above, thermodynamic analysis, especially

exergy analysis, was most successfully applied in the design and optimization of




energy conversion systems (see Szargut et al. 1988; Kotas 1995; Bejan et al. 1996;

Szargut 2005; Borel and Favrat 2010).

Along the same lines, but on a more general level, entropy analysis has been

suggested to be used in finding the optimal design of a broader class of processes.

Bejan introduced entropy production (he uses the term entropy generation) as a

means of thermodynamically assessing and optimizing the losses connected with

heat transfer, fluid flow, and mass transfer irreversibility (Bejan 1996). Bejan’s

entropy generation minimization (EGM) approach is basically a way to optimize

the design of systems and to assess their efficiency. It requires knowledge of the

geometrical setup of the machines and the thermodynamic properties of the internal

flows of matter and energy inside the analyzed system (or model).

Exergy analysis is still developed further and finds its ways into ever more

applications. It is combined with economic evaluation in the field of exergoeco-nomics (Tsatsaronis 1999; Rosen 2010), and it is also used within the field of

life-cycle assessment (Cornelissen 1997; Cornelissen and Hirs 2002; Dewulf and

van Langenhove 2002a, b; Stewart and Weidema 2005; Bosch et al. 2007). Also

entropy analysis is applied to life-cycle assessment (Goßling-Reisemann 2011).

8 Summary

Exergy and entropy analysis have experienced a great success in application

throughout the recent decades in the fields of chemical engineering, energy con-version, and general technological design. However, there were comparatively less

applications as an approach toward measuring resource consumption. Resource

consumption is most often discussed within the field of life-cycleassessment (LCA),

a highly standardized methodology for assessing environmental impacts of products

and services. Despite decades of methodological development of LCA and at least

20 years of successful application of this methodology, there is still no consensus

on what resource consumption really is and how it should be included in LCA. The

main reason seems to be the high data requirements for thermodynamic analysis

in combination with the wide scope of typical LCA applications. First steps in

building a basis for future thermodynamic analysis in LCA have been made, for

example, by adding exergy values of natural resources to an LCA database (Bosch

et al. 2007), but the use of this data is still demanding and far from common

practice. Combining LCA databases with more general thermodynamic databases

might be another approach which might lead to a more widespread use of the

thermodynamically defined concept of resource consumption in LCA (cf. G oßling-

Reisemann 2011). Still, exergy and even more so entropy remain rather abstract

measures and need to be better communicated as valuable concepts for assessing the

material side of sustainability to a broader audience, especially engineers concerned

with sustainability.




References

S.H. Amini, J.A.M. Remmerswaal, M.B. Castro, M.A. Reuter, Quantifying the quality loss and

resource efficiency of recycling by means of exergy analysis. J. Clean. Prod. 15(10), 907–913

(2007)

G. Angerer, L. Erdmann, F. Marscheider-Weidemann, M. Scharp, A. Lullmann, V. Handke, M.

Marwede, Rohstoffe f¨ ur Zukunftstechnologien: Einfluss des branchenspezifischen Rohstoffbe-

darfs in rohstoffintensiven Zukunftstechnologien auf die zuk¨ unftige Rohstoffnachfrage. ISI-

Schriftenreihe Innovationspotenziale (Fraunhofer Verlag, Stuttgart, 2009)

I. Aoki, Entropy principle for human development, growth and aging. J. Theor. Biol. 150(2),

215–223 (1991)

I. Aoki, Entropy production in living systems – from organisms to ecosystems. Thermochim. Acta

250(2), 359–370 (1995)

I. Aoki, Entropy law in aquatic communities and the general entropy principle for the development

of living systems. Ecol. Model. 215(1), 89–92 (2008)

K. Arrow, P. Dasgupta, L. Goulder, G. Daily, P. Ehrlich, G. Heal, S. Levin, K. M aler, S. Schneider,

Are we consuming too much? J. Econ. Perspect. 18(3), 147–172 (2004)

K. Arrow, G. Daily, P. Dasgupta, P. Ehrlich, L. Goulder, G. Heal, S. Levin, K. M aler, S. Schneider,

D. Starrett, B. Walker, Consumption, investment, and future well-being reply to Daly et al.

Conserv. Biol. 21(5), 1363–1365 (2007)

R.U. Ayres, L.W. Ayres, A. Masini, An application of exergy accounting to five basic metal

industries, in Sustainable Metals Management: Securing Our Future – Steps Towards a Closed

Loop Economy, ed. by A. von Gleich, R.U. Ayres, S. Goßling-Reisemann. Eco-Efficiency in

Industry and Science, vol. 19 (Springer, Dordrecht, 2006), pp. 141–194

I. Barin, Thermochemical Data of Pure Substances, 3rd edn. (VCH, Weinheim, 1995)

A. Bejan, Entropy Generation Minimization: The Method of Thermodynamic Optimization of

Finite-Size Systems and Finite-Time Processes. Advanced Topics in Mechanical Engineering

Series, vol. 2 (CRC, Boca Raton, 1996)

A. Bejan, G. Tsatsaronis, M.J. Moran, Thermal Design and Optimization (Wiley, New York, 1996)L. Borel, D. Favrat, Thermodynamics and Energy Systems Analysis: From Energy to Exergy

(EFPL/CRC, Lausanne, 2010)

M.E. Bosch, S. Hellweg, M.A.J. Huijbregts, R. Frischknecht, Applying cumulative exergy demand

(CExD) indicators to the ecoinvent database. Int. J. Life Cycle Assess. 12(3), 181–190 (2007)

BP, BP Statistical review of world energy June 2009: spreadsheet file (2009), http://www.bp.

com/liveassets/bp internet/globalbp/globalbp uk english/reports and publications/statistical en

ergy review 2008/STAGING/local assets/2009 downloads/statistical review of world energy

full report 2009.xls. Accessed 28 May 2011

V.M. Brodyansky, The Efficiency of Industrial Processes: Exergy Analysis and Optimization

(Elsevier, Amsterdam, 1994)

M.B.G. Castro, J.A.M. Remmerswaal, M.A. Reuter, U.J.M. Boin, A thermodynamic approach to

the compatibility of materials combinations for recycling. Resour. Conserv. Recycl. 43(1), 1–19

(2004)

Centre for Research in Computational Thermochemistry (CRCT), F*A*C*T – facility for theanalysis of chemical thermodynamics: online database (2011), http://www.crct.polymtl.ca/fact/

R. Clausius, Uber die bewegende Kraft der Warme. Ann. Phys. 79, 368–397, 500–524 (1850)

L. Connelly, C.P. Koshland, Exergy and industrial ecology—part 1: an exergy-based definition

of consumption and a thermodynamic interpretation of ecosystem evolution. Exergy 1(3),

146–165 (2001a)

L. Connelly, C.P. Koshland, Exergy and industrial ecology—part 2: a non-dimensional analysis of

means to reduce resource depletion. Exergy 1(4):234–255 (2001b)

R.L. Cornelissen, Thermodynamics and sustainable development – the use of exergy analysis and

the reduction of irreversibility. Dissertation, University of Twente, 1997




R.L. Cornelissen, G.G. Hirs, The value of exergetic life cycle assessment besides LCA. Energy

Convers. Manag. 43(9), 1417–1424 (2002)

H. Daly, B. Czech, D. Trauger, W. Rees, M. Grover, T. Dobson, S. Trombulak, Are we consuming

too much-for what? Conserv. Biol. 21(5), 1359–1362 (2007)

W.G. Davenport, E.H. Partelpoeg, Flash Smelting: Analysis, Control and Optimization (Pergamon,

Oxford, 1987)

J. Dewulf, H. van Langenhove, Assessment of the sustainability of technology by means of a

thermodynamically based life cycle analysis. Environ. Sci. Pollut. Res. Int. 9(4), 267–273

(2002a)

J. Dewulf, H. van Langenhove, Quantitative assessment of solid waste treatment systems in the

industrial ecology perspective by exergy analysis. Environ. Sci. Technol. 36(5), 1130–1135

(2002b)

J. Dewulf, M.E. Bosch, B. de Meester, G. van der Vorst, H.V. Langenhove, S. Hellweg,

M.A.J. Huijbregts, Cumulative exergy extraction from the natural environment (CEENE) a

comprehensive life cycle impact assessment method for resource accounting. Environ. Sci.Technol. 41(24), 8477–8483 (2007)

W. Ebeling, A. Engel, R. Feistel, Physik der Evolutionsprozesse (Akademie-Verl., Berlin, 1990)

European Commission, Economy-Wide Material Flow Accounts and Derived Indicators:

A Methodological Guide (Office for Official Publications of the European Communities,

Luxembourg, 2001)

European Commission, Critical Raw Materials for the EU: Report of the Ad-hoc Working Group

on defining critical raw materials, Brussels (2010)

R.P. Feynman, R.B. Leighton, M.L. Sands, The Feynman Lectures on Physics. The Definitive and

Extended Edition (Addison-Wesley, San Francisco/Harlow, 2009)

N. Georgescu-Roegen, The Entropy Law and the Economic Process (Harvard University Press,

Cambridge, 1971)

P. Glansdorff, I. Prigogine, Thermodynamic Theory of Structure, Stability and Fluctuations (Wiley,

London, 1971)

S. Goßling, Entropy production as a measure for resource use: method development and application

to metallurgical processes. Dissertation. University of Hamburg, 2001, http://www.sub.uni-

hamburg.de/opus/volltexte/2004/1182/

S. Goßling-Reisemann, What is resource consumption and how can it be measured?: Theoretical

considerations. J. Ind. Ecol. 12(1), 10–25 (2008a)

S. Goßling-Reisemann, What is resource consumption and how can it be Measured? Application

of entropy analysis to copper production. J. Ind. Ecol. 12(4), 570–582 (2008b)

S. Goßling-Reisemann, Entropy production and resource consumption in life cycle assessments, in

Thermodynamics and the Destruction of Resources, ed. by B. Bakshi, T. Gutowski, D. Sekulic

(Cambridge University Press, New York, 2011)

S. Goßling-Reisemann, A. von Gleich, V. Knobloch, B. Cebulla, Bewertungsmaßstabe fur metallis-

che Stoffstrome: von Kritikalitat bis Entropie, in Methoden der Stoffstromanalyse: Konzepte,

agentenbasierte Modellierung und ¨ Okobilanz, ed. by F. Beckenbach. Stoffstromanalysen, vol.

1, 1st edn. (Metropolis, Marburg, 2011)

T. Graedel, D. van Beers, M. Bertram, K. Fuse, R. Gordon, A. Gritsinin, A. Kapur, R. Klee, R.

Lifset, Multilevel cycle of anthropogenic copper. Environ. Sci. Technol. 38(4), 1242–1252(2004)

C. Hageluken, The challenge of open cycles – barriers to a closed loop economy demonstrated for

consumer electronics and cars, in R’07 World Congress: Recovery of Materials and Energy for

Resource Efficiency (EMPA, Davos, 2007)

C. Hageluken, M. Buchert, H. Stahl, Stoffstr¨ ome der Platingruppenmetalle: Systemanalyse und

Maßnahmen f¨ ur eine nachhaltige Optimierung der Stoffstr¨ ome der Platingruppenmetalle;

Endbericht (GDMB-Medienverl., Clausthal-Zellerfeld, 2005)

W.M. Haynes, D.R. Lide, CRC Handbook of Chemistry and Physics: A Ready-Reference Book of

Chemical and Physical Data (CRC, Boca Raton, 2010)




D. Janke, L. Savov, M.E. Vogel, Secondary materials in steel production and recycling, in

Sustainable Metals Management: Securing Our Future – Steps Towards a Closed Loop

Economy, ed. by A. von Gleich, R.U. Ayres, S. Goßling-Reisemann. Eco-Efficiency in Industry

and Science, vol. 19 (Springer, Dordrecht, 2006), pp. 313–334

Z. Kolenda, J. Donizak, A. Holda, J. Szmyd, M. Zembura, An analysis of cumulative energy and

exergy consumption in copper production, in International Symposium ECOS’92: Conference

Proceedings, Zaragoza (The American Society of Mechanical Engineers, New York, 1992),

pp. 275–282

D. Kondepudi, I. Prigogine, Modern Thermodynamics: From Heat Engines to Dissipative Struc-

tures (Wiley, Chichester, 1998)

T.J. Kotas, The Exergy Method of Thermal Plant Analysis (Krieger Publishing, Malabar, 1995)

P. Linstrom, W. Mallard (eds.), NIST Chemistry WebBook (http://webbook.nist.gov ): NIST

Standard Reference Database Number 69, June 2010. National Institute of Standards and

Technology, Gaithersburg, 20899 (2010)

Merriam-Webster, Definition of “consumption” (2011), http://www.merriam-webster.com/ dictionary/consumption. Accessed 28 May 2011

National Research Council (NRC), Minerals, Critical Minerals, and the U.S. Economy (The

National Academies Press, Washington, DC, 2008)

G. Nicolis, I. Prigogine, Self-organization in Non-equilibrium Systems: From Dissipative Struc-

tures to Order Through Fluctuations (Wiley, New York, 1977)

Z. Rant, Exergie, ein neues Wort fur technische Arbeitsf ahigkeit. Forschung. Ing. Wesen 22, 36–37

(1956)

H. Rechberger, Entwicklung einer Methode zur Bewertung von Stoffbilanzen in der Abfall-

wirtschaft . Wiener Mitteilungen, vol. 158 (Technical University Institute fur Wassergute und

Abfallwirtschaft, Wien, 1999)

H. Rechberger, T. Graedel, The contemporary European copper cycle: statistical entropy analysis.

Ecol. Econ. 42(1), 59–72 (2002)

M.A. Reuter, U.M.J. Boin, A. van Schaik, E.V. Verhoef, K. Heiskanen, Y. Yang, G. Georgalli,

The Metrics of Material and Metal Ecology: Harmonizing the Resource, Technology and Environmental Cycles (Elsevier, Amsterdam, 2005)

M. Ritthoff, H. Rohn, C. Liedtke, Calculating MIPS: Resource Productivity of Products and

Services. Wuppertal Spezial, vol. 27 (Wuppertal-Institute for Climate, Environment and Energy,

Wuppertal, 2002)

M.A. Rosen, Economics and Exergy: An Enhanced Approach to Energy Economics (Nova Science

Publisher’s, Hauppauge, 2010)

F. Schmidt-Bleek, MAIA: Einf¨ uhrung in die Material-Intensit¨ ats-Analyse nach dem MIPS-Konzept .

Wuppertal Texte (Birkhauser, Berlin, 1998)

F. Schmidt-Bleek, R. Kluting, Wieviel Umwelt braucht der Mensch?: MIPS – das Maß f¨ ur

¨ okologisches Wirtschaften (Birkhauser, Berlin, 1994)

T. Seager, T. Theis, A uniform definition and quantitative basis for industrial ecology. J. Clean.

Prod. 10(3), 225–236 (2002)

M. Stewart, B.P. Weidema, A consistent framework for assessing the impacts from resource use –

a focus on resource functionality. Int. J. Life Cycle Assess. 10(4), 240–247 (2005)J. Szargut, Exergy Method: Technical and Ecological Applications. Developments in Heat Transfer,

vol. 18 (WIT, Southampton, 2005)

J. Szargut, D.R. Morris, F.R. Steward, Exergy Analysis of Thermal, Chemical and Metallurgical

Processes (Hemisphere Publishing, New York, 1988)

G. Tsatsaronis, Design optimization using exergoeconomics, i n Thermodynamic Optimization

of Complex Energy Systems, ed. by A. Bejan, E. Mamut. Proceedings of the NATO

Advanced Study Institute on Thermodynamics and the Optimization of Complex Energy

Systems, Neptun, July 1998. 3, High Technology, vol. 69 (Kluwer, Dordrecht/Boston, 1999),

pp. 101–115




VDI Gesellschaft Energietechnik, Kumulierter Energieaufwand Begriffe, Definitionen, Berech-

nungsmethoden: Cumulative Energy Demand Terms, Definitions, Methods of Calculation.

VDI-Richtlinien, 4600 (Beuth, Berlin, 1997)

A. von Gleich, Outlines of a sustainable metals industry, in Sustainable Metals Management:

Securing Our Future – Steps Towards a Closed Loop Economy, ed. by A. von Gleich, R.U.

Ayres, S. Goßling-Reisemann. Eco-Efficiency in Industry and Science, vol. 19 (Springer,

Dordrecht, 2006), pp. 3–39

Wuppertal Institut, MIPS Online (2011), http://www.wupperinst.org/en/projects/topics online/

mips/index.html. Accessed 28 May 2011

goessling2013_thermodynamicsandresourceconsumption

Documents