Biooprocesos Necesidades de Modelado Para La Evaluacion Del Proceso y La Sostenibilidad

8/16/2019 Biooprocesos Necesidades de Modelado Para La Evaluacion Del Proceso y La Sostenibilidad

1/9

Computers and Chemical Engineering 34 (2010) 1009–1017

Contents lists available at ScienceDirect

Computers and Chemical Engineering

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p c h e m e n g

Review

Bioprocesses: Modeling needs for process evaluation and sustainabilityassessment

Concepción Jiménez-González a, John M. Woodley b,∗

a GlaxoSmithKline, Sustainability and Environment, 5 Moore Drive, CS.1152, Research Triangle Park, NC 27709-3398, USAb Center for Process Engineering and Technology, Department of Chemical and Biochemical Engineering, Technical University of Denmark,

Søltofts Plads, DK-2800 Lyngby, Denmark

a r t i c l e i n f o

Article history:Received 3 September 2009

Received in revised form 14 March 2010

Accepted 17 March 2010

Available online 25 March 2010

Keywords:

Bioprocesses

Biocatalysis

Fermentation

Modeling

Simulation

Life cycle assessment (LCA)

Environmental footprint

Sustainability

a b s t r a c t

The next generation of process engineers will face a new set of challenges, with the need to devise newbioprocesses, with high selectivity for pharmaceuticalmanufacture, and for lower value chemicals man-

ufacture based on renewable feedstocks. In this paper the current and predicted future roles of process

system engineering and life cycle inventory and assessment in the design, development and improve-

ment of sustainable bioprocesses are explored. The existing process systems engineering software tools

will prove essential to assist thiswork. However, the existing tools will also require further development

suchthat they can also be used to evaluate processes against sustainability metrics, as well as economics

as an integral part of assessments. Finally, property models will also be required based on compounds

not currently present in existing databases. It is clear that many new opportunities for process systems

engineering will be forthcoming in the area of integrated bioprocesses.

© 2010 Elsevier Ltd. All rights reserved.

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1009

2. Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1010

3. Industrial biotechnology processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1010

3.1. Fermentation processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1010

3.2. Microbial catalysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1011

3.3. Enzyme processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1011

4. The role of process systems engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1011

4.1. Evaluation of process options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1011

4.2. Evaluation of platform chemicals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1012

4.3. Process integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1012

4.4. Biorefinery design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1012

4.5. Biocatalyst design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1012

5. Assessing the sustainability of bioprocesses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10135.1. Life cycle inventory and assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1014

6. Mapping modeling needs of bioprocesses—an example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1015

7. Future outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1016

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1016

R e f e r e n c e s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1016

∗ Corresponding author.

E-mail address: [email protected] (J.M. Woodley).

1. Introduction

Process systems engineering offers many tools for the chemi-

cal engineer. Today, for example, modeling, simulation and process

evaluation tools are routinely applied to optimization problems in

0098-1354/$ – see front matter © 2010 Elsevier Ltd. All rights reserved.

doi:10.1016/j.compchemeng.2010.03.010

http://www.sciencedirect.com/science/journal/00981354http://www.elsevier.com/locate/compchemengmailto:[email protected]://localhost/var/www/apps/conversion/tmp/scratch_6/dx.doi.org/10.1016/j.compchemeng.2010.03.010http://localhost/var/www/apps/conversion/tmp/scratch_6/dx.doi.org/10.1016/j.compchemeng.2010.03.010mailto:[email protected]://www.elsevier.com/locate/compchemenghttp://www.sciencedirect.com/science/journal/00981354


2/9

1010 C. Jiménez-González, J.M. Woodley / Computers and Chemical Engineering 34 (2010) 1009–1017

the bulk chemicals and fuels sector, where small process improve-

ments yield significant economic returns. In the last 20 years

bioprocesses have become more common. In particular they have

found application in the production of high value products such as

pharmaceuticals (and their intermediates). The process engineer-

ing emphasis in these cases is on rapid process implementation

(rather than optimized development). However, in recent years

bioprocesses have also been applied to bigger volume products

such as fine chemicals, bulk chemicalsand fuels.In these cases pro-

cess improvement is the emphasis since this will yield significant

returns. In addition to the direct process improvements, biopro-

cesses have also frequently been justified on the basis that they

are processes with potentially lower environmental impact than

their chemical synthetic counterparts. The main synthetic oper-

ations in bioprocesses include fermentation, microbial catalysis

and enzyme catalysis. Downstream options are dependent on the

nature of the product (macromolecular or low molecular weight

compounds (‘small molecules’)). Small molecules are frequently

processed in a similar way to other chemical products, although

dilute aqueous solutions bring specific problems which need to be

addressed,both fromthe viewpoint of process optimizationand the

environmental footprint. For instance, the downstream processing

of some small molecule bioprocesses could include large amounts

of organic solvents for extraction from aqueous solutions. In thesecases, the organic solvents require processing, recycle, control and

ultimately safe disposal. Macromolecules require more specialist

operations such as filtration or chromatography. However, in all

cases the molecules are frequently sensitive to extremes of pH and

temperature, placing specific restrictions and constraints on pro-

cessing methods. Biocatalyst recovery (frequently for recycle) also

necessitates filtration and centrifugation.

From this discussion it is clear that engineers and others

involved in implementing new processes need to address a range

of questions. For example: when should a bioprocess, rather than a

chemical process, be implemented? If a bioprocess is to be imple-

mented, can the existing infrastructure (feedstock, utilities and

plant) be used? How can process plant be adapted for different

biomass in different geographical regions? What is the optimumbiorefinery? What options exist for process integration? What are

the environmental, health andsafety issues of bioprocesses in com-

parison with chemical processes? What is the environmental foot-

printof a bioprocesscomparedwith its chemicalcounterpart? How

can bioprocesses be designed to maximize process efficiency, min-

imize environmental impact, as well as maximize sustainability?

Many of these questions can currently be addressed qualita-

tively, but to have real value it is necessary to assess the questions

on a quantitativebasis. In order to achieve thiseffectively therefore,

computer-based tools are required. Over the last decades, process

systems engineering has already developed many of the appropri-

ate tools. Nevertheless, some further developments are required.

Forexample,in the case of bioprocessesan extra optionavailable to

the engineer is the improvement of the catalyst itself. This requiresmodels which takeinto accountcatalyst properties. In addition, one

can see life cycle inventory and assessment (LCI/A) modeling tools

and methods as a logical extension of process systems engineer-

ing.LCI/A methodologiesallow for the estimation of environmental

impactacross theentire life cycleof a process or product. LCI/A esti-

mations rely heavily on the characterization of the process and its

unit operations using process systems engineering modeling and

simulation techniques.

Hence we are nowat the point where process engineering tools

need to be applied to the complete set of bioprocesses, includ-

ing pharmaceuticals, fine chemicals, bulk chemicals and fuels. In

this paper the specific role of process systems engineering and life

cycle inventory and assessment in the development, design and

improvement of sustainable bioprocesses will be discussed.

2. Scope

Biotechnology is an enormous sector of industry from high

value, low volume products(such as pharmaceuticals)to low value,

high volume products (such as biofuels). To date the majority of

implemented bioprocesses have focused on the former group. The

emphasis here has been on implementing processes effectively to

meetthe tough regulatory demands placed on suchproducts. Rapid

process implementation, rather than optimization, has been the

necessary focus of process engineering (e.g. Pollard & Woodley,

2007; Woodley, 2008). The latter group of bio-based products (and

associated processes), represent a different challenge. These are

the new sectors of industrial (also called ‘white’) biotechnology

where new opportunities exist for alternative feedstocks based on

renewable resources such as biomass and clean processes with

reduced solvent inventories, renewable catalysts and mild con-

ditions for reaction and separation (e.g. Dale, 2003). Here there

remain some significant hurdles to achieve full-scale implemen-

tation. For example, for cost-effective synthesis one can start from

fermentation of starch or sugars (ultimately from biomass given

suitablycost-effective pretreatment). However, fermentationby its

very nature is a ratherinefficient process with a significant amount

of substrate/reactant required for cell energy, cell growth and

other products. This inherent weakness foruse in chemicalsynthe-sis has stimulated genetic and metabolic engineering methods to

improve strains. A parallel development with protein engineering

has developed around enzymatic catalysis. Furthermore, the new

‘bio-economy’ will require the development of a suitable infras-

tructure and, like the oil-based counterpart will demand very high

yield processes meaning that process engineering for the future

implementation and development of these processes will have an

increasingly important role, alongside the biological methods for

biocatalyst improvement. In addition, the timely identification of

environmental, healthand safety issues to be managed will be cru-

cial to facilitate the development of sustainable bioprocesses. Most

importantly it is imperative that any claims of ‘greenness’ are con-

sidered in the wider framework of sustainability. Attempting to

assess and compare the sustainability of bioprocesses must have aholistic scope based on life cycle thinking, which is strongly based

on the output of systems engineering modeling and simulation

techniques. Given the maturity of thefield of process systems engi-

neering it is clear thatmany newopportunitieswill be forthcoming.

3. Industrial biotechnology processes

Three major types of bioprocess can be identified dependent on

the nature of the biocatalyst. These are outlined beneath and the

key process features are outlined in Table 1.

3.1. Fermentation processes

For a significant number of chemicals, the use of fermenta-tion has become a standard alternative to fossil-based feedstocks

and technology. Nevertheless the possibility of growing microbial

cells on a variety of sugars (derived from renewable biomass) has

re-invigorated interest in this area. The consequence is that fer-

mentationat a large-scale will become more commonin the future

chemical industry. Many different types of fermentation process

(using different strains to produce different products) can take

place in thesame process plant which is a significant advantage. The

plant is relatively simple and the challenges lie in adequate mixing

(sometimes withmaterials havingcomplexrheology),suitableoxy-

gen input (for aerobic processes)and process control. Downstream,

the separation process depends on the product, but will nearly

always need to avoid high temperatures and extremes of pH. The

solvent is water, meaning that thedilute product streamcombined


3/9

C. Jiménez-González, J.M. Woodley / Computers and Chemical Engineering 34 (2010) 1009–1017 1011

Table 1

Process features of the three major types of bioprocess for chemicals production. (I) represents options for immobilized enzyme.

Feature Fermentation Microbial catalysis Enzymatic catalysis

Yield on substrate Low Medium High

Catalyst recycle Potentially via a continuous process Via filtration Via immobilization

Reactor options Stirred tank Stirred tank Stirred tank

Bubble column Bubble column Packed bed (I)

Fluidised bed (I)

Membrane

with the presence of many other products presents a significant

process engineering challenge. Both large molecular weight and

low molecular weight products can be made by fermentation. The

processes either focus on low molecular weight productswhich can

subsequentlybe used as platform chemicals or fuels or high molec-

ular weight compounds such as enzymes (for application in a range

of industries, including detergents, textiles and foodingredients)or

therapeutic proteins.

3.2. Microbial catalysis

In fermentation, by definition, the catalyst is growing during the

process. This means that some of the reactant (or substrate) willinevitably be diverted from the product towards the catalyst, low-

eringthe yield. An alternative (fornon-growthassociated products)

is to grow the cells first and subsequently carry out the reaction

to increase the yield. This also enables the possibility of growth

and reaction on different substrates (reactants) or under different

conditions (such as temperature or pH) in each stage. Likewise the

optimal cellconcentrationfor conversion canbe selected(Woodley,

2006) after growth and suitable media for effective product recov-

ery have been chosen. For processes requiring oxygen it can be

highly important to select the optimal cell concentration in order

to avoid mass transfer limitations. Several tools are now available

for evaluating the oxygen supply issues in such reactions (Baldwin

& Woodley, 2006; Law, Baldwin,Chen, & Woodley, 2006). The three

potential routes using microbial catalysis are shown in Fig. 1.

3.3. Enzyme processes

The presence of so many products at the end of fermentation

or microbial catalysis is a consequence of the complexity of cells,

where manyenzymescatalyze reactionsgiving a spectrumof prod-

ucts as well as decreasing the yield of the desired product on

the reactant. An alternative, for short pathways, is to isolate the

enzymes and then immobilize them on a solid support or behind

a membrane or via aggregation, such that they are large enough

and have the right properties to be recycled (like a heterogeneous

catalyst). In this way a yield of product on the catalyst of around

5–10tonnes/kg immobilized biocatalyst can be achieved, which

typically enables industrial implementation. Such an approach has

been widely used to assist in the synthesis of high value com-

pounds such as pharmaceuticals and a more limited number of

well-known lower value products such as high fructose corn syrup

(HFCS). Many of theseprocesses have also been modeled (e.g.Chen,

Baganz, & Woodley, 2007). Enzymatic processes can also be carried

out using soluble enzymes (i.e., non-immobilized), although these

present challenges in terms of separating and recycling the cat-

alysts (enzymes) when compared with the immobilized enzyme

processes.

4. The role of process systems engineering

4.1. Evaluation of process options

For some higher value products a bioprocess may be the only

route to a given product (to ensure correct folding of a therapeutic

protein for example or the synthesis of an optically pure phar-

maceutical intermediate). However, the more usual situation is

that there are other competing routes to the same product. There-

fore, for now, biotechnology is just one of a number of options

for the production of chemicals and fuels. The economic drivers

for implementation depend on existing infrastructure, feedstock

costs, feedstock availability as well as the efficiency of the relevant

(bio)catalyst and (bio)process technology. At the same time, there

are environmental drivers and, in the wider sense, sustainability

drivers for the selection of different process alternatives.

One example of the current applications of process systemsengineering is the estimation of global warming potential and the

design of processesthat minimizethis impact.Glasser, Hildebrandt,

Hausberger, Patel, and Glasser (2009) f or instance have recently

proposed using process systems engineering tools such as mass

and energy balances, thermodynamics and process work balances

to minimize energy use and green house gas equivalents. This is an

example of howprocess system engineering togetherwith thermo-

dynamics can be used to set metrics and targets against important

aspects or impacts. It is also an example of current methodolo-

gies that tend to focus on one impact andits corresponding leading

metric (in this case, energy consumption).

However, the sustainability drivers normally cover several

impacts and are by no means simple, as they require the balance

of different sets of goals and metrics that can present trade-offs in

Fig. 1. Alternative process scenarios for use of microbial cells for non-growth associated biocatalysis. (Route 1—combined fermentation and microbial catalysis; Route

2—fermentationseparated frommicrobial catalysis;Route3—fermentation separatedfrommicrobialcatalysis withintermediateprocessingto change catalystconcentration.)


4/9


some cases. Objective functions to be optimized should not exclu-

sively be basedon economics but increasingly alsoon sustainability

metrics (e.g. Henderson, Jimenez-Gonzalez, Preston, Constable, &

Woodley, 2008) and integrated with life cycle analysis. This will

need to include evaluation of feedstocks and products as well as

processes, including energy and mass integration. This presents a

fascinating set of alternative routes and technologies from a given

feedstockand/or to a given product(s). Process systems engineering

has a particular role to enable such evaluations on a quantitative

basis, notonly fromthe process perspective, butalso fromthe wider

sustainability aspect. Quantitation is key since it enables rigorous

comparisons and assessments, which build confidence in decision-

making. Process systems engineering also brings the advantages

of rapid computational methods. Such simulations allow alterna-

tives to be quickly evaluated. This is important to enable the use of

toolsearly in process and product development.Finally,the answer

in a specific case to the problem formulated here will in addition

depend on regional factors. Feedstock availability and cost is highly

dependent on geographical location. A parallel set of evaluations

concerning the need to retrofit existing plant, or build new plant,

is also required.

4.2. Evaluation of platform chemicals

While the increasing cost of oil is driving particular interest

in the production of new fuels from biomass there is little doubt

that today of equal importance is the production of chemicals from

biomass. Indeed for thesupply of fuels in the future there are many

potential sources aside from biomass. In a world with limited (or

very expensive) oil it is less clear where the chemicals of the future

will originate. Thereis currently an existing infrastructure basedon

the use of the seven established platform chemicals (toluene; ben-

zene; xylene; 1,3-butadiene; propylene; ethene; methane). In the

short term onecould consider if we can use the same infrastructure

andjust create the seven chemicals from alternative sources. How-

ever, in thelonger term it will be necessaryto devisenew processes

based on a different set of platform chemicals. One group will be

based around glucose (the hydrolytic product of starch and cellu-lose and therefore readily available from biomass). In a biorefinery

itwillbe necessaryto develop a structurewhich canmanagea range

of feedstocks, a range of technologies and a range of products. This

presents a considerable challenge for design and optimization as

well as process integration. An interesting example which illus-

trates the complexity and the challenge that lies ahead is the use

of glucose or fructose to produce 5-hydroxymethylfurfural (HMF)

or 2,5-furandicarboxylic acid (FDA) (Boisen et al., 2009). Greatest

value is obtained by going the whole way from glucose to FDA.

However even in this small reaction pathway there are many alter-

native technologies.Some canbe integrated together,some givethe

required yield and selectivity, some are difficult to implement and

others are untested at scale. This illustrates very well the challenge

that design engineers face.

4.3. Process integration

The primary solvent for most bioprocesses, with a few excep-

tions, is water. Consequently the downstream process is frequently

difficult and this is emphasized by the need to carry out sepa-

rations at moderate temperatures. Given the dilute nature of the

streams it is frequently the case that the majority of the costs

and environmental, health and safety impacts are therefore in the

downstream process. The dilute nature of the streams has his-

torically also driven the need for energy-intensive separation. For

instance, in some fine chemical and pharmaceutical applications

of biocatalysis, large amounts of organic solvents may be used in

the extraction and purification of products from an aqueous biocat-

alytic reaction stream. For higher volume products, such as liquid

fuels, removal of water becomes an essentialrequirement to reduce

costs and avoid transporting significant amounts of water. In other

cases the product may be integrated within a biorefinery concept

although at some point water will need to be removed. Conse-

quently the integration of water use, and reuse via recycle, is an

essential part of the design of industrial bioprocess facilities. In

addition, bioprocesses need to be designed with process synthesis

and process integration approaches, thus avoiding a process that

is efficient in one part and inefficient in another. Existing tools of

mass and energy integration such as pinch technology will have

an important role. The issue of water integration in a biorefinery

is in many ways analogous to the issue of heat integration in a

conventional refinery.

4.4. Biorefinery design

Two major types of biorefinery have been identified for the

future, based on lignocellulose biomass utilization to provide a

range of sugars (for subsequent (bio)catalysis or fermentation) and

oil-basedmaterial(from biomass).In eachcase thecurrentresearch

emphasis on biorefineries is to ensure all the fractions of a par-

ticular biomass in a given situation are fully exploited. Likewise

the development of downstream products is now being explored.For example glycerol (as a byproduct of biodiesel production) can

be used as a platform chemical (for example via fermentation to

produce 1,3-propanediol). Another interesting example concerns

the production of bio-ethanol. This is widely developed as a fuel

although there is considerable economic incentive for develop-

ing a range of other products (e.g. acetic acid) from ethanol, in

other words using it as a platform chemical ( Rass-Hansen, Falsig,

Jørgensen, & Christensen, 2007). It is clear that evaluating integra-

tion of product and feed streams in this way, as well as the use of

products as fuels or platform chemicals will be an important role

for process systems engineering.From thesustainability viewpoint,

the utilization of lignocellulosic material has perhaps the highest

desirability, since these materials are typically of low value as a

waste from other processes (e.g. bagasse). There is little doubt thatthe increasing range of technologies and opportunities as a result

of enzyme-basedor fermentation-basedcatalysis willgive complex

integration problems, which may require new tools.

4.5. Biocatalyst design

A particular feature of bioprocesses is the use of biocatalysts,

which may exist in several forms as indicated earlier and where

options existfor modification.At thesimplestlevel as a protein (iso-

lated enzyme), the options for swapping amino acids via protein

engineering exist. New enzymes which have been modified may

display newtolerance to reactor conditions such as temperature or

pH and may also have improved selectivity or reactivity (activity)

on a given (non-natural)substrate or reactant. Order-of-magnitudeimprovements have been found in a number of cases although

understanding the most effective method of making changes to

the enzyme depends on past precedent and, to some extent, struc-

tural knowledge (e.g. Hibbert et al., 2005). In the case of microbial

catalysts, individual enzymes can be over-expressed (increasing

reactionrate of a given cell) andthe regulatory control scheme fixed

to direct the carbon to giveimproved ratesand yields (viametabolic

engineering). Some start has also been made to the development

of pathways where enzymes coming from a variety of sources are

clonedintosingle host to make a newpathwayvia a combination of

genetic engineering and de-novo pathway engineering (e.g. Chen et

al., 2006). In all these areas it is clear that those involved in process

systems engineering need to inform the biological engineers about

what is required in a given case and setsuitabletargets.Philosophi-


5/9


Fig. 2. The three spheres of sustainability through a triple bottom line assessment.

cally it is interesting to notethat process implementation maycome

via process improvements or alternatively via catalyst improve-

ments. In many cases both will be required. Understanding the

necessary balance between these areas, as well as their integra-

tion with each other will be important for the future development

of the field. Process systems engineering is particularly powerful in

its ability to predict and can therefore be used to direct decision-

making and process development.

5. Assessing the sustainability of bioprocesses

As discussed before, bioprocesses have frequently been high-

lighted as greener chemistry or engineering, since they address

many of the green chemistry and green engineering principles

(Anastas & Warner, 2000) by offering reactions that are potentially

more atom economic, operate under mild conditions, use mostly

non-hazardous chemicals and have less protection/deprotection

steps. However, this tends to be true mostly when looking at

the reaction part of the process, in other words, the biocatalysis.

However, it cannot be generalized when analyzing the entire pro-

cess that in some cases may include the use of a large amount of

organic solventsfor downstream processing. Thisis one of the areas

in which systems engineering, in conjunction with a transparent

application of life cycle inventory and assessment methodologies

can (and must) play a pivotal role.

Determining whether a process is sustainable (or ‘green’) is by

no means a simple feat. It is more akin to a multi-variable opti-

mization that is very familiar to systems engineers, and for which

several proposals and methods have been presented (Carvalho,

Gani, & Matos, 2006;Gani, Jørgensen, & Jensen, 2005; Grossmann &

Daichendt, 1996; Uerdingen, Gani, Fisher, & Hungerbuhler, 2003).

For an objective assessment of the sustainability of a process, there

is the need to utilize the tools that system engineers have devel-

oped duringrecentyearsand apply them with a life cycle approach.

It is necessaryto move from thebasicanalysis of the biocatalysis by

itself (or reactions) and discreet unit operations (separations) anduse a systems engineering approach. This implies utilizing multi-

variate optimization techniques coupled withlife cycle assessment

methodologies for a more objective analysis of their ‘greenness’ or

sustainability. This would allowus to develop bioprocesses thatare

sustainable by design, in such a way that they:

• optimize the use of material and energy resources,• eliminateor minimize environment,health and safety hazards by

design, and• integrate life cycle thinking in the design.

In a more general sense, sustainable bioprocesses in particular,

and processes in general are/will be the processes that:

• minimize environmental impacts,• are economically viable, and• are socially responsible (OECD, 2002).

Analyzing and comparing sustainability will require a com-

prehensive assessment that balances the three different spheres

of sustainability (see Fig. 2). This can only be achieved through

a multi-variate optimization that will account for environmentalperformance, economic viability and social responsibility (which

includes health and safety aspects). In addition, these assessments

needto leveragethe toolsof systems engineeringto ensure theinte-

gration of a holistic approach that considers the entire life cycle of

the process.

Another important concept when assessing the efficiency and

the sustainability of processes is the differences between new

process performance and retrofit performance. For instance, in

comparing the sustainability or performance of a well-known pro-

cess with a new bioprocess, a situation that one often encounters

is the fact that initially, the new process may not have the same

levelof performance as the established technology, mainly because

they areat differentpoints in the development curve, andtherefore

the new process is sub-optimal. On the other hand, the establishedprocess can be retrofitted to increase its performance. Retrofitting

and new process development is not a new concept from the sys-

tems engineering viewpoint. However, additional modeling work

is needed to estimate the achievable performance limits of a

fully developed process and an established process that under-

goesretrofit.This willallow moremeaningful comparisons without

unnecessarily penalizing the new process for its lack of develop-

ment, or the established process for the lack of timely retrofitting.

Inthe recentpasttherehavebeenmanyattemptsto measure the

‘greenness’ of syntheticroutes, and the approaches have generated

a seriesof ‘greenmetrics’. Most of theapproacheshavesearchedfor

a simple metric in an attempt to provide a low resolution view of

how‘green’ is a givenprocess.E-factorwasone ofthe first measures

of greenness proposed to highlight the amount of waste gener-atedin order to produce 1 kg ofproduct (Sheldon, 1992, 2007). This

metric, while simple to understand, has several key drawbacks by

focusingon waste instead of efficiency, neglecting a viewof thetype

of waste generated, notaccountingfor the relative impacts, and the

lackof life cycle thinking. For instance, bioprocesses have in general

large amounts of wastewater produced, which would indicate an

extremely large E-factor, but at the same time the actual impact of

the effluent mightnot beas largeas anE-factorwould suggest,since

the waste is relatively benign. Additional metrics have focused on

efficiency, especially on mass efficiency (or its inverse, mass inten-

sity) which addresses the first part of the disadvantages of the E-

factor (Constable, Curzons, & Cunningham, 2002; ACS GCI PR, 2008;

Constable, Jimenez-Gonzalez,& Lapkin, 2008). However,it has been

widely recognized that measuring the sustainability or even the


6/9


‘greenness’ of a process is a multi-objective optimization problem

that must take into consideration the efficiency of the entire pro-

cess regardingthe useof mass and energy, the environment, health

and safety characteristics of materials, and the inclusion of life cycle

thinking amongst others (Constable et al., 2001).

Some efforts have been made to comprehensively address and

compare the sustainability of processes in general and biopro-

cesses in particular. These methodologies have been employed in

some instances to assess the sustainability, environmental, health

and safety aspects of bioprocesses (Cowan, Oxenbøll, & Holm,

2008; Jimenez-Gonzalez, Constable, Curzons, & Cunningham,

2001; Jimenez-Gonzalez,Constable, Curzons,& Cunningham,2002;

Jodicke, Zenklusen, Weidenhaupt, & Hungerbuhler, 1999; Kim &

Dale, 2005, 2006; Kim, Jimenez-Gonzalez, & Dale, 2009; OECD,

2002; Patel et al., 2006; Wolf, 2005). These methodologies attempt

to measure the sustainabilityof bioprocesses and in some instances

they compare bioprocesses with their chemical alternatives.

For instance, a technology comparison framework ( Jimenez-

Gonzalez et al., 2002) that accounts for environment, health, safety

and life cycle assessment impacts, was used to compare the estab-

lished chemical process and a two-enzyme biocatalytic process

for the production of 7-ACA (Henderson et al., 2008). The con-

clusion of this assessment was that the bioprocess was ‘greener’

when compared with the chemical process. This was driven bythe fact that the chemical process uses more hazardous materials,

requires about 25% more process energy than the enzymatic pro-

cess and, has a larger life cycle environmental impact: for instance,

uses approximately 60% more energy, 16% more mass (excluding

water), has double the greenhouse gas impact andabout 30%higher

photochemical ozone creation potential and acidification potential

impacts. However, although this type of assessment is useful and

more common as time passes, there is an ongoing need for mod-

eling methodologies that will seamlessly integrate sustainability

factors during bioprocess design and development. Normally eco-

nomic factors are an integral consideration, and since the 1970s

environmental factors at the unitoperationand sometimes process

levels have been considered. Nevertheless the need for integrat-

ing and embedding sustainability principles into bioprocess designstill remains an area of opportunity for process engineers. Systems

thinking and systems engineering are the skill and the discipline

that will need to play an important role to make this happen, and a

holistic view of bioprocesses and their interrelations will be imper-

ative.

5.1. Life cycle inventory and assessment

Oneof thetools to analyze systems holistically is lifecycle inven-

tory and assessment (LCIA). LCIA is a methodology used to evaluate

the environmental profile of an activity or process from the extrac-

tion of raw materials to its end-of-life. The resource consumption

and emissions are inventoried and assessed from the perspective of

extraction of raw materials, production, transportation, sales, dis-tribution, use, and final fate (Fig. 3). Depending on the goal and

scope of the assessment, the boundaries can be set differently; for

instance a ‘cradle-to-gate’ assessment might be adequate when

comparing two alternative processes to the same product; or a

‘gate-to-grave’ assessment may suffice when comparing two dif-

ferent end-of-life technologies. The results of these assessments

can be reported as direct inventory data (for example life cycle

energy, life cycle mass, life cycle emissions), measures of individual

potential impacts (such as global warming or acidification), or as

an aggregatescore or index forhigh-levelcomparison (for example

Eco-Indicator 99). LCIA methodologies and standards are described

in detailin theliterature (CML, 2002; Heijungs, 1992; Hendrickson,

Lave, & Matthews, 2006; ISO, 1997, 2006; PRé Consultants, 2001;

US EPA, 2003).

Fig.3. Lifecycle assessment to evaluate theenvironmentalprofileof a process from

the extraction of raw materials, production, transportation, sales, distribution, use,

and final fate.

LCIA methodologies are in a way an extension of systems engi-

neering and provide a directly applicable framework to assessthe sustainability of processes. In addition to the traditional envi-

ronmental life cycle assessment (which has increasingly included

health and safety impacts), life cycle costing (LCC, or total cost

assessment, TCA) and the more recent social life cycle assess-

ment (SLCA) attempt to complete the holistic view of sustainability

(Heinrich, 2006; Hochschorner & Finnveden, 2006; Hunkeler &

Rebitzer, 2005; Jørgensen, Le Bocq, Nazarkina, & Hauschild, 2008;

Jørgensen, Hauschild, Jørgensen, & Wangel, 2009; Klöpffer, 2003;

Rebitzer & Seuring, 2003).

In the area of bioprocesses, the application of LCIA is still not a

widespread practice. There are however, examples on how several

practitioners have applied LCA metrics primarily usingcase studies

to better understand the wider environmental implications of bio-

processes and to compare them with chemical routes. This typeof assessment has provided some key insights, such as the role

of separations, a more systematic and holistic method to evalu-

ating waste impacts, and the nuances of renewability (Cowan et

al., 2008; Kim & Dale, 2005, 2006; Patel et al., 2006; Vink, Rabago,

Glassner, & Gruber, 2003; Wolf, 2005). For instance, a comparison

of a process using metal catalysts and one using biocatalysts for

the enantioselective reductionof ketoestersin pharmaceutical syn-

thesis was performed using a streamlined LCIA methodology. The

analysis identifiedunit operations and reaction conditions thathad

the largest significance on the impact of the synthesis. It was also

concluded that whether the metal catalysts were better than bio-

catalysts depended mainly on the work-up from the use of organic

solvents and energy-intensive steps ( Jodicke et al., 1999).

One typical example of the application of LCIA is the relation-ship of bioprocesses and the utilization of renewable resources.

While the use of renewable resources is indeed a goal from a

sustainability viewpoint, there is more complexity in evaluating

‘renewability’. For example, there are the material resources and

the energy required to produce renewable materials, whichin turn

may (or may not) be renewable. There might also be other envi-

ronmental impacts such as the use of toxic compounds such as

herbicides that might pose environmental trade-offs. Therefore it

is necessary to assess renewability from a life cycle standpoint.

For instance, desired materials that are extracted from plants may

be separated using organic solvents, and then isolated from the

extraction solvent through a series of purification steps (for exam-

ple additional solvent extraction or distillation). Another example

is the proportion of non-renewable feedstocks as part of a material


7/9


supply chain and the contribution of those feedstocks to the over-

all renewability of the materials used in a bioprocess. For instance,

the production process of furfural based on biomass utilizes mate-

rials such as sulfuric acid, methanol or carbon monoxide which are

often derived from fossil sources; in addition to the energy which

is sourced from renewable and non-renewable energy carriers. A

further factorto consider is the potentialcompeting useof land and

the impact derived from potential land-use change, which at this

time is an area of ongoing debate (Fargione, Hill, Tilman, Polasky,

& Hawthorne, 2008; Kløverpris, Wenzel, & Nielsen, 2008).

Developing life cycle inventories and assessing the LCIAimpacts

of bioprocesses is not a simple endeavor given the large amount

of data needed from different sources. The more materials that are

involved in thebioprocesses, the more life cycleinventory data will

need to be collected, verified and analyzed. On the other hand, the

life cycle inventory data for biomaterials is not always available.

While there have been efforts to increase the body of knowledge of

life cycle inventories and impacts of bioprocesses and materials

either derived from biomass or needed in bioprocesses, consid-

erable challenges remain. These challenges have influenced the

development and use of streamlined life cycle assessment method-

ologies and ab initio modeling approaches to estimate the life cycle

impacts of bioprocesses and bio-derived materials. This is precisely

oneof theopportunitiesfor systems engineeringto addvalue, as thedevelopment of reliable,consistent,transparent, accurateand easy-

to-use modeling and streamlined techniques for LCIA will continue

to be an important need to be able to routinely assess the sustain-

ability of bioprocesses.

In the future, the development of true sustainability assess-

ments,with an embedded LCIA approach will be necessary, aligned

with the early modeling needs highlighted in this article. In order

to routinelyassess sustainabilityof bioprocesses and to embedsus-

tainability principles into bioprocess design and development, the

following modeling needs can be highlighted:

• Better deterministicmodelsof unitoperationsthat arepart of bio-

processes, such as fermentation, biocatalysis. This would need to

include fundamental design parameters to design more resourceefficient bioprocesses.

• Development and enhancement of property prediction pack-

ages that would facilitate estimations of resources (e.g.

energy requirement) and the utilization of optimization

techniques.• More extensive use of process integration techniques on biopro-

cesses, especially at the development phase.• Better understanding of life cycle inventory and impacts of bio-

processes and bio-derived materials.• Increased understanding of the uncertainties in modeling bio-

processes, both from the viewpoint of process design and

sustainability assessment.• Improved consistency and transparency of LCIA methodologies

as applied to bioprocesses.• Improved streamlined LCIA methodologies that are easy to use

by academia and industry alike.• More routine application of multi-objective optimization tech-

niques for sustainability assessments of bioprocesses.• Enhanced understanding of the interactions of the environmen-

tal,social and economicaspects of bioprocesses for a holisticview

of sustainability.

Addressing these modeling and process understanding needs

will make it possible to integrate sustainability principles into pro-

cess design and development in a far more rigorous manner.

6. Mapping modeling needs of bioprocesses—an example

Henderson et al. (2008) compared the chemical process and a

two-enzyme biocatalytic process for the production of 7-ACA. We

have discussed briefly the results of the assessment in terms of

the life cycle impacts of both synthetic routes. We will now use

that example to map some of the modeling needs of bioprocesses

discussed in this paper.

Fig. 4 depicts the different phases evaluated in the assess-

ment, which include the extraction of the raw materials and the

production processes with their corresponding energy and waste

treatment requirements. As can be seen in Fig. 4, the production of

the final API, formulation, distribution, use and end-of-life consid-

erations are not included in the assessment.

In terms of models used for rawmaterials, the life cycle impactsof the materials was modeled using a combination of life cycle

inventory data developed by ab initio methodologies based on

chemical engineering methods and principal component analysis

Fig. 4. Use of models in the 7-ACA evaluation (Henderson et al., 2008).


8/9


to fill the data gaps. For most common chemicals and solvents,

most of the life cycle information was available. However, for the

bioprocess, as mentioned above, the availability of life cycle inven-

tory data of substrates, enzymes and feedstocks was limited and

remains under development.

The information describing the production processes was in its

entirety taken from process descriptions, internal reports, batch

records and process data, and no models were used. This type

of data was available since the bioprocess had been run at the

commercial scale. However, if the same type of comparison was

intendedto berepeatedwitha process ineither a conceptual design

stage or a process with limited development, it would not be pos-

sible given the lack of models.

Relatively standard models were available and used to estimate

the life cycle impacts of energy production and waste treatment.

The waste amounts and compositionswere estimatedbased on the

process descriptions using mass balances directly. Energy require-

ments were also estimated based on process descriptions using

typical heat transfer models. To calculate energy requirements,

pure component physical property data gaps (e.g. heats of forma-

tion) were estimated using molecular modeling based on group

contribution methods, specifically the Marrero and Gani method

(Marrero & Gani, 2001). Nevertheless, there remains a need to

increase the accuracy of the models to estimate pure componentproperties for complex molecules and enzymes.

7. Future outlook

The development of newbioprocesses as a complement to exist-

ing chemical and fuel production methods is an exciting endeavor

that will occupy many process engineers in the future. There will

be a particular role for process systems engineers in this devel-

oping sector with the advantages of quantitative decision-making

toolsand rapid simulation thatthis brings, including process design

and sustainability principles. In the future suitable models will

inform developments at the infrastructural level (evaluation of

biorefineries, feedstocks and integration), the process level (evalu-

ation of alternative technologies and process integration) as wellas the catalyst level (evaluation of alternatives for protein and

metabolic engineering). In addition, these models will allow the

integration of sustainability principles into process design and

development.

The further development of process systems engineering tools

(including property prediction packages and the development of

a database for bio-based molecules) will be required. To rou-

tinely assess sustainability of bioprocesses will require as well

more robust and transparent environmental life cycle inventory

databases of bio-derived materials; as well as better modeling

and understanding of the social and economic aspects of sus-

tainability and their relationships. Finally, an increasing dialogue

amongst the biochemical engineers, biologists and other disci-

plines with related areas of expertise will be necessary to enablethe vision of sustainable industrial biotechnology to be fully

exploited.

Acknowledgements

The authors wish to thank GlaxoSmithKline’s Biotransforma-

tions Team in general, and Peter Sutton, JosephAdamsand Andrew

Collis in particular for their contributions, input andsupport to this

article and the development of bioprocesses.

References

A.C.S./G.C.I. P.R.(2008).AmericanChemical Society,GreenChemistry Institute, Phar-

maceutical Roundtable website www.acs.org/greenchemistry.

Anastas, P. T., & Warner, J. C. (2000). Green chemistry: Theory and practice . Oxford:Oxford University Press.

Baldwin, C. V. F., & Woodley, J. M. (2006). On oxygen limitation in a whole-cellbiocatalytic Baeyer–Villigeroxidation process. Biotechnologyand Bioengineering ,95, 362–369.

Boisen, A., Christensen, T. B., Fu, W., Gorbanev, Y. Y., Hansen, T. S., Jensen, J. S., et al. (2009). Process integration for the conversion of glucose to2,5-furandicarboxylic acid. Chemical Engineering Research and Design, 87 ,1318–1327.

Chen, B. H., Baganz, F., & Woodley, J. M. (2007). Modelling and optimisation of atransketolasemediatedcarbon–carbon bondformationreaction. Chemical Engi-

neering Science, 62, 3178–3184.Chen, B. H.,Sayar, A.,Kaulmann, U.,Dalby, P.A., Ward, J. M.,& Woodley, J. M. (2006).

Reaction modelling and simulation to assess the integrated use of transketo-lase and -transaminase for the synthesis of an aminotriol. Biocatalysis andBiotransformation, 24, 449–457.

C.M.L. (2002). In J. Gunée (Ed.), Life cycle assessment. An operational guide to the ISOstandards. NL: Centrum voor Milieukunde Leiden, Leiden University.

Carvalho, A., Gani, R., & Matos, H. (2006). Design of sustainable processes: System-atic generation & evaluation of alternatives. In W. Marquardt, & C. Pantelides(Eds.), 16th European symposium on computer aided process engineering and 9thinternational symposiumon process systems engineering 2006 Elsevier B.V., vol. 2,(pp. 817–822).

Constable, D. J. C., Curzons, A. D., & Cunningham, V. L. (2002). Metrics to ‘GreenChemistry’—Which are the best? Green Chemistry, 4, 521–527.

Constable, D. J. C., Curzons, A. D., Freitas dos Santos, L. M., Geen, G. R., Kitteringham, J., Smith, P., et al. (2001). Green chemistry measures for process research anddevelopment. Green Chemistry, 3, 7–9.

Constable, D. J. C., Jimenez-Gonzalez, C., & Lapkin, A. (2008). Process metrics. In A.Lapkin, & D. J. C. Constable (Eds.), Green chemistry metrics (p. 352). Blackwell

Publishers.Cowan, D., Oxenbøll, K. M., & Holm, H. C. (2008). Oil Mill Gazeeter , 113, 10–13.Dale, B. E. (2003). ‘Greening’ the chemical industry: Research and development

priorities for bio-based industrial products. Journal of Chemical Technology andBiotechnology, 78, 1093–1103.

Environmental Protection Agency. (2003). Tool for the reduction and assessment of chemical and other environmental impacts (TRACI): User’s guide and system doc-umentation. EPA 600/R-02/052. Cincinnati, OH, USA: National Risk ManagementResearch Laboratory.

Fargione,J., Hill, J.,Tilman, D.,Polasky,S., & Hawthorne, P. (2008). Land clearing andthe biofuel carbon debt. Science, 319, 1235–1238.

Gani, R., Jørgensen, S. B., & Jensen, N. (2005). Design of sustainable processes: Sys-tematic generation & evaluationof alternatives. In 7thworld congressof chemicalengineering

Grossmann, I. E., & Daichendt, M. M. (1996). Computers and Chemical Engineering , 20(6/7), 665–683.

Glasser, D., Hildebrandt, D., Hausberger, B., Patel, B., & Glasser, B. J. (2009). Systemsapproach to reducing energy usageand carbon dioxide emissions. AIChE Journal,

55, 2202–2207.Heijungs, R. (1992). Environmental life cycle assessment of products, Guide andbackgrounds. NOH report 9266 and 9267, commissioned by the National Reuseof Waste Research Programme (NOH), in collaboration with CML, TNO and B&G.Leiden.

Heinrich,A. (2006). Socialimpactsin product lifecycles—Towards lifecycle attributeassessment. International Journal of LCA, 1(Special issue 1), 97–104.

Henderson, R. K., Jimenez-Gonzalez, C., Preston, C., Constable, D. J. C., & Woodley, J. M. (2008). C omparison of biocatalytic and chemical synthesis: EHS and LCAcomparison for 7-ACA synthesis. Industrial Biotechnology, 4, 180–192.

Hendrickson, C. T., Lave, L., & Matthews, H. S. (2006). Environmental life cycle assess-mentof goodsand services:An input–output approach. Washington,DC: Resourcesfor the Future. ISBN:1-933115r-r23-8.

Hibbert, E. G., Baganz, F., Hailes, H. C., Ward, J. M., Lye, G. J., Woodley, J. M., et al.(2005). Directed evolution of biocatalytic processes. Biomolecular Engineering ,

22, 11–19.Hochschorner, E., & Finnveden, G. (2006). Life cycle approach in the procurement

process: The case of defence material. LCA, 11(3), 200–208.Hunkeler, D., & Rebitzer, G. (2005). The future of life cycle assessment. International

Journal of LCA, 10(5), 305–308.International Organization of Standardization. (2006). ISO 14044–Environmental

management—Life cycle assessment—Requirements and guidelines. Geneva,Switzerland: ISO.

International Organization of Standardization. (1997). ISO 14040–Environmentalmanagement—Life cycle assessment—Principles and framework. Geneva, Switzer-land: ISO.

Jimenez-Gonzalez, C., Constable, D. J. C., Cu rzons, A. D., & Cunningham, V. L. (2002).Developing GSK’s green technology guidance: Methodology for case-scenariocomparison of technologies. Journal of Clean Technologies and EnvironmentalPolicy, 4, 44–53.

Jimenez-Gonzalez, C., Constable, D. J. C., Cu rzons, A. D., & Cunningham, V. L. (2001).How do you select the ‘greenest’ technology? Development of guidance for thepharmaceutical industry. Clean Products and Processes, 3, 35–41.

Jodicke, G., Zenklusen, O., Weidenhaupt, A., & Hungerbuhler, K. (1999). Journal of Cleaner Production, 7 , 159–166.

Jørgensen,A., Hauschild, M., Jørgensen,M. S., & Wangel, A. (2009). Relevance and fea-sibility of social life cycleassessment froma company perspective. International

Journal of LCA, 14(3) (online first).

http://www.acs.org/greenchemistryhttp://www.acs.org/greenchemistryhttp://www.acs.org/greenchemistry


9/9


Jørgensen, A., Le Bocq, A., Nazarkina, L., & Hauschild, M. (2008). Methodologies forsocial life cycle assessment. International Journal of LCA, 13(2), 96–103.

Kim, S., & Dale, B. (2005). Life cycle assessment study of biopolymers(polyhydroxyalkanoates)—Derived from non-tilled corn. International Journal of LCA, 10, 200–210.

Kim, S., & Dale, B. (2006). Ethanol fuels: E10 or E85—Life cycle perspectives. Inter-national Journal of LCA, 11, 117–121.

Kim, S., Jimenez-González, C., & Dale, B. E. (2009). Enzymes for pharmaceuticalapplications—A cradle-to-gate life cycle assessment. International Journal of LifeCycle Assessment , 14(5), 392–400.

Klöpffer,W. (2003). Life-cyclebased methods for sustainable product development.

International Journal of LCA, 8(3), 157–159.Kløverpris,J. H.,Wenzel,H., & Nielsen,P. H.(2008). Life cycle inventorymodelling of

landuse induced by cropconsumption.Part 1. Conceptualanalysisand method-ological proposal. International Journal of LCA, 13, 13–21.

Law, H.E. M.,Baldwin, C.V. F.,Chen, B.H.,& Woodley,J.M. (2006). Processlimitationsin a whole-cell catalysed oxidation: Sensitivity analysis. Chemical Engineering Science, 61, 6646–6652.

Marrero, J., & Gani, R. (2001). Group contribution based estimation of pure compo-nent properties. Fluid Phase Equilibria, 183–184, 183–203.

O.E.C.D.(2002). Theapplication of biotechnology toindustrialsustainability—Aprimer .Organization for Economic Cooperation and Development.

Patel, M., Dornburg, V., Hermann, B., Roes, L., Hüsing, B., Overbeek, L., et al. (2006).Medium and long term opportunities and risks of the biotechnological produc-tion of bulk chemicals from renewable resources. The BREW project – Finalreport – The Potential of White Biotechnology, Utrecht. 452pp.

Pollard,D. J., & Woodley,J. M. (2007). Biocatalysis forpharmaceuticalintermediates:The future is now. Trends in Biotechnology, 25, 66–73.

PRé Consultants. (2001). Eco-Indicator 99. A damage oriented method for life cycleimpact assessment . PRé Consultants.

Rass-Hansen, J., Falsig, H., Jørgensen, B., & Christensen, C. H. (2007). Bioethanol:Fuel or feedstock. Journal of Chemical Technology and Biotechnology, 82,329–333.

Rebitzer, G., & Seuring, S. (2003). Life cycle costing: A new SETAC Europe workinggroup. International Journal of LCA, 8(2), 110–111.

Sheldon, R. A. (1992). Organic synthesis—Past, present and future. Chemistry andIndustry, 23, 903–906.

Sheldon, R. A. (2007). The E factor: Fifteen years on. Green Chemistry, 9, 1273–1283.Uerdingen, E., Gani, R., Fisher, U., & Hungerbuhler, K. (2003). A new screening

methodology for the identification of economically beneficial retrofit optionsfor chemical processes. AIChE Journal, 49(9), 2400–2418.

Vink, E. T. H., Rabago, K. R., Glassner, D. A., & Gruber, P. R. (2003). Application of lifecycleassessment to Natureworks© polylactide production. Polymer Degradationand Stability, 80, 403–419.

Wolf, O. (Ed.). (2005). Techno-economic feasibility of large-scale production of bio-based polymers in Europe. Seville, Spain: European Commission. Joint ResearchCenter, 256pp.

Woodley, J. M. (2006). Microbial biocatalytic processes and their development. Advances in Applied Microbiology, 60, 1–15.

Woodley, J. M. (2008). New opportunities for biocatalysis: Making pharmaceuticalprocesses greener. Trends in Biotechnology, 26, 321–327.

Biooprocesos Necesidades de Modelado Para La Evaluacion Del Proceso y La Sostenibilidad

Documents

Transcript of Biooprocesos Necesidades de Modelado Para La Evaluacion Del Proceso y La Sostenibilidad