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Bio-Economy: Chances, Challenges, and Perspective of the System as a Whole

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Bio-Economy: Chances,

Challenges, and Perspective of

the System as a Whole

Andreas Pfennig

Products, Environment, and Processes (PEPs)

Department of Chemical Engineering

Université de Liège

www.chemeng.uliege.be/pfennig

andreas.pfennig@uliege.be

presented at ECCE12, ECAB5, 15.-19.09.2019, Florence, Italy

agenda

2

motivation

world population

utilization of land-area

bio-economy: chances & challenges

consequences

Pfennig, A., 2019:

Sustainable Bio‐ or CO2 economy: Chances, Risks, and

Systems Perspective.

ChemBioEng Reviews, 6(3), 90-104.

https://doi.org/10.1002/cben.201900006

(2)

THE major driver

world population

7 600 000 000

food

2.8 kg/(cap d)

energy

21 000 kWh/(cap a)

materials

ca. 0.9 kg/(cap d)

fossil resources

5.6 kg/(cap d)

land area

agricultural: 7 000 m

2

/cap

3

1960

1980

2000

2020

2040

2060

2080

2100

0

2

4

6

8

10

12

14

16

variant:

w

o

rl

d

p

o

p

u

la

ti

o

n

i

n

b

ill

io

n

year

low

medium

high

to

d

a

y

95% interval

future development of world population

source: United Nations

World Population Prospect 2019 Revision

(3)

2000

2010

2020

2030

2040

2050

7

8

9

10

11

12

w

o

rld

p

o

p

u

la

tio

n

2

0

5

0

in

b

illio

n

year of publication

high va

riant

me

dium

var

iant

low

va

ria

nt

11.62 billion in 2050

development of UN-WPP prediction for 2050

5

future development of world population

6

1960

1980

2000

2020

2040

2060

2080

2100

0

2

4

6

8

10

12

14

16

18

20

e

x

p

e

c

te

d

d

e

v

e

lo

p

m

e

n

t

to

d

a

y

w

o

rl

d

p

o

p

u

la

ti

o

n

i

n

b

ill

io

n

year

up

pe

r l

im

it

11.62 billion

in 2050

Club of Rome

IPCC SR1.5

EU

var

ian

t:

hig

h

medium

low

(4)

modelling approach

not an IAM (integrated assessment model)

based on simple balances:

influence of individual parameters directly visible

main drivers easy to realize

negative influence of too detailed models:

H. Hasse, 2003: Thermodynamics of Reactive Separations.

in: K. Sundmacher, A. Kienle (Eds):

Reactive Distillation. Status and Future Directions.

Wiley-VCH, Weinheim

7

world population × demand per person

required land area =

land-area specific productivity

1960

0

1980

2000

2020

2040

2060

2080

2100

500

1000

1500

2000

overa

ll - se

ven m

ajor c

rops

ove

rall

ve

get

al p

rim

ary

pr

odu

cts

s

p

e

c

if

ic

p

ro

d

u

c

ti

v

it

y

i

n

k

c

a

l

/

(m

2

a

)

year

se

ve

n m

ajo

r c

ro

ps

land-area specific agrigultural productivity

seven major crops:

• barley

• corn

• oil palm

• rice

• soybeans

• sugar cane

• wheat

(5)

2000 2020 2040 2060 2080 2100 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

a)

biomaterials combustion pasture plant-based food forests meadows and pasture la n d a re a m 2 /c a p year arable land feed

remaining forest

land-area: challenging, high pop. variant

9

land-area: challenging, medium pop. variant

10

2000 2020 2040 2060 2080 2100 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 biomaterials biofuels pasture plant-based food forests meadows and pasture la n d a re a m 2 /c a p year arable land feed forests +

(6)

land-area: challeng., high, vegetal

11

2000 2020 2040 2060 2080 2100 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

forests +

afforestation,

bio-energy, etc.

biomaterials combustion pasture plant-based food forests meadows and pasture la n d a re a m 2 /c a p year arable land feed

land-area: challeng., medium pop., vegetal

2000 2020 2040 2060 2080 2100 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 biomaterials biofuels pasture plant-based food forests meadows and pasture la n d a re a m 2 /c a p year arable land feed

forests +

afforestation, bio-energy, etc.

additionally available land area

due to limiting population

growth and nutritional habits

(7)

options for bio-based chemicals 2050

13

gen feedstock products radius

km fi rs t g e n e ra ti o n sugar beet sugar or ethanol + CO2 10.4 ethanol 14.6 ethylene 18.7

sugar cane sugar or ethanol + CO2 7.5

ethanol 10.5

corn sugar or ethanol + CO2 13.4

ethanol 18.7

wheat sugar or ethanol + CO2 17.5

ethanol 24.5

oil palm plant oil 11.4

rape seed plant oil 30.1

s

e

c

o

n

d miscanthus/reeds sugar or ethanol + CO2 5.7

ethanol 7.9

wood sugar or ethanol + CO2 14.8

ethanol 20.7 th ir d corn straw sugar or ethanol + CO2 20.1 ethanol 28.2

wheat straw sugar or ethanol + CO2 23.2

ethanol 32.5

arable land

2050

0 500 1000 1500 area in m2 /cap

goal

ranges:

maximum national and world average productivity projected for 2050 color: ■technically realized ■partly pilot-plant Pfennig, A., 2019: ChemBioEng Reviews, 6(3), 90-104. https://doi.org/10.1002/cben.201900006

bio- vs. CO

2

-economy

utilize CO

2

from point source

methane

1124 € / tC

methanol

844 € / tC

utilize CO

2

from air

methane

1650 € / tC

methanol

1360 € / tC

starch from wheat

616 € / tC

crude oil

≈ 440 € / tC

(8)

conclusion

15

bio-based chemistry:

cheaper, developed technology

competition for land area

CO

2

-based chemistry:

more expensive, new processes

no fertile land area required

Choices:

A. CO

2

-based chemistry

significant economic & technological risks for our future

B. bio-based chemistry, conventional

more people undernourished

cut down forests

C. bio-based chemistry, vegan, 2 children per family

cheap, developed, enough space for ecology

You choose with your daily choices!

Bio-Economy: Chances,

Challenges, and Perspective of

the System as a Whole

Andreas Pfennig

Products, Environment, and Processes (PEPs)

Department of Chemical Engineering

Université de Liège

www.chemeng.uliege.be/pfennig

andreas.pfennig@uliege.be

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