lecture: advanced environmental assessments · calorific value of burned coal 27.7 mj/kg 15.7 mj/kg...

||www.ifu.ethz.ch/ESD

Spatial LCA

20.01.2017Stefanie Hellweg 1

Lecture:

Advanced Environmental Assessments

||www.ifu.ethz.ch/ESD 20.01.2017 2

Learning Goals

1. Understand when site-dependent models are needed

2. Understand the computational structure of regionalized

LCA (inventory analysis and impact assessment)

3. Get to know examples of regionalized LCA case studies


||www.ifu.ethz.ch/ESD 20.01.2017 3Advanced Environmental Assessments

Why regionalization in LCA?

• Background inventory data may change as a function of site

(e.g. different technologies).

• Emissions and resource use flows may have a different impact,

depending on the site (e.g. different sensitivities, background

concentrations, …).

Regionalization (LCI and LCIA data) can reduce uncertainties

due to spatial variability.


Spatial differences in LCI

• Example of electricity from coal power plants

Germany India

Calorific value of burned coal 27.7 MJ/kg 15.7 MJ/kg

Emission abatement Desulphurisation,

denitrification, and dedusting

operating in most power

plants

In most power plants only

dedusting

CO2 92 g/MJ coal 96 g/MJ coal

NOx 0.06 g/MJ coal 0.63 g/MJ coal

SO2 0.07 g/MJ coal 0.89 g/MJ coal

PM2.5 0.005 g/MJ coal 0.202 g/MJ coal

Net efficiency of power plant 36 % 32 %

ecoinvent 3.1


0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

India Germany

ReCiPe points/kWh

Remaining substances

Nitrogen oxides

Sulfur dioxide

Particulates, < 2.5 um

Hard coal in ground

Carbon dioxide, fossil

Differences in impact due to spatial variability in LCI data

• Example of electricity from coal power plants

ecoinvent 3.1

20.01.2017 5Advanced Environmental Assessments


Source: Ecoinvent 2.2


• Climate change effects of electricity supply mixes in Europe

20.01.20176



Mutel et al. Env Sc & Technology, 2011, Hellweg & Mila y Canals, Science, 2014

• 558 coal power plants

• 1,322 gas power plants

• 1,296 hydropower plants

• 51 nuclear power plants

• 1,230 other plants

(mainly renewables)


• Climate change effects of US electricity supply technologies

20.01.2017 7Advanced Environmental Assessments

||www.ifu.ethz.ch/ESD 20.01.2017Bernhard Steubing 8

Spatial differences in LCI: new approach

followed by ecoinvent v3

||www.ifu.ethz.ch/ESD 20.01.2017Bernhard Steubing 9

Geographical impact distribution (climate

change)

Steubing B, G Wernet, J Reinhard, C Bauer, E Moreno, The ecoinvent database version 3 (part II):

analyzing LCA results and comparison to version 2. accepted by Int J LCA, 2015


Electricity related impacts (climate change) in

global and Euorpean datasets

v2.2

v3.1

Global Europe

Steubing B, G Wernet, J Reinhard, C Bauer, E Moreno, The ecoinvent database version 3 (part II):

analyzing LCA results and comparison to version 2. accepted by Int J LCA, 2015


How can spatial inventory data and impact

assessment be combined?

*

Spatial characterization factorsSpatial LCI

Spatial Impact scores

2015Advanced Environmental Assessments 11


Recap: Computational structure of site-generic LCA

Output

Inte

rmedia

te

pro

ducts

as

inputs

Environm

enta

l

inte

rventions

A = demand matrix (nxn)

Technosphere (economical

system)

B = biosphere matrix (mxn)

(environmental interventions)

a11 a12 … a1n

a21 a22 … a2n

. A .

. .

an1 an2 … ann

b11 b12 … b1n

b21 b22 … b2n

. B .

. .

bm1 bm2 … bmn

For background reading: R. Heijungs et al., The Computational Structure of Life

Cycle Assessment, Springer Science+Business Media Dordrecht 2002





Slide source: Chris Mutel 2013





)()( 1 fdiagAIB

h: total environmental impact

diag(c): diagonal matrix constructed from the characterization vector c

diag(f): diagonal matrix constructed from the demand vector f

I : identity matrix,

)()( 1 fdiagAIBcdiagh Impact:

Inventory:



assessment be combined (computational structure)?

Mutel et al. Environmental Science & Technology, 2011

• R is the characterization matrix, which has rows of spatial

units and columns of environmental flows.

• M is the inventory mapping matrix with rows of technological

processes, and columns of inventory spatial units. It indicates

where a technological process occurs.

• If the inventory spatial scale is not the same as the LCIA spatial

scale, we need a geographic transform matrix G; G has rows

of inventory spatial units and columns of LCIA spatial units. Row

values represent the proportional area of an inventory spatial unit

that is located in each LCIA spatial unit (rows sum to 1).


ℎ = (𝑀𝐺𝑅)𝑇°𝐵 𝐼 − 𝐴 −1𝑑𝑖𝑎𝑔(𝑓)

“◦”: element-wise multiplication (Hadamard product)




Picture source: C. Mutel 2013; Mutel et al. Environmental Science & Technology, 2011

• M : inventory mapping matrix





• R : characterization matrix; example:






• G : geographic transform matrix







5.075.0

75.21

75.21

525.1

5.075.0

01

5.05.0

5.05.0

525.1

5.075.0

01

5.05.0

10

01

01

i ii

A

B

C

em1 res1 em1 res1

A

B

C





…

Technical processes

Em

issio

ns/r

esourc

es

…

Technical processes

Em

issio

ns/r

esourc

es

AmountsCharacterization factors

(process related)

◦



Case study I: US power plants

Results for ecosystem damage of water consumption




Acidification

Emission sources: power plants, traffic, industry, animalraising

Excess inflow ofprotons (into soil orwater)

Ecosystem impacts

Examples:

• SOx H2SO4

• NOx HNO3

• NHx NH3



Spatial aspects and variability

Air emissions are transported over large distances

Soil and water systems have different buffer capacitiesand respond differently: carbonate buffered soils hardlychange while sensitive soil systems react strongly toacidification




Results for acidification




Case study II: Worldwide land-occupation

impacts from agriculture and forestry

20.01.2017Advanced Environmental Assessments

2

9

Chaudhary et

al. 2016, ES&T


Impacts of land use due to Swiss food

consumption


• Forage, soybean, wheat and wine are the products imported most by

amount.

• Import share from Germany, France, Italy and Austria and the European

ports of Belgium and Netherlands large, but biodiversity impacts are

rather low.

• Cocoa beans and coffee imports were responsible for the biggest land-

use related biodiversity impact in South and Central America and

Southeast Asia.

• The total imported impacts are respectively 25, 52, 500 and 430

times higher than biodiversity loss due to domestic crop land use

for Swiss consumption in Switzerland.

• By contrast: the ratio of total land embodied in imported products

and net domestic agricultural land used for consumption was

approximately 5.

PhD project A. Chaudhary 2015


Regionalization makes LCA more complex, but it can

Reduce uncertainties due to spatial variability (e.g. see

variability in impact assessment results of US power plants)

Identify regional hotspots of impact and possibly provide an

incentive to relocate production to less sensitive regions (see

case studies on US power plants and global agricultural

production and forestry)

Increase our understanding of regionally distributed value

chains (see Swiss food consumption case study)

Understand better the relation between the location(s) of

impacts and the responsible actors (see Swiss food

consumption case study)

Conclusions from the case studies


Conclusions and Take-home messages

• Regionalization in LCI is necessary when e.g. technologies

vary as a function of space

• Regionalization in LCIA is needed when emissions or resource

use flows have a different impact, depending on the site

• There are computational methods to consider and combine

regionalized LCI and LCIA data, even if the spatial support is

different.

• Only some few software systems (OpenLCA, Brightway) are

currently able to deal with regionalization in LCIA

• LCI data is often not available in a properly regionalized manner

• Regionalized LCIA methods exist for several impact categories

(e.g. www.lc-impact.eu); development is ongoing

http://www.lc-impact.eu/

lecture: advanced environmental assessments · calorific value of burned coal 27.7 mj/kg 15.7 mj/kg...

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