Exploring the Relevance of Uncertainty in the Life Cycle Assessment of Forest Products

Frida Røyne

Department of Chemistry

Umeå University

Doctoral thesis 2016

Copyright © Frida Røyne

This work is protected by the Swedish Copyright Legislation (Act 1960:729)

ISBN: 978-91-7601-455-4

Front cover picture: Louise Quistgaard

Electronic version available at http://umu.diva-portal.org/

Tryck/Printed by: VMC-KBC, Umeå

Umeå, Sweden, 2016

How can we support and perpetuate the rights of all living things to share

in a world of abundance? How can we love the children of all species - not

just our own - for all time? Imagine what a world of prosperity and health

in the future would look like, and begin designing for it right now.

- William McDonough and Michael Braungart

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Table of Contents

Table of Contents ii

Abstract iv

Sammanfattning på svenska vi

List of Abbreviations viii

List of Publications x

1. Introduction 1

1.1 The role of biomass 1

1.2 Assessing the environmental impact of bio-based products 2

1.3 Addressing uncertainty 3

2. Aim and Scope 5

2.1 Research questions 5

2.2 Scope and limitations 6

3. Research journey through the appended papers 7

4. Transition to a bio-economy: the case of the

Stenungsund chemical industry cluster 9

5. Scientific Background 11

5.1 Systems analysis 11

5.2 Life Cycle Assessment 12

5.2.1 System boundaries 14

5.2.2 Climate impact assessment 15

5.2.3 Allocation 17

5.3 Uncertainty in LCA 19

5.3.1 Attributional and consequential LCA 20

5.3.2 LCA as decision support 20

6. Methods and Case studies 23

6.1 Sensitivity analysis of system boundary setting 24

6.2 Uncertainty analysis of climate impact assessment practices 27

6.3 Allocation methods testing and development 29

7. Results and Discussion 31

7.1 Identifying, estimating, and dealing with uncertainty 31

7.1.1 System boundaries 31

7.1.2 Climate impact assessment 37

7.1.3 Allocation 43

7.2 Representability of the case studies 45

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7.3 The role of LCA in guiding the forest based bio-economy 47

8. Conclusions and Future work 51

8.1 Guidance for the forest-based bio-economy 51

8.2 Method development 52

8.3 Ways forward 53

9. Acknowledgements 55

References 57

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Abstract

The role of forest biomass as a replacement for fossil fuels and products is

becoming increasingly prominent as a means to mitigate climate change. To

guide a sustainable transition towards a forest-based bio-economy, it is

important that advantages and disadvantages of forest products are

assessed, to ensure that the products deliver environmental impact

reduction. Life Cycle Assessment (LCA) has become heavily relied upon for

assessing the environmental impact of bio-based products. However, LCAs

of similar product systems can lead to results that differ considerably, and

the method is, thus, associated with uncertainties. It is, therefore, necessary

to explore the relevance of uncertainties, to build knowledge about enablers

and challenges in using LCA for assessing forest products.

Three important challenges in the context of uncertainty in LCA are the

focus of this thesis: 1) system boundaries, 2) climate impact assessment

practice, and 3) allocation. More specifically, the relevance of a) including

and excluding life cycle phases, b) potentially important climate aspects, and

c) applying different allocation methods, was assessed. Case studies involved

a chemical industry cluster, a biorefinery, and single product value chains for

a plastic box, a fuel, and a building.

In summary, the thesis demonstrates that:

A major share of the environmental impact related to the production

of an industry cluster can occur outside the cluster gates, so when

strategies involving a transition to forest biomass feedstock are

developed and evaluated, a life cycle perspective reveals the full

environmental impact reduction potential.

For bio-based products differing in functional properties from the

fossil products they are meant to replace, material deterioration in

the use phase can contribute substantially to overall environmental

performance. This is acknowledged if all life cycle phases are

regarded.

As climate aspects commonly not assessed in forest product LCAs

could influence results greatly, and even affect the outcome of

comparisons between forest and non-forest products, the climate

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impact of forest products is uncertain. It is, therefore, important that

this uncertainty is acknowledged and communicated, and that

appropriate methods and guidelines are developed.

The choice of allocation method in the LCA of biorefinery products

can have a major influence on results, especially for physically non-

dominant products and in consequential studies. In these cases,

scenario analysis is especially valuable to show the possible range of

results.

LCA provides useful guidance for forest product development and

production as the life cycle approach reveals causes of environmental impact

throughout the product value chain. Proper identification, estimation, and

management of uncertainties strengthen the provision of reliable decision

support.

Keywords: LCA, wood, forestry, uncertainty, biorefinery, industrial

symbiosis, allocation, system boundaries, bio-economy

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Sammanfattning på svenska

Att ersätta fossila bränslen och produkter med skogsbiomassa blir ett allt

viktigare sätt att försöka minska klimatförändringen. För att säkerställa en

hållbar övergång till en skogsbaserad bioekonomi är det viktigt att

fördelarna och nackdelarna med skogsprodukter bedöms, för att klargöra att

de faktiskt ger minskad miljöpåverkan. Livscykelanalys (LCA) är en flitigt

använd metod för att bedöma miljöpåverkan från biobaserade produkter.

Dock kan LCA:er på snarlika produktsystem komma fram till resultat som

skiljer sig avsevärt. Metoden är således förknippad med osäkerheter. Det är

därför nödvändigt att undersöka betydelsen av osäkerheter och därigenom

bygga upp kunskap om förutsättningar för och utmaningar i användningen

av LCA för bedömning av skogsprodukters miljöprestanda.

Avhandlingen fokuserar på tre viktiga utmaningar som alla rör osäkerheter i

LCA: 1) systemgränser, 2) praxis vid bedömning av klimatpåverkan, och 3)

allokering. Närmare bestämt bedöms betydelsen av a) inkluderandet och

exkluderandet av livscykelfaser, b) potentiellt viktiga klimataspekter och c)

olika allokeringsmetoder. Fallstudier har gjorts på ett kemiskt

industrikluster, ett bioraffinaderi och produktvärdekedjorna för en plastlåda,

ett fordonsbränsle samt en byggnad.

Sammanfattningsvis visar avhandlingen att:

En stor del av miljöpåverkan relaterad till ett industriklusters

produktion kan uppstå utanför klustrets grindar. När strategier som

innebär en övergång till skogsbasserat råmaterial utvecklas och

utvärderas är det således viktigt att använda ett livscykelperspektiv,

så att den fulla potentialen för minskad miljöpåverkan synliggörs.

För biobaserade produkter som skiljer sig i funktionella egenskaper

från de fossila produkter de är avsedda att ersätta riskerar

materialförsämring i användningsfasen att väsentligt minska den

övergripande miljöprestandan. Om detta är fallet framgår tydligt om

alla livscykelfaser beaktas.

Klimataspekter som vanligtvis inte bedöms i LCA-studier på

skogsprodukter kan påverka resultatet kraftigt och även påverka

resultatet av jämförelser mellan skogs och icke-skogsprodukter.

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Således är den faktiska klimatpåverkan av skogsprodukter osäker.

Det är därför viktigt att osäkerheten uppmärksammas och

kommuniceras samt att lämpliga metoder och riktlinjer för

bedömning av klimatpåverkan från skogsprodukter utvecklas.

I LCA av bioraffinaderiprodukter kan val av allokeringsmetod ha en

stor inverkan på resultaten. Detta gäller särskilt för fysiskt icke-

dominanta produkter och i konsekvensanalyser. I dessa fall är

scenarioanalys speciellt värdefullt att använda för att visa möjliga

skillnader i resultat.

LCA ger värdefull vägledning för utveckling och produktion av

skogsprodukter, då livscykeltänkandet beaktar orsakerna till miljöpåverkan i

produkternas hela värdekedjor. Korrekt identifiering, uppskattning och

hantering av osäkerheter stärker tillförlitligheten av beslutsunderlaget.

Nyckelord: LCA, trä, skogsbruk, osäkerhet, bioraffinaderi, industriell

symbios, allokering, systemgränser, bioekonomi

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List of Abbreviations

ABS = Acrylonitrile butadiene styrene

EIA = Environmental Impact Assessment

EIO = Economic Input-Output

EoL = End-of-Life

ERA = Environmental Risk Assessment

ESA = Environmental Systems Analysis

EU = European Union

GHG = Greenhouse gas

GWP = Global warming potential

ILCD = International Reference Life Cycle Data System

ILUC = Indirect land use change

IPCC = Intergovernmental Panel on Climate Change

ISO = International Organization for Standardization

LCA = Life Cycle Assessment

MFA = Material Flow Analysis

PA = Polyamide

PC = Polycarbonate

PEF = Product Environmental Footprint

PLA = Polylactic acid

SOG = Stripper off gas

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x

List of Publications

I. Røyne, F., Berlin, J., Ringström, E., 2015. Life cycle

perspective in environmental strategy development on the

industry cluster level: A case study of five chemical companies.

Journal of Cleaner Production, 86: 125-131.

II. Røyne, F., Hackl, R., Ringström, E., Berlin, J. Environmental

evaluation of industry cluster strategies with a life cycle

perspective: Replacing fossil feedstock with forest-based

feedstock and increasing thermal energy integration. Submitted

to the Journal of Industrial Ecology, 2015.

III. Røyne, F., Peñaloza, D., Sandin, G., Berlin, J., Svanström, M.,

2016. Climate impact assessment in life cycle assessments of

forest products: Implications of method choice for results and

decision-making. Journal of Cleaner Production, 116: 90-99.

IV. Sandin, G., Røyne, F., Berlin, J., Peters, G. M., Svanström, M.,

2015. Allocation in LCAs of biorefinery products: Implications

for results and decision-making. Journal of Cleaner Production,

93: 213-221.

V. Røyne, F., Berlin, J. The importance of including service life in

the climate impact comparison of bioplastics and fossil-based

plastics. Submitted to the International Journal of Life Cycle

Assessment, 2016.

Contribution of the author to appended papers

Paper I

Frida Røyne performed the data collection and analysis of the life cycle

xi

assessment together with Emma Ringström, and was responsible for the

writing of the paper.

Paper II

Frida Røyne performed the data collection and analysis of the life cycle

assessments together with Emma Ringström, and was responsible for the

writing of the paper.

Paper III

Frida Røyne was the main responsible for the literature analysis and the fuel

case study, and coordinated the writing of the paper.

Paper IV

Frida Røyne contributed with the methanol case and forestry data, and

participated in the writing of the paper.

Paper V

Frida Røyne performed the data collection and analysis of the life cycle

assessment and was responsible for the writing of the paper.

Work related to the thesis has also been presented in the

following reports

Røyne, F., Ringström, E., Berlin, J. 2015. Life Cycle Assessment of

forest based raw materials for the Stenungsund chemical industry

cluster. SP Report 2015:30. Borås: SP Technical Research Institute

of Sweden. Available from

www.sp.se/en/publications/Sidor/Publikationer.aspx.

Sandin, G., Peñaloza, D., Røyne, F., Staffas, L., Svanström, M. 2015.

The method’s influence on climate impact assessment of biofuels

and other uses of forest biomass. Report No 2015:10, f3 The

Swedish Knowledge Centre for Renewable Transportation Fuels.

Available from www.f3centre.se.

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1. Introduction

On December 12 2015, The Guardian announced: “Governments have

signaled an end to the fossil fuel era, committing for the first time to a

universal agreement to cut greenhouse gas emissions and to avoid the most

dangerous effects of climate change” [1]. Almost 200 countries had agreed

on the ambitious goal to limit global warming below 2 °C and strive to keep

temperatures at 1.5 °C above pre-industrial levels [2]. The United Nations

conference on climate change in Paris (COP21), thus, marks an immensely

important turning point.

COP21 is, however, not the finish line. It is the starting line. To reduce

climate change, greater efforts are needed than what have been

demonstrated until now. Various actions have been proposed and employed

in efforts to reduce climate change. One of them is to replace fossil resources

with bio-based alternatives.

1.1 The role of biomass

The role of biomass as a replacement for fossil fuels and products is

becoming increasingly prominent [3]. Biomass is central to environmental

impact reduction strategies in companies [4-7], local and national

governments [8-12], and even on a trans-national level [13, 14]. The

European Union has, in recent years, taken action to strengthen the “bio-

economy”, defined as “...the sustainable production and conversion of

biomass into a range of food, health, fibre and industrial products and

energy” [15].

However, worries about the overexploitation of biomass resources and

indirect impacts of land use raise questions about the sustainability of

pursuing a bio-economy strategy [16, 17]. Just because a product is bio-based

does not automatically imply that it is better. Two types of business

constellations have been identified as promising for reducing the

environmental impact of the production of bio-based products1: biorefineries

1 Bio-based products are, in this thesis, defined as products (food and feed excluded) derived from biomass in

general, such as agriculture crops, wood, and waste.

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and industrial symbiosis systems [18]. The concept of industrial symbiosis

has been defined as a collective approach of traditionally separate industries

to obtain competitive advantages involving physical exchanges of materials,

energy, water, and/or by-products [19]. The arrangement has been

demonstrated to be environmentally profitable in several case studies [20],

also for bio-based systems [21, 22]. Biorefineries can be described as plants

processing and converting biomass into useful products, such as fuels, other

energy carriers, and chemicals [23], with a high degree of process integration

[24]. Both concepts, thus, take advantage of interconnectivity to reduce

environmental impact. The complexity of the systems implies that it is an

intricate task to evaluate the environmental impact of the products [25, 26].

Nonetheless, to guide a sustainable transition towards a bio-economy, it is

important that advantages and disadvantages of bio-based products are

assessed, to ensure that the products deliver environmental impact

reductions.

1.2 Assessing the environmental impact of bio-based products

One method, which has become heavily relied on for assessing the

environmental impact of bio-based products, is Life Cycle Assessment (LCA)

[27]. LCA is a method defined as the “compilation and evaluation of the

inputs, outputs and the potential environmental impacts of a product

system throughout its life cycle” [28]. The first LCAs were conducted in the

late 1960s. Early LCAs were primarily conducted to identify environmental

hot spots in the life cycle of packaging products and to compare different

packaging options [29]. Today, the method has gained great importance in

many areas and for many types of decision-making [9, 30]. It is even

mandatory for the environmental assessment of biofuels under the

Renewable Energy Directive [31].

Even though LCA offers intriguing potential to guide the development and

production of bio-based products, the method is associated with

uncertainties. For example, LCAs of similar bioenergy systems have led to

results that differ considerably [32, 33]. A study of the greenhouse gas

(GHG) emissions of ethanol has shown that the result can vary by a factor up

to 6.4, depending on whether land is converted for the purpose of biomass

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cultivation [34]. One reason for differing results is that the ISO standards

governing LCA practice [28, 35] are descriptions of the methodology in

general, and, thereby, the LCA practitioner is left with much flexibility to

interpret best practice.

Baumann and Tillman [29] have listed the most critical LCA methodology

choices as:

the definition of functional unit

system boundaries and allocation procedure

type of data used, and

impact assessment.

The same critical choices have been highlighted as those most significant for

causing differences in the results of LCAs of bio-based product systems [36].

For example, the way environmental problems are modelled and measured

in the impact assessment is limited by simplified assumptions concerning

the cause-effect chain of environmental problems and a lack of scientific

knowledge [29]. For bio-based products, these limitations lead to differences

in, for instance, the modelling of soil emissions and land use [37] and the

time lag between CO2 uptake during biomass growth and CO2 release from

biomass incineration [38].

1.3 Addressing uncertainty

Uncertainty in LCA results stems from the attempt to convert the variability

of the real world into results through parameters, models, and choices [39].

This is not a trait limited to the LCA method, but as LCA is increasingly

relied upon to deliver accurate decision support, it is important to consider

and manage uncertainties [40].

The thesis title indicates the two areas of focus of this thesis. One area is

forest products2. Sweden is covered by almost 70% forest [41], and forestry

has been an important industry for centuries. Forest biomass also represents

an alternative to biomass with agricultural origin, considering that the use of

agro-biomass for non-food applications can have severe consequences for

2 Forest products are in this thesis defined as products derived from forest biomass.

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food security [42, 43]. Forest biomass has, thus, intriguing potential to play a

role in replacing fossil resources in Sweden [44]. There are; however, as

already mentioned, also uncertainties regarding the potential for

environmental improvement. The second area is, consequently, uncertainty.

As the cover illustration implies, this thesis represents a journey into the

depths of a method, about uncovering uncertainties, and exploring

possibilities.

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2. Aim and Scope

The aim of this thesis is twofold. The first aim is to provide guidance for

environmentally sound decision-making for forest product development and

production. The second aim is to contribute to the methodological

development of LCA of forest products.

2.1 Research questions

RQ1: What is the relevance of system boundaries for the uncertainty of

forest product LCA results?

To what extent can single- or multi-product LCA results be

influenced by the inclusion/exclusion of life cycle phases?

In what way can guidance to decision-makers be influenced by the

inclusion/exclusion of life cycle phases?

RQ2: What is the relevance of uncertainty in the climate impact assessment

of forest products?

To what extent can results change if climate aspects not commonly

included are included in the climate impact assessment?

What are the current possibilities for dealing with uncertainty?

RQ3: What is the relevance of allocation for uncertainty in biorefinery

product LCA results?

For which types of products is the choice particularly important?

For which types of decision contexts is the choice particularly

important?

The results of this thesis are aimed at providing information for LCA

practitioners, researchers, and decision-makers to raise awareness about the

relevance of uncertainty and improve LCA practice. This is done to ensure

that the potential of LCA is maximized, while challenges are acknowledged,

so that the credibility of the method as a means to provide decision support

is strengthened.

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2.2 Scope and limitations

The geographical scope of the thesis is Sweden, and the industries and forest

biomass under study relate to Swedish conditions. Other types of biomass

and regions can have challenges other than those primarily focused on in

this thesis [45]. For example, indirect land use change can be prominent for

agricultural products [46], and rainforests have other growth rates and

conditions than boreal forests.

Forest biomass can be expected to be used as a feedstock for many different

applications. Therefore, the employed case studies cover different system

types and sizes:

a chemical industry cluster

a biorefinery, and

single-product value chains for a plastic box, a fuel, and a building.

Climate impact is the environmental impact category in focus in this thesis.

As most forests in Sweden are boreal forests with long rotation periods (it

takes 70-120 years for a tree to mature in a typical boreal forest [47]), effects

of time lag between CO2 uptake during biomass growth and CO2 release from

biomass incineration are potentially relevant to consider in the climate

impact assessments of forest products. In some of the case studies, the focus

on climate impact was chosen deliberately as a simplification, as other

method choices were in focus (allocation and system boundary selection).

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3. Research journey through the appended papers

The papers of this thesis form a journey towards enlightenment. The journey

started in 2012 when I was a fresh LCA practitioner, unaware of the many

bumps in the road that performing an LCA can imply. I got involved in the

project “Skogskemi” (Forest Chemistry) [48], with the task of assessing the

environmental impact of several chemical production routes with forest

biomass as the feedstock. The first step was to create a baseline for

comparison, which was easier said than done as the baseline was the total

production of the largest industry cluster in Sweden, with numerous inputs,

outputs, and inter-company flows. We discovered that the inclusion or

exclusion of upstream, onsite, and downstream processes had a strong

influence on the results, and that life cycle thinking was decisive for a holistic

assessment. The efforts resulted in Paper I, which can be seen as both

starting point and founding principle for the following research.

Paper II is the second part of the assessment of the forest-based chemical

production routes above. Instead of writing a pure LCA case study paper, I

wanted to further explore the implication of including or excluding life cycle

phases. I, therefore, decided to compare the “Skogskemi” strategy of

exchanging 25% of the current petroleum use with forest feedstock, with a

strategy of increased energy integration, which had earlier been proposed by

another PhD student (Roman Hackl) [49]. Life cycle thinking was

demonstrated to be highly relevant.

The forest product focus made me aware that the index used to assess

climate change in LCA, the global warming potential (GWP), is a simplified

index which does not cover certain features, such as the dynamics of carbon

flows, and that such features could have an influence on results. Full of

optimism, I reasoned that if I only understood the complexities of climate

impact assessment I could conduct the climate assessment correctly. I joined

efforts with two other PhD students at SP (Gustav Sandin Albertsson and

Diego Peñaloza), both working with LCA on forest products, to meet the

challenge. We soon understood that the issue was highly complex, and our

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efforts to estimate the scale of the uncertainty and implications for decision

support resulted in Paper III.

Another challenge encountered in the assessment of the forest-based

chemical production routes was how the environmental impact of the

production process should be divided between production outputs. As

Gustav Sandin Albertsson encountered the same challenge in a similar case

study, we set out to explore the implication of applying different methods

together. That research resulted in Paper IV.

During my PhD period, I was involved in a second major project:

“Sustainable recycling of ‘green’ plastics” [50]. My task was to conduct an

LCA of a bio-based plastic. I discovered that the case was an important

complement to the thesis as it explores an aspect not encountered in the

“Skogskemi” project. The bio-chemicals expected to be produced by the

industry cluster would be so-called drop-in products, which means that the

function and durability of the bio-chemicals would not differ from fossil-

based chemicals. However, not all fossil products can be expected to be

exchanged with bio-drop-ins. For example, only a limited number of

conventional plastics have bio-plastic drop-ins, so it can be expected that

they will behave differently. Nevertheless, the use phase is often excluded

from bio-plastic LCA studies [51]. Paper V, thus, became a continuation of

the train of thought from the two first papers, in which the implications of

including or excluding life cycle phases were the focus.

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4. Transition to a bio-economy: the case of the Stenungsund chemical industry cluster

The research focus of the PhD project has its starting point in the

environmental strategy work of a chemical industry cluster in Stenungsund,

a town on the West Coast of Sweden. The cluster consists of the five chemical

companies AGA, AkzoNobel, Borealis, INOVYN (former known as INEOS),

and Perstorp. The companies employ approximately 2,500 people and are all

members of large international groups [5].

The five companies produce a range of products and intermediates,

including chemicals, plastics, gases, and fuels. Figure 1 provides an overview

of the exchanges in the industry cluster. The companies interact vigorously

with each other in terms of material exchange. Energy integration, however,

is still limited [52].

Figure 1 Flows of materials into and products from the Stenungsund chemical

cluster and exchanges within the cluster [52]. Only major flows are shown. Arrow

size indicates the flow size.

Although by international standards the cluster is quite small, it is the largest

industry cluster in Sweden in terms of production volume. The cluster

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accounts for around 5% of Sweden's total fossil fuel usage (mainly

feedstock), and is a major emitter of fossil CO2. The companies, thus, face

challenges, but they also have the possibility to meet these challenges since

they collaborate and share the vision of reducing environmental impact [52].

The 2030 vision is that the cluster should mainly use biomass as raw

material [5]. One of the efforts to reach this vision was the project

“Skogskemi” (Forest Chemistry) [48], which ran 2012-2014, with the

purpose of exploring the possibility of exchanging fossil-based raw materials

with bio-based raw materials, and to strengthen a long-term sustainable

competitive production for two of Sweden’s primary industries: the forest

industry and the chemical industry. Three production technologies that

convert forest biomass to chemicals were explored:

Methanol production from purified KRAFT pulp mill stripper off

gases (SOGs).

N-butanol production via ethanol, acetaldehyde, and

crotonaldehyde.

Olefins produced through a methanol-to-olefins (MTO) process and

dehydration of ethanol.

Case studies from the project were used in three of the papers:

In Paper I, the assessment of the environmental impact of the

current Stenungsund industry cluster was used to explore the

implications of applying a life cycle perspective in the strategy

development on the cluster level.

In Paper II, the implementation of the olefin production route was

compared to an energy integration strategy for the industry cluster,

to explore the influence of system boundaries.

In Paper IV, the methanol production from purified KRAFT pulp

mill SOGs was used as a technology case study to test allocation

methods.

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5. Scientific Background

The papers of the thesis are all based on the method LCA. To position the

research, the purpose of this section is to outline LCA, define the research

front, and to describe and explain the relevance of the areas of focus of this

thesis.

5.1 Systems analysis

Facilities producing bio-based products, such as biorefineries, are not

isolated units but parts of a larger system [53]. A system can be described as

a “set of objects together with relationships between the objects and

between their attributes” [54]. The technical system is interlinked with the

natural system where the biomass originates from, the social system, and the

economic system. This must be kept in mind when bio-based products are

analysed.

Systems analysis as a scientific discipline emerged as a complement to

reductionist thinking. Breaking down problems into separate, more simple

elements could not explain certain multi-variable phenomena in disciplines

such as biology, psychology, and sociology [55]. The multidisciplinary

systems perspective is applied at the department at SP Technical Research

Institute of Sweden where this PhD project was conducted. SP states that

“finding the right strategic path, and implementing the technical changes

that will have the greatest effect on such problem areas as energy use and

environmental impact, often requires a systems science approach, whether

concerned with process optimisation in industry or the creation of

legislation and policy measures” [56].

Systems analysis is not one single method or even a set of methods, but an

approach for handling problems from an interdisciplinary point of view [57].

Interdisciplinary implies complexity, and, therefore, many different methods

have emerged that cover different aspects of single-system and inter-system

behaviour. LCA is one of several methods within the area of environmental

systems analysis (ESA). Examples of ESA methods include Environmental

Impact Assessment (EIA), Material Flow Analysis (MFA), and

12

Environmental Risk Assessment (ERA) [29]. Because of their different

features, these methods cannot easily replace each other [58]. What makes

LCA unique is the life cycle approach combined with a focus on product

functions [59].

5.2 Life Cycle Assessment

LCA is one of the most used methods for the environmental assessment of

product systems. LCA offers the possibility to quantitatively compile and

evaluate the potential environmental impact of products, technologies, and

services from a life cycle approach, from “cradle” (resource extraction) to

“grave” (e.g. landfill or incineration) [60, 61]. LCA reveals resource demand

as well as product and process emissions and waste, and translates these into

environmental impact categories [35]. The holistic scope of LCA helps avoid

problem-shifting from one life-cycle phase to another, between regions, or

environmental problems [60, 62].

LCA is comprised of goal and scope definition, inventory analysis, impact

assessment, and interpretation (Figure 2). In the goal and scope

definition, the question to be addressed and the limitations of the research

are stated, and the functional unit is determined (e.g. 1 ton methanol, 10 km

driven, or 5 years of service life). In the inventory analysis, the processes

of the product system are identified. Once the system is established, either

process-specific or generic data are collected. In the impact assessment,

potential environmental impact contributions associated with the emissions

and resources used are determined. This includes choosing relevant

environmental impact categories (e.g. global warming, eutrophication, and

acidification), assigning inventory data to the chosen environmental impact

categories, and characterizing environmental impact level by multiplying

emission inventory by characterization factors. The last step consists of the

interpretation of results and drawing conclusions from the study. This can

include various robustness tests, such as uncertainty and sensitivity

analyses, in which the influence of methodological choices throughout the

LCA are evaluated [35]. As implied in Figure 2, LCA is an iterative and not a

linear process, in which choices made in various phases can be reviewed

throughout the study period.

13

Figure 2 The phases of an LCA according to ISO 14044 [35].

Although ISO standards [28, 35] and guidelines [61, 63] provide guidance on

how to conduct an LCA, there are many choices which the LCA practitioner

has to make. The LCA practitioner can encounter different challenges

depending on what is specific to the system under study. Reap et al. [64, 65]

have categorised what they believe to be the largest challenges in the

different LCA phases. In addition, Baumann and Tillman have listed the

overall most critical LCA methodology choices [29]. Based on their

categorisations, issues that have been defined as especially important and

challenging for biofuels [36] (but that are also important for other bio-based

products) and aspects that I encountered during my PhD project (see Section

3), the focus in this thesis is on:

the choice of system boundaries (goal and scope definition),

climate impact assessment (impact assessment), and

the choice of allocation method (inventory analysis).

These three selected issues are among those that, according to Reap et al.

[65], rank specifically high on severity (severity representing problem

magnitude, likelihood of occurrence, and chance of detecting an error should

it occur). The authors point out that solutions exist, but also that there is no

consensus on the most appropriate framework. It is, therefore, important to

pay particular attention to these issues when addressing the uncertainty of

LCA results.

14

5.2.1 System boundaries

System boundaries define what is included and excluded in the study. They

can refer to different dimensions of product systems, such as boundaries in

relation to natural systems, geographical boundaries, time boundaries, and

boundaries within the technical system [29]. In this thesis, the boundaries in

relation to the natural system are explored along with the implications of the

inclusion and exclusion of life cycle phases. Time boundaries in climate

impact assessment are also explored (Section 5.2.2).

Figure 3 shows an example of the life cycle of a forest-based chemical

product. The life cycle starts with the “cradle” of the product, the extraction

of resources. In the case of a bio-based product, that is the harvest of the

biomass. The “grave” of the product is the End-of-Life (EoL) of the product,

in this case, the incineration of the discarded product. A cradle-to-grave

study, thus, represents the whole life cycle of a product.

Figure 3 The life cycle of forest-based methanol from purified KRAFT pulp SOGs

(from the Forest Chemistry project [48], see Section 4).

An LCA does not, however, necessarily have to cover the whole life cycle of a

product. Depending on the goal of the study, the system boundaries can

encompass cradle-to-gate (the gate of the production factory), or even be

limited to gate-to-gate. Such a limitation can, in many cases, be reasonable,

as the assessment of the whole life cycle is time and data demanding. If a

product is compared to another, it is, however, important that they are

compared on an equal basis and that the system boundaries encompass all

15

relevant life cycle phases. This is highly relevant for the bio-economy

strategy, which advocates an exchange of fossil resources with biomass.

Existing LCAs on bio-based products do not always have a cradle-to-grave

approach. The majority of LCAs on bioplastics and bioplastic products

exclude life cycle phases beyond production [51]. The same tendency has

been identified for forest products [66]. In a literature review of LCA case

studies on biorefinery systems, cradle-to-gate was found to be the most used

approach [23]. Industrial symbiosis systems, which could be an important

future production route for bio-based products, are usually assessed with a

gate-to-gate approach [67]. Excluding life cycle phases can cause uncertainty

in results if, for example, life cycle phases are left out in product comparisons

of functionally non-equivalent products. The exclusion can also hinder

identifying improvement potential in product value chains, as processes in

disregarded life cycle phases could be the source of significant impact.

5.2.2 Climate impact assessment

All impact assessment frameworks have an impact category called climate

change or global warming, and all use the GWP index developed by the

Intergovernmental Panel on Climate Change (IPCC) [68]. However, the

GWP is a simplified index [69]. It measures how much heat a GHG traps in

the atmosphere over a specific time interval and does not, for example,

capture the dynamic nature of carbon flows in the forest and the life cycle of

forest products [70]. Figure 4 summarizes aspects that could be of

importance in the climate impact assessment of forest products.

16

Figure 4 A fuel product system (short-lived product) and a building product

system (long-lived product) illustrate aspects that could be of relevance in the

climate impact assessment of forest products.

Throughout the life cycle of a forest product, there are exchanges of GHGs

between the product system, the atmosphere, and the ground. Emissions and

carbon sequestration can occur over a long period of time if the product is

long-lived, as long-lived products can store carbon and as forests are

relatively slow-grown. The climate neutrality assumption of biogenic CO2

emissions (aspect C) comes from the assumption that there is a balance in

the system, in which an amount equivalent to the CO2 emissions at EoL is

resequestered by the forest in a constant cycle. The cycle does, however, have

a time lag, especially in slow-grown forests [71]. Such a temporal shift

between emitted and sequestered carbon (aspect A) may contribute to a

temporary increase in radiative forcing [72, 73]. One way to account for

17

timing is to give a credit to forest products which temporarily store carbon in

the technosphere and, thus, cause a temporary reduction of the radiative

forcing (aspect D). The time perspective of the characterisation factor also

influences results, as the choice of time period influences the relative

importance of different types of GHG emissions (aspect B).

The handling of multifunctional EoL processes (aspect E) (such as when the

energy content of non-energy forest products, e.g. building materials, is used

at the products' EoL for heat and/or power production) also affects results,

as this requires allocation (treated in Section 5.2.3).

One example of carbon exchanges is soil organic carbon changes (aspect F).

Stocks of carbon stored below ground are especially large for boreal forests

[74] (the dominant forest type in Sweden), and forestry might interfere with

these stocks and emit soil carbon. The scale of these emissions could be

considerable [72, 75].

There are also indirect climate effects, in the form of indirect land use

change (ILUC) (aspect G). ILUC occurs when there is competition for land in

one location which displaces some other potential use of that land to another

location. ILUC can result in a positive or negative climate impact, which can

be significant compared to the direct climate impact of bio-based products

[46].

Another phenomenon which can have an effect on climate impact is the

albedo effect, which is the capacity of the earth’s surface to reflect sunlight

back to space. The albedo effect (aspect H) is greater when the surface is

white (e.g. snow covered) and smooth (e.g. clear-cut forest) [76, 77]. In

addition there is the effect of aerosols (aspect I), which are created by

organic vapours from the forest and reflect sunlight in the atmosphere [78].

5.2.3 Allocation

One of the most discussed methodological issues in LCA is the allocation of

emissions and other environmental burdens between products which are co-

produced in a process [60]. This is an important issue in LCAs of bio-based

products and biorefinery products [79-85], as the products are often

18

produced in complex common processes which are seldom feasible to split

into sub-processes. Figure 5 illustrates how this applies to both the

cultivation of the feedstock (with, for forestry, co-products such as timber,

pulpwood, and fuelwood) and biorefinery processes (with co-products such

as pulp for paper or textile production, fuel, and heat).

Figure 5 Flowchart of a biorefinery system. Included flows correspond to the co-

products of two multifunctional processes (forestry and biorefinery).

ISO 14044 provides a stepwise process for dealing with multifunctional

processes. Wherever possible, allocation should be avoided by division into

subprocesses [35]. This is, however, seldom possible in practice, as

multifunctional processes are not likely to consist of physically separate sub-

processes [86]. Another possibility is to use system expansion whereby the

functional unit is set to include the functions of all co-products, or a main

product is selected and given credit for the avoided environmental burdens

from products assumed to be substituted by its co-products. If this is not

possible, partitioning should be applied, in which the environmental burdens

are allocated to co-products based on an attribute, such as a physical

attribute like mass, volume, or energy content, or an economic attribute like

production cost or market value [35]. The choice of allocation method in

biorefineries and industrial symbiosis systems producing bio-based products

has been shown to provide diverging results [22, 87]. The ISO standard

states that when several allocation procedures seem applicable, a sensitivity

analysis should be conducted, so that the impact of different procedures on

the result of the study is illustrated [35].

19

5.3 Uncertainty in LCA

If we would be able to model the world perfectly, as is assumed in the

positivist worldview [88], LCA would have unlimited potential. LCA results

would provide reliable and consistent support to various decisions:

individual consumer choices, company investments, and governmental

policy development. However, as was outlined in Section 5.2.1-5.2.3, there

are various aspects that diminish the accuracy of LCA results. The influence

that one parameter (such as allocation procedure) has on the value of

another (such as the GWP) can be defined as sensitivity [89]. Sensitivity

contributes to variability or uncertainty. While uncertainty can be

understood as the result of, for example, inaccurate measurements and

model assumptions, variability can be understood as the consequence of

inherent variations in the real world [90].

There exist different typologies for describing uncertainties in LCA [91]. One

comprehensive typology is that by Huijbregts et al. [92], who distinguish

uncertainty according to three types:

1. Parameter uncertainty: Uncertainty in data caused by imprecise

estimates, assumptions, or measurements

2. Scenario uncertainty: Uncertainty caused by value choices

3. Model uncertainty: Uncertainty in a model’s ability to represent

the real world

The uncertainty stemming from choices of system boundaries (Papers I, II

and V) and allocation methods (Paper IV) can be categorized as scenario

uncertainty. Categorising the uncertainty in the climate impact assessment

of forest products (Paper III) is less obvious. The uncertainty of how

different aspects contribute to climate impact causes model uncertainty.

Examples are the biogeophysical mechanisms of the forest that, among

others, regulate the emission of organic vapours, and the amount of solar

radiation reflected by the land surface (albedo), biogeochemical processes

such as sequestration and emission of CO2 [93], and the variability of

characterization factors. Choices of time horizons and the handling of

multifunctional EoL processes lead to scenario uncertainty. Type 1,

parameter uncertainty, is not covered specifically in this thesis. This

delimitation is further discussed in Section 7.2.

20

5.3.1 Attributional and consequential LCA

When we talk about uncertainty, we should also mention the distinction

between attributional and consequential LCA. An attributional LCA can be

referred to as the description of the environmentally relevant physical flows

to and from a life cycle and its subsystems, while a consequential LCA can be

referred to as the assessment of the consequences of actions to the flows

[94].

It can be argued that an environmental assessment only covers actual effects

if a consequential approach is applied in which all possible consequences are

regarded. This has been heavily debated. For example, Plevin et al.’s [95]

critique of the practice of not including marginal system changes when

climate mitigation potentials are assessed attracted four letters to the editor

and led to an editorial outlining the controversy [96]. What should be

termed consequential and attributional is not clear-cut, and it can be

disputed when a consequential or an attributional approach is appropriate

[97].

One question is whether or not to account for consequences, another is

whether it is possible to do so. Which effects to include is seldom trivial [53,

98] especially when the value chain assessed includes a magnitude of

decision-makers, and the scale of future production is uncertain, such as in

the case of bio-based products [33, 99]. In this thesis, the sensitivity of

various methodological choices is discussed. The general approach is

attributional LCA, but some of the methodological choices can be defined as

components of consequential LCA: the use of system expansion (Paper IV)

and accounting for ILUC (Paper III).

5.3.2 LCA as decision support

All LCA applications (e.g. identification of value chain hot-spots and

comparison of products) ultimately aim at influencing action to obtain

improvements [100]. Examples of decision-making contexts of relevance for

LCAs of forest products (inspired by lists of LCA contexts and purposes in

the literature [23, 29, 35, 101, 102]) are listed in Table 1.

21

Table 1 Examples of decision-making contexts of relevance for LCAs of forest

products.

Stand-alone LCA Comparative LCA

Specific

product

Context 1: Guiding a development

project aimed at incremental

improvements of an existing

forest product by identifying

climate impact hot-spots of the

product life cycle and

continuously screening proposed

development routes.

Context 2: Guiding public

procurement by comparing the

climate impact of a forest product

and alternative products.

Generic

product

Context 3: Determining the

priorities of a national research

programme for financing

research and development on

forest products by identifying

climate impact hot-spots in the

life cycle of a certain category of

forest products.

Context 4: Guiding policy-making

aimed at supporting low-carbon

technologies for maximum climate

impact mitigation by evaluating

the benefits of a certain category

of forest products compared to

alternative products.

As LCA is becoming increasingly popular [9, 103], ensuring credibility

becomes more and more important. If uncertainty is not properly taken into

account, an LCA may give rise to incorrect decisions [104, 105]. Another

consequence can be that decision-makers will not fully acknowledge an LCA

because they consider the uncertainty of the results to be too high,

underestimated, or ignored [106].

22

23

6. Methods and Case studies

This section describes and motivates the methods used to pursue the aim of

the thesis. LCA was used as an overarching approach to assess all the case

studies and to derive methodological insight into system boundary setting,

climate impact assessment practice, and allocation procedures. Case studies

have a long tradition as a research method in management research [107]. In

this thesis, case studies are used as a method to quantitatively test the

relevance of uncertainty issues, to guide LCA method development. Table 2

provides an overview of the methods and case studies used in the papers to

address the research questions.

Table 2 Methods and case studies used in the appended papers and research

questions addressed.

Paper RQ Method Case study

I RQ1 Sensitivity analysis of

system boundary setting

with LCA

The environmental impact of the

current Stenungsund chemical

industry cluster

II RQ1 Sensitivity analysis of

system boundary setting

with LCA and

environmental cost-

effectiveness analysis

The potential for environmental

impact reduction for the

Stenungsund chemical industry

cluster by introducing 25% forest

feedstock and energy integration

III RQ2 Literature analysis to

reveal common climate

impact assessment

practices, and extreme

value analysis to assess the

possible uncertainty range

of results

The climate impact of a wood-

based ethanol fuel and a timber

structure building

IV RQ3 Allocation method testing

and development

The climate impact of biorefinery

products

V RQ1 Sensitivity analysis of

system boundary setting

with LCA

The climate impact of a fossil-

based plastic box, compared to a

hypothetical fossil-bio-blend box,

and a hypothetical bioplastic box

24

Finnveden et al. [60] distinguish between three ways of approaching

uncertainty. The “scientific” way is to retrieve better data and make better

models. The “social” way is to discuss uncertainty issues with stakeholders to

find consensus on data and choices. The “statistical” way, which is what is

used in this thesis, is not to try to remove or reduce uncertainty, but to

examine the relevance. This is done through quantifications of the extent to

which LCA results could change due to choices or uncertainty in existing

models.

6.1 Sensitivity analysis of system boundary setting

The sensitivity of system boundary setting was explored in Papers I, II, and

V. In the first two papers, the Stenungsund chemical industry cluster

(introduced in Section 4) was used as a case study to explore the effect on

results of including or excluding life cycle phases in LCA.

In Paper I, the approach was to study the companies in the industry cluster

as a single unit. The functional unit of the study was set to be the total

production of the system in 2011. The value chain of the many industry

cluster products can be divided into three: upstream, on-site, and

downstream processes (See Figure 6).

By assessing the environmental impact of both upstream and onsite

processes, and applying a range of environmental impact categories, the

sensitivity of leaving out processes outside the cluster gates could be

demonstrated. A truly holistic study would also have included downstream

processes. This was, however, not possible, as tracking the path of the vast

array of products would be an enormous undertaking. What we could

achieve was to estimate CO2 emissions from an assumed end-of-life

incineration of the products. It was possible to make this GWP estimation by

using the carbon content of the products as a projection.

25

Figure 6 Simplified flowchart of an industry cluster.

While Paper I deals with the potential of applying a life cycle perspective to

the strategy development of an industry cluster, the perspective was

implemented in practice in Paper II. Two strategies were evaluated:

1. The “forest strategy” which is the exchange of 25% of the current

fossil feedstock with forest feedstock and, thereby, producing bio-

olefins (described in Section 4), and

2. The “energy integration strategy”, which is the reduction of

emissions from fossil fuel production and combustion through the

implementation of hot water systems collecting and distributing

excess process heat, and the redistribution of excess steam and fuel

throughout the industry cluster (further described in Hackl [49]).

We sought to demonstrate whether or not and how the results of the

evaluation change when only consequences within the industry cluster are

examined, as opposed to the entire value chain of the cluster.

Adding an economic dimension contributes with a more equal basis of

comparison than only “environmental impact reduction”, as the two

strategies investigated in Paper II are highly different in both nature and

scale (e.g. required infrastructure change). There are various ways of

combining environmental and economic metrics. One much used concept is

“eco-efficiency”, which is defined in the ISO 14045 standard [108] as the

ratio between the economic value created by a product system and the cost in

terms of environmental impact caused. The usefulness of the concept has

been questioned, as it promotes relative environmental improvements in

product value chains but not necessarily an absolute improvement in terms

of a shift to a more sustainable business structure [109]. Consequently, a

more goal-specific terminology was chosen: “environmental cost-

26

effectiveness analysis” [110], in order to assess the decreased climate impact

per invested Euro as opposed to the economic value created per unit of

environmental damage.

As outlined in Section 3, Paper V can be seen as complementing the

research in Papers I and II with a focus on the use phase. The approach

was to compare the climate impact of the life cycle of an engine component

storage box currently made of the fossil-based plastic acrylonitrile butadiene

styrene (ABS) (Figure 7) with a hypothetical case study of the same box

produced from a blend of polycarbonate and the bioplastic polylactic acid

(PC/PLA), and a box made of a biopolyamide (PA1010).

Figure 7 Plastic storage box for engine components made of acrylonitrile

butadiene styrene (ABS).

The reason for choosing the PC/PLA and PA1010 materials was twofold: 1)

both materials could be used for the application (outcome of deliberations by

the polymer experts in the project group), and 2) PLA and PA1010 represent

alternatives: PA1010 is a high performance and durable material [111], but

costly. PLA is less costly but sensitive to heat and humidity [112] (which is

why a blend with PC was assumed). Although the biomass feedstock of PLA

and PA1010 are corn and castor oil, respectively, the case can also be seen as

relevant for the forest focus of the thesis, as wood can be expected to be a

future feedstock for many materials, including plastics [113].

27

6.2 Uncertainty analysis of climate impact assessment

practices

In Paper III, an extensive literature analysis was conducted to determine

how LCA practitioners currently assess the climate impact of forest products.

A range of product categories were investigated: energy, fuels, construction

materials, plastics, chemicals, and other commodities. Forest biomass types

included solid timber, forest residues, and industrial waste wood, from slow-

grown boreal forests to short-rotation wood crops. To determine common

practice, we analysed how the climate impact aspects of Figure 4 (Section

5.2.2) were handled in the climate impact assessment of each paper. The

aspects cover what has (until now) been identified as having a potential

effect on the climate impact of forest products. 101 journal papers were

included in the literature analysis, published 1997-2013.

To show how different aspects of climate impact can be expected to be of

relevance for the aggregated life cycle climate impact of forest products, we

employed two case studies. We selected a short-lived product (a wood-based

fuel: ethanol, with data from Bright and Strømman [114]) and a long-lived

product (a building with a solid wood structure and wood materials in the

building envelope, with data from Peñaloza et al. [115]). The rationale for the

cases is that they represent extremes in terms of service life and, therefore,

different aspects of climate impact can be expected to be of relevance for

their aggregated life cycle impact. The timing of GHG emissions and carbon

sequestration (aspect A in Figure 4) and credit for carbon stored in products

(aspect D in Figure 4) increase in relevance with the service life of the

product.

Our approach was to demonstrate the most extreme results, positive and

negative, which could be obtained by including potentially relevant climate

aspects in the climate impact assessment. The extreme value analysis

(referred to as “calculation of extreme values” in Guinée et al. [63]) was

conducted with methods or approaches that differ from those currently most

often applied. As no standard or universally agreed procedure for calculating

the climate impact from some of the aspects exists, we used figures from

28

other studies as estimates. Aspects A, D, and E were only applied to the

building case study as it is a long-lived product. The approaches are

presented in Table 3.

Table 3 Methodological practices applied in the case studies in Paper III. Letters A-

I refer to the climate aspects in Figure 4, section 5.2.2.

Climate aspect Alternative practice

A. Timing of GHG emissions

and carbon sequestration

Discounting of emissions and dynamic LCA

[116].

B. Time perspective of the

climate impact metric

20 years or 500 years [117].

C. Climate neutrality

assumption of biogenic CO2

sequestration and emissions

Biogenic and fossil CO2 emissions are

assumed to have the same climate impact.

D. Credit for carbon stored in

product

Carbon storage is credited using the ILCD

Handbook method [102] and the method

proposed by Cherubini et al. [73]

E. Credit for avoided climate

impact due to multifunctional

EoL processes

Credit for replacing energy from solar power,

natural gas, or coal.

F. Climate impact from soil

disturbances

Both negative and positive climate impact are

considered. The calculation is based on the

model of Kilpeläinen et al. [118] for negative

impact and the results from Stephenson et al.

[119] for positive impact (only relevant for the

fuel case study).

G. Climate impact from ILUC Excluded due to lack of knowledge and

methodology.

H. Climate impact from

changes in the albedo effect

Considered using results from Cherubini et al.

[120].

I: Climate impact from

aerosols

Excluded due to lack of knowledge and

methodology.

29

6.3 Allocation methods testing and development

The ISO standard requires that a sensitivity analysis is conducted when

different allocation methods seem applicable [35]. Huijbregts [39] suggest

dealing with uncertainty caused by choices with either standardization,

expert judgements, or scenario analysis. In Paper IV, we used scenario

analysis to explore how the choice of allocation method influences results.

Six methods were tested:

1. The main product bears the entire environmental burden.

2. Substitution: the entire environmental burden of the multifunctional

process is allocated to the main product, but the main product is also

given credit for the avoided emissions of products assumed to be

substituted with the other co-products.

3. Traditional partitioning based on economic value.

4. Traditional partitioning based on exergy.

5. A hybrid method combining elements of substitution and

partitioning, developed by Cherubini et al. [26]. The method

allocates most of the environmental burden to the product that

prevents the most environmental burden in other systems.

6. An alternative hybrid method developed by us, using the opposite

rationale of the Cherubini et al. [26] method, allocating less

environmental burden to co-products with great potential to

mitigate environmental burdens.

A fictitious biorefinery system was used for the case study, producing

sulphate pulp for paper production (50 t/h), a lignin-based precursor to an

automotive fuel (purified from the black liquor of the pulping process) (3.3

t/h), methanol (0.05 t/h) (see Section 4 for technical details), and heat (16

GW). These products can potentially be produced at a traditional pulp mill

converted into a modern biorefinery. Such a plant would be highly integrated

in terms of the use and recovery of chemicals and energy, and it would, thus,

be highly challenging to divide the processes into subprocesses and, thereby,

avoid allocation.

30

31

7. Results and Discussion

This section presents the results of the case studies used to approach the

research aim of the thesis. Uncertainty levels, implications, and measures for

how to deal with the identified uncertainty are reviewed. The ability of the

case studies to cover uncertainty issues for forest products is discussed, as

well as implications of the results for the role of LCA.

7.1 Identifying, estimating, and dealing with

uncertainty

7.1.1 System boundaries

Research question 1 is: What is the relevance of system boundaries for the

uncertainty of forest product LCA results? To answer the research question,

LCA was applied to two systems: a plastic motor component storage box

value chain and the value chain of the product portfolio of a chemical

industry cluster.

To what extent can single- or multi-product LCA results be

influenced by the inclusion/exclusion of life cycle phases?

The environmental impact of the multi-product chemical industry cluster

was assessed in Paper I. LCAs of industrial symbiosis systems are usually

limited to processes within the cluster itself [67]. Our assessment, however,

demonstrates that the major share of environmental impact of such systems

can originate from processes outside the cluster gates. All seven

environmental impact categories assessed for the Stenungsund chemical

industry cluster were found, to a greater extent (59-100%), to be caused by

off-site rather than on-site processes. Dong et al. [121] and Sokka et al [21]

also found that a major share of environmental impact for industrial

symbiosis systems can be caused by off-site processes. The fact that the

systems they assessed are located in other countries (China and Finland) and

that the systems are of different sizes and industries (a whole economic zone

and a pulp and mapper mill symbiosis) underlines that the importance of

off-site processes is not limited to our case study.

32

Dong et al. [121] and Sokka et at. [21] only included on-site and upstream

processes (impact from the production of materials and energy).

Downstream processes were excluded, other than the waste management

from the industry park (Dong et al. [121]), which was found to represent

limited impact. Our estimation of downstream GWP contributed to the

analysis with intriguing insight. An assumed EoL scenario of product

incineration was responsible for 60% of the life cycle GWP, rendering the

upstream and on-site processes with only 24% and 16% of the impact,

respectively. This underlines that the choice to limit an assessment to on-site

processes contributes substantial uncertainty to the actual environmental

impact of industry clusters and industrial symbiosis systems. Even though

on-site GHG emissions from the Stenungsund industry cluster accounted for

the smallest share of the total GWP results, the impact was significant in a

Swedish context. On-site GHG emissions corresponded to as much as 1.5% of

the 61.4 million tonnes of GHG emissions in Sweden in 2011 [122].

In Paper II, again the importance of a life cycle perspective was

demonstrated. The study in the paper examined the potential identified in

Paper I in practice, by adopting a life cycle perspective on the evaluation of

the potential of two strategies to reduce environmental impact. It was found

that the outcome of the evaluation depends heavily on whether only on-site

consequences are assessed or if upstream and downstream processes are

also included. Whereas the potential of the energy integration strategy to

reduce GWP was the greatest on site, due to the reduced burning of fossil

fuels within the industry cluster, on-site reductions were only a minor share

of the total reduction potential of the forest strategy (Figure 8). The energy

integration strategy could result in a 20% reduction in the GWP caused by

GHG emissions occurring outside the cluster boundaries, whereas the forest

strategy could result in a reduction of up to 82% outside the cluster

boundaries. Figure 8 does not show absolute results. The forest strategy

represents a much greater potential to reduce GWP (1633 kton CO2-eq) than

the energy integration strategy (97 kton CO2-eq), but it entails substantially

higher investment costs (376 and 59 million Euros, respectively [49, 123]).

33

Figure 8 GWP reduction potential of replacing fossil feedstock with forest-based

feedstock and increasing thermal energy integration in the Stenungsund chemical

industry cluster.

What it was not possible to assess was the influence of including or excluding

the use phase of the cluster products. 45% of the externally sold products are

plastics without emissions to air in the use phase. However, a range of

chemicals in the product portfolio, such as paint, fuels, hygiene products,

lubricants, and asphalt, can give rise to emissions from heating, mixing, and

application [124]. For the strategy comparison, the exclusion of the use

phase has no effect on results, as the industry cluster product types and

volumes would be the same for all scenarios (the forest olefins would be

drop-in chemicals). The exclusion of the use phase, however, limits the

ability to identify improvement potential in that particular life cycle phase, as

well as the ability to capture the potential of strategies which could reduce

use phase environmental impact.

The case studies in Papers I and II consider an industry cluster in which

the companies were open and willing to share information on purchased and

sold material and energy volumes, and on-site emissions. Such openness is,

however, not always the case. A solution in cases when data is not available

can be to employ hybrid LCA, which is an integration of Economic Input-

Output (EIO) analysis and LCA. An EIO analysis uses sectoral monetary

transaction matrixes that describe relationships of industries within a

national economy [125]. It has been argued that hybrid LCA reduces

uncertainty as it mitigates data unavailability in LCA and aggregation errors

in Input-Output analyses [126, 127]. An example of hybrid LCA used for

industrial symbiosis systems is the study by Dong et al. [121], where the

method was employed in the carbon footprinting of an industry park in

China. There are, however, two limits to the approach. The first is that EIO

34

only contributes with information on GHG emissions, thereby excluding the

possibility of including environmental impact categories other than GWP.

The second limit is that the aggregation level of the data hinders the

possibility of providing detailed guidance on improvement strategies, as

provided in Paper II.

The inability to assess the use phase due to a complex system structure was

overcome in the study in Paper V, in which single product life cycles were

investigated. The climate impact of the life cycle of an engine component

storage box currently made of the fossil-based plastic ABS was compared to a

hypothetical case study of the same box made from the fossil-bio-plastic

blend PC/PLA and a box made of the bioplastic PA1010. It was found that

excluding the use phase from the assessment contributes to great uncertainty

in results. Whereas the climate impact of the production of the different

plastic materials differs only slightly (20%), the PC/PLA engine component

storage box was found to have a more than six times higher climate impact

than the ABS and PA1010 boxes, when the entire life cycle is taken into

account. The dominant contributor to climate impact is premature material

deterioration due to humidity and heat during service life, which prevents

the product from fulfilling its required function (five years of service life).

Uncertainty in LCA results arising from a disregard for the use phase is not

necessarily related to the environmental impact of the use phase processes

themselves. Use phase process impact can play a minor role in the total life

cycle of a product. The washing process of the boxes in Paper V played a

minor role, as has also been shown for the washing process of garments

[128]. More important can be the effect use phase processes have on product

deterioration. Several types of long-lived products do not demand

maintenance in the life cycle phase (e.g. car panels, computer cases, and

plastic shelving). Maintenance is, however, not the only potential source of

material degradation. Proximity to overheated mechanical and electrical

components, as experienced by car panels and computer cases, could also

inflict deterioration [129].

To take the intended application and function of materials into account in

material and product development and environmental assessments, it is

necessary to know how the material will react to use phase processes. A lack

35

of knowledge of real-life material behaviour in the use phase can be

overcome by laboratory experiments conducted by material experts, as in

Paper V. Another option is to employ existing models developed for

predicting material behaviour, such as Miller et al. [130] did in a study on

natural fiber-reinforced composite materials.

In what way can guidance to decision-makers be influenced by the

inclusion/exclusion of life cycle phases?

The focus on the cradle-to-gate environmental performance of bioplastics,

the most common practice [51], could contribute to the impression that the

sole challenges related to a transition from fossil-based plastics to bioplastics

occur in the biomass cultivation and material production. Bioplastics can,

however, be made into a variety of products for a variety of uses [51], so

material application and EoL options can be of great importance. LCAs that

exclude life cycle phases beyond production could mislead decision-makers

in the plastics industry to promote bioplastic research and development

without any regard for downstream processes. In Paper V, the PC/PLA

blend was assumed to be incinerated at EoL, as there is currently no market

for recycled blends [131]. Piemonte [132] argues that the best waste

management option for bioplastics from an energy saving perspective is

recycling. Ensuring the possibility to recycle future bioplastic products could

thus be important.

It could be assumed that a product that has received more attention in the

LCA world would be assessed based on service and not mass or volume.

Biofuels have received much attention because of mandatory production

targets [31], and many LCAs have been performed on biofuels. However, in a

literature study of 72 biofuel LCAs only 1/3 of the studies were found to

employ a service-based functional unit: km driven [133]. Gnansounou et al.

[34] argue that it is of great importance to consider service related to

distance travelled, as the mechanical efficiency can vary from one fuel or

engine to the other. The life cycle environmental performance of biofuels

cannot be determined based on litre of fuel, and neither can it for bioplastic

products be determined based on kg of plastic.

36

The precision of the guidance for single-product systems is enhanced with a

life cycle focus. The same goes for the guidance for multi-product systems.

For the Stenungsund industry cluster, a transition to a forest feedstock based

production is encouraged if all relevant processes are included in the

environmental assessment, as 82% of the potential for GWP reduction is

located outside the cluster boundaries.

The environmental cost-efficiency analysis in Paper II was an additional

means for exploring the implications of applying different system

boundaries: assessing environmental impact reduction benefits for the

isolated industry cluster, or for the whole value chain of the cluster products.

Figure 9 shows how the comparison of benefit in terms of reduced GWP per

Euro spent has the opposite result for the two scenarios, and that the forest

strategy is clearly superior from a life cycle perspective. The environmental

cost-effectiveness, thus, adds a dimension to the environmental assessment,

as it indicates that value-for-money depends on system boundaries. Philp

[11] argues that the potential of bulk bio-chemicals (e.g. olefins) to reduce

GHG emissions is hindered by the high economies of scale of

petrochemicals, which have had their process and supply chains perfected

and production plants amortised. Another economic hinder are policy

incentives benefiting biofuels and not bio-based chemicals [134]. The

environmental cost-effectiveness analysis of Paper II could provide a

rationale for investing in bio-based production in spite of the seeming

economic superiority of petrochemicals and the current tax exemption policy

for biofuel.

37

Figure 9 Environmental cost-effectiveness of the forest strategy and the energy

integration strategy.

Ristola and Mirata [135] argue that industrial symbiosis systems have the

potential to support the development of alternative systems with a more

desirable environmental profile. The mere existence of symbiotic exchanges,

however, does not necessarily promote a sustainable transition. When

symbiotic exchanges reduce the demand for feedstock and energy volumes,

costs will also decrease. The consequence can be that the industry prevails

and that the necessity of a radical transition decreases (such as basing

production on bio-based feedstock). The most used example of industrial

symbiosis in the literature [136, 137], the Danish Kalundborg industry

cluster, has experienced an increase in resource efficiency due to symbiotic

exchanges [138]. However, the cluster has also increased its oil refinery

capacity significantly in recent years [139]. The oil-based industry has, thus,

prevailed. Reduced costs due to symbiotic exchanges could be an important

contributor to that development. As industrial symbiosis systems are both

promoted and increasing in numbers around the globe [140, 141], it becomes

more and more important that their expansion and development is

supported by holistic assessments.

7.1.2 Climate impact assessment

Research question 2 is: What is the relevance of uncertainty in the climate

impact assessment of forest products? To answer the research question,

common practice was identified, and alternative practices were applied to

case studies.

38

To what extent can results change if climate aspects not commonly

included are included in the climate impact assessment?

The analysis of 101 forest product LCAs in Paper III reveals that the

common climate impact assessment practice is to:

seldom (3%) regard the timing of GHG emissions and carbon

sequestration,

most often (69%) use a climate impact metric with a 100-year time

perspective,

most often (69%) regard biogenic CO2 emissions as climate neutral,

never credit carbon storage in products,

only credit avoided impact in 34% of the studies including

multifunctional EoL processes,

seldom (7%) account for soil disturbances, and

never or almost never account for impacts due to a changed albedo

effect (0%), ILUC (0%), and the forest’s influence on aerosol

formation (1%).

In addition, the methodological choices are often not clearly articulated,

causing additional uncertainty when interpreting results.

Based on the analysis, both the common practice and methods or approaches

that differ from those most often applied (as listed in Table 3, Section 6.2)

were applied to two case studies: a forest-based ethanol fuel and a timber

structure building. The forest products were compared with functionally

equivalent non-forest products, using the common practice as well as the

lowest and highest results possible with any combination of the alternative

methods. Figure 10 shows the result of the fuel case study and indicates a

striking difference in result when different climate aspects are taken into

account. It also shows that the inclusion or exclusion of climate aspects can

render the climate impact of the ethanol both considerably lower and higher

than the petrol. This means that the results of climate impact assessments of

forest studies are highly uncertain.

39

Figure 10 Results from the fuel case study, for driving 1 km with an ethanol fuel

(100% forest-based) and petrol, respectively.

Figure 11 shows the result of the building case study. The lowest and highest

results for the wood building also differ, but not to the same extent as for the

ethanol. The comparison between the wood and concrete buildings is also

less influenced by the choice of methodology than the comparison between

the fuels. This is because the operational energy dominates the results, and

the compared buildings have similar heating and electricity use in the

operation phase. Since the heating demand is assumed to be supplied mainly

by non-bio-based energy, the difference does not significantly influence the

outcome of different climate impact assessment practices. However, the case

study considers buildings with low energy use, and the results are, therefore,

more sensitive to choices in the climate impact assessment methodology

than conventional buildings in which the operational energy would be more

dominant. If a high proportion of operational energy came from biomass

sources, the results would be more sensitive to the choice of methodology.

Finally, it should be noted that the building envelope in the studied concrete

building is very similar to the envelope in the wood building, with a high

content of wood materials. If the wood building would be compared with a

40

building made entirely of concrete, the effects of changes in climate

assessment methodology would be more significant.

Figure 11 Results from the building case study, for one square metre of a multi-

dwelling building with a wood or concrete structure, respectively.

It was not possible to estimate the effect on results of ILUC and aerosols. The

quantitative assessment of aerosols are challenging as there is still no

complete understanding of how the particles react [142]. Klein et al. [66]

state that ILUC should be regarded for forest products but that there are still

no methods to estimate whether there is such an impact. Lambin and

Meyfroidt [143] claim that the increasing land requirements for industrial

forestry could replace natural forests and encroach on agricultural land.

Whether an increase in demand for Swedish boreal forest biomass could

cause more forest biomass to be extracted elsewhere is not clear. Currently,

less of this biomass is harvested than what grows yearly [144]. However, if

biomass demand increases substantially as a result of a forest based bio-

economy strategy, ILUC could become a relevant impact to consider.

The biggest challenge with climate impact assessment of forest products is

that the uncertainty of results is the consequence of so many different

sources of uncertainties, for example, not only a lack of understanding of

41

phenomena in nature but also the spatial and temporal variability of these,

and the choice of model for describing them.

What are the current possibilities for dealing with uncertainty?

Standards and guidelines for the LCA of forest products exist. Examples are

the EU sustainability criteria for biofuels [31] and the Product

Environmental Footprint (PEF) guide [145]. These do not, however, include

guidelines on how to deal with the aspects of Figure 4 (Section 5.2.2) other

than changes in soil organic carbon. Such changes should, according to the

standards, only be included if there is land use transformation (e.g. from

forest land to agricultural land). This is not the case for Swedish boreal forest

products. The recent developed Swedish standard for LCA on bio-based

products states that timing can be important, but that it should be reported

separately [146]. Thus, the use of the standards generates the same results

as the common practice (identified in Paper III). This is indicated in Figure

12. The figure is from Sandin et al. [147] and shows the potential for climate

impact reduction by substituting forest products with non-forest products

(bio-butanol with diesel, viscose with cotton or polyester, a timber structure

building with a concrete structure building, and bio-methanol with natural

gas-based methanol).

Figure 12 also includes a climate impact assessment method which takes the

timing of GHG emissions and carbon sequestration into account, dynamic

LCA [116]. Results are shown for different temporal (20 and 100 years) and

spatial (stand and national) system boundaries, as dynamic LCA leaves it to

the practitioner to select such boundaries. The method is, however, no

complete solution, as it does not address aspects such as aerosols, albedo,

and ILUC. In addition, the method is only one of several suggested

“advanced” climate impact assessment methods within LCA (there is e.g.

also GWPbio [73]). Dynamic LCA is neither included in any established LCA

framework or standard. Moreover, as can be seen in Figure 12, results from

using dynamic LCA diverge greatly (due to the choice of temporal and spatial

system boundaries). Thus, the method is not a solution to the high variability

in LCA results that was pointed out in Section 1.2.

42

Figure 12 Climate impact reduction if a forest product is assumed to substitute its

benchmark product. Adapted from Sandin et al. [147]

Although there are currently no methods available that include all potentially

important climate aspects, the high interest in LCA of bio-based products

and the bio-economy will likely fuel the method development process.

Advances in LCA, however, also rely on knowledge generated in related

fields, such as climate science. Thus, improving climate impact assessment

practices is not something the LCA research community can overcome in

isolation [148].

Even though uncertainty in climate impact assessment results is currently

unavoidable, the uncertainty can still be managed. As long as the LCA

practitioner is aware of and communicates uncertainty, results can form part

of valuable decision support. In Paper II, the potential for GWP reduction

of a shift in the production in the Stenungsund industry cluster from fossil

feedstock to forest-based feedstock was evaluated. Biogenic CO2 emissions

43

were assumed to be climate neutral, and, thereby, the forest strategy was

determined to provide substantial downstream impact reduction potential.

In a long-term perspective, the climate neutrality assumption holds true. If,

however, short term climate mitigation is the target, it could be relevant to

take into consideration that the carbon cycle has a time lag in slow-grown

boreal forests. Such discussions should accompany climate impact

assessments. In addition, practitioners should be careful in stating that a

forest product is environmentally superior to a fossil counterpart based on

climate impact assessments. As can be seen in Figure 10, a forest product can

be assessed to have a higher or lower climate impact than its fossil

counterpart, depending on which climate aspects are regarded.

7.1.3 Allocation

Research question 3 is: What is the relevance of allocation for uncertainty

in biorefinery product LCA results? To answer the research question,

Paper IV assessed the influence of different allocation methods on the

climate impact assessments of biorefinery products.

For which types of products is the choice particularly important?

Figure 13 shows the results for two of the biorefinery outputs: the main

product, pulp, and a by-product, methanol.

From the figure, it is evident that different methods can yield very different

results. This is most prominent for the methanol. The simplest methods: 1)

the main product bears the entire burden, 3) economic allocation, and 4)

allocation based on exergy, yield similar results for the pulp, but not for the

methanol. The reason the results are similar for the pulp is that it is the

biorefinery product that dominates both in physical and economic terms.

The difference is more prominent for more advanced and consequential

methods: 2) substitution, 5) the hybrid method, and 6) the alternative

hybrid method, especially for the methanol. Method 6 yields extreme results

compared to other methods when the studied product is physically

insignificant in relation to one of the other co-products (in this study, three

orders of magnitude).

44

Figure 13 Climate impact of the biorefinery products pulp and methanol using

different allocation methods. Numbers 1-6 refer to the allocation methods listed in

Section 6.3.

For which types of decision contexts is the choice particularly

important?

In attributional studies, if a physically dominant product of the

multifunctional system is in focus (such as the pulp), relevant allocation

methods (1, 3, and 4) yield similar results, and the choice of method is, thus,

less important. But if a non-dominant product (such as the methanol) is in

focus, the choice of method is more important. In consequential studies, in

which system expansion with substitution is a reasonable option, the choice

of allocation method is more important than in attributional studies.

The ISO 14044 [35] hierarchy of allocation methods (see Section 5.2.3) is

recommended in the Swedish standard on LCA of bio-based products [146],

45

and by Ahlgren et al. [25] for biorefinery products. However, as the hierarchy

is challenging to follow in many cases [149], there is a need for more case-

specific guidelines. Some product-specific recommendations exist. For

example, Tufvesson et al. [150] recommend system expansion for bio-based

bulk chemicals, and partitioning based on economic value for bio-based fine

chemicals. The Renewable Energy Directive [31] requires partitioning based

on energy content for biofuels. The findings herein highlight the influence of

physical scale and decision context and are, thus, a contribution to the

growing body of recommendations. As biorefineries are seen by the EU as a

pillar of sustainable biomass processing in the future [151], the

environmental impact of biorefinery products will continue to be in focus,

along with a demand for thoroughly thoughtout and clearly communicated

allocation choices.

The method proposed by Cherubini et al. [26] (method 5) was found to be

potentially problematic because it favours products with low potential to

mitigate environmental burdens. The results of the alternative hybrid

method in this thesis (method 6), which favours products with high potential

for mitigation, were, however, highly influenced by the relative physical

significance of its co-products. The result of assessments using method 6

could be difficult to interpret for decision-makers accustomed to traditional

allocation procedures. Although conceptually interesting, the alternative

hybrid method needs further testing and/or development to become a viable

option. It may be appropriate with a cut-off rule regarding the order-of-

magnitude differences between co-products.

7.2 Representability of the case studies

As the title implies, this thesis is focused on uncertainty and forest products.

The possibility to generalize the thesis contributions depends on how much

of the uncertainty aspect and how many types of forest products the thesis

covers.

Of the three uncertainty types listed (see Section 5.2), this thesis covers two.

The one not addressed specifically is parameter uncertainty. Parameter

uncertainty regards the uncertainty of input data due to imprecise,

46

incomplete, outdated, or lacking measurements. A relevant example is the

challenge of obtaining data on enzyme production, which has been shown to

represent a significant environmental impact in the production of ethylene

based on woody biomass [152, 153]. To reduce parameter uncertainty, many

databases have been developed in the last decades [60], and LCA software

provides the ability to calculate parameter uncertainty using Monte Carlo

analysis. Parameter uncertainty has been addressed in several forest product

LCAs (e.g. [154-157]). While parameter uncertainty has been a focus for a

long time [158], uncertainty due to value choices has recently started to

receive more attention [91, 148, 159, 160].

Another parameter that uncertainty derives from is the choice among data

sources, as for example different technologies in factories producing the

same material [39]. McKone et al. [33] and Hetherington et al. [161] address

this as a grand challenge for LCA of biofuels, as many alternative production

routes exist, and it is uncertain what will be chosen as the primary market

alternatives in the future. The case studies in the papers of this thesis are

limited to Sweden, and the forest biomass is limited to boreal forest species

and Scandinavian forest management practices. Specific production routes

and technologies were investigated. Different conditions could yield different

results. Thus, the case studies cannot be claimed to represent all forest

product systems. Nevertheless, the case studies focused on some highly

important factors, such as the difference in features between short- and

long-lived products (which has implications for the climate impact

assessment), and drop-in versus non-drop-in products (which has

implications for the relevance of system boundaries).

Even though the thesis covers several uncertainty types, it does not cover all

causes of uncertainty. For example, other environmental impact categories

than GWP would also be relevant to study. An example of an aspect that is

highly relevant for forest products, and related with much uncertainty, is the

impact on biodiversity. Management and harvesting techniques used in

modern managed forests can have a significant impact on biodiversity due to

the resulting habitat changes [162, 163]. Despite this damage potential, there

is still no consensus or methodological agreement on how impact assessment

of biodiversity should be incorporated into LCA, both due to limited

47

understanding of effects of biomass harvesting on the intricate composition

of ecosystems, and a lack of inventory databases [164-166]. Another example

of a methodological LCA issue which would be relevant to focus more on is

the definition of functional unit (addressed for Paper V in Section 7.1.1). For

the multifunctional production process of biorefineries and industrial

symbiosis systems, defining a functional unit is not straightforward [23,

133], and thus a source of uncertainty.

The field of uncertainty in LCA of forest products includes numerous

aspects. This thesis contributes with pieces to the larger puzzle of gaining

knowledge and proposing improved practice.

7.3 The role of LCA in guiding the forest based bio-

economy

There are high expectations on LCA to guide product development and

strategies towards a bio-economy [167]. This thesis demonstrates that LCA

can support the environmentally sustainable transition to new products (e.g.

bioplastics), business constellations (e.g. industrial symbiosis systems and

biorefineries), and alternative systems with a more desirable environmental

profile (e.g. from a petrochemical to a biochemical production profile). The

thesis has, however, also demonstrated that there are uncertainties in the

LCA of forest products which should not be overlooked. So how can we

ensure that the potential of LCA is maximized, while challenges are

acknowledged?

LCA is currently being used to provide support for decisions regarding the

future of the European forest-based bio-economy. ClimWood 2030 [168]

and FORMIT [169] are projects that aim to analyse the climate mitigation

potential associated with the use of forest biomass in the EU. LCA is used in

the projects to assess the substitution effect of a range of forest products, and

the results are combined with outcomes of other methods that model

changes in forest carbon pools. This means that LCA practitioners in the

projects will encounter the uncertainties discussed in this thesis for product

types, production technologies, and harvesting locations representing the

whole of the EU. The LCA practitioners could choose not to address the

48

uncertainties and, instead, settle for the common way of assessing climate

impact, one allocation method, and limit system boundaries to the

production of a product. This would, however, mean that the guidance

provided by the LCAs on how to use forest biomass in the EU lacks

important information about uncertainty ranges. As this thesis has

demonstrated, the ranges can be substantial and should not be overlooked.

Uncertainty has been defined as “any deviation from the unachievable ideal

of completely deterministic knowledge of the relevant system” [170]. It is

important to bear the word “unachievable” in mind. To a lesser or greater

extent, uncertainty will always be present. Slade et al. [153] claim that

biofuel systems are inherently more affected by LCA methodological

shortcomings and differences in interpretation than typical petrochemical

processes. The authors reason that this is due to the multi-scale nature of

biomass supply chains, which differ from the standardized equipment and

commodity feedstock of fossil fuels. This is also demonstrated in Paper III,

in which the forest-based fuel is highly affected by inclusions or exclusions of

certain climate aspects, whereas the fossil fuel is hardly affected (see Figure

10 in Section 7.1.2).

Even though we might not be able to control the degree of uncertainty, we

can control the way we deal with uncertainty. When using LCA for decision-

making, ensuring credibility is crucial. To enhance credibility, there must be

transparency in both uncertainty management (i.e. description and

motivation of methods and uncertainty analysis approaches) and clear

uncertainty communication [27]. Data uncertainty has been in focus for a

long time (see Section 7.2), but it is important that all types of uncertainty

receive attention. It is not sufficient to present LCA case studies with bar

charts showing that a forest product is 5% better than its fossil counterpart

without an indication of the significance or robustness of this difference. And

it should not be up to the decision-maker to figure out whether or not the 5%

difference is significant.

Another important point is that the role of LCA is not carved in stone. LCA is

currently being employed to answer major questions, such as “is the use of

ethanol from sugarcane bringing the most environmental gain to the

49

Brazilian society when used for plastic or fuel?” [171], and “is the

environmentally optimal use of residual and waste woody biomass in Europe

heat, electricity or transportation?” [172]. But can the product-focused LCA

method prove that certain actions are environmentally preferable, or is the

ability of LCA limited to descriptive analyses? McManus et al. claim that

“LCA is balanced between its past and continuing future as a data-based,

rigorous retrospective tool for product and process optimization and its

parallel future as a policy or strategic planning tool” [27]. If this is the path

on which LCA is heading, defining the role of the method becomes extremely

important for future credibility and continuous employment. McKone et al.

[33] have made the valuable point that the solution is that we must recognize

that LCA is a process and not a product, that LCA provides learning and not

definite answers.

Winston Churchill once said: “No one pretends that democracy is perfect or

all wise. Indeed, it has been said that democracy is the worst form of

Government, except for all the other forms that have been tried from time

to time”. We should not pretend that LCA is perfect either. But just like

democracy we should neither dismiss it. LCA is the best method we have for

the environmental assessment of product value chains [30]. And we should

take advantage of that in our efforts to reduce climate change and other

environmental impacts. We should continue our endeavours to improve and

refine the method, but also be open for ways to combine LCA with other

methods and use elements of LCA in other frameworks. Combined with

Economic Input-Output analysis, insight into product systems can become

insight into economies. Combined with Multi-Criteria Decision analysis,

descriptions can become decisions. Combined with Transition Studies,

recommendations can become action. LCA is not a goal in itself. LCA is a

means, a small piece in a large puzzle, to support a sustainable way forward.

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51

8. Conclusions and Future work

As stated in Section 2, the aim of this thesis was 1) to provide guidance for

environmentally sound decision-making for forest product development and

production, and 2) to contribute to the methodological development of LCA

of forest products. To address the thesis aim, forest product LCA-related

aspects were explored: choice of system boundaries, climate impact

assessment practice, and choice of allocation method. Case studies were

chosen to assess the relevance of the aspects for different system types and

sizes: a chemical industry cluster, a biorefinery, and single product value

chains for a plastic box, a fuel, and a building.

8.1 Guidance for the forest-based bio-economy

Use a life cycle perspective in forest product and strategy

development.

The majority of the environmental impact of the Stenungsund petrochemical

industry cluster occurs outside the cluster boundaries. A transition to 25%

forest biomass feedstock could provide a 25% reduction in climate impact, of

which the largest part would occur in upstream and downstream processes.

A comparison of fossil and bioplastic products demonstrated that the climate

impact of the plastic materials differs by 20%. However, if material

properties in the use phase are taken into account, the climate impact of the

plastic products differs by more than six times.

Be aware of the uncertain climate impact of forest products.

A major driver for the bio-economy strategy is the expectation of climate

change mitigation. However, as this thesis has demonstrated, it is not self-

evident that all forest product applications can fulfil this expectation. The

common practice of assessing the climate impact of forest products is to

exclude potentially important climate aspects. These aspects could influence

results greatly (by about a factor of 10) in both a positive and negative

direction, and even affect the outcome of comparisons between forest and

non-forest products.

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8.2 Method development

The case studies in the thesis demonstrated that LCA can be used to provide

valuable decision support for a transition towards a forest-based bio-

economy. To improve the ability of LCA to deliver decision support, there are

several areas in which the LCA practice should advance and in which the

LCA method itself needs further development. These include:

The importance of extending the system boundaries of LCAs of

industrial symbiosis systems beyond on-site processes.

Industrial symbiosis systems have the potential to support the development

of alternative systems with a more desirable environmental profile, and a life

cycle perspective can reveal the full potential of such a transition.

The high impact that allocation choices have on LCA results in

studies of physically non-dominant biorefinery products and in

consequential studies.

In these cases, scenario analysis is especially valuable to show the possible

range of results.

The importance of assessing bio-based products based on function.

Some bio-based products differ in functional properties from the fossil

products they are meant to replace. The comparison of such products should

be based on the same functional properties.

The lack of knowledge of the climate impact of forest products.

LCA practitioners must be aware of, and communicate, the lack of

knowledge of the climate impact of forest products, which causes high

uncertainty in results. There is a need for method development that ensures

an inclusion of all climate aspects.

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8.3 Ways forward

During this PhD project, the question “what should we use the forest for?”

often came to mind. The bio-economy strategy implies that biomass is used

in a range of applications, but biomass does not exist in absolute abundance

[113], and is not the most suitable source for all energy and product

segments. For example, solar, wind, and hydropower could be more suitable

fuel sources for transport, as it can be argued that biomass should be

dedicated to products (e.g. construction, plastics, and chemicals), which

cannot be made of electricity. Cascading, the use of the same resource in

multiple successional applications, is another concept that should be more

investigated. Cascading has been identified as a promising measure for

improving the environmental performance of wood utilization systems [173,

174].

It is important to understand how different resources can be used most

efficiently in terms of economic, environmental, and social criteria. In order

to achieve optimal use of wood, studies are needed that include all relevant

system components. Future research should 1) discern which methods and

models that can assess the sustainable and efficient use of wood resources, 2)

discuss pros and cons of the different approaches, 3) suggest how the

approaches can benefit from being combined, and 4) put the suggestions

into action.

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55

9. Acknowledgements

This PhD project would not have been possible without financing from

Bio4Energy, a strategic research environment appointed by the Swedish

government.

Thanks to my supervisors for always believing in me. Thanks to my SP

supervisor Johanna Berlin for employing me in spite of my untraditional

background and for giving me so much freedom and support. Thanks to my

Umeå supervisors Mats Tysklind and Stina Jansson for the always

welcoming atmosphere.

Emma Ringström at AkzoNobel taught me a lot about LCA and the Gabi

software and was an invaluable companion in the huge quest to assess the

environmental impact of an industry cluster.

An SP colleague, Louise Quistgaard, made the nice cover illustration. My

colleagues at SP have been a priceless social support to me during these

years, and the Swedish fika-tradition is like therapy to a frustrated PhD soul.

The same goes for my numerous lunch partners at Chalmers.

I have had many valuable forest product LCA discussion partners throughout

recent years. These include, among others, Olivia Cintas, Christin Liptow,

Maria Lindqvist, Magdalena Svanström, Rickard Arvidsson, and Matty

Janssen.

A special recognition goes to Diego Peñaloza and Gustav Sandin Albertsson.

You have been my fellow forest product LCA musketeers, and I have

appreciated your company immensely.

Also thanks to my family in Norway, for always supporting my choices in life,

and to Gunnar, for sharing my daily life as a PhD student and for being my

safe haven.

56

57

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