The effort on mitigating climate change has conjured up a vision of a bioeconomy. Therefore, industrial production has to turn away from fossil-based resources to bio-based ones. In Germany, the BioEconomy Cluster aims to establish a bioeconomy region that is based on non-food biomass, especially wood. The complexity of this transition raises doubts as to whether it necessarily leads to a better, more sustainable living in the regions. Currently, life cycle assessment tools are viewed as adequate to evaluate sustainability aspects associated to products. A method to analyse potential social effects of products is at an early stage. Therefore, this PhD thesis develops a social life cycle assessment approach to assess wood-based production systems in a bioeconomy region in Germany.
A framework was formulated with major concepts and definitions applied. The goal and scope comprise to identify of social hotspots and opportunities of the foreground activities involved in a production system in a German bioeconomy region. The system boundary was defined as an area smaller than a country and major stakeholder categories were selected. In addition the organisations’ conduct was determined as the main unit of analysis.
Based on the frameworks’ major elements a social indicator set with seven social indices (e.g. health & safety; participation) and 32 social indicators (e.g. accidents) was selected to make the inventories. Therefore, sustainability standards and sLCA case studies were screened and stakeholder interviews were conducted to set up a final set.
Within this PhD thesis context-specific performance reference points (PRPs) were determined for the sLCIA phase. Compared with the organisations’ indicator values, they indicate a “relatively poor” or “relatively better” social performance (i.e. a social opportunity or hotspot). The PRPs considered the classification of economic sector of the assessed organisation and in some cases the size of the organisation as factors influencing the potential social effects.
The framework provides major elements (i.e. a context-specific indicator set and characterisation approach) to assess relevant social effects associated with the organisations production activities involved in a products production. Therefore, the sLCA approach supports producer’s decision making which may mitigate negative social effects and accelerate positive ones.:Summary i
Acknowledgements ii
List of Publications vii
List of Figures ix
List of Tables xii
List of Abbreviations xiii
1 Introduction 1
1.1 Bioeconomy and sustainability 1
1.2 The BioEconomy Cluster 2
2 Social Life Cycle Assessment, S-LCA 3
2.1 The history of sLCA 3
2.2 The UNEP-SETAC guidelines 4
2.3 Review on sLCA 5
2.3.1 Goal and scope definition 8
2.3.2 Social life cycle inventory 9
2.3.3 Characterisation 10
3 Research question and aim of the thesis 12
4 Social life cycle assessment: in pursuit of a framework for assessing wood-based products from bioeconomy regions in Germany 14
4.1 Abstract 14
4.2 Introduction 15
4.2.1 Germany’s wood-based bioeconomy 15
4.2.2 Social life cycle assessment 16
4.2.3 Goal and structure of the paper 17
4.3 Defining the goal and scope 17
4.3.1 Defining the goal—the purpose of the developed sLCA approach 17
4.3.2 Regional system boundaries 18
4.3.3 The production system 19
4.3.4 Stakeholder categories 19
4.3.5 Defining and using a functional unit 20
4.3.6 Activity variables—relating social effects to the product 21
4.3.7 Social indices and indicators 22
4.3.8 Developing context-specific social indices and indicators 23
4.3.9 Presenting the social effects to regional producers 24
4.4 Social life cycle inventory (sLCI) 25
4.4.1 SLCIs in global hotspot assessment studies 25
4.4.2 SLCIs in regional hotspot assessment studies 26
4.5 Social life cycle impact assessment (sLCIA) 27
4.5.1 Characterisation method: international PRPs 28
4.5.2 Characterisation method: national PRPs 28
4.5.3 Characterisation method: sector PRPs 29
4.5.4 Characterisation method: regional PRPs 29
4.6 An sLCA framework for regional bioeconomy chains 31
4.7 Summary and outlook 33
5 Social life cycle assessment indices and indicators to monitor the social implications of wood-based products 35
5.1 Abstract 35
5.2 Introduction 36
5.3 Materials and methods 38
5.3.1 Screening criteria 38
5.3.2 Overview of research steps 40
5.3.3 Screening of global sustainability standards 41
5.3.5 Screening of national sustainability and forest certification standards 43
5.3.6 Screening of sLCA case studies 43
5.3.8 Stakeholder interviews 44
5.3.9 Selection based on feasibility of implementation 46
5.4 Results and discussion 48
5.4.1 Index: health and safety 52
5.4.2 Index: adequate remuneration 52
5.4.3 Index: adequate working time 53
5.4.4 Index: employment 53
5.4.5 Index: knowledge capital 54
5.4.6 Index: equal opportunities 55
5.4.7 Index: participation 56
5.5 Outlook 56
5.6 Conclusion 57
6 How not to compare apples and oranges: Generate context-specific performance reference points for a social life cycle assessment model 59
6.1 Abstract 59
6.2 Introduction 60
6.2.1 Background 60
6.2.2 The RESPONSA framework 61
6.2.3 Goal of this work 64
6.3 Influence factors recognised in the context-specific characterisation approach for the German wood-based bioeconomy 65
6.3.1 Classification of the influential conditions 65
6.3.2 The geographical location 68
6.3.3 The economic sector 68
6.3.4 The size of the organisation 69
6.4 The scoring approach and data sources 69
6.4.1 The scoring approach 69
6.4.2 Data sources to determine PRPs 70
6.5 Characterisation approach for quantitative indicators 70
6.5.1 Characterisation of quantitative indicators (full data) 70
6.5.2 Characterisation of quantitative indicators (partial data) 71
6.6 Characterisation approach for qualitative indicators 73
6.6.1 Characterisation of qualitative indicators with binary answers on a sectoral level 73
6.6.2 Characterisation of qualitative indicators with ranked answers on a sectoral level 74
6.6.3 Characterisation of qualitative indicators on a sectoral and organisational size level 76
6.7 Exemplary case study 77
6.7.1 Classifying organisations in the product system 77
6.7.2 Determining the sLCIs 78
6.7.3 sLCIA step 78
6.7.4 Relating social effects to the product 81
6.7.5 Discussion of the results 83
6.8 Discussion and outlook 84
6.9 Conclusion 85
7 Discussion of the main results 87
7.1 Organisations as unit of analysis 87
7.2 A country as major system boundary 88
7.3 A context-specific indicator set 89
7.4 Impact assessment: Economic sector and organisational size PRPs 90
7.5 The interpretation of the results 92
7.6 Limitations of the approach 94
7.7 Use for the Cluster 95
7.8 Outlook 96
8 Conclusion 97
9 Use of RESPONSA – A REgional SPecific cONtext-ualised Social life cycle Assessment tool 100
9.1 The RESPONSA user interface 100
9.1.1 Inputs from the organisations 101
9.1.2 The calculation made by RESPONSA 102
9.1.3 Output for the organisation 103
References cv
Appendix A cxiii
Appendix B cxx
Appendix C cxxiv
CURRICULUM VITAE cxxviii
Author contribution cxxx
Eigenständigkeitserklärung cxxxiii
Bibliographische Beschreibung cxxxiv
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:34798 |
| Date | 06 August 2019 |
| Creators | Siebert, Anke |
| Contributors | Universität Leipzig |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/acceptedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 10.1007/s11367-016-1066-0, https://doi.org/10.1016/j.jclepro.2017.02.146, https://doi.org/10.1016/j.jclepro.2018.06.298 |
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