Global Integration Model for Life Cycle Assessment in Small and Medium Sized Enterprises

Research output: Book/ReportPh.D. thesisResearch

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Abstract

Small and medium sized enterprises (SMEs) are the backbone of economic activity across sectors and countries, yet their use of life cycle assessment (LCA) is limited. Given their pivotal role in economies, SMEs have been identified key stakeholders who need to be engaged if the United Nations’ Sustainable Development Goals are to be achieved, but SMEs face particular challenges and any SME engagement needs to make allowance for those challenges.
This PhD investigates how LCA can be adapted for use by SMEs in agribusiness value chains in ways that create value for the core business by improving their environmental and economic sustainability. Four case studies of three agribusiness value chains were completed as part of this PhD, to analyse the different ways in which LCA can be used by SMEs and the value chains in which they are located. Chapter 1 includes an overview of SMEs (their existence and prevalence), the innovation focus of SMEs in agricultural value chains, and existing models for engaging with SMEs. The chapter then considers how circular economy thinking can be incorporated into agribusiness supply chains, in particular the primary production and processing stages, and how indicators can be used to measure performance on different levels in a value chain. The existence of management systems as a means of capturing metrics and improving performance is also addressed.
Chapter 2 covers the sisal value chain in Tanzania, which produces sisal fibre, most of which is exported. Sisal leaves are comprised of only 3-5% fibre, so the processing of sisal leaves generates large volumes of solid waste. Nutrient depletion during sisal cultivation and subsequent loss during the anaerobic degradation of the sisal processing waste was identified in the initial stages of the case study as a potential economic threat to the industry, so an assessment of nutrient depletion during the cultivation stage was completed. A circular economy approach was then used to identify potential nutrient sources within the Tanzanian economy that could be used for codigestion with the sisal wastes, to produce a stabilised solid that could be recycled for its nutrient value and biogas which could be used in electricity generation. LCA was used to compare the different nutrient sources, identify the best co-substrates and highlight where additional data were required. The chapter concludes by suggesting how the LCA results could be used to maintain and improve the financial and environmental performance of the sisal value chain.
The pork value chain in Denmark, Australia and China is covered in Chapter 3, using the LCA results from an existing report to develop two metrics that reflect the performance of the upstream (on-farm) portion of the supply chain. One metric was the human edible protein required (HEPR), which is a ratio of the amount of human edible protein consumed to produce one kilogram of human edible protein as pork meat and is an indicator of whether the supply chain is a net producer or consumer of human edible protein. This enables a comparison between supply chains producing the same product, in this instance pork meat, and supply chains producing different products, such as other sources of human edible protein, either animal or plant-based. The other metric was the amount of arable land required to produce one kilogram of human edible protein. The analysis showed that the HEPR was strongly dependant on the feed conversion ratio, which is a measure of the efficiency of a pig’s ability to convert feed grain to weight gain. The arable land use was also dependant on the HEPR but was more strongly dependant on the grain yield, which is largely influenced by factors such as climate and soil. Danish pork production was found to be the most efficient of the three systems evaluated, as measured by both the HEPR and arable land metric. Australia was the second most efficient as measured by HEPR but the worst in the arable land metric due to low grain yields. China was the least efficient as measured by HEPR, and the arable land metric was between the Danish and Australian values. Much of the discussions to date relating to pork have centred on its superior performance relative to ruminant supply chains in terms of greenhouse gas emissions, so the inclusion of these two metrics broadens the debate about food production in the context of the need to feed 9-10 billion people, and the emerging competition for land between food, fuel and fibre.
Chapter 4 covers two case studies in the red meat supply chain. One case study investigates how well existing LCAs represent SME processors, whether climate change is a suitable proxy for other impact categories, and what circular economy opportunities exist for regional SME meat processors to reduce their environmental impacts using LCA as the analytical tool to prevent burden shifting. This identified that current LCA inventories do not appear to represent SME processors accurately, that climate change is not a suitable proxy for other impact categories and that there is significant potential for circular economy opportunities, particularly bioenergy production and use within the supply chain. The other case study looks at the major non-sheep processes contributing to the environmental impacts of sheep production in regenerative agriculture, using a delta LCA that models only the differences between conventional and regenerative agriculture. This identified that there appears to be significant potential with regenerative agriculture systems to offset a significant proportion of, if not all, supply chain climate change emissions. The ability of soil to sequester carbon and the impact of improved animal welfare on productivity in regenerative agriculture systems were identified as areas requiring further investigation.
In Chapter 5, a model is proposed for integrating risk management, circular economy approaches and LCA to assist SMEs in agribusiness value chains. The model varies according to the current status of the value chain in terms of indicators, management systems, innovation focus and existing linkage models.
Original languageEnglish
Number of pages275
Publication statusPublished - 2019

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