Life cycle assessment (LCA) has been increasingly applied to livestock production systems to estimate their environmental footprints, but the degree of uncertainties associated with these values is known to be generally high. This thesis explores novel methods of LCA modelling to reduce uncertainty associated with environmental footprints of meat production systems, with the view to contribute to objective and transparent debates about the role of livestock in global food security. Three innovative approaches are proposed in this thesis. First, as information on individual animals is often unavailable, livestock data are often aggregated at the time of inventory analysis. To investigate the level of bias caused by this aggregation, Chapter 3 uses primary data collected at the North Wyke Farm Platform in Southwest England and calculates emission intensities for individual animals and their intra-farm distributions, providing a step towards deriving optimal animal selection strategies based on livestock LCA. Second, the severity of greenhouse gas emissions from agricultural production is known to vary spatially and temporally, yet available LCA frameworks often fail to sufficiently consider these differences due to data constraints. To evaluate the degree of avoidable uncertainties attributable to this practice, Chapter 4 conducts an original field experiment to derive site-specific nitrous oxide emission factors, which are subsequently used in Chapter 5 to compare LCA results derived under these localised values and generic alternatives intended for the widest possible users. Finally, while LCA results are typically communicated in the form of environmental burdens per output of mass, it is gradually becoming recognised that product quality also needs to be accounted for to truly understand the value of each farming system to society. Using data from seven livestock production systems encompassing cattle, sheep, pigs, and poultry, Chapter 6 develops new methods to incorporate nutritional values of meat products into livestock LCA.
|Date of Award||7 May 2019|
- The University of Bristol
|Supervisor||Michael Lee (Supervisor) & Taro Takahashi (Supervisor)|