Sensitivity analysis of greenhouse gas emissions from a pork production chain

Groen, E.A.; Zanten, H.H.E. van; Heijungs, Reinout; Bokkers, E.A.M.; Boer, I.J.M. de

doi:10.1016/j.jclepro.2016.04.081

Cited by 35 publications

(26 citation statements)

References 21 publications

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“…Thus, interaction effects between parameters are ignored (Saltelli and Annoni, 2010). Groen et al (2016b) mention two weaknesses associated with this method, i.e., the number of inputs parameters assessed is usually a subset of all input parameters and the arbitrary choice of the predefined change may not reflect the actual uncertainty range.…”

Section: One-at-a-time Approachmentioning

confidence: 99%

“…Steinman et al ( 2014) (ID 4) used sequential perturbation analysis to assess the sensitivity of the results with respect to the uncertain parameters (since only those can be reduced by additional research), using the 2.5 th and 97. Multiplier method Groen et al (2016b) and Wolf et al (2017) (ID 8 and 9) used the multiplier method (lowest green graph in fig. 5) as a local sensitivity analysis.…”

Section: One-at-a-time Approachmentioning

confidence: 99%

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How to decide and visualize whether uncertainty or variability is dominating in life cycle assessment results: A systematic review

Michiels

2020

Environmental Modelling & Software

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Section: One-at-a-time Approachmentioning

confidence: 99%

Section: One-at-a-time Approachmentioning

confidence: 99%

How to decide and visualize whether uncertainty or variability is dominating in life cycle assessment results: A systematic review

Michiels

2020

Environmental Modelling & Software

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“…This analysis is carried out to differentiate between the influence and the importance of an input data on the output [13]. It also helps in deploying mitigation strategies to overcome this issue [23,24].…”

Section: Introductionmentioning

confidence: 99%

Scientific Challenges in Performing Life-Cycle Assessment in the Food Supply Chain

Đjekić

Pojić

Tonda³

et al. 2019

Foods

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This paper gives an overview of scientific challenges that occur when performing life-cycle assessment (LCA) in the food supply chain. In order to evaluate these risks, the Failure Mode and Effect Analysis tool has been used. Challenges related to setting the goal and scope of LCA revealed four hot spots: system boundaries of LCA; used functional units; type and quality of data categories, and main assumptions and limitations of the study. Within the inventory analysis, challenging issues are associated with allocation of material and energy flows and waste streams released to the environment. Impact assessment brings uncertainties in choosing appropriate environmental impacts. Finally, in order to interpret results, a scientifically sound sensitivity analysis should be performed to check how stable calculations and results are. Identified challenges pave the way for improving LCA of food supply chains in order to enable comparison of results.

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“…Thus, the improvement of their estimates would reduce the uncertainties and improve the reliability of N use indicators significantly. Several studies on LCA of livestock systems had also identified the importance of EFs in the quantification of greenhouse gas emissions (Groen et al, 2016;Wolf et al, 2017;Zhu et al, 2016). Attempts should thus be made to estimate locally-specific EFs, based measurements or mathematical models that take into consideration environmental conditions, such as climate, temperature, and management.…”

Section: Limitation Of This Methodsmentioning

confidence: 99%

“…Several studies have evidenced the influence of the uncertainties in the data on the variance of the environmental indicators (Groen et al, 2014a;Heijungs, 1996;Oenema et al, 2013). Such uncertainties can limit the direct utilisation of these indicators at country-level, to shape the policy and decision-making (Elduque et al, 2015;Gerber et al, 2013;Groen et al, 2016;Mu et al, 2017).…”

Section: Data Qualitymentioning

confidence: 99%

Nutrient challenges in global livestock supply chains : an assessment of nitrogen use and flows

Uwizeye¹

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The rapid growth of the livestock sector has altered the way the sector influences global nutrient flows and emissions, with repercussions on environmental and public health issues. Designing interventions for better environmental sustainability will require a framework and indicators adapted to the increasingly long, and complex livestock supply chains. To develop such a framework, we reviewed existing studies and found that four methods were used previously to analyse nutrient use in the livestock sector, namely a nutrient balance, nutrient use efficiency (NUE), material flow analysis and life cycle assessment. Among these methods, NUE appeared as a suitable approach to benchmark nutrient management that can be integrated in life cycle approach to compute the supply chain level NUE, which is proposed as a valuable indicator of nutrient management sustainability. To this end, we developed a comprehensive framework of indicators to assess the sustainability of nutrient use. The framework encompassed three indicators, including the life-cycle nutrient use efficiency (life-cycle-NUE), life-cycle net nutrient balance (life-cycle-NNB) and nutrient hotspot index (NHI). It was tested and the indicators proposed were found to be suitable to describe nitrogen (N) and phosphorus dynamics and were all needed. This framework requires detailed data, which are highly variable at global level, resulting in large uncertainties of the results. Focusing on N, we proposed a method, which relies on a global sensitivity, to identify the important inputs parameters that contribute significantly to the variance of the results, using the Global Environmental Assessment Model (GLEAM) dataset. The results showed that uncertainties of a few important input parameters, such as manure deposited and applied could explain most of the variance of N use indicators. Fixing non-important parameters and substituting important parameters in GLEAM for new field survey data, improved the results of N use indicators. Subsequently, we applied the framework to assess N use, flows and emissions, in the global pork supply chains and to evaluate the effects of feeding swill to pigs as a strategy to integrate better livestock in a circular bio-economy. The results showed that N emissions into the environment amount to around 14.7 Tg N y −1 , of which 68% is lost to watercourses. These results showed that the efficiency of N use and the magnitude of N losses per unit of area depend chiefly on the region, origin of feed, and manure management. The substitution of swill for grains and soybeans resulted in the improvement of N use indicators and abate N emissions. Implementing swill feeding would require innovative policies to guide the collection, treatment, and usage of swill, and ensure safety and traceability. Applying the framework to global livestock supply chains showed that they are responsible for around one-third of human-induced N emissions (65 Tg N y −1) of which 63% take place in 2 regions (i.e. South Asia and East and Southeast Asia), and 61% at t...

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Sensitivity analysis of greenhouse gas emissions from a pork production chain

Cited by 35 publications

References 21 publications

How to decide and visualize whether uncertainty or variability is dominating in life cycle assessment results: A systematic review

How to decide and visualize whether uncertainty or variability is dominating in life cycle assessment results: A systematic review

Scientific Challenges in Performing Life-Cycle Assessment in the Food Supply Chain

Nutrient challenges in global livestock supply chains : an assessment of nitrogen use and flows

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