How to quantify uncertainty and variability in life cycle assessment: the case of greenhouse gas emissions of gas power generation in the US

M Hauck, Z J N Steinmann, I J Laurenzi, R Karuppiah, M A J Huijbregts
2014 Environmental Research Letters  
This study quantified the contributions of uncertainty and variability to the range of life cycle 12 greenhouse gas (LCGHG) emissions associated with conventional gas-fired electricity generation in the U.S. 13 Whereas uncertainty is defined as lack of knowledge and can potentially be reduced by additional research, vari-14 ability is an inherent characteristic of supply chains and cannot be reduced without physically modifying the 15 system. The life-cycle included four stages: production,
more » ... es: production, processing, transmission and power generation, and 16 utilized a functional unit of 1 kWh of electricity generated at plant. Technological variability requires analyses of 17 life cycles of individual power plants, e.g. combined cycle plants or boilers. Parameter uncertainty was modeled 18 via Monte Carlo simulation. Our approach reveals that technological differences are the predominant cause for 19 the range of LCGHG emissions associated with gas power, primarily due to variability in plant efficiencies. 20 Uncertainties in model parameters played a minor role for 100-year time horizon. Variability in LCGHG emis-21 sions was a factor of 1.4 for combined cycle plants, and a factor of 1.3 for simple cycle plants (95% CI, 100-year 22 horizon). The results can be used to assist decision-makers in assessing factors that contribute to LCGHG emis-23 sions despite uncertainties in parameters employed to estimate those emissions. 24 25
doi:10.1088/1748-9326/9/7/074005 fatcat:pu7ofwampbeahgbsoymcnikkgq