Life Cycle Assessment of an Engine with Input-Output Based Hybrid Analysis Method

Abstract

Life cycle inventory (LCI) compilations of large and medium-sized equipment manufacturing is labor intensive and time consuming due to complexities involved in data collection processes. Process based Life Cycle Assessment (P-LCA) methods can provide accurate inventory results with up-to-date data; however, it also suffers from several problems including system boundary identification, high cost, data confidentiality, and long timespans. Economic Input–Output (EIO) based inventory is fast and operable method for applying data on a national level which helps to negate truncation errors. This paper conducts an IO based hybrid inventory analysis for a diesel engine manufactured in China with Chinese Economic Input–Output Table and Life Cycle Database. The energy requirements and quantifications regarding air pollutants of the engine's entire life cycle are identified. Moreover, the differences between the LCI results achieved by IO based hybrid approach and process based analysis methods are also presented. Sensitivity analysis of various fuel efficiencies is conducted to demonstrate the effect of fuel efficiency on overall impacts of the engine through its life cycle. Finally, Monte Carlo Simulation is adopted to analyze the uncertainties of various data sources on the LCA results.