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This lecture covers the importance of data quality in Life Cycle Assessment (LCA), focusing on inventory data format, control, and measurement procedures. It explains the criteria for defining data quality, including geographic, temporal, and technological aspects. The lecture also delves into uncertainty factors, such as sample size, reliability, and completeness, and their application to the quality matrix. Additionally, it discusses the calculation of a quality index and the Data Quality Rating (DQR) system. The presentation emphasizes the significance of transparency, reliability, and expert review in life cycle inventories, as well as the impact transfer and allocation rules in LCA.
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