Life Cycle Inventory Analysis: Methods and Data

Life Cycle Inventory (LCI) Analysis is the second phase of Life Cycle Assessment (LCA), covering the development of unit process datasets, multi-functionality, data quality, and databases. It discusses the history, principles, and algorithms of LCI analysis, as well as inventory indicators and the link between LCI and LCIA.

Format: Paperback / softback
Length: 209 pages
Publication date: 01 September 2022
Publisher: Springer Nature Switzerland AG

Life Cycle Inventory (LCI) Analysis is a crucial step in the comprehensive Life Cycle Assessment (LCA) framework, which has been gaining attention since its early attempts in the 1970s. Since then, life cycle inventory analysis has remained a central component of LCA.

Chapter 1, titled "Introduction to Life Cycle Inventory Analysis," delves into the history of inventory analysis, spanning from its early days in the 1970s to the establishment of standards such as SETAC and ISO. It explores the evolution of inventory analysis methodologies and the role played by organizations like SETAC and ISO in shaping the field.

Chapter 2, "Principles of Life Cycle Inventory Modeling," introduces the fundamental principles of setting up an LCI model and conducting LCI analysis. It explains the core LCI model and its extensions, which enable more accurate representation of real-world scenarios. The chapter emphasizes the importance of developing high-quality and transparent unit process datasets for LCA studies.

Chapter 3, "Development of Unit Process Datasets," highlights the challenges involved in creating comprehensive and accurate unit process datasets. It emphasizes the need for careful consideration of data sources, data collection methods, and data validation procedures. The chapter underscores the significance of developing unit process datasets of the highest quality to ensure reliable LCA results.

Chapter 4, "Multi-functionality in Life Cycle Inventory Analysis: Approaches and Solutions," explores the identification of multi-functional processes within a product or system. It discusses various approaches and methodologies for capturing and analyzing multi-functional aspects, such as material flow and energy flows. The chapter provides practical solutions for addressing multi-functionality in LCI analysis and highlights the importance of considering multiple functionalities in LCA studies.

Chapter 5, "Data Quality in Life Cycle Inventories," examines the quality of data gathered and used in LCI analysis. It discusses state-of-the-art indicators and concepts to assess data quality, including the fitness for purpose concept. The chapter introduces key indicators and methodologies for evaluating the reliability and validity of LCI data.

Chapter 6, "Life Cycle Inventory Data and Databases," provides a comprehensive overview of life cycle inventory data and databases. It distinguishes between foreground and background data, discusses recommendations for starting a database, explores data exchange and quality assurance concepts, and presents the scientific basis of LCI databases. The chapter highlights the importance of maintaining accurate and up-to-date LCI databases to support LCA studies effectively.

Chapter 7, "Algorithms of Life Cycle Inventory Analysis," delves into the mathematical models underpinning LCI analysis. It discusses the development of algorithms and computational methods for conducting LCI analysis, including the use of software tools and models. The chapter explores the scientific basis of LCI algorithms and their role in generating reliable and accurate LCA results.

In conclusion, Life Cycle Inventory (LCI) Analysis plays a vital role in the comprehensive LCA framework, providing a detailed understanding of the environmental impacts associated with a product or system throughout its entire life cycle. By employing the principles and methodologies outlined in this book, researchers, practitioners, and policymakers can effectively evaluate the environmental impacts of products and systems and make informed decisions to promote sustainability and reduce environmental impact.

Weight: 400g
Dimension: 154 x 235 x 14 (mm)
ISBN-13: 9783030622725
Edition number: 1st ed. 2021