The Availability of Suitable Datasets for the LCA Analysis of Chemical Substances

Abstract

The practicality of adopting Life Cycle Assessment to support decision-making can be limited by the resource-intensive nature of data collection and Life Cycle Inventory modelling.The number of chemical products increases continuously and long-term analyses show that overall growth of chemicals demand and production as well as faster growth in emerging regions is a trend that is expected to continue in the future. Regrettably, chemical inventories are typically among the most challenging to model because of the lack of available data and the large number of material and energy flows. This explains why it is so important for the Life Cycle Assessment community to have effective methods to implement life cycle inventories of chemicals available.This chapter deals with the issues of Life Cycle Inventory analysis for chemical processes and the related lack of data concerning inventories of basic and fine chemicals substances. The overall aim of the chapter is to illustrate the different possibilities/approaches that the scientific Life Cycle Assessment community has developed in order to overcome such a lack of data concerning the inventories of a specific (basic and/or fine) chemical substance both for input and output flows. Their main advantages and drawbacks are identified and discussed briefly.

A review of inventory modeling methods for missing data in life cycle assessment

“…The theoretical method requires chemical and physical properties data of components, such as molecular weight, standard enthalpy of formation, boiling point, and so on. (Cuéllar-Franca et al, 2016;Righi et al, 2020). The sources of relevant information include chemical process encyclopedia, design equations, physical and thermodynamic data for chemical handbooks and literature, such as Perry's Chemical Engineers'…”

Recycling process development with integrated life cycle assessment – a case study on oxygen transport membrane material

“…Data availability and process understanding are significant challenges for early-stage LCA studies in chemistry. 62 For instance, many studies lack sufficient consideration of the process chemicals and emissions. In the study of Agarski et al , 47 it remains unclear why NO x process emissions are not considered for all the product systems with the presence of nitrate ions.…”

Life Cycle Assessment of the Polyvinylidene Fluoride Polymer with Applications in Various Emerging Technologies

“…There are many developments on different knowledge-based and data-driven simulation approaches to estimate life cycle inventories, such as missing inventory estimation tool (MIET), artificial neural networks (ANN), , bill of materials (BOM), and unit process data. , However, there are limitations with these methods. More specifically, MIET suffers from data aggregation, relying on the national input–output tables with respect to input requirements; in this way, the inventory data suffers from scarce accuracy . ANN and BOM still rely on collecting large amounts of information, such as chemical reaction equations, process characteristics of chemicals, and design details of products.…”

“…More specifically, MIET suffers from data aggregation, relying on the national input−output tables with respect to input requirements; in this way, the inventory data suffers from scarce accuracy. 44 ANN and BOM still rely on collecting large amounts of information, such as chemical reaction equations, process characteristics of chemicals, and design details of products. These methods are applicable for specific products and rely on extensive domain knowledge.…”