(769c) A Combined Hazard and Life Cycle Assessment of Six Amine Solvents for Post-Combustion CO2 Capture
A multi-criteria assessment is carried out for 6 different solvents used for post-combustion CO2 capture. Monoethanolamine (MEA) is considered the standard solvent for CO2 capture. The performance of Methyldiethanolamine (MDEA), 2-Amino-2-methyl-1-propanol (AMP), Piperazine (PZ), Diethanolamine (DEA) and Diglycolamine (DGA) as solvents is compared to that of MEA from an Environmental, Health and Safety (EHS) hazard assessment and from a Life Cycle Assessment (LCA) perspective. Cumulative Energy Demand (CED), Global Warming Potential (GWP), Eco-Indicator 99 (EI99) and RECIPE are calculated for the capture process using each solvent. The EHS assessment covers the use of EHS method, the Inherent Safety Index (ISI) method, the Hazard Identification and Ranking (HIRA) method and the Integrated Inherent Safety Index (I2SI) method.
Solvent loss through degradation is accounted for in the assessment, as solvent replacement rates are included in the life cycle impact assessment and degradation products are included in the EHS hazard analysis. A framework for solvent degradation based on molecular structure is established based on experimental degradation rates available in literature. This framework then enables a more thorough assessment of more solvents even where experimental degradation data is scarce.
For the hazard analysis, a framework is established to overcome the issue of data gaps. In many cases and especially for the less used solvents, crucial properties required for the EHS assessment are missing such as (Threshold Limit Values) TLV and Immediately dangerous to Life and Health (IDLH) values. This makes it very difficult to use methods that only rely on such data without flexibility such as the ISI method. Hence the framework helps to give estimates for these values, translated from other properties, whenever they are missing.
The presented frameworks make it possible to extend the assessment to other solvents where little experimental data is available. DGA represents a case where TLV and degradation data are unavailable. Assessments are carried out with the application of both frameworks for estimating missing data.