Process-oriented life cycle assessment modelling of (bio)energy technologies

Concetta Lodato*

*Corresponding author for this work

Research output: Book/ReportPh.D. thesis

31 Downloads (Pure)

Abstract

In the endeavour of reducing greenhouse gas emissions (GHGs) mainly due to human activities, reaching carbon neutrality by 2050 and maintaining global
mean temperatures below political targets, new and efficient solutions are needed. Bio-based energy, or bioenergy, plays an important role in a world
where the majority of GHG emissions are from energy. Bioenergy technologies convert biomass to energy. Using biomass as residues from human activities
or organic fraction of waste to produce bioenergy has several advantages: i) providing solutions to waste management, ii) promoting material recirculation
toward bio-based energy, iii) supplying fossil energy demand, and avoiding for example land use changes of using crops for energy. Bioenergy technologies
will contribute to a non-fossil and more sustainable society by transforming bioresources into energy. There are a wide range of challenges associated with
this transition such as availability of bioresources, spatial distribution of bioresources, and various conversion technologies. The selection of the environmentally most appropriate technologies to valorise the specific bioresources is also a challenge. Bioresource properties, conversion yields, outputs and rejects, as well as process performance for the bioresources in question need to be systematically evaluated and addressed by assessing the environmental impacts. Life cycle assessment (LCA) is a standardised method for assessing the environmental performance of technologies and systems. There is a need to expand and improve the modelling of bioenergy technologies, beyond black-box process models in conventional LCA modelling tools. Black-box models typically ignore the links between feedstock characteristics and process outputs. For example, adapting the inventory of a technology to reproduce another one. As such, these models do not reflect changes of operational conditions or conversion efficiencies in a process pathway. Thereby, the reproducibility of a technology and adaptability of the model to specific case studies are limited. The consequence is lack of transparency and limited flexibility from a modelling perspective. The main goal of this PhD project was to provide a process-oriented LCA modelling framework and apply this to a range of selected bioenergy technologies (e.g. anaerobic digestion, gasification, and upgrading units) and systems of technologies. The framework allowed quantitative and parametrized physical chemical input-output relationships. The generalised principles for processoriented LCA modelling were developed and implemented into the modelling framework, EASETECH+, as an extension to the existing LCA model, EASETECH. A range of illustrative examples was used to explain and highlight key features and LCA modelling approaches associated with the framework. The feasibility of the process-oriented modelling approach was demonstrated upon implementation of technology models within the LCA model EASETECH, including use of all novel operators and functions for model definition in EASETECH+. The new process-oriented framework facilitates LCA modelling of a wide range of conversion processes relevant for bioenergy technologies, including material recirculation, multiple outputs, conditional sequence flows, linear and non-linear responses in conversion pathways. Based on the PhD, a range of novel process-oriented technology models were implemented into EASETECH as ready-to-use technology templates for newcase-studies, including:
i) biorefinery, ii) anaerobic digestion, iii) thermal gasification; iv) bio-based methane upgrading.
The consequences of subdividing a technology into unit-processes was givenby a second generation biorefinery, managing bioresources with high cellulose, hemicellulose, and lignin content. Pretreatment, hydrolysis, fermentation and distillation, and recovery were the four unit processes identified. Input -output relationships with parameters (e.g. conversion efficiency) were included in each unit-process. Changes of parameters within unit-processes had changes on the mass, substance, energy balance, thus on the intermediate outputs (e.g. simple sugars), final outputs (e.g. ethanol), and environmental performance. For example, increasing the conversion efficiency of cellulose increased the production of sugars and ethanol causing more global warming savings. A systematic approach accommodating the process-oriented modelling principles was developed and applied on a regional case for bio-based methane supply in the French region of Occitania. This allowed finding environmentallyefficient import/export strategies to supply the gas demand of a region considering:
i) availability and properties of bioresources on the region, ii) biological and thermochemical degradation of bioresources, through anaerobic digestion
and gasification (both with upgrading), iii) environmental performance of conversion pathways and impacts (induced and avoided) by the current management of the involved bioresources. This can support practical actions toward local bioeconomy and climate goals.
Original languageEnglish
Place of PublicationKgs. Lyngby
PublisherTechnical University of Denmark
Number of pages49
Publication statusPublished - 2020

Fingerprint Dive into the research topics of 'Process-oriented life cycle assessment modelling of (bio)energy technologies'. Together they form a unique fingerprint.

Cite this