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The greenhouse gas mitigation potential of green biorefineries in - - PowerPoint PPT Presentation

Oct 31, 2023 108 likes •317 views

University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development The greenhouse gas mitigation potential of green biorefineries in Austria Stefan Hltinger, Mathias Kirchner, Johannes Schmidt &

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

The greenhouse gas mitigation potential

  • f green biorefineries in Austria

Stefan Höltinger, Mathias Kirchner, Johannes Schmidt & Erwin Schmid University of Natural Resources and Life Sciences, Vienna

24 August 2016, (LTU) Luleå, Sweden

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Outline

  • Introduction
  • Biorefinery
  • Motivation for biorefinery research
  • Drivers for green biorefinery development in Austria
  • Data and methodology
  • Integrated modelling approach
  • Spatially explicit data
  • LCA approach
  • Results and outlook
  • Profitability of different green biorefinery concepts
  • GHG mitigation potential

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Definition and classification

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IEA Task 42 Classification of Biorefineries 1

  • Raw materials (agricultural-, forest- and aquatic biomass, biogenic residuals and

waste materials)

  • Intermediates (Platform) (starch, proteins, fibres, press juice, biogas, syngas)
  • Processes (mechanical, thermochemical, chemical and biotechnological)
  • Products (food, feed, chemicals, materials, fuels, electricity, heat)

„Biorefining is the sustainable processing of biomass into a spectrum of marketable bio-based products and bioenergy.”

IEA - Task 42 Biorefineries

1 Cherubini et al. (2009). Toward a common classification approach for biorefinery systems. Biofpr.

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Motivation for GBR research

  • Biorefineries are promoted for
  • Mitigating climate change 1
  • Replacing fossil resources by renewable raw materials or waste 2
  • Increasing economic efficiency and sustainability of energy technologies 3
  • Drivers for the green biorefinery concept in Austria
  • Oversupply of grassland biomass due to changes

in agricultural policies and structures

  • Alternative utilization for grassland biomass to preserve cultural

landscape

  • Employment opportunities for rural areas

1 EC (2008). 20 20 by 2020 - Europe's climate change opportunity 2 EC (2011). A resource-efficient Europe - Flagship initiative under the Europe 2020 Strategy” 3 EC (2009). “Investing in the Development of Low Carbon Technologies (SET-Plan)”

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Objectives

  • Spatially explicit, techno-economic
  • ptimization model (BioResume) to assess
  • economic feasibility of various green

biorefinery (GBR) concepts

  • determine key parameters that affect the

profitability

  • GHG mitigation potential
  • Impact of different policy support schemes

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Green Biorefinery (GBR) concepts

  • Assessment of GBR concepts and biogas (CHP)

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Feedstocks and products

GBR - Concept Feedstock Press juice Press cake GBR_fibres grass silage feed proteins, biogas CHP fibres for technical applications GBR_amino_acids grass silage amino acids, lactic acid Biogas CHP Biogas grass silage Biogas CHP

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Integrated modelling framework

EPIC

Biophysical process simulation model

PASMA[grid]

Austrian agricultural and forestry sector model Simulates biophysical processes such as crop yields and nutrient cycles at 1x1 km Derives economically optimal production

BioResume

Biorefinery supply chain optimization model Maximizes profits along the biorefinery supply chain by selecting optimal. plant locations and capacities

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

PASMA[grid]

  • Biomass supply
  • Spatially explicit biomass supply

curves at 1x1 km resolution

  • competition with livestock,

bioenergy and food production

  • aggregated to 20x20 km supply

regions for MIP model

  • Direct and indirect soil

emissions

  • GHG emissions for different

management intensities (fertilizer inputs)

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Annual grass silage supply per 20x20 km supply region at a feedstock price of 100 Euro per t dm

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

BioResume – Input data

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Spatially explicit data Techno-economic and LCA data

  • Biomass supply and soil GHG

emissions of different management intensities (1x1 km)

  • 174 supply regions (20x20 km)
  • 79 potential sites
  • Road network dataset
  • Annualized capital costs
  • Operating costs
  • Energy inputs and costs
  • Transportation costs and GHG

emissions

  • Product yields and prices
  • GHG emissions of reference

products

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Life cycle GHG emissions of GBRs

  • Scope
  • Ghg mitigation potential of utilizing one t dm grass silage in different

green biorefinery systems compared to energetic utilization in biogas plants

  • Functional unit – input orientated
  • 1 t dm biomass input
  • System boundaries
  • GHG emissions from cradle to factory gate
  • Cultivation and harvest (soil emissions and machinery), biomass

transport and processing in GBR

  • Reference system

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System boundaries and reference systems

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Sensitivity and uncertainty analysis

  • Sensitivity analysis
  • Monte-Carlo simulation with 500 model runs with feasible ranges for
  • product yields and prices
  • Life cycle GHG emissions of biorefineries
  • Ghg emissions of substituted products
  • Uncertainty analysis
  • Impact of single model parameters on model results uncertainty

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Results – Supply chain design

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  • Optimal capacities for

biorefineries are on average about 6 times larger than for biogas plants

  • 8-14 GBRs instead of 30-35

biogas plants to optimally utilize the biomass potential

  • Average biomass

transportation distances increase from 30 km up to 45-50 km

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Results - Profitability

  • All concepts are economically

feasible under current policy support schemes

  • GBR_amino acids and

GBR_fibres are not economically feasible in 6% and 1% of the simulation runs for, respectively

  • Biogas lower profitability, but

also lower uncertainty due to guaranteed feed-in tariff

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Results – GHG emissions

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Results – GHG mitigation

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Effect of abolishing feed-tariffs for bioenergy

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Conclusions

  • Green biorefineries can offer a profitable utilization

pathway for grass silage in Austria

  • biogas plants rely on the current policy support schemes

(feed-in tariffs)

  • Profitability of green biorefineries is very sensitive to
  • market prices of key products (organic acids and technical fibres)
  • the development of separation and downstream costs
  • upscaling costs from pilot- to industrial scale
  • The GHG mitigation potential per t dm biomass input is in a

similar range than the pure energetic utilization in biogas plants

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Outlook

  • Limited LCA approach
  • only GHG emissions covered
  • Non renewable energy inputs
  • Land use implications
  • Demand restrictions biorefinery products
  • Limitation for overall mitigation potential

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University of Natural Resources and Life Sciences, Vienna Institute for Sustainable Economic Development

Thank you! Thank you for your interest

University of Natural Resources and Life Sciences, Vienna Department of Economics and Social Sciences Institute for Sustainable Economic Development Stefan Höltinger, Mathias Kirchner, Johannes Schmidt, Erwin Schmid Feistmantelstraße 4, A-1180 Vienna Tel.: +43 1 47654-73119 stefan.hoeltinger@boku.ac.at , http://www.wiso.boku.ac.at/inwe/

Supported by the Austrian Climate Research Programme Project ADAPT-CATMILK (KR13AC6K11112)