Unlocking the potential of the bioeconomy for climate change reduction: The optimal use of lignocellulosic biomass in Germany.

The concept of a circular bioeconomy has become a new economic leitmotif for reducing greenhouse gas (GHG) emissions. Its central narrative rests on the idea of replacing fossil resources with biobased ones for a broad spectrum of products including, for example, heat, electricity, fuels, plastics,...

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Publicado en:Journal of Industrial Ecology Vol. 28; no. 1; pp. 144 - 160
Autores principales: Lubjuhn, Sebastian, Venghaus, Sandra
Formato: Artículo
Publicado: Springer Nature Feb2024
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2024
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      pub: Springer Nature
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        10.1111/jiec.13455
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        atl: Unlocking the potential of the bioeconomy for climate change reduction: The optimal use of lignocellulosic biomass in Germany.
      aug:
        au:
          Lubjuhn, Sebastian
          Venghaus, Sandra
        affil:
          School of Business and Economics, RWTH Aachen University, Aachen, Germany
          Forschungszentrum Jülich Institut für Energie‐ und Klimaforschung, Systemforschung und Technologische Entwicklung (IEK‐STE), Jülich, Germany
      su:
        Industrial ecology
        Greenhouse gases
        Linear programming
        Lignocellulose
        Heat pumps
      sug:
        subj:
          Industrial ecology
          Plumbing, heating and air-conditioning equipment and supplies merchant wholesalers
          Heating equipment and commercial refrigeration equipment manufacturing
          Plumbing, Heating, and Air-Conditioning Contractors
          Air-Conditioning and Warm Air Heating Equipment and Commercial and Industrial Refrigeration Equipment Manufacturing
          Greenhouse gases
          Linear programming
          Lignocellulose
          Heat pumps
      keyword:
        bioeconomics
        greenhouse gas emissions
        heat sector
        industrial ecology
        lignocellulosic biomass
        linear programming
        bioeconomics
        greenhouse gas emissions
        heat sector
        industrial ecology
        lignocellulosic biomass
        linear programming
      ab: The concept of a circular bioeconomy has become a new economic leitmotif for reducing greenhouse gas (GHG) emissions. Its central narrative rests on the idea of replacing fossil resources with biobased ones for a broad spectrum of products including, for example, heat, electricity, fuels, plastics, or chemicals. Yet, the amount of available bio‐resources is limited, rendering some technologies successful while leaving behind others. Lignocellulosic biomass (LBM) is a key resource already used on a large scale for heating purposes or electricity production and increasingly for the production of chemicals and biofuels. Because market mechanisms do not necessarily drive a cost‐optimal use with respect to their GHG‐reduction potential, a new bi‐objective linear optimization model under long‐term scenarios was developed for Germany accounting for competition with non‐biobased technologies. In the biofuels and biochemicals sectors, multi‐output processes that address industrial symbiosis and fossil references are used to compute profits and GHG emission savings of biobased products. However, in the absence of a reference for heat, a detailed representation of the heat sector is used in which heat demand for 19 subsectors is met, thus deriving costs and emission savings endogenously. When explicitly accounting for GHG emission reduction targets, biomass is optimally used in high‐temperature industries whereas heat pumps dominate in building heat. Because of the optimal use of biomass in industrial usage, subsidies for biomass heating are found to be inefficient in the building sector. Catalytic hydropyrolysis to produce biogasoline and biodiesel using LBM dominates the production of biofuels while biochemicals—strongly depending on oil price developments—will become competitive on a large scale after 2030.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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