Have a personal or library account? Click to login
Bioresource Value Model. Case of Fisheries Cover

References

  1. [1] Vea E. B., Romeo D., Thomsen M. Biowaste Valorisation in a Future Circular Bioeconomy. Procedia CIRP 2018:69:591–596. https://doi,org/10.1016/J.PROCIR.2017.11.06210.1016/j.procir.2017.11.062
  2. [2] European Commission. Communication From The Commission To The European Parliament, The European Council, The Council, The European Economic And Social Committee And The Committee Of The Regions The European Green Deal. Brussels: EC, 2019.
  3. [3] Mikova N., Eichhammer W., Pfluger B. Low-carbon energy scenarios 2050 in north-west European countries: Towards a more harmonised approach to achieve the EU targets. Energy Policy 2019:130(C):448–460. https://doi.org/10.1016/J.ENPOL.2019.03.04710.1016/j.enpol.2019.03.047
  4. [4] Silveira S., et al. Opportunities for bioenergy in the Baltic Sea Region. Energy Procedia 2017:128:157–164. https://doi.org/10.1016/J.EGYPRO.2017.09.03610.1016/j.egypro.2017.09.036
  5. [5] Jonsson P. R., et al. Report on the importance of connectivity as a driver of biodiversity (populations, species, communities, habitats). BIO-C3 Deliv. D3.3. EU Bonusproject BIO -C3. Kiel: BIO-C3, 2016. https://doi.org/10.3289/BIO-C3_D3.3
  6. [6] Bell J., et al. EU ambition to build the world’s leading bioeconomy—Uncertain times demand innovative and sustainable solutions. New Biotechnol. 2018:40:25–30. https://doi.org/10.1016/J.NBT.2017.06.01010.1016/j.nbt.2017.06.01028676417
  7. [7] European Commission. Biomass production, supply, uses and flows in the European Union. Luxembourg: Publication office of the European Union, 2018.
  8. [8] Kamm B., Kamm M. Principles of biorefineries. Appl. Microbiol. Biotechnol. 2004:64(2):137–145. https://doi.org/10.1007/S00253-003-1537-710.1007/s00253-003-1537-714749903
  9. [9] Sanz-Hernández A., Esteban E., Garrido P. Transition to a bioeconomy: Perspectives from social sciences. J. Clean. Prod. 2019:224:107–119. https://doi.org/10.1016/J.JCLEPRO.2019.03.16810.1016/j.jclepro.2019.03.168
  10. [10] Fava F., et al. Biowaste biorefinery in Europe: opportunities and research & development needs. New Biotechnol. 2015:32(1):100–108. https://doi.org/10.1016/J.NBT.2013.11.00310.1016/j.nbt.2013.11.00324284045
  11. [11] Zihare L., et al. Bioeconomy triple factor nexus through indicator analysis. New Biotechnol. 2021:61:57–68. https://doi.org/10.1016/J.NBT.2020.11.00810.1016/j.nbt.2020.11.00833220518
  12. [12] Heimann T. Bioeconomy and SDGs: Does the Bioeconomy Support the Achievement of the SDGs? Earth’s Futur. 2019:7(1):43–57. https://doi.org/10.1029/2018EF00101410.1029/2018EF001014
  13. [13] de Albuquerque T. L., et al. Biotechnological Strategies for the Lignin-Based Biorefinery Valorization. Ref. Modul. Chem. Mol. Sci. Chem. Eng. 2019. https://doi.org/10.1016/B978-0-12-409547-2.14570-610.1016/B978-0-12-409547-2.14570-6
  14. [14] Sauvée L., Viaggi D. Biorefineries in the bio-based economy: opportunities and challenges for economic research. Bio-based Appl. Econ. 2016:5(1):1–4. https://doi.org/10.13128/BAE-18336
  15. [15] Carioca J. O. B., Leal M. R. L. V. Ethanol Production from Sugar-Based Feedstocks. In Murray Moo-Young (eds) Comprehensive Biotechnology. 2nd Ed. Academic Press 2011:27–35. https://doi.org/10.1016/B978-0-08-088504-9.00184-710.1016/B978-0-08-088504-9.00184-7
  16. [16] Yu S., et al. Nanocellulose from various biomass wastes: Its preparation and potential usages towards the high value-added products. Environ. Sci. Ecotechnology 2021:5:100077. https://doi.org/10.1016/J.ESE.2020.10007710.1016/j.ese.2020.100077
  17. [17] Velvizhi G., et al. Integrated biorefinery processes for conversion of lignocellulosic biomass to value added materials: Paving a path towards circular economy. Bioresour. Technol. 2022:343:126151. https://doi.org/10.1016/J.BIORTECH.2021.12615110.1016/j.biortech.2021.126151
  18. [18] Lu H., et al. Bioprospecting microbial hosts to valorize lignocellulose biomass – Environmental perspectives and value-added bioproducts. Chemosphere 2021. In Press. https://doi.org/10.1016/J.CHEMOSPHERE.2021.13257410.1016/j.chemosphere.2021.132574
  19. [19] Tortorella M. M., et al. A Methodological Integrated Approach to Analyse Climate Change Effects in Agri-Food Sector: The TIMES Water-Energy-Food Module. Int. J. Environ. Res. Public Heal. 2020:17(21):7703. https://doi.org/10.3390/IJERPH1721770310.3390/ijerph17217703
  20. [20] Mercure J. F., et al. Environmental impact assessment for climate change policy with the simulation-based integrated assessment model E3ME-FTT-GENIE. Energy Strateg. Rev. 2018:20:195–208. https://doi.org/10.1016/J.ESR.2018.03.00310.1016/j.esr.2018.03.003
  21. [21] Barker T. The effects on competitiveness of coordinated versus unilateral fiscal policies reducing GHG emissions in the EU: an assessment of a 10% reduction by 2010 using the E3ME model. Energy Policy 1998:26(14):1083–1098. https://doi.org/10.1016/S0301-4215(98)00053-610.1016/S0301-4215(98)00053-6
  22. [22] Novero A. U., et al. The use of light detection and ranging (LiDAR) technology and GIS in the assessment and mapping of bioresources in Davao Region, Mindanao Island, Philippines. Remote Sens. Appl. Soc. Environ. 2019:13:1–11. https://doi.org/10.1016/J.RSASE.2018.10.01110.1016/j.rsase.2018.10.011
  23. [23] Turner R., et al. Estimation of soil surface roughness of agricultural soils using airborne LiDAR. Remote Sens. Environ. 2014:140:107–117. https://doi.org/10.1016/J.RSE.2013.08.03010.1016/j.rse.2013.08.030
  24. [24] Partridge M. D., Rickman D. S. Computable General Equilibrium (CGE) Modelling for Regional Economic Development Analysis. 2008:44(10):1311–1328. https://doi.org/10.1080/0034340070165423610.1080/00343400701654236
  25. [25] Fouré J., Guimbard H., Monjon S. Border carbon adjustment and trade retaliation: What would be the cost for the European Union? Energy Econ. 2016:54:349–362. https://doi.org/10.1016/j.eneco.2015.11.02110.1016/j.eneco.2015.11.021
  26. [26] Malins C., Plevin R., Edwards R. How robust are reductions in modeled estimates from GTAP-BIO of the indirect land use change induced by conventional biofuels? J. Clean. Prod. 2020:258:120716. https://doi.org/10.1016/j.jclepro.2020.12071610.1016/j.jclepro.2020.120716
  27. [27] Brinkman M., et al. The distribution of food security impacts of biofuels, a Ghana case study. Biomass and Bioenergy 2020:141:105695. https://doi.org/10.1016/j.biombioe.2020.10569510.1016/j.biombioe.2020.105695
  28. [28] Komarek A. M., et al. Income, consumer preferences, and the future of livestock-derived food demand. Glob. Environ. Chang. 2021:70:102343. https://doi.org/10.1016/J.GLOENVCHA.2021.10234310.1016/j.gloenvcha.2021.102343761205734857999
  29. [29] Laborde D., et al. Assessment framework and operational definitions for long-term scenarios. FOODSECURE Work. Pap. Hague: WUR, 2013.
  30. [30] Havlík P., et al. Climate change mitigation through livestock system transitions. Proc. Natl. Acad. Sci. U. S. A. 2014:111(10):3709–3714. https://doi.org/10.1073/PNAS.130804411110.1073/pnas.1308044111395614324567375
  31. [31] Grosky W. I., Stanchev P. L. An Image Data Model. In Laurini R. (eds) Advances in Visual Information Systems. VISUAL 2000. Lecture Notes in Computer Science, vol. 1929. Springer, 2000. https://doi.org/10.1007/3-540-40053-2_210.1007/3-540-40053-2_2
  32. [32] Gibon T., et al. A Methodology for Integrated, Multiregional Life Cycle Assessment Scenarios under Large-Scale Technological Change. Environ. Sci. Technol. 2015:49(18):11218–11226. https://doi.org/10.1021/ACS.EST.5B0155810.1021/acs.est.5b0155826308384
  33. [33] Pauliuk S., Hertwich E. G. Prospective Models of Society’s Future Metabolism: What Industrial Ecology Has to Contribute. In Clift R., Druckman A. (eds) Taking Stock of Industrial Ecology. Springer, 2016. https://doi.org/10.1007/978-3-319-20571-7_210.1007/978-3-319-20571-7_2
  34. [34] Pavičević M., et al. The potential of sector coupling in future European energy systems: Soft linking between the Dispa-SET and JRC-EU-TIMES models. Applied Energy 2020:267:115100. https://doi.org/10.1016/J.APENERGY.2020.11510010.1016/j.apenergy.2020.115100
  35. [35] Perpiña Castillo C., et al. Modelling agricultural land abandonment in a fine spatial resolution multi-level land-use model: An application for the EU. Environ. Model. Softw. 2021:136:104946. https://doi.org/10.1016/J.ENVSOFT.2020.10494610.1016/j.envsoft.2020.104946789368733664629
  36. [36] Krzemień J. Application of Markal Model Generator in Optimizing Energy Systems. J. Sustain. Min. 2013:12(2):35–39. https://doi.org/10.7424/JSM13020510.7424/jsm130205
  37. [37] Perissi I., et al. Cross-Validation of the MEDEAS Energy-Economy-Environment Model with the Integrated MARKAL-EFOM System (TIMES) and the Long-Range Energy Alternatives Planning System (LEAP). Sustain. 2021:13(4):1967. https://doi.org/10.3390/SU1304196710.3390/su13041967
  38. [38] Seebregts A., et al. Endogenous learning and technology clustering: Analysis with MARKAL model of the Western European energy system. Int. J. Glob. Energy Issues 2000:14(1–4):289–319. https://doi.org/10.1504/IJGEI.2000.00443010.1504/IJGEI.2000.004430
  39. [39] Salvucci R., et al. Modelling transport modal shift in TIMES models through elasticities of substitution. Appl. Energy 2018:232:740–751. https://doi.org/10.1016/J.APENERGY.2018.09.08310.1016/j.apenergy.2018.09.083
  40. [40] Jaunzems D., et al. Adaptation of TIMES model structure to industrial, commercial and residential sectors. Environ. Clim. Technol. 2020:24(1):392–405. https://doi.org/10.2478/RTUECT-2020-002310.2478/rtuect-2020-0023
  41. [41] Stolarski M. J., et al. Bioenergy technologies and biomass potential vary in Northern European countries. Renew. Sustain. Energy Rev. 2020:133:110238. https://doi.org/10.1016/J.RSER.2020.11023810.1016/j.rser.2020.110238
  42. [42] Lauka D., Barisa A., Blumberga D. Assessment of the availability and utilization potential of low-quality biomass in Latvia. Energy Procedia 2018:147:518–524. https://doi.org/10.1016/J.EGYPRO.2018.07.06510.1016/j.egypro.2018.07.065
  43. [43] Irmak S. Biomass as Raw Material for Production of High-Value Products. In Biomass Vol. Estim. Valorization Energy. London: Intechopen, 2017. https://doi.org/10.5772/6550710.5772/65507
DOI: https://doi.org/10.2478/rtuect-2021-0089 | Journal eISSN: 2255-8837 | Journal ISSN: 1691-5208
Language: English
Page range: 1179 - 1192
Published on: Dec 17, 2021
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2021 Lauma Zihare, Zane Indzere, Nidhiben Patel, Maksims Feofilovs, Dagnija Blumberga, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.