Latvijas klimata un enerģētikas politikas mērķi, risinājumi un analīzes metodes
DOI:
https://doi.org/10.22364/adz.56.13Keywords:
enerģētikas un klimata politika, siltumnīcefekta gāzes, klimata neitralitāte, modelēšana, Eiropas Savienība, investīciju analīzeAbstract
Ievērojot modelēšanas rīku dažādību, ja iespējams un citas metodes nav acīmredzami labākas, priekšroka jādod metodēm un rīkiem, kas jau iepriekš izmantoti Latvijas pētījumos
References
Adedeji, O. et al. (2014) Global Climate Change. Journal of Geoscience and Environment Protection, 2, 114–122.
Andersen, K. S. et al. (2019) Bridging the gap using energy services: Demonstrating a novel framework for soft linking top-down and bottom-up models. Energy, 169, 277–293.
Babatunde, K. A.; Begum, R. A.; Said F. F. (2017) Application of computable general equilibrium (CGE) to climate change mitigation policy: A systematic review. Renewable & Sustainable Energy Reviews, 78, 61–71.
Balyk, O. et al. (2019) TIMES-DK: Technology-rich multi-sectoral optimisation model of the Danish energy system. Energy Strategy Reviews, 23, 13–22.
Bataille, F. G. N. et al. (2019) Prospects for energy economy modelling with big data: Hype, eliminating blind spots, or revolutionising the state of the art? Applied Energy, 239, 991–1002.
Bazbauers, G.; Cimdina, G. (2011) The Role of the Latvian District Heating System in the Development of Sustainable Energy Supply. Environmental and Climate Technologies, 7, 27–31.
Blumberga, A. et al. (2015) Achieving sustainability in non-ETS sectors using system dynamics modelling practice. Chemical Engineering Transactions, 45, 871–876.
Bolwig, S. et al. (2019) Review of modelling energy transitions pathways with application to energy system flexibility. Renewable & Sustainable Energy Reviews, 101, 440–452.
Butler, C. D. (2018) Climate change, health and existential risks to civilization: A comprehensive review (1989–2013). International Journal of Environmental Research and Public Health, 15, 2266.
Capros, P. et al. (2014) Description of models and scenarios used to assess European decarbonisation pathways. Energy Strategy Rewievs, 2, 3–4, 220–230.
Chen, W. et al. (2017) Shared social-economic pathways (SSPs) modeling: Application of global multi-region energy system model. Energy Procedia, 142, 2467–2472.
Cilinskis, E.; Blumberga, D. (2017) Latvijas klimata politika un valsts attīstības plānošanas sistēma. Akadēmiskā Dzīve, 53, 139–148.
Climate Change Resaurce Center (2020) Natural Climate Cycles. Pieejams: https://www.fs.usda.gov/ccrc/climate-basics/climate-primer/natural-climate-cycles (17.08.2020.).
Climate Interactive (2020) En-ROADS Guide Documentation. Pieejams: https://docs.climateinteractive.org/projects/en-roads/en/latest/ (17.08.2020).
Cortekar, J.; Themessl, M.; Lamich K. (2020) Systematic analysis of EU-based climate service providers. Climate Services, 17, 100125.
Doukas, H. A.; Nikas, A. (2020) Decision support models in climate policy. European Journal of Operational Research, 280, 1, 1–24.
Eiropas Komisija (2019) Eiropas zaļais kurss. Pieejams: https://eur-lex.europa.eu/legal-content/LV/TXT/?uri=CELEX:52019DC0640 (17.08.2020.).
Griscom, B. W. et al. (2017) Natural climate solutions. Proceedings of the National Academy of Sciences of the Unitaed States of America, 114, 44, 11645–11650.
Hainaut, H.; Cochran, I. (2018) The Landscape of domestic climate investment and finance flows: Methodological lessons from five years of application in France. International Economics, 155, 69–83.
Hainaut, H.; Ledez, M.; Parrier, Q.; Leguet, B.; Geoffron, P. (2020) Investing in Climate can Help France Drive its Economic Recovery. Paris : I4CE. Pieejams: https://www.i4ce.org/wp-core/wp-content/uploads/2020/04/I4CE-Investating-in-climate-economic-recovery.pdf (17.08.2020.).
Hall, L. M. H.; Buckley, A. R. (2016) A review of energy systems models in the UK: Prevalent usage and categorisation. Applied Energy, 169, 607–628.
Herbst, A.; Toro, F.; Reitze, F.; Jochem, E. (2012) Introduction to Energy Systems Modelling. Swiss Journal of Economics and Statistics, 148 (2), 111–135.
Hugues, P.; Assoumou, E.; Maizi, N. (2016) Assessing GHG mitigation and associated cost of French biofuel sector: Insights from a TIMES model. Energy, 113, 288–300.
IPCC (2017) IPCC special report on the impacts of global warming of 1.5 °C. Pieejams: https://www.ipcc.ch/sr15/ (17.08.2020.).
Jacobson, M. Z. et al. (2018) Matching demand with supply at low cost in 139 countries among 20 world regions with 100% intermittent wind, water, and sunlight (WWS) for all purposes. Renewable Energy, 123, 236–248.
Kamenders, A.; Rochas, C.; Novikova, A. (2019) Investīcijas energoefektivitātes un atjaunīgo energoresursu projektos Latvijā. Riga : Riga Technical University. Pieejams: https://www.ikem.de/wp-content/uploads/2020/03/Kamenders-et-al.-2019.-Energy-and-Climate-Investment-Map-for-Latvia-2018.-Full-Report.-Latvian.pdf (17.08.2020.).
Keppo, P. H.; Li, I.; Strachan, N. (2018) Incorporating homeowners’ preferences of heating technologies in the UK TIMES model. Energy, 148, 716–727.
Klavs, G.; Kudrenickis, I.; Rekis, J. (2015) Development of Latvia Greenhouse Gas reduction Policy: Modelling and analyses. 15th International Multidisciplinary Scientific GeoConference SGEM, 921–932.
Klavs, G.; Rekis, J. (2016) Introduction of Energy and Climate Mitigation Policy Issues in Energy – Environment Model of Latvia. Latvian Journal of Physics and Technical Sciences, 53, 6, 12–20.
Krook-Riekkola, A.; Berg, C.; Ahlgren, E. O.; Patrik, S. (2017) Challenges in top-down and bottom-up soft-linking : Lessons from linking a Swedish energy system model with a CGE model. Energy, 141, 803–817.
Laha, P.; Chakraborty, B. (2017) Energy model – A tool for preventing energy dysfunction. Renewable & Sustainable Energy Reviews, 73, 95–114.
Lamperti, F. et al. (2020) Climate change and green transitions in an agent-based integrated assessment model. Technological Forecasting and Social Change, 153, 119806.
Latvijas Republikas Ministru kabinets (2020) Latvijas stratēģija klimatneitralitātes sasniegšanai līdz 2050. gadam. Pieejams: http://tap.mk.gov.lv/mk/tap/?pid=40462398 (17.08.2020.).
Lindroos, T. J.; Lehtilä, A.; Koljonen, T.; Kofoed-Wiuff, A. (2018) Baltic Energy Technology Scenarios 2018. Pieejams: https://www.nordicenergy.org/publications/baltic-energy-technology-scenarios-2018/ (17.08.2020.).
Lund, H. et al. (2017) Simulation versus optimisation: Theoretical positions in energy system modelling. Energies, 10, 7, 1–17.
Lund, H.; Østergaard, P. A.; Connolly, D.; Mathiesen, B. V. (2017) Smart energy and smart energy systems. Energy, 137, 556–565.
NEKP (2020) Par Latvijas Nacionālo enerģētikas un klimata plānu 2021.–2030. gadam. Pieejams: https://likumi.lv/ta/id/312423-par-latvijas-nacionalo-energetikas-un-klimata-planu-2021-2030-gadam (17.08.2020).
Nicola, M. et al. (2020) The Socio-Economic Implications of the Coronavirus and COVID-19 Pandemic: A Review. IJS Publishing Group.
OECD (2017) Investing in Climate, Investing in Growth. Paris : OECD Publishing.
Panos, E.; Kannan, R. (2016) The role of domestic biomass in electricity, heat and grid balancing markets in Switzerland. Energy, 112, 1120–1138.
Papachristos, G. (2019) System dynamics modelling and simulation for sociotechnical transitions research. Environmental Innovation and Societal Transitions, 31, 248–261.
Pfenninger, S. et al. (2018) Opening the black box of energy modelling: Strategies and lessons learned. Energy Strategy Reviews, 19, 63–71.
Pleßmann, G.; Blechinger, P. (2017) How to meet EU GHG emission reduction targets?: A model based decarbonization pathway for Europe’s electricity supply system until 2050. Energy Strategy Reviews, 15, 19–32.
Porubova, J.; Bazbauers, G. (2010) Analysis of Long-Term Plan for Energy Supply System for Latvia that is 100% Based on the Use of Local Energy Resources. Environtal and Climate Technologies, 4, 1, 82–90.
Ringkjøb, H.-K.; Haugan, P. M.; Solbrekke, I. M. (2018) A review of modelling tools for energy and electricity systems with large shares of variable renewables. Renewable & Sustainable Energy Reviews, 96, 440–459.
Sharma, T., Balachandra, P. (2019) Model based approach for planning dynamic integration of renewable energy in a transitioning electricity system. International Journal of Electrical Power & Energy Systems, 105, 642–659.
Son, H.; Kim, C. (2020) A Deep Learning Approach to Forecasting Monthly Demand for Residential-Sector Electricity. Sustainability, 12, 8, 3103.
Subramanian, A. S. R.; Gundersen, T.; Adams, T. A. (2018) Modeling and simulation of energy systems: A review. Processes, 6, 238.
Tol, R. S. J. (2019) Climate Economics: Economic Analysis of Climate, Climate Change and Climate Policy. Edward Elgar.
UNEP (2014) Using Models for Green Economy Policymaking. Pieejams: https://www.un-page.org/files/public/content-page/unep_models_ge_for_web.pdf (17.08.2020.).
UNFCCC (2015) Paris Agreement. Pieejams: https://unfccc.int/process-and-meetings/the-paris-agreement/the-paris-agreement (17.08.2020.).
United Nations Environment Programme (2019) Emissions gap report 2019. Pieejams: https://wedocs.unep.org/bitstream/handle/20.500.11822/30797/EGR2019.pdf (17.08.2020.).
Wang, Z.; Wu, J.; Liu, C.; Gu, G. (2017) Integrated Assessment Models of Climate Change Economics. Springer.
Wei, N.; Li, C.; Peng, X.; Zeng, F.; Lu, X. (2019) Conventional models and artificial intelligence-based models for energy consumption forecasting: A review. Journal of Petroleum Science and Engineering, 181, 106187.
Wiese, F. et al. (2018) Balmorel open source energy system model. Energy Strategy Reviews, 20, 26–34.
Yang, P. et al. (2018) Social cost of carbon under shared socioeconomic pathways. Global Environmental Change, 53, 225–232.
Ziemele, J. et al. (2016) System dynamics model analysis of pathway to 4th generation district heating in Latvia. Energy, 110, 85–94.
Ziemele, J. et al. (2017) Impact of economical mechanisms on CO2 emissions from non-ETS district heating in Latvia using system dynamic approach. International Journal of Energy and Environmental Engineering, 9, 111–121.
