IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v246y2022ics0360544222002559.html
   My bibliography  Save this article

Going beyond European emission targets: Pathways for an urban energy transition in the city of Riga

Author

Listed:
  • Oliveira, Fabio Fava
  • Sousa, Duarte M.
  • Kotoviča, Nika

Abstract

The city of Riga, currently updating their energy planning strategy for 2020–2030, surpassed the emission reduction target of the EU for 2030. Suitable targets for Riga are a reduction by 61% (2030) and 70% (2050), respectively, compared to 1990 levels. To achieve these objectives, this paper describes the research work defining pathways and measures in line with the planned actions of Riga, that focus on three thematic areas: green hydrogen, solar engagement, and modern transportation. The characterisation and comparison of the pathways is based on a graphical indicator method and weighting different factors accordingly to the Riga energy framework. The research done shows that production of green hydrogen is economically viable for Riga, achieving a Levelized Cost of Electricity of 0.0395 EUR/kWh and a Levelized Cost of Hydrogen of 3.67 EUR/kgH2. Rooftop photovoltaic systems represent an appealing option for the citizens if a feed-in tariff of 0.1 EUR/kWh is awarded. As additional outcomes, this paper proposes alternative loan schemes such as voucher return packages that can foster citizen engagement in renewable projects and defines strategies to reduce road emissions that could include the development of microalgae carbon capture systems and the creation of a fossil-free last-mile delivery zone.

Suggested Citation

  • Oliveira, Fabio Fava & Sousa, Duarte M. & Kotoviča, Nika, 2022. "Going beyond European emission targets: Pathways for an urban energy transition in the city of Riga," Energy, Elsevier, vol. 246(C).
    • Handle: RePEc:eee:energy:v:246:y:2022:i:c:s0360544222002559
    DOI: 10.1016/j.energy.2022.123352
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222002559
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.123352?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ghanadan, Rebecca & Koomey, Jonathan G., 2005. "Using energy scenarios to explore alternative energy pathways in California," Energy Policy, Elsevier, vol. 33(9), pages 1117-1142, June.
    2. Niels Agatz & Paul Bouman & Marie Schmidt, 2018. "Optimization Approaches for the Traveling Salesman Problem with Drone," Transportation Science, INFORMS, vol. 52(4), pages 965-981, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zong, Fang & Li, Yu-Xuan & Zeng, Meng, 2023. "Developing a carbon emission charging scheme considering mobility as a service," Energy, Elsevier, vol. 267(C).
    2. Kılkış, Şiir, 2023. "Integrated urban scenarios of emissions, land use efficiency and benchmarking for climate neutrality and sustainability," Energy, Elsevier, vol. 285(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pei, Zhi & Dai, Xu & Yuan, Yilun & Du, Rui & Liu, Changchun, 2021. "Managing price and fleet size for courier service with shared drones," Omega, Elsevier, vol. 104(C).
    2. Qiqian Zhang & Xiao Huang & Honghai Zhang & Chunyun He, 2023. "Research on Logistics Path Optimization for a Two-Stage Collaborative Delivery System Using Vehicles and UAVs," Sustainability, MDPI, vol. 15(17), pages 1-20, September.
    3. Stefan Poikonen & Bruce Golden, 2020. "The Mothership and Drone Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 249-262, April.
    4. Cheng, Chun & Adulyasak, Yossiri & Rousseau, Louis-Martin, 2020. "Drone routing with energy function: Formulation and exact algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 364-387.
    5. Perwez, Usama & Sohail, Ahmed & Hassan, Syed Fahad & Zia, Usman, 2015. "The long-term forecast of Pakistan's electricity supply and demand: An application of long range energy alternatives planning," Energy, Elsevier, vol. 93(P2), pages 2423-2435.
    6. Yang Xia & Wenjia Zeng & Xinjie Xing & Yuanzhu Zhan & Kim Hua Tan & Ajay Kumar, 2023. "Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing," Annals of Operations Research, Springer, vol. 327(1), pages 89-127, August.
    7. Lachman, Daniël A., 2011. "Leapfrog to the future: Energy scenarios and strategies for Suriname to 2050," Energy Policy, Elsevier, vol. 39(9), pages 5035-5044, September.
    8. Vincent F. Yu & Shih-Wei Lin & Panca Jodiawan & Yu-Chi Lai, 2023. "Solving the Flying Sidekick Traveling Salesman Problem by a Simulated Annealing Heuristic," Mathematics, MDPI, vol. 11(20), pages 1-21, October.
    9. Snežana Tadić & Mladen Krstić & Ljubica Radovanović, 2024. "Assessing Strategies to Overcome Barriers for Drone Usage in Last-Mile Logistics: A Novel Hybrid Fuzzy MCDM Model," Mathematics, MDPI, vol. 12(3), pages 1-25, January.
    10. Hafezi, Reza & Akhavan, AmirNaser & Pakseresht, Saeed & Wood, David A., 2019. "A Layered Uncertainties Scenario Synthesizing (LUSS) model applied to evaluate multiple potential long-run outcomes for Iran's natural gas exports," Energy, Elsevier, vol. 169(C), pages 646-659.
    11. Lixin Shen & Jie Sun & Dong Yang, 2024. "Research on Path Optimization for Collaborative UAVs and Mothership Monitoring of Air Pollution from Port Vessels," Sustainability, MDPI, vol. 16(12), pages 1-33, June.
    12. Yin, Yunqiang & Li, Dongwei & Wang, Dujuan & Ignatius, Joshua & Cheng, T.C.E. & Wang, Sutong, 2023. "A branch-and-price-and-cut algorithm for the truck-based drone delivery routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1125-1144.
    13. Jeong, Ho Young & Yu, David J. & Min, Byung-Cheol & Lee, Seokcheon, 2020. "The humanitarian flying warehouse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    14. Kloster, Konstantin & Moeini, Mahdi & Vigo, Daniele & Wendt, Oliver, 2023. "The multiple traveling salesman problem in presence of drone- and robot-supported packet stations," European Journal of Operational Research, Elsevier, vol. 305(2), pages 630-643.
    15. Aikaterini Papapostolou & Charikleia Karakosta & Kalliopi-Anastasia Kourti & Haris Doukas & John Psarras, 2019. "Supporting Europe’s Energy Policy Towards a Decarbonised Energy System: A Comparative Assessment," Sustainability, MDPI, vol. 11(15), pages 1-26, July.
    16. Tiniç, Gizem Ozbaygin & Karasan, Oya E. & Kara, Bahar Y. & Campbell, James F. & Ozel, Aysu, 2023. "Exact solution approaches for the minimum total cost traveling salesman problem with multiple drones," Transportation Research Part B: Methodological, Elsevier, vol. 168(C), pages 81-123.
    17. Soares, Ricardo & Marques, Alexandra & Amorim, Pedro & Parragh, Sophie N., 2024. "Synchronisation in vehicle routing: Classification schema, modelling framework and literature review," European Journal of Operational Research, Elsevier, vol. 313(3), pages 817-840.
    18. Li, Hongqi & Wang, Haotian & Chen, Jun & Bai, Ming, 2020. "Two-echelon vehicle routing problem with time windows and mobile satellites," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 179-201.
    19. Zajac, Sandra & Huber, Sandra, 2021. "Objectives and methods in multi-objective routing problems: a survey and classification scheme," European Journal of Operational Research, Elsevier, vol. 290(1), pages 1-25.
    20. Zhang, Guowei & Zhu, Ning & Ma, Shoufeng & Xia, Jun, 2021. "Humanitarian relief network assessment using collaborative truck-and-drone system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:246:y:2022:i:c:s0360544222002559. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.