{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T03:59:53Z","timestamp":1777089593584,"version":"3.51.4"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T00:00:00Z","timestamp":1705276800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T00:00:00Z","timestamp":1705276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Urban Info"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Solar photovoltaic (PV) farming is increasingly being used to power electric vehicles (EVs). Although many studies have developed dynamic EV charging prediction and scheduling models, few of them have coupled rooftop PV electricity generation with the spatiotemporal EV charging demands at an urban scale. Thus, this study develops a research framework containing three interconnected modules to investigate the feasibility of EV charging powered by rooftop PVs. The framework is constructed by the statistics of time serial EV charging demands at each station, the planning of rooftop PV installations associated with all charging stations, and the development of a dynamic dispatching algorithm to transmit surplus electricity from one station to another. The algorithm can maximize the overall balance between supply and demand, maximize the total PV electricity generation while minimising the total PV area, minimize the number of PV charging stations used as the suppliers for dynamic dispatch, and minimize the total electricity transmission distance between stations given the same power supply. The experiment utilizes a complete EV charging dataset containing 5574 charging piles with more than 9.7 million records in June and July in Guangzhou, China. The results show that rooftop PVs can supply more than 90% of the charging demand. The results encourage and inspire us to generalize and promote such a solution in other cities. Future work can refine the algorithm by adapting different PV sizes into various charging stations to further improve the electricity generation capability and the dynamic dispatching efficiency.<\/jats:p>","DOI":"10.1007\/s44212-023-00031-7","type":"journal-article","created":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T09:02:27Z","timestamp":1705309347000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["An urban-scale spatiotemporal optimization of rooftop photovoltaic charging of electric vehicles"],"prefix":"10.1007","volume":"3","author":[{"given":"Nanfan","family":"Ji","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9965-0948","authenticated-orcid":false,"given":"Rui","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Ziyi","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Linlin","family":"You","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,15]]},"reference":[{"issue":"2","key":"31_CR1","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1038\/s41928-022-00726-w","volume":"5","author":"K Afridi","year":"2022","unstructured":"Afridi, K. (2022). The future of electric vehicle charging infrastructure. Nature Electronics, 5(2), 62\u201364.","journal-title":"Nature Electronics"},{"issue":"11","key":"31_CR2","doi-asserted-by":"publisher","first-page":"14855","DOI":"10.1002\/er.8187","volume":"46","author":"ARA Alphonse","year":"2022","unstructured":"Alphonse, A. R. A., Raj, A. P. P. G., & Arumugam, M. (2022). Simultaneously allocating electric vehicle charging stations (EVCS) and photovoltaic (PV) energy resources in smart grid considering uncertainties: a hybrid technique. International Journal of Energy Research, 46(11), 14855\u201314876.","journal-title":"International Journal of Energy Research"},{"key":"31_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2020.117451","volume":"200","author":"M Alqahtani","year":"2020","unstructured":"Alqahtani, M., & Hu, M. (2020). Integrated energy scheduling and routing for a network of mobile prosumers. Energy, 200, 117451.","journal-title":"Energy"},{"issue":"8","key":"31_CR4","doi-asserted-by":"publisher","first-page":"9757","DOI":"10.1109\/TVT.2023.3254604","volume":"72","author":"A Andreou","year":"2023","unstructured":"Andreou, A., Mavromoustakis, C. X., Batalla, J. M., Markakis, E. K., Mastorakis, G., & Mumtaz, S. (2023). UAV trajectory optimisation in smart cities using modified a * algorithm combined with haversine and vincenty formulas. IEEE Transactions on Vehicular Technology, 72(8), 9757\u20139769.","journal-title":"IEEE Transactions on Vehicular Technology"},{"key":"31_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.segy.2021.100001","volume":"1","author":"T Bostr\u00f6m","year":"2021","unstructured":"Bostr\u00f6m, T., Babar, B., Hansen, J. B., & Good, C. (2021). The pure PV-EV energy system \u2013 A conceptual study of a nationwide energy system based solely on photovoltaics and electric vehicles. Smart Energy, 1, 100001.","journal-title":"Smart Energy"},{"key":"31_CR6","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.energy.2013.10.092","volume":"64","author":"G Cardoso","year":"2014","unstructured":"Cardoso, G., Stadler, M., Bozchalui, M. C., Sharma, R., Marnay, C., Barbosa-P\u00f3voa, A., & Ferr\u00e3o, P. (2014). Optimal investment and scheduling of distributed energy resources with uncertainty in electric vehicle driving schedules. Energy, 64, 17\u201330.","journal-title":"Energy"},{"key":"31_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.cageo.2014.01.002","volume":"66","author":"C Catita","year":"2014","unstructured":"Catita, C., Redweik, P., Pereira, J., & Brito, M. (2014). Extending solar potential analysis in buildings to vertical facades. Computers & Geosciences, 66, 1\u201312.","journal-title":"Computers & Geosciences"},{"key":"31_CR8","doi-asserted-by":"publisher","first-page":"400","DOI":"10.1016\/j.egyr.2018.06.004","volume":"4","author":"W Charfi","year":"2018","unstructured":"Charfi, W., Chaabane, M., Mhiri, H., & Bournot, P. (2018). Performance evaluation of a solar photovoltaic system. Energy Reports, 4, 400\u2013406.","journal-title":"Energy Reports"},{"key":"31_CR9","doi-asserted-by":"crossref","unstructured":"Chen Q., Liu S., Qu H., Zhu R., & You L. (2022, December). TWAFR-GRU: An Integrated Model for Real-time Charging Station Occupancy Prediction, In 19th IEEE International Conference on Ubiquitous Intelligence and Computing (pp. 1611-1618). IEEE.","DOI":"10.1109\/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00233"},{"key":"31_CR10","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.isprsjprs.2018.01.024","volume":"138","author":"L Cheng","year":"2018","unstructured":"Cheng, L., Xu, H., Li, S., Chen, Y., Zhang, F., & Li, M. (2018). Use of LiDAR for calculating solar irradiance on roofs and fa\u00e7ades of buildings at city scale: Methodology, validation, and analysis. ISPRS Journal of Photogrammetry and Remote Sensing, 138, 12\u201329.","journal-title":"ISPRS Journal of Photogrammetry and Remote Sensing"},{"key":"31_CR11","doi-asserted-by":"publisher","first-page":"912","DOI":"10.1016\/j.rser.2017.08.017","volume":"81","author":"UK Das","year":"2018","unstructured":"Das, U. K., Tey, K. S., Seyedmahmoudian, M., Mekhilef, S., Idris, M. Y. I., Deventer, W. V., Horan, B., & Stojcevski, A. (2018). Forecasting of photovoltaic power generation and model optimization: a review. Renewable and Sustainable Energy Reviews, 81, 912\u2013928.","journal-title":"Renewable and Sustainable Energy Reviews"},{"key":"31_CR12","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1016\/j.jpowsour.2012.10.007","volume":"236","author":"P Denholm","year":"2013","unstructured":"Denholm, P., Kuss, M., & Margolis, R. M. (2013). Co-benefits of large scale plug-in hybrid electric vehicle and solar PV deployment. Journal of Power Sources, 236, 350\u2013356.","journal-title":"Journal of Power Sources"},{"key":"31_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2020.117680","volume":"202","author":"O Elma","year":"2020","unstructured":"Elma, O. (2020). A dynamic charging strategy with hybrid fast charging station for electric vehicles. Energy, 202, 117680.","journal-title":"Energy"},{"issue":"3","key":"31_CR14","doi-asserted-by":"publisher","first-page":"1576","DOI":"10.1109\/TSG.2013.2260363","volume":"4","author":"T Ersal","year":"2013","unstructured":"Ersal, T., Ahn, C., Peters, D. L., Whitefoot, J. W., Mechtenberg, A. R., Hiskens, I. A., Peng, H., Stefanopoulou, A. G., Papalambros, P. Y., & Stein, J. L. (2013). Coupling between component sizing and regulation capability in microgrids. IEEE Transactions on Smart Grid, 4(3), 1576\u20131585.","journal-title":"IEEE Transactions on Smart Grid"},{"issue":"11","key":"31_CR15","doi-asserted-by":"publisher","first-page":"4811","DOI":"10.5194\/essd-14-4811-2022","volume":"14","author":"P Friedlingstein","year":"2022","unstructured":"Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Qu\u00e9r\u00e9, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., . . . Zheng, B. (2022). Global Carbon Budget 2022. Earth System Science Data, 14(11), 4811\u20134900.","journal-title":"Earth System Science Data"},{"key":"31_CR16","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.apenergy.2015.03.013","volume":"148","author":"J Gooding","year":"2015","unstructured":"Gooding, J., Crook, R., & Tomlin, A. S. (2015). Modelling of roof geometries from low-resolution LiDAR data for city-scale solar energy applications using a neighbouring buildings method. Applied Energy, 148, 93\u2013104.","journal-title":"Applied Energy"},{"key":"31_CR17","doi-asserted-by":"publisher","first-page":"2486","DOI":"10.1038\/s41467-020-16184-x","volume":"11","author":"G He","year":"2020","unstructured":"He, G., Lin, J., Sifuentes, F., Liu, X., Abhyankar, N., & Phadke, A. (2020). Rapid cost decrease of renewables and storage accelerates the decarbonization of China\u2019s power system. Nature Communications, 11, 2486.","journal-title":"Nature Communications"},{"issue":"2","key":"31_CR18","doi-asserted-by":"publisher","first-page":"158","DOI":"10.2747\/0272-3646.29.2.158","volume":"29","author":"S Huang","year":"2008","unstructured":"Huang, S., Rich, P. M., Crabtree, R. L., Potter, C. S., & Fu, P. (2008). Modeling monthly near-surface air temperature from solar radiation and lapse rate: application over complex terrain in yellowstone national park. Physical Geography, 29(2), 158\u2013178.","journal-title":"Physical Geography"},{"key":"31_CR19","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.apenergy.2019.04.113","volume":"250","author":"Z Huang","year":"2019","unstructured":"Huang, Z., Mendis, T., & Xu, S. (2019). Urban solar utilization potential mapping via deep learning technology: a case study of Wuhan, China. Applied Energy, 250, 283\u2013291.","journal-title":"Applied Energy"},{"key":"31_CR20","doi-asserted-by":"publisher","first-page":"154804","DOI":"10.1109\/ACCESS.2021.3128491","volume":"9","author":"AS Khwaja","year":"2021","unstructured":"Khwaja, A. S., Venkatesh, B., & Anpalagan, A. (2021). Performance analysis of LSTMs for daily individual EV charging behavior prediction. IEEE Access, 9, 154804\u2013154814.","journal-title":"IEEE Access"},{"key":"31_CR21","doi-asserted-by":"publisher","first-page":"100076","DOI":"10.1016\/j.etran.2020.100076","volume":"6","author":"D Li","year":"2020","unstructured":"Li, D., Zouma, A., Liao, J. T., & Yang, H. Z. (2020). An energy management strategy with renewable energy and energy storage system for a large electric vehicle charging station. eTransportation, 6, 100076.","journal-title":"eTransportation"},{"issue":"3","key":"31_CR22","doi-asserted-by":"publisher","first-page":"719","DOI":"10.35833\/MPCE.2020.000460","volume":"10","author":"S Li","year":"2021","unstructured":"Li, S., Hu, W., Cao, D., Dragi\u010devi\u0107, T., Huang, Q., Chen, Z., & Blaabjerg, F. (2021). Electric vehicle charging management based on deep reinforcement learning. Journal of Modern Power Systems and Clean Energy, 10(3), 719\u2013730.","journal-title":"Journal of Modern Power Systems and Clean Energy"},{"issue":"4","key":"31_CR23","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1038\/s43017-022-00285-w","volume":"3","author":"Z Liu","year":"2022","unstructured":"Liu, Z., Deng, Z., Davis, S. J., Giron, C., & Ciais, P. (2022). Monitoring global carbon emissions in 2021. Nature Reviews Earth & Environment, 3(4), 217\u2013219.","journal-title":"Nature Reviews Earth & Environment"},{"issue":"19","key":"31_CR24","doi-asserted-by":"publisher","first-page":"7029","DOI":"10.3390\/en15197029","volume":"15","author":"X Luo","year":"2022","unstructured":"Luo, X., Pan, L., & Yang, J. (2022). Mineral resource constraints for China\u2019s clean energy development under carbon peaking and carbon neutrality targets: quantitative evaluation and scenario analysis. Energies, 15(19), 7029.","journal-title":"Energies"},{"key":"31_CR25","doi-asserted-by":"publisher","first-page":"14","DOI":"10.3389\/fenvs.2014.00014","volume":"2","author":"V Masson","year":"2014","unstructured":"Masson, V., Bonhomme, M., Salagnac, J. L., Briottet, X., & Lemonsu, A. (2014). Solar panels reduce both global warming and urban heat island. Frontiers in Environmental Science., 2, 14.","journal-title":"Frontiers in Environmental Science."},{"key":"31_CR26","first-page":"37","volume":"9","author":"MP McCarthy","year":"2010","unstructured":"McCarthy, M. P., Best, M. J., & Betts, R. A. (2010). Climate change in cities due to global warming and urban effects. Geophysical Research Letters, 9, 37.","journal-title":"Geophysical Research Letters"},{"key":"31_CR27","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/j.energy.2014.11.069","volume":"80","author":"P Nunes","year":"2015","unstructured":"Nunes, P., Farias, T., & Brito, M. C. (2015). Day charging electric vehicles with excess solar electricity for a sustainable energy system. Energy, 80, 263\u2013274.","journal-title":"Energy"},{"key":"31_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.techfore.2022.121517","volume":"177","author":"M Papoutsoglou","year":"2022","unstructured":"Papoutsoglou, M., Rigas, E. S., Kapitsaki, G. M., Angelis, L., & Wachs, J. (2022). Online labour market analytics for the green economy: the case of electric vehicles. Technological Forecasting and Social Change, 177, 121517.","journal-title":"Technological Forecasting and Social Change"},{"issue":"6283","key":"31_CR29","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1126\/science.aad4424","volume":"352","author":"A Polman","year":"2016","unstructured":"Polman, A., Knight, M., Garnett, E. C., Ehrler, B., & Sinke, W. C. (2016). Photovoltaic materials: present efficiencies and future challenges. Science, 352(6283), 307\u2013307.","journal-title":"Science"},{"issue":"4","key":"31_CR30","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1145\/3511666","volume":"65","author":"H Schmeck","year":"2022","unstructured":"Schmeck, H., Monti, A., & Hagenmeyer, V. (2022). Energy informatics: key elements for tomorrow\u2019s energy system. Communications of the ACM, 65(4), 58\u201363.","journal-title":"Communications of the ACM"},{"key":"31_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.eiar.2021.106571","volume":"89","author":"S Shi","year":"2021","unstructured":"Shi, S., & Yin, J. (2021). Global research on carbon emissions: A scientometric review. Environmental Impact Assessment Review, 89, 106571.","journal-title":"Environmental Impact Assessment Review"},{"issue":"12","key":"31_CR32","doi-asserted-by":"publisher","first-page":"3207","DOI":"10.3390\/rs15123207","volume":"15","author":"Y Wang","year":"2023","unstructured":"Wang, Y., Wang, M., Teng, F., & Ji, Y. (2023). Remote sensing monitoring and analysis of Spatiotemporal changes in China\u2019s Anthropogenic carbon emissions based on XCO2 data. Remote Sensing, 15(12), 3207.","journal-title":"Remote Sensing"},{"key":"31_CR33","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1016\/j.renene.2016.07.003","volume":"99","author":"MS Wong","year":"2016","unstructured":"Wong, M. S., Zhu, R., Liu, Z., Lu, L., Peng, J., Tang, Z., Lo, C. H., & Chan, W. K. (2016). Estimation of Hong Kong\u2019s solar energy potential using GIS and remote sensing technologies. Renewable Energy, 99, 325\u2013335.","journal-title":"Renewable Energy"},{"key":"31_CR34","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1016\/j.energy.2015.03.051","volume":"85","author":"C Wouters","year":"2015","unstructured":"Wouters, C., Fraga, E. S., & James, A. M. (2015). An energy integrated, multi-microgrid, MILP (mixed-integer linear programming) approach for residential distributed energy system planning \u2013 a South Australian case-study. Energy, 85, 30\u201344.","journal-title":"Energy"},{"key":"31_CR35","doi-asserted-by":"publisher","first-page":"1901","DOI":"10.1016\/j.energy.2015.07.013","volume":"90","author":"Y Yang","year":"2015","unstructured":"Yang, Y., Zhang, S., & Xiao, Y. (2015). An MILP (mixed integer linear programming) model for optimal design of district-scale distributed energy resource systems. Energy, 90, 1901\u20131915.","journal-title":"Energy"},{"key":"31_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2021.129833","volume":"330","author":"X Yao","year":"2022","unstructured":"Yao, X., Fan, Y., Zhao, F., & Ma, S. C. (2022). Economic and climate benefits of vehicle-to-grid for low-carbon transitions of power systems: a case study of China\u2019s 2030 renewable energy target. Journal of Cleaner Production, 330, 129833.","journal-title":"Journal of Cleaner Production"},{"key":"31_CR37","doi-asserted-by":"crossref","unstructured":"You, L., Tuncer, B., Zhu, R., Xing, H., & Yuen, C. (2019). A Synergetic Orchestration of Objects, Data, and Services to Enable Smart Cities. IEEE Internet of Things Journal, 6(6), 10496\u201310507.","DOI":"10.1109\/JIOT.2019.2939496"},{"issue":"1","key":"31_CR38","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1109\/TII.2015.2494884","volume":"12","author":"R Yu","year":"2016","unstructured":"Yu, R., Zhong, W., Xie, S., Yuen, C., Gjessing, S., & Zhang, Y. (2016). Balancing power demand through EV mobility in vehicle-to-grid mobile energy networks. IEEE Transactions on Industrial Informatics, 12(1), 79\u201390.","journal-title":"IEEE Transactions on Industrial Informatics"},{"issue":"1","key":"31_CR39","doi-asserted-by":"publisher","first-page":"228","DOI":"10.3390\/rs15010228","volume":"15","author":"Y Zhang","year":"2023","unstructured":"Zhang, Y., Qin, W., Wang, L., Yang, C., Su, X., & Wu, J. (2023). Enhancement of Photovoltaic power potential in China from 2010 to 2020: the contribution of air pollution control policies. Remote Sensing, 15(1), 228.","journal-title":"Remote Sensing"},{"key":"31_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2019.101738","volume":"51","author":"R Zhu","year":"2019","unstructured":"Zhu, R., Kondor, D., Cheng, C., Zhang, X., Santi, P., Wong, M. S., & Ratti, C. (2022b). Solar photovoltaic generation for charging shared electric scooters. Applied Energy,\u00a0313, 118728.","journal-title":"Hong Kong. Sustainable Cities and Society"},{"key":"31_CR41","doi-asserted-by":"publisher","first-page":"1111","DOI":"10.1016\/j.renene.2020.02.050","volume":"153","author":"R Zhu","year":"2020","unstructured":"Zhu, R., Kwan, M. P., Perera, A. T. D., Fan, H., Yang, B., Chen, B., Chen, M., Qian, Z., Zhang, H., Zhang, X., Yang, J., Santi, P., Ratti, C., Li, W., & Yan, J. (2023). GIScience can facilitate the development of solar cities for energy transition. Advances in Applied Energy, 10, 100129.","journal-title":"Renewable Energy"},{"key":"31_CR42","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2021.103614","volume":"78","author":"R Zhu","year":"2022","unstructured":"Zhu, R., Wong, M. S., Kwan, M. P., Chen, M., Santi, P., & Ratti, C. (2022a). An economically feasible optimization of photovoltaic provision using real electricity demand: a case study in New York City. Sustainable Cities and Society, 78, 103614.","journal-title":"Sustainable Cities and Society"},{"key":"31_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2022.118728","volume":"313","author":"R Zhu","year":"2022","unstructured":"Zhu, R., Wong, M. S., You, L., Santi, P., Nichol, J., Ho, H. C., Lu, L., & Ratti, C. (2020). The effect of urban morphology on the solar capacity of three-dimensional cities. Renewable Energy, 153, 1111\u20131126.","journal-title":"Applied Energy"},{"key":"31_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.adapen.2023.100129","volume":"10","author":"R Zhu","year":"2023","unstructured":"Zhu, R., You, L., Santi, P., Wong, M. S., & Ratti, C. (2019). Solar accessibility in developing cities: a case study in Kowloon East. Hong Kong. Sustainable Cities and Society, 51, 101738.","journal-title":"Advances in Applied Energy"}],"container-title":["Urban Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44212-023-00031-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44212-023-00031-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44212-023-00031-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T09:18:34Z","timestamp":1705310314000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44212-023-00031-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,15]]},"references-count":44,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["31"],"URL":"https:\/\/doi.org\/10.1007\/s44212-023-00031-7","relation":{},"ISSN":["2731-6963"],"issn-type":[{"value":"2731-6963","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,15]]},"assertion":[{"value":"13 August 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 November 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 November 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 January 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no conflict of interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"4"}}