► Kokosalakis, G., Merika, A., & Triantafyllou, A. (2021). Energy efficiency and emissions control: The response of the second-hand containerships sector. Energy Economics, 100, Article 105378. https://doi.org/10.1016/j.eneco.2021.105378
We explore factors that impact on price determination of second-hand containerships. Employing data-driven selection techniques to secure a sound model specification, we make use of a population of 5431 containerships and 1680 transactions registered in Clarksons database during 2005Q1-2020Q4. We find that energy efficiency, ship-specific characteristics, and attributes associated with buyers' and shipbuilders' nationality are significant determinants of ship price. The impact of environmental regulations as a driver of second-hand containership prices is also revealed. Compliance with emission controls impacts second-hand containership prices strongly and positively. Energy efficiency considerations are found to be increasingly important determinants of containership prices in the S&P market in the backwash of the 2008 crisis.
► Serafeim, A. V., Kokosalakis, G., Deidda, R., Karathanasi, I., & Langousis, A. (2022a). Probabilistic estimation of minimum night flow in water distribution networks: Large-scale application to the city of Patras in western Greece. Stochastic Environmental Research and Risk Assessment, 36(2), 643-660. https://doi.org/10.1007/s00477-021-02042-9
We introduce two alternative probabilistic approaches for minimum night flow (MNF) estimation in water distribution networks (WDNs), which are particularly suited to minimize noise effects, allowing for a better representation of the low flows during night hours, as well as the overall condition of the network. The strong point of both approaches is that they allow for confidence interval estimation of the observed MNFs. The first approach is inspired by filtering theory, and proceeds by identifying a proper scale for temporal averaging to filter out noise effects in the obtained MNF estimates. The second approach is more intuitive, as it estimates MNF as the average flow of the most probable low-consumption states of the night flows. The efficiency of the developed methods is tested in a large-scale real world application, using flow-pressure data at 1-min temporal resolution for a 4-monthly winter period (i.e. November 2018–February 2019) from the water distribution network of the City of Patras (i.e. the third largest city in Greece). Patras’ WDN covers an area of approximately 27 km2, consists of 700 km of pipeline serving approximately 213,000 consumers, and includes 86 Pressure Management Areas (PMAs) equipped with automated local stations for pressure regulation. Although conceptually and methodologically different, the two probabilistic approaches lead to very similar results, substantiating the robustness of the obtained findings from two independent standpoints, making them suitable for engineering applications and beyond.
► Serafeim, A. V., Kokosalakis, G., Deidda, R., Karathanasi, I., & Langousis, A. (2022b). Probabilistic minimum night flow estimation in water distribution networks and comparison with the water balance approach: Large-scale application to the city center of Patras in western Greece. Water, 14(1), Article 98. https://doi.org/10.3390/w14010098
Quantification of water losses (WL) in water distribution networks (WDNs) is a crucial task towards the development of proper strategies to reduce them. Currently, WL estimation methods rely on semi-empirical assumptions and different implementation strategies that increase the uncertainty of the obtained estimates. In this work, we compare the effectiveness and robustness of two widely applied WL estimation approaches found in the international literature: (a) the water balance, or top-down, approach introduced by the International Water Association (IWA), and (b) the bottom-up or minimum night flow (MNF) approach, based on a recently proposed probabilistic MNF estimation method. In doing so, we use users’ consumption and flow-pressure data from the 4 largest pressure management areas (PMAs) of the WDN of the city of Patras (the third largest city in Greece), which consist of more than 200 km of pipeline, cover the entire city center of Patras, and serve approximately 58,000 consumers. The obtained results show that: (a) when MNF estimation is done in a rigorous statistical setting from high resolution flow-pressure timeseries, and (b) there is sufficient understanding of the consumption types and patterns during day and night hours, the two approaches effectively converge, allowing for more reliable estimation of the individual WL components. In addition, when high resolution flow-pressure timeseries are available at the inlets of PMAs, the suggested version of the bottom-up approach with probabilistic estimation of MNF should be preferred as less sensitive, while allowing for confidence interval estimation of the individual components of water losses and development of proper strategies to reduce them.