Database.use.hdl: https://hdl.handle.net/20.500.14172/20963
Now showing 1 - 10 of 71
  • research article
    Pérez-Ruzafa, Angel
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    Molina Cuberos, Gregorio José
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    García-Oliva, Miriam
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    Marcos, Concepción
    Science of the total environment
    Coastal lagoons are among the most productive marine ecosystems in the world. Annual primary production varies from 50 to > 500 g C m−2 year−1, being of the same order of magnitude as that of the upwelling areas. Many lagoons lie within the range of eutrophic (300–500 g C m−2 year−1) or hypereutrophic (> 500 g C m−2 year−1) conditions. The high productivity of coastal lagoons makes them subject of exploitation by many marine fishes and invertebrates, that use them as nursery areas and feeding grounds during their early life cycle phases, and most lagoons support important fisheries or maintain aquaculture exploitations. The high levels of their biological production can be explained by some of their common features as shallowness and the strong influence of terrestrial systems. Shallowness favors that the photic zone extends to the lagoon bottom and that wind can promote the resuspension of nutrients and organisms. The interaction with land also introduces significant amounts of nutrients. However, trophic variables can explain < 43 % of the fishing yields, and further than the trophic status of the lagoons, several works showed that the biological productivity of coastal lagoons can be explained by their geomorphological features such as the positive influence of shoreline development and the negative influence of depth. Using the Mar Menor lagoon as a case study, we propose that although nutrient inputs and light can be limiting factors for photosynthetic based productivity, increasing fishing yield up to a certain limit, the productivity of lagoons is mainly promoted by more general forces associated to physical and chemical gradients.
      5WOS© IF 9.8WOS© AIF 6.5Scopus© SNIP 2.026
  • In coastal lagoons, eutrophication and hydrology are interacting factors that produce distortions in biogeochemical nitrogen (N) and phosphorus (P) cycles. Such distortions affect nutrient relative availability and produce cascade consequences on primary producer's community and ecosystem functioning. In this study, the seasonal functioning of a coastal lagoon was investigated with a multielement approach, via the construction and analysis of network models. Spring and summer networks, both for N and P flows, have been simultaneously compiled for the northern transitional and southern confined area of the hypertrophic Curonian Lagoon (SE Baltic Sea). Ecological Network Analysis was applied to address the combined effect of hydrology and seasonality on biogeochemical processes. Results suggest that the ecosystem is more active and presents higher N and P fluxes in summer compared to spring, regardless of the area. Furthermore, larger internal recycling characterizes the confined compared to the transitional area, regardless of the season. The two areas differed in the fate of available nutrients. The transitional area received large riverine inputs that were mainly transferred to the sea without the conversion into primary producers' biomass. The confined area had fewer inputs but proportionally larger conversion into phytoplankton biomass. In summer, particularly in the confined area, primary production was inefficiently consumed by herbivores. Most phytoplanktonic N and P, in the confined area more than in the transitional area, were conveyed to the detritus pathway where P, more than N, was recycled, contributing to the unbalance in N:P stoichiometry and favouring N-fixing cyanobacteria over other phytoplankton groups. The findings of this study provide a comprehensive understanding of N and P circulation patterns in lagoon areas characterized by different hydrology. They also support the importance of a stoichiometric approach to trace relative differences in N and P recycling and abundance, that promote blooms, drive algal communities and whole ecosystem functioning.
      9WOS© IF 9.8WOS© AIF 6.5Scopus© SNIP 2.026
  • research article
    Plungė, Svajūnas
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    Schürz, Christoph
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    Strauch, Michael
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    Piniewski, Mikołaj
    Environmental modelling & software
    The Soil and Water Assessment Tool (SWAT) is applied worldwide for modeling basin-scale processes. Its latest version (SWAT+) adds new capabilities to the tool, and collectively with increasing computational power and availability of public datasets expands model complexity as well as provides pathways for serious errors in the model setup process. These models are used to run scenarios to support decision-making processes, hence undetected faults can have a substantial socio-economic and environmental impact. We propose a 5-step SWAT+ model setup verification workflow assessing the soundness of processes related to weather, water balance, management, plant growth, point source and tile drain flows. We developed an R package, called SWATdoctR, which guides the user through the model setup verification process, allowing the identification of typical, but repeatedly overlooked, issues. The workflow and the functionality of the tool is demonstrated in 4 SWAT+ setups in different catchments, at various stages of model setup.
      24WOS© IF 4.9WOS© AIF 6.65Scopus© SNIP 1.558
  • research article
    Severini, Edoardo
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    Magri, Monia
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    Soana, Elisa
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    Faggioli, Marco
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    Celico, Fulvio
    Agricultural water management
    In the last decades, the intensification of agricultural practices has deeply altered nitrogen (N) and water cycles. Climate change and drought events are expected to further increase the human impacts on the hydrological and biogeochemical cycles, and these impacts are gaining the attention of the scientific community. Here we show how the Chiese River watershed (Lombardy Region, Italy) represents an interesting opportunity to analyse the effects of traditional irrigation practices on N contamination in the context of water scarcity. During summer, flood irrigation is mostly sustained by groundwater withdrawal. Additional water withdrawals from the river contribute to the dry out of the Chiese River. The use of wells for irrigation over permeable and fertilized soils and the percolation of nitrate (NO3-) from the vadose zone to groundwater result in the accumulation of NO3- in groundwater and limited N losses via denitrification due to dominant oxic conditions. These practices contrast other measures targeting the reduction of N excess over arable land. In the Chiese River watershed, the N surplus from Soil System Budget calculations decreased by 43% since the early 2000 s but NO3- concentration in groundwater remained high and stable (up to 98.0 mg NO3- L−1). The dried-out Chiese River gains groundwater and NO3- concentration at the river mouth approaches 32.2 mg NO3- L−1. Our results suggest how the mismanagement of the watershed (overabundant fertilization and flood irrigation using groundwater) increases the N concentration both in the river and groundwater, leading to the violation of both Nitrate and Water Framework directives. We anticipate our assay to be a starting point for the conversion of the northern Po Plain to more efficient irrigation and fertilization practices to contrast severe droughts driven by climate change like the one who struck the Po Plain in summer 2022.
      7WOS© IF 6.7WOS© AIF 3.9Scopus© SNIP 2.018
  • research article
    Lorre, Elise
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    Riboni, Nicolò
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    Bianchi, Federica
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    Orlandini, Serena
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    Furlanetto, Sandra
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    Careri, Maria
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    Talanta open
    Phthalate esters (PAEs) are the most widely used plasticizers worldwide and are considered as ubiquitous environmental contaminants. Due to both their ubiquity and potential health and environmental risks, their determination is a matter of worldwide concern. In the present study, an efficient method based on ultrasonic-assisted solvent extraction followed by gas chromatography-mass spectrometry is proposed for the simultaneous determination of PAEs and di(2-ethylhexyl) adipate in estuarine sediments and shells. Method optimization was successfully carried out according to Quality by Design principles. Shaking time, ultrasonic time, extractant volume, and solvent type were selected as Critical Method Parameters. Validation proved method reliability for the determination of the investigated analytes, achieving detection limits in the 0.1–0.7 ng g–1 and 0.1–0.5 ng g–1 range for sediments and shells, respectively. A good precision was obtained with RSD < 20% and trueness (recovery) in the 73(±7)–120(±10)% and 70(±10)–111(±3)% range, for sediments and shells, respectively. Finally, the method was applied to analyze sediment samples and mollusc shells, collected from the Curonian Lagoon (Southeast Baltic Sea). Di(2-ethylhexyl) phthalate was present in all the analyzed samples, thus pointing out its ubiquity in estuarine environment. PAEs were also found in shell debris or living mussels, highlighting them as a hotspot of organic contaminants, especially in transitional environments, where accumulation of organic rich deposits is limited.
      8Scopus© SNIP 1.128
  • research article
    Jang, Hayoung
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    Mujeeb-Ahmed, M.P.
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    Wang, Haibin
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    Park, Chybyung
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    Hwang, Insik
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    Jeong, Byongug
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    Zhou, Peilin
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    Ocean engineering
    The concept and design of ammonia as a marine fuel are still in the embryonic stage which requires an in-depth investigation of its applicability in terms of its safety and potential risks, both in the design and operational phases of a ship's lifecycle. The paper examines and compares the state-of-the-art safety regulations, rules, standards and guidelines relevant to ammonia-fuelled ships available in various classification societies reports and international regulations such as the IGF codes and summarises their gaps and limitations. The paper critically analyses three major hazards namely toxicity, chemical corrosion, fire and explosion and their potential impact on the human, environment and ship in the event of ammonia leakage. Various hazardous areas considered include ammonia leakage at the bunkering station, fuel preparation room, engine room and storage room and its impact on the ship's general arrangement. In addition, this study reviews and discusses various qualitative and quantitative risk assessment methods employed in ships using low-flashpoint fuels and their relevance and potential suitability for ships powered by ammonia. The paper concludes with important findings and recommendations to aid designers, operators, safety experts, and policymakers in the further development of safety within the framework of risk assessment and management. Overall, this study provides valuable insights into the safety considerations of using ammonia as a marine fuel and highlights the need for further research and development in this area.
      5WOS© IF 5WOS© AIF 3.775Scopus© SNIP 2.112
  • research article; ;
    Journal for nature conservation
    Moult, the process of replacing old feathers with new, is a critical event in the annual cycle of all bird species. In the Curonian Lagoon, situated in the south-eastern Baltic Sea, recreational activities and shipping lanes occur in close proximity to the staging areas of waterfowl. Knowledge on the habitat use of these birds however is scant. In this study, we combined visual observations, satellite telemetry and the distribution of macrophytes to study habitat use by moulting herbivorous mute swans (Cygnus olor) and analysed how the localities of the swans depended on the distribution of macrophyte habitats and anthropogenic activities. Our data highlighted the most important swan staging areas within the Lithuanian part of the Curonian Lagoon, this specifically being mostly shallow areas (<1-metre depth) with diverse and high-density coverage of submerged vegetation dominated by charophytes and pondweeds. The submerged macrophyte habitats in water depths of 1–2 m and stands of clasping-leaf pondweeds were considered less important for swans. Our results showed that mute swans exploited only half the most suitable habitat areas for feeding. Based on indirect assessment of the relationship between the abundance of swans and disturbance by kitesurfing and boating, we discuss possible impacts on their moulting grounds. Knowledge on both selection of moulting grounds and habitat use by waterbirds is necessary for effective management and biodiversity conservation.
      3WOS© IF 2WOS© AIF 3.8Scopus© SNIP 0.838
  • research article
    O'Shea, Ryan E.
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    Nima Pahlevan
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    Brandon Smith
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    Boss, Emmanuel
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    Daniela Gurlin
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    Krista Alikas
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    Kersti Kangro
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    Kudela, Raphael M.
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    Remote sensing of environment
    The simultaneous remote estimation of biogeochemical parameters (BPs) and inherent optical properties (IOPs) from hyperspectral satellite imagery of globally distributed optically distinct inland and coastal waters is a complex, unsolved, non-unique inverse problem. To tackle this problem, we leverage a machine-learning model termed Mixture Density Networks (MDNs). MDNs outperform operational algorithms by calculating the covariance between the simultaneously estimated products. We train the MDNs on a large (N = 8237) dataset of co-aligned, in situ measured, hyperspectral remote sensing reflectance (Rrs), BPs, and absorbing IOPs from globally representative optically distinct inland and coastal waters. The estimated IOPs include absorption due to phytoplankton (aph), chromophoric dissolved organic matter (acdom), and non-algal particles (anap). The estimated BPs include chlorophyll-a, total suspended solids, and phycocyanin (PC). MDNs dramatically reduce uncertainty in the retrievals, relative to operational algorithms, when using a 50/50 dataset split, where the MDNs are trained on a randomly selected half of the in situ dataset and validated on the other half. Our model is shown to have higher, or equivalent, generalization performance than the calculated operational algorithms available for all BPs and IOPs (except PC) via a leave-one-out cross-validation assessment. The MDNs are sensitive to uncertainties in the hyperspectral satellite Rrs, resulting from instrument noise and atmospheric correction; there is a difference of ∼37.4–62.8% (using median symmetric accuracy) between the MDNs' estimates derived from co-located satellite-derived Rrs and in situ Rrs. Of the IOPs, acdom and anap are less sensitive to uncertainties in hyperspectral satellite imagery relative to aph, with remote estimates of aph exhibiting incorrect spectral shape and magnitude relative to in situ measured IOPs. Despite the uncertainties in satellite derived Rrs, the spatial distributions of BPs and IOPs in MDN-derived product maps of Lake Erie and the Curonian Lagoon, based on imagery taken with the Hyperspectral Imager for the Coastal Ocean (HICO) and PRecursore IperSpettrale della Missione Applicativa (PRISMA), are confirmed via co-aligned in situ measurements and agree with the literature's understanding of these well-studied regions. The consistency and accuracy of the model on HICO and PRISMA imagery, despite radiometric uncertainties, demonstrate its applicability to future hyperspectral missions, such as the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, where the simultaneous estimation model will serve as a key part of phytoplankton community composition analysis.
      1WOS© IF 13.5WOS© AIF 5.833Scopus© SNIP 3.527
  • research article;
    White, Michael
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    Arnold, Jeffrey
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    Bieger, Katrin
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    Allen, Peter
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    Gao, Jungang
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    Gambone, Marilyn
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    Meki, Manyowa
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    Kiniry, James
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    Gassman, Philip W.
    Agricultural systems
    CONTEXT: Despite a steady increase in staple crop yields over the past ten years, current agricultural production must escalate even more to keep pace with the expected world population growth, which in turn will require improved agricultural methods that are adapted to many environmental pressures. Comprehensive models that can simulate crop production systems and the impact of management and conservation practices on natural resources and the environment, including water quality at large scale present important contributions to this challenge. OBJECTIVE: To this end we developed the National Agroecosystem Model (NAM): a comprehensive model that uses the updated Soil and Water Assessment Tool (SWAT+) to accurately simulate staple crop yields across the contiguous United States (CONUS), with an initial focus on Corn (Zea mays L.) and Soybean (Glycine max L. Merr.) yields. METHODS: Available open-access data was used to setup this high-resolution modeling system, where every 8- digit hydrologic unit (HUC8) is represented as an individual SWAT+ simulation. A total of 2201 HUC8 simulations across the CONUS were interconnected from upstream to downstream to make the NAM. Field boundary data was used to setup the NAM in such a way that every identified cultivated field is modeled as a unique Hydrologic Response Unit (HRU). Simulated corn and soybean yield from over 2.5 million field-type HRUs were compared to reported average annual corn and soybean yields for the respective area for the 2015–2020 period. RESULTS AND CONCLUSIONS: Results show a good agreement between simulated and reported yields (R2 = 0.90 for corn and R2 = 0.70 for soybeans), with a very good model performance in the high corn and soybean pro- duction region of the US Corn Belt (Relative Error < ±5%). SIGNIFICANCE: Apart from assessing the capability of the updated SWAT+ model, we also demonstrate the new crop yield calibration module embedded in SWAT+, highlight changes to the plant growth module, and model parameterization. Results of an analysis of possible crop production differences for corn and soybeans in irri- gated, tiled, and non-irrigated-non-tiled fields are also discussed. The versatility of the NAM provides the pos- sibility to analyze information on impacts of changing conservation practices and enables identification of conservation gains and remaining conservation needs at the national scale.
    WOS© IF 6.6WOS© AIF 3.8Scopus© SNIP 1.965
  • The energy efficiency of port container terminal equipment and the reduction of CO2 emissions are among one of the biggest challenges facing every seaport in the world. The article presents the modeling of the container transportation process in a terminal from the quay crane to the stack using battery-powered Automated Guided Vehicle (AGV) to estimate the energy consumption parameters. An AGV speed control algorithm based on Deep Reinforcement Learning (DRL) is proposed to optimize the energy consumption of container transportation. The results obtained and compared with real transportation measurements showed that the proposed DRL-based approach dynamically changing the driving speed of the AGV reduces energy consumption by 4.6%. The obtained results of the research provide the prerequisites for further research in order to find optimal strategies for autonomous vehicle movement including context awareness and information sharing with other vehicles in the terminal.
      68  1Scopus© Citations 1WOS© IF 6.8WOS© AIF 3.8Scopus© SNIP 2.006