Ships operating on fossil fuel release pollutant emissions into the atmosphere. Released pollutants have a negative effect on the environment and human health, especially in port cities. For this ...reason, it is very important to properly evaluate these emissions so they can be managed. The current and most common methodologies for shipping pollution evaluation are used for whole port areas or larger terminals over a long period of time and are not analyzed in terms of detailed activity, which may lead to underestimations in certain areas. This study aims to evaluate emissions from ships in port by combining ships’ technical, AIS and EMEP data that allow us to evaluate emissions in port, not as a singular area source but enables individual ship emissions evaluation at any given point in time. To achieve this emission calculation, an algorithm was compiled by using EMEP/EEA Tier 3 methodology. The developed method presents a way to evaluate emissions in a detailed manner not only for groups of ships but also for individual ships if that is required. This method also lets us analyze shipping emissions’ intensity throughout all port territory and identify the most excessive pollution sources. However, the method adds additional work for researchers because of the huge data arrays required for complex calculations.
In the last decade the reduction of carbon dioxide emissions in the transport sector, including the marine sector, has become the direction of its strategic development. Increased air pollution in ...the air is one of the main reasons for premature deaths around the globe. It was determined that while many methods provide adequate information about pollution levels, improvements could be made to avoid major errors. The traditional methods are either expensive or require a lot of data and human resources to correctly evaluate those data arrays. To avoid these problems, artificial neural networks (ANN) and other machine learning methods are widely used nowadays. Many ANN models for ship pollution evaluation in ports either included the whole port area or went even further and included cities near port areas. These studies show that ANNs can be effectively used to evaluate air pollution in a wide area. However, there is a lack of research on ANN usage for individual ship pollution or ship plume evaluation. This study attempts to fill this gap by developing an ANN model to evaluate an individual ship’s plumes by combining several data sources such as AIS data, meteorological data, and measured the ship’s plume pollutants concentration. Results show good correlation; however, additional limitations have to be overcome regarding data filtering and the overall accuracy of the model.
Straipsnyje analizuojama vandenilio prisotinto vandens nauda organizmui bei panaudojimo galimybės įvairių ligų simptomams mažinti. Analizei atlikti buvo peržiūrėta mokslinė literatūra apie vandenilio ...prisotintą vandenį, jo panaudojimo galimybes bei naudą organizmui. Kasdienis vandeniliu papildyto vandens naudojimas mažina oksidacinį stresą, stabdo ligų vystymąsi bei palengvina simptomus, stabdo ląstelių senėjimo procesus, turi teigiamą poveikį odos išvaizdai: sumažina UV odos pažeidimus, padidina I tipo kolageno sintezę odoje. Rezultatų analizė patvirtino, kad vandenilio prisotintas vanduo saugus sveikiems asmenims, o sergantiems kokiomis nors ligomis prieš vartojant tokį vandenį rekomenduojama pasitarti su gydytoju.
This publication deals with the evaluation of forecasting the emissions of ships operating in the port through neural networks. Analyzed particulate matter (PM1, PM2.5, PM10, TSP) emissions from ...ships at various parts of the port. The research is based on usage of AIS system data, the technical database of the ship, the ambient air measurement data and the ambient air pollution measuring data for the use of neural network training. Results showed that trained neuronal networks could be sufficiently accurate (the correlation coefficient amounted from 0.82 to 0.92 depending on pollutant) to use for ship operating in the port emissions evaluation.
Didėjanti beglitiminių duonos gaminių paklausa verčia ieškoti naujų gamybos būdų. Norint ją išspręsti, ieškoma naujų strategijų, kaip pašalinti kenksmingą glitimą iš kviečių, rugių bei miežių ir ...pagaminti subalansuotus produktus, turinčius geras juslines savybes. Šiame straipsnyje įvertintas tam tikrų augalų sulčių ir ekstraktų efektyvumas, naudojant jas kaip glitimo imunogeniškumo sumažinimo priemones. Tirtas glitimo kiekis kviečių sėlenose ir kviečių krakmole, prieš ir po fermentacijos su natūraliais augalų ekstraktais. Glitimo kiekis kviečių krakmole po fermentacijos su kivių, papajų ir ananasų sultimis gautas 15–18 mg/kg, po apdorojimo juodgrūdės ekstraktu – 28 mg/kg. Šios priemonės glitimo kiekį sėlenose sumažino iki 530–3500 mg/kg. Taigi augalų ekstraktai pašalino kviečių krakmolo imunogeniškumą ir sumažino imunoreaktyvių peptidų kiekį kviečių perdirbimo šalutinėse frakcijose, kuriose pradinis glitimo kiekis yra didesnis, tačiau nepasiekė saugios ribos, leistinos beglitiminių produktų gamyboje.
