Conference proceedings

Displaying 1 - 10 of 15 in CEST2023 (remove filter), Environmental data analysis and modelling (remove filter)

CEST Proceedings are published under the ISSN 2944-9820.

Fair and Efficient Allocation of EU Emission Allowances

(Corresponding) Dimos S., Fotakis D., Mathioudaki A., Papadopoulos K.

Topic:

Environmental data analysis and modelling

Under the European Union Emission Trading System (EU ETS), the European Union issues and allocates emission allowances (EUA) to the member states to cap the total volume of Greenhouse Gas (GHG) emissions. Since the first years of operation, the EU ETS allocation procedure has undergone multiple...Read more

Keywords:

EU ETS, Cap-and-Trade, Emission Trading System, Allowance Allocation, Individual Fairness

DOI:

https://doi.org/10.30955/gnc2023.00077

Conference:

CEST2023

Paper ID:

cest2023_00077

Grey Forecasting Models Optimized by Firefly Algorithm for Natural Gas Consumption Prediction in Turkey

Ozcan T., (Corresponding) Konyalioglu A., Beldek B.

Topic:

Environmental data analysis and modelling

Natural Gas is assumed to have a vital role as an energy source in all countries, serving as the primary fuel for industries, homes, and various sectors. The forecasting of natural gas consumption is very crucial for efficient energy management and the formulation of appropriate policies related to...Read more

Keywords:

Natural gas consumption; Grey forecasting; Parameter optimization; Firefly algorithm

DOI:

https://doi.org/10.30955/gnc2023.00117

Conference:

CEST2023

Paper ID:

cest2023_00117

A Machine Learning Approach for the prediction of solid fuels consumption in Turkey

Celik N., (Corresponding) Konyalioglu A.

Topic:

Environmental data analysis and modelling

Solid fuels are very crucial energy sources as most of industries use them for obtaining heat, electricity and light. Furthermore, since solid fuels are scarce sources in Turkey, it is very important to forecast the consumption in order to effectively manage the energy policies and to conduct an...Read more

Keywords:

Solid Fuels, Environmental Data Analysis, Machine Learning

DOI:

https://doi.org/10.30955/gnc2023.00118

Conference:

CEST2023

Paper ID:

cest2023_00118

Rule-based Quantification and Mapping of Ecosystem Services Across Three Spatial Scales by Example of Germany

Schlutow A., (Corresponding) Schröder W., Nickel S., Jenssen M.

Topic:

Environmental data analysis and modelling

The state of ecosystems influences their services for humans. Therefore, the European Union aims to assess and map ecosystem conditions and ecosystem services at the level of the Union and the Member States, in order to implement maintenance or protection measures, if necessary. This paper aims at...Read more

Keywords:

Ecosystem condition; ecosystem integrity; EU Biodiversity Strategy; Geographic Information System.

DOI:

https://doi.org/10.30955/gnc2023.00130

Conference:

CEST2023

Paper ID:

cest2023_00130

Capability of high resolution satellite images to characterize urban surfaces: spectra comparison and correlation with in field/lab measurements

(Corresponding) Despini F., Costanzini S., Parmeggiani D., Ferrari C., Teggi S., Muscio A., Silvestri M., Rabuffi F., (Corresponding) Musacchio M.

Topic:

Environmental data analysis and modelling

Environmental remote sensing is an increasingly useful tool for the study of large areas thanks to new sensors with high spatial resolution. These sensors could be able to identify and analyse several urban surfaces, like roofs and pavements. Thus they could be used to study urban areas for several...Read more

Keywords:

Remote sensing, environment, UHI, urban surfaces

DOI:

https://doi.org/10.30955/gnc2023.00133

Conference:

CEST2023

Paper ID:

cest2023_00133

A Deep Learning Model, interpreted with an XAI technique, to simulate and optimize the remediation of oil-drilling cuttings in bubble flow reactors

Kalari K., Christodoulis K., Bali N., Theodoropoulou M., (Corresponding) Tsakiroglou C.

Topic:

Environmental data analysis and modelling

A multitask deep neural network (DNN) is developed to simulate the ozonation of oil-drilling cuttings (ODC) and is interpreted through a technique of explainable artificial intelligence (XAI) to provide knowledge about the experimental conditions that will maximize the decontamination of ODC. On a...Read more

Keywords:

Ozonation, Soil Remediation, Bubble Column Reactor, Deep Neural Networks, Multitask Learning, Explainable Artificial Intelligence.

DOI:

https://doi.org/10.30955/gnc2023.00166

Conference:

CEST2023

Paper ID:

cest2023_00166

Predicting Land Cover Map Changes in the Philippines for use in LULC-based Carbon Capture Monitoring using Deep Learning

Camaclang R., Ballesteros F., (Corresponding) Labao A.

Topic:

Environmental data analysis and modelling

In the area of Carbon Capture and Storage (CSS), monitoring plays an important role not only to determine if there is any anomalies in the release of CO2 in the atmosphere, but also to prepare for disasters and to plan better future developments in the industrial sector, transportation sector, real...Read more

Keywords:

Land Use and Land Cover (LULC), Land Cover Prediction, Carbon Capture and Storage, Deep Learning

DOI:

https://doi.org/10.30955/gnc2023.00171

Conference:

CEST2023

Paper ID:

cest2023_00171

Analysis of the Sars-COVID 19 trend: from time series to visibility graphs

(Corresponding) Simone A., Cesaro A., Esposito G.

Topic:

Environmental data analysis and modelling

Sars COVID-19 epidemic continues to represent a relevant and current topic, which is of concern mainly with respect to possible variants. Predictive monitoring can address the need to reduce the risk of spreading the virus, but it needs to rely on non-invasive, as well as effective and inexpensive...Read more

Keywords:

Sars-COVID19, time series analysis, visibility algorithms, graph theory, Wastewater-Based Epidemiology

DOI:

https://doi.org/10.30955/gnc2023.00202

Conference:

CEST2023

Paper ID:

cest2023_00202

UrbEm: a method and tool to refine regional emission inventories for urban atmospheric studies

(Corresponding) Kakouri A., Ramacher M., Kuenen J., Speyer O., Gerasopoulos E., Athanasopoulou E.

Topic:

Environmental data analysis and modelling

As cities are growing in size and complexity, the estimation of air pollution exposure requires detailed spatial representation of air pollution levels. Intra-urban atmospheric studies require up-to-date and credible emission inventories. The Copernicus Atmosphere Monitoring Service (CAMS) provides...Read more

Keywords:

air pollution, emissions, urban air quality, Chemistry Transport Modelling

DOI:

https://doi.org/10.30955/gnc2023.00219

Conference:

CEST2023

Paper ID:

cest2023_00219

Simulating the fate of selected PAHs in Saronikos Gulf, Eastern Mediterranean, using a far-field water-quality model.

(Corresponding) Mazioti A., Kolovoyiannis V., Petalas S., Mamoutos I., Potiris E., Krasakopoulou E., Tragou E., Zervakis V.

Topic:

Environmental data analysis and modelling

The aim of this study is to investigate the distribution of selected Polycyclic Aromatic Hydrocarbons (PAHs) and predict their fate in the marine area of Saronikos Gulf. A three-dimensional model (Delft3D-FLOW) was used to simulate sea circulation and hydrographic variables (salinity, temperature...Read more

Keywords:

PAHs, marine pollution, coastal environmental modelling, Delft3D, Saronikos Gulf

DOI:

https://doi.org/10.30955/gnc2023.00221

Conference:

CEST2023

Paper ID:

cest2023_00221