Autor: Krzemień, A. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Forecast of methane emission from closed underground coal mines exploited by longwall mining - a case study of Anna coal mine
Autorzy:: Duda, A.
Krzemień, A.
Powiązania:: https://bibliotekanauki.pl/articles/91954.pdf
Data publikacji:: 2018
Wydawca:: Główny Instytut Górnictwa
Tematy:: gas hazard
coal mine methane
greenhouse gas
coal mine closure
methane emission forecast
underground coal mine
zagrożenie gazowe
metan kopalniany
gaz cieplarniany
zamknięcie kopalni
prognoza emisji metanu
podziemna kopalnia węgla
Opis:: Closure and post-closure periods in underground coal mines present specific risks that have to be handled with sound management practices in order to achieve sustainability within the mining sector. These risks may negatively affect the environment and result in hazards on the surface caused by phenomena occurring in the rock mass after mining operations. One of the hazards that has to be considered in the process of coal mine closure is gas, which is caused by methane emission after mining operations cease. This paper presents a forecast of methane emissions conducted within the framework of the Research Fund for Coal and Steel “MERIDA” project, using a model that was developed by the National Institute for the Environment and Industrial Hazards (INERIS) from France, and the Central Mining Institute (GIG) in Katowice, from Poland. This model enables the estimation of the volume of methane emitted into longwall goafs from relaxed undermined and overmined coal seams in order to assess in a further step the risk of methane emissions into the atmosphere from closed/sealed underground coal mines. For a critical analysis of the forecasted methane emissions into the longwall goafs, the results obtained with this model were compared with a gas decline curve generated for longwall goafs from closed/sealed underground coal mines in Australia, where long term full range data was available. The results of the analysis allowed the forecasted emissions and, thus, the accuracy of the model to be validated. The forecast was developed in the “Anna” coal mine, property of the PGG Company, which is located in the southern part of the Upper Silesian region in the south of Poland, near the border with the Czech Republic, and that is undergoing a closure process.
Źródło:: Journal of Sustainable Mining; 2018, 17, 4; 184-194
2300-1364
2300-3960
Pojawia się w:: Journal of Sustainable Mining
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Risk assessment of a post-combustion and amine-based CO2 Capture Ready Process
Autorzy:: Krzemień, A.
Więckol-Ryk, A.
Duda, A.
Koteras, A.
Powiązania:: https://bibliotekanauki.pl/articles/92044.pdf
Data publikacji:: 2013
Wydawca:: Główny Instytut Górnictwa
Tematy:: risk analysis
post-combustion
HAZOP
amine
analiza ryzyka
spalanie wtórne
amina
Opis:: CO2 Capture Ready Process, as a part of Carbon Capture and Storage (CCS) technology, is a response to international political pressure and the priority of the European Commission to reduce anthropogenic CO2 emissions since it is connected with concerns regarding global warming. This is currently considered as an option for lessing CO2 emissions into the atmosphere. Many laboratory experiments, as well as pilot projects, have been carried out using different capture systems, but until now no experience from the one-to-one size operational installation has been gained. The energy industry must meet several challenges associated with the start-up of the new full-scale project. This paper investigates the problems that can occur while linking a new technology like the CO2 Capture Ready Process to a working fossil fuel power plant. A Hazard and Operability study (HAZOP) has been used, as it is a structured and systematic examination of a planned or existing process or operation, in order to identify and evaluate problems that may represent risks to personnel or equipment. A case study of a post-combustion CO2 capture system with an aqueous monoethanolamine as a solvent is presented, as it is the most likely system to be used in Polish power plants. Basic problems in the analysis as well as the parameters that should be considered to determine vulnerabilities of the process were successfully identified. Gaining experience about the installation’s behaviour while connected to the existing equipment of any power plant is critical for future CCS projects.
Źródło:: Journal of Sustainable Mining; 2013, 12, 4; 18-23
2300-1364
2300-3960
Pojawia się w:: Journal of Sustainable Mining
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Forecasting European thermal coal spot prices
Autorzy:: Krzemień, A.
Riesgo Fernandez, P.
Suárez Sánchez, A.
Sánchez Lasheras, F.
Powiązania:: https://bibliotekanauki.pl/articles/92159.pdf
Data publikacji:: 2015
Wydawca:: Główny Instytut Górnictwa
Tematy:: thermal coal
price forecasting
time series analysis
neural network
autoregressive model
węgiel energetyczny
prognoza cen
analiza szeregów czasowych
sieć neuronowa
model autoregresyjny
Opis:: This paper presents a one-year forecast of European thermal coal spot prices by means of time series analysis, using data from IHS McCloskey NW Europe Steam Coal marker (MCIS). The main purpose was to achieve a good fit for the data using a quick and feasible method and to establish the transformations that better suit this marker, together with an affordable way for its validation. Time series models were selected because the data showed an autocorrelation systematic pattern and also because the number of variables that influence European coal prices is very large, so forecasting coal prices as a dependent variable makes necessary to previously forecast the explanatory variables. A second-order Autoregressive process AR(2) was selected based on the autocorrelation and the partial autocorrelation function. In order to determine if the results obtained are a good fit for the data, the possible drivers that move the European thermal coal spot prices were taken into account, establishing a hypothesis in which they were divided into four categories: (1) energy side drivers, that directly relates coal prices with other energy commodities like oil and natural gas; (2) demand side drivers, that relates coal prices both with the Western World economy and with emerging economies like China, in connection with the demand for electricity in these economies; (3) commodity currency drivers, that have an influence for holders of different commodity currencies in countries that export or import coal; and (4) supply side drivers, involving the production costs, transportation, etc. Finally, in order to analyse the time series model performance a Generalized Regression Neural Network (GRNN) was used and its performance compared against the whole AR(2) process. Empirical results obtained confirmed that there is no statistically significant difference between both methods. The GRNN analysis also allowed pointing out the main drivers that move the European Thermal Coal Spot prices: crude oil, USD/CNY change and supply side drivers.
Źródło:: Journal of Sustainable Mining; 2015, 14, 4; 203-210
2300-1364
2300-3960
Pojawia się w:: Journal of Sustainable Mining
Dostawca treści:: Biblioteka Nauki

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