Stochastic Analysis in Production Process and Ecology Under Uncertainty [electronic resource] /
Bieda, Bogusław.author.
The monograph addresses a problem of stochastic analysis based on the uncertainty assessment by simulation and application of this method in ecology and steel industry under uncertainty. The first chapter defines the Monte Carlo (MC) method and random variables in stochastic models. Chapter two deals with the contamination transport in porous media. Stochastic approach for Municipal Solid Waste transit time contaminants modeling using MC simulation has been worked out. The third chapter describes the risk analysis of the waste to energy facility proposal for Konin city, including the financial aspects. Environmental impact assessment of the ArcelorMittal Steel Power Plant, in Kraków – in the chapter four – is given. Thus, four scenarios of the energy mix production processes were studied. Chapter five contains examples of using ecological Life Cycle Assessment (LCA) – a relatively new method of environmental impact assessment – which help in preparing pro-ecological strategy, and which can lead to reducing the amount of wastes produced in the ArcelorMittal Steel Plant production processes. Moreover, real input and output data of selected processes under uncertainty, mainly used in the LCA technique, have been examined. The last chapter of this monograph contains final summary. The log-normal probability distribution, widely used in risk analysis and environmental management, in order to develop a stochastic analysis of the LCA, as well as uniform distribution for stochastic approach of pollution transport in porous media has been proposed. The distributions employed in this monograph are assembled from site-specific data, data existing in the most current literature, and professional judgment.
Description based upon print version of record.
Includes bibliographical references.
Introduction -- 1. Introduction to Monte Carlo (MC) method. Random variables in stochastic models -- 2. Stochastic model of the diffusion of pollutants in landfill management using Monte Carlo simulation -- 3. The role of risk assessment in investment costs management, based on the example of Waste Treatment (Gasification) Facility in the City of Konin -- 4. Stochastic analysis of the environmental impact of energy production processes, based on the example of ArcelorMittal Poland S.A. Power Plant, Unit in Kraków, Poland -- 5. Stochastic analysis, using Monte Carlo (MC) simulation, of the life cycle management of waste, from an annual perspective, generated by ArcelorMittal Poland S.A. Unit in Kraków, Poland -- 6. Summary.
The monograph addresses a problem of stochastic analysis based on the uncertainty assessment by simulation and application of this method in ecology and steel industry under uncertainty. The first chapter defines the Monte Carlo (MC) method and random variables in stochastic models. Chapter two deals with the contamination transport in porous media. Stochastic approach for Municipal Solid Waste transit time contaminants modeling using MC simulation has been worked out. The third chapter describes the risk analysis of the waste to energy facility proposal for Konin city, including the financial aspects. Environmental impact assessment of the ArcelorMittal Steel Power Plant, in Kraków – in the chapter four – is given. Thus, four scenarios of the energy mix production processes were studied. Chapter five contains examples of using ecological Life Cycle Assessment (LCA) – a relatively new method of environmental impact assessment – which help in preparing pro-ecological strategy, and which can lead to reducing the amount of wastes produced in the ArcelorMittal Steel Plant production processes. Moreover, real input and output data of selected processes under uncertainty, mainly used in the LCA technique, have been examined. The last chapter of this monograph contains final summary. The log-normal probability distribution, widely used in risk analysis and environmental management, in order to develop a stochastic analysis of the LCA, as well as uniform distribution for stochastic approach of pollution transport in porous media has been proposed. The distributions employed in this monograph are assembled from site-specific data, data existing in the most current literature, and professional judgment.
Environmental management.
Statistics .
Energy systems.
Energy policy.
Energy and state.
Ecology .
Mathematical models.
Environmental Management.
Statistics for Life Sciences, Medicine, Health Sciences.
Energy Systems.
Energy Policy, Economics and Management.
Ecology.
Mathematical Modeling and Industrial Mathematics.