School of Chemical and Environmental Engineering

Now offering two distinct diplomas: Chemical Engineering and Environmental Engineering

# Risk Analysis

1. COURSE INFORMATION:

 School Chemical and Environmental Engineering Course Level Undergraduate Direction Chemical Engineering Course ID ENVE 451 Semester 9th Course Category Elective Course Modules Instruction Hours per Week ECTS Lectures and Tutorials 3 T=2, E=1, L=0 5 Course Type Scientific Area Prerequisites Instruction/Exam Language Greek The course is offered to Erasmus students No Course URL https://www.eclass.tuc.gr/courses/MHPER225/

2. LEARNING OUTCOMES

 Learning Outcomes Upon successful completion of the course, the student will be able to:Recall basic principles of statistics and data analysis and decision makingRecognize decision-making criteria and the concept of risk in project planning and management as well as the concept of cost/benefit analysisuse appropriate software in decision-makingAssess environmental riskManage projects with environmental policy criteriaAnalyse environmental data General Competencies/Skills Review, analyze and synthesize data and information, with the use of necessary technologiesDecision makingWork in teamsDesign and management of environmental engineering works/projects

3. COURSE SYLLABUS

 Elements of probability and statistics, Bayes theorem, Discrete and Continuous Theoretical Probability Distributions, Statistical data analysis, Uncertainty of estimates.Decision trees. Extending the calculation of the cost of pollution by adding the loss of value of a good.Bayesian Decision Making Theory (prior and posterior distributions). Hazard and Bayesian optimal decision.Sensitivity analysis and influence of number of samples on decisions.Use of the loss function in promoting environmental policy. Economic value of information. Repentance and loss of opportunity.Correlation of risk and cost/benefit analysisEnvironmental risk (pollutants and permissible exposure limits - practical applications). Risk analysis of hydrological projects and processes.Risk analysis using spatial analysis.Introduction to Game Theory for water resources management. The integration of data and qualitative information in decision-making.Decision-making criteria (minimax, maximin), applications in economic and environmental subjectsPresentation of Irrigania software for the application of non-fixed-sum game theory (decision-making) in water resources management.

4. INSTRUCTION and LEARNING METHODS - ASSESSMENT

 Lecture Method Direct (face to face) Use of Information and Communication Technology Specialized softwarePower point presentationsE-class support Instruction Organisation Activity Workload per Semester (hours) - Lectures 28 - Tutorials 11 - Projects 51 - Autonomous study 35 Course Total 125 Assessment Method I. Written final examination (50%). - Questions of theoretical knowledge. - Theoretical problems to be resolved.ΙΙ. Autonomous assignments (20%).III. Group assignments (30%).