Learning outcome

A candidate who has passed the course will have a learning outcome in the form of acquired knowledge, skills, and general competence, as described below.

Knowledge

The candidate:

• can identify and characterize main gas pollutants from mobile and stationary sources
• has advanced knowledge about the environmental effects of gas pollutant emissions
• understands the principles of the main methods used to reduce or avoid gas pollution
• can identify heat integration potentials in a given thermal process
• understands the principles of energy optimization in general, and pinch technology in particular

Skills

The candidate:

• can apply methods, procedures and equations in relevant emission-related calculations
• is able to analyse a given pollution problem and suggest appropriate options to solve or reduce the emission problem
• can apply systematic methods of calculating minimum energy demand in a heat exchanger network
• can establish an optimum heat exchanger network

General competence

The candidate:

• is able to communicate major aspects of a given pollution problem through report writing

Course Description

• Classification of gas pollutants
• International agreements and legislation on gas pollutants
• Sources, characteristics and environmental impacts of selected gas pollutants (dust, CO₂, NO_x, N₂O, SO_x, H₂S, HCl and other chlorine compounds, HF and other fluorine compounds, CO, VOC/TOC, tar, soot, dioxins/furanes, other organic compounds, heavy metals)
• Emission measurements (flow, velocity, temperature, pressure, gas concentrations, isokinetic sampling of dust)
• Purification methods for particles (settlers, cyclones, wet scrubbers, electrostatic precipitators, bag filters)
• Purification methods for gases (absorption with or without regeneration, adsorption with or without regeneration, catalytic or non-catalytic chemical conversion, membrane separation)
• Heat recovery and design of heat exchanger networks (pinch technology; composite curves; heat cascades; MER networks; split streams)
• Network optimization; heat pumps and power production in energy optimization
• Integration of distillation columns
• Economic trade-offs in energy optimization (investment versus operating cost)
• Retrofit in energy optimization
• Introduction to Hysys (PC software)
• Integration of CO₂ removal
• Plant visit

Assessment Methods

The final test counts 60 %; the mid-term test counts 25 %; the assignment counts 15 %. Grades A-F are used. To pass the course, the final test must be passed.

The final test and the mid-term test are used to assess knowledge and skills. The assignment is used to assess knowledge, skills and general competence.

Minor adjustments may occur during the academic year, subject to the decision of the Dean