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School of Engineering
- Undergraduate major in Mechanical Engineering
- Undergraduate major in Systems and Control Engineering
- Undergraduate major in Electrical and Electronic Engineering
- Undergraduate major in Information and Communications Engineering
- Undergraduate major in Industrial Engineering and Economics
- Common courses
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
- School of Environment and Society
- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
-
School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Graduate major in Industrial Engineering and Economics
- Instructor(s)
- Kanamori Yuko Takakura Junya Hirayama Tomoki Hiruta Yuki
- Class Format
- Lecture (Livestream)
- Media-enhanced courses
- Day/Period(Room No.)
- Mon1-2() Thr1-2()
- Group
- -
- Course number
- IEE.B530
- Credits
- 2
- Academic year
- 2022
- Offered quarter
- 2Q
- Syllabus updated
- 2022/3/16
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
This cource focuses on modeling on global environmental issue such as global warming and economic growth. Topics include IAM (Integrated Assessment Model), its component models such as bottom-up model, top-down model, population projection, demand estimation), and future scenario. The course enables students to understand the characteristics of models through lectures. The models introduced in this cource have been used in discussion such as future CO2 emission target and corbon tax. Students will be interested in global environmental issue and think about the issue by themselves after this cource. Lectures will be given by class teacher (Kanamori) and three external lecturers.
Student learning outcomes
By the end of this course, students will be able to:
1) Understand characteristics of the models which are used in global environemental issues.
2) Think and propose about appropriate model framework.
3) Have a appropriate presentation about 2).
Keywords
Global environmental issue, economic grouwth, model analysis, IAM (Integrated Assessment Model)
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | ✔ Communication skills | ✔ Critical thinking skills | Practical and/or problem-solving skills |
Class flow
Class 1 - Class 14: Each topics are explained.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Intoroduction of IAM | Understand the cource aims |
| Class 2 | Introduction of future scenarios | Understand future scenarios |
| Class 3 | Introduction of AIM/ExSS | Understand AIM/ExSS (Accounting model) |
| Class 4 | Introduction of models in household sector (1) | Understand various models in household sector |
| Class 5 | Introduction of models in household sector (2) | Understand various models in household sector |
| Class 6 | Introduction of AIM/Enduse | Understand AIM/Enduse (bottom-up model) |
| Class 7 | Introduction of AIM/CGE | Understand AIM/CGE structure |
| Class 8 | Use of AIM/Enduse | Understand how AIM / Enduse was used in environmental policy |
| Class 9 | Impact assessment model 1 (Introduction of various impact assessment model） | Understand various impact assessment model |
| Class 10 | Impact assessment 2 (Example of impact assessment) | the latest findings of impact assessment on climate change issues |
| Class 11 | Introduction of population and household projection | Understand popuplation and household projection |
| Class 12 | Power demand analysis at regional-scale | Understand power demand analysis at regional-scale |
| Class 13 | Machine learning analysis in the energy field | Understand the advantages of the machine learning algorithms in the energy analysis |
| Class 14 | Setting challenge to solve global environmental issue and collection of data for modeling | Understand how to collect data for modeling |
Out-of-Class Study Time (Preparation and Review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to course material.
Textbook(s)
Cource matereals are distributed in each class.
Reference books, course materials, etc.
Reference books are shown in each class.
Assessment criteria and methods
Main report (50%)
Evaluation by 3 external lecturers (mainly mini-report) (total 50%)
Related courses
- IEE.B331 ： Applied Microeconomics
- IEE.B531 ： Frontier of Environmental Economics and Policy Studies
- IEE.B333 ： Environmental Economics
Prerequisites (i.e., required knowledge, skills, courses, etc.)
There is no prerequisite for this course.
