Skip to main content

Earth and Environmental Sciences - Fall 2023 Junior

Course # EAES 3052

6 Credits

Course Description

Environmental governance refers to how and why societies and governments manage the relationship between human beings and the natural world. To study environmental governance is to study the rationales, rhetoric and structures of environmental management systems, and to compare these systems to understand why certain environmental problems are managed as they are, what approaches to environmental management are more (or less) successful, and for whom and in what ways they are (or are not) successful. This course seeks to provide tools for describing, discussing and analyzing the issues that underpin environmental management problems.

Learning Outcomes

Upon completion of the course, the students should be able to:

  • Apply key concepts and theories of institutional analysis in relation to environmental issues.
  • Evaluate the effectiveness of four major institutional forms (state, market, civil society, and global governance bodies) in addressing environmental problems.
  • Analyze a particular environmental management problem through the lens of an applicable governance model in writing.

Course Assignments and Grading

Item

Weight

Participation

10%

Reading posts

60%

Essay

30%

Course # EAES 3063

6 Credits

Course Description

Introduction to Geological Materials and Resources introduces the physical and chemical properties and characteristics of minerals, rocks and sediments, including the techniques of measuring or determining their values in the lab and in-situ. The relationships between rock types and plate tectonics, and the origins and characteristics of geological resources are discussed. Students will complete laboratory and/or field-based studies as part of this course.

Course Learning Outcomes

At the end of this course the students will be able to:

  • Identify hand specimens of common rock forming minerals and rock types, both in the laboratory and in the field.
  • Relate mineral properties to composition, atomic structure, bonding, and the occurrence of those minerals in different rock types.
  • Describe the processes of formation of common rock types, and use their textural, chemical and mineralogical features to classify them.
  • Predict where certain rock types have formed at different periods of geological time and where they are forming today, using plate tectonics through time as a framework.
  • Apply knowledge of rock forming processes to interpret the geological history of an area based on samples and geological maps, with a particular focus on the local region.
  • Relate important economic minerals to their mineral deposit types, geological setting and deposit formation processes.

Course Assessment and Grading

Item

Weight

In class quizzes – 6 quizzes.

 

12%

Labs. - 8 Labs.

 

16%

Field trip attendance and report – 1 day filed trip (9 hours)

 

8%

In class participation / activities

 

6%

Homework Assignments – 6 home works

12%

Project – The topic will be given during the lectures. 

16%

Final exam

30%

Course # EAES 4045

6 Credits

Course Description

Welcome to Sedimentary Geology and Stratigraphy. This course covers one of the most widespread types of rocks on the Earth’s surface – sedimentary rocks. It includes classification of different types of sedimentary rocks, their composition, their structures and textures, sediment production, transport and deposition processes, sedimentary environments and systems, and stratigraphic patterns. The goal of this course is to provide students with theoretical and practical knowledge to distinguish sedimentary rocks in the field, to observe and document the lithological composition of sedimentary rocks, their macroscopic and microscopic textures and structures, and to interpret the origin of sedimentary rocks based on facial analysis of sedimentary deposits.

Course learning Outcomes

Upon the completion of the course, students will be able to:

  • Document sedimentary rocks, their structure, texture and composition in field.
  • Acquire and interpret data from sedimentary deposits to recreate the mechanisms responsible for their formation and evolution.
  • Collect or use existing data at many scales (outcrop to grain) to construct and evaluate a hypothesis about the type and spatial distribution of sedimentary environments or facies.
  • Interpret changes in a depositional environment across time (stratigraphic change) at many geographical and temporal scales, using data from sedimentary rocks and successions.
  • Correlate between different sequences of sedimentary rocks across space and reconstruct sedimentary basins of the geological past and their environments

Course Assignments and Grading

Item 

Weight

Attendance 

10% 

Practical activities (labs + short fieldtrips) 

45% 

Mid-term Exam (quiz) 

15% 

Final Exam (quiz) 

30% 

Course # DMNS 2035

6 Credits

Course Description

This is an introduction to statistics for economics students. This course will cover elementary probability including introducing random variables, and discrete and continuous probability distributions so that students can use the language of probability in statistics. The second part of the course will cover inferential statistics wherein students will learn how to conclude a population based on a random sample. No prior preparation in probability and statistics is required, but familiarity with basic algebra and calculus is assumed.

Course learning Outcomes

Upon the completion of the course, students will be able to:

  • Apply a variety of methods for explaining, summarizing, and presenting data and interpreting results clearly using appropriate diagrams, titles, and labels when required.
  • Summarize the ideas of randomness and variability and the way in which these link to probability theory to allow the systematic and logical collection of statistical techniques of great practical importance in many applied areas.
  • Perform inference to test the significance of common measures such as means and proportions.
  • Use simple linear regression and correlation analysis and know when it is appropriate to do so.

Course Assignments and Grading

Item

Weight

Homework

25 %

Attendance and participation in discussions

5 %

Two quizzes

10 %

Midterm exam

30 %

Final exam

30 %

Course # EAES 4751E

6 Credits

Course Description

Programming in Python is an introductory course that covers programming techniques and tools to manipulate, manage, and analyze relevant data. The course focuses on the Python programming language that students will use to solve statistical analysis and GIS problems, apply Machine Learning and Deep Learning techniques, and create a website using Django framework. The tasks will be accomplished by identifying and using existing Python packages as well as appropriate open-source software extensions. The course introduces basic to advanced statistical functions, data visualization, and data manipulation techniques. The relevant functions in data science are explained. The main goal of this course is to give students an understanding of the breadth of different programming applications. In particular, students will be taught how to design and write effective code using Python to perform routine and specialized data manipulation, management, statistical analysis, GIS analysis, and web application development tasks.

Course learning Outcomes

Upon the completion of the course, students will be able to:

  • Explain the theoretical concepts of different data types
  • Conceptualize and create loops and if/else statements in Python
  • Create specialized functions in Python to handle results
  • Manipulate data for descriptive statistical analysis in Python
  • Use Django framework for development of different types of websites, in particular, a highly customizable app, such as an internet magazine website
  • Use special packages, such as panda, to create graphs and convert plain text to formatted text.
  • Using the packages NumPy, Matplotlib, Pandas and Skikit-Learn for various mathematical calculations, data manipulation, graphing and creating machine learning algorithms.

Course Assignments and Grading

Item

Weight 

6 Home Assignments 

60% 

Class attendance and participation 

10% 

Final Project 

30% 

Course # MDIA 4083E

6 Credits

Course Description

This course increases students’ knowledge and skills in using communication to advance different environmental discourses by connecting the local with the global. Students study a range of visual and written texts to learn how environmental communication is used by different actors in society to achieve certain outcomes. The role of communication is studied at the intersections of other key issues such as biodiversity, sustainable development, and climate change. Through the evaluation and creation of a range of texts students gain an understanding of how various contexts and media shape environmental communication discourses in the public sphere. Using holistic and systems thinking students conduct research, identify target audience and design effective messages that place community concerns at the centre.

Course learning Outcomes

Upon the completion of the course, students will be able to:

  • Examine the ways in which different political, cultural, economic and geographical contexts shape environmental communication discourses in the public sphere.
  • Evaluate a range of texts and assess their effectiveness on the intended audience.
  • Examine how visual texts act as cultural prism that shape our understanding of nature.
  • Discuss the role of media in reporting key environmental issues in different societies while connecting the local with the global.
  • Design communication responses to engage a variety of audiences about environmental issues.

Course Assignments and Grading

Item

Weight 

Seminar and Synoptic Paper 

Output:  Presentation and written 800 words +/- 10%  

10% 

Content Analysis of environmental news reports  

Output: Essay of 1500 words +/-10% 

30% 

Participatory media content 

Output:  5 minute video or photo story  

30% 

 

Environmental communication campaign plan (group activity) 

Output:  Campaign report:  2000 words +/- 10% (collaborative).  

30%