Aims and Fit of Module

This course provides students with an in-depth understanding of environmental health, covering major types of environmental pollution and their effects on human health. Students will learn how environmental health risks are assessed, how pollutants interact with the human body, and how policies and regulations address environmental pollution. The course also develops students' data analysis skills through AI-assisted coding applied to real-world environmental datasets. This course is recommended for students on the ecology and ESG tracks as an introduction to environmental pollution, and for students on the pollution track with a particular interest in environmental health.

Learning outcomes

A. Distinguish between major sources and types of environmental pollution.

B. Critically assess environmental epidemiology research.

C. Examine how pollutants interact with the human body.

D. Evaluate environmental risk assessment and risk management processes.

E. Analyze how environmental health programs are developed, managed, and evaluated.

F. Apply AI-assisted data analysis techniques to process and interpret environmental pollution datasets.

Method of teaching and learning

This module will be delivered through lectures and seminars supplemented with real-world case studies. Lab sessions provide hands-on experience in AI-assisted data analysis using environmental pollution datasets. Students will also visit the Suzhou Ecological and Environmental Agency.