Air quality data analysis and interpretation
Project Description

Regional air pollution is a critical challenge to the whole human society, and impact profoundly on economy and lives of human beings. The project is aiming to understands how the air quality varies on both regional and global scales and how our lives are thereby affected based on data analysis and interpretation.

Gu Dasa
Course type
Applicant's Roles

The applicant is expected to: 1) generate and organize air quality data from laboratory, outfield, airborne and satellite observations; 2) analyze the spatial and temporal variations of major air pollutants; 3) interpret the data with statistical analysis and numerical modeling tools.

Students with background or interest in environment, chemistry, mathematics, and physics are welcome to apply.

Applicant's Learning Objectives

The applicants is expected to learn:
1) compositions and characteristics of major air pollutants;
2) methods and tools to generate data from air quality observations;
3) methods and tools of statistical data analysis and interpretation.

Complexity of the project