This is a project that revolves around the technique of data visualization and especially it attempts to discuss the question of how to make “meaningful” and “interesting” usage of the increasingly exposed public data released from the government. I decided on the theme of visualizing the air quality in the city I am living in and its pollution state by building a generative system that takes a dataset as input. This generative visualization system analyses all the data in a CSV file about all the average individual air quality indices in all of Shanghai's districts. After the data is parsed in Processing, all those data entries are fed into a custom visualization algorithm that I wrote which takes an image of a place in Shanghai and turns it into an artistic and generative aesthetics made with particulate matters and particles running on a flow field influenced by those data. More specifically, the dataset is analyzed to affect the properties of particulates, particles, the vector field as well as the process of applying a convolution matrix (Sobel operator) to the input image. Lastly, a PDF book is automatically created after running the program, which includes all of the visualization results generated by the data entries（air quality data indices) on each day of December 2020. All data entries on each date are provided below the corresponding visualization result.