Bad Air

This project can help people understand the trends of pollution going on throughout the United States from 1980 to 2020 through visualizations. Through the use of bar charts, pie charts we can see how different pollutants affect areas over time.

The EPA has recorded the data in around 1000+ counties in the US The data can be found here: https://aqs.epa.gov/aqsweb/airdata/download_files.html#Annual.

• Good" AQI is 0 - 50. Air quality is considered satisfactory, and air pollution poses little or no risk.

• "Moderate" AQI is 51 - 100. Air quality is acceptable; however, for some pollutants, there may be a moderate health concern for a very small number of people. For example, people who are unusually sensitive to ozone may experience respiratory symptoms.

• "Unhealthy for Sensitive Groups" AQI is 101 - 150. Although general public is not likely to be affected at this AQI range, people with lung disease, older adults and children are at a greater risk from exposure to ozone, whereas persons with heart and lung disease, older adults and children are at greater risk from the presence of particles in the air.

• "Unhealthy" AQI is 151 - 200. Everyone may begin to experience some adverse health effects, and members of the sensitive groups may experience more serious effects.

• "Very Unhealthy" AQI is 201 - 300. This would trigger a health alert signifying that everyone may experience more serious health effects.

• "Hazardous" AQI greater than 300. This would trigger health warnings of emergency conditions. The entire population is more likely to be affected.

• Max AQI: Ma

• 90th Percentile AQI,

• Median AQI

• Days CO: No. of days when Carbon Monoxide was the major pollutant

• Days NO2: No. of days when NO2 was the major pollutant

• Days Ozone: No. of days when Ozone was the major pollutant

• Days SO2: No. of days when SO2 was the major pollutant

• Days PM2.5 No. of days when Fine particulate matter (PM2.5) was the major air pollutant

• Days PM10 No. of days when Fine particulate matter (PM10) was the major air pollutant

This whole project is developed in HTML/CSS and Javascript. I’ve used d3 D3.js which is a JavaScript library for producing dynamic, interactive data visualisations in web browsers. It makes use of Scalable Vector Graphics, HTML5, and Cascading Style Sheets standards

Data: Using a python script I combined all the csv files into data.csv. For testing purposes I also made other datasets which just had the data for Ohio and Hamilton.

Live website

Code

Structure:

I created a main.js and corresponding different class JS files for all the visualizations. The structure was pretty similar to a normal web project. Separate folder for JS/CSS/Data.