On-Line Data Tools for Student Learning in Environmental Health

On-Line Data Tools for Student Learning in Environmental Health

Today’s blog post is brought to you by Dr. Ben Greenfield. 

In my experience, on-line data tools have been really useful for teaching environmental sciences to university students and adult learners. I also think they could have good application in K-12 settings. By “on-line data tools” I mean free websites that provide public access to any kind of data. 

In this blog post, I introduce and describe two on-line data tools that are easy to access, enable self-directed learning, and demonstrate real problems with potential relevance to everyone. The tools I highlight are especially useful for teaching, because they all have interesting and user-friendly visualization apps built right into them. This enables students to practice finding patterns in data, and can offer the benefits of almost immediate student-directed learning. 

Due to my research and teaching interests, the tools below describe aspects of the environment that can affect people’s health. I live in the US and am more familiar with this country. So these tools report air pollution in the U.S. There will be similarly useful tools in other fields, or based in other parts of the world. My preferred tools don’t just show the environmental data; they go further to compare results to relevant human health benchmarks. This enables students to inquire about the potential impacts of the pollutant or other environmental factor to people in the surrounding community. 

Considering all of the above, here are a couple of my favorite tools. 

  1. Air Data: Quality Data Collected at Outdoor Monitors Across the US

Tool Developer: U.S. Environmental Protection Agency

https://www.epa.gov/outdoor-air-quality-data

This site is an amazing introduction to air pollution patterns and trends, how air pollution is regulated in the U.S., and data visualization in general. It is based on air monitoring data collected by the U.S. EPA and state agencies. These collections are required under the U.S. Clean Air Act. 

When you click the website, you gain access to a wide range of resources, data access portals, and visualization tools. My favorite part and where I would begin is the “Data Viz” section at the bottom of the page. Each of the links in this section is a different data visualization tool. They are all very well developed. A great place to start is the “Tile Plot – Multiyear.” With it, you can get incredible visualizations of trends in air pollutants over time. A good way to start is to pick a city that interests you and then plot the different pollutants over the last 20 years. The intuitive color scheme represents comparison to different public health thresholds. These thresholds were developed by the EPA to evaluate whether sites meet the Clean Air Act air quality criteria. I believe that green and yellow colors are considered acceptable within the regulations, whereas orange, red, and brown are unacceptable. The time scale and interpretation of these calculations can be complicated, and can be further investigated on line.

  1. PurpleAir Map

Tool Developer: PurpleAir, LLC, using MapTiler and OpenStreetMap

https://www.purpleair.com/map

This tool also focuses on air pollution. However unlike the Air Data tool above, the data source for this tool is air pollution sensors placed by everyday folks like you and me. The map on the tool shows all of the results from PurpleAir sensors, which can be purchased by anyone for less than $300 (https://www2.purpleair.com/collections/air-quality-sensors). The PurpleAir sensors record particulate matter air pollution and some other variables, which are then mapped at the sensor locations. So in addition to indicating air pollution spatial patterns, the PurpleAir map is also a very powerful visualization of the benefits of open and collaborative data through the world wide web.

The interface of the PurpleAir allows you to easily move the map around throughout the world, although different parts of the world have varying coverage. Students can investigate specific patterns further, either with the tool, or by targeted research. For example, why are levels of particulate matter usually very high in northern India? (answers may include: high population density, high reliance on polluting fuel sources that burn dirty, limited access to cleaner fuel sources. For more, see Ajay Pillarisetti’s amazing blog post: https://snarglr.com/s/2015/01/field-notes-measuing-village-air-pollution-in-bajada-pahari/ )

There is also easy ability to see changes in time. Just click on one of the sites. The data are not carefully curated; thus data validity may be more of an issue for PurpleAir than for E.P.A.’s Air Data (tool #1). For example, particulate matter measurements can be influenced by changes in humidity which temporarily expands the size of the airborne particles without changing their harmfulness. Like the Air Data map, the color scheme is based on U.S. EPA air quality thresholds. 

There are additional things that can be done with the PurpleAir results. Sites surrounded by a black circle are indoor locations, where uncircled sites are outdoor. So indoor vs. outdoor sites can be visually compared in some regions. Each sensor generates paired monitoring results (two duplicate sensors) which can be visually or analytically compared to evaluate precision. There is also an easy to use data-download tool, enabling more detailed exploration of additional site data. So the PurpleAir tool is especially useful for practicing with data access, data manipulation (also called “data wrangling”), analysis of things like averages, and plotting patterns.

Notes

A few notes on my list of tools. First, I have only used the tools on my home or work computers with high-speed internet. I’m not sure how well they would work on cell phones or lower-speed internet connections. Second, I am not affiliated with any of the tools or their developers – I’m a college professor. 

Stay tuned for more interesting tool recommendations from Dr. Ben Greenfield!