[Tutorial Kit] Building a Community Health Indicator List for Air Quality in Airtable
- Shamini V De Silva
- 2 hours ago
- 6 min read
Workshop Chapters
Recorded live Feb 24 2026, timestamps below
02:45:14 What is PM 2.5?
04:42:11 What is Airtable?
05:30:13 Finding Data
06:26:08 Entering Data Overview
07:29:15 Opening Airtable
10:30:22 Airtable Views
🎯 Data Challenge
Create a data story for air pollution in your region by comparing local concentrations of PM2.5 to the primary (health-based) standard for PM2.5 set by the Environmental Protection Agency's (EPA).
3 Learning Objectives
Query & Collect 📊 data on air pollution in your region.
Analyze data using the data tool: 🧰 🛠️ Airtable.
Visualize & Humanize data by creating an indicator list and formula phrase in Airtable.
Prerequisites. Beginner-friendly, no prior experience needed.
Keywords and core concepts also covered:
How do we measure air pollution, and why does it matter to health?
Basics of inputting data in 🧰 🛠️ Airtable
Airtable features: Formulas, Views, AI image generation.
What you'll need to complete this challenge
⏰ Time. 20-40 minutes
🧰 Tools: Airtable.
A free Airtable Account
READ-ONLY TEMPLATE Airtable Base:
https://airtable.com/appNTli7mUkQ9UbsD/shrfN9xHUdC8ShVpt
To create an editable copy of this read-only base (a.k.a. "database"), make a copy to your workspace. First, click the link above, then "Copy base".
Click "Copy base" to create an editable copy of the READ-ONLY Template. The copy will save to your own workspace. Changes to your copy will not be viewable by anyone. 📊 Data:
Indicator: PM2.5: Highest Annual Average Concentration (Monitor + Modeled Data), 2020, by County.
Data Source: National Environmental Public Health Tracking Network, Data Explorer tool. https://ephtracking.cdc.gov/DataExplorer/
Key Terms and Definitions
PM2.5 (or PM2.5) is fine particulate matter that is 2.5 micrometers (i.e. microns, µm) in diameter or smaller.
PM2.5 concentration (µg/m³) is measured as particle weight (micrograms, µg) for every cubic meter of air (m³).
The primary (health-based) standard for PM2.5. The Environmental Protection Agency's (EPA's) annual National Ambient Air Quality Standard (NAAQS) for fine particulate matter (PM2.5) is 9.0 µg/m³. Above 9.0 µg/m³ is considered harmful to health (EPA, 2025).
What is PM2.5 and Why Does It Matter?
PM2.5 refers to fine particulate matter that is 2.5 micrometers or smaller—about 30 times thinner than a human hair. These particles come from sources like vehicle emissions, wildfires, and fossil fuel combustion (United States Environmental Protection Agency, 2023). Because they are so small, they can enter the lungs and bloodstream, increasing the risk of heart disease, stroke, asthma, and poor birth outcomes (United States Environmental Protection Agency, 2024).
Step-by-Step Walkthrough
Monitoring PM2.5 and comparing it to National Ambient Air Quality Standards is essential for protecting public health.
By the end of this tutorial, you will:
find county-level PM2.5 data (2020),
input and organize data in Airtable,
compare local concentrations of air pollution to the National Ambient Air Quality Standard for PM2.5 (9.0 µg/m³), and
build a short, narrative-style data story phrase that can be used for Community Health Assessments.
Step 1: Set Up Your Airtable Workspace
Airtable is a powerful tool for managing and presenting information clearly. Key features include:
Basic Features
FILTER and GROUP data to focus on specific indicators
HIDE fields that are not currently needed
VIEW Different table formats to organize information
More Advanced Features
AI-generated summaries that help create narrative insights from your data
Automations
For this tutorial:
Log in to Airtable or "Sign Up for Free" and create an account by verifying your email and following the instructions provided by Airtable.
Open the READ-ONLY TEMPLATE Airtable Base: https://airtable.com/appNTli7mUkQ9UbsD/shrfN9xHUdC8ShVpt
"Copy base" to your own workspace for editing. Note: This step is not included in the video of the live workshop.
Open your EDITABLE COPY of the Base.
Go to:
TAB or TABLE: "START HERE 🏁"
VIEWS: "Grid View"
See the Grid (or Spreadsheet) with rows
Next, in the first column of the Grid, under the last row, click on the ‘+’ symbol to add a new row and enter the following under the appropriate fields:
Your name (edit as needed)
The chosen county
The state where that county is located (via dropdown - this field is linked to the ‘US States’ table).
The “Summary” field has been set to auto-fill using a formula.
Step 2: Collect PM2.5 Data
If not seeing the Query Panel, click on ‘SELECT DATA’ in the top-left corner
In the Query Panel, select:
STEP 1: CONTENT
Content Area: Air Quality
Indicator: Current and Historical Air Quality
Measure: PM2.5 (highest annual average concentration, monitored + modeled)
STEP 2: GEOGRAPHY TYPE: State by County
STEP 3: GEOGRAPHY: Choose state
STEP 4: TIME: 2020
STEP 5: ADVANCED OPTIONS: No Advanced Options
Click Button: GO
Once the map loads, hover over your chosen county to find the value (e.g., Average: 15.6)
Step 3: Collect Asthma Prevalence Data
Gathering this data will further add to the data story and may back up our claims that high PM2.5 levels can have negative effects on health outcomes.
While still in the National Environmental Public Health Tracking Network Data Explorer Tool:
Click on the ‘X’ icon to clear previous data → then, click on ‘SELECT DATA’
In the Query Panel, select:
STEP 1: CONTENT
Content Area: Asthma
Indicator: Prevalence of Asthma among Adults
Measure: Age-adjusted Prevalence of Current Asthma among Adults (Model-based; County)
STEP 2: GEOGRAPHY TYPE: State by county
STEP 3: GEOGRAPHY: Choose state
STEP 4: TIME: 2020
STEP 5: ADVANCED OPTIONS: No Advanced Options
Click Button: GO
Once the map loads, hover over your chosen county to record the percentage (e.g., Percent: 9.2%)
Step 4: Add Queried Data to Airtable
Go to your copy of the Airtable base and enter the data gathered above under the appropriate fields.
PM2.5 data goes under the field: ‘PM2.5: Highest Annual Average Concentration in 2020 (µg/m³)'
Then, indicate how this value compares to the EPA standard of 9.0 µg/m³
Asthma prevalence goes under ‘Age-Adjusted Prevalence of Current Asthma Among Adults in 2020 (%)’
Then, indicate how this value compares to the national prevalence.
Step 5: Generate Your Data Story
Under the field ‘Phrase’, some text will be generated based on your inputs in the previous fields. This field has been set to use a formula to transform raw data into a meaningful statement that can be used in a Community Health Needs Assessment.
Example:
“In 2020, the average PM2.5 level in Los Angeles County, California, was 15.6 µg/m³, which was higher than the National Ambient Air Quality Standard of 9 µg/m³ set to protect public health. This means that many residents were exposed to pollution levels above what is considered safe. Breathing in high levels of PM2.5 over time can increase the risk of serious health problems, including heart attacks, asthma, and stroke.”
Final Takeaway
By combining environmental and health data in Airtable, you can turn a single data point into a compelling story. This approach is widely used in community health assessments to identify risks, highlight disparities, identify solutions, and inform policy decisions.
You've Earned a Certificate! | |
BroadStreet Certificate (FREE) | |
CPH - Certified in Public Health Recertification Credits (1 credit hr) ($10) | Pending approval by the National Board of Public Health Examiners (NBPHE) |
Note: We review projects every 2-4 weeks, and typically at the end of the month.
Instructors
 | Diana Saad, MPH Data for Change Program Coordinator BroadStreet Institute Diana has a passion for exploring data and using tools like Airtable and over the past year has worked with dozens of trainees on Airtable setup, indicator exploration, data stories, and logic models. Diana is passionate about health and wellness, specifically for women and children. |
References
Bekkar, B., Pacheco, S., Basu, R., & DeNicola, N. (2020). Association of air pollution and heat exposure with preterm birth, low birth weight, and stillbirth in the US: A systematic review. JAMA Network Open.
Bowe B, Xie Y, Yan Y, Al-Aly Z. (2019). Burden of Cause-Specific Mortality Associated With PM2.5 Air Pollution in the United States. JAMA Network Open. 2019;2(11):e1915834. doi:10.1001/jamanetworkopen.2019.15834
Congressional District Health Dashboard, Why Do We Measure Air Pollution? https://www.congressionaldistricthealthdashboard.org/metric/air-pollution-particulate-matter
Parasin, N., Amnuaylojaroen, T., & Saokaew, S. (2024). Prenatal PM2.5 exposure and its association with low birth weight: A systematic review and meta-analysis. Toxics, 12(7), 446. https://doi.org/10.3390/toxics12070446
Sethi, Y., Mehta, S., Padda, I., Marlecha, P., & Moinuddin, A. (2026). Impact of PM2.5 exposure on cardiovascular diseases [IPEC Study]: An updated umbrella review of systematic reviews and meta-analyses. European Journal of Preventive Cardiology.
University of Wisconsin Population Health Institute. (2025). County health rankings & roadmaps. Retrieved from https://www.countyhealthrankings.org
United States Environmental Protection Agency. (2023, July 11). Particulate matter (PM) basics. United States Environmental Protection Agency. https://www.epa.gov/pm-pollution/particulate-matter-pm-basics
United States Environmental Protection Agency. (2024, July 16). Health and Environmental Effects of Particulate Matter (PM). US EPA. https://www.epa.gov/pm-pollution/health-and-environmental-effects-particulate-matter-pm