Clean Air

The Coalition for Clean Air (CCA) is an advocacy group based in Los Angeles that works with various stakeholders to Coalition for Clean Air: Home protect public health, improve air quality, and prevent climate change.
How it started
CCA was founded in 1971 and is California’s only statewide organization working exclusively on air quality issues. From creating the idea for California’s original Smog Check program in 1981 to ensuring the first national ban on the toxic dry cleaning chemical “perc” to helping pass legislation to put 1 million electric vehicles on California’s roads by 2025, CCA has paved the way for socially and environmentally responsible air policy nationally and worldwide.
Our Work
Today we maintain a small, dedicated staff with offices in Sacramento and Los Angeles working toward the goal of clean air throughout California.

Data4Good (D4G) is partnering with CCA to build a software tool that aggregates air quality data located throughout the Los Angeles region.
Challenges Observed
CCA currently utilizes data from over 200+ PurpleAir clean air sensors throughout the Los Angeles county area. The sensors, however, all operate independently. PurpleAir’s interface for accessing data has limitations that make it time-consuming and difficult to work with.  There is also no existing interface or business logic for people that would make it easier to use.
Phase 1 Goals:
• Create a high fidelity prototype for a user interface of aggregated PurpleAir data
• Work on modules for the business logic to submit for validation
• Create a roadmap (or define the inputs required for a roadmap) for subsequent development phases.

Solutions & Outcomes

Our solution was to use a Rapid Sprint process, that allowed us to go from concept to a tested prototype in ten days. We created two key deliverables during this time:


A clickable figma prototype, user tested by industry experts, which informs the phase two development of the web application.


Scripts written to address converting raw data into usable information in the form of Python + R code for clean air sensor calibration, quality control, and PM2.5 to ACI conversion.

Total Effort

The stakeholders were thrilled with the progress of the project to date and would love to see it progress forward.

600+ volunteer hours

(12 people, 10 days, 5 hours / day average)

6+ hours of expert

3+ advisory hours


• Defining regulatory requirements of calibrating clean air sensor data
• Learning best practices of performing QC on sensors
• Learning algorithms for converting clean air formats
• Creation of user profiles and journeys
• User interface design
• Clickable Figma prototype
• Expanded features list
• 6 Python/R scripts for business logic for MVP features for automating
• Outlier detection
• Defining data frames
• Aggregating data from sensors in LA area
• Sensor calibration per EPA standards
• Quality Control evaluation of sensors
• Converting PM2.5 data to AQI (air quality / health index)

Team Members


Helen Ding

Ivan Escusa

Jesse Mann

Michelle Lee

Eddie Park

Patrick Bowman

Thuong Dinh

Tiffany Feng


Jessy Escobedo

Team Advisors

Tim Dye

Advisor - Domain Expert

Biayna Bogosian

D4G Advisory Board

Todd Terrazas


Ronni Kimm


Mukund Kaushik

For more information and ways to get involved contact Todd Terrazas or Ronni Kimm.