# Scope of this Dataset

The Eaton Fire in Southern California contaminated homes across Altadena, Pasadena, and Sierra Madre with hazardous ash and soot. Residents feared serious health risks prompting Eaton Fire Residents United (EFRU), a grassroots coalition of community members, to begin collecting, compiling, and publicly sharing residential contamination testing data taken by professional industrial hygienists. 

This dataset contains anonymized, professionally collected contamination test results from over 200 affected homes. Researchers and advocates can leverage this dataset to study contamination patterns and support evidence-based policy improvements related to wildfire recovery and public health.

More information about EFRU as well as a live version of this information is available at www.efru.la

# Contents

## Datasheet for Dataset

The included Datasheet for Dataset provides comprehensive details about the dataset's contents, methods of collection, data anonymization practices, and suggested use-cases.

## Standard Operating Procedures

The SOP document contains detailed procedures for processing the original resident-provided test reports to anonymize and compile the data.

## Code Examples

A basic Python Notebook is included for loading, exploring, and visualizing the dataset. This script should facilitate researchers getting started with the dataset.

## Data

The dataset includes contaminant levels measured inside 201 homes in CSV format. Each row in the CSV provides:
* Anonymized location (nearest cross-street)
* Peak measured concentrations of contaminants and other elements, including wildfire debris (ash, soot, char), asbestos, lead, arsenic, antimony, barium, beryllium, cadmium, chromium, cobalt, copper, mercury, molybdenum, nickel, selenium, silver, thallium, vanadium, and zinc.
* User-reported proximity to burned structures
* Damage and remediation status at testing time

## Updates

The dataset will be updated periodically as additional residential testing results become available. Further releases as well as minor corrections are expected as this is an ongoing effort by community volunteers.

# Acknowledgements

We express our profound gratitude to community members who have voluntarily shared their reports and helped us compile this dataset, all in pursuit of rebuilding a healthier, safer community. We also acknowledge Jennifer Cotton, Jordan Boye, and Dawn Fanning for their contributions as well as the entire EFRU community.