Download Smell Report Data for Allegheny County


We take every precaution to protect any personally identifiable data. All information shown on the public map visualization for Smell PGH is anonymous and location data is skewed to protect your privacy. Personal contact information you enter in the settings tab is only shared with ACHD and not stored in our database. Our backend database only contains anonymous User IDs created by your app service (Apple or Google Play).

This data is in a CSV format. You can open it in Google Sheets, Excel, or any text editor. Each smell report is a unique line item. Each field in the line is separated by commas. Data fields include:

  • Date and time of smell report
    • You can choose to download the data in UTC time or your local time
    • Your local time will be the time stamp on the machine you use to download the data
    • The date/time will be formatted as follows: 06/01/2016 01:47:52 -04:00
    • In the example above, the "-04:00" at the end of the string indicates time zone
  • Smell value (a number 1 through 5, with 5 being the most severe)
  • Location of smell report (ZIP code only)
  • Smell description and symptoms linked to odor (if provided)
Select the Pittsburgh city or enter ZIP codes:
Enter ZIP codes, seperated by comma:
Select a timezone:
Select a time range:
Download data in csv format:

Looking for a more specific data query? Visit Smell PGH API to learn more about our API.

Smell Data Analysis and Research


In the Pittsburgh region, using the smell reports and the air quality data from local agency monitoring stations, we developed a statistical model to predict upcoming smell events and send push notifications to inform communities. The dataset and the code are publicly available on GitHub. Our analysis indicated that smell events in Pittsburgh are related to the joint effect of wind directions and hydrogen sulfide readings. This research shows that engaging residents in documenting their experiences with pollution odors can help identify local air pollution patterns. To learn more, check our research paper below. A preprint of the paper can be downloaded here.

Yen-Chia Hsu, Jennifer Cross, Paul Dille, Michael Tasota, Beatrice Dias, Randy Sargent, Ting-Hao (Kenneth) Huang, and Illah Nourbakhsh. 2019. Smell Pittsburgh: community-empowered mobile smell reporting system. In Proceedings of the 24th International Conference on Intelligent User Interfaces (IUI '19). ACM, New York, NY, USA, 65-79. DOI: https://doi.org/10.1145/3301275.3302293

Smell Report Highlight Reel


The following video animates the daily summary of smell reports. Each frame in the video represents one day.