Smoke from agricultural fires is a potentially important source of fine particulate matter (PM_2.5) in the US. Sugarcane is burned in Florida to facilitate the harvesting process, with the majority of these fires occurring in the Everglades Agricultural Area (EAA), where there is only one regulatory air quality monitor. During the 2022–2023 sugarcane burning season (October–May), we used public low-cost PurpleAir sensors, regulatory monitors, and 29 PurpleAir sensors deployed for this study to quantify PM2.5 from agricultural fires. We found satellite imagery is of limited use for detecting smoke from agricultural fires in Florida due to the cloud cover, overnight smoke, and the fires being small and short-lived. For these reasons, surface measurements are critical for capturing increases in PM_2.5 from smoke, and we used multiple smoke-identification criteria. During the study period, median 24-hour PM_2.5 concentrations increased by 2.3–6.9 µg m^-3 on smoke-impacted days compared to unimpacted days, with smoke observed on 4–28% of the campaign days (ranges from the different smoke-identification criteria). Further, short-term PM_2.5 increases were observed over 40 µg m^-3 during smoke events. We contrast the region near the EAA with large populations of low-income and minoritized groups to the more affluent coastal region. The inland region experienced more smoke-impacted monitor days than the Florida east coast region, and there was a higher study-average smoke PM_2.5 concentration in the inland area. These findings highlight the need to increase air quality monitoring near the EAA.

We deployed 29 PurpleAir PM_2.5 sensors in southern Florida during October 2022 - May 2023. PurpleAir sensors are low-cost devices (~$300 USD) that use light scattering techniques to estimate PM_2.5 mass (µg m^-3). We performed several quality checks of the raw PurpleAir data (“CF1”) using the methods outlined in a previous study (https://doi.org/10.1029/2023GH000982). We took 10-minute averages of the PM_2.5 estimates and then removed data with the following conditions: (1) temperature > 65 ^oC (0.0092 % of observations), (2) relative humidity > 100% (0.0007 % of observations), (3) channel disagreement > 10% from the average of the two channels or 10 µg m^-3 in the absolute difference between the channels (1.4 % of observations), and (4) measurements > 500 µg m^-3 (0.0007 % of observations). We applied the Barkjohn et al. (2021) correction factor to all the quality-checked 10-minute average PurpleAir data from the deployment in Florida (https://doi.org/10.5194/amt-14-4617-2021). This correction factor was developed for the entire US and scales PM_2.5 based on measurement concentrations and relative humidity.