Spatial and Temporal Variations in SO2 and PM2.5 Levels Around Kīlauea Volcano, Hawai'i During 2007–2018

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The 2018 Lower East Rift Zone (LERZ) eruption of Kilauea volcano, Hawai'i, resulted in a significant increase in gas emissions from the volcano and a change in the dominant location of emissions. This led to significant changes to air quality in downwind communities. We analyse two sets of open-access data and present measurements of atmospheric sulfur dioxide (SO2) and aerosol particulate matter smaller than 2.5 um (PM2.5) collected by the Hawai'i Department of Health (HDOH) and National Park Service (NPS) operational air quality monitoring networks between 2007 and 2018; and a community-operated network of low-cost PM2.5 sensors on the Island of Hawai'i. During this period, the two most significant escalations in Kilauea's volcanic emissions were: the summit eruption that began in 2008 (Kilauea emissions averaged 5 - 6 kt/day SO2 over the course of the eruption) and the LERZ eruption in 2018 when SO2 emission rates likely reached 200 kt/day in June. In this paper we focus on characterising the airborne pollutants arising from the 2018 LERZ eruption and the spatial distribution and severity of air pollution events across the Island of Hawai'i. The LERZ eruption caused the most frequent and severe exceedances of Environmental Protection Agency 24-hour-mean PM2.5 air quality thresholds in Hawai'i since 2010. In Kona, for example, there were eight exceedances during the 2018 LERZ eruption, where there had been no exceedances in the previous eight years as measured by the HDOH and NPS networks. SO2 air pollution during the LERZ eruption was most severe in communities in the south and west of the island, with maximum 24-hour-mean mass concentrations of 728 ug/m^3 recorded in Ocean View (100 km west of the LERZ emission source) in May 2018. Data from the low-cost sensor network correlated well with data from the HDOH PM2.5 instruments (Kona station, R^2 = 0.89), demonstrating that these low-cost sensors provide a robust means to augment reference-grade instrument networks.

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