Review of Low-Cost Air Quality Monitoring Deployed In the 2018 Kīlauea Eruption

A newly published research article that focuses on the air quality during the 2018 eruption of Kīlauea in the Lower East Rift Zone has been released publicly. Researchers developed a low-cost network of sensors to detect sulfur dioxide (SO2) and particulate matter (PM). The network of 30 nodes (would have been 32 nodes but two were lost to the lava) was able to provide estimates for human exposure to both pollutants during the eruption, improving upon previous monitoring. Each node in the network provided information in real-time, and were able to be deployed with stand-alone power and a small profile and footprint on the environment. The low-cost sensor network was able to track the changes in eruptive activity and overall trends of volcanic emissions, as well as estimate the potential exposure levels of residents downwind from the vents. Findings indicate that the highest levels of SO2 in 2018 were immediately downwind of the eruptive vents, while the highest concentrations of particulate matter was along the western Kona side of the island. The trade winds moved the volcanic plume along the south side of the island and formed into sulfuric acid, and accumulates as PM. “Poor air quality is a global public health issue, contributing to millions of premature deaths per year worldwide. Low-cost air quality sensors are a promising tool to improve monitoring capabilities. In this study, we built and deployed a low-cost sensor network for emergency response during an extreme air quality event, the 2018 Kīlauea Lower East Rift Zone eruption. This network was used to estimate fine-scale population exposures to multiple pollutants, to measure the chemical transformation of volcanic emissions, and to provide real-time observations as part of emergency management efforts.” ~ Ben Crawford, et. al. Image captions: Fig. 1 - “Satellite- and ground-based monitoring of air quality before, during, and after the LERZ eruption. (A and B) Satellite observations of column integrated SO2 and aerosol optical depth (AOD) from May to July, comparing the average of 3 y prior to the eruption (2015 to 2017), the year of the eruption (2018), and the year following the eruption (2019). SO2 (shown in Dobson Units [DU]) and AOD measurements are taken from the Ozone Mapping and Profiler Suite (OMPS) instrument aboard Suomi National Polar-orbiting Partnership (NPP) (50 km product, Version 2) and the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua platform (10 km product, Collection 6.1), respectively. Daily satellite observations are gridded and averaged at 0.5° × 0.5° horizontal resolution. (C and D) Concentrations of SO2 and PM2.5 for all of 2018, as measured by the Hawai‘i Department of Health ground-level regulatory station at Ocean View.” Fig. 2 - “Average concentrations of SO2 (A) and PM2.5 (B), as measured by the LCS network (colored circles) and the regulatory network stations (gray circles). Data are from a 15-d period from July 15 to August 1, 2018; only the LCS nodes that were in near-continuous operation during this time are shown. For SO2, 17 sensors are shown, accounting for 70,414 people within 5 km. For PM2.5, 20 are shown, accounting for 86,856 people within 5 km. In total, there are 16 stations with both SO2 and PM2.5 measurements, accounting for 73,013 people within 5 km (Fig. 3). The full time series for all sensors are shown SI Appendix, Figs. S3 and S5.” Fig. 3. “Population exposure to volcanic pollutants, measured by the LCS network over the 15-d study period. (A and B) Mean pollutant distribution as a function of cumulative near-node population (residents living within 5 km of each node: 73,013 total). Bar width is proportional to nearby population, and bar height is the average pollutant concentration measured by each node. Sensor nodes are differentiated by color, as shown on the inset map. Stations are arranged from lowest to highest average concentration. (C and D) Population distribution as a function of hourly exposure frequency to SO2 and PM2.5. Here, the distribution of hourly concentrations experienced by each sensor node is weighted by population within 5 km of the node and arranged by average concentration. Estimation of near-node population is given in the SI Appendix. Hourly population-weighted time series data to create (C and D) is shown in SI Appendix, Fig. S9. An equivalent figure using regulatory network data are shown for comparison in SI Appendix, Fig. S10.” Full Paper: Mapping pollution exposure and chemistry during an extreme air quality event (the 2018 Kīlauea eruption) using a low-cost sensor network. (2021) Ben Crawford, et. al. https://www.pnas.org/content/118/27/e2025540118