Recent technological advances in both air sensing technology and Internet of Things (IoT)\nconnectivity have enabled the development and deployment of remote monitoring networks of air\nquality sensors. The compact size and low power requirements of both sensors and IoT data loggers\nallow for the development of remote sensing nodes with power and connectivity versatility. With\nthese technological advancements, sensor networks can be developed and deployed for various\nambient air monitoring applications. This paper describes the development and deployment of a\nmonitoring network of accurate ozone (O3) sensor nodes to provide parallel monitoring in an air\nmonitoring site relocation study. The reference O3 analyzer at the station along with a network of\nthree O3 sensing nodes was used to evaluate the spatial and temporal variability of O3 across four\nSouthern California communities in the San Bernardino Mountains which are currently represented\nby a single reference station in Crestline, CA. The motivation for developing and deploying the\nsensor network in the region was that the single reference station potentially needed to be relocated\ndue to uncertainty that the lease agreement would be renewed. With the implication of siting a new\nreference station that is also a high O3 site, the project required the development of an accurate and\nprecise sensing node for establishing a parallel monitoring network at potential relocation sites. The\ndeployment methodology included a pre-deployment co-location calibration to the reference\nanalyzer at the air monitoring station with post-deployment co-location results indicating a mean\nabsolute error (MAE) < 2 ppb for 1-h mean O3 concentrations. Ordinary least squares regression\nstatistics between reference and sensor nodes during post-deployment co-location testing indicate\nthat the nodes are accurate and highly correlated to reference instrumentation with R2 values > 0.98,\nslope offsets < 0.02, and intercept offsets < 0.6 for hourly O3 concentrations with a mean\nconcentration value of 39.7 ± 16.5 ppb and a maximum 1-h value of 94 ppb. Spatial variability for\ndiurnal O3 trends was found between locations within 5 km of each other with spatial variability\nbetween sites more pronounced during nighttime hours. The parallel monitoring was successful in\nproviding the data to develop a relocation strategy with only one relocation site providing a 95%\nconfidence that concentrations would be higher there than at the current site.
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