Abstract. Sensor networks are being more widely used to characterize and understand compounds in the atmosphere like ozone (O 3 ). This study employs a measurement tool, called the U-Pod, constructed at the University of Colorado Boulder, to investigate spatial and temporal variability of O 3 in a 200 km 2 area of Riverside County near Los Angeles, California. This tool contains low-cost sensors to collect ambient data at non-permanent locations. The U-Pods were calibrated using a pre-deployment field calibration technique; all the U-Pods were collocated with regulatory monitors. After collocation, the U-Pods were deployed in the area mentioned. A subset of pods was deployed at two local regulatory air quality monitoring stations providing validation for the collocation calibration method. Field validation of sensor O 3 measurements to minute-resolution reference observations resulted in R 2 and root mean squared errors (RMSEs) of 0.95-0.97 and 4.4-5.9 ppbv, respectively. Using the deployment data, ozone concentrations were observed to vary on this small spatial scale. In the analysis based on hourly binned data, the median R 2 values between all possible UPod pairs varied from 0.52 to 0.86 for ozone during the deployment. The medians of absolute differences were calculated between all possible pod pairs, 21 pairs total. The median values of those median absolute differences for each hour of the day varied between 2.2 and 9.3 ppbv for the ozone deployment. Since median differences between U-Pod concentrations during deployment are larger than the respective root mean square error values, we can conclude that there is spatial variability in this criteria pollutant across the study area. This is important because it means that citizens may be exposed to more, or less, ozone than they would assume based on current regulatory monitoring.
Recent advances in air pollution sensors have led to a new wave of low-cost measurement systems that can be deployed in dense networks to capture small-scale spatio-temporal variations in ozone, a pollutant known to cause negative human health impacts. This study deployed a network of seven low-cost ozone metal oxide sensor systems (UPods) in both an open space and an urban location in Boulder, Colorado during June and July of 2015, to quantify ozone variations on spatial scales ranging from 12 m between UPods to 6.7 km between open space and urban measurement sites with a measurement uncertainty of ~5 ppb. The results showed spatial variability of ozone at both deployment sites, with the largest differences between UPod measurements occurring during the afternoons. The peak median hourly difference between UPods was 6 ppb at 1:00 p.m. at the open space site, and 11 ppb at 4:00 p.m. at the urban site. Overall, the urban ozone measurements were higher than in the open space measurements. This study evaluates the effectiveness of using low-cost sensors to capture microscale spatial and temporal variation of ozone; additionally, it highlights the importance of field calibrations and measurement uncertainty quantification when deploying low-cost sensors.
Abstract. Sensor networks are being more widely used to characterize and understand compounds in the atmosphere such as ozone and carbon dioxide. This study employs a measurement tool, called the U-Pod, constructed at the University of Colorado Boulder, to investigate spatial and temporal variability of O3 and CO2 in a 314 km 2 area of Riverside County near Los Angeles, 10California. This tool provides low-cost sensors to collect ambient data at non-permanent locations. The U-Pods were calibrated using a pre-deployment field calibration technique; all the U-Pods were collocated with regulatory monitors. After collocation, the U-Pods were deployed in the area mentioned. A subset of pods was deployed at two local regulatory air quality monitoring stations providing validation for the collocation calibration method. Field validation of sensor O3 and CO2 measurements to minute resolution reference observations resulted in R-squared and root mean squared errors (RMSE) of 0.95 -0.97 and 4.4 -15 7.2 ppbv for O3 and 0.79 and 15 ppmv CO2, respectively. Using the deployment data, ozone and carbon dioxide concentrations were observed to vary on this small spatial scale. In the analysis based on hourly binned data, the median R-squared values between all possible U-Pod pairs varied from 0.52 to 0.86 for ozone during the deployment. The medians of absolute differences were calculated between all possible pod pairs, 21 pairs total. The median values of those median absolute differences for each hour of the day varied between 2.2 and 9.3 ppb for the ozone deployment. For carbon dioxide, distributions 20 of all measurements vary from 413 -425 ppm during the calibration (collocation) and 406 -472 during the deployment. Since median differences between U-Pod concentrations during deployment are larger than the respective root mean square error values for ozone and carbon dioxide, we can conclude that there is spatial variability in these pollutants across the study area. This is important because it means that citizens may be exposed to more ozone than they would assume based on current regulatory monitoring. 25Atmos. Meas. Tech. Discuss., https://doi
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.