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Intra-urban spatial variability of surface ozone and carbon dioxide in Riverside, CA: viability and validation of low-cost sensors

机译:加利福尼亚里弗赛德市内城市表面臭氧和二氧化碳的空间变异性:低成本传感器的可行性和验证

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摘要

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 O and CO in a 314 km area of Riverside County near Los Angeles, California. 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 O and CO measurements to minute resolution reference observations resulted in R-squared and root mean squared errors (RMSE) of 0.95–0.97 and 4.4–7.2 ppbv for O and 0.79 and 15 ppmv CO, 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 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.
机译:抽象。传感器网络已被广泛用于表征和理解大气中的化合物,例如臭氧和二氧化碳。这项研究采用了一种称为U-Pod的测量工具,该工具是由科罗拉多大学博尔德分校建造的,用于调查加利福尼亚州洛杉矶附近河滨县314公里处的O和CO的时空变化。该工具提供了低成本传感器,可以在非永久性位置收集环境数据。使用部署前的现场校准技术对U-Pods进行了校准。所有U-Pods均与监管监控器并置。搭配后,U-Pods被部署在上述区域。在两个当地监管空气质量监测站部署了一个豆荚子集,以验证搭配校准方法。传感器O和CO测量的现场验证与分钟分辨率的参考观测值有关,O和0.79和15µppmv CO的R平方和均方根误差(RMSE)分别为0.95-0.97和4.4-7.2ppppv。使用部署数据,观察到臭氧和二氧化碳的浓度在这个小的空间范围内变化。在基于小时分类数据的分析中,在部署期间,所有可能的U-Pod对之间的中值R平方值在0.52到0.86之间变化。计算所有可能的吊舱对之间的绝对差的中位数,总共21对。对于臭氧部署,一天中每个小时的绝对中位数绝对值的中位数在2.2至9.3ppb之间变化。对于二氧化碳,所有测量值的分布在校准(并置)过程中为413–425 ppm,在部署过程中为406–472。由于在部署过程中U-Pod浓度之间的中位数差异大于臭氧和二氧化碳各自的均方根误差值,因此可以得出结论,整个研究区域中这些污染物的空间变异性。这很重要,因为这意味着公民可能会比根据目前的监管监测所假设的臭氧暴露量更多。

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