Whitehill Andrew R, Lunden Melissa, LaFranchi Brian, Kaushik Surender, Solomon Paul A
Center for Environmental Measurement and Modeling, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina, 27711, United States of America.
Aclima, Inc., San Leandro, California, 24577, United States of America.
Atmos Meas Tech. 2024 May 17;17(9):2991-3009. doi: 10.5194/amt-17-2991-2024.
Air pollution monitoring using mobile ground-based measurement platforms can provide high quality spatiotemporal air pollution information. As mobile air quality monitoring campaigns extend to entire fleets of vehicles and integrate smaller scale air quality sensors, it is important to address the need for assessing these measurements in a scalable manner. We explore collocation-based evaluation of air quality measurements in a mobile platform using fixed regulatory sites as a reference. We compare two approaches - a standard collocation assessment technique where the mobile platform is parked near the fixed regulatory site for a period of time and an expanded approach using measurements while the mobile platform is in motion in the general vicinity of the fixed regulatory site. Based on the availability of fixed reference site data, we focus on three pollutants (ozone, nitrogen dioxide, and nitric oxide) with distinct atmospheric lifetimes and behaviors. We compare measurements from a mobile laboratory with regulatory site measurements in Denver, Colorado, USA and in the San Francisco Bay Area, California, USA. Our one-month Denver dataset includes both parked collocation periods near the fixed regulatory sites as well as general driving patterns around the sites, allowing a direct comparison of the parked and mobile collocation techniques on the same dataset. We show that the mobile collocation approach produces similar performance statistics, including coefficients of determination and mean bias errors, as the standard parked collocation technique. This is particularly true when the comparisons are restricted to specific road types, with residential streets showing the closest agreement and highways showing the largest differences. We extend our analysis to a larger (year-long) dataset in California, where we explore the relationships between the mobile measurements and the fixed reference sites on a larger scale. We show that using a 40-hour running median converges to within ±4 ppbv of the fixed reference site for nitrogen dioxide and ozone and up to about 8 ppbv for nitric oxide. We propose that this agreement can be leveraged to assess instrument performance over time during large-scale mobile monitoring campaigns. We demonstrate an example of how such relationships can be used during large-scale monitoring campaigns using small sensors to identify potential measurement biases.
使用移动地面测量平台进行空气污染监测能够提供高质量的时空空气污染信息。随着移动空气质量监测活动扩展到整个车辆车队，并集成了更小尺度的空气质量传感器，以可扩展的方式评估这些测量结果的需求变得至关重要。我们探索以固定监管站点为参考，对移动平台上的空气质量测量进行基于并置的评估。我们比较了两种方法——一种标准的并置评估技术，即移动平台在固定监管站点附近停放一段时间；另一种扩展方法是在移动平台在固定监管站点附近移动时使用测量数据。基于固定参考站点数据的可用性，我们重点关注三种具有不同大气寿命和行为的污染物（臭氧、二氧化氮和一氧化氮）。我们将移动实验室的测量结果与美国科罗拉多州丹佛市和美国加利福尼亚州旧金山湾区的监管站点测量结果进行比较。我们在丹佛的一个月数据集包括在固定监管站点附近的停放并置期以及站点周围的一般驾驶模式，从而能够在同一数据集上直接比较停放和移动并置技术。我们表明，移动并置方法产生的性能统计数据，包括决定系数和平均偏差误差，与标准的停放并置技术相似。当比较限于特定道路类型时尤其如此，住宅街道显示出最接近的一致性，而高速公路显示出最大的差异。我们将分析扩展到加利福尼亚州更大的（为期一年的）数据集，在那里我们在更大规模上探索移动测量与固定参考站点之间的关系。我们表明，使用40小时运行中位数，二氧化氮和臭氧可收敛到固定参考站点的±4 ppbv范围内，一氧化氮可达约8 ppbv。我们建议，可以利用这种一致性来评估大规模移动监测活动期间仪器随时间的性能。我们展示了一个例子，说明在大规模监测活动中如何利用这种关系，使用小型传感器识别潜在的测量偏差。
