State Key Laboratory of Pollution Control and Resource Reuse, Tongji University, Shanghai, China 200092, P.R.China.
College of Environmental Science and Engineering, Tongji University, Shanghai 200092, P.R. China.
Environ Sci Technol. 2024 Nov 19;58(46):20566-20576. doi: 10.1021/acs.est.4c04217. Epub 2024 Oct 5.
Traffic-related air pollutants (TRAPs) emitted from vehicle tailpipes disperse into nearby microenvironments, posing potential exposure risks. Thus, accurately identifying the emission hotspots of TRAPs is essential for assessing potential exposure risks. We investigated the relationship between turbulent kinetic energy () and pollutant dispersion () through an integrated field measurement. A five-year near-road sampling campaign (5 min based) near a light-duty vehicle-restricted roadway and an on-road sampling campaign (5 s based) on isolated proving grounds were conducted. The was first calculated based on vehicle emission and pollutant concentrations and then paired with measurements. Here, 198 near-road and 377 on-road measurement pairs were collected. In the near-road measurements, and showed a positive relationship ( ≥ 0.69) with the vehicle flow rate, while they showed similar decay patterns and sensitivity to vehicle types in the on-road measurements. A relationship between and (-) was developed through these measurements, demonstrating a robust correlation ( ≥ 0.61) and consistent slope values (1.1-1.3). These findings provide field evidence for the positive association between and , irrespective of the measurement techniques or locations. The - relationship enables vehicle emission estimation with as the sole input, facilitating the identification of emission hotspots with high spatiotemporal resolution.
交通相关空气污染物（TRAPs）从车辆排气管中排放出来，散布到附近的微环境中，构成潜在的暴露风险。因此，准确识别 TRAPs 的排放热点对于评估潜在的暴露风险至关重要。我们通过综合现场测量研究了湍流动能耗散（）与污染物扩散（）之间的关系。在一条轻型车辆限制道附近进行了为期五年的近路采样活动（基于 5 分钟），并在孤立的试验场进行了上路采样活动（基于 5 秒）。首先根据车辆排放和污染物浓度计算出，然后与测量结果进行配对。在这里，收集了 198 对近路和 377 对上路测量结果。在近路测量中，和表现出与车流量的正相关关系（≥0.69），而在上路测量中，它们表现出相似的衰减模式和对车辆类型的敏感性。通过这些测量结果，建立了与之间的关系（-），显示出强大的相关性（≥0.61）和一致的斜率值（1.1-1.3）。这些发现提供了现场证据，证明了与之间存在正相关关系，无论测量技术或位置如何。-关系使得仅使用作为输入即可进行车辆排放估算，从而能够以高时空分辨率识别排放热点。
