School of Chemical Engineering, National Technical University of Athens, 15780, Zografos, Athens, Greece.
Institute for Environmental Research and Sustainable Development, National Observatory of Athens, 15236, Athens, Greece.
Environ Monit Assess. 2020 Sep 9;192(10):627. doi: 10.1007/s10661-020-08569-8.
Numerous health studies have linked the exposure to particulate matter with adverse health effects, while there is an increasing scientific interest in the particle metrics of surface area (SA) and lung-deposited SA (LDSA) concentration. In the present study, two integrated SA estimation methods, both based on widely used instrumentation, were applied at an urban traffic environment in Athens for a 6-month period. The first estimation method used the size distribution by number to estimate SA (average SA 669.3 ± 229.0 μm cm), while the second method used a simple inversion scheme that incorporates number and mass concentrations (average SA 1627.9 ± 562.8 μm cm). In pairwise comparisons, SA levels were found two times greater than the corresponding SA, but exhibited a strong correlation (r = 0.73). SA and SA concentrations correlated well with the traffic-related pollutants NO (r = 0.64 and 0.78) and equivalent black carbon (r = 0.53 and 0.51). The diurnal variation of SA concentrations by size range indicated traffic as a major controlling factor. Estimated LDSA (53.9 μm cm on average) concentrations were also clearly affected by anthropogenic emissions with more pronounced associations in the 0.01-0.4 μm range (r = 0.66 with NO and r = 0.65 with equivalent black carbon). Validating estimated LDSA through simultaneous measurements with a reference instrument revealed that the estimation method underestimates LDSA by a factor between 2 and 3, exhibiting, however, a high correlation (r = 0.79). Overall, the performance of estimation methods appear satisfactory and indicate that a trustworthy assessment of the temporal variability of SA and LDSA concentration metrics can be provided in real time, on the basis of relatively lower-cost instrumentation, especially in view of recent advances in particle sensing technologies.
大量健康研究表明,暴露于颗粒物与不良健康影响有关,而科学界对表面积(SA)和肺部沉积表面积(LDSA)浓度的颗粒指标越来越感兴趣。在本研究中,两种基于广泛使用的仪器的集成 SA 估算方法应用于雅典的城市交通环境中,为期 6 个月。第一种估算方法使用数浓度分布来估算 SA(平均 SA 为 669.3 ± 229.0 μm cm),而第二种方法使用简单的反演方案,该方案结合了数浓度和质量浓度(平均 SA 为 1627.9 ± 562.8 μm cm)。在成对比较中,SA 水平比相应的 SA 高两倍,但相关性很强(r = 0.73)。SA 和 SA 浓度与交通相关污染物 NO(r = 0.64 和 0.78)和等效黑碳(r = 0.53 和 0.51)很好地相关。按粒径范围划分的 SA 浓度的日变化表明,交通是主要的控制因素。估计的 LDSA(平均浓度为 53.9 μm cm)也明显受到人为排放的影响,在 0.01-0.4 μm 范围内相关性更强(与 NO 的 r = 0.66,与等效黑碳的 r = 0.65)。通过与参考仪器的同时测量来验证估计的 LDSA,发现估计方法低估了 LDSA 约 2 至 3 倍,但具有很高的相关性(r = 0.79)。总的来说,估算方法的性能表现令人满意,表明可以基于相对低成本的仪器,实时提供 SA 和 LDSA 浓度指标的时间变化的可靠评估,特别是考虑到最近在颗粒感测技术方面的进展。