利用无人机垂直剖面和敏感性分析,评估严重污染空气盆地中的 CMAQ 模型差异†。

IF 2.8 Q3 ENVIRONMENTAL SCIENCES
Zihan Zhu, Khanh Do, Cesunica E. Ivey and Don R. Collins
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引用次数: 0

摘要

2020 年 8 月至 11 月期间,在加利福尼亚州河滨市每天部署一架无人驾驶飞行器,对臭氧和颗粒物进行垂直测量。飞行在清晨和傍晚进行,共获得 321 个从地表到离地面 500 米的垂直剖面图。测得的臭氧混合比与加利福尼亚州朱鲁帕谷 Riverside-Rubidoux 管制空气监测站点的地面测量值以及 CMAQ 模拟浓度进行了统计比较,以分别评估与最近参考监测值的一致性以及模型再现观测到的垂直结构的技能。默认模型配置在上午高估了地面臭氧 17.7 ppb,在下午平均低估了 2.9 ppb。通过在一系列模拟中修改关键的物理和排放设置,研究了模型对行星边界层(PBL)、涡扩散、氮氧化物排放和挥发性有机化合物排放等因素的敏感性。我们发现,默认 CMAQ 模拟中使用的默认 PBL 方案与天花板观测数据相比,夜间的 PBL 高度会出现负偏差,而白天则会出现正偏差。对于观测区域而言,氮氧化物的排放量在很大程度上被低估,从而导致模型中的臭氧浓度出现偏差。最后,我们提出了实现模型与局部测量值相等的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Assessing CMAQ model discrepancies in a heavily polluted air basin using UAV vertical profiles and sensitivity analyses†

Assessing CMAQ model discrepancies in a heavily polluted air basin using UAV vertical profiles and sensitivity analyses†

An unmanned aerial vehicle was deployed daily in Riverside, CA from August to November 2020, capturing vertical ozone and particulate matter measurements. Flights took place in the early morning and late afternoon, resulting in 321 vertical profiles from the surface to 500 m above ground level. The measured ozone mixing ratio is statistically compared with ground-based measurements at the Riverside–Rubidoux regulatory air monitoring site in Jurupa Valley, CA and with CMAQ simulated concentrations to assess consistency with the nearest reference monitor and model skill at reproducing the observed vertical structure, respectively. The default model configuration overestimates ground-level ozone by 17.7 ppb in the morning and underestimates it by an average of 2.9 ppb in the afternoon. The sensitivity of the model to factors such as planetary boundary layer (PBL), eddy diffusivity, NOx emissions, and VOC emissions is investigated by modifying key physics and emissions settings in a series of simulations. We found that our default PBL scheme used in the default CMAQ simulation negatively biases the PBL height in the nighttime and positively biases it in the daytime compared to the observations retrieved from a ceilometer. For the observational region of interest, NOx emissions are concluded to be largely underestimated, leading to biases in modeled ozone concentration. We conclude with recommendations for achieving model parity with localized measurements.

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