Kim Hyeonmin, Park Rokjin J, Hong Song-You, Park Do-Hyeon, Kim Sang-Woo, Oak Yujin J, Feng Xu, Lin Haipeng, Fu Tzung-May
School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea.
School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea.
Sci Total Environ. 2024 Dec 10;955:176838. doi: 10.1016/j.scitotenv.2024.176838. Epub 2024 Oct 11.
Vertical mixing within the planetary boundary layer (PBL) is crucial for determining surface-level pollutant concentrations. However, standard PBL schemes in chemical transport models (CTMs) often fail to adequately define the upper bounds of vertical mixing, particularly at night. This limitation frequently results in overestimated nocturnal concentrations of pollutants near the surface. To address this issue, we propose a parameterization of mixed layer height (MLH) derived from the Yonsei University (YSU) PBL scheme and thoroughly evaluate it by comparing simulations with various observations. We utilized the Weather Research and Forecasting model coupled with GEOS-Chem (WRF-GC) to simulate gas and aerosol distributions over South Korea during the Satellite Integrated Joint Monitoring of Air Quality (SIJAQ) campaign in 2021. The WRF-GC simulations incorporating the MLH parameterization improved the excessive titration of O and the overproduction of HNO and NO in the model. Consequently, the model performances in gaseous and aerosol simulations showed a better agreement with observations, with changes in normalized mean biases (NMBs) of NO (from 50 % to -27 %), O (from -49 % to -28 %), NO (from 126 % to 91 %), NH (from 113 % to 85 %), BC (from 322 % to 135 %), and PM (from 58 % to 28 %).
行星边界层(PBL)内的垂直混合对于确定地表污染物浓度至关重要。然而,化学传输模型(CTMs)中的标准PBL方案往往无法充分界定垂直混合的上限,尤其是在夜间。这种局限性常常导致地表附近污染物夜间浓度被高估。为解决这一问题,我们提出了一种基于延世大学(YSU)PBL方案推导的混合层高度(MLH)参数化方法,并通过将模拟结果与各种观测数据进行比较来全面评估它。我们利用与GEOS-Chem耦合的天气研究和预报模型(WRF-GC)来模拟2021年空气质量卫星综合联合监测(SIJAQ)活动期间韩国上空的气体和气溶胶分布。纳入MLH参数化的WRF-GC模拟改善了模型中O的过度滴定以及HNO和NO的过量生成。因此,气态和气溶胶模拟中的模型性能与观测结果显示出更好的一致性,NO的归一化平均偏差(NMBs)变化(从50%降至-27%),O的变化(从-49%降至-28%),NO的变化(从126%降至91%),NH的变化(从113%降至85%),BC的变化(从322%降至135%),以及PM的变化(从58%降至28%)。