Investigating uncertainties in air quality models used in GMAP/SIJAQ 2021 field campaign: General performance of different models and ensemble results

IF 4.2 2区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
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Abstract

The international field campaign, GMAP/SIJAQ 2021, was conducted in Korea from October 18th to November 25th to enhance the performance and validation of the Geostationary Environment Monitoring Spectrometer (GEMS) products algorithm and obtain a better understanding of the current air pollution status of the Korean Peninsula. Five chemical transport models (CTMs), including CMAQ, CMAQ-GIST, CAMx, WRF-Chem, and WRF GEOS-Chem, were utilized during the campaign to assist in organizing the observation plan and identifying changes in pollutant concentrations and their spatiotemporal distribution in Korea following the Korea–United States Air Quality (KORUS-AQ) 2016. In this study, we evaluated the forecasting performance, strengths, and limitations of these five CTMs and their ensemble in simulating air quality. Intensive measurement data and intercomparisons were employed to explain discrepancies between observed and simulated results. A comparison of the CTM ensemble results for PM2.5 and various gaseous pollutants between the current GMAP/SIJAQ 2021 and previous KORUS-AQ 2016 campaigns showed the R-value for the total mass PM2.5 concentration increased from 0.88 to 0.94. This improvement is related to CTM updates, including the emission inventory and better reproductions of the concentrations of gaseous species. However, the models consistently underestimated carbon monoxide (CO) concentrations, similar to the results from KORUS-AQ. This finding still suggests a further challenge that requires consideration of missing anthropogenic sources. The results of the ensemble model agreed well with the chemical composition of PM2.5 observed at the intensive monitoring station. However, for NO3 and NH4+, discrepancies were primarily due to inaccuracies in the meteorological inputs, such as precipitation, relative humidity (RH), and nighttime planetary boundary layer height (PBLH) in the CTMs. Hence, all models overestimated the concentration of elemental carbon (EC), therefore, it is necessary to revise EC emissions in the SIJAQv2 inventory, as these apply to unusual levels recorded in Seoul during the reference year of 2018.
调查 GMAP/SIJAQ 2021 实地活动中使用的空气质量模型的不确定性:不同模型的一般性能和集合结果
10 月 18 日至 11 月 25 日,在韩国开展了名为 "GMAP/SIJAQ 2021 "的国际实地活动,以提高地球静止环境监测分光仪(GEMS)产品算法的性能和验证,并更好地了解朝鲜半岛当前的空气污染状况。在这次活动中使用了五个化学传输模式(CTMs),包括 CMAQ、CMAQ-GIST、CAMx、WRF-Chem 和 WRF GEOS-Chem,以协助组织观测计划,并确定 2016 年韩美空气质量(KORUS-AQ)之后韩国污染物浓度及其时空分布的变化。在本研究中,我们评估了这五种 CTM 及其集合在模拟空气质量方面的预报性能、优势和局限性。我们采用了大量测量数据和相互比较来解释观测结果和模拟结果之间的差异。对当前的 GMAP/SIJAQ 2021 和之前的 KORUS-AQ 2016 活动中 PM2.5 和各种气态污染物的 CTM 集合结果进行比较后发现,PM2.5 总质量浓度的 R 值从 0.88 增加到了 0.94。这一改进与 CTM 更新有关,包括排放清单和气体物种浓度的更好再现。然而,模型始终低估了一氧化碳(CO)的浓度,这与 KORUS-AQ 的结果类似。这一发现表明,还需要考虑缺失的人为源。集合模型的结果与密集监测站观测到的 PM2.5 化学成分非常吻合。然而,对于 NO3- 和 NH4+,差异主要是由于气象输入的不准确,如 CTM 中的降水、相对湿度(RH)和夜间行星边界层高度(PBLH)。因此,所有模型都高估了元素碳(EC)的浓度,因此有必要修订 SIJAQv2 清单中的元素碳排放量,因为这些排放量适用于 2018 参考年首尔记录的异常水平。
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来源期刊
Atmospheric Environment
Atmospheric Environment 环境科学-环境科学
CiteScore
9.40
自引率
8.00%
发文量
458
审稿时长
53 days
期刊介绍: Atmospheric Environment has an open access mirror journal Atmospheric Environment: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review. Atmospheric Environment is the international journal for scientists in different disciplines related to atmospheric composition and its impacts. The journal publishes scientific articles with atmospheric relevance of emissions and depositions of gaseous and particulate compounds, chemical processes and physical effects in the atmosphere, as well as impacts of the changing atmospheric composition on human health, air quality, climate change, and ecosystems.
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