The impact of nudging coefficient for the initialization on the atmospheric flow field and the photochemical ozone concentration of Seoul, Korea

Choi, Hyun‐Jung; Lee, Hwa Woon; Sung, Kyoung-Hee; Minjung, Kim; Kim, Yoo-Keun; Jung, Woo‐Sik

doi:10.1016/j.atmosenv.2009.05.051

Cited by 12 publications

(11 citation statements)

References 9 publications

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“…First, four‐dimensional data assimilation (FDDA), including grid analysis nudging and observational nudging, was applied; this continuous dynamical assimilation could reduce the model uncertainties and thereby increase the modeling accuracy. The effects of FDDA on the simulated meteorological fields and predicted O 3 concentrations have been investigated in previous studies [e.g., Barna and Lamb , 2000; Choi et al , 2009]. Grid analysis nudging using the National Center for Environmental Protection (NCEP) 1° × 1° reanalysis data was applied on the outermost domain [ Stauffer and Seaman , 1990], while observational nudging was applied in the finest domain [ Liu et al , 2005].…”

Section: Methodsmentioning

confidence: 99%

An ozone episode in the Pearl River Delta: Field observation and model simulation

Jiang¹,

Guo²,

Wang³

et al. 2010

J. Geophys. Res.

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[1] In the fall of 2007 concurrent air sampling field measurements were conducted for the first time in Guangzhou (at Wan Qing Sha (WQS)) and Hong Kong (at Tung Chung (TC)), two cities in the rapidly developing Pearl River Delta region of China that are only 62 km apart. This region is known to suffer from poor air quality, especially during the autumn and winter months, when the prevailing meteorological conditions bring an outflow of continental air to the region. An interesting multiday O 3 pollution event (daily maximum O 3 > 122 ppbv) was captured during 9-17 November at WQS, while only one O 3 episode day (10 November) was observed at TC during this time. The mean O 3 mixing ratios at TC and WQS during the episode were 38 ± 3 (mean ± 95% confidence interval) and 51 ± 7 ppbv, respectively, with a mean difference of 13 ppbv and a maximum hourly difference of 150 ppbv. We further divided this event into two periods: 9-11 November as Period 1 and 12-17 November as Period 2. The mixing ratios of O 3 and its precursors (NO x and CO) showed significant differences between the two periods at TC. By contrast, no obvious difference was found at WQS, indicating that different air masses arrived at TC for the two periods, as opposed to similar air masses at WQS for both periods. The analysis of VOC ratios and their relationship with O 3 revealed strong O 3 production at WQS during Period 2, in contrast to relatively weak photochemical O 3 formation at TC. The weather conditions implied regional transport of O 3 pollution during Period 1 at both sites. Furthermore, a comprehensive air quality model system (Weather Research and Forecasting-Community Multiscale Air Quality model (WRF-CMAQ)) was used to simulate this O 3 pollution event. The model system generally reproduced the variations of weather conditions, simulated well the continuous high O 3 episode event at WQS, and captured fairly well the elevated O 3 mixing ratios in Period 1 and low O 3 levels in Period 2 at TC. The modeled surface O 3 distributions and flow structures clearly illustrated the occurrence of O 3 formation and the impact of regional transport on O 3 levels in Period 1 in the Pearl River Delta. Further analysis of O 3 formation indicated that horizontal transport was the main contributor to the O 3 increase at TC during Period 1, while at WQS O 3 levels were dominated by photochemical production during both periods. The low O 3 levels at TC during Period 2 were attributable to lower temperatures and the arrival of fresh maritime air masses brought in by strong easterly winds. This study highlights how contrasting precursor concentrations and photochemical conditions can occur over a very small distance, and it provides a rare opportunity to better understand ozone production and precursor source origins on a finer scale in this region.

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Section: Methodsmentioning

confidence: 99%

An ozone episode in the Pearl River Delta: Field observation and model simulation

Jiang¹,

Guo²,

Wang³

et al. 2010

J. Geophys. Res.

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“…Moreover, O 3 , which is the main fo- (Bessagnet et al, 2016). Possible reasons for this behavior, as also discussed in Ciarelli et al (2016), can be the injection height of the SO 2 emissions from high-stack point sources which are placed in the first model layer (i.e., up to 20 m), especially near the harbors and coastal areas, as well as insufficient conversion to sulfate and deposition processes. The CO concentrations were underestimated (MB and MGE were close in absolute terms and correlation was poor).…”

Section: Model Performance Evaluationmentioning

confidence: 98%

Low modeled ozone production suggests underestimation of precursor emissions (especially NOx) in Europe

Oikonomakis¹,

Aksoyoğlu²,

Ciarelli³

et al. 2017

Preprint

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Abstract. High surface ozone concentrations, which usually occur when photochemical ozone production takes place, pose a great risk to human health and vegetation. Air quality models are often used by policy makers as tools for the development of ozone mitigation strategies. However, the modeled ozone production is often not or not enough evaluated in many ozone modelling studies. The focus of this work is to evaluate the modeled ozone production in Europe indirectly, with the use of the ozone&#8211;temperature correlation for the summer of 2010 and to analyze its sensitivity to precursor emissions and meteorology by using the regional air quality model, CAMx. The results show that the model significantly underestimates the observed high afternoon surface ozone mixing ratios (&#8805;&#8201;60&#8201;ppb) by 10&#8211;20&#8201;ppb and overestimates the lower ones (<&#8201;40&#8201;ppb) by 5&#8211;15&#8201;ppb, resulting in a misleading good agreement with the observations for average ozone. The model also underestimates the ozone&#8211;temperature regression slope by about a factor of 2 for most of the measurement stations. To investigate the impact of emissions, three scenarios were tested: (i) increased VOC emissions by a factor of 1.5 and 2 for the anthropogenic and biogenic VOC emissions, respectively, (ii) increased NO<sub<x emissions by a factor of 2, and (iii) a combination of the first two scenarios. For southern and central (except the Benelux area) Europe, doubling NOx emissions seems to be the most efficient scenario to reduce the underestimation of the observed high ozone mixing ratios without significant degradation of the model performance for the lower ozone mixing ratios. The model performance for ozone&#8211;temperature correlation is also better when NOx emissions are doubled. In the Benelux area, however, the third scenario (where both NOx and VOC emissions are increased) leads to a better model performance. The impact of meteorology was examined with two sensitivity tests: (i) increased surface temperature by 4&#8201;&#176;C, and (ii) reduced wind speed by 50&#8201;%. Both scenarios lead to a consistent increase in all surface ozone mixing ratios, thus improving the model performance for the high ozone values but significantly degrading it for the low ozone values. Overall, the modeled ozone is predicted to be more sensitive to its precursor emissions (especially NOx) and therefore their uncertainties, which seem to be responsible for the model underestimation of the observed high ozone mixing ratios and ozone production.

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“…The same data were also used for four-dimensional data assimilation (FDDA) above the planetary boundary layer (PBL) in the WRF simulations. Moreover, the observational nudging in the meteorological simulations (i.e., the use of FDDA) has been shown to improve the prediction of ozone by the air quality models (Choi et al, 2009). The model was run as a 48 h forecast and was then re-initialized.…”

Section: Meteorologymentioning

confidence: 99%

Low modeled ozone production suggests underestimation of precursor emissions (especially NOx) in Europe

et al. 2018

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Abstract. High surface ozone concentrations, which usually occur when photochemical ozone production takes place, pose a great risk to human health and vegetation. Air quality models are often used by policy makers as tools for the development of ozone mitigation strategies. However, the modeled ozone production is often not or not enough evaluated in many ozone modeling studies. The focus of this work is to evaluate the modeled ozone production in Europe indirectly, with the use of the ozone-temperature correlation for the summer of 2010 and to analyze its sensitivity to precursor emissions and meteorology by using the regional air quality model, the Comprehensive Air Quality Model with Extensions (CAMx). The results show that the model significantly underestimates the observed high afternoon surface ozone mixing ratios (≥ 60 ppb) by 10-20 ppb and overestimates the lower ones (< 40 ppb) by 5-15 ppb, resulting in a misleading good agreement with the observations for average ozone. The model also underestimates the ozone-temperature regression slope by about a factor of 2 for most of the measurement stations. To investigate the impact of emissions, four scenarios were tested: (i) increased volatile organic compound (VOC) emissions by a factor of 1.5 and 2 for the anthropogenic and biogenic VOC emissions, respectively, (ii) increased nitrogen oxide (NO x ) emissions by a factor of 2, (iii) a combination of the first two scenarios and (iv) increased trafficonly NO x emissions by a factor of 4. For southern, eastern, and central (except the Benelux area) Europe, doubling NO x emissions seems to be the most efficient scenario to reduce the underestimation of the observed high ozone mixing ratios without significant degradation of the model performance for the lower ozone mixing ratios. The model performance for ozone-temperature correlation is also better when NO x emissions are doubled. In the Benelux area, however, the third scenario (where both NO x and VOC emissions are increased) leads to a better model performance. Although increasing only the traffic NO x emissions by a factor of 4 gave very similar results to the doubling of all NO x emissions, the first scenario is more consistent with the uncertainties reported by other studies than the latter, suggesting that high uncertainties in NO x emissions might originate mainly from the road-transport sector rather than from other sectors. The impact of meteorology was examined with three sensitivity tests: (i) increased surface temperature by 4 • C, (ii) reduced wind speed by 50 % and (iii) doubled wind speed. The first two scenarios led to a consistent increase in all surface ozone mixing ratios, thus improving the model performance for the high ozone values but significantly degrading it for the low ozone values, while the third scenario had exactly the opposite effects. Overall, the modeled ozone is predicted to be more sensitive to its precursor emissions (especially traffic NO x ) and therefore their uncertainties, which seem to be responsible for the model un...

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The impact of nudging coefficient for the initialization on the atmospheric flow field and the photochemical ozone concentration of Seoul, Korea

Cited by 12 publications

References 9 publications

An ozone episode in the Pearl River Delta: Field observation and model simulation

An ozone episode in the Pearl River Delta: Field observation and model simulation

Low modeled ozone production suggests underestimation of precursor emissions (especially NO<sub>x</sub>) in Europe

Low modeled ozone production suggests underestimation of precursor emissions (especially NO<sub><i>x</i></sub>) in Europe

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The impact of nudging coefficient for the initialization on the atmospheric flow field and the photochemical ozone concentration of Seoul, Korea

Cited by 12 publications

References 9 publications

An ozone episode in the Pearl River Delta: Field observation and model simulation

An ozone episode in the Pearl River Delta: Field observation and model simulation

Low modeled ozone production suggests underestimation of precursor emissions (especially NO&lt;sub&gt;x&lt;/sub&gt;) in Europe

Low modeled ozone production suggests underestimation of precursor emissions (especially NO&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt;) in Europe

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Low modeled ozone production suggests underestimation of precursor emissions (especially NO<sub>x</sub>) in Europe

Low modeled ozone production suggests underestimation of precursor emissions (especially NO<sub><i>x</i></sub>) in Europe