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Low modeled ozone production suggests underestimation of precursor emissions (especially NOsubix/i/sub) in Europe

机译:较低的模拟臭氧产生量表明低估了欧洲的前体排放量(尤其是NO x

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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 (NOsubix/i/sub) emissions by a factor of 2, (iii)?a combination of the first two scenarios and (iv)?increased traffic-only NOsubix/i/sub emissions by a factor of 4. For southern, eastern, and central (except the Benelux area) Europe, doubling NOsubix/i/sub 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 NOsubix/i/sub emissions are doubled. In the Benelux area, however, the third scenario (where both NOsubix/i/sub and VOC emissions are increased) leads to a better model performance. Although increasing only the traffic NOsubix/i/sub emissions by a factor of 4 gave very similar results to the doubling of all NOsubix/i/sub emissions, the first scenario is more consistent with the uncertainties reported by other studies than the latter, suggesting that high uncertainties in NOsubix/i/sub 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 NOsubix/i/sub) and therefore their uncertainties, which seem to be responsible for the model underestimation of the observed high ozone mixing ratios and ozone production.
机译:高表面臭氧浓度通常发生在发生光化学臭氧生产时,对人类健康和植被构成了巨大风险。决策者通常将空气质量模型用作制定臭氧缓解策略的工具。但是,在许多臭氧建模研究中,对臭氧生产的模拟往往没有得到足够的评估。这项工作的重点是通过利用2010年夏季的臭氧与温度的相关性,间接评估欧洲模拟的臭氧生产,并通过使用区域空气质量模型“综合”来分析其对前体排放和气象的敏感性。带有扩展功能的空气质量模型(CAMx)。结果表明,该模型显着低估了观测到的午后高表面臭氧混合比(≥?? 60?ppb)10–20?ppb,高估了较低的下午表面臭氧混合率(≤?40?ppb)5–15ppb ,导致与平均臭氧观测值的误导性良好协议。对于大多数测量站,该模型还低估了臭氧温度回归斜率约2倍。为了调查排放的影响,测试了四种情况:(i)人为和生物源VOC排放的挥发性有机化合物(VOC)排放分别增加了1.5和2倍;(ii)氮氧化物(NO)的增加了 x )排放量增加了2倍,(iii)前两种情况的组合,以及(iv)仅交通流量NO x 排放量的4倍。对于欧洲南部,东部和中部(比荷卢三国之外的地区),NO x 排放量似乎翻了一番这是减少低观测到的高臭氧混合比而不降低低臭氧混合比的模型性能的最有效方案。当NO x 排放量增加一倍时,臭氧温度相关性的模型性能也更好。但是,在比荷卢经济联盟地区,第三种情况(NO x 和VOC排放均增加)导致更好的模型性能。尽管仅将流量NO x 排放增加4倍,结果却与所有NO x 翻倍的结果非常相似sub x 交通部门,而不是其他部门。通过三个敏感性测试检查了气象学的影响:(i)使表面温度提高4°C,(ii)使风速降低50 %%,并且(iii)使风速提高一倍。前两种情况导致所有表面臭氧混合比的持续增加,从而提高了高臭氧值时的模型性能,但对于低臭氧值时却大大降低了模型性能,而第三种情况则产生了完全相反的效果。总体而言,预计模拟的臭氧对其前驱物排放(尤其是交通NO x )及其不确定性更加敏感,这似乎是造成模型低估的原因。观察到的高臭氧混合比和臭氧产量。

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