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Observation and modeling of the evolution of Texas power plant plumes

机译:德克萨斯电厂烟羽演化的观测和建模

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During the second Texas Air Quality Study 2006 (TexAQS II), a full range ofpollutants was measured by aircraft in eastern Texas during successivetransects of power plant plumes (PPPs). A regional photochemical model isapplied to simulate the physical and chemical evolution of the plumes. Theobservations reveal that SO2 and NOy were rapidly removed fromPPPs on a cloudy day but not on the cloud-free days, indicating efficientaqueous processing of these compounds in clouds. The model reasonablyrepresents observed NOx oxidation and PAN formation in the plumes, butfails to capture the rapid loss of SO2 (0.37 h?1) andNOy (0.24 h?1) in some plumes on the cloudy day. Adjustments to thecloud liquid water content (QC) and the default metal concentrations in thecloud module could explain some of the SO2 loss. However, NOy inthe model was insensitive to QC. These findings highlight cloud processingas a major challenge to atmospheric models. Model-based estimates of ozoneproduction efficiency (OPE) in PPPs are 20–50 % lower thanobservation-based estimates for the cloudy day.
机译:在2006年第二次德克萨斯州空气质量研究(TexAQS II)中,德克萨斯州东部的飞机在连续进行电厂羽流(​​PPPs)横断面期间测量了各种污染物。应用区域光化学模型来模拟羽流的物理和化学演化。结果表明,在阴天而不是无云天,SO 2 和NO y 迅速从PPPs中去除,表明这些化合物在云中的高效水处理。该模型合理地代表了观察到的烟气中NO x 的氧化和PAN的形成,但是未能捕获SO 2 的快速损失(0.37 h ?1 )阴天在一些羽流中和NO y (0.24 h ?1 )。调节云模块中的液态水含量(QC)和默认金属浓度可以解释SO 2 的一些损失。然而,模型中的 y 对QC不敏感。这些发现强调了云处理是大气模型的主要挑战。基于模型的PPP中臭氧生产效率(OPE)的估算值比阴天基于观测的估算值低20-50%。

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