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用于在社区多尺度空气质量(CMAQ)模型版本5.1中扩展水相化学的框架。

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1.

作者信息

Fahey Kathleen M, Carlton Annmarie G, Pye Havala O T, Baek Jaemeen, Hutzell William T, Stanier Charles O, Baker Kirk R, Appel K Wyat, Jaoui Mohammed, Offenberg John H

机构信息

Computational Exposure Division, National Exposure Research Laboratory, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA.

Department of Chemistry, University of California, Irvine, Irvine, CA, USA.

出版信息

Geosci Model Dev. 2017;10(4):1587-1605. doi: 10.5194/gmd-10-1587-2017.

Abstract

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM -KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosenbrock solver (Rodas3) to integrate the stiff system of ordinary differential equations (ODEs) that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds. CMAQ's standard cloud chemistry module (AQCHEM) is structurally limited to the treatment of a simple chemical mechanism. This work advances our ability to test and implement more sophisticated aqueous chemical mechanisms in CMAQ and further investigate the impacts of microphysical parameters on cloud chemistry. Box model cloud chemistry simulations were performed to choose efficient solver and tolerance settings, evaluate the implementation of the KPP solver, and assess the direct impacts of alternative solver and kinetic mass transfer on predicted concentrations for a range of scenarios. Month-long CMAQ simulations for winter and summer periods over the US reveal the changes in model predictions due to these cloud module updates within the full chemical transport model. While monthly average CMAQ predictions are not drastically altered between AQCHEM and AQCHEM-KMT, hourly concentration differences can be significant. With added in-cloud secondary organic aerosol (SOA) formation from biogenic epoxides (AQCHEM-KMTI), normalized mean error and bias statistics are slightly improved for 2-methyltetrols and 2-methylglyceric acid at the Research Triangle Park measurement site in North Carolina during the Southern Oxidant and Aerosol Study (SOAS) period. The added in-cloud chemistry leads to a monthly average increase of 11-18 % in "cloud" SOA at the surface in the eastern United States for June 2013.

摘要

本文描述了用于社区多尺度空气质量(CMAQ)建模系统5.1版的可扩展水相化学选项(AQCHEM -KMT(I))的开发与实施。在此,使用了2.2.3版的动力学预处理器(KPP)来生成一个罗森布罗克求解器(Rodas3),以对描述CMAQ云团传质、化学动力学和清除过程的常微分方程(ODE)刚性系统进行积分。CMAQ的标准云化学模块(AQCHEM)在结构上仅限于处理简单的化学机制。这项工作提升了我们在CMAQ中测试和实施更复杂水相化学机制的能力,并进一步研究微物理参数对云化学的影响。进行了箱式模型云化学模拟,以选择高效的求解器和容差设置,评估KPP求解器的实施情况,并评估替代求解器和动力学传质对一系列情景下预测浓度的直接影响。对美国冬季和夏季进行的为期一个月的CMAQ模拟揭示了在完整化学传输模型中由于这些云模块更新而导致的模型预测变化。虽然AQCHEM和AQCHEM -KMT之间的月度平均CMAQ预测没有显著改变,但每小时的浓度差异可能很大。在南方氧化剂和气溶胶研究(SOAS)期间,在北卡罗来纳州研究三角园测量点,随着生物源环氧化物形成的云内二次有机气溶胶(SOA)的增加(AQCHEM -KMTI),2 -甲基四醇和2 -甲基甘油酸的归一化平均误差和偏差统计略有改善。2013年6月,在美国东部,云内化学的增加导致地表“云”SOA每月平均增加11 - 18%。

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