Application and Evaluation of Two Air Quality Models for Particulate Matter for a Southeastern U.S. Episode
Application and Evaluation of Two Air Quality Models for Particulate Matter for a Southeastern U.S. Episode
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DOI：
10.1080/10473289.2004.10471012
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发表时间：
2004-12
影响因子：
2.7
通讯作者：
Yang Zhang;B. Pun;Shiang-Yuh Wu;K. Vijayaraghavan;C. Seigneur
中科院分区：
文献类型：
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作者：
Yang Zhang;B. Pun;Shiang-Yuh Wu;K. Vijayaraghavan;C. Seigneur
摘要应用Models-3社区多尺度空气质量（CMAQ）模拟系统和扩展的颗粒物综合空气质量模式（PMCAMx）模拟了1999年6月29日至7月10日南方氧化剂研究事件，两种嵌套水平网格尺寸：32 km的粗分辨率和8 km的细分辨率。臭氧（O3）、空气动力学直径小于或等于2.5 μm的颗粒物的预测空间变化在美国东部和南部的一些城市/郊区，两个模型得出的空气动力学直径小于或等于10 μm的颗粒物（PM2.5）和颗粒物（PM10）在农村地区相似，但彼此之间存在显著差异，其中PMCAMx倾向于预测比CMAQ更高的O3和PM值。两种模型都倾向于预测高于观察到的O3值。对于超过60 ppb的O3观测值，O3性能符合美国环境保护署的CMAQ标准（使用两种格栅）和PMCAMx标准（仅使用细格栅）。当观察到的O3值超过40 ppb时，PMCAMx变得不令人满意，CMAQ略微令人满意。两个模型预测的硫酸盐（SO 4 2−）和有机物的含量相似，并且都预测SO 4 2−是PM2.5的最大贡献者。PMCAMx通常预测铵（NH 4+），硝酸盐（NO3 −）和黑碳（BC）的含量高于CMAQ。CMAQ的PM性能通常与其他PM模型一致，而PMCAMx预测的NO3-、NH 4+和BC浓度高于观察值，这降低了其性能。对于美国东南部地区的PM10和PM2.5预测，CMAQ的平均归一化粗差（MNGE）和平均归一化偏差的范围为37-43%和-33-4%，PMCAMx为50-59%和7-30%。两个模型都预测了NO3 −的最大MNGE（CMAQ为98-104%，PMCAMx为138-338%）。两种模型的NO3 −预测不准确可能是由于氨排放清单的不准确性和某些条件下气体/颗粒分配的不确定性造成的。除了这些不确定性，PMCAMx的显着PM overpredictions可能是由于缺乏湿去除PM和可能的低估在白天的垂直混合。
Abstract The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29–July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O3), particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 μm (PM10) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O3 and PM than CMAQ. Both models tend to predict O3 values that are higher than those observed. For observed O3 values above 60 ppb, O3 performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O3 values above 40 ppb. Both models predict similar amounts of sulfate (SO4 2−) and organic matter, and both predict SO4 2− to be the largest contributor to PM2.5. PMCAMx generally predicts higher amounts of ammonium (NH4 +), nitrate (NO3 −), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO3 −,NH4 +, and BC than observed, which degrades its performance. For PM10 and PM2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37–43% and –33–4% for CMAQ and 50–59% and 7–30% for PMCAMx. Both models predict the largest MNGEs for NO3 − (98–104% for CMAQ, 138–338% for PMCAMx). The inaccurate NO3 − predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.