Predicting Near-Road PM2.5 Concentrations Comparative Assessment of CALINE4, CAL3QHC, and AERMOD
Predicting Near-Road PM2.5 Concentrations Comparative Assessment of CALINE4, CAL3QHC, and AERMOD
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DOI：
10.3141/2123-04
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发表时间：
2009-01-01
影响因子：
1.7
通讯作者：
Claggett, Michael
中科院分区：
文献类型：
--
作者：
Chen, Hao;Bai, Song;Claggett, Michael
越来越多的科学证据表明，颗粒物（PM）与人类健康的不利影响之间存在关联。因此，准确预测近路PM2.5浓度对于项目级交通一致性和健康风险分析至关重要。本研究评估的能力和性能的三个分散模型-CALINE 4，CAL 3QHC和AERMOD-在预测近道路PM2.5浓度。比较评估包括查明三种模式在方法和数据要求方面的差异。加州萨克拉门托的一个十字路口和伦敦的一条忙碌道路被用作采样点，以评估模型预测与观测到的PM2.5浓度之间的差异。筛选图和统计检验表明，在萨克拉门托站点，CALINE 4和CAL 3QHC表现中等，而AERMOD低于预测的PM2.5浓度。对于伦敦站点，当道路排放源导致的增量浓度较低时，CALINE 4和CAL 3QHC均导致预测过高，而当增量浓度较高时，则发生预测过低。街道峡谷效应和受体位置可能导致伦敦站点模型的性能相对较差。
Scientific evidence has increasingly shown an association between particulate matter (PM) and adverse human health impacts. Accurately predicting near-road PM2.5 concentrations is therefore important for project-level transportation conformity and health risk analysis. This study assessed the capability and performance of three dispersion models-CALINE4, CAL3QHC, and AERMOD-in predicting near-road PM2.5 concentrations. The comparative assessment included identifying differences among the three models in relation to methodology and data requirements. An intersection in Sacramento, California, and a busy road in London were used as sampling sites to evaluate how model predictions differed from observed PM2.5 concentrations. Screen plots and statistical tests indicated that, at the Sacramento site, CALINE4 and CAL3QHC performed moderately well, while AERMOD under-predicted PM2.5 concentrations. For the London site, both CALINE4 and CAL3QHC resulted in overpredictions when incremental concentrations due to on-road emission sources were low, while underpredictions occurred when incremental concentrations were high. The street canyon effect and receptor location likely contributed to the relatively poor performance of the models at the London site.