Epsilon Associates, Inc., 3 Clock Tower Place, Suite 250, Maynard, MA 01754, USA.
J Air Waste Manag Assoc. 2013 Jul;63(7):844-54. doi: 10.1080/10962247.2013.798599.
The U.S. Environmental Protection Agency (EPA) plume volume molar ratio method (PVMRM) and the ozone limiting method (OLM) are in the AERMOD model to predict the 1-hr average NO2/NO(x) concentration ratio. These ratios are multiplied by the AERMOD predicted NO(x) concentration to predict the 1-hr average NO2 concentration. This paper first briefly reviews PVMRM and OLM and points out some scientific parameterizations that could be improved (such as specification of relative dispersion coefficients) and then discusses an evaluation of the PVMRM and OLM methods as implemented in AERMOD using a new data set. While AERMOD has undergone many model evaluation studies in its default mode, PVMRM and OLM are nondefault options, and to date only three NO2 field data sets have been used in their evaluations. Here AERMOD/PVMRM and AERMOD/OLM codes are evaluated with a new data set from a northern Alaskan village with a small power plant. Hourly pollutant concentrations (NO, NO2, ozone) as well as meteorological variables were measured at a single monitor 500 m from the plant. Power plant operating parameters and emissions were calculated based on hourly operator logs. Hourly observations covering 1 yr were considered, but the evaluations only used hours when the wind was in a 60 degrees sector including the monitor and when concentrations were above a threshold. PVMRM is found to have little bias in predictions of the C(NO2)/C(NO(x)) ratio, which mostly ranged from 0.2 to 0.4 at this site. OLM overpredicted the ratio. AERMOD overpredicts the maximum NO(x) concentration but has an underprediction bias for lower concentrations. AERMOD/PVMRM overpredicts the maximum C(NO2) by about 50%, while AERMOD/OLM overpredicts by a factor of 2. For 381 hours evaluated, there is a relative mean bias in C(NO2) predictions of near zero for AERMOD/PVMRM, while the relative mean bias reflects a factor of 2 overprediction for AERMOD/OLM.
This study was initiated because the new stringent 1-hr NO2 NAAQS has prompted modelers to more widely use the PVMRM and OLM methods for conversion of NO(x) to NO2 in the AERMOD regulatory model. To date these methods have been evaluated with a limited number of data sets. This study identified a new data set of ambient pollutant and meteorological monitoring near an isolated power plant in Wainwright, Alaska. To supplement the existing evaluations, this new data were used to evaluate PVMRM and OLM. This new data set has been and will be made available to other scientists for future investigations.
美国环境保护署（EPA）羽流体积摩尔比方法（PVMRM）和臭氧限制方法（OLM）都在 AERMOD 模型中用于预测 1 小时平均的 NO2/NO(x)浓度比。这些比值乘以 AERMOD 预测的 NO(x)浓度，以预测 1 小时平均的 NO2 浓度。本文首先简要回顾了 PVMRM 和 OLM，并指出了一些可以改进的科学参数化（例如相对扩散系数的规范），然后讨论了使用新数据集评估 AERMOD 中 PVMRM 和 OLM 方法的情况。虽然 AERMOD 在其默认模式下已经进行了许多模型评估研究，但 PVMRM 和 OLM 是非默认选项，迄今为止，只有三个 NO2 现场数据集用于它们的评估。在这里，使用来自阿拉斯加北部一个小村庄的新数据集对 AERMOD/PVMRM 和 AERMOD/OLM 代码进行了评估，该村庄有一个小型发电厂。在距离工厂 500 米的一个单一监测器处测量了每小时的污染物浓度（NO、NO2、臭氧）以及气象变量。根据每小时操作员的记录计算了电厂的运行参数和排放量。考虑了 1 年的每小时观测值，但评估仅使用当风向在包括监测器在内的 60 度扇区且浓度高于阈值时的小时数。结果发现，PVMRM 在预测 C(NO2)/C(NO(x))比值方面几乎没有偏差，在该地点，该比值主要在 0.2 到 0.4 之间。OLM 预测的比值过高。AERMOD 过高预测了最大的 NO(x)浓度，但对较低的浓度有低估的偏差。AERMOD/PVMRM 过高预测了最大的 C(NO2)，约为 50%，而 AERMOD/OLM 预测值过高了 2 倍。在评估的 381 个小时中，AERMOD/PVMRM 的 C(NO2)预测值的相对平均偏差接近零，而 AERMOD/OLM 的相对平均偏差反映了 2 倍的过高预测。
这项研究是因为新的严格的 1 小时 NO2 NAAQS 促使建模者更广泛地使用 PVMRM 和 OLM 方法在 AERMOD 监管模型中从 NO(x)转换为 NO2。迄今为止，这些方法已经使用了有限数量的数据集进行了评估。本研究确定了一个新的环境污染物和气象监测数据集，该数据集位于阿拉斯加怀恩赖特的一个孤立的发电厂附近。为了补充现有的评估，本研究使用了新的数据来评估 PVMRM 和 OLM。这个新数据集已经并将提供给其他科学家用于未来的研究。
