Masiol Mauro, Squizzato Stefania, Chalupa David, Rich David Q, Hopke Philip K
Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY 14642.
Department of Environmental Medicine, University of Rochester Medical Center, Rochester, NY 14642, United States.
Aerosol Air Qual Res. 2018 Aug;18(8):2029-2037. doi: 10.4209/aaqr.2018.02.0056. Epub 2018 Jul 27.
The performance of a low cost ozone monitor (Aeroqual Series 500 portable gas monitors using a metal oxide sensor for ozone; model OZL) was assessed under field conditions. Ten ozone monitors were calibrated under clean-air laboratory conditions and controlled ozone concentrations of 5 to 100 ppb. Good linearity and response were obtained relative to a research-grade ozone monitor. One monitor was co-located at a regulatory air quality monitoring station that uses a U.S. federal equivalent method (FEM) ozone analyzer. Raw data from the Aeroqual monitor collected over 4 months (June-October) at a 10-minute time-resolution, showed good agreement (r=0.83) with the FEM values but with an overestimation of ~12%. Data were averaged to different time resolutions; 1 h time averaged concentrations showed the best fit with the FEM results (r=0.87). Data analyses suggested the potential of interferences due to temperature, relative humidity, nitrogen oxides, and volatile organic compounds. Correction models using temperature, humidity, and nitrogen dioxide (NO) were tested to relate the monitor concentrations to the FEM values. Temperature and humidity were two readily available variables. The model (#3) that added NO did not provide a substantial improvement in the fit. Thus, the models with only temperature and humidity can be easily developed by any user. The best model explained 91% of the variance and showed statistically significant improvement of the goodness of fits as well as decreased influence of the interfering variables on the diurnal and weekly patterns. The correction models were also able to lower the effect of seasonal temperature changes, allowing the use of the monitors over long-term sampling campaigns. Thus, the Aeroqual ozone monitor can return "FEM-like" concentrations after appropriate corrections. Data provided by a network of monitors could provide intra-urban spatial variations in ozone concentrations and provide more accurate human exposure assessments by reducing exposure misclassification.
在实地条件下评估了一种低成本臭氧监测仪（使用金属氧化物传感器的Aeroqual 500系列便携式气体监测仪用于臭氧监测；型号为OZL）的性能。在清洁空气实验室条件下以及5至100 ppb的受控臭氧浓度下对10台臭氧监测仪进行了校准。相对于一台研究级臭氧监测仪，获得了良好的线性和响应。将一台监测仪与一个使用美国联邦等效方法（FEM）臭氧分析仪的空气质量监管监测站放置在一起。在4个月（6月至10月）期间以10分钟时间分辨率收集的Aeroqual监测仪的原始数据，与FEM值显示出良好的一致性（r = 0.83），但高估了约12%。将数据平均到不同的时间分辨率；1小时时间平均浓度与FEM结果显示出最佳拟合（r = 0.87）。数据分析表明存在因温度、相对湿度、氮氧化物和挥发性有机化合物导致干扰的可能性。测试了使用温度、湿度和二氧化氮（NO）的校正模型，以将监测仪浓度与FEM值相关联。温度和湿度是两个容易获取的变量。添加NO的模型（#3）在拟合方面没有带来实质性改善。因此，任何用户都可以轻松开发仅包含温度和湿度的模型。最佳模型解释了91%的方差，显示出拟合优度在统计上有显著改善，同时干扰变量对日变化和周变化模式的影响也有所降低。校正模型还能够降低季节性温度变化的影响，从而允许在长期采样活动中使用这些监测仪。因此，经过适当校正后，Aeroqual臭氧监测仪可以给出“类似FEM”的浓度值。由监测仪网络提供的数据可以提供城市内部臭氧浓度的空间变化，并通过减少暴露错误分类来提供更准确的人体暴露评估。
