Collingwood Scott, Zmoos Jesse, Pahler Leon, Wong Bob, Sleeth Darrah, Handy Rodney
Department of Pediatrics, University of Utah, Salt Lake City, UT 84108.
Rocky Mountain Center for Occupational & Environmental Health, Department of Family & Preventive Medicine, University of Utah, Salt Lake City, UT 84108.
J Aerosol Sci. 2019 Sep;135:21-32. doi: 10.1016/j.jaerosci.2019.04.017. Epub 2019 Apr 26.
Particulate matter (PM) has demonstrably increased rates of cardiovascular and respiratory related disease; thus, a low-cost sensor that accurately measures PM is desirable including for smaller and more private environments such as residential homes. The low-cost Dylos and the Utah Modified Dylos Sensor (UMDS) have been shown to be highly correlated with references instruments for measuring particle counts and aerosol concentrations, which makes them useful tools for air quality studies. An analytical calibration equation (calibration) is used to describe the linear relationship between the UMDS and a reference instrument, providing the best estimate of PM concentrations when the UMDS is operated. In this study, an investigation of measurement variation of a UMDS was performed using a low-cost calibration technique to determine differences between the brand new UMDS pre-calibration equation (Pre), a contaminated UMDS post-calibration equation (Post), and a cleaned UMDS clean calibration equation (CC). The UMDS were calibrated against a high-grade aerosol spectrometer (Grimm model 1.109) as a reference instrument. Calibrations took place in a home or office environment. Counts per volume units from the UMDS were matched to the Grimm's for comparison. The investigation of the UMDS for measurement variation was performed for the approximate estimates of PM by using the small bin (i.e. ≥0.50μm) subtracted from the large bin (i.e. ≥2.5μm), and for total particulates by using the large bin. Linear regressions were performed between the UMDS and the Grimm per calibration event, which produced R values and slopes that were indicative of measurement variation. Data exceeding the upper limit of quantification (ULOQ) of 106,000 particles/liter and the lower limit of quantification (LLOQ) of 4 particles/liter were excluded from statistical comparison. R values greater or equal to 0.70 were used to assess measurement variation as a quality control standard for valid comparisons. A rank sum statistical test between calibration comparisons was performed. Pre/Post and Pre/CC had significant differences indicating measurement variation. Post/CC did not have any significant differences; cleaning the UMDS had no effect and did not demonstrate measurement variation. Reasons for measurement variation may include instrument contamination (dust/dirt), hardware degradation, altered fan flow rates, and potentially inadequate cleaning of the UMDS. Future work may investigate the rate of measurement variation in order to develop a recommended re-calibration schedule in order to maintain the most accurate estimates of PM for UMDS in long-term operation.
颗粒物(PM)已显著增加了心血管和呼吸系统相关疾病的发病率;因此,需要一种低成本的传感器来精确测量PM,包括在诸如住宅等较小且更私密的环境中。已证明低成本的戴洛斯传感器(Dylos)和犹他改良戴洛斯传感器(UMDS)与用于测量颗粒计数和气溶胶浓度的参考仪器高度相关,这使其成为空气质量研究的有用工具。一个分析校准方程(校准)用于描述UMDS与参考仪器之间的线性关系,在UMDS运行时提供PM浓度的最佳估计值。在本研究中,使用低成本校准技术对UMDS的测量变化进行了调查,以确定全新的UMDS校准前方程(Pre)、受污染的UMDS校准后方程(Post)和清洁后的UMDS清洁校准方程(CC)之间的差异。将UMDS与一台高级气溶胶光谱仪(格林模型1.109)作为参考仪器进行校准。校准在家庭或办公室环境中进行。将UMDS的每体积单位计数与格林仪器的计数进行匹配以作比较。通过使用从大粒径范围(即≥2.5μm)中减去小粒径范围(即≥0.50μm)来对PM进行近似估计,并通过使用大粒径范围来对总颗粒物进行测量变化的调查。在每次校准事件中,对UMDS和格林仪器之间进行线性回归,得出的R值和斜率可表明测量变化。超过106,000颗粒/升的定量上限(ULOQ)和4颗粒/升的定量下限(LLOQ)的数据被排除在统计比较之外。R值大于或等于0.70用于评估测量变化,作为有效比较的质量控制标准。在校准比较之间进行了秩和统计检验。Pre/Post和Pre/CC存在显著差异,表明存在测量变化。Post/CC没有任何显著差异;清洁UMDS没有效果,也未显示出测量变化。测量变化的原因可能包括仪器污染(灰尘/污垢)、硬件退化、风扇流速改变以及UMDS可能清洁不充分。未来的工作可能会研究测量变化的速率,以便制定推荐的重新校准时间表,从而在长期运行中保持对UMDS的PM最准确估计。