Measurement of atmospheric pollen concentrations is inexact, yet pollen concentrations are universally reported without estimate of accuracy. These imprecise values are nevertheless used for modelling, forecasting and public health decision-making. Estimation of the variability in reported pollen concentrations would help resolve associations between weather and pollen aerobiology as well as associations between pollen exposure and health. For any given daily atmospheric pollen level, a statistical variability would be expected in the set of possible measures. This variability is introduced and compounded by many factors including human error, classification error or instrument variability, as well as variability derived from strategies used to count and scale the airborne pollen sample. Here, we performed numeric simulations of pollen deposition and modelled the variability in contemporary pollen density estimates. Statistical distribution of the mean and variance of these simulated counts was compared with an existing pollen count dataset. Both simulations and actual pollen data showed that a significant range of atmospheric pollen concentrations could be inferred from the same daily pollen collection. The range of possible concentrations varied both with the atmospheric pollen density and with the portion of the daily pollen sample that is counted. Furthermore, pollen concentration data were shown to be non-normal and heteroscedastic, which has implications for a variety of tests (e.g. ANOVA), for regression analysis, and for pollen forecasting and forecast verification. These results reinforce the importance of counting as much of the collected pollen impaction surface as feasible to minimise the uncertainty in reported pollen levels. The outcomes of this study suggest that confidence intervals for daily pollen concentrations should be reported.

中文翻译：

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标准化花粉监测：量化空气中花粉浓度测量的置信区间

大气花粉浓度的测量是不准确的，但花粉浓度的报告普遍存在，而没有估计准确度。尽管如此，这些不精确的值仍用于建模、预测和公共卫生决策。估计报告的花粉浓度的可变性将有助于解决天气与花粉空气生物学之间的关联以及花粉暴露与健康之间的关联。对于任何给定的每日大气花粉水平，在一组可能的测量中预计会出现统计变化。这种可变性是由许多因素引入并加剧的，包括人为错误、分类错误或仪器可变性，以及源自用于计数和缩放空气传播花粉样本的策略的可变性。这里，我们对花粉沉积进行了数值模拟，并对当代花粉密度估计的变异性进行了建模。将这些模拟计数的平均值和方差的统计分布与现有的花粉计数数据集进行比较。模拟和实际花粉数据都表明，可以从相同的每日花粉收集推断出大气花粉浓度的显着范围。可能的浓度范围随大气花粉密度和每日花粉样本的计数而变化。此外，花粉浓度数据被证明是非正态和异方差的，这对各种测试（例如方差分析）、回归分析以及花粉预测和预测验证都有影响。这些结果强调了尽可能多地计算收集到的花粉撞击表面的重要性，以最大限度地减少报告的花粉水平的不确定性。这项研究的结果表明，应该报告每日花粉浓度的置信区间。