Long-term monitoring stations for atmospheric pollutants are often equipped with low-resolution concentration samplers. In this study, we analyse the errors associated with using monthly average ammonia concentrations as input variables for bidirectional biosphere-atmosphere exchange models, which are commonly used to estimate dry deposition fluxes. Previous studies often failed to account for a potential correlation between ammonia exchange velocities and ambient concentrations. We formally derive the exact magnitude of these errors from statistical considerations and propose a correction scheme based on parallel measurements using high-frequency analysers. In case studies using both modelled and measured ammonia concentrations and micrometeorological drivers from sites with varying pollution levels, we were able to substantially reduce bias in the predicted ammonia fluxes. Neglecting to account for these errors can, in some cases, lead to significantly biased deposition estimates compared to using high-frequency instrumentation or corrected averaging strategies. Our study presents a first step towards a unified correction scheme for data from nation-wide air pollutant monitoring networks to be used in chemical transport and air quality models.

中文翻译：

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在估算NH3干沉积通量时使用低分辨率浓度数据的隐性成本。

大气污染物长期监测站通常配备有低分辨率浓度采样器。在这项研究中，我们分析了将每月平均氨浓度用作双向生物圈-大气交换模型输入变量的相关误差，该模型通常用于估算干沉降通量。先前的研究通常无法解释氨交换速度与环境浓度之间的潜在相关性。我们从统计学的角度正式得出这些误差的精确幅度，并基于使用高频分析仪的并行测量结果提出一种校正方案。在案例研究中，使用模拟和测量的氨浓度以及来自不同污染水平的地点的微气象驱动器，我们能够大幅降低预测的氨通量中的偏差。与使用高频仪器或校正后的平均策略相比，在某些情况下忽略这些错误可能会导致沉积估计值明显偏差。我们的研究提出了迈向统一校正方案的第一步，该方案针对来自全国范围的空气污染物监测网络的数据用于化学运输和空气质量模型。