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改进的方法计算在不完全数据覆盖情况下环境空气污染物的年平均值。

Improved strategies for calculating annual averages of ambient air pollutants in cases of incomplete data coverage.

机构信息

Analytical Science Division, National Physical Laboratory, Hampton Road, Teddington, Middlesex TW11 0LW, UK.

出版信息

Environ Sci Process Impacts. 2013 May;15(5):904-11. doi: 10.1039/c3em00039g.

Abstract

The consequences of missing data during air quality monitoring activities and the calculation of the annual average mass concentration of ambient pollutants are discussed. Possible strategies for mitigating totally and partially missing data during given measurement periods are presented and evaluated. A mathematical description of a preferred method for the determination of annual average concentration using the simple mean, and not using time weighting to account for missing data, is justified. It is hoped this discussion paper will provoke debate in the air quality community about the best way to assess measured concentrations of ambient pollutants against legislative values.

摘要

讨论了空气质量监测活动和环境污染物年平均质量浓度计算过程中数据缺失的后果。提出并评估了在给定测量期间减轻完全和部分数据缺失的可能策略。使用简单平均值而不是使用时间加权来考虑缺失数据来确定年平均浓度的首选方法的数学描述是合理的。希望本讨论文件能引发空气质量界关于如何根据立法值评估环境污染物测量浓度的最佳方法的辩论。

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