Trend analysis and outlier distribution of CO2 and CH4: A case study at a rural site in northern Spain

CO2 and CH4 outliers may have a noticeable impact on the trend of both gases. Nine years of measurements since 2010 recorded at a rural site in northern Spain were used to investigate these outliers. Their influence on the trend was presented and two limits were established. No more than 23.5% of ou...

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Veröffentlicht in:The Science of the total environment 2022-05, Vol.819, p.153129-153129, Article 153129
Hauptverfasser: Pérez, Isidro A., García, M. Ángeles, Sánchez, M. Luisa, Pardo, Nuria
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Sprache:eng
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Zusammenfassung:CO2 and CH4 outliers may have a noticeable impact on the trend of both gases. Nine years of measurements since 2010 recorded at a rural site in northern Spain were used to investigate these outliers. Their influence on the trend was presented and two limits were established. No more than 23.5% of outliers should be excluded from the measurement series in order to obtain representative trends, which were 2.349 ± 0.012 ppm year−1 for CO2 and 0.00879 ± 0.00004 ppm year−1 for CH4. Two types of outliers were distinguished. Those above the trend line and the rest below the trend line. Outliers were described by skewed distributions where the Weibull distribution figures prominently in most cases. A qualitative procedure was presented to exclude the worst fits, although five statistics were considered to select the best fit. In this case, the modified Nash-Sutcliffe efficiency is prominent. Finally, three symmetrical distributions were added to fit the observations when outliers are excluded, with the Gaussian and beta distributions providing the best fits. As a result, certain skewed functions, such as the lognormal distribution, whose use is frequent for air pollutants, could be questioned in certain applications. [Display omitted] •A fraction of outliers should be excluded to determine the concentration trend.•Outliers can be described by skewed distributions.•The distributions for outliers above or below the trend line may be different.•The modified Nash-Sutcliffe efficiency is a sensitive goodness-of-fit statistic.
ISSN:0048-9697
1879-1026
DOI:10.1016/j.scitotenv.2022.153129