Chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances
Background Chemical surveillance in surface waters is crucial to identify potential threats to the health of freshwater ecosystems. Usually, the concentrations of pollutants are highly variable over the course of the year and often result in non-normally distributed data sets. Therefore, the Europea...
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Gespeichert in:
| Autor*in: |
Babitsch, Denise [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2020 |
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| Übergeordnetes Werk: |
Enthalten in: Umweltwissenschaften und Schadstoff-Forschung - Heidelberg : Springer, 1989, 32(2020), 1 vom: 16. Jan. |
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| Übergeordnetes Werk: |
volume:32 ; year:2020 ; number:1 ; day:16 ; month:01 |
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| DOI / URN: |
10.1186/s12302-019-0285-y |
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SPR024868043 |
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| 520 | |a Background Chemical surveillance in surface waters is crucial to identify potential threats to the health of freshwater ecosystems. Usually, the concentrations of pollutants are highly variable over the course of the year and often result in non-normally distributed data sets. Therefore, the European Water Framework Directive recommends measuring, e.g. priority substances at least 12 times a year to achieve an acceptable accuracy level for the estimation of the true mean annual loads. However, in Europe priority substances are often measured much less frequently. In this context, the aim of the present study was to analyze how sample size, temporal variability and skewness of the data sets influence the accuracy of the mean annual load estimation and the assessment of annual average environmental quality standards. For this purpose, sample size simulations using weekly composite samples of benzo(a)pyrene, 4-tert-octylphenol, fluoranthene and di(2-ethylhexyl) phthalate, selected as representatives for priority substances, were carried out. Results The sample size simulations showed two general patterns: the accuracy of the mean annual load estimation increased with increasing sample size and skewness and temporal variability were more apparent in smaller sample sizes. In right-skewed data sets, small sample sizes led, on average, to a systematic underestimation of the true mean annual load whilst in a few cases these led to an overestimation. Although the study was carried out on priority substances, results can be transferable to other pollutants. Furthermore, in small sample sizes a considerable proportion of the simulated means failed to detect annual average environmental quality standard exceedances. Conclusions The results of the present study indicate that the usage of small sample sizes is likely to result in an underestimation of the true mean annual pollutant loads in chemical surveillance and scientific research, thus potentially jeopardizing the validity of results. Therefore, it is recommended to avoid the usage of small sample sizes for the determination of mean annual pollutant loads. Furthermore, priority substances should be sampled according to the European Water Framework Directive guidelines at least 12 times/year to improve the assessment of the threat posed by pollutants to freshwater ecosystems in Europe. | ||
| 650 | 4 | |a Micropollutant |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Priority substance |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Sample size simulation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Monitoring |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Weekly composite sample |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Accuracy assessment |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Uncertainty |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a European Water Framework Directive |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Temporal variability |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Sundermann, Andrea |4 aut | |
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10.1186/s12302-019-0285-y doi (DE-627)SPR024868043 (SPR)s12302-019-0285-y-e DE-627 ger DE-627 rakwb eng Babitsch, Denise verfasserin (orcid)0000-0003-2211-1601 aut Chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2020 Background Chemical surveillance in surface waters is crucial to identify potential threats to the health of freshwater ecosystems. Usually, the concentrations of pollutants are highly variable over the course of the year and often result in non-normally distributed data sets. Therefore, the European Water Framework Directive recommends measuring, e.g. priority substances at least 12 times a year to achieve an acceptable accuracy level for the estimation of the true mean annual loads. However, in Europe priority substances are often measured much less frequently. In this context, the aim of the present study was to analyze how sample size, temporal variability and skewness of the data sets influence the accuracy of the mean annual load estimation and the assessment of annual average environmental quality standards. For this purpose, sample size simulations using weekly composite samples of benzo(a)pyrene, 4-tert-octylphenol, fluoranthene and di(2-ethylhexyl) phthalate, selected as representatives for priority substances, were carried out. Results The sample size simulations showed two general patterns: the accuracy of the mean annual load estimation increased with increasing sample size and skewness and temporal variability were more apparent in smaller sample sizes. In right-skewed data sets, small sample sizes led, on average, to a systematic underestimation of the true mean annual load whilst in a few cases these led to an overestimation. Although the study was carried out on priority substances, results can be transferable to other pollutants. Furthermore, in small sample sizes a considerable proportion of the simulated means failed to detect annual average environmental quality standard exceedances. Conclusions The results of the present study indicate that the usage of small sample sizes is likely to result in an underestimation of the true mean annual pollutant loads in chemical surveillance and scientific research, thus potentially jeopardizing the validity of results. Therefore, it is recommended to avoid the usage of small sample sizes for the determination of mean annual pollutant loads. Furthermore, priority substances should be sampled according to the European Water Framework Directive guidelines at least 12 times/year to improve the assessment of the threat posed by pollutants to freshwater ecosystems in Europe. Micropollutant (dpeaa)DE-He213 Priority substance (dpeaa)DE-He213 Sample size simulation (dpeaa)DE-He213 Monitoring (dpeaa)DE-He213 Weekly composite sample (dpeaa)DE-He213 Accuracy assessment (dpeaa)DE-He213 Uncertainty (dpeaa)DE-He213 European Water Framework Directive (dpeaa)DE-He213 Temporal variability (dpeaa)DE-He213 Sundermann, Andrea aut Enthalten in Umweltwissenschaften und Schadstoff-Forschung Heidelberg : Springer, 1989 32(2020), 1 vom: 16. Jan. (DE-627)319337200 (DE-600)2014183-X 1865-5084 nnns volume:32 year:2020 number:1 day:16 month:01 https://dx.doi.org/10.1186/s12302-019-0285-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_60 GBV_ILN_95 GBV_ILN_370 GBV_ILN_2360 AR 32 2020 1 16 01 |
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10.1186/s12302-019-0285-y doi (DE-627)SPR024868043 (SPR)s12302-019-0285-y-e DE-627 ger DE-627 rakwb eng Babitsch, Denise verfasserin (orcid)0000-0003-2211-1601 aut Chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2020 Background Chemical surveillance in surface waters is crucial to identify potential threats to the health of freshwater ecosystems. Usually, the concentrations of pollutants are highly variable over the course of the year and often result in non-normally distributed data sets. Therefore, the European Water Framework Directive recommends measuring, e.g. priority substances at least 12 times a year to achieve an acceptable accuracy level for the estimation of the true mean annual loads. However, in Europe priority substances are often measured much less frequently. In this context, the aim of the present study was to analyze how sample size, temporal variability and skewness of the data sets influence the accuracy of the mean annual load estimation and the assessment of annual average environmental quality standards. For this purpose, sample size simulations using weekly composite samples of benzo(a)pyrene, 4-tert-octylphenol, fluoranthene and di(2-ethylhexyl) phthalate, selected as representatives for priority substances, were carried out. Results The sample size simulations showed two general patterns: the accuracy of the mean annual load estimation increased with increasing sample size and skewness and temporal variability were more apparent in smaller sample sizes. In right-skewed data sets, small sample sizes led, on average, to a systematic underestimation of the true mean annual load whilst in a few cases these led to an overestimation. Although the study was carried out on priority substances, results can be transferable to other pollutants. Furthermore, in small sample sizes a considerable proportion of the simulated means failed to detect annual average environmental quality standard exceedances. Conclusions The results of the present study indicate that the usage of small sample sizes is likely to result in an underestimation of the true mean annual pollutant loads in chemical surveillance and scientific research, thus potentially jeopardizing the validity of results. Therefore, it is recommended to avoid the usage of small sample sizes for the determination of mean annual pollutant loads. Furthermore, priority substances should be sampled according to the European Water Framework Directive guidelines at least 12 times/year to improve the assessment of the threat posed by pollutants to freshwater ecosystems in Europe. Micropollutant (dpeaa)DE-He213 Priority substance (dpeaa)DE-He213 Sample size simulation (dpeaa)DE-He213 Monitoring (dpeaa)DE-He213 Weekly composite sample (dpeaa)DE-He213 Accuracy assessment (dpeaa)DE-He213 Uncertainty (dpeaa)DE-He213 European Water Framework Directive (dpeaa)DE-He213 Temporal variability (dpeaa)DE-He213 Sundermann, Andrea aut Enthalten in Umweltwissenschaften und Schadstoff-Forschung Heidelberg : Springer, 1989 32(2020), 1 vom: 16. Jan. (DE-627)319337200 (DE-600)2014183-X 1865-5084 nnns volume:32 year:2020 number:1 day:16 month:01 https://dx.doi.org/10.1186/s12302-019-0285-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_60 GBV_ILN_95 GBV_ILN_370 GBV_ILN_2360 AR 32 2020 1 16 01 |
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10.1186/s12302-019-0285-y doi (DE-627)SPR024868043 (SPR)s12302-019-0285-y-e DE-627 ger DE-627 rakwb eng Babitsch, Denise verfasserin (orcid)0000-0003-2211-1601 aut Chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2020 Background Chemical surveillance in surface waters is crucial to identify potential threats to the health of freshwater ecosystems. Usually, the concentrations of pollutants are highly variable over the course of the year and often result in non-normally distributed data sets. Therefore, the European Water Framework Directive recommends measuring, e.g. priority substances at least 12 times a year to achieve an acceptable accuracy level for the estimation of the true mean annual loads. However, in Europe priority substances are often measured much less frequently. In this context, the aim of the present study was to analyze how sample size, temporal variability and skewness of the data sets influence the accuracy of the mean annual load estimation and the assessment of annual average environmental quality standards. For this purpose, sample size simulations using weekly composite samples of benzo(a)pyrene, 4-tert-octylphenol, fluoranthene and di(2-ethylhexyl) phthalate, selected as representatives for priority substances, were carried out. Results The sample size simulations showed two general patterns: the accuracy of the mean annual load estimation increased with increasing sample size and skewness and temporal variability were more apparent in smaller sample sizes. In right-skewed data sets, small sample sizes led, on average, to a systematic underestimation of the true mean annual load whilst in a few cases these led to an overestimation. Although the study was carried out on priority substances, results can be transferable to other pollutants. Furthermore, in small sample sizes a considerable proportion of the simulated means failed to detect annual average environmental quality standard exceedances. Conclusions The results of the present study indicate that the usage of small sample sizes is likely to result in an underestimation of the true mean annual pollutant loads in chemical surveillance and scientific research, thus potentially jeopardizing the validity of results. Therefore, it is recommended to avoid the usage of small sample sizes for the determination of mean annual pollutant loads. Furthermore, priority substances should be sampled according to the European Water Framework Directive guidelines at least 12 times/year to improve the assessment of the threat posed by pollutants to freshwater ecosystems in Europe. Micropollutant (dpeaa)DE-He213 Priority substance (dpeaa)DE-He213 Sample size simulation (dpeaa)DE-He213 Monitoring (dpeaa)DE-He213 Weekly composite sample (dpeaa)DE-He213 Accuracy assessment (dpeaa)DE-He213 Uncertainty (dpeaa)DE-He213 European Water Framework Directive (dpeaa)DE-He213 Temporal variability (dpeaa)DE-He213 Sundermann, Andrea aut Enthalten in Umweltwissenschaften und Schadstoff-Forschung Heidelberg : Springer, 1989 32(2020), 1 vom: 16. Jan. (DE-627)319337200 (DE-600)2014183-X 1865-5084 nnns volume:32 year:2020 number:1 day:16 month:01 https://dx.doi.org/10.1186/s12302-019-0285-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_60 GBV_ILN_95 GBV_ILN_370 GBV_ILN_2360 AR 32 2020 1 16 01 |
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10.1186/s12302-019-0285-y doi (DE-627)SPR024868043 (SPR)s12302-019-0285-y-e DE-627 ger DE-627 rakwb eng Babitsch, Denise verfasserin (orcid)0000-0003-2211-1601 aut Chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2020 Background Chemical surveillance in surface waters is crucial to identify potential threats to the health of freshwater ecosystems. Usually, the concentrations of pollutants are highly variable over the course of the year and often result in non-normally distributed data sets. Therefore, the European Water Framework Directive recommends measuring, e.g. priority substances at least 12 times a year to achieve an acceptable accuracy level for the estimation of the true mean annual loads. However, in Europe priority substances are often measured much less frequently. In this context, the aim of the present study was to analyze how sample size, temporal variability and skewness of the data sets influence the accuracy of the mean annual load estimation and the assessment of annual average environmental quality standards. For this purpose, sample size simulations using weekly composite samples of benzo(a)pyrene, 4-tert-octylphenol, fluoranthene and di(2-ethylhexyl) phthalate, selected as representatives for priority substances, were carried out. Results The sample size simulations showed two general patterns: the accuracy of the mean annual load estimation increased with increasing sample size and skewness and temporal variability were more apparent in smaller sample sizes. In right-skewed data sets, small sample sizes led, on average, to a systematic underestimation of the true mean annual load whilst in a few cases these led to an overestimation. Although the study was carried out on priority substances, results can be transferable to other pollutants. Furthermore, in small sample sizes a considerable proportion of the simulated means failed to detect annual average environmental quality standard exceedances. Conclusions The results of the present study indicate that the usage of small sample sizes is likely to result in an underestimation of the true mean annual pollutant loads in chemical surveillance and scientific research, thus potentially jeopardizing the validity of results. Therefore, it is recommended to avoid the usage of small sample sizes for the determination of mean annual pollutant loads. Furthermore, priority substances should be sampled according to the European Water Framework Directive guidelines at least 12 times/year to improve the assessment of the threat posed by pollutants to freshwater ecosystems in Europe. Micropollutant (dpeaa)DE-He213 Priority substance (dpeaa)DE-He213 Sample size simulation (dpeaa)DE-He213 Monitoring (dpeaa)DE-He213 Weekly composite sample (dpeaa)DE-He213 Accuracy assessment (dpeaa)DE-He213 Uncertainty (dpeaa)DE-He213 European Water Framework Directive (dpeaa)DE-He213 Temporal variability (dpeaa)DE-He213 Sundermann, Andrea aut Enthalten in Umweltwissenschaften und Schadstoff-Forschung Heidelberg : Springer, 1989 32(2020), 1 vom: 16. Jan. (DE-627)319337200 (DE-600)2014183-X 1865-5084 nnns volume:32 year:2020 number:1 day:16 month:01 https://dx.doi.org/10.1186/s12302-019-0285-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_60 GBV_ILN_95 GBV_ILN_370 GBV_ILN_2360 AR 32 2020 1 16 01 |
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10.1186/s12302-019-0285-y doi (DE-627)SPR024868043 (SPR)s12302-019-0285-y-e DE-627 ger DE-627 rakwb eng Babitsch, Denise verfasserin (orcid)0000-0003-2211-1601 aut Chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2020 Background Chemical surveillance in surface waters is crucial to identify potential threats to the health of freshwater ecosystems. Usually, the concentrations of pollutants are highly variable over the course of the year and often result in non-normally distributed data sets. Therefore, the European Water Framework Directive recommends measuring, e.g. priority substances at least 12 times a year to achieve an acceptable accuracy level for the estimation of the true mean annual loads. However, in Europe priority substances are often measured much less frequently. In this context, the aim of the present study was to analyze how sample size, temporal variability and skewness of the data sets influence the accuracy of the mean annual load estimation and the assessment of annual average environmental quality standards. For this purpose, sample size simulations using weekly composite samples of benzo(a)pyrene, 4-tert-octylphenol, fluoranthene and di(2-ethylhexyl) phthalate, selected as representatives for priority substances, were carried out. Results The sample size simulations showed two general patterns: the accuracy of the mean annual load estimation increased with increasing sample size and skewness and temporal variability were more apparent in smaller sample sizes. In right-skewed data sets, small sample sizes led, on average, to a systematic underestimation of the true mean annual load whilst in a few cases these led to an overestimation. Although the study was carried out on priority substances, results can be transferable to other pollutants. Furthermore, in small sample sizes a considerable proportion of the simulated means failed to detect annual average environmental quality standard exceedances. Conclusions The results of the present study indicate that the usage of small sample sizes is likely to result in an underestimation of the true mean annual pollutant loads in chemical surveillance and scientific research, thus potentially jeopardizing the validity of results. Therefore, it is recommended to avoid the usage of small sample sizes for the determination of mean annual pollutant loads. Furthermore, priority substances should be sampled according to the European Water Framework Directive guidelines at least 12 times/year to improve the assessment of the threat posed by pollutants to freshwater ecosystems in Europe. Micropollutant (dpeaa)DE-He213 Priority substance (dpeaa)DE-He213 Sample size simulation (dpeaa)DE-He213 Monitoring (dpeaa)DE-He213 Weekly composite sample (dpeaa)DE-He213 Accuracy assessment (dpeaa)DE-He213 Uncertainty (dpeaa)DE-He213 European Water Framework Directive (dpeaa)DE-He213 Temporal variability (dpeaa)DE-He213 Sundermann, Andrea aut Enthalten in Umweltwissenschaften und Schadstoff-Forschung Heidelberg : Springer, 1989 32(2020), 1 vom: 16. Jan. (DE-627)319337200 (DE-600)2014183-X 1865-5084 nnns volume:32 year:2020 number:1 day:16 month:01 https://dx.doi.org/10.1186/s12302-019-0285-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_60 GBV_ILN_95 GBV_ILN_370 GBV_ILN_2360 AR 32 2020 1 16 01 |
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Usually, the concentrations of pollutants are highly variable over the course of the year and often result in non-normally distributed data sets. Therefore, the European Water Framework Directive recommends measuring, e.g. priority substances at least 12 times a year to achieve an acceptable accuracy level for the estimation of the true mean annual loads. However, in Europe priority substances are often measured much less frequently. In this context, the aim of the present study was to analyze how sample size, temporal variability and skewness of the data sets influence the accuracy of the mean annual load estimation and the assessment of annual average environmental quality standards. For this purpose, sample size simulations using weekly composite samples of benzo(a)pyrene, 4-tert-octylphenol, fluoranthene and di(2-ethylhexyl) phthalate, selected as representatives for priority substances, were carried out. Results The sample size simulations showed two general patterns: the accuracy of the mean annual load estimation increased with increasing sample size and skewness and temporal variability were more apparent in smaller sample sizes. In right-skewed data sets, small sample sizes led, on average, to a systematic underestimation of the true mean annual load whilst in a few cases these led to an overestimation. Although the study was carried out on priority substances, results can be transferable to other pollutants. Furthermore, in small sample sizes a considerable proportion of the simulated means failed to detect annual average environmental quality standard exceedances. Conclusions The results of the present study indicate that the usage of small sample sizes is likely to result in an underestimation of the true mean annual pollutant loads in chemical surveillance and scientific research, thus potentially jeopardizing the validity of results. Therefore, it is recommended to avoid the usage of small sample sizes for the determination of mean annual pollutant loads. 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Chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances Micropollutant (dpeaa)DE-He213 Priority substance (dpeaa)DE-He213 Sample size simulation (dpeaa)DE-He213 Monitoring (dpeaa)DE-He213 Weekly composite sample (dpeaa)DE-He213 Accuracy assessment (dpeaa)DE-He213 Uncertainty (dpeaa)DE-He213 European Water Framework Directive (dpeaa)DE-He213 Temporal variability (dpeaa)DE-He213 |
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chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances |
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Chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances |
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Background Chemical surveillance in surface waters is crucial to identify potential threats to the health of freshwater ecosystems. Usually, the concentrations of pollutants are highly variable over the course of the year and often result in non-normally distributed data sets. Therefore, the European Water Framework Directive recommends measuring, e.g. priority substances at least 12 times a year to achieve an acceptable accuracy level for the estimation of the true mean annual loads. However, in Europe priority substances are often measured much less frequently. In this context, the aim of the present study was to analyze how sample size, temporal variability and skewness of the data sets influence the accuracy of the mean annual load estimation and the assessment of annual average environmental quality standards. For this purpose, sample size simulations using weekly composite samples of benzo(a)pyrene, 4-tert-octylphenol, fluoranthene and di(2-ethylhexyl) phthalate, selected as representatives for priority substances, were carried out. Results The sample size simulations showed two general patterns: the accuracy of the mean annual load estimation increased with increasing sample size and skewness and temporal variability were more apparent in smaller sample sizes. In right-skewed data sets, small sample sizes led, on average, to a systematic underestimation of the true mean annual load whilst in a few cases these led to an overestimation. Although the study was carried out on priority substances, results can be transferable to other pollutants. Furthermore, in small sample sizes a considerable proportion of the simulated means failed to detect annual average environmental quality standard exceedances. Conclusions The results of the present study indicate that the usage of small sample sizes is likely to result in an underestimation of the true mean annual pollutant loads in chemical surveillance and scientific research, thus potentially jeopardizing the validity of results. Therefore, it is recommended to avoid the usage of small sample sizes for the determination of mean annual pollutant loads. Furthermore, priority substances should be sampled according to the European Water Framework Directive guidelines at least 12 times/year to improve the assessment of the threat posed by pollutants to freshwater ecosystems in Europe. © The Author(s) 2020 |
| abstractGer |
Background Chemical surveillance in surface waters is crucial to identify potential threats to the health of freshwater ecosystems. Usually, the concentrations of pollutants are highly variable over the course of the year and often result in non-normally distributed data sets. Therefore, the European Water Framework Directive recommends measuring, e.g. priority substances at least 12 times a year to achieve an acceptable accuracy level for the estimation of the true mean annual loads. However, in Europe priority substances are often measured much less frequently. In this context, the aim of the present study was to analyze how sample size, temporal variability and skewness of the data sets influence the accuracy of the mean annual load estimation and the assessment of annual average environmental quality standards. For this purpose, sample size simulations using weekly composite samples of benzo(a)pyrene, 4-tert-octylphenol, fluoranthene and di(2-ethylhexyl) phthalate, selected as representatives for priority substances, were carried out. Results The sample size simulations showed two general patterns: the accuracy of the mean annual load estimation increased with increasing sample size and skewness and temporal variability were more apparent in smaller sample sizes. In right-skewed data sets, small sample sizes led, on average, to a systematic underestimation of the true mean annual load whilst in a few cases these led to an overestimation. Although the study was carried out on priority substances, results can be transferable to other pollutants. Furthermore, in small sample sizes a considerable proportion of the simulated means failed to detect annual average environmental quality standard exceedances. Conclusions The results of the present study indicate that the usage of small sample sizes is likely to result in an underestimation of the true mean annual pollutant loads in chemical surveillance and scientific research, thus potentially jeopardizing the validity of results. Therefore, it is recommended to avoid the usage of small sample sizes for the determination of mean annual pollutant loads. Furthermore, priority substances should be sampled according to the European Water Framework Directive guidelines at least 12 times/year to improve the assessment of the threat posed by pollutants to freshwater ecosystems in Europe. © The Author(s) 2020 |
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Background Chemical surveillance in surface waters is crucial to identify potential threats to the health of freshwater ecosystems. Usually, the concentrations of pollutants are highly variable over the course of the year and often result in non-normally distributed data sets. Therefore, the European Water Framework Directive recommends measuring, e.g. priority substances at least 12 times a year to achieve an acceptable accuracy level for the estimation of the true mean annual loads. However, in Europe priority substances are often measured much less frequently. In this context, the aim of the present study was to analyze how sample size, temporal variability and skewness of the data sets influence the accuracy of the mean annual load estimation and the assessment of annual average environmental quality standards. For this purpose, sample size simulations using weekly composite samples of benzo(a)pyrene, 4-tert-octylphenol, fluoranthene and di(2-ethylhexyl) phthalate, selected as representatives for priority substances, were carried out. Results The sample size simulations showed two general patterns: the accuracy of the mean annual load estimation increased with increasing sample size and skewness and temporal variability were more apparent in smaller sample sizes. In right-skewed data sets, small sample sizes led, on average, to a systematic underestimation of the true mean annual load whilst in a few cases these led to an overestimation. Although the study was carried out on priority substances, results can be transferable to other pollutants. Furthermore, in small sample sizes a considerable proportion of the simulated means failed to detect annual average environmental quality standard exceedances. Conclusions The results of the present study indicate that the usage of small sample sizes is likely to result in an underestimation of the true mean annual pollutant loads in chemical surveillance and scientific research, thus potentially jeopardizing the validity of results. Therefore, it is recommended to avoid the usage of small sample sizes for the determination of mean annual pollutant loads. Furthermore, priority substances should be sampled according to the European Water Framework Directive guidelines at least 12 times/year to improve the assessment of the threat posed by pollutants to freshwater ecosystems in Europe. © The Author(s) 2020 |
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