Best Practices in Environmental Data Handling for Degradation Kinetics Estimation
Learn about data quality, replicates, dealing with concentrations below LOD or LOQ, handling outliers and time-zero samples in environmental fate studies for estimating degradation kinetics. Explore essential guidelines and methods presented in the FOCUS report Chapter 6.1.
Best Practices in Environmental Data Handling for Degradation Kinetics Estimation
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Presentation Transcript
Data handling Sabine Beulke, CSL, York, UK FOCUS Work Group on Degradation Kinetics Estimating Persistence and Degradation Kinetics from Environmental Fate Studies in EU Registration Brussels, 26-27 January 2005
Outline • Data quality • Replicates • Concentrations below LOD or LOQ • Experimental artefacts • Outliers • Time zero samples • Data weighting For more information see Chapter 6.1 of the FOCUS report
Data quality • Dissipation pattern and - for metabolites and sediment data - the increase, plateau and decline phase must be clearly established • No. of data points (n) >> no. of parameters (p) (theoretical minimum n = p+1, but this is often not sufficient) • The better the quality the smaller the no. of datapoints needed
Replicates • Use true replicates individually in the optimisation • Average replicate analytical results from same sample prior to curve fitting • Average all replicates prior to calculating 2 statistics
Concentrations below LOD or LOQ Parent in soil, total water-sediment system, water column • Set all concentrations between LOD and LOQ to measured value or 0.5 x (LOD+LOQ) • Set first sample < LOD to 0.5 x LOD • Omit samples after first non-detect unless later samples > LOQ Set to measured value Set to 0.5 x LOD Omit
Concentrations below LOD or LOQ Metabolite in soil and parent and metabolite in sediment • Set time zero samples < LOD to 0 • Set sample <LOD just before & after detectable amount to 0.5 LOD • Omit all other samples < LOD (exceptions) • Set concentrations between LOD and LOQ to measured value or 0.5 x (LOD+LOQ)
Experimental artefacts • Discard results clearly arising from analytical or procedural errors before analysis • If microbial activity declined significantly during study: Include all data initially, then exclude later sampling points and repeat fitting
DT50 42 days DT50 34 days Outliers • Include all data in curve fitting as a first step • Omit outliers based on expert judgement • Statistical outlier test where possible
Time zero samples • Include initial amount of parent (soil, total w/s system and water column) in parameter estimation as a first step M0 variable: DT50 = 68 days Note: This hypothetical dataset is not described well by SFO kinetics and is only used to illustrate the effect of fixing or estimating the initial concentration. M0 fixed: DT50 = 48 days
Time zero samples • Add time-zero concentrations of metabolites > 0 to parent unless due to impurity in application solution • Add time-zero concentrations > 0 of parent or metabolite in sediment to water M0 variable: DT50 = 68 days M0 fixed: DT50 = 48 days Note: This hypothetical dataset is not described well by SFO kinetics and is only used to illustrate the effect of fixing or estimating the initial concentration.
Data weighting No transformation: DT50 = 51 days No transformation: DT50 = 54 days Log transformed: DT50 = 57 days Log transformed: DT50 = 108 days Always use unweighted data as a first step! Note: This hypothetical dataset is not described well by SFO kinetics and is only used to illustrate the effect of log-transformation.