Data underlying the publication: Sensitivity analysis of the Substance Emission Model v2.1.2 component of the Greenhouse Emission Model
doi: 10.4121/6c61effc-9d0c-4246-8a22-ad7618f4f278
CC BY-NC-SA 4.0
In the analysis ensembles of 7-year SEM simulations were performed for 100 assessments for different scenarios and substances. For each assessment, an ensemble of 365 simulations was performed with varying dates of substance application, covering every day of the year. For each simulation the following postprocessing was performed on the daily substance emission (g.m-2.d-1) from the greenhouse and its 10-day moving average:
* Determine the of the annual maximum for each of the 7 simulation years.
* Calculate the 50th and 90th percentiles over the 7 annual maxima (referred to as PEC50 and the PEC90, respectively).
This results in four PEC values (PEC50--daily, PEC90--daily, PEC50--10-day-average, PEC90--10-day-average) for each of the 100x365 simulations. Next, for each of the 100 assessments, the results of the 365 simulations were processed as follows:
* Calculate the 90th percentile over 365 values for the four PEC values--this is referred to as the "true" 90th percentile.
* Remove 5 simulations for application dates 7-Feb, 21-Apr, 3-Jul, 14-Sep and 26-Nov, resulting in a set of 360 simulations. This is done because 360 has more divisors than 365.
Subsequently, processing was performed on subsamples of different sizes N, taken from the 360 simulations. The following subsample sizes were considered: 12, 15, 18, 20, 24, 30, 36, 40, 45, and 60. For each subsample size N, M_N = 360/N sets of subsamples were taken with application date evenly spread over the year. For example, for N=12, M_12=30 sets of application dates were selected, with each set one day offset to the next. This results in 10 sets of subsamples of varying size. For each set N, the following processing was performed:
* For each M_N values for the four PECs, calculate the relative difference compared to the true 90th percentile (based on the full 365 set of simulations; see above) as follows: RD = (PEC_est-PEC_365)/PEC_365.
* Calculate the 10th percentile over the M_N relative differences for each of the four PECs; this is referred to as the 90th percentile underestimation
* For each M_N values for the four PECs, calculate the multiplication factor relative to the true 90th percentile as follows: MF = PEC_est/PEC_365.
* Calculate the 90th percentile over the M_N multiplication factors for each of the four PECs.
This results in 4000 values for the relative difference and multiplication factor for each combination of assessment (100), subsample size N (10), and PEC quantity (4). The relative underestimations form the data underlying Figure 13.3 in Braakhekke et al. (2024). The multiplication factors for N=12 form the data underlying table 13.1 in Braakhekke et al. (2024).
- 2024-10-31 first online
- 2024-12-17 published, posted
DATA
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9c375451c8676844096430b66aaeb94creadme.txt - 36,955 bytesMD5:
c9664bc6dd6e9daf25e863b0d569de6fSEM_SAD_90prc_MultplFac_PEC50.csv - 38,234 bytesMD5:
efaced6b730daa650b7d55e231c47972SEM_SAD_90prc_MultplFac_PEC90.csv - 43,373 bytesMD5:
b1b11899d89b0a528e57fcede11b1d67SEM_SAD_90prc_RelUnderEst_PEC50.csv - 45,008 bytesMD5:
342921fed889ade18f76b8abb8ad8216SEM_SAD_90prc_RelUnderEst_PEC90.csv -
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