Comment on: Describing water treatment process performance: Why average log-reduction can be a misleading statistic by Schmidt, P.J., Anderson, W.B. and Emelko, M.B. (Water Res, on-line 115702, 2020)

Autor: Susan Petterson, W.A.M. Hijnen, P.W.M.H. Smeets
Rok vydání: 2020
Předmět:
Zdroj: Water research. 185
ISSN: 1879-2448
Popis: The authors present a study on how to deal with the quantification of treatment processes to eliminate micro-organisms. They point to an obvious point in misinterpreting logarithmic data by calculating the over-all performance by calculating the mean of the log-values of removal fractions instead of averaging the removal fractions themselves. This is common knowledge, and many publications have demonstrated how periods of poor performance compromise overall treatment efficacy and can dominate the microbial risk to consumers (Gale, 2002a; Gale et al., 2002b; Hunter et al., 2009; Jaidi et al. 2009; Smeets et al., 2010; Petterson and Stenstrom, 2015). It is therefore valid to determine the average performance over time from one treatment process, including for a number of parallel operated process units, using the proposed method. However, in their paper Schmidt et al. apply this method to recalculate Microbial Elimination Capacity or log-reduction values from the literature review by Hijnen and Medema, 2010 to their ‘effective log-reduction’ (Table 2 in the Schmidt et al. paper). Additionally, they apply their ‘effective log-reduction’ method to reanalyze the QMRA example in Box 2.4 of the QMRA guidelines of WHO (2016), leading to exceeding the annual risk of 10−6 DALYs per person. To our opinion this is an incorrect interpretation and use of that literature data collected by Hijnen and Medema, 2010. It does not make sense to use these reported values to represent the variability in performance over time at a single treatment plant. Those log-reduction data were abstracted from independent process studies performed under variable operational conditions under different scales (lab-scale to full-scale) and, depended on the published data, representing the effective average removal or a number of individual log reduction values over time.
Databáze: OpenAIRE