Abstract
In this work, a novel definitive screening design (DSD) was initially used to investigate the in situ chemical oxidation of acid orange-II (AO II) dye using a homogeneous cobalt-catalyzed peroxymonosulfate (Co2+/PMS) system.
Highlights
In situ chemical oxidation (ISCO) is an option that has been developed over the past decade to degrade various organic pollutants.[1]
The in situ chemical oxidation of acid orange-II (AO II) by homogeneous Co2+/ PMS system was initially studied by adopting a sequential experimental strategy consisting of a screening phase (DSD) followed by a optimizing phase (CCRD)
The main conclusions of the work were the following: (1) It had been realized that both de nitive screening design (DSD) and central composite rotatable design (CCRD) models are reliable and predictive tools with excellent accuracy
Summary
In situ chemical oxidation (ISCO) is an option that has been developed over the past decade to degrade various organic pollutants.[1] Speci cally, a very recent process developed for ISCO involves the use of Co2+-catalyzed peroxymonosulfate (Co2+/PMS), which exhibits the advantages of excellent reactivity with contaminants and high longevity in the subsurface.[2] the performance of the process depends on multiple operating variables, such as anions, natural organic matter (NOM), solution pH, external energy (e.g., UV light, electric eld and ultrasound), etc.[3,4,5] For this reason, the traditional onefactor-at-a-time approach to optimization is time and regent extensive, and it is o en unable to yield globally optimal operating conditions To overcome these limitations, the most common strategy is to employ statistical design methods, such as Box–Behnken design, Doehlert design and central composite rotatable design (CCRD).[6] the number of experiments required (NER) for these methods will increase exponentially with the number of variables tested.[7,8,9] For example, NER are 17, 36, 58, 100, 177, 324 and 635 for 3, 4, 5, 6, 7, 8 and 9-factor CCRD matrix, respectively. DSD is very promising for optimization of processes which involve a large number of operating variables
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