The effect of polysaccharidic gums on activated carbon treatment of textile wastewater

Abstract The merits of activated carbon for removal of organic compounds from wastewater have been well documented in the literature. On the other hand there is a lack of published data on the use of activated carbon for the removal of trace metals from wastewater. Experiments were designed to assess the possibility that activated carbon treatment would remove aluminum, cadmium, chromium, cobalt, copper, iron, lead, manganese, mercury, nickel, silver and zinc from wastewater. All metals studied were tested over the pH range 3-11. Greater than 99.5% removal was achieved by pH adjustment and activated carbon treatment for most of the metals tested.

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Disinfection byproduct formation from algal organic matters after ozonation or ozone combined with activated carbon treatment with subsequent chlorination

Journal of Environmental Sciences ◽

10.1016/j.jes.2020.12.009 ◽

2021 ◽

Vol 104 ◽

pp. 233-241

Author(s):

Qiufeng Lin ◽

Feilong Dong ◽

Cong Li ◽

Junkui Cui

Keyword(s):

Activated Carbon ◽

Organic Matters ◽

Disinfection Byproduct ◽

Byproduct Formation ◽

Carbon Treatment

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Digital Smoke Taint Detection in Pinot Grigio Wines Using an E-Nose and Machine Learning Algorithms Following Treatment with Activated Carbon and a Cleaving Enzyme

Fermentation ◽

10.3390/fermentation7030119 ◽

2021 ◽

Vol 7 (3) ◽

pp. 119

Author(s):

Vasiliki Summerson ◽

Claudia Gonzalez Viejo ◽

Damir D. Torrico ◽

Alexis Pang ◽

Sigfredo Fuentes

Keyword(s):

Machine Learning ◽

Activated Carbon ◽

Low Cost ◽

Aroma Compounds ◽

Machine Learning Algorithms ◽

Enzyme Treatment ◽

Mean Values ◽

Volatile Aroma ◽

Carbon Treatment ◽

Volatile Aroma Compounds

The incidence and intensity of bushfires is increasing due to climate change, resulting in a greater risk of smoke taint development in wine. In this study, smoke-tainted and non-smoke-tainted wines were subjected to treatments using activated carbon with/without the addition of a cleaving enzyme treatment to hydrolyze glycoconjugates. Chemical measurements and volatile aroma compounds were assessed for each treatment, with the two smoke taint amelioration treatments exhibiting lower mean values for volatile aroma compounds exhibiting positive ‘fruit’ aromas. Furthermore, a low-cost electronic nose (e-nose) was used to assess the wines. A machine learning model based on artificial neural networks (ANN) was developed using the e-nose outputs from the unsmoked control wine, unsmoked wine with activated carbon treatment, unsmoked wine with a cleaving enzyme plus activated carbon treatment, and smoke-tainted control wine samples as inputs to classify the wines according to the smoke taint amelioration treatment. The model displayed a high overall accuracy of 98% in classifying the e-nose readings, illustrating it may be a rapid, cost-effective tool for winemakers to assess the effectiveness of smoke taint amelioration treatment by activated carbon with/without the use of a cleaving enzyme. Furthermore, the use of a cleaving enzyme coupled with activated carbon was found to be effective in ameliorating smoke taint in wine and may help delay the resurgence of smoke aromas in wine following the aging and hydrolysis of glycoconjugates.

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