Prediction of Odor Concentration Emitted from Wastewater Treatment Plant Using an Artificial Neural Network (ANN)
Round 1
Reviewer 1 Report
The scope of the paper is clear and I confirm the necessity of doing research in this direction.
Many abbreviations used, especially in the abstract, and they are not defined previously.
I have serious doubts that an actual problem can be solved in this manner- as proposed by the authors. At least the model should be attested by significant measurements - that really are also not very adequate described and possible presently.
Prediction accuracy of 70% is quite low. And it is still a prediction compared to reality that is also not totally based on a sound methodology all over.
Author Response
Please see the attachment.
Author Response File: 
Author Response.docx
Reviewer 2 Report
The odour problem definitely belongs to current scientific trends. A lot of scientific work and studies are devoted to this. The research proposed is certainly interesting, but there is no reference to what has already been done in this field. The use of ANN in odour prediction is not a scientific novelty. I suggest that the authors edit this manuscript in this respect and take into account the comments below:
page 2, line 50, it should be demonstrated whether such research has already been carried out by other research teams to refer to these results.
page 2, line 60, the use of ANN is not only in environmental engineering. ANN has found many applications from sewage treatment plants, through biogas plants to fragrance interactions.
Below are some publications that are worth using:
- Modeling and optimization of biogas production from a waste digester using artificial neural network and genetic algorithm. Resour. Conserv. Recycl. 2010, 54, 359–363
- The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process, Sustainability, 2019, 11(16), 4407
- Chemical and odor characterization of gas emissions released during composting of solid wastes and digestates. J. Environ. Manag. 2019, 233, 39–53.
- Odor concentration (OC) prediction based on odor activity values (OAVs) during composting of solid wastes and digestates. Atmos. Environ. 2019, 201, 1–12.
- Determination of Odor Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks. Sensors 2018, 18, 519
- Measurement of odor intensity by an electronic nose. J. Air Waste Manag. Assoc. 2000, 50, 1750–1758.
page 2, line 61-65, There is no information what is new in this work? How is this work different from others? The use of ANN in odour assessment from a sewage treatment plant is not a scientific novelty. You have to underline what is scientific novelty.
page 2, chapter 2.2 This chapter should be compiled, information on ANN is generally known.
page 4, line 118-121, How do you know what smell are present? Has any instrumental analysis been carried out? I suggest in the table to provide the values of the thresholds of palpability for the described smell compounds.
page 7, line 207-211, There is no comparison of results achieved with the work of other authors. It is hard to tell if the results achieved are interesting.
References - the authors used only 7 references, it follows that they did not refer to the state of knowledge in a given field.
Author Response
Please see the attachment.
Author Response File: Author Response.docx
Round 2
Reviewer 2 Report
I accept the authors' responses to my comments. You can also see the changes made and the attitude to make corrections that the article was the best. I recommend for further stages of evaluation.
