Pragmatic analysis of wastewater treatment methods from a statistical perspective
Wastewater treatment is an environmental issue of the utmost importance. Pesticides, industrial waste, chemical fertilizers, and radioactive waste are some of the causes for water pollution. Several models exist for treating contaminated wastewater. In this study an application-specific review of va...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IWA Publishing
2023-01-01
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| Series: | Water Practice and Technology |
| Subjects: | |
| Online Access: | http://wpt.iwaponline.com/content/18/1/1 |
| _version_ | 1828012672291962880 |
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| author | Pournima Pande Ashish Bhagat |
| author_facet | Pournima Pande Ashish Bhagat |
| author_sort | Pournima Pande |
| collection | DOAJ |
| description | Wastewater treatment is an environmental issue of the utmost importance. Pesticides, industrial waste, chemical fertilizers, and radioactive waste are some of the causes for water pollution. Several models exist for treating contaminated wastewater. In this study an application-specific review of various wastewater treatment models is performed. Extensions to existing treatment models are discussed to improve their performance. The treatment models are compared statistically based on performance metrics such as quality of treated water, sludge percentage at output, complexity of treatment, time needed for treatment, and deployment cost. The treatment models are ranked using a novel parameter called Model Rank, which combines all performance metrics into a single number. According to the results, six models, including Advanced Oxidation Processes with Ozone treatment (AOPO), Kernel Principal Components Analysis based one-class Support Vector Machine (KPCA SVM), and four others, have a rank greater than 3.5. The AOPO model has the highest model rank of 3.85 and performs better than all other models. This study might aid major stakeholders in the waste treatment industry, including researchers, in selecting the appropriate waste water treatment method per their requirements.
HIGHLIGHTS
Application-specific pragmatic review of various wastewater treatment models.;
Assistance in identification of various advantages, limitations, and future research scope in these models.;
Statistical comparison of various performance metrics of different models.;
Using statistical analysis, identifying the best possible method or methods.;
Recommendations of various extensions to models for improving process performance; |
| first_indexed | 2024-04-10T09:35:21Z |
| format | Article |
| id | doaj.art-69a35bf6caaf42c9b325d27ee5b3e583 |
| institution | Directory Open Access Journal |
| issn | 1751-231X |
| language | English |
| last_indexed | 2024-04-10T09:35:21Z |
| publishDate | 2023-01-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Water Practice and Technology |
| spelling | doaj.art-69a35bf6caaf42c9b325d27ee5b3e5832023-02-17T17:33:02ZengIWA PublishingWater Practice and Technology1751-231X2023-01-0118111510.2166/wpt.2022.153153Pragmatic analysis of wastewater treatment methods from a statistical perspectivePournima Pande0Ashish Bhagat1 Yeshwantrao Chavan College of Engineering, Wanadongari, Nagpur, Maharashtra, India Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Sawangi (M), Wardha, Maharashtra, India Wastewater treatment is an environmental issue of the utmost importance. Pesticides, industrial waste, chemical fertilizers, and radioactive waste are some of the causes for water pollution. Several models exist for treating contaminated wastewater. In this study an application-specific review of various wastewater treatment models is performed. Extensions to existing treatment models are discussed to improve their performance. The treatment models are compared statistically based on performance metrics such as quality of treated water, sludge percentage at output, complexity of treatment, time needed for treatment, and deployment cost. The treatment models are ranked using a novel parameter called Model Rank, which combines all performance metrics into a single number. According to the results, six models, including Advanced Oxidation Processes with Ozone treatment (AOPO), Kernel Principal Components Analysis based one-class Support Vector Machine (KPCA SVM), and four others, have a rank greater than 3.5. The AOPO model has the highest model rank of 3.85 and performs better than all other models. This study might aid major stakeholders in the waste treatment industry, including researchers, in selecting the appropriate waste water treatment method per their requirements. HIGHLIGHTS Application-specific pragmatic review of various wastewater treatment models.; Assistance in identification of various advantages, limitations, and future research scope in these models.; Statistical comparison of various performance metrics of different models.; Using statistical analysis, identifying the best possible method or methods.; Recommendations of various extensions to models for improving process performance;http://wpt.iwaponline.com/content/18/1/1complexityoxidationozonetreatmentwastewater |
| spellingShingle | Pournima Pande Ashish Bhagat Pragmatic analysis of wastewater treatment methods from a statistical perspective Water Practice and Technology complexity oxidation ozone treatment wastewater |
| title | Pragmatic analysis of wastewater treatment methods from a statistical perspective |
| title_full | Pragmatic analysis of wastewater treatment methods from a statistical perspective |
| title_fullStr | Pragmatic analysis of wastewater treatment methods from a statistical perspective |
| title_full_unstemmed | Pragmatic analysis of wastewater treatment methods from a statistical perspective |
| title_short | Pragmatic analysis of wastewater treatment methods from a statistical perspective |
| title_sort | pragmatic analysis of wastewater treatment methods from a statistical perspective |
| topic | complexity oxidation ozone treatment wastewater |
| url | http://wpt.iwaponline.com/content/18/1/1 |
| work_keys_str_mv | AT pournimapande pragmaticanalysisofwastewatertreatmentmethodsfromastatisticalperspective AT ashishbhagat pragmaticanalysisofwastewatertreatmentmethodsfromastatisticalperspective |