Challenging analytical task: analysis and monitoring of arsenic species in water
Samo za registrovane korisnike
2014
Autori
Rajaković-Ognjanović, VladanaJovanović, Branislava M.
Živojinović, Dragana
Rajaković, Ljubinka V.
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Analysis and monitoring of arsenic is still a challenging analytical task. Due to its complex behaviour (different forms of arsenic that can be present depending on pH and oxidation states of arsenic) as well as demanding analytical procedures and instrumental tools for control of arsenic concentration in drinking water which is set to 10 mu g L-1, there are still some open questions and issues when arsenic is the scientific topic. In this paper the idea was to use a multivariate statistical approach to identify the key variables and their relation to high arsenic concentration in surface waters of Serbia. The main idea was to identify and connect the key water quality parameters with arsenic concentration and to suggest adequate treatment technologies for water purification and arsenic removal. The data set for multivariate statistical approach were water quality parameters of surface water samples from Serbia. The artificial neural network (ANN) was applied for data analysis. After a...pplying ANN the results showed strong relation between arsenic concentration and P-tot, SO42-, COD, carbonate, N-org, DO, and SiO2 content. What could be concluded from the obtained results is that high concentration of organic matter, proportional to nutrients (nitrogen and phosphorus), silica (SiO2) and dissolved oxygen highly correlates with the dissolved arsenic which implies that the most adequate technology for the water treatment could be precipitation, which in general includes coagulation. What remains unquestioned and needs to be performed is arsenic speciation analysis.
Ključne reči:
arsenic / multivariate statistical approach / surface water qualityIzvor:
Environmental Engineering and Management Journal, 2014, 13, 9, 2275-2282Izdavač:
- Gheorghe Asachi Technical University of Iasi, Romania
DOI: 10.30638/eemj.2014.254
ISSN: 1582-9596
WoS: 000347161400020
Scopus: 2-s2.0-84932611964
Institucija/grupa
Tehnološko-metalurški fakultetTY - JOUR AU - Rajaković-Ognjanović, Vladana AU - Jovanović, Branislava M. AU - Živojinović, Dragana AU - Rajaković, Ljubinka V. PY - 2014 UR - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/2699 AB - Analysis and monitoring of arsenic is still a challenging analytical task. Due to its complex behaviour (different forms of arsenic that can be present depending on pH and oxidation states of arsenic) as well as demanding analytical procedures and instrumental tools for control of arsenic concentration in drinking water which is set to 10 mu g L-1, there are still some open questions and issues when arsenic is the scientific topic. In this paper the idea was to use a multivariate statistical approach to identify the key variables and their relation to high arsenic concentration in surface waters of Serbia. The main idea was to identify and connect the key water quality parameters with arsenic concentration and to suggest adequate treatment technologies for water purification and arsenic removal. The data set for multivariate statistical approach were water quality parameters of surface water samples from Serbia. The artificial neural network (ANN) was applied for data analysis. After applying ANN the results showed strong relation between arsenic concentration and P-tot, SO42-, COD, carbonate, N-org, DO, and SiO2 content. What could be concluded from the obtained results is that high concentration of organic matter, proportional to nutrients (nitrogen and phosphorus), silica (SiO2) and dissolved oxygen highly correlates with the dissolved arsenic which implies that the most adequate technology for the water treatment could be precipitation, which in general includes coagulation. What remains unquestioned and needs to be performed is arsenic speciation analysis. PB - Gheorghe Asachi Technical University of Iasi, Romania T2 - Environmental Engineering and Management Journal T1 - Challenging analytical task: analysis and monitoring of arsenic species in water EP - 2282 IS - 9 SP - 2275 VL - 13 DO - 10.30638/eemj.2014.254 ER -
@article{ author = "Rajaković-Ognjanović, Vladana and Jovanović, Branislava M. and Živojinović, Dragana and Rajaković, Ljubinka V.", year = "2014", abstract = "Analysis and monitoring of arsenic is still a challenging analytical task. Due to its complex behaviour (different forms of arsenic that can be present depending on pH and oxidation states of arsenic) as well as demanding analytical procedures and instrumental tools for control of arsenic concentration in drinking water which is set to 10 mu g L-1, there are still some open questions and issues when arsenic is the scientific topic. In this paper the idea was to use a multivariate statistical approach to identify the key variables and their relation to high arsenic concentration in surface waters of Serbia. The main idea was to identify and connect the key water quality parameters with arsenic concentration and to suggest adequate treatment technologies for water purification and arsenic removal. The data set for multivariate statistical approach were water quality parameters of surface water samples from Serbia. The artificial neural network (ANN) was applied for data analysis. After applying ANN the results showed strong relation between arsenic concentration and P-tot, SO42-, COD, carbonate, N-org, DO, and SiO2 content. What could be concluded from the obtained results is that high concentration of organic matter, proportional to nutrients (nitrogen and phosphorus), silica (SiO2) and dissolved oxygen highly correlates with the dissolved arsenic which implies that the most adequate technology for the water treatment could be precipitation, which in general includes coagulation. What remains unquestioned and needs to be performed is arsenic speciation analysis.", publisher = "Gheorghe Asachi Technical University of Iasi, Romania", journal = "Environmental Engineering and Management Journal", title = "Challenging analytical task: analysis and monitoring of arsenic species in water", pages = "2282-2275", number = "9", volume = "13", doi = "10.30638/eemj.2014.254" }
Rajaković-Ognjanović, V., Jovanović, B. M., Živojinović, D.,& Rajaković, L. V.. (2014). Challenging analytical task: analysis and monitoring of arsenic species in water. in Environmental Engineering and Management Journal Gheorghe Asachi Technical University of Iasi, Romania., 13(9), 2275-2282. https://doi.org/10.30638/eemj.2014.254
Rajaković-Ognjanović V, Jovanović BM, Živojinović D, Rajaković LV. Challenging analytical task: analysis and monitoring of arsenic species in water. in Environmental Engineering and Management Journal. 2014;13(9):2275-2282. doi:10.30638/eemj.2014.254 .
Rajaković-Ognjanović, Vladana, Jovanović, Branislava M., Živojinović, Dragana, Rajaković, Ljubinka V., "Challenging analytical task: analysis and monitoring of arsenic species in water" in Environmental Engineering and Management Journal, 13, no. 9 (2014):2275-2282, https://doi.org/10.30638/eemj.2014.254 . .