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Non-Targeted Screening of Wastewater Organic Disinfection Byproducts using Low Density Polyethylene (LDPE) Passive Samplers

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dc.contributor.author Rahim, Sajjad
dc.date.accessioned 2021-09-20T07:17:36Z
dc.date.available 2021-09-20T07:17:36Z
dc.date.issued 2020-09-08
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/26144
dc.description Supervised by: Dr. Azhar Mahmood en_US
dc.description.abstract Insufficient water supply and deterioration in water quality are serious concerns in various regions of the world. These problems are due to several reasons that include sustained urban development, pollution of surface and underground water, uneven water resources distribution and recurrent droughts worldwide due to global warming. Therefore, new sustainable water management models are emerging. Wastewater treatment offers treated wastewater with a quality that should be beneficial for use. To achieve this goal, wastewater treatment usually involves several steps, such as biodegradation of organic matter, precipitation of suspended solids, nutrients removal, and disinfection to inactivate or kill pathogenic microorganisms. Disinfectants produce a wide range of disinfection by-products (DBP), having health and regulatory concerns. Conventionally ‘Grab Sampling’ has been the preferred method for DBPs monitoring but may not be sufficient or economically feasible thus alternative techniques are needed. In this study, non targeted screening of disinfection by-products was performed by Low Density Polyethylene (LDPE) passive sampling at Membrane Bioreactor (MBR) waste water treatment plant in Islamabad. This research study consisting of two-parts i.e. computational and experimental. First part based on development of two parameter model for the estimation of Low Density Polyethylene (LDPE) to water partition coefficients. For this purpose, data sets were retrieved from literature. Then most suitable dependent variable (Kpdms) and independent variables (Kow and Kaw) was selected using AIC information criteria AKIAKE. Subsequently, Multi Linear Regression (MLR) was performed to train the model on experimental datasets while cross validation was done by using models1 via ‘R’ programming. Principal Component Analysis (PCA) was also executed for dimensionality analysis to check the redundancy of this model and to ascertain which variable is contributing to maximum information. In second part, being the most convenient passive sampler, LDPE was being selected and prepared. At time of deployment, four replicates field strip samples were simultaneously submerged into waste water with the help of BBQ grills and metallic gauzes, and exposed for period of 15 and 30 days from Aug 2018 to Dec 2018. After these exposure experiments, the samples were carefully retrieved, instantly wrapped in aluminum foil and carried to the lab in ice box to secure the adsorbed contaminants for further analysis. These adsorbed contaminants were extracted by ethyl acetate. Resultant samples were stored in vials for GCMS time of flight MS analysis and characterized via NIST library match. 116 DIBs were identified on the basis of library match score > 800. Results were further processed for risk and fate analysis through modelling of EPI suite. Results of non-targeted screening of disinfection by-products have suggested that the disinfected waste water is still not safe for non-potable use and need further polishing treatment using Titanium Nanotubes (TNTs) and char. en_US
dc.language.iso en_US en_US
dc.publisher School Of Natural Sciences National University of Sciences & Technology (NUST) Islamabad, Pakistan en_US
dc.subject Non-Targeted Screening Wastewater Organic Disinfection Byproducts using Low Density Polyethylene (LDPE) Passive Samplers en_US
dc.title Non-Targeted Screening of Wastewater Organic Disinfection Byproducts using Low Density Polyethylene (LDPE) Passive Samplers en_US
dc.type Thesis en_US


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