http://reposit.library.du.ac.bd:8080/xmlui/xmlui/handle/123456789/16 2026-04-28T09:13:59Z 2026-04-28T09:13:59Z Parvin, Nargis http://reposit.library.du.ac.bd:8080/xmlui/xmlui/handle/123456789/4816 2026-04-19T04:07:09Z 2026-04-19T00:00:00Z

A Comprehensive Analysis of Residual Antibiotics, Organochlorine Pesticides and Heavy Metals in Beef and Chicken Parvin, Nargis Bangladesh is renowned for its agriculture-based economy. The farming of poultry and livestock is extremely popular in the country. Consumers in Bangladesh have a strong preference for beef and chicken meat, and these products are widely available. Toxic substances from various sources can permeate food animals through their feed and the environment, eventually making their way through the entire food chain via bioaccumulation and biomagnification. Additionally, these chemicals can enter the human body through the consumption of these foods, leading to significant public health concerns. This doctoral research focuses on identifying and measuring chemical pollutants such as leftover antibiotics, organochlorine pesticides, and heavy metals in beef and broiler chicken meat as well as liver samples, while assessing the health risks associated with each contaminant. Additionally, it aims to explore potential methods for reducing these contaminants. In this research, the presence of antibiotic residues (including tetracycline, oxytetracycline, chlortetracycline, amoxicillin, and patulin) in samples of beef meat, liver, and chicken meat, liver was examined utilizing reversed-phase High Performance Liquid Chromatography with a photodiode array detector (HPLC-PDA). Organochlorine pesticides and heavy metals were assessed using Gas Chromatography with an electron capture detector (GC-ECD) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS), respectively. The beef and chicken meat and liver samples were extracted employing a modified version of the Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) method designed for antibiotics and organochlorine pesticides. A total of 180 biological samples, including beef meat, beef liver, and broiler chicken meat and liver, were collected for this study from local markets of Dhaka North and South City, Bangladesh. A total of one hundred and twenty samples (with 30 each of beef meat, beef liver, chicken meat, and chicken liver) were examined for each antibiotic. The correlation coefficients (r²) demonstrated a linear relationship, measuring 0.9978, 0.9980, and 0.9988 for oxytetracycline, tetracycline, and chlortetracycline, respectively, across six concentration levels. Matrix-matched calibration was performed for each matrix, resulting in linear correlation coefficients (r²) of 0.9980, 0.9990, and 0.9981 for beef meat; 0.9985, 0.9984, and 0.9973 for beef liver; 0.9988, 0.9982, and 0.9993 for chicken meat; and 0.9980, 0.9985, and 0.9991 for chicken liver concerning oxytetracycline, tetracycline, and chlortetracycline, respectively. The intra-day and inter-day recovery tests for each of the tetracyclines (TCs) were conducted, with relative standard deviation (RSD%) remaining below 10%. The Limit of Detection (LOD) for oxytetracycline, tetracycline, and chlortetracycline were recorded at 1.11, 1.15, and 1.19 μg/kg, respectively, with the associated Limit of Quantification (LOQ) being 3.17, 3.84, and 3.96 μg/kg. Residual oxytetracycline was V found and measured in eight beef liver samples, with levels varying from 86.76 to 368.97 μg/kg, all below the Maximum Residue Limit (MRL) set by Codex. However, one beef liver sample surpassed the MRL established by the European Union (EU), registering at 368.97 μg/kg. Oxytetracycline was detected in three chicken meat samples (220.94, 153.45, and 101.32 μg/kg), tetracycline was present in two samples (715.00 and 698.88 μg/kg), and chlortetracycline was found in one sample (677.35 μg/kg). Four of the positive samples exceeded the Codex recommended MRL, while six positive chicken meat samples were above the MRL limit set by the EU. The linear correlation coefficient (r²) for standard amoxicillin across six different concentrations was determined to be 0.9982. For amoxicillin in various samples, the respective linear correlation coefficients (r²) were 0.9979 for beef meat, 0.9980 for beef liver, 0.9995 for chicken meat, and 0.9981 for chicken liver. The intra-day and inter-day recovery experiments were conducted for amoxicillin, yielding a relative standard deviation (RSD%) within 10%. The limit of detection (LOD) and limit of quantification (LOQ) for the validated method were found to be 0.55 and 1.84 μg/kg for standard amoxicillin, respectively. The Codex Alimentarius Commission and the EU have established a maximum residue level (MRL) of 50 μg/kg for amoxicillin in beef and chicken meat and liver. Residual levels of amoxicillin were identified in seven beef meat samples, with concentrations ranging from 4.89 to 9.36 μg/kg, and in fifteen beef liver samples, which varied from 10.39 to 89.47 μg/kg. Among the beef liver samples, two exceeded the MRL, with values of 53.46 μg/kg (BL10) and 89.47 μg/kg (BL14). The linear correlation coefficient (r²) was determined to be linear at 0.9991 for standard patulin across six different concentrations. For patulin, the correlation coefficients (r²) were found to be linear at 0.9984, 0.9983, 0.9980, and 0.9990 in beef meat, beef liver, chicken meat, and chicken liver, respectively. An intra-day and inter-day recovery study was conducted for patulin, and the RSD% remained within 10%. The limit of detection (LOD) for the proposed method was established at 0.18 and 0.60 μg/kg for standard patulin. Residual levels of patulin antibiotic (as well as mycotoxin) were identified in twenty-five beef samples, with concentrations ranging from 47.72 to 193.91 μg/kg, and in eighteen chicken meat samples, with levels from 16.94 to 310.53 μg/kg. Patulin was detected in six beef liver samples, with concentrations between 43.31 and 166.91 μg/kg, and in eleven chicken liver samples, with levels ranging from 14.75 to 52.88 μg/kg. The health risk for each antibiotic was assessed for adults, and the hazard index (HI) was found to be less than 1. A total of one hundred and twenty samples (30 each of beef meat, beef liver, chicken meat, and chicken liver) were subjected to analysis for organochlorine pesticides (OCPs). To establish a standard calibration curve, six varying concentrations of a standard solution (comprising 20 OCPs) were injected into the gas chromatograph-electron capture detector VI (GC-ECD). The correlation coefficients (r²) showed a linear relationship, with values of 0.9999, 0.9994, 0.9990, 0.9988, 0.9980, 0.9997, 0.9991, 0.9994, 0.9993, 0.9996, 0.9983, 0.9978, 0.9995, 0.9985, 0.9990, 0.9997, 0.9981, 0.9991, 0.9994, and 0.9998 for alpha- BHC, gamma-BHC, beta-BHC, delta-BHC, heptachlor, aldrin, heptachlor epoxide, transchlordane, cis-chlordane, endosulfan I, 4, 4’-DDE, dieldrin, endrin, 4, 4’-DDD, endosulfan II, endrin aldehyde, 4, 4’-DDT, endosulfan sulfate, methoxychlor, and endrin ketone, respectively. Recovery experiments for intra-day and inter-day were conducted for 20 OCPs, and the relative standard deviation percentage (RSD%) remained within the acceptable limit of 20%. Out of thirty beef meat samples tested, alpha-BHC was detected in 11 samples (ranging from 1.01 to 62.49 μg/kg), gamma-BHC in 9 samples (with levels from 1.22 to 103.01 μg/kg), beta-BHC in 9 samples (from 1.13 to 8.94 μg/kg), and delta- BHC in 28 samples (with concentrations between 84.45 and 329.08 μg/kg). Heptachlor was found in 13 samples (ranging from 0.97 to 29.64 μg/kg), while aldrin was present in 20 samples (from 0.96 to 61.71 μg/kg). Heptachlor epoxide appeared in 28 samples (with levels from 57.87 to 304.25 μg/kg), trans-chlordane was found in 14 samples (from 0.86 to 7.90 μg/kg), and cis-chlordane in 18 samples (ranging from 0.61 to 6.22 μg/kg). Endosulfan I was detected in 26 samples (with concentrations between 1.23 and 22.86 μg/kg), and 4, 4´-DDE was found in 20 samples (ranging from 0.17 to 21.41 μg/kg). Dieldrin was present in 22 samples (from 0.47 to 36.50 μg/kg), endrin in 17 samples (ranging from 0.63 to 16.98 μg/kg), and 4, 4´-DDD was detected in 23 samples (with levels from 0.48 to 38.94 μg/kg). Endosulfan II was found in 27 samples (ranging from 1.61 to 187.29 μg/kg), and endrin aldehyde was present in 19 samples (from 0.98 to 24.70 μg/kg). Additionally, 4, 4´-DDT was detected in 15 samples (ranging from 0.24 to 76.81 μg/kg), endosulfan sulfate in 12 samples (with levels from 0.83 to 11.10 μg/kg), methoxychlor was found in 18 samples (ranging from 0.77 to 14.04 μg/kg), and endrin ketone was present in 4 samples (from 0.83 to 10.55 μg/kg), all measured in μg/kg. Among the thirty beef liver samples analyzed, alpha-BHC was detected in 28 samples (ranging from 17.40 to 340.42 μg/kg), gamma-BHC in 16 samples (from 1.75 to 15.79 μg/kg), beta- BHC in 16 samples (from 2.87 to 42.82 μg/kg), delta-BHC in 24 samples (from 2.24 to 26.41 μg/kg), heptachlor in 22 samples (ranging from 4.67 to 16.67 μg/kg), aldrin in 21 samples (from 0.66 to 20.93 μg/kg), heptachlor epoxide in 28 samples (ranging from 65.92 to 197.61 μg/kg), trans-chlordane in 16 samples (from 0.43 to 29.68 μg/kg), cis-chlordane in 10 samples (from 1.19 to 6.22 μg/kg), endosulfan I in 24 samples (ranging from 1.15 to 5.02 μg/kg), 4, 4´-DDE in 11 samples (from 0.10 to 3.38 μg/kg), dieldrin in 21 samples (ranging from 1.03 to 6.43 μg/kg), endrin in 20 samples (from 1.03 to 6.43 μg/kg), 4, 4´- DDD in 7 samples (ranging from 0.59 to 1.84 μg/kg), endosulfan II in 20 samples (from 0.22 to 25.55 μg/kg), endrin aldehyde in 26 samples (from 0.21 to 31.55 μg/kg), 4, 4´-DDT VII in 9 samples (ranging from 3.08 to 17.75 μg/kg), endosulfan sulfate in 2 samples (from 0.04 to 0.05 μg/kg), and methoxychlor in 8 samples (ranging from 0.26 to 11.67 μg/kg). In the thirty chicken meat samples, alpha-BHC was detected in 2 samples (at 1.00 and 2.87 μg/kg), gamma-BHC in 1 sample (at 4.94 μg/kg), delta-BHC in 27 samples (ranging from 5.91 to 201.65 μg/kg), heptachlor in 4 samples (ranging from 6.81 to 8.93 μg/kg), aldrin in 10 samples (from 1.60 to 33.93 μg/kg), heptachlor epoxide in 25 samples (ranging from 137.76 to 270.60 μg/kg), trans-chlordane in 13 samples (from 3.64 to 27.96 μg/kg), cischlordane in 7 samples (ranging from 0.44 to 2.24 μg/kg), endosulfan I in 25 samples (from 1.72 to 5.91 μg/kg), 4, 4´-DDE in 2 samples (at 0.41 and 1.69 μg/kg), dieldrin in 12 samples (ranging from 0.72 to 13.53 μg/kg), endrin in 10 samples (from 0.44 to 12.73 μg/kg), 4, 4´-DDD in 17 samples (ranging from 1.48 to 5.75 μg/kg), endosulfan II in 9 samples (from 0.97 to 56.96 μg/kg), endrin aldehyde in 16 samples (ranging from 0.93 to 5.03 μg/kg), 4, 4´-DDT in 7 samples (from 1.39 to 71.84 μg/kg), endosulfan sulfate in 6 samples (ranging from 0.21 to 3.14 μg/kg), and methoxychlor in 13 samples (from 1.59 to 5.95 μg/kg). In a study of thirty chicken liver samples, alpha-BHC was detected in 23 samples, with concentrations ranging from 2.12 to 159.13 μg/kg. Gamma-BHC was present in 3 samples, showing levels between 2.17 and 5.85 μg/kg, while beta-BHC was found in 10 samples, with values between 13.87 and 69.96 μg/kg. Delta-BHC was identified in 25 samples, displaying concentrations from 1.67 to 224.65 μg/kg. Heptachlor was detected in 3 samples, at levels ranging from 3.01 to 7.78 μg/kg. Aldrin appeared in 10 samples, with concentrations varying from 0.91 to 259.93 μg/kg. Heptachlor epoxide was found in 28 samples, with a range of 58.71 to 196.47 μg/kg. Trans-chlordane was present in 3 samples, with levels from 5.26 to 336.49 μg/kg, and cis-chlordane was identified in 4 samples, showing concentrations between 0.12 and 280.64 μg/kg. Endosulfan I was found in 26 samples, with values ranging from 1.23 to 22.86 μg/kg. The compound 4, 4'-DDE was detected in 9 samples (0.54 to 12.79 μg/kg), while dieldrin was present in another 9 samples, ranging from 0.84 to 9.09 μg/kg. Endrin was found in 9 samples, with concentrations between 1.24 and 40.29 μg/kg, and 4, 4'-DDD was detected in 10 samples, showing levels from 0.35 to 28.90 μg/kg. Endrin aldehyde appeared in 18 samples, with concentrations ranging from 1.12 to 307.65 μg/kg. 4, 4'-DDT was identified in 12 samples, at levels between 1.37 and 29.80 μg/kg, while endosulfan sulfate was found in 5 samples (0.97 to 204.26 μg/kg) and methoxychlor in another 5 samples, ranging from 0.72 to 5.68 μg/kg. Endrin ketone was present in 4 samples, with concentrations from 1.95 to 4.47 μg/kg. The health risks associated with these pesticides were assessed, revealing that the hazard indices for delta-BHC, heptachlor, aldrin, heptachlor epoxide, endrin, endrin aldehyde, and endrin ketone exceeded 1 for both adults and children. VIII A total of 120 biological samples were examined, comprising 30 each of beef meat, beef liver, chicken meat, and chicken liver for ten heavy metals. The samples underwent digestion with concentrated HNO3 and H2O2. In the ICP-MS, four varying concentrations of a standard solution (a mix of the ten metals) were injected to establish calibration curves. A linear correlation coefficient (r²) was determined for chromium (Cr), nickel (Ni), lead (Pb), cadmium (Cd), arsenic (As), manganese (Mn), cobalt (Co), copper (Cu), zinc (Zn), and selenium (Se), with values of 0.9988, 0.9989, 0.9990, 0.9991, 0.9991, 0.9994, 0.9991, 0.9994, 0.9998, and 0.9993, respectively. The Limits of Detection (LOD) and Limits of Quantification (LOQ) were calculated for each of the ten metals. Copper (Cu), manganese (Mn), cobalt (Co), zinc (Zn), and selenium (Se) were detected and quantified across all beef and chicken meat and liver samples. The concentration of Cu ranged from 2.82 x 10⁻⁵ to 1.24 x 10⁻⁴, 0.09 to 0.23, 0.93 to 4.68, and 3.94 to 12.52; Mn levels ranged from 1.77 x 10⁻³ to 6.69 x 10⁻², 7.62 to 57.28, 0.005 to 0.05, and 0.04 to 0.10; Co concentrations were between 2.89 x 10⁻³ to 2.95 x 10⁻², 5.33 to 11.82, 0.03 to 6.28, and 2.95 to 9.18; Zn levels varied from 0.11 to 0.55, 81.03 to 203.27, 23.70 to 41.20, and 41.26 to 152.73, while Se was found in a range of 5.02 x 10⁻⁵ to 4.40 x 10⁻⁴, 0.38 to 1.54, 0.48 to 0.81, and 1.12 to 2.54 in all beef meat, beef liver, chicken meat, and chicken liver samples, respectively. Cr concentrations were found to be between 2.63 x 10⁻⁵ to 3.20 x 10⁻⁴, 0.06 to 0.20, 0.58 to 1.68, and 0.32 to 1.42 in 30 beef meat, 9 beef liver, 30 chicken meat, and 30 chicken liver samples. Ni levels varied from 2.43 x 10⁻⁵ to 9.86 x 10⁻⁵, 0.04 to 0.92, 0.10 to 1.45, and 0.06 to 42.63 in 30 beef meat, 29 beef liver, 29 chicken meat, and 30 chicken liver respectively. Pb was found at concentrations ranging from 1.12 x 10⁻⁶ to 7.46 x 10⁻⁴, 0.05 to 24.36, 0.05 to 1.71, and 0.03 to 5.28 in 30 beef meat, 29 beef liver, 26 chicken meat, and 22 chicken liver. Cd levels were detected between 4.82 x 10⁻⁶ to 5.61 x 10⁻⁴, 0.04 to 1.17, 0.14 to 0.18, and 0.04 to 0.24 in 30 beef meat, 12 beef liver, 2 chicken meat, and 3 chicken liver respectively. As concentration ranged from 1.34 x 10⁻⁶ to 4.41 x 10⁻⁴, 0.01 to 0.69, 0.005 to 0.52, and 0.005 to 10.79 mg/kg in 30 beef meat, 28 beef liver, 19 chicken meat, and 24 chicken liver samples respectively. The health risk assessment (EDI, THQ, HI, TCR) for heavy metals was conducted for both adults and children. Chemical pollutants can build up in the fatty tissues of beef and poultry, potentially changing the fatty acid profile and causing genetic mutations. Therefore, the fatty acid composition and overall fat content were examined using gas chromatography with a flame ionization detector (GCFID). The average fat content (%) calculated was 1.57, 6.19, 0.78, and 2.95% for beef meat, beef liver, broiler chicken meat, and liver, respectively. This research underscores comprehensive evidence of the occurrence of antibiotic, pesticide, and heavy metal residues in raw beef and broiler chicken meat and liver in Bangladesh. Although most samples were within internationally accepted limits, several exceeded Codex and EU MRLs, posing potential public health concerns. This thesis is submitted for the degree of Doctor of Philosophy.

2026-04-19T00:00:00Z Suraiya, Sayma http://reposit.library.du.ac.bd:8080/xmlui/xmlui/handle/123456789/4810 2026-04-13T04:22:04Z 2026-04-13T00:00:00Z

Optimal Production Planning Models for Garment Industries in Bangladesh under Stochastic Atmosphere Suraiya, Sayma A key pillar of Bangladesh’s economy, the ready-made garment (RMG) industry makes a substantial contribution to the country’s GDP, foreign exchange earnings, and job creation. This study presents a thorough modeling framework for production planning optimization in Bangladesh’s RMG sector under both deterministic and stochastic circumstances. In order to maximize profit and optimize production planning of the RMG industry, this study develops first a deterministic linear programming (LP) model. The model finds the optimal product mix and output levels to effectively meet demand while lowering production costs and increasing profitability when it is applied to a real-world factory setting in Gazipur, Dhaka. Uncertainties in global demand trends, variable manufacturing costs, volatile raw material prices, and dynamic international trade rules etc. are the most vital reasons of the continuously increased challenges to the industry. This research seeks to develop strong decision-making frameworks to support strategic and tactical decision-making under such uncertainty. Taking into consideration economic fluctuations, the deterministic LP is expanded in this stage into stochastic programming models (SLP) in which all significant factors are represented as random variables, including cost coefficients, demand levels, labor availability, and processing durations. Another stochastic model also formed in this research by combining all the scenarios, as it is not actually predictable which situation would be come. This approach provides a strong planning for RMG under a variety of circumstances by capturing holistic uncertainty. A two-stage stochastic linear programming model (TSLP), in which only a chosen subset of parameters remains stochastic, is developed next in this study to reduce uncertainty. Following the revelation of parameter realizations, decisions taken in stage one are modified in stage two. This model improves tractability and increases adaptability. Expected Value of Perfect Information (EVPI) and Value of the Stochastic Solution (VSS), two important parameters in stochastic programming that measure the advantages of uncertainty modeling and perfect foresight, are used to assess the performance of deterministic, general stochastic, and two-stage stochastic models. xiii In next, two separate two-stage stochastic (TSLP) models are formulated in this study, where the demand uncertainty represents various scenarios, including seasonal variations. In this case, the fluctuation of one product’s demand is presented. Key uncertainties in demand, export prices, labor costs, raw material costs, and operational costs related to that specific product are included in scenarios that are created using historical data and probabilistic distributions. These models are then expanded into a multistage stochastic programming (MSLP) model, which simulates a decision process by allowing decision variables to change over several stages as demand unfolds and gradually adapting decisions at each stage to capture dynamic changes and integrating learning over time. By applying these models, a RMG factory can be able to decide the best production planning along with the profit and cost optimization. A comparison between the two-stage and multistage is presented next. LINDO and AMPL (A Mathematical Programming Language) are used to solve all the deterministic and stochastic models, while Excel Solver is applied for preparing all the graphical presentations of this study. In terms of predicted profit, robustness to uncertainty, and overalsl operational efficiency, the stochastic models perform noticeably better than the deterministic model, according to computational results validated using real-world data gathered from RMG companies in Bangladesh. By offering an integrated optimization framework that enables RMG stakeholders to use scenario-based planning, efficient, uncertainty-aware design tools from deterministic LP to comprehensive multistage stochastic programming. Optimization tools to increase profitability, the study adds both theoretically and practically significant, as global markets continue to vary. By presenting a thorough modeling framework designed to address the unique difficulties faced by Bangladesh’s RMG industry in order to facilitate adaptable and proactive decision-making. In the geopolitically unstable environment, where flexibility and risk-aware planning are critical also in the post-COVID atmosphere, these findings are especially pertinent. And provide resiliency in a world economy that is becoming more and more uncertain. This thesis is submitted for the degree of Doctor of Philosophy.

2026-04-13T00:00:00Z Hossain, Mukul http://reposit.library.du.ac.bd:8080/xmlui/xmlui/handle/123456789/4794 2026-03-03T04:59:01Z 2026-03-03T00:00:00Z

Fabrication of Zinc Oxide (ZnO) Nanorods on Aluminium Doped ZnO (AZO) Seeding Layers Hossain, Mukul Aluminium-doped zinc oxide (AZO) thin films and ZnO nanorods (NRs) were synthesized and characterized to explore their structural, optical, and electrical properties. AZO seed layers with varying Al concentrations 2, 3, 5, and 8 mol% were deposited on soda-lime glass via spin coating, followed by hydrothermal growth of ZnO NRs. XRD and SEM confirmed vertically aligned, c-axis-oriented nanorods, with morphology influenced by doping and annealing temperature. Optimal crystallinity was achieved at 250 °C, while higher temperatures led to lattice relaxation and reduced structural quality. Photoluminescence revealed UV near-band-edge emission (~380 nm) and visible deep-level emission (500–700 nm), with DLE intensity suppressed at 8 mol% doping, indicating reduced defect density. Both AZO and ZnO NRs showed high optical transparency, and band gaps ranged from 3.44–3.55 eV (AZO) and 3.05–3.15 eV (ZnO NRs), tunable via Al doping. The electrical conductivity and film thickness were strongly influenced by both Al concentration and annealing conditions. The favorable combination of structural integrity, high transparency, tunable band gaps, and improved conductivity renders these AZO/ZnO nanostructures promising candidates for application in a wide range of optoelectronic devices. This thesis is submitted for the degree of Master of Philosophy.

2026-03-03T00:00:00Z Islam, Md. Nazrul http://reposit.library.du.ac.bd:8080/xmlui/xmlui/handle/123456789/4782 2026-03-02T05:48:00Z 2026-03-02T00:00:00Z

Particle Phase Organic Compounds in the Atmospheric Particulate Matter at Urban and Rural Areas in Bangladesh Islam, Md. Nazrul Particle Phase Organic Compounds (PPOCs) are significant organic fraction of atmospheric suspended particulate matter. They comprise of harmful chemicals which have adverse effects on human health. There is very limited research regarding the source, seasonal variation and health impact of PPOCs in Bangladesh. The objectives of this study are to measure the 16 PPOCs at four different locations with seasonal variation, correlation coefficient, source identification with positive matrix factorization (PMF), influence of wind direction with backward air mass trajectory analysis by HYSPLIT and potential health risk assessment. In this study, suspended particulate matter samples have collected on quartz filters with a low volume sampler (Model: 700) at four locations in Bangladesh (Dhaka, Rajshahi, Narayangonj and Bhola) for one year at each location between January, 2016 and February, 2020. Concentration of 16 organic compounds (Naphthalene, Anthracene, Diazinon, Deltamethrin, Pyrabenzoxime, Pyrazosulfuran, Prophenophos, Butachlor, Propiconazole, Cymoxanil, Cypermethrin, Lamdacyhalothrin, Dimethoate, Chlorpyriphos, Carbofuran, and Metalaxyl) were determined with a Gas Chromatography-Mass Spectrometry (GC-MS). The total average PPOCs concentration was 11.60 ± 0.1 μgm-³ in Dhaka, 8.69± 0.3 μgm-³ in Rajshahi, 11.84±0.4 μgm-³ in Narayangonj and 7.22± 0.2 μgm-³ in Bhola. These concentrations were 2 to 18 times higher during winter season than that of monsoon season. The PPOCs concentration was similar between Dhaka and Narayangonj and it was 32% higher than Rajshahi and Bhola. Source apportionment by Positive Matrix Factorization (PMF) revealed five sources of PPOCs - diesel exhaust, biomass burning, industrial emission, gasoline exhaust, and other sources. Industrial emission was predominant in urban areas whereas biomass burning was the major pollution vi source in rural areas. Backward air mass trajectory analysis by Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) indicated that during winter more than half of the period wind (60%) comes entirely from the Indo- Gangetic Plain (IGP) region originating from Africa. In monsoon, half of the wind (50%) comes entirely from the Indian Ocean through the Bay of Bengal. According to the health risk assessment study, 16 PPOCs had a Hazard Index (HI) value of 30.19, indicating a serious non-carcinogenic effect. The largest contributor to the hazard index (32%) was dimethoate. One in 340 people had a chance of getting cancer in their lifetime. The average lifetime cancer risk value (2.9410-3) was higher than the US Environmental Protection Agency's (USEPA) recommended threshold (110- 4). Naphthalene was found to pose the highest carcinogenic risk. As particulate phase organic compounds are mostly emitted from anthropogenic sources and pose severe health threat, so public awareness should be raised and more detailed research should be conducted in local and regional level. This thesis is submitted for the degree of Doctor of Philosophy.

2026-03-02T00:00:00Z