Qatar Foundation Annual Research Conference Proceedings Volume 2018 Issue 1

Study of polyaniline-silver nanocomposite as humidity sensor J. Bhadra, A. Popelka, N. J. Al-Thani, A. Abdulkareem Center for Advanced Materials, Qatar University, Qatar Abstract In this piece of work focus on fabrication of resistive type humidity sensor using polyaniline-silver nanocomposite (PPVA-Ag). Four different nanocomposites using four concentrations of silver (0.5,1.0, 1.5 and 2.0 M) and polyaniline (PANI) dispersed in polyvinyl alcohol matrix (PVA). PANI, and PVA concentrations are kept constant. Thin PPVA-Ag film on interdigited gold electrode fingers gives excellent sensitivity towards humidity at room temperature. 1. Introduction Since last few decades the information of nanoscience and nanotechnology has been explored extensively to obtain functionalized nanomaterials. One such category of nanomaterial is the polymer- metal nanocomposite, with enhanced mechanical, elastic, optical, electrical and dielectric properties [1]. Polymer nanocomposites are materials with nanosized one dimensional inorganic filler particles (around 10–100 ˚A), dispersed in an organic polymer matrix. An important parameter which has significant importance in many industries such as food, agricultural, clinical equipment and electronics is humidity, it is considered to be one of the most frequently measured physical parameters [2-3]. With the advancement in moisture sensitive technologies, research to achieve high efficient, low cost, reliable and miniature size of material sensitive to humidity change has gained acceleration. As among metal nanoparticles, Ag has high electrical and thermal conductivities, so the composite of Ag dispersed in PANI-PVA matrix gives rise to a functional materials, with improved antimicrobial activity and sensitivity towards humidity. This paper we focus on surface analysis of the thin film obtained using scanning electron microscopy and study on the humidity sensitivity. 2. Methods 2.1 Synthesis of Ag nanoparticles Four different concentrations of silver nitrate (AgNO3) is dispersed in aqueous PVA solution under constant stirring and heating at 60°C followed by photo reduction using UV-lamp having wavelength 390 nm for 24 hours. After exposing the above solutions with UV light for 24 hours, finally, yellowish-red colloid of Ag nanoparticles with average diameters of ∼30 nm and ∼70 nm uniformly dispersed in PVA are obtained. 2.2. Synthesis of PANI-Ag nanocomposite and pure PANI: The PANI-Ag nanocomposite blend is synthesized by in-situ chemical polymerization (Figure-1) of aniline monomer in the colloid solution obtained from section 2.1. During this process, aniline-DBSA is added to the Ag-PVA colloidal solution, followed by addition of the aqueous APS solution dropwise. The resulting blend mixture is left to react for 24 h under constant stirring at 5–10 °C. The colloidal solution obtained are used to prepare thin film on glass slide and interdigitated gold electrode washed with DI water and acetone and dried. Keeping the other concentrations and methods constant four different PPVA-Ag nanocomposites are prepared with 0.5, 1.0,1.5 and 2.0 M of AgNO3.

Figure 1: Steps followed to prepare PANI-Ag nanocomposites 2.3. Study of Effect of humidity on the PPVA-Ag nanocomposites A homemade setup is used to study of effect of humidity on the PPVA-Ag nanocomposites coated on the interdigited gold electrode fingers using dropcast method. The humidity chamber consists of transparent polymer with three holes for nitrogen gas inlet, humidity inlet and electrical wires for conductivity measurement. The schematic diagram of the setup is shown in the Figure 2. Humidity meter and the polymer coated electrodes are placed inside the chamber. The control of humidity inside the chamber has been done using humidifier and N2 gas during the experiment. And keithley sourcemeter 2400 has been used to measure the resistivity.

Figure 2: Schematic diagram of humidity measurement setup 3.1 Scanning Electron Microscopy studies The results of surface morphology analysis using SEM are shown in Figure 3. From the images it is seen that Ag nanoparticles are well dispersed in PANI-PVA matrix. Such results are observed because chemical method of preparation has been adopted. With the increase of Ag concentration there are not much changes in the particle size, however the degree of agglomeration increase, that causes the increase in surface roughness.

Figure 3: SEM images of (a) PPVA-Ag-0.5, (b) PPVA-Ag-1.0, (c) PPVA-Ag-1.5 and (d) PPVA-Ag-2.0. 3.2 Effect of Humidity We have used all the four types of composites for this measurement. For this measure at first the humidity chamber is blown with N2 gas for few minutes to reduce the humidity to RH 20 % at room temperature. Once the reading in the humidity meter is stable, resistance of the thin film has been measured. Each time for resistance measurement voltage reading for 10 mA current has been repeated for 10 times with time sweep of 500 ms. In order to reduce the error we repeated the whole measurement for 15 times at each RH measured, shown in Figure 4 for PPVA-Ag 1.0M sample. During the experimental process each step is maintained at constant parameters till the electrical signals reading reached a steady value. All the four plots describing resistance change as a function of humidity for each composite measured has been shown in inset of Figure 4. It is has been observed that, there is not much difference between the resistance curves as a function humidity for all the four composites. As the humidity increases water vapour contributes to the reducing the conductivity in two ways, firstly water molecules donate electrons to the valence band of PANI molecules, therefore decreasing the number of holes and increasing the bandgap and secondly as PVA is hydrophilic, so it absorbs water molecules and get expanded, this leads to increase the interparticular distances between the conducting fillers of the composites, and reducing the conductivity. Because of these two reasons higher the RH level lower the electrical conductivity.

Figure 4: The effect of Relative humidity on the resistance of PPVA-Ag-1.0M, Inset The effect of Relative humidity on the resistance of four PPVA-Ag samples.4. Reference: [1] M. Joulazadeh, A. H. Navarchian, Advances in Polymer Technology, 33, 2014, 21461. [2] A. T. Ramaprasad, V. Rao, Sens. Actuat. B, 148, 2010, 117–125. [3] J. Wang, X. Wang, X. Wang, Sens. Actuat. B, 108, 2005, 445–449

Energy policy and security of a country heavily depends on its resources, geography, demographics and economic structure. While most active strategies include the discovery, extraction and utilization (through new infrastructure) of energy resources, a more subtle approach to reduce energy demand and increase energy security is to use the resources more efficiently and conserve them to increase the life span in which they can be used. This understated approach is the implementation of energy efficiency policy. Energy efficiency taken holistically includes the improvements in technology as well as changes in human behavior to do a task with less amount of energy. While different studies have shown the impact of efficiency policies and programs on individual economic sectors (i.e. industrial, commercial, residential, agriculture and transport), a complete overview of the impact of efficiency on economy has received little attention. This approach overlooks the interdependence of each economic sector and their influence on each other. Similarly, the rebound effect, a consequence and a major element of efficiency is avoided in these studies as well. Rebound effect is the increase in energy consumption because of lower prices of energy commodities due to increase in efficiency. The rebound effect not only has a direct impact on the individual sector, like driving more miles because of a more efficient vehicle, it has also indirect consequences, such as going to a vacation because of the money being saved through efficiency. Thus, the study of efficiency, its dynamic influence and calculating a realistic magnitude are required to ideally approach the costs and benefits of implementing an efficiency program or policy. This research looks into the economy wide impacts of energy efficiency and the dynamic interaction and impacts of each sector on the other. First, a hierarchal list of variables, which influence the energy supply and demand of any economy, is created. Second, a list of indicators which measure the health of an economy is formed. Using data for the top 10, oil and gas producing countries (these countries give a good mix of economies which heavily rely on oil and gas rents such as Qatar, UAE, Saudi Arabia as well as economies, which produce some of the highest energy resources, while relying very little on its influence on their economies, such as US, Norway), the magnitude and impact of each variable to the economy is calculated. These variables are then used to create a system dynamics model which includes the production, conversion and transportation of energy from different sources to consumption in different sectors. Estimated energy efficiency measures and impacts are then incorporated into the systems model to see the effect of efficiency as well as the rebound effect on the economy. A major goal of this study is to find the future impacts of energy efficiency policies and the consequences of these policies, if they are not implemented because of financial constraints or present gains (such as more revenues from greater resource production). The cost benefits as well as the effective implementation of efficiency measures are calculated and compared using the economic indicators obtained in the second step. Finally, these indicators can be used to determine as to why some countries are more efficient with their energy resources as compared to others.

Energy consumption for air conditioning purposes accounts for 60-80% of electricity used in Qatar. As District Cooling Plants (DCPs) has a potential to reduce energy consumption and CO2 emissions, Qatar and GCC are continuously shifting paradigm towards adoption of DC plants to satisfy the rapidly growing demand in all sectors. However, DC plants usually rely on wet cooling towers for disposing the excess heat to the ambient. Hence the efficiency of DCPs is significantly influenced by the cooling tower effectiveness in heat disposal, which is dominated by latent heat or evaporation of water in a counter atmospheric current air stream. Operation district cooling plants (DCPs) under extremely high humidity in summer represents one of the major thermodynamic limitations in terms of maintain the outlet water temperature of cooling towers (i.e. chiller's condenser cooling water) as low as possible to guarantee higher efficiency of DCPs. The cooling tower efficiency degrades considerably at higher relative humidity of air, which approaches saturation limits in summer, where the cooling demand is high. The ambient wet-bulb (WB) temperature is a limiting factor for the capacity of cooling towers (CT), which determines the inlet cooling water temperature to the chiller's condenser (outlet water temperature from the CT). Due to prevailing weather conditions in Qatar and GCC, this temperature is designed based on 31 °C WB temperature in summer, which result in a 34 °C inlet condenser cooling water temperature. This represents a thermodynamic limitation to reduce the energy consumption of chillers, which lies under the focus of this study. Desiccant cooling is an environmentally attractive alternative to conventional mechanical air-conditioning, especially for air dehumidification purposes. It does not require ozone depleting refrigerants and it can be run off low temperature solar heat or waste heat. The electrical coefficient of performance of desiccant cooling can be above 20, making it over 6 times more efficient than conventional air cooled vapor compression system. This project seeks to develop new processes to reduce air humidity and WB temperature by around 6 °C prior to entering the CT to break the above mentioned thermodynamic limitation. Air dehumidification takes place using liquid to air membrane (3-fluid LAMEEs) for further dehumidification of air. A hybrid solar PV-Thermal system is used for regeneration of both desiccant systems. Lumped and numerical analysis has been conducted using COMSOL Multiphysics software to predict the outlet air temperature and humidity for 3-fluid LAMEEs when used for air cooling and dehumidifying. Results of the numerical and lumped analysis showed that the 3-fluid LAMEE alone can effectively decrease the humidity content of ambient air by up to 40%, while the outlet air temperature can be reduced by 6 °C. Accordingly, the inlet cooling water temperature to the chiller's condenser (outlet water temperature from the CT) can be reduced to 27-28 C, which provides a potential saving of around 25% in energy consumption of the Chiller in district cooling plants.

The consumption of electricity in residential buildings exceeds 20% in Qatar and can go up to 50% in other hot countries like Kuwait. The air-conditioning systems in hot countries like Qatar consumes around 60–80% of the total energy demand in buildings. This triggers researchers and industry experts in the built environment to explore new avenues towards reducing the cooling load on a building and study influential factors to enhance energy efficiency in buildings in such extreme climatic conditions. The carbon foot print of buildings can be reduced by reducing the cooling load through passive building design, using high efficiency equipment and incorporating renewable energy technologies such as solar systems, air source heat pumps, wind generators and ground source heat pumps are few to name that are widely used among many other available renewable technologies. The focus of this research work is on the Passivehouse building design incorporating solar hybrid Photovoltaic Thermal collectors (PV/T) as a source of renewable electricity and solar hot water for domestic use. Two different designs of a residential building for Modern Agro-Industrial Communities in Qatar were considered i.e. Pyramidal Shaped Building and Square Shaped Building. 3D energy models were created for both type of buildings using the IES software (Integrated Environmental Solutions) in virtual environment and thermal analysis was carried out. For the same building type, orientation and structure, two different criteria were applied to the model i.e. Passivehouse design vs. Conventional design. Pyramid shaped buildings are more stable but tend to cost more to construct when compared to traditional buildings. The sloping external walls tend to gain more solar energy and daylight through windows installed on the external walls. This provides an opportunity for solar panels installation on the external walls. The solar gain through external windows can be reduced to a minimum by effective solar shading and the daylight harvesting system can further reduce the artificial lighting gain inside the building. The results show that the passive house design of a building can save more than 70% of the cooling plant load, the as installed plant size and associated infrastructure. This will also considerably reduce the annual operational and maintenance cost of the building with just an extra 15% in construction cost. The cost analysis of passive house in comparison with a conventional house was carried out by QGBC (Qatar Green Building Council). In a nutshell this research work demonstrates how buildings' cooling load and carbon foot print can be reduced by effective solar shading, lower infiltration rates (air tight building design), highly insulated building fabric, natural ventilation, daylight harvesting system (that can help reduce artificial lighting gain inside the building) and heat recovery system.

The paper studies the effectiveness of applying value engineering to concrete mixtures. It was conducted in the State of Qatar on a number of strategic construction projects for the 2022 World Cup projects, in order to generally improve the quality and productivity of ready-mixed concrete used in construction and hydraulic projects. The application of value engineering to such concrete mixtures resulted in the following: Improving the quality of concrete mixtures and increasing the durability of buildings; Optimizing the use of resources, and enhancing sustainability; Reducing the use of cement, thus reducing CO2 emissions which ensure the protection of environment and public health; And Increasing the market share and competitiveness of concrete producers The research shows that applying of value engineering to concrete is an effective way to save around 5% of the total costs of concrete mixtures and, in turn, reducing the costs of construction projects.

Nowadays, many electrical utilities are moving towards self-healing distribution grid. This is realized by adding to distribution system various sensors, intelligent electronic devices (IEDs), phasor measurement units (PMU), sequence of event recorders (SERs), reclosers, detectors, measurement units, automated controllers, and other automation equipment. Those elements provide a continuous stream of data to support grid performance and improve its reliability. Huge amount of data obtained from different smart grid sources satisfy all the Big Data (BD) characteristics. The success of future electric grid depends mainly on the effective utilization of the huge amount of the data flow. This mass of information is essential to make next generation electric grid more efficient, reliable, secure, independent, and supportive during normal conditions and contingencies. The self-healing grid requires a robust real-time computation system that monitors, processes, provides predictive analytics, performs data mining and statistics, and makes faster decisions of the diverse and complex data collected within the traditional and nextgeneration electric grid. This helps to detect, locate, and isolate various faults, reconfigure and reroute power of the distribution network to minimize service disruptions and outages.Implementation of self-healing control system is associated with big data utilization which is a persisting challenge. Computational complexity challenges is associated with processing huge amounts of data during operation of the electric power system. Therefore, this paper presents acomprehensive studies of the impact of implementing a smart real-time dynamic self-healing control strategy using BD process platform with deep learning technique on the distribution system for current grid and future smart grid. The deep learning technique is a subfield of machine learning. The deep learning is shown to be highly efficient solution for the analysis of massive amounts of data which is performed by discovering and utilizing available regularities in the inputs to help self-healing control system to network reconfiguration, and coordination of various distributed energy resourcesin the smart grid. The deep learning system complexity does notdepend on the number of grid buses, this is because the power flow solving time is approximately linear with respect to the number of system buses. However, the complexity of the system depends on the number of the system inputs. The Long Short Term Memory (LSTM) recurrent neural network will be used in modeling sequential data such as time series data. Such network has the ability to learn contextual information over the history of the input sequence. The BD analyticswill be used as a key to deal with the uncertainties and different sizes of structured and unstructured data. The advanced analytics techniques such as predictive analytics, in addition to data mining, statistics, and faster decisions making will be utilized for data coming from sensors within the traditional and next-generation electric grid. The studies performed are based on real-time monitoring and control of the network topology and operating conditions taking into account different power sources and hybrid renewable energy sources which usually have different characteristics on the electric power grid. Finally, the real-time implementations of the proposed system will achieve dynamic resources optimization, network reconfiguration, and optimum operation of power grid using LSTM with big data platform.

In this work, a new dc-ac converter is proposed for grid integration purposes, namely, capacitor-tapped multi-module dc-ac voltage source converter. The main advantages of the proposed converter when compared with the conventional dc-ac modular multilevel converter (assuming the same voltage rating of semiconductor devices) are: (i) employment of a lower number of semiconductor devices, but with a higher current rating hence it provides operation with a lower number of gate driver circuits, and (ii) employment of a lower number of dc capacitors which reduces the number of measured variables, which affects positively the cost and reduces the computational burden of the employed controller.

Climate change is the most pressing global environmental issue today, with a potentially devastating impact on human development. According to the Intergovernmental Panel on Climate Change (IPCC) reports, Qatar is ranked as the highest CO2 per capita emitter globally. Qatar is contributing to the reductions of anthropogenic carbon dioxide (CO2) by supplying the world with Liquid Natural Gas (LNG), yet Qatar is being negatively imaged as highest CO2 per capita emitter. The reading of the highest CO2per capita has affected Qatar's ability to attract green investments and to improve the country's attraction in the tourism market. Qatar's position as the leader CO2 per capita has made it unattractive for investors both internally and externally because of the perception that the investment would not be ‘green’. The per capita emissions are a result of two main factors: the total absolute emissions and the total population. Two major and significant factors, consumption and population, should be taken into consideration when discussing the total absolute emissions for Qatar: The assumption for this equation is that the population uses all the produced energy, which is the denominator. This assumption is a disadvantage to Qatar due both to its low population and the fact that it is an energy producer. CO2emission would be much lower for Qatar if a consumption-based accounting system was used for the calculation of the per capita value. The use of emissions accounting measure is of vital importance to individual countries. There are two feasible carbon emissions accounting units: production-based accounting and consumption-based accounting systems. Production-based accounting is linked to economic system boundaries (greenhouse gas emissions from resident institutional units, analogous to gross domestic product). It involves measuring the emissions occurring within a country's boarder and does not take into account production chains extended across boundaries. An illustration of a production-based system examines the emissions generated from fuel purchases and allocates them the country producing the fuel, not the country consuming the fuel (OECD, 2016). While the Consumption based accounting system is related to how much this country emit for its domestic uses. Data are more difficult to obtain for the consumption-based approach because the computations are more complicated to compile as it relies on input-output tables, which includes all steps in production from raw material extraction through the final assembly and ultimately the final sale of the product (General Secretariat for Development Planning, 2009).The controversy comes in determining responsibility: is it the player initiating the polluting process (consumer) or the player producing the pollution (producer)? Consumption-based measures are preferred by developing countries while production-based measures are preferred by developed countries. Qatar is unfairly portrayed as the highest carbon dioxide emitter in the world in terms of per capita measures. Qatar's carbon footprint takes into account Qatar's energy production rather than the country's domestic consumption. The main argument of the paper is to discuss Qatar's CO2 emissions per capita compared to other reporting measures, and to examine the difference between using a consumption based CO2 emissions accounting system versus a production-based one for Qatar. The paper discusses the complications of using a production-based accounting versus a consumption-based accounting system for Qatar carbon dioxide emissions calculations. The research applies both of Quantitative and Qualitative Analysis. The Quantitative analysis is related to roughly re-estimate Qatar's CO2 Per Capita emissions figure based on Consumption based accounting system. The qualitative analysis focuses on creating different comparisons to compare Qatar's CO2 emissions in terms of different reporting measures to three different categories. First category is comparing Qatar's emissions against GCC countries; these countries have the major common attribute that they are mainly dependent on oil and gas revenues, similar demographic location, weather and lifestyle. The analysis outcomes of this category illustrates that KSA has the highest emissions for CO2 intensity and for the absolute emissions. The second comparison category is comparing Qatar's CO2 emissions against major Liquified Natural Gas (LNG) producers which are Australia and Malaysia. These comparisons showed that Australia has the highest emissions of Absolute CO2, CO2 intensity as well as the emissions per GDP. The third category was to compare Qatar's position related to the major global emitters, such as China, India, Russia, and USA. This comparison resulted in China having the highest absolute emissions, CO2Intensity as well as emissions per GDP. The Analysis outcome of the comparisons highlights that Qatar is not the highest CO2emitter in terms of absolute CO2 emissions, emissions intensity, and emissions per GDP compared to the GCC countries, major LNG producers and the world largest emitters. Qatar has the highest CO2 emissions per Capita due to two main factors: Qatar is the largest LNG producer and Qatar has a relatively small population when compared to other countries. Qatar is a developing country, it is the largest LNG exporter and it has third highest natural gas reserves in the world. Qatar makes an indirect contribution to mitigating the impact of climate change, which is done though exporting a clean form of energy, i.e., Liquefied Natural Gas. Even though Qatar is a major contributor for the supplying the world with clean energy, Qatar has taken other initiatives to minimize its carbon emissions. Continuous research and development will be a key element to Qatar overcoming the climate change challenges through Research and Development Centres. In summary, the research paper has four main sections. The first section of the paper includes a background on climate change, its impact and mitigations. The second section discusses Qatar's global position using different CO2 emission reporting measures, including Absolute CO2emissions (kt), CO2emissions per GDP (kg per PPP$ of GDP), CO2intensity (kg per kg of oil equivalent energy use), CO2emissions per capita (metric tons per capita). The third part explores Qatar's CO2 per capita calculation incorporating the consumption-based accounting system and assessing the complications of using a production-based accounting versus a consumption-based accounting system for Qatar carbon dioxide emissions calculations. The last section covers Qatar's clean initiatives and offers recommendation towards net zero emissions and improving Qatar sustainability figures.

The fluid flow and solute transport through fractures in rocks are processes that have importance for many areas of the geosciences, ranging from groundwater hydrology to petroleum engineering. It is well known that fractures play an important role in flow and transport processes through geologic formation and number of environmentally relevant problems require the analysis of mass transport in subsurface systems. As Qatar»s aquifer is Karstic, the development of an appropriate numerical model is necessary to take account the high contrast between the fractures and the porous matrix. Fractures are the set of rock discontinuities that can occur in geological formations at different scales. They intensively affect the transport processes because they represent the preferential flow and mass migration paths. In this study, we introduce an adaptation of the Eulerian Lagrangian Localized Adjoint Method (ELLAM) [1] for the simulation of mass transport in fractured porous media. The fractures are represented explicitly using the discrete fracture model (DFM) which handles explicitly the fractures and matrix. It involves describing each fracture individually and discretizing fractures as well as matrix [2]. Specific physical and geometrical properties are imposed for the fractures and matrix domains. This model can be used in the domains where a relatively small number of fractures exist. DFM is the most accurate model because fractures are considered without any simplification. However, this model requires enormous computational time and memory due to the dense meshes resulting from the explicit discretization of the fractures. As a consequence, its use requires highly efficient numerical methods for solving the flow and mass transport. The flow problem is solved using the Mixed Hybrid Finite Element Method (MHFEM) [3] which is well known to be accurate and efficient for complex geometries. It provides consistent and accurate velocity even in highly heterogeneous domain, which is a relevant property for flow in FPM. The obtained velocity field is then used to solve the mass transport problem with ELLAM. ELLAM combines an Eulerian and Lagrangian treatments without any splitting procedure by considering trial functions that depend on time and space. The results obtained by Celia et al. [1] demonstrated the mass conservation of the ELLAM in its formulation and its high computational efficiency compared to classical numerical method. In this work, a new ELLAM implementation is developed to address numerical artifacts (spurious oscillations and numerical dispersion) arising from the high contrast of velocities between fractures and porous matrix. Moreover, the efficiency of the developed ELLAM implementation was improved, taking advantage of the parallel computing on shared memory architecture for the tasks related to particles tracking and linear system resolving. The performance of ELLAM was tested by comparison against the Eulerian discontinuous Galerkin method based on several benchmarks dealing with different fracture configurations. The results highlight the robustness and accuracy of ELLAM, as it allows the use of large time steps, and overcomes the Courant-Friedrichs-Lewy (CFL) restriction. This work contribute to the Aquifer Storage and Recovery (ASR) project of Qatar which aims at artificially storing water in the aquifer for future use by developing an efficient and accurate model for mass transport in fractured porous media. References [1] Celia, M.A., Russell, T.F., Herrera, I., Ewing, R.E.: An Eulerian-Lagrangian localized adjoint method for the advection-diffusion equation. Advances in Water Resources. 13, 187–206 (1990). doi:10.1016/0309-1708(90)90041-2 [2] Karimi-Fard, M., Durlofsky, L.J., Aziz, K.: An Efficient Discrete-Fracture Model Applicable for General-Purpose Reservoir Simulators. SPE Journal. 9, 227–236 (2004). doi:10.2118/88812-PA [3] Younes, A., Ackerer, P., Delay, F.: Mixed finite elements for solving 2-D diffusion-type equations. Reviews of Geophysics. 48, (2010). doi:10.1029/2008RG000277

The geographical and hydrological characteristics and industrial activities of the Arabian/Persian Gulf contribute to its classification as a stressed marine environment. The persistency of some contaminants released by human activity is putting additional pressure on this already fragile system. Several studies have assessed the chemical contamination levels in Qatari coastal sediments but this is one of a few studies that assessed their eco-genotoxicological impacts, by using cytogenetic endpoints in a local model bivalve species. Bivalves were specifically selected for this study due to their role as filter feeders, high tolerance for harsh environmental conditions, and availability around Qatar. In this project, determination of Polycyclic Aromatic Hydrocarbons (PAHs), Total Petroleum Hydrocarbons (TPHs) and trace metals in surface sediments and pearl oyster -Pinctada radiata- was conducted in samples collected from 3 coastal locations in Qatar: Umm Bab, Dukhan and Al-Wakra. The selected sites were expected to be dissimilar in regard to the chemical pollutant level and contaminants distribution due to the different anthropogenic activities. Initial aneuploidy levels –numerical abnormality in chromosomes- in oysters were examined between December 2015 to February 2016 through randomly selecting 140 well spread metaphases. Metaphases with 26 chromosomes were recorded as diploid or normal and the ones with less or more number of chromosomes considered aneuploidy (Ebied, 1999). The ability of the oysters to adapt in terms of chemical contaminants accumulation and aneuploidy level when moved between sites with different levels of chemical pollution was assessed in the second sampling in April 2016, and using experimental approach with three treatments (control, transplanted, and translocated). The control treatments were collected from the original site and kept there, the transplanted treatments consisted of individuals composed from the other two sites and moved to Al-Wakra and the opposite, while the translocated treatment were the ones moved from Dukhan to Umm Bab and versa vise. Statistical analysis showed significant difference between sediment in the three sites; TPHs concentrated in Umm Bab, higher concentrations of metals found in Dukhan, while PAHs concentrated the most in AL-Wakra. Hydrocarbons and metals were detected in higher doses in oyster tissues collected in first sampling comparing to those analyzed in the second sampling with consistency of accumulating same contaminants. Predation by gastropod whelks caused high mortality of oyster during the second stage of the study especially in Dukhan control while transplanted animals from Al-Wakra were the least selected by gastropods. Mortality rates in Dukhan were generally higher than in other sites, except for oysters transplanted from Al-Wakra to Dukhan. Positive correlation was found between the high levels of contaminants and aneuploidy during the first phase. Unexpectedly, to the usually observed in bivalves, there was a bigger percentage of abnormal cells with chromosomal gain (hyperdiploids) than with chromosomal loss (hypodiploids) in all treatments. Among all the treatments, transplanted oysters showed the lowest level of aneuploidy followed by translocated, then control. In other words: oysters moved from site to another, regardless of the contamination levels at origin and destination, showed some recovery from initial aneuploidy levels. Further research is needed to determine the underlying mechanisms for this pattern.