Qatar Foundation Annual Research Conference Proceedings Volume 2016 Issue 1

Background & Objective: Air pollution is a major problem that has been recognised throughout the world for hundreds of years. In the middle ages, the burning of coal in cities released increasing amounts of smoke and sulphur dioxide to the atmosphere. In the late 18th century, the Industrial Revolution, beginning in the UK, led to escalation in pollutant emissions based around the use of coal by both homes and industry.Pollutant emissions continued to grow through the 19th and early 20th centuries leading to poor Air Quality (AQ). In more recent times, pollution from motor vehicles has become the most recognised AQ issue. Present pollution monitoring is revealing that if we don't act swiftly then vehicle pollution could harm our environment and reduce the quality of life for future generations. The number of cars, both in Qatar and in most countries around the world, is currently steadily increasing, and a speed up in technological development is required to combat the pollution problem. Poor AQ has negative effects on the environment and thus on our wellbeing. Air pollution from transport vehicles includes emissions of carbon monoxide, particulates, nitrogen oxides and dioxide, hydrocarbons and so on. Whilst much attention has been directed towards poor outdoors AQ we sometimes forget that we spend up to 90% of our time indoors. Consequently, keeping the air which we breathe at home clean is crucial, particularly for vulnerable people including babies, children, pregnant women and the unborn babies, the elderly, and those suffering from respiratory or allergic diseases such as asthma. Although in the majority of homes the indoor AQ (IAQ) is fairly good, CO, SO2, NO2 etc… are just some of the indoor air pollutants which can give cause for concern. The level of indoor air pollutants depends on factors such as outdoor air pollutants, construction materials and interior finishing, poorly-designed air conditioning and ventilation systems, and households and furniture (via outgassing from fabrics, paints, pets, etc.). Over-ventilation, as often thought, does not solve the problem. Nevertheless, this illusory solution is not adequate in the hot climate of the Gulf region as it leads to unacceptable levels in power demand. Sustaining economic and social growth is impossible without a holistic environmental vision that places environmental preservation for Qatar's future generations at the forefront. The QNV2030 aim to strike a balance between developmental needs (human, society, economy) and the protection of its natural environment, whether land, sea or air. Echoing international initiatives, Qatar has recently undertaken relentless intensive steps in an attempt to address the problem of AQ. The QNV2030 associated Qatar National Development Strategy 2011-2016 (QNDS 2011-2016), through a set of well-defined recommendations, stresses on the need to address the issues of environment and air pollution. To meet these needs, in this extended abstract we present SERENO (SEnsor and REceiver Node), a renewable energy-harvested sensor node that intelligently monitors air quality continuously without human intervention. This paper discusses the challenges of designing an autonomous system powered by ambient energy harvesting. Preliminary results demonstrate that, the presented platform could effectively report and trace air quality levels in a sort of set and forget scenario using a mesh network topology to cover as large as possible area deploying from tens to thousand nodes. Methods: The advances in low power electronics and in electrochemical sensors have enabled the development of low cost and power efficient air quality monitoring systems (dedicated to specific target gas and analysis) suitable for even stringent environments and disruptive locations, where air quality assessment is required without human intervention. Environmental energy harvesting technologies has been developed to maximize wireless sensor systems' lifetime and minimize energy consumption by adopting ultra-low power electronics (i.e. ultra-low power controller, low-power AO and CMOS switches). The use of virtually no-power consumed sensors (e.g. electrochemical sensors connected to signal conditioning electronics with supply current around 1 uA) coupled with wireless communication, working on the principle duty cycling (i.e. the device remains in low power SLEEP mode for almost 100% of the time) helps in maximizing the power efficiency and lifetime of the system. It makes the system operative only to perform designated tasks i.e. sensor warm-up, sampling, data processing and wireless data transmission or communication. The top view diagram of the renewable energy harvested system for air quality monitoring named SERENO is given below. Figure 1 shows the 6 sensors operative on the PCB. The general description of the proposed system is described below.

Fresh fruit and vegetables are an important part of a healthy diet as they are a significant source of vitamins and minerals. However, fresh fruits and vegetables can also be a source of toxic substances such as pesticides. Pesticides are a several and diverse group of chemical compounds, which applied to crops at various stages of cultivation and during production and post-harvest treatment of agricultural commodities. Recently, the government of Qatar has attempted to encourage agricultural production. Despite a noticeable increase in agricultural production in Qatar, however, this increase does not fulfill the need of residents in Qatar. Therefore, Qatar imports large amounts of food products from other countries which are large agricultural producers. The lack of information regarding pesticide residues in food in Qatar implies the necessity to determinate their concentrations in food items. Organochlorine pesticides (also known as chlorinated hydrocarbons) are primarily insecticides with relatively low mammalian toxicity, fat soluble and normally persistent in the environment. Many chlorinated hydrocarbons have the ability to accumulate inside the body due to their lipophilic nature. The study was aimed to examine the occurrence of organochlorine pesticides residues in some local and imported vegetables and fruits in Qatar, as a prelude to assess the risks related to their consumption. In order to achieve this aim, the following specific objectives were carried out: (i) determine the amount of 10 organochlorine pesticides (Heptachlor, aldrin, dieldrin, Endrin, a-chlordane, g-chlordane, endosulfane I, methoxychlor, α-BHC and β-BHC) in seven mostly consumed vegetables and fruits in Qatar using Gas chromatography-electron capture detector (GC-ECD), (ii) screen the residues of pesticides in these vegetables and fruits using scan mode of Gas chromatography- mass spectrometry (GC-MS), and (iii) perform statistical analyses to data obtained. A total of 127 samples of most 7 consumed fresh vegetables and fruit from local and import production were analyzed. The samples included: 26 samples of fruits and 101 samples of vegetables. Samples were extracted within 24 hours and stored at 4°C until the analysis. The simple random sampling and stratified random sampling were used as sampling procedures for collecting the vegetables and fruits. For all vegetables and fruits except strawberries, simple random sampling was used. For strawberries sampling, the stratified random sampling procedure was used. The EPA Method 8081 was chosen as a reference method for the preparation and extraction method with some modification. Additionally, the Dionex Application Note 332 “Accelerated solvent extraction of pesticide residues in food products”, 2012, was used as extraction method for vegetables and fruits. The fresh fruits and vegetables samples were collected from farms and market a day before extraction. Each sample was divided in to two groups: washed sample with water and unwashed sample. No sample digestion was needed prior to extraction. A clean-up procedure is usually carried out to remove co-extracted compounds that may cause interference in the chromatographic determination or be detrimental to the analytical instrumentation. Following extraction, 5 g of anhydrous sodium sulfate were added to the collection vial to adsorb co-extracted water. The vial was shaken for 15 s and the water-free extract was decanted into a clean vial. Two solid phase extraction techniques were used (Florisil and Silica Gel). The EPA method 3620C- Florisil Cleanup and Method 3630C- Silica Gel Cleanup were used as reference methods for cleaning the samples. All samples were cleaned up using 2 g Florisil Clean-Prep Cartridge. However, some interferants that are not removed by Florisil Cartridge would be removed by a second cleanup technique which was Silica Gel cleanup. For the Quality Control and Quality Assurance measures (QC/QA), the Limit of detection and limit of quantitation were calculated for all analytes. The LOD and LOQ were calculated using 10 samples of the lowest concentration of spike (10 ppb). The evaluation of the recoveries of studied pesticides were done by adding known concentration of an internal standard (Decachlorobiphenyl) to about 10% of total number of samples. The range from 93.6% to 106.6% was the percent recoveries in spiked samples. Residues of 10 OCPs (Heptachlor, aldrin, dieldrin, Endrin, a-chlordane, g-chlordane, endosulfane I, methoxychlor, α-BHC and β-BHC) were identified using GC/ECD. The GC/ECD analyses were performed on an Agilent 6890 N equipped with a splitless injector and a 7683 autoinjector. The analysis by GC/MS was carried out on an Agilent 7890A MSD 5973 equipped with a split/splitless Inlet and a 7683B autoinjector. Separations were conducted using an HP-1 30 m 0.25 mm 0.25 μm column for GC/ECD and Rxi-5SILMS 30 m 0.25 mm 0.25 μm column for the GC/MS. The GC/MS data were acquired and processed with a wiley7n.1 and NIST98 Libraries. The most frequently detected OCPs in the samples were heptachlor, g-chlordane and a-chlordane. Two statistical analysis tests were used to determine significance (pair-difference t-test and analysis of variance (ANOVA)). In most of the comparisons between the washed and unwashed samples, no-significant differences were observed (P > 0.05). Here, there is a dire require for controlling program for residues of pesticides in food products. Since florisil and silica were used for cleanup, heavy matrix interferences were observed in most of the samples, consisting primarily of fatty acids. Thus the detection and identification of trace levels of pesticides in this complex profile can be very time-consuming and laborious. The level of pesticide residues contamination may be considered a potential public health problem, since pesticides are characterized by various degrees of toxicity to non-target species, including human beings. The results underscore the need for regular monitoring of large samples to determine the pesticide residues, especially for the imported samples. This research can be implemented as a regular monitoring for the presence of OCPs in fruits and vegetables. Also the results of this research can be used as reference for future work. Future studies should consider the processing factors other than washing with tap water in order to account for the reduction or removal of pesticides such as: washing (with acetic acid, sodium chloride and soap) and peeling. Also as a recommendation, we need to look to other types of food that are sold in Qatar and may contain pesticides residues, such as grains and dates. Future studies also should look to the presence of other type of pesticides such as organophosphorous and carbamates compounds.

Fadwa El Mellouhi1, Akinlolu Akande2, Sergey Rashkeev1, Mohamed El-Amine Madjet1, Golib Berdiyorov2, Carlo Motta2, Stefano Sanvito2 and Sabre Kais1, Fahhad Alharbi1

1Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar

2School of Physics and CRANN, Trinity College Dublin, Ireland

In the past four years, the solar cell field has experienced an unprecedented meteoritic emergence of a new family of solar cell technologies; namely, perovskites solar cells (PSC) using (CH3NH3)PbI3 as absorber. [1] However, two main challenges prevent deploying PSC technology: the presence of the toxic element lead (Pb) and their structural instability.

The CRANN-QEERI initiative for Solar Energy Harvesting Materials (CRAQSolar project) aims at establishing a new research protocol for the rational and rapid design of advanced materials for solar energy harvesting. This will drastically accelerate the time necessary for materials discovery and will allow us to produce a new generation of photovoltaic compounds displaying high efficiency, ease of manufacturability, longevity and low costs. Our research protocol is based on the rational design of new compounds by means of state-of-the-art high-throughput electronic structure theory, followed by synthesis, processing and characterization. In particular we will target both chemical synthesis and liquid phase processing, two protocols, which guarantee handling of materials at low temperature and low costs. The grand objective of CRAQSolar is that of revolutionizing such cycle and to provide a way for producing a significant pallet of new promising compounds for further optimization. In particular the project has two targets:

Objective 1: Developing new hybrid organic/inorganic perovskites (HOIPs) with robust solar harvesting efficiency but also useful thermal and mechanical stability. These should be synthesized/processed chemically and have mobility superior to their all-organic counterparts.

Objective 2: Developing a range of compounds made of 2D materials (such as MoS2, TiS2, GaS, etc.) with strong light absorption properties and long-living excitons. These will be processed from the liquid phase so that solar cells devices may be produced by ink-jet printing.

We conducted extensive density functional theory (DFT) calculations on the prototypical light absorbing perovskite, CH3NH3PbI3, in its cubic phase, by taking into consideration the experimentally reported evidence of the fast rotation of CH3NH3 at room temperature. This compound has the standard AMX3 perovskite structure, where the cation position, A, is taken by methyl-ammonium, CH3NH3.

Ground-state total energies and forces were computed using DFT calculations with the FHI-aims all-electron quantum chemistry code [2]. These were used to optimize the crystal geometry, without the use of constraints. The GGA in the Perdew-Burke-Ernzerhof (PBE) parameterization was employed. Long-range van der Waals interactions have been taken into account via the Tkatchenko and Scheffler (TS) scheme [3]. The reciprocal space integration was performed over an 8 × 8 × 8 Monkhorst-Pack grid after performing convergence tests on the energy and forces.

Our pioneering work for this class of material consisted of lifting the limitation imposed in previous studies on the orientation of the organic molecule. This means that we did not limit our analysis to CH3NH3 oriented along the (100) or the (111) direction, for which the high Oh symmetry is maintained, but we also explore cases where the symmetry was lowered. Our main conclusion was that such symmetry lowering has profound consequences on the electronic structure namely that the bandgap changes from direct to indirect depending on the orientation of the CH3NH3 group.[4] Crucially such symmetry-lowering configurations represent local minima in the free energy surface of the crystal and they are stabilized by van der Waals (vdW) interactions. These are the key ingredients not only for obtaining accurate lattice parameters but also for the internal geometry. Our calculations then return a picture of the CH3NH3PbI3 as a “dynamical” bandgap semiconductor, in which the exact position of the conduction band minimum depends on the particular spatial arrangement of the molecules. Importantly our results are robust against bandgap corrections and spin-orbit interaction, and deliver an absorption spectrum in good agreement with experimental data near absorption edge.

These preliminary studies suggest that better efficiency might be achieved by seeking novel molecules maybe combined with different halides in order to enhance the symmetry breaking in these compounds. Our finding thus offers a design strategy to increase the efficiency of hybrid halide perovskites. This also lays a foundation in screening and designing alternative nontoxic lead-free materials.

The two classes of compounds selected for CRAQSolar's exploration encompass some among the most promising materials for developing a solar energy harvesting technology. In particular, since both can be grown and processed chemically from the liquid phase, they offer the possibility of achieving high energy-conversion efficiency, while maintaining low fabrication costs. Furthermore, these are families of compounds comprising a vast number of members with highly tunable properties, so that they are the ideal platform for a large-scale search.

Our efforts to design lead free family of hybrid materials demonstrate that the design of hybrid materials containing organic cations might require careful considerations among them the size of the cell used during the screening process. Our strategy will be presented as well as some resulting promising compounds.

Acknowledgement

Computational resources are provided by research computing at Texas A&M University at Qatar and the Swiss Super Computing Center(CSCS). This work is supported by the Qatar National Research Fund (QNRF) through the National Priorities Research Program (NPRP 8-090-2-047)

References

[1] M. Peplow, “The perovskite revolution [news],” Spectrum, IEEE, vol. 51, no. 7, pp. 16–17, 2014.

[2] V. Blum, R. Gehrke, F. Hanke, P. Havu, V. Havu, X. Ren, K. Reuter and M. Scheffler, Ab initio molecular simulations with numeric atom-centered orbitals, Comp. Phys. Comm. 180, 2175 (2009).

[3] A. Tkatchenko and M. Scheffler, Accurate molecular van der Waals interactions from ground-state electron density and free-atom reference data, Phys. Rev. Lett. 102, 073005 (2009).

[4] C. Motta, F. El Mellouhi, S. Kais, N. Tabet, F. Alharbi, and S. Sanvito, Revealing the role of organic cations in hybrid halide perovskites CH3NH3PbI3, Nature Communications 6, Article number:7026 (2015) (doi:10.1038/ncomms8026)

Karst is ubiquitous on the peninsula of Qatar, including depressions, sinkholes, and caves. Faulting and fractures play a major role in the development of karst, where fluids find pathways through limestone and dissolve the host rock. The resulting fissures may grow larger as more surface water is funneled through to form cavities or karst. Sinkholes may also form, when cavern roofs collapse, and it is this last characteristic that is of concern to rapidly growing metropolitan areas, that expand in heretofore unexplored regions. Qatar has seen a recent boom in construction, including the planning and development of complete new sub-sections of metropolitan areas. Before planning and construction can commence, the development areas need to be investigated to determine their suitability for the planned project. Of particular concern are ubiquitous karst features that are prone to collapse, particularly when surface loading is increased due to the construction of new buildings. In this paper, we present the results of a study to demonstrate a variety of seismic techniques to detect the presence of a karst analog in form of a vertical water-collection shaft located on the campus of Qatar University, Doha, Qatar. Seismic waves are well suited for karst detection and characterization. Voids represent high-contrast seismic objects that exhibit strong responses due to incident seismic waves. However, the complex geometry of karst, including shape and size, makes their imaging nontrivial. While karst detection can be reduced to the simple problem of detecting an anomaly, karst characterization can be complicated by the 3D nature of the problem of unknown scale, where irregular surfaces can generate diffracted waves of different kind. In our current paper we build upon previous results (Gritto et al, 2015) and employ a variety of seismic techniques to demonstrate the detection and characterization of a vertical water collection shaft analyzing the phase, amplitude and spectral information of seismic waves that have been scattered by the object. The experiment consisted of seismic transmission and reflection surveys, using a 10 kg sledge hammer as a source and three-component 10 Hz geophones to record the data. We used the reduction in seismic wave amplitudes and the delay in phase arrival times in the geometrical shadow of the vertical shaft to independently detect and locate the object in space. Additionally, we use narrow band-pass filtered data combining two orthogonal transmission surveys to detect and locate the object. Our analysis showed that ambient noise recordings may generate data with sufficient signal-to-noise ratio to successfully detect and locate subsurface voids. This is a result of the low intrinsic attenuation of seismic waves by the limestone and dolomite rocks that are ubiquitous throughout Qatar. Being able to use ambient noise recordings would eliminate the need to employ active seismic sources that are time consuming and more expensive to operate.

Bimetallic catalyst shows distinct physical and chemical properties differ from its monometallic catalyst due to the high synergy between the monometals. Bimetals of transition metals shows different applications in the field of catalysis, batteries and solar energy conversion etc. CuCo bimetallic catalysts are excellent candidate for the applications in the field of heterogeneous catalysis, solid state sensor, energy storage devices, and lithium-ion batteries. With the increase in fuel cell application, need of H2 source also rises. H2 can be extracted from the hydrogen rich precursors of light alcohol such as methanol and ethanol that can be produced from corn stover, starch containing materials and other biomass byproducts. Ethanol is low toxic and easy handling renewable source for H2 production for fuel cell applications and the production of ethanol is environmentally sustainable. Transition metal possess high C-C cleavage bond which is an indispensable property in ethanol conversion. Steam reforming, partial oxidation, dehydrogenation and decomposition are the main routes for the hydrogen generation from ethanol. Out of these, decomposition technique is a low temperature process and suitable for small scale fuel cell applications e.g. charging cell phones, computers etc. We follow decomposition route for H2 production along with other necessary byproducts. Bimetallic CuCo catalyst shows good performance during ethanol decomposition for hydrogen production in the temperature range of 50°C-400°C. Various physical and chemical techniques (such as thermal method, precipitation methods, pyrolysis process, sonochemical method, polyol method, microwave irradiation, sol-gel process, combustion method etc.) have been reported for the synthesis of different morphological structures of bimetallic nanoparticles In this work we are following combustion synthesis method to prepare cobalt catalysts which have been reported to be active for ethanol-hydrogen production. This work focuses primarily on understanding the reaction mechanism leading to various products using in situ DRIFTS studies. Combustion synthesis was opted for synthesis due to various advantages such as low energy requirement, single step, fast and economic synthesis process as it does not require expensive equipment. In Solution Combustion Synthesis (SCS) the precursors were mixed to form a homogenous solution and heated it over the hotplate heater to initiate the combustion process which resulted in the synthesis of nanoparticles with uniform properties. Typically, it consist a redox reaction of the homogeneous mixture of metal nitrate (oxidizing agent) and oxygen containing fuels (reducing agent) such as glycine, urea, glucose, citric acid etc. The reaction between NH3 and HNO3 released during decomposition of glycine and metal nitrate respectively produces the energy required for single step combustion synthesis. At higher value of φ, the reactive medium generates H2 rich reducing environment to convert metal oxide to metallic form Bimetallic CuCo were synthesized from the aqueous solution of cobalt nitrate (Co(NO3)2·6H2O), copper nitrate (Cu(NO3)2·6H2O) and glycine (C2H5NO2) in solution combustion synthesis (SCS) method using a fuel to oxidizer ratio of φ 0.5, 1, 1.75 and 2.5. The amount of precursors was calculated based on the synthesis of 1.5 g product in the output. These precursors were mixed in 75 ml of water and stir continuously for 1 hr to form a homogenous mixture. The solution was heated over a hot plate heater until all the water got evaporated. Once it reaches the ignition temperature, the combustion reaction started locally at one point and then spread inside the beaker. The resulted powder was grinded using a mortar and pestle to get a uniform powder to be used for catalytic investigations. Synthesized particles were characterized using XRD, SEM and TEM. Ethanol decomposition over bimetallic CuCo were conducted using in situ diffuse reflectance infrared fourier transform spectroscopy (DRIFT) study under N2 flow at different temperatures (50, 100, 200, 300, 400°C). Temperature-time profile of CuCo shows an increase in combustion temperature with increase in fuel ratio with maximum temperature at φ =  1 (stoichiometric ratio) and after that it decreases. The XRD shows the presence of copper-cobalt component in their oxidized states. Theoretical studies shows increase in particle size with maximum flame temperature. Crystalline size calculation using Scherrer formula shows the same trend in particle size calculation as in Table 1. SEM of as-synthesized nanoparticles of cobalt oxide at different molar ratios from 0.5 to 2.5 in SCS mode shows the nanoparticles of high porosity that are randomly distributes as well as agglomerated. Mostly this high porosity is due to the escaping of excess gases during combustion process. Also the EDS results are in consistent with the XRD results showing higher amount of oxide in the synthesized CuCo compound. TEM image in Fig. 1 also shows agglomeration that is common in solution combustion mode with non-uniform sized particles. Copper-cobalt oxide synthesized using combustion technique has been reduced to pure nanocrystal by passing hydrogen in the reaction chamber at 300°C. An FTIR spectrum at 50 and 100°C shows the presence of adsorbed ethanol and ethoxy species over the reduced catalyst. IR band at 3669 cm^− 1 indicates the presence of OH from adsorbed ethanol on the catalyst surface. At higher temperature the molecularly adsorbed ethoxy species is converted into acetate species along with the presence of carbonate species. After increasing the temperature from 200°C the intensity CO2 band at 2335-2367 cm^− 1 is evident. At this temperature the acetate species are dehydrogenated to acetaldehyde and other intermediate species. Strong acetate band of 1760 cm^− 1 above 200°C could be due to the transformation of acetaldehyde formed by the dehydrogenation of ethanol to either ethyl acetate or acetic acid though the nucleophilic reaction of ethoxy or hydroxyl species with the surface aldehyde. The presence of IR band between 2830-2695 cm^− 1 shows the presence of aldehyde group in the decomposition reaction. At higher temperature, the presence of carbonate species is evident with the carbonate layer formation from SEM and TEM images. This carbon layer at higher temperature hinders the action of catalyst in ethanol decomposition reaction.

Acknowledgement

This publication was made possible by JSREP grant (JSREP-05-004-2-002) from the Qatar national research fund (a member of Qatar foundation). The statements made herein are solely the responsibility of the author(s). The authors also wish to acknowledge the technical services granted by Central Laboratory Unit (CLU) and Gas Processing Centre (GPC) at Qatar University along with QU internal grant (QUUG-CENG-CHE-14/15-9) to support this research

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total U.S. GHG emissions in 2013. This is why the adoption of hybrid and all-electric vehicles (EVs) instead of conventional gasoline powered vehicles with renewable source of power has been identified as the most effective GHG emissions mitigation strategy. This strategy not only saves considerable amounts of transportation-related CO2, but also reduces the demand for electricity in buildings, which is mainly supplied by coal-fired generation. Since solar energy is the only source of renewable energy that can be applied at a small scale (e.g. directly to the roof decking or solar window), this paper focuses only on the mitigation strategies in which EVs are powered by solar energy. One reason mitigation strategies are having difficulty delivering the desired outcome sought by policy makers is that many factors that affect the success or scale of GHG emissions reductions are uncertain and complex. Vehicle's specification (e.g. battery capacity, weight, and optimal energy use), road type and driving behavior (e.g. average speed), and environmental conditions (e.g. temperature and sunlight) are among the many factors affecting either energy consumption or generation and characterized by a significant degree of uncertainty. Thus, urban community planners and policy makers are confounded with huge amounts of unknown parameters, in which they wish to find the best solution from all feasible solutions (e.g. the largest GHG emissions reduction that a mitigation strategy can achieve) in the presence of uncertainty. The objective of this paper is to develop a stochastic mathematical model for energy consumption and mitigation strategy analysis that maximizes GHG emissions reductions based on the current demand trend and market prices. In this model, we consider EV and solar system costs, as well as the human activities (e.g. time spent in the building, time spent driving, and distance traveled) and environmental impacts (e.g. temperature, humidity, and sunlight) under uncertain conditions. What makes this study different from previous energy management or GHG emissions mitigation research is its focus on small-scale energy system and its validation process. Although mitigation actions through large-scale changes in energy system (e.g. new renewable energy power plant) will undoubtedly result in the largest GHG emissions reductions, but they also require major changes in the generation part of the energy sector and definitely need more investment. One the other hand, small-scale GHG emissions mitigation actions (e.g. EVs powered by solar energy) can be accomplished by local communities and characterized by a short decision making cycle, need much less investment, and also eliminate electricity losses in transmission and distribution systems. These all make small-scale GHG emissions mitigation strategies more practical and feasible. Another principal problem with prior energy management or GHG emissions mitigation research is that optimization models have not been validated with real data. In contrast, the proposed optimization approach is validated by comparing the estimated values of the optimal decision and actual values as realizations of the uncertain elements become known. Problem Statement The use of hybrid or EVs alone does not necessarily reduce the transportation's GHG emissions and it depends on the energy source. A conventional gasoline powered vehicle with 30 miles per gallon (mpg) fuel efficiency emits about 0.65 pounds CO2 per mile driven. In contrast, an EV with an average energy use of 3 mile per kWh emits about 0.71 pounds CO2 per mile driven when coal-fired electricity is used, and it emits 0.40 pounds CO2 per mile driven when natural gas-fired electricity is used. In order to optimize the mitigation strategies in which EVs are powered by solar energy (EV + solar power strategy), both energy supply (electricity generation) and demand (electricity consumption) sides must be considered. Research Methodology There are three primary solar systems: off-grid, grid-tied, and hybrid. Off-grid solar systems feed the extra energy the solar panels produce into batteries, while grid-tied solar systems send excess power to the electrical grid. Both off-grid and grid-tied systems yield the same amount of CO2 emissions reduction when the solar panels produce enough power for charging EV's batteries. When the solar panels are not producing the power required for charging an EV (e.g. during cloudy weather or night), however, grid-tied systems use electricity from the grid but off-grid systems use electricity stored in batteries. Depending on the electrical grid energy source in this case, a mitigation strategy using grid-tied systems may add a significant amount of CO2 to the atmosphere. Hybrid solar systems offer the flexibility of using a battery backup and being connected to the grid. Therefore, the outcome of a mitigation strategy using hybrid systems depends largely on the power generation capacity of the solar system. The area of solar panels, the solar cell efficiency and temperature coefficient, irradiance of input light, and temperature are the main factors affecting the capacity of a solar system. In the present problem, the decisions variables are the type of EV, which determines the optimal EV's energy use, the capacity of the solar system in the case of grid-tied system as well as the solar system storage capacity in the case of off-grid and hybrid system. Under a pre-specified budget constraint, the objective is to find these decision variables in such way to maximize GHG emissions reductions. The present model starts the optimization process by identifying the energy source of electricity generation. The electrical grid energy source is determined by the electricity demand at time t, Load t, and the electric power plants generating capacity, PPCj. The time index t takes integer values between 1 and N, where N is the time horizon of the analysis and the units of time measurement are hours. For instance, Load30 indicates the electricity demand on day 2, 6 AM. Smaller time horizons for the analysis and the prediction require less computation efforts but they are less accurate. To obtain a perfect reference for the best possible GHG emissions mitigation strategy, we solve a stochastic optimization problem with a prediction horizon of 1 hour over a year, thus N is 1 ×  365 × 24 = 8760 hours. The power plant index j indicates the respective set of the renewable (j = 1), nuclear- (j = 2), natural-gas (j = 3), coal- (j = 4), and oil-fired (j = 5) power plant. Load t is a probabilistic variable because it is unknown at the time the decision should be made; however, PPCj is a deterministic variable and is known for the analysis region. It is assumed that the supply level is sufficient to meet peak demand. The CO2 emissions at time t are then calculated for each type of solar system. For a grid-tied system, the CO2 emissions (measured in lb or kg) are calculated which may be positive or negative. A Negative value indicates a reduction in the CO2 emissions. When an EV is charging at time t, the energy generated by solar panel will be used in transportation sector. However, when an EV is not charging, all the energy will be used in the building. For an off-grid system, the factor that can seriously affect the CO2 emissions is the solar battery's state of charge. This factor is a function of the solar system storage capacity, and the charging duration, which starts at the last prediction horizon, and ends at time t. Once the solar batteries are fully charged, the extra energy the solar panels produce will be used only in the building. Since off-grid solar systems are not connected to the electrical grid, the energy produced by the system can meet at most the building's demand (DB) and the rest is wasted. This happens when the solar batteries are fully charged and the system is producing more energy than building's load. In the off-grid system, the EV is charged using the electricity stored in batteries. When the energy required to fully charging the EV exceeds the electricity stored in batteries, the EV will be charging using both the batteries and the electrical grid. In contrast to an off-grid solar system, no extra power is wasted in hybrid systems because they can send excess power to the electrical grid. In order to reduce more GHG emissions, the energy generated by solar panel must preferably be used to charge EV's vehicle batteries. For a grid-tied system, this happens when the EV is charging right when the solar system is producing energy. Off-grid and hybrid solar systems offer the flexibility of using a battery backup to charge the EV even when the solar system is not producing enough energy, for example during cloudy weather or night. Thus, it is assumed that the power from the solar system is first used to charge the batteries and then excess power is used in the building or fed into the electrical grid. In order to estimate the electricity generated by solar system, the distributions of stochastic variables such as solar irradiance and temperature are obtained from the weather records over the last 20 years from 1994 to 2014. Also, a database of 46 solar panels from 15 manufacturers is used to obtain solar cell efficiency and temperature coefficient. The average efficiency of 15.86% and temperature coefficient of -0.44 %/°C are used in the analysis. In order to estimate the electricity demand at a given time, the distributions of hourly load are obtained from the operable electric generating plants with a combined rated capacity of 1 MW or more over the last 18 years from 1996 to 2014. The Energy Information Administration (EIA) was the primary sources of hourly load data. Results and Conclusions Results show that among three primary solar systems (i.e. off-grid, grid-tied, and hybrid), a hybrid system consists of 7 modules of solar panels with 6 kWh storage capacity was found to be the best solution. Hybrid solar systems overcome the disadvantage of off-grid solar systems by sending the excess power to the electrical grid and reduce more CO2 emissions than grid-tied solar systems by using the electricity stored in batteries in transportation sector instead of buildings. The presented model is also capable of estimating CO2 emissions reductions from mitigation strategies in which EVs are powered by solar energy. With this capability, urban community planners and policy makers will know how long it will take for their strategy to meet GHG emissions reduction targets. The stochastic optimization problem was solved with a prediction horizon of an hour over a month. Then, CO2 emissions reductions estimated by the presented stochastic model were compared with actual data collected on an hourly basis for the analysis period of one month (720 hours). The results showed an accuracy of about 4% when the EV is powered by a grid-tied or hybrid solar system. When applied to an EV + off-grid solar power strategy, the stochastic model estimated CO2 emissions reductions 11% lower than the actual reductions. Overall, the presented stochastic model had better performance than deterministic methods for different types of solar systems.

In the present architecture of the electric power grids, energy is generated in large-scale that is remotely located from consumers and transmitted using passive high-voltage transmission networks to substations. The electric power is then delivered to consumers via medium and low-voltage distribution systems. Line frequency transformers (LFTs) enable high-efficiency and long-distance power transmission by stepping up the voltage on the transmission side. On the distribution side, the voltage is stepped down for industrial, commercial, and residential consumers. Furthermore, the traditional electric power system is characterized by hierarchical control structures with minimal feedback, limited energy storage, and passive loads. In recent years, the electric power system has been facing increasing stress due to fundamental changes in demand growth, technology change, and consumer preference. There has been a paradigm shift from centralized generation and control to distributed generation, storage and local control; in particular, there has been a global growth of investments in Renewable Energy Sources (RES) such as wind and solar. These RES generate fluctuating electric power and therefore they require Energy Storage Systems (ESS) to enable a time-shift between energy production and consumption. The high penetration of RES and other Distributed Generation (DG) types such as fuel cells (FCs) and Micro-Turbines (MTs) impose significant challenges on the operation of power system and coordination of supply and demand in real time. At the same time, the power system will need to react to events for which it was not designed for. Microgrids (MGs), being controllable small scale power networks, have become popular in distributed systems by facilitating an effective and smooth integration of distributed energy resources, loads, and energy storage devices into existing power systems. They help reduce expenditure by reducing network congestion, line losses and line costs and thereby higher energy efficiency. Power electronics converters are used in microgrids to control the routing of electricity and also provide flexible distributed generation sources interfaces to the distribution network to ensure stable and secure operation of the grid. These power converters rely on the type of microgrid (AC or DC), as well as on other features of the devices (voltage levels, power flow direction, etc.). In addition, they usually include a transformer in order to obtain galvanic isolation. The solid state transformer (SST), which is also called Electronic Power Transformer (EPT), Active Power Electronics Transformer (APET) and Intelligent TRansformer (ITR), has been proposed to replace the traditional line frequency distribution transformers. The basic operation of the SST is first to change the 50Hz AC voltage to high frequency (normally in the range of several to tens of kilohertz), then this high frequency voltage is stepped up/down by a high frequency transformer with significantly decreased volume and weight, and finally shaped back into the desired 50Hz voltage to feed the load. The SST is a power electronics circuit that provides a flexible method for interfacing microgrids with the existing Medium-Voltage (MV) power distribution system. It achieves voltage transformation via a high-frequency isolated transformer, therefore the mass and volume of the system can be reduced. Current and voltage are independently controlled via power semiconductor devices which enables grid support functions not present in the traditional LFT, including voltage and power factor regulation, fault isolation and limitation, filtering harmonic, reactive power compensation, power flow control and voltage and load disturbance rejection. However, at the present time, the commercial success of SSTs has been limited. Efforts have been made to design and implement SSTs with satisfactory performance, as well as explore its use at the distribution system level. The SST can functionally replace the traditional LFT and some power electronics converters, thus indicating a potentially more integrated and compact system. Although the concept of the SST can be seen straight forward, its implementation is a challenge. The SST combines the high voltage, high power, and high frequency operation, which make its design and operation a real challenge. To implement the SST, different power devices can be combined with different circuit topologies in different configurations. In addition, different core materials and transformer structures may be considered to build the high frequency transformer with different phase connections. Furthermore, due to power rating limitation of the semiconductor devices and magnetic components, SST topologies may have several SST cells connected in series or in parallel. Numerous degrees of freedom for the SST modularization are available, which lead to a vast amount of possible arrangements depending on the different levels of modularization in the three modularization axes: degree of power conversion partitioning; degree of phase modularity and number of levels or series/parallel connected cells. Since the level of modularity in each of these different directions is independent, these three axes can be considered to be orthogonal to each other and each element represents a specific design with a certain degree of modularization in each of the axes. The SST can be used as an enabling tool for interfacing microgrids (AC and DC) to medium voltage distribution network. For a SST-based microgrid, the performance of the microgrid mainly depends on the control algorithms of the SSTs. Generally, there are three SST control levels: system level, equipment level, and switch level. For a well-designed SST, the equipment level and firing level control strategies are well defined. However, the system level control strategy can be changed to fit different applications. In order to operate a microgrid properly and reliably, SST- based power control strategies should be developed to accommodate the modes of operation: grid-connected mode and standalone mode. That is why, the development of a controller that manages active and reactive power flow between the DC microgrid, the AC microgrid and the main distribution network is one of the most important research topic for the SST. Furthermore, investigating the effect of grid faults on the stability and performance of the SST is another hot research topic in the same area. Also, the SST can be used in different applications, such as: oil and gas and electric transportation applications. To give an overview of the SST, this work will present a review of the different levels of modularization, all possible control algorithms for the different control levels. Furthermore, stability and reliability analysis for grid connected SST will be reviewed. Finally, all possible application of the SST will be presented.

Qatar peninsula is an arid country with limited water resources. With little rainfall of approximately 80 mm per year and no surface water, aquifers are the only source of natural water in Qatar. The groundwater aquifer receives around 50 million m³ per year as natural recharge, whereas annual groundwater abstraction is more than 220 million m³, mainly used for agriculture. Groundwater occurs in a form of fresh lenses mainly in the northern part of the country, sitting atop of brackish and saline groundwater. Seawater has progressively intruded inland over the last decades because of over-pumping. As a result, the water table has dramatically dropped to unprecedented levels and salinity increased, in addition to other adverse environmental impacts. Because of its karstic nature, Qatar aquifer is prone to different sources of adverse environmental impacts. The concept of aquifer vulnerability is based on the idea that some areas above an aquifer provide more resistant to contamination than others (Vrba and Zaporozec 1994). Mapping groundwater vulnerability using hydrogeological settings gives a clear understanding of natural variation from one point to another within an aquifer. Vulnerability mapping is a powerful tool that can be used for groundwater protection and land management. In this study, vulnerability map was created based on hydrogeological parameters, land use and natural groundwater quality. All maps have been prepared and manipulated within Geographical Information System (GIS). The final vulnerability map was obtained as a sum of different rated maps using Raster Calculator. Two different approaches were used to create vulnerability maps (a) DRASTIC approach, which depends on general hydrogeological settings, and (b) EPIK approach, which focuses on karst hydrogeology. DRASTIC approach uses seven rated maps of: depth to water table, recharge, aquifer media, soil media, topography, vadose zone and hydraulic conductivity to calculate a weighted index map of vulnerability (Aller et al., 1987). EPIK approach is based on (1) epikarst, (2) protection cover, (3) infiltration rate and (4) karstic network. Depth to water table varies from a few meters near the coast to tens of meters further inland and recharge occur mainly in the many land depressions that spread all over the country. These land depressions vary in diameter from a few meters to more than two kilometers. These depressions were formed as a result of land collapse due to cavities underneath. The cavities are the result of dissolution of limestone over thousands of years. In all cases, these depressions have a high weight in vulnerability assessment. Soil may provide some sort of aquifer protection depending on its type and thickness. The dominant soil in Qatar is lithosol, which is composed of rocky soil and provide no protection. Some loamy sand exists in farm lands, which is normally derived by rainfall runoff and provide some protection cover. Aquifer media comprises limestone with dolomite, chalk and clay of variable thicknesses. Three main layers of limestone occur in Qatar. These layers are from top to bottom (1) Dam and Dammam Formation, (2) Rus Formation and (3) Umm Alraduma Formation. Results of aquifer tests show aquifer is highly heterogeneous, which is typical in karst environment with high variation of hydraulic conductivity values. A thick layer of gypsum occurs within the middle layer of limestone (Rus) in the southern part of the country and has a great implication on water quality. This layer is soluble in water, which deteriorates the groundwater quality. All the previously discussed hydrogeological settings have been used to create vulnerability maps in Qatar. While DRASTIC laid more weight on coastal sediments, as they appear to be highly vulnerable in the final map, EPIK approach laid more weights on karst formations in the middle of the country. DRASTIC approach shows high vulnerability areas occur along the coastline and in land depressions Results of both approaches show the high vulnerable areas are those were land depressions occur.

Qatar seeks to generate 2% of its electricity from solar power by 2020 (Bryden et al., 2013, REN 2015), and 20% by either 2024 (PV Insider, 2014) or 2030 (REN, 2015). Since electricity is produced almost entirely from natural gas in Qatar, these renewable energy targets introduce the prospect of natural gas savings that can be made use to increase trade and/or reduce carbon emissions. Electricity production in Qatar has been growing at a very fast pace since the mid-nineties. An estimated 7.3 millions of tons of oil equivalent (Mtoe) of natural gas were used in 2013 to produce 34.7 terawatt-hours (TWh), double the amount in 2007 and over five times as compared to 1997 (Table 1).

Table 1: Electricity production with associate natural gas (NG) use in Qatar 1971–2013. Source for electricity data: http://www.iea.org. Gas usage calculated as the estimated average efficiency for power plants using natural gas in the US for the period 2003–2013 (40.84%) estimated by the U.S. Energy Information Administration (http://www.eia.gov/electricity/annual/html/epa_08_01.html). Year – TWh produced in Qatar – NG used (Mtoe)1971 0.285 0.0601972 0.358 0.0751973 0.380 0.0801974 0.413 0.0871975 0.513 0.1081976 0.717 0.1511977 0.835 0.1761978 1.196 0.2521979 1.877 0.3951980 2.351 0.4951981 2.700 0.5691982 2.998 0.6311983 3.194 0.6731984 3.507 0.7381985 3.918 0.8251986 4.249 0.8951987 4.329 0.9121988 4.592 0.9671989 4.624 0.9741990 4.818 1.0141991 4.643 0.9781992 5.153 1.0851993 5.522 1.1631994 5.815 1.2241995 5.976 1.2581996 6.575 1.3841997 6.869 1.4461998 8.122 1.7101999 8.584 1.8072000 9.134 1.9232001 9.951 2.0952002 10.940 2.3042003 12.012 2.5292004 13.233 2.7862005 14.396 3.0312006 17.080 3.5962007 19.462 4.0982008 21.616 4.5512009 24.158 5.0872010 28.144 5.9262011 30.730 6.4702012 34.787 7.3252013 34.668 7.300

Ten-year forward projections, with cap limits of 200 Mtoe on yearly natural gas production, indicate that electricity production will peak at 48.4 TWh in 2021, with an associated natural gas use of 10.2 Mtoe (Table 2). Cap limits on natural gas production are necessary to prevent early depletion of natural gas reserves in Qatar, which have been estimated at 138 year at current output rates (QNB 2015).

Table 2: Ten-year projections (2014–2024) for electricity production and associated natural gas (NG) use in Qatar (Sanfilippo & Pedersen, in preparation). These projections assume that yearly NG production will not grow beyond 200 Mtoe. Year – Energy production (TWh) – NG needed for energy production (Mtoe) 2013 34.67 7.32014* 32.55 6.92015* 23.30 4.92016* 24.48 5.22017* 23.06 4.92018* 31.96 6.72019* 43.97 9.32020* 48.04 10.12021* 48.41 10.22022* 47.97 10.12023* 45.96 9.72024* 43.61 9.2.

The foreseen use of solar power to generate of electricity could yield a natural gas surplus of 0.2 Mtoe in 2020 and up to 1.8 Mtoe by 2024 or 2030, to reach 3.9 Mtoe thereafter, assuming a PV market peak of 43% in electricity generation – over 3.35% of Qatar total natural gas exports in 2013. This surplus could be repurposed for natural gas trade, and countries in the Far East stand as the most natural trading partners. Exports to Japan, Korea & China accounted for 41% of Qatar's NG world trade in 2013 (http://www.iea.org). Japan and Korea have historically been some of the greatest importers of natural gas from Qatar, and China is quickly emerging as a strong trading partner due to its growing need for energy. China's share in Total Primary Energy Supply (TPES) worldwide has grown from 7% in 1971 to 22% in 2013 (http://www.iea.org). China is now the world largest energy consumer with a 5% lead over the United States, the country that topped the list with 29% share of the world TPES in 1971. China's natural gas imports from Qatar rose from 0.5 to 8.8 Mtoe in only 5 years, from 2009 to 2013. Moreover, China is quickly becoming a major trading partner for Qatar. For the period 2009–2014, the trade between the two nations grew at a Compound Annual Growth Rate (CAGR) of 35.38%, as compared to 28.92% for the period 2003–2008 (http://data.imf.org). Across the same periods, Qatar's trade shows a sharp CAGR decline with both Japan (2009–2014 CAGR: 12.6 vs. 2003–2008 CAGR: 25.37%) and Korea (2009–2014 CAGR: 33.12 vs. 2003–2008 CAGR: 22.1%). Considering these market trends, China appears the most likely candidate partner for additional natural gas trade from Qatar. While the recent turbulence in Asian markets signals a slowdown in China's economy, it is unlikely that China's position as the world largest energy consumer will change in the years to come. Moreover, foreign natural gas is playing an increasingly important role in Chinese energy market (Higashi 2009). Despite plans by the Chinese government to expand domestic production, the internal Chinese natural gas market remains unbalanced (Li et al., 2014). The development and implementation of a new strategic roadmap are needed to manage the local production, marketing and transportation of gas efficiently. These changes may take decades to come to fruition, during which reliance on natural gas imports is bound to grow. In terms of carbon emissions, the amount of CO2 equivalent to the prospected 3.9 Mtoe of natural gas replaced by solar energy (see above) is 9,053,724 US tons, assuming the IEA estimate that each million British thermal units (MBtu) of energy generated by natural gas generate 117 pounds of CO2 emissions (http://www.eia.gov/tools/faqs/faq.cfm?id = 73&t = 11).

References

Bryden, J. Riahi, l., Zissler, R., (2013). MENA: Renewables Status Report. United Arab Emirates Ministry of Foreign Affairs, REN 21. International Renewable Energy Agency (IRENA).

Higashi, N. (2009). Natural gas in China. IEA Energy Markets and Security Working Papers.

Li, Z., Zhang, Q., Farfan Reyes, S., Wang, Z., (2014) Natural Gas Development strategy modeling in China. 4th International Association for Energy Economics Asian Conference, Beijing, China, September 19–21, 2014.

PV Insider, (2014). PV in MENA: Turning Policy into Projects. Retrieved on Nov 1, 2015 from http://www.pv-insider.com/menasol/pdf/policyintoplants.pdf. QNB, (2015).

QNB Economic Commentary, 21 June, 2015. REN21, (2015).

Renewables 2015 Global Status Report. http://www.ren21.net/status-of-renewables/global-status-report/. Sanfilippo, A. & Pederson, L., (in preparation).

Impacts of PV Adoption in Qatar on Natural Gas Exports to the Far East. In Lester, L. & Efird, B. (eds.) Energy Relations and Policy Making in Asia: The benefits of mutual interdependence, Palgrave Macmillan.