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Coal firing power stations represent the second largest source of global NOx emissions. The current practice of predicting likely exit NOx levels from multi-burner furnaces on the basis of single burner test rig data has been proven inadequate. Therefore, to further improve current NOx reduction technologies and assist in the assessment of NOx levels in new and retrofit plant cases, an improved understanding of the impact of burner interactions is required. The aim of this research is two-fold: firstly, to experimentally investigate isothermal flow interactions in multi-burner arrays for different swirl directions and burner pitches in order to gain a better understanding of burner interaction effects within multi-burner furnaces. Secondly, to carry out numerical modelling in order to determine turbulence models which give the best agreement to experimental data. Experimental investigations were carried out using flow visualisation for qualitative and 3D laser Doppler anemometry for quantitative measurements. Numerical modelling was performed using the computational fluid dynamics software, Fluent, to compare performance between k-ε, k- ω and RSM turbulence models. Experimental investigation showed that the recirculation zone of the chequerboard configuration is more sensitive to the change in pitch than that of the columnar configuration. Further, it was found that the smaller pitch is more sensitive to change in configuration than the wider pitch. The analysis of fluctuating components, u’, v’ and w’ showed that the burner flow is highly anisotropic at burner exit. Numerical investigation showed that the k-ω turbulence model consistently performed below the other two models. The statistical comparison between k-ε and RSM turbulence models revealed that, for prediction of the swirl velocity profiles, the RSM model overall performed better than the k-ε turbulence model. The visual and statistical analyses of turbulent kinetic energy profiles also showed that the RSM turbulence model provides a closer match to the experimental data than the k-ε turbulence model.

Currently, four areas of Texas have been designated by the United States Environmental Protection Agency (EPA) as non-attainment areas because they exceeded the national one-hour ground-level ozone standard of 0.12 parts-per-million (ppm). Ozone is formed in the atmosphere by the reaction of Volatile Organic Compounds (VOCs) and Nitrogen Oxides (NOx) in the presence of heat and sunlight. In May 2002, The Texas State Legislature passed Senate Bill 5, the Texas Emissions Reduction Plan (TERP), to reduce the emissions of NOx by several sources. As part of the 2001 building energy performance standards program which is one of the programs in the TERP, the Texas Legislature established the 2000 International Energy Conservation Code (IECC) as the state energy code. Since September 1, 2001, the 2000 IECC has been required for newly constructed single and multifamily houses in Texas. Therefore, this study develops and applies portions of a methodology to calculate the energy savings and NOx emissions reductions from the adoption of the 2000 IECC to new single family houses in non-attainment and affected counties in Texas. To accomplish the objectives of the research, six major tasks were developed: 1) baseline data collection, 2) development of the 2000 IECC standard building simulation, 3) projection of the number of building permits in 2002, 4) comparison of energy simulations, 5) validation and, 6) NOx emissions reduction calculations. To begin, the 1999 standard residential building characteristics which are the baseline construction data were collected, and the 2000 IECC standard building characteristics were reviewed. Next, the annual and peak-day energy savings were calculated using the DOE-2 building energy simulation program. The building characteristics and the energy savings were then crosschecked using the data from previous studies, a site visit survey, and utility billing analysis. In this thesis, several case study houses are used to demonstrate the validation procedure. Finally, the calculated electricity savings (MWh/yr) were then converted into the NOx emissions reductions (tons/yr) using the EPA's eGRID database. The results of the peak-day electricity savings and NOx emissions reductions using this procedure are approximately twice the average day electricity savings and NOx emissions reductions.

Higher atmospheric concentration of greenhouse gases (GHG) such as carbon dioxide and methane has contributed to an increase in Earth's mean surface air temperature and caused climate changes. This largely reflects the increase in global energy consumption, which is heavily dependent on oil, natural gas, and coal. If not controlled, the combustion of these fossil fuels can also produce high levels of nitrogen oxides (NOx) and soot emissions, which adversely affect the air quality. New and extremely challenging fuel efficiency and exhaust emissions regulations are driving the development and optimisation of powertrain technologies as well as the use of low carbon fuels to cost-effectively meet stringent requirements and minimise the transport sector's GHG emissions. In this framework, the dual-fuel combustion has been shown as an effective means to maximise the utilisation of renewable liquid fuels such as ethanol in conventional diesel engines while reducing the levels of NOx and soot emissions. This research has developed strategies to optimise the use of ethanol as a substitute for diesel fuel and improve the effectiveness of dual-fuel combustion in terms of emissions, efficiency, and engine operational cost. Experimental investigations were performed on a single cylinder heavy-duty diesel engine equipped with a high pressure common rail injection system, cooled external exhaust gas recirculation, and a variable valve actuation system. A port fuel injection system was designed and installed, enabling dual-fuel operation with ethanol energy fractions up to 0.83. At low engine loads, in-cylinder control strategies such as the use of a higher residual gas fraction via an intake valve re-opening increased the combustion efficiency (from 87.7% to 95.9%) and the exhaust gas temperature (from 468 K to 531 K). A trade-off between operational cost and NOx reduction capability was assessed at medium loads, where the dual-fuel engine performance was less likely to be affected by combustion inefficiencies and in-cylinder pressure limitations. At high load conditions, a Miller cycle strategy via late intake valve closing decreased the in-cylinder gas temperature during the compression stroke, delaying the autoignition of the ethanol fuel and reducing the levels of in-cylinder pressure rise rate. This allowed for the use of high ethanol energy fractions of up to 0.79. Finally, the overall benefits and limitations of optimised ethanol-diesel dual-fuel combustion were compared against those of conventional diesel combustion. Higher net indicated efficiency (by up to 4.4%) combined with reductions in NOx (by up to 90%) and GHG (by up to 57%) emissions can help generate a viable business case of dual-fuel combustion as a technology for future high efficiency and clean heavy-duty engines.

The aim of this research is to develop an optimisation tool to support the preliminary design of gas turbine combustors by providing a partial automation of the design process. This tool is to enable better design to be obtained faster, providing a reduction in the development costs and time to market of new engines. The first phase of this work involved the analysis of the combustor design process with the aim of identifying the critical tasks that are suitable for being automated and most importantly identifying the key parameters describing the performance of a combustor. During the second phase of this work an adequate design methodology for this problem was defined. This led to the development of a design optimisation Toolbox based on genetic algorithms, containing the tools required for it's proper integration into the combustor preliminary design environment. For the development of this Toolbox, extensive work was performed on genetic algorithms and derived techniques in order to provide the most efficient and robust optimisation method possible. The optimisation capability of the Toolbox was first validated and metered on analytical problems of known solution, where it demonstrated excellent optimisation performance especially for higher-dimensional problems. In a second step of the testing and validation process the combustor design capability of the Toolbox was demonstrated by applying it to diverse combustor design test cases. There the Toolbox demonstrated its capacity to achieve the required performance targets and to successfully optimise some key combustor parameters such as liner wall cooling flow and NOx emissions. In addition, the Toolbox demonstrated its ability to be applied to different types of engineering problems such as wing profile optimisation.

Electricity generating units (EGUs) are major emitters of both nitrogen oxides (NOx) and CO₂, and cap-and-trade programs are either currently used or proposed as management strategies for both pollutants. Emission cap and trade programs for these two pollutants have generally been considered independently, but since each EGU will have a characteristic NOx to CO₂ emission ratio, these programs are inherently connected. This thesis examines the extent to which CO₂ emission pricing and NOx emission markets are likely to influence each other, using Texas as a case study. The relationship is first demonstrated with a simple scenario of four power plants, followed by a second scenario accounting for the largest 34 plants in Texas. The analysis demonstrates that future CO₂ pricing will cause NOx emissions markets to be inefficient at reducing emissions through changes in the dispatching order. There will also exist a greater potential for NOx price spikes. Two plausible alternatives to this problem are suggested: a temporally- and spatially-variable NOx program, or increased emphasis on retrofitting the existing fleet of power plants for NOx reduction. / text

Knowledge of NOx (NO2 + NO) emissions is useful to understand processes affecting air quality and climate change. Emission inventories of surface NOx have high uncertainties. Satellite remote sensing has enabled measurements of trace gases in the atmosphere over a large regional and temporal scale. Inverse modeling of NO2 observations from satellites can be used to improve existing emissions inventories. This study seeks to understand the difference in two methods of inverse modeling: the mass balance approach and the adjoint approach using the GEOS-Chem chemical transport model and its adjoint. Using both synthetic satellite observations and those derived from the SCIAMACHY satellite instrument, this paper found that the performance of these two inversions was affected by pixel smearing and observational error. Smearing reduced the accuracy of the mass balance approach, while high observational error reduced the accuracy of the adjoint approach. However, both approaches improved the a priori emissions estimate.

A comprehensive model, previously developed and tested for prediction of behavior of continuous fluidized bed combustors is extended to incorporate NOx formation and reduction reactions and applied to the simulation of METU 0.3 MWt Atmospheric Bubbling Fluidized Bed Combustor (ABFBC) burning lignites with high volatile matter in their own ashes. The predictive accuracy of the model was assessed by comparing its predictions with measurements taken previously on the same rig. Favorable comparisons are obtained between the predicted and measured temperatures and concentrations of gaseous species along the combustor. Results show that determination of partitioning of coal nitrogen into char nitrogen and volatile nitrogen, and release of volatile nitrogen along the combustor are found to be the most important parameters that affect NOx formation and reduction in bubbling fluidized bed combustors. The system model proposed in this study proves to be a useful tool in qualitatively and quantitatively simulating the processes taking place in an atmospheric fluidized bed combustor.

The aim of this research is to develop an optimisation tool to support the preliminary design of gas turbine combustors by providing a partial automation of the design process. This tool is to enable better design to be obtained faster, providing a reduction in the development costs and time to market of new engines. The first phase of this work involved the analysis of the combustor design process with the aim of identifying the critical tasks that are suitable for being automated and most importantly identifying the key parameters describing the performance of a combustor. During the second phase of this work an adequate design methodology for this problem was defined. This led to the development of a design optimisation Toolbox based on genetic algorithms, containing the tools required for it's proper integration into the combustor preliminary design environment. For the development of this Toolbox, extensive work was performed on genetic algorithms and derived techniques in order to provide the most efficient and robust optimisation method possible. The optimisation capability of the Toolbox was first validated and metered on analytical problems of known solution, where it demonstrated excellent optimisation performance especially for higher-dimensional problems. In a second step of the testing and validation process the combustor design capability of the Toolbox was demonstrated by applying it to diverse combustor design test cases. There the Toolbox demonstrated its capacity to achieve the required performance targets and to successfully optimise some key combustor parameters such as liner wall cooling flow and NOx emissions. In addition, the Toolbox demonstrated its ability to be applied to different types of engineering problems such as wing profile optimisation.