The investigation of mechanisms in environmental catalysis using time-resolved methods

The formation of nitrogen oxides (NOx) during a combustion process is difficult to avoid because of the large exotherm and the consequent problem of avoiding local high-temperature spikes. Consequently, for many applications, such as for automotive power generation, there will be a continuing need to use catalytic after-treatment to reduce harmful emissions. The investigation of the mechanisms of the key catalytic reactions in environmental catalysis can provide an insight into the action of the catalyst, and time-resolved methods offer a powerful means to study these processes under realistic conditions. The use of Temporal Analysis of Products (TAP) and Steady State Isotopic Transient Kinetic Analysis (SSITKA) methods to investigate the reduction of NOx under various experimental conditions is described. From a detailed analysis of the SSITKA profiles, it is shown that at low temperatures the mechanism for the formation of N-2 and N2O from NO may differ from the conventional high-temperature mechanism. This is supported by density functional theory calculations, which show that the barrier to the formation of N2O from the reaction of N(ads) and NO(ads) may be too high to allow this process to occur at low temperatures. The alternative reaction of NO(ads) + NO(ads) = N2O(g) + O(ads) is shown to be much more favorable and is consistent with the SSITKA analysis. The remarkable effect of hydrogen as a reductant at low temperatures is described, and alternative interpretations of the role of hydrogen are discussed.

The use of short time-on-stream in situ spectroscopic transient kinetic isotope techniques to investigate the mechanism of hydrocarbon selective catalytic reduction (HC-SCR) of NOx at low temperatures

The problem of differentiating between active and spectator species that have similar infrared spectra has been addressed by developing short time-on-stream in situ spectroscopic transient isotope experimental techniques (STOS-SSITKA). The techniques have been used to investigate the reaction mechanism for the reduction of nitrogen oxides (NOx) by hydrocarbons under lean-burn (excess oxygen) conditions on a silver catalyst. Although a nitrate-type species tracks the formation of isotopically labeled dinitrogen, the results show that this is misleading because a nitrate-type species has the same response to an isotopic switch even under conditions where no dinitrogen is produced. In the case of cyanide and isocyanate species, the results show that it is possible to differentiate between slowly reacting spectator isocyanate species, probably adsorbed on the oxide support, and reactive isocyanate species, possibly on or close to the active silver phase. The reactive isocyanate species responds to an isotope switch at a rate that matches that of the rate of formation of the main product, dinitrogen. It is concluded that these reactive isocyanates could potentially be involved in the reduction of NOx whereas there is no evidence to support the involvement of nitrate-type species that are observable by infrared spectroscopy.

Low-Temperature Selective Catalytic Reduction (SCR) of NOx with n-Octane Using Solvent-Free Mechanochemically Prepared Ag/Al2O3 Catalysts

Low-temperature (<200 degrees C) hydrocarbon selective catalytic reduction of NOx has been achieved for the first time in the absence of hydrogen using a solvent-free mechanochemically prepared Ag/Al2O3 catalyst. Catalysts prepared by this ball-milling method show a remarkable increase in activity for the reduction of nitrogen oxides with octane by lowering the light-off temperature by up to 150 degrees C compared with a state-of-the-art 2 wt %Ag/Al2O3 catalyst prepared by wet impregnation. The best catalyst prepared from silver oxide showed 50% NOx conversion at 240 degrees C and 99%, at 302 degrees C. The increased activity is not due to an increased surface area of the support, but may be associated with a change in.the'defeet structure of the alumina surface, leading to the formation of the small silver clusters necessary for the activation of the octane without leading to total combustion. On the other hand, since one possible role of hydrogen is to remove inhibiting species from the silver, we cannot exclude some change in the chemical properties of the silver as a result of the ball-milling treatment.

A review of biomass co-firing in North America

Biomass fuels have long been accepted as useful renewable energy sources, especially in mitigating greenhouse gases (GHG), nitrogen oxides, and sulfur oxide emissions. Biomass fuel is carbon neutral and is usually low in both nitrogen and sulfur. For the past decade, various forms of biomass fuels have been co-combusted in existing coal-fired boilers and gas-fired power plants. Biomass is used as a supplemental fuel to substitute for up to 10% of the base fuel in most full commercial operations. There are several successful co-firing projects in many parts of the world, particularly in Europe and North America. However, despite remarkable commercial success in Europe, most of the biomass co-firing in North America is limited to demonstration levels. This review takes a detailed look at several aspects of biomass co-firing with a direct focus on North America. It also explores the benefits, such as the reduction of GHG emissions and its implications. This paper shows the results of our studies of the biomass resources available in North America that can be used in coal-fired boilers, their availability and transportation to the power plant, available co-firing levels and technologies, and various technological and environmental issues associated with biomass co-firing. Finally, the paper proffers solutions to help utility companies explore biomass co-firing as a transitional option towards a completely carbon-free power sector in North America.

Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

Increasing the accuracy of Nitrogen Dioxide (NO2) pollution mapping using geographically weighted regression (GWR) and geostatistics.

Nitrogen Dioxide (NO2) is known to act as an environmental trigger for many respiratory illnesses. As a pollutant it is difficult to map accurately, as concentrations can vary greatly over small distances. In this study three geostatistical techniques were compared, producing maps of NO2 concentrations in the United Kingdom (UK). The primary data source for each technique was NO2 point data, generated from background automatic monitoring and background diffusion tubes, which are analysed by different laboratories on behalf of local councils and authorities in the UK. The techniques used were simple kriging (SK), ordinary kriging (OK) and simple kriging with a locally varying mean (SKlm). SK and OK make use of the primary variable only. SKlm differs in that it utilises additional data to inform prediction, and hence potentially reduces uncertainty. The secondary data source was Oxides of Nitrogen (NOx) derived from dispersion modelling outputs, at 1km x 1km resolution for the UK. These data were used to define the locally varying mean in SKlm, using two regression approaches: (i) global regression (GR) and (ii) geographically weighted regression (GWR). Based upon summary statistics and cross-validation prediction errors, SKlm using GWR derived local means produced the most accurate predictions. Therefore, using GWR to inform SKlm was beneficial in this study.