Mechanistic studies on the degradation of gasoline oxygenates by advanced oxidation technologies and the reaction of 4-methyl-1,2,4-triazoline-3,5-dione with tetracyclopropylethylene

Gasoline oxygenates (MTBE, methyl tert-butyl ether; DIPE, di-isopropyl ether; ETBE, ethyl tert-butyl ether; TAME, tert-amyl ether) are added to gasoline to boost octane and enhance combustion. The combination of large scale use, high water solubility and only minor biodegradability has now resulted in a significant gasoline oxygenate contamination occurring in surface, ground, and drinking water systems. Combination of hydroxyl radical formation and the pyrolytic environment generated by ultrasonic irradiation (665 kHz) leads to the rapid degradation of MTBE and other gasoline oxygenates in aqueous media. ^ The presence of oxygen promotes the degradation processes by rapid reaction with carbon centered radicals indicating radical processes involving O 2 are significant pathways. A number of the oxidation products were identified. The formation of products (alcohols, ketones, aldehydes, esters, peroxides, etc) could be rationalized by mechanisms which involve hydrogen abstraction by OH radical and/or pyrolysis to form carboncentered radicals which react with oxygen and follow standard oxidation chain processes. ^ The reactions of N-substituted R-triazolinediones (RTAD; R = CH 3 or phenyl) have attracted considerable interest because they exhibit a number of unusual mechanistic characteristics that are analogous to the reactions of singlet oxygen (1O2) and offer an easy way to provide C-N bond(s) formation. The reactions of triazolinedione with olefins have been widely studied and aziridinium imides are generally accepted to be the reactive intermediates. ^ We observed the rapid formation of an unusual intermediate upon mixing tetracyclopropylethylene with 4-methyl-1,2,4-triazoline-3,5-dione in CDCl 3. Detailed characterization by NMR (proton, 13C, 2-D NMRs) indicates the intermediate is 5,5,6,6-tetracyclopropyl-3-methyl-5,6-dihydro-oxazolo[3,2- b][1,2,4]-triazolium-2-olate. Such products are extremely rare and have not been studied. Upon warming the intermediate is converted to 2 + 2 diazetidine (major) and ene product (minor). ^ To further explore the kinetics and dynamics of the reaction activation energies were obtained using Arrhenius plots. Activation energies for the formation of the intermediate from reactants, and 2+2 adduct from the intermediate were determined as 7.48 kcal moll and 19.8 kcal mol−1 with their pre-exponential values of 2.24 × 105 dm 3 mol−1 sec−1 and 2.75 × 108 sec−1, respectively, meaning net slow reactions because of low pre-exponential values caused by steric hindrance. ^

Advanced oxidation of arsenic species in aqueous solutions

Ingestion of arsenic from contaminated water is a serious problem and affects the health of more than 100 million people worldwide. Traditional water purification technologies are generally not effective or cost prohibitive for the removal of arsenic to acceptable levels (≤10 ppb). Current multi-step arsenic removal processes involve oxidation, precipitation and/or adsorption. Advanced Oxidation Technologies (AOTs) may be attractive alternatives to existing treatments. The reactions of inorganic and organic arsenic species with reactive oxygen species were studied to develop a fundamental mechanistic understanding of these reactions, which is critical in identifying an effective and economical technology for treatment of arsenic contaminated water. ^ Detailed studies on the conversion of arsenite in aqueous media by ultrasonic irradiation and TiO2 photocatalytic oxidation (PCO) were conducted, focusing on the roles of hydroxyl radical and superoxide anion radical formed during the irradiation. ·OH plays the key role, while O2 -· has little or no role in the conversion of arsenite during ultrasonic irradiation. The reaction of O2-· does not contribute in the rapid conversion of As(III) when compared to the reaction of As(III) with ·OH radical during TiO2 PCO. Monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA) are readily degraded upon TiO2 PCO. DMA is oxidized to MMA as the intermediate and arsenate as the final product. For dilute solutions, TiO2 also may be applicable as an adsorbent for direct removal of arsenic species, namely As(III), As(V), MMA and DMA, all of which are strongly adsorbed, thus eliminating the need for a multi-step treatment process. ^ Phenylarsonic acid (PA) was subjected to gamma radiolysis under hydroxyl radical generating conditions, which showed rapid degradation of PA. Product analysis and computational calculation both indicate the arsenate group is an ortho, para director. Our results indicate · OH radical mediated processes should be effective for the remediation of phenyl substituted arsonic acids. ^ While hydroxyl radical generating methods, specifically AOTs, appear to be promising methods for the treatment of a variety of arsenic compounds in aqueous media, pilot studies and careful economic analyses will be required to establish the feasibility of AOTs applications in the removal of arsenic. ^

Mechanistic studies on the advanced oxidation and photochemical transformation of cyanotoxins (microcystins)

The increased occurrence of cyanobacteria (blue-green algae) blooms and the production of associated cyanotoxins have presented a threat to drinking water sources. Among the most common types of cyanotoxins found in potable water are microcystins (MCs), a family of cyclic heptapeptides containing substrates. MCs are strongly hepatotoxic and known to initiate tumor promoting activity. The presence of sub-lethal doses of MCs in drinking water is implicated as one of the key risk factors for an unusually high occurrence of primary liver cancer. ^ A variety of traditional water treatment methods have been attempted for the removal of cyanotoxins, but with limited success. Advanced Oxidation Technologies (AOTs) are attractive alternatives to traditional water treatments. We have demonstrated ultrasonic irradiation and UV/H2O2 lead to the degradation of cyanotoxins in drinking water. These studies demonstrate AOTs can effectively degrade MCs and their associated toxicity is dramatically reduced. We have conducted detailed studies of different degradation pathways of MCs and conclude that the hydroxyl radical is responsible for a significant fraction of the observed degradation. Results indicate preliminary products of the sonolysis of MCs are due to the hydroxyl radical attack on the benzene ring and substitution and cleavage of the diene of the Adda peptide residue. AOTs are attractive methods for treatment of cyanotoxins in potable water supplies. ^ The photochemical transformation of MCs is important in the environmental degradation of MCs. Previous studies implicated singlet oxygen as a primary oxidant in the photochemical transformation of MCs. Our results indicate that singlet oxygen predominantly leads to degradation of the phycocyanin, pigments of blue green algae, hence reducing the degradation of MCs. The predominant process involves isomerization of the diene (6E to 6Z) in the Adda side chain via photosensitized isomerization involving the photoexcited phycocyanin. Our results indicate that photosensitized processes play a key role in the environmental fate and elimination of MCs in the natural waters. ^

The investigation of photocatalysts and iron based materials in the oxidation and adsorption of toxic organic and chromium materials

The presences of heavy metals, organic contaminants and natural toxins in natural water bodies pose a serious threat to the environment and the health of living organisms. Therefore, there is a critical need to identify sustainable and environmentally friendly water treatment processes. In this dissertation, I focus on the fundamental studies of advanced oxidation processes and magnetic nano-materials as promising new technologies for water treatments. Advanced oxidation processes employ reactive oxygen species (ROS) which can lead to the mineralization of a number of pollutants and toxins. The rates of formation, steady-state concentrations, and kinetic parameters of hydroxyl radical and singlet oxygen produced by various TiO2 photocatalysts under UV or visible irradiations were measured using selective chemical probes. Hydroxyl radical is the dominant ROS, and its generation is dependent on experimental conditions. The optimal condition for generation of hydroxyl radical by of TiO2 coated glass microspheres is studied by response surface methodology, and the optimal conditions are applied for the degradation of dimethyl phthalate. Singlet oxygen (1O2) also plays an important role for advanced processes, so the degradation of microcystin-LR by rose bengal, an 1O2 sensitizer was studied. The measured bimolecular reaction rate constant between MC-LR and 1O2 is ∼ 106 M-1 s-1 based on competition kinetics with furfuryl alcohol. The typical adsorbent needs separation after the treatment, while magnetic iron oxides can be easily removed by a magnetic field. Maghemite and humic acid coated magnetite (HA-Fe3O4) were synthesized, characterized and applied for chromium(VI) removal. The adsorption of chromium(VI) by maghemite and HA-Fe3O4 follow a pseudo-second-order kinetic process. The adsorption of chromium(VI) by maghemite is accurately modeled using adsorption isotherms, and solution pH and presence of humic acid influence adsorption. Humic acid coated magnetite can adsorb and reduce chromium(VI) to non-toxic chromium (III), and the reaction is not highly dependent on solution pH. The functional groups associated with humic acid act as ligands lead to the Cr(III) complex via a coupled reduction-complexation mechanism. Extended X-ray absorption fine structure spectroscopy demonstrates the Cr(III) in the Cr-loaded HA-Fe 3O4 materials has six neighboring oxygen atoms in an octahedral geometry with average bond lengths of 1.98 Å.

Advanced methodologies in dynamic traffic assignment modeling of managed lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. ^ Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. ^ Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. ^ With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.^

Advanced Methodologies in Dynamic Traffic Assignment Modeling of Managed Lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.