Mechanism Study On Plasma-catalytic Removal Of Volatile Organic Compounds(VOCs)

China’s annual energy consumption keeps growing with its industrialization and urbanization, which emits a large amount of various gaseous pollutants including particulate matters (PM), SO2, NOx, heavy metal (Hg) and volatile organic compounds (VOCs). These pollutants result in severe regional air quality issues like haze (PM2.5) and photochemical smog (O3), which has become a great concern of the whole country. In recent years, with the introduction of a series of stringent emission standards and laws, the emissions of PM, SO2, NOx, heavy metal (Hg) is greatly reduced. As a result, the emission of VOCs is becoming more significant. VOCs are regarded as one of the precursors of PM2.5 and O3. The vast majority of VOCs are biological toxic, even some of them are carcinogen suspects. At these points, the investigation of cost-beneficial VOC control technologies are of great significance under current situation.Non-thermal plasma (NTP) is able to generate chemical reactive species like energetic electrons, OH, O, N radicals and metastable N2(A) even at room temperature. The species could attack VOCs molecules and nonselectively rupture its chemical bonds, resulting in the removal of VOCs. However, the formation of hazardous and toxic by-products are the major concern when using NTP alone in VOCs control. Moreover, the improvement in energy utilization efficiency should also be considered. Researchers found that the combination of NTP and heterogeneous catalysis could significantly improve the efficiency of VOC removal and drive the reactions towards deep oxidation due to the synergetic effects between NTP and catalysts. Previous works mainly focused on experimental optimization of opearting parameters of plasma and introduction of various catalysts to generate and maximum the synergetic effect. The research on the whole reaction process, especially the interactions between NTP and catalysts are rarely reported. In this work, acetone and formaldehyde are used as model VOC pollutans. The mechanisms of plasma-catalytic removal of model VOCs are discussed.Firstly, we investigated the discharge characteristics of plasma-catalytic reactors. After introduction of packing materials, the discharge mode shifted from microdischarge inside the plasma region to a combination of space micro-discharges and surface discharge. The dissipated energy of single discharge period increased in the presence of packing materials which were closely related to the relative permittivity of packing materials. The specific energy density (SED) followed the sequence of γ-Al2O3> α-Al2O3> glass beads> NTP only. Both oxygen and water molecules were electronegative, which can quench energetic electrons generated in plasma and limit the increase of discharge current. Thus, under the same applied voltage, the SED of plasma reactor decreased at higher oxygen content and relative humidity. Compared to the NTP alone, plasma reactor with packing materials are more sensitive to humidity and oxygen content.Plasma-catalytic removal of acetone is used as a model. The effects of various catalyst support on acetone removal are investigated considering different operating parameters. The results indicated that acetone removal effeciency increased at higher SED. At a same SED, γ-Al2O3 showed the best performance in terms of removal efficiency and energy efficiency. The combination of NTP and γ-Al2O3 greatly inhibited the formation of gaseous by-products like ozone, NO2 and N2O. Moreover, the no N-containing organic by-products are detected in the effluent in the presence of γ-Al2O3. The increase of oxygen content and humidity favors the formation of O and OH radicals, but it accelarates the quench of energetic electrons. Thus, high oxygen content inhibits the removal of acetone, while an optimal relative humidity of 10% for acetone removal are observed in this work.The active phase of catalysts affects the utilization of radicals and VOCs removal effects. The screening of active phase are conducted using acetone as the model pollutants, while γ-Al2O3 are used as the support. The results showed an enhancement in acetone removal efficiency and CO2 selectivity, while the formation of two typical by-products HCHO and HCOOH were inhibited. CuOx/y-Al2O3 exhibited best performance among the tested catalysts. Catalyst characterizations indicated that the redox properties of catalyst samples may play a more important role than the physical structure. A simplified kinetic model was proposed based on the experimental results. According to the model, the overall reaction of plasma-catalytic removal of acetone obeys first-order. The introduction of catalyst effectively accelarated the removal of acetone.In the process of formaldehyde removal, electronic excitations and ratational-vibrational excitations are the major energy exits. With increasing SED, more O, N radicals can be generated together with metastable N2 species, which in turn improve the removal of formaldehyde. The modification of Cu-based metal oxides with Ce further improved the redox properties of the catalysts and capability for VOC removal. CulCel catalyst with a Cu/Ce molar ratio of 1:1 showed the best formaldehyde removal efficiency and CO2 selectivity. The interactions between Cu and Ce species showed a synergetic effect. Compared to single metal oxides, Cu-Ce mixed catalysts possessed larger specific surface area, smaller crystalline size, which are beneficial for the oxidation of formaldehyde. The existance of abundant Ce3+, oxygen vacancies and surface adsorbed oxygen on Cu-Ce catalyts could participate in the surface reactions, leading to the deep oxidation of formaldehyde towards CO2 and H2O.Based on the experimental results and theoretical analysis, a three-layer artificial neural network was established and optimized to model and predict the process of plasma-catalytic removal of acetone in the presence of Mn-Ce catalysts. Relative importance of four operating parameters, namely discharge power, initial concentration, gas flow rate and catalyst composition, were calculated using the ANN model. Discharge power was found to be the most important factor affecting the removal of acetone, while catalyst composition ranked the second position. Gas flow rate and initial concentration of the pollutants had minor effect on the whole process. The model was able to model and predict the system performance under tested and untested working conditions.