Typical Volatile Organic Compounds Research Articles

Comparison between vacuum and modified-atmosphere packaging on dynamic analysis of flavor properties and microbial communities in fresh-cut potatoes (Solanum tuberosum L.)

Fresh-cut potatoes are prone to browning and quality deterioration during storage, which leads to a short shelf life. In the present study, we investigated the sensory quality attributes, flavor profiles, and bacterial community composition of fresh-cut potato cubes stored at 4 °C for 18 days in vacuum packaging and 30 % CO2/70 % N2 modified-atmosphere packaging. In addition, a correlation analysis of volatile organic compounds and bacterial taxa was performed. In total, 26 types of volatile organic compounds were identified; aldehydes were considered as the main contributors to the odor, and the off-flavor was mainly described as a mixture of oily, spicy, and beany flavors. The dominant bacteria in all packaged potatoes were fermentative gram-negative bacteria Alcaligenaceae and Sphaerotilus. Notably, compared with vacuum packaging, modified-atmosphere packaging inhibited the generation and development of undesirable flavors and maintained the sensory profile of fresh-cut potatoes in a better manner during storage.

A Colorimetric Label‐Free Sensor Array of Metal–Organic‐Framework‐Based Fabry–Pérot Films for Detecting Volatile Organic Compounds and Food Spoilage

AbstractThe unambiguous detection and classification of volatile organic compounds (VOCs) are crucial in many fields. For using VOC‐sensing to explore the alteration and spoilage of food, very inexpensive sensors are desired. Simple colorimetric sensors seem highly attractive for these applications. Here, a label‐free, colorimetric sensor array made of metal‐organic‐framework‐based (MOF‐based) Fabry‐Pérot (FP) films is presented where the signal read‐out is performed either by their optical spectra or by pictures taken with a smartphone camera. Exposing the FP‐MOF‐films to various VOCs causes a reversible shift of the photonic pattern, where the magnitude of the shift depends on the VOC type, its concentration, and the MOF structure. The application of machine‐ learning‐ algorithms on the sensor data allows to identify the VOCs with a high classification accuracy (92% at 100 ppm). It is shown that the sensor array read‐out can also be performed with a common smartphone camera, also precisely classifying the VOC analytes. Moreover, fresh and spoiled food, like milk and meat, is distinguished by its head space. Thus, the study presents a very inexpensive platform of small colorimetric sensors that allow determining the quality, alteration, and spoilage of food, and it may contribute to realizing smart labels and intelligent packaging.

Utilizing Machine Learning for Rapid Discrimination and Quantification of Volatile Organic Compounds in an Electronic Nose Sensor Array

Volatile organic compounds (VOCs) are ubiquitous in the surroundings, originating from both industrial and natural sources. VOCs directly impact the quality of both indoor and outdoor air and play a significant role in processes such as fruit ripening and the body’s metabolism. VOC monitoring has seen significant growth recently, with an emphasis on developing low-cost, portable sensors capable of both vapor discrimination and concentration measurements. VOC sensing remains challenging, mainly because these compounds are nonreactive, appear in low concentrations and share similar chemical structures that results in poor sensor selectivity. Therefore, individual gas sensors struggle to selectively detect target VOCs in the presence of interferences. Electronic noses overcome these limitations by employing machine learning for pattern recognition from arrays of gas sensors. Here, an electronic nose fabricated with four types of functionalized gold nanoparticles demonstrates rapid detection and quantification of eight types of VOCs at four concentration levels. A robust two-step machine learning pipeline is implemented for classification followed by regression analysis for concentration prediction. Random Forest and support vector machine classifiers show excellent results of 100% accuracy for VOC discrimination, independent of measured concentration levels. Each Random Forest regression analysis exhibits high R2 and low RMSE with an average of 0.999 and 0.002, respectively. These results demonstrate the ability of gold nanoparticle gas sensor arrays for rapid detection and quantification.

Low-concentration and multi-component NMHCs capture from oil field exhaust using porous ZIF-8/iso-hexadecane slurry

Non-methane hydrocarbons (NMHCs) are a common type of volatile organic compounds (VOCs) pollutant in the petrochemical industry and have attracted widespread attention because of their adverse health effects and environmental impacts. In this paper, we report a new porous slurry formed with zeolitic imidazolate framework-8 (ZIF-8) and iso-hexadecane to capture the low-concentration and multi-component NMHCs (mainly ethane (C2H6), propane (C3H8), and n-butane (n-C4H10)) from the oil field exhaust. The sorption capacity of C2H6 in the slurry is significantly higher than that of nitrogen (N2) and methane (CH4). Moreover, the slurry demonstrated a clear advantage for C2H6 over N2 and CH4 in competitive adsorption through the pressure-drop curves. In the NMHCs capture experiments, the C3H8 and n-C4H10 concentrations after purification can be reduced to below 100 ppm, while the C2H6 concentration can reach approximately 180 ppm. More encouragingly, in the breakthrough tests, the slurry exhibits a perfect kinetic separation selectivity for multi-component NMHCs. Furthermore, to avoid structural collapse of ZIF-8 material during long-term use in acidic and wet environments, a certain amount of 2-methylimidazole was retained in the slurry as a protective agent in the material synthesis process. In this way, the ZIF-8 materials in the slurry can retain the stable characteristic structure in an aqueous and acidic environment and keep the capture capacity for NMHCs without degradation. We believe the porous ZIF-8/iso-hexadecane slurry is a promising capture agent for low-concentration and multi-component NMHCs with strong purification capacity and stability.

Recent Advances of VOCs Catalytic Oxidation over Spinel Oxides: Catalyst Design and Reaction Mechanism.

Volatile organic compounds (VOCs) harm the environment and human health and have been of wide concern and purified efficiently by catalytic oxidation. Spinel oxides, mainly composed of transition metal elements with low price and extensive sources, have been widely investigated as efficient and stable catalysts for VOCs oxidation due to their adjustable element composition, flexible structure, and high thermal/chemical stability. However, it is necessary to dissect the design of the spinel in a targeted way to satisfy the removal of different types of VOCs. This article systematically summarizes the recent advances regarding the application of spinel oxides for VOCs catalytic oxidation. Specifically, the design strategies of spinel oxides were first introduced to clarify their effect on the structure and properties of the catalyst. Then the reaction mechanism and degradation pathway of different kinds of VOCs on the spinel oxides were in detail summarized, and the characteristic requirements of the spinel oxides for various VOCs purification were analyzed. Furthermore, the practice applications were also discussed. Finally, the prospects were proposed to guide the rational design of spinel-based catalysts for VOCs purification and intensify the understanding of reaction mechanisms.

Improving oxidation removal of toluene in plasma coupling perovskite catalysts system by constructing Au sites on a La0.5Ce0.5CoO3-δ

Plasma-catalysis technique is a promising approach to control air pollution caused by volatile organic compounds (VOCs). Perovskite-type oxides have excited much interest in constructing plasma-catalytic system for the oxidation removal of VOCs owing to their flexible electronic structure, alterable geometry, unique catalytic properties and high stability. However, the perovskites commonly suffer from low surface area and small amounts of active surface sites because of their high synthesis temperature, which limits the synergism between the perovskites and plasma and thus decreases the performance of plasma-catalytic oxidation of VOCs. Here we show that the oxidation removal of toluene (typical refractory VOCs) in the plasma-catalytic system is improved by constructing Au sites on a perovskite of La0.5Ce0.5CoO3-δ (Au/La0.5Ce0.5CoO3-δ). Compared with plasma-catalytic systems integrated by LaCoO3 or La0.5Ce0.5CoO3-δ, coupling the Au/La0.5Ce0.5CoO3-δ with plasma enables the boost of toluene conversion and CO2 selectivity, but suppresses the generation of secondary pollutants (O3 and NOx). The calculation of apparent activation energy (Ea) demonstrates that the plasma-catalytic system integrated by Au/La0.5Ce0.5CoO3-δ obtains lower Ea of 6.9 kJ/mol than those integrated by LaCoO3 (9.5 kJ/mol) and La0.5Ce0.5CoO3-δ (8.1 kJ/mol) as well as plasma alone (15.0 kJ/mol), confirming a favorable toluene oxidation process in the plasma coupling Au/La0.5Ce0.5CoO3-δ system. Catalyst characterizations, discharge diagnosis and density functional theory calculations suggest that depositing Au on the La0.5Ce0.5CoO3-δ render the favorable gas and surface reactions for toluene oxidation in the plasma-catalytic system and thus a strong synergism between the perovskites and plasma, by modulating the discharge mode and creating large numbers of highly active Auδ+-Oδ--Ce interfacial sites on the surface of La0.5Ce0.5CoO3-δ.

Separation of furfuryl alcohol from water using hydrophobic deep eutectic solvents

Furfuryl alcohol (FA) is an important organic chemical feedstock that must be separated from water to upgrade it into high-value-added products. Since FA forms an azeotrope with water, liquid-liquid extraction is a suitable option for separating both compounds. This work evaluates the separation of FA from water using hydrophobic deep eutectic solvents (DES). Three DES were prepared using menthol, thymol, and octanoic acid by combining them in molar ratio as follows: thymol + octanoic acid (1:2), menthol + octanoic acid (1:2), and thymol + menthol (1:1). Experimental liquid-liquid equilibria (LLE) of ternary systems water + FA + DES measured at 313.15 K and 101.13 kPa were used to determine the distribution coefficient and selectivity values for FA when using each DES. The experimental results were compared with molecular dynamics (MD) using Martini 3 force field and modeled using Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) without any adjustable binary parameters. According to the results, selectivities and distribution coefficients using hydrophobic DES have comparable values to traditional volatile organic compounds (VOCs) used to separate FA from water. In general, DES shows better distribution coefficients compared with typical organic solvents. According to the results, a good alternative would be menthol + octanoic acid (1:2) or thymol + menthol (1:1) to replace typical VOCs. MD and PC-SAFT provide accurate estimations for ternary LLE in the range of examined thermodynamic conditions, which confirms the predictive consistency of both approaches. Microscopic properties computed with MD simulations evidence a surface activity or absolute adsorption of FA in the interfacial region, which is correlated with favorable distribution coefficients and selectivities.

VOC transport in an occupied residence: Measurements and predictions via deep learning

Monitoring and prediction of volatile organic compounds (VOCs) in realistic indoor settings are essential for source characterization, apportionment, and exposure assessment, while it has seldom been examined previously. In this study, we conducted a field campaign on ten typical VOCs in an occupied residence, and obtained the time-resolved VOC dynamics. Feature importance analysis illustrated that air change rate (ACR) has the greatest impact on the VOC concentration levels. We applied three multi-feature (temperature, relative humidity, ACR) deep learning models to predict the VOC concentrations over ten days in the residence, indicating that the long short-term memory (LSTM) model owns the best performance, with predictions the closest to the observed data, compared with the other two models, i.e., recurrent neural network (RNN) model and gated recurrent unit (GRU) model. We also found that human activities could significantly affect VOC emissions in some observed erupted peaks. Our study provides a promising pathway of estimating long-term transport characteristics and exposures of VOCs under varied conditions in realistic indoor environments via deep learning.

Source profile study of VOCs unorganized emissions from typical aromatic devices in petrochemical industry

Volatile organic compounds (VOCs) are significant pollutants generated during the processes of petroleum refining and chemical production. Aromatic hydrocarbons, in particular, pose a great risk to human health. Nevertheless, unorganized emissions of VOCs from typical aromatics units remain poorly studied and reported. Therefore, it is vital to achieve precise control over aromatic hydrocarbons while managing VOCs. In this study, two typical aromatics production devices in petrochemical enterprises, namely aromatics extraction devices and ethylbenzene devices, were selected. The fugitive emissions of VOCs from the process pipelines in the units were investigated. Samples were collected and transferred using the EPA bag sampling method and HJ 644 and analyzed using gas chromatography–mass spectrometry. The results indicated that a total of 112 VOCs were emitted during the six rounds of sampling in the two types of devices, with alkanes (61 %), aromatic hydrocarbons (24 %), and olefins (8 %) being the primary types of VOCs emitted. The results also revealed the unorganized emissions characteristic substances of VOCs in the two types of devices, with slight differences in the types of VOCs emitted. The study found significant differences in the detection concentrations of aromatic hydrocarbons and olefins, as well as the types of detected chlorinated organic compounds (CVOCs), between the two sets of aromatics extraction units in distinct regions. These differences were closely related to the processes and leakages in the devices and can be effectively controlled by enhancing leak detection and repair (LDAR) and other measures. This article offers guidance for compiling VOCs emission inventories and improving the management of VOCs emissions in petrochemical enterprises by refining the source spectrum at the device scale. The findings are significant for analyzing VOCs unorganized emission factors and promoting safe production in enterprises.

Terpenoid VOC profiles and functional characterization of terpene synthases in diploid and tetraploid cytotypes of Chrysanthemum indicum L

Chrysanthemum indicum L. is a valuable medicinal plant with diploid and tetraploid forms that are widely distributed in central and southern China, and it contains abundant volatile organic compounds (VOCs). Despite the discovery of some terpene synthase (TPS) in C. indicum (i.e., CiTPS) in previous studies, many TPSs and their corresponding terpene biosynthesis pathways have yet to be discovered. In the present study, terpenoid VOCs in different tissues from two cytotypes of C. indicum were analyzed. We identified 52 types of terpenoid VOCs and systematically investigated the content and distribution of these compounds in various tissues. The two cytotypes of C. indicum exhibited different volatile terpenoid profiles. The content of monoterpenes and sesquiterpenes in the two cytotypes showed an opposite trend. In addition, four full-length candidate TPSs (named CiTPS5–8) were cloned from Ci-GD4x, and their homologous TPS genes were screened based on the genome data of Ci-HB2x. These eight TPSs displayed various tissue expression patterns and were discovered to produce 22 terpenoids, 5 of which are monoterpenes and 17 are sesquiterpenes. We further proposed corresponding terpene synthesis pathways, which can enable the establishment of an understanding of the volatile terpenoid profiles of C. indicum with different cytotypes. This knowledge may provide a further understanding of germplasm in C. indicum and may be useful for biotechnology applications of Chrysanthemum plants.

Si-Doped Nitrogenated Holey Graphene (C2N) as a Promising Gas Sensor for O-Containing Volatile Organic Compounds (VOCs) and Ammonia

Two-dimensional (2D) crystalline materials have been regarded as promising sensor materials due to their large specific surface area, high sensitivity, and low cost. In the present work, based on the density functional theory (DFT) method, the sensor performance of novel silicon (Si)-doped nitrogenated holey graphene (SiC2N) toward five typical VOCs (HCHO, CH3OH, C3H6O, C6H6, and C2HCl3) and ammonia were systematically investigated. The results demonstrated that Si doping could effectively decrease the band gap of C2N and simultaneously provide active sites for gas adsorption. Through comprehensive analyses of adsorption energies and electronic properties, the SiC2N was found to exhibit high selectivity for O-containing VOCs (HCHO, CH3OH, and C3H6O) and NH3 via a covalent bond. Moreover, after the HCHO, CH3OH, C3H6O, and NH3 adsorption, the band gap of SiC2N greatly decreases from 1.07 eV to 0.29, 0.13, 0.25, and 0.12 eV, respectively, which indicated the enhancement the conductivity and enabled the SiC2N to be a highly sensitive resistive-type sensor. In addition, the SiC2N possesses a short recovery time. For instance, the recovery time of HCHO desorbed from SiC2N is 29.2 s at room temperature. Our work anticipates a wide range of potential applications of Si-doped C2N for the detection of toxic VOCs and ammonia, and supplies a valuable reference for the development of C2N-based gas sensors.

Polydimethylsiloxane-coated macroporous silica adsorbent in thermal desorption gas chromatography

Polydimethylsiloxane (PDMS)-coated macroporous silica (MPSi) particles were developed for the extraction of volatile organic compounds (VOCs) from air samples in thermal desorption-gas chromatographic analysis. The gas sample was collected by a gas sampling pump at 100 mL/min. Different amounts of PDMS coating were prepared, and the fundamental extraction and desorption performances were investigated using even numbered n-alkanes of C8–C28. The extraction efficiency increased by increasing PDMS coating, and the desorption efficiency showed more than 99% at a desorption temperature of 310°C for all the investigated adsorbents. This remarkable desorption performance showed a higher peak area of the analytes than that of the Tenax TA-packed thermal desorption tube, especially for higher molecular weight compounds. Furthermore, an activated carbon particle of Carbopack X was introduced on the latter side of the PDMS-MPSi to extract low-molecular weight compounds. This double-bed-type extraction tube showed a successful determination of a wide range of VOCs. The double-bed-type extraction tube was then applied to the extraction of VOCs related to sick building syndrome (SBS). The results for the extraction and desorption performances of the SBS-related VOCs were well agreed with that of alkanes, and the applicability of the extraction tube to the determination of other types of conventional VOCs were confirmed.

Pt/CeMnOx/Diatomite: A Highly Active Catalyst for the Oxidative Removal of Toluene and Ethyl Acetate

Pt nanoparticles and a CeMnOx composite were loaded on the surface of the natural diatomite material to generate the Pt/CeMnOx/diatomite using the redox precipitation and impregnation methods. The physicochemical properties of the catalysts were characterized by means of various techniques. The catalytic properties and resistance to H2O and SO2 of the catalysts were measured for the oxidation of typical volatile organic compounds (i.e., toluene and ethyl acetate). Among all of the as-prepared samples, Pt/CeMnOx/diatomite exhibited the highest catalytic activity: the temperatures (T90%) at a toluene or ethyl acetate conversion of 90% were 230 and 210 °C at a space velocity (SV) of 20,000 mL g−1 h−1, respectively, and the turnover frequency (TOFPt) at 220 °C was 1.04 μmol/(gcat s) for ethyl acetate oxidation and 1.56 μmol/(gcat s) for toluene oxidation. In particular, this sample showed a superior catalytic activity for ethyl acetate oxidation at low temperatures, with its T50% being 185 °C at SV = 20,000 mL g−1 h−1. In addition, the Pt/CeMnOx/diatomite sample possessed good sulfur dioxide resistance during the toluene oxidation process. In the presence of SO2, some of the SO2 molecules were adsorbed on diatomite, which protected the active sites from being poisoned by SO2 to a certain extent. The pathways of ethyl acetate and toluene oxidation over Pt/CeMnOx/diatomite or Pt/CeMnOx were as follows: The C–C and C–O bonds in ethyl acetate are first broken to form the CH3CH2O* and CH3CO* species or toluene is first oxidized to benzaldehyde and benzoic acid, and all of these intermediates are then converted to CO2 and H2O. This work can provide a strategy to develop efficient catalysts with high catalytic activity, durability, low cost, and easy availability under actual working conditions.

Exploring the volatile metabolites of three Chorisia species: Comparative headspace GC–MS, multivariate chemometrics, chemotaxonomic significance, and anti-SARS-CoV-2 potential

Chorisia (syn. Ceiba) species are important ornamental, economic, and medicinal plants that are endowed with a diversity of secondary metabolites; however, their volatile organic compounds (VOCs) have been scarcely studied. Therefore, this work explores and compares the headspace floral volatiles of three common Chorisia species, namely Chorisia chodatii Hassl., Chorisia speciosa A. St.-Hil, and Chorisia insignis H.B.K. for the first time. A total of 112 VOCs of varied biosynthetic origins were identified at different qualitative and quantitative ratios, encompassing isoprenoids, fatty acid derivatives, phenylpropanoids, and others. Flowers of the investigated species showed perceptibly differentiated volatile profiles, with those emitted by C. insignis being dominated by non-oxygenated compounds (56.69 %), whereas oxygenated derivatives prevailed among the volatiles of C. chodatii (66.04 %) and C. speciosa (71.53 %). The variable importance in the projection (VIP) in the partial least-squares–discriminant (PLS-DA) analysis described 25 key compounds among the studied species, of which linalool was verified as the most important aroma compound based on VIP values and significance analysis, and it could represent the most typical VOC among these Chorisia species. Furthermore, molecular docking and dynamics analyses of both the major and the key VOCs displayed their moderate to promising binding interactions with four main proteins of SARS-CoV-2, including Mpro, PLpro, RdRp, and spike S1 subunit RBD. The current results collectively cast new light on the chemical diversity of the VOCs of Chorisia plants as well as their chemotaxonomic and biological relevance.

VOCs and PM listing of Eucalyptus globulus combustion in residential wood stoves

Pollutant residential emissions from wood stoves have significant impacts both on the environment and people's health. The above makes it essential to know the types of volatile organic compounds emitted during combustion and explore their relationship with particulate matter and greenhouse gas emissions. This paper studies and analyzes these emissions using Eucalyptus globulus as fuel varying its moisture levels. Emissions were determined using an adapted commercial stove. The concentration levels of volatile organic compounds and particulate matter increase with the moisture of wood. When analyzing volatile organic compounds, particulate matter, and O2 with the combustion stages of wood, it is found that their concentrations were higher in the ignition and the reload stage. The concentrations of CO2 and NOx were higher in the reload stage. Other chemical compounds, such as toluene, xylene, and benzene, were also found within the volatile organic compounds listing, which increased their concentration in the ignition and stable reload stages. However, in the quenching stage, they are not present. Finally, the dispersion of these molecules in the environment is evaluated, obtaining that if the atmospheric conditions are adverse, these molecules remain in the environment in direct contact with the people living in those places.

Metal–Organic Framework (MOF) Derivatives as Promising Chemiresistive Gas Sensing Materials: A Review

The emission of harmful gases has seriously exceeded relative standards with the rapid development of modern industry, which has shown various negative impacts on human health and the natural environment. Recently, metal-organic frameworks (MOFs)-based materials have been widely used as chemiresistive gas sensing materials for the sensitive detection and monitoring of harmful gases such as NOx, H2S, and many volatile organic compounds (VOCs). In particular, the derivatives of MOFs, which are usually semiconducting metal oxides and oxide-carbon composites, hold great potential to prompt the surface reactions with analytes and thus output amplified resistance changing signals of the chemiresistors, due to their high specific surface areas, versatile structural tunability, diversified surface architectures, as well as their superior selectivity. In this review, we introduce the recent progress in applying sophisticated MOFs-derived materials for chemiresistive gas sensors, with specific emphasis placed on the synthesis and structural regulation of the MOF derivatives, and the promoted surface reaction mechanisms between MOF derivatives and gas analytes. Furthermore, the practical application of MOF derivatives for chemiresistive sensing of NO2, H2S, and typical VOCs (e.g., acetone and ethanol) has been discussed in detail.

Optimization of photocatalytic oxidation reactor for air purifier design: Application of artificial neural network and genetic algorithm

Photocatalytic oxidation (PCO) is a promising approach for eliminating volatile organic compounds (VOCs) from indoor environments. The generation of toxic by-products, however, prevents this method becomes widely used. There is a lack of comprehensive model for the prediction of PCO removal efficiency and by-products generation, and its optimization. To address that, this study focusses on modeling and optimization of PCO based on artificial neural networks and genetic algorithms. The concentrations of target VOCs and three common by-products are estimated using the ANN model, which takes seven input parameters into account. They include; PCO type, number of PCO layers, air velocity, relative humidity, light intensity, and target VOC and its concentration. A number of ANN-based estimation concentration models are trained, validated, and tested using the experimental data from bench and pilot scale set-ups (a total of 260 data points). The best performance is achieved with a three-layer feed-forward back-propagation structure with 11 neurons in the hidden layer (7:11:4), tansig-purelin transfer function, and Levenberg-Marquardt (LM) as the training algorithm. The proposed ANN model could be trained to predict the concentration of different VOCs and formed by-products with a high accuracy (R2 of 0.99), which was further validated and tested with 0.98 and 0.97 precision, respectively. The relative importance of input parameters in the removal of target VOC and generated by-products showed that PCO media and type of target VOC were the most influential variables. Further, multi-objective optimization for maximizing removal efficiency and minimizing by-products showed that the optimal condition for PCO process is achieved when two layers of glass fiber-based PCO media is used as a photocatalyst, and the system is operating at air velocity of 0.91 m/s and relative humidity of 48.7%, and butyraldehyde concentration of 47.3 ppb.

Competitive adsorption characteristics of gasoline evaporated VOCs in microporous activated carbon by molecular simulation

The activated carbon in the vehicle's carbon canister needs to adsorb a variety of VOCs (Volatile Organic Compounds) emitted by gasoline evaporation, while the difference in gas adsorption capacity can lead to adsorption competition phenomena. In this study, three typical VOCs (toluene, cyclohexane, and ethanol) were selected to study the adsorption competition characteristics between multi-component gases at different pressures by molecular simulation method. In addition, the effect of temperature on adsorption competition was also investigated. The results show that the selectivity of activated carbon to toluene is negatively correlated with the adsorption pressure, but the opposite is true for ethanol, and the change of cyclohexane is not significant. The competitive order of the three VOCs is toluene > cyclohexane > ethanol at low pressure, which becomes ethanol > toluene > cyclohexane at high pressure. With increasing pressure, the interaction energy decreases from 12.87 kcal/mol to 11.87 kcal/mol, where the electrostatic interaction energy increases from 1.97 kcal/mol to 2.54 kcal/mol. In microporous activated carbon, the competition is mainly manifested in that ethanol preempts the low-energy adsorption sites of toluene in the pore size of 10 Å to 18 Å, while gas molecules near the surface of activated carbon or in smaller pore sizes are stably adsorbed without competition. Despite the fact that high temperature decreases the total adsorption capacity, activated carbon selectivity for toluene increases instead, while the competitiveness of polar ethanol decreases significantly.

Evaluating the feasibility of air environment management system for VOCs through ‘VOCs specification’ of petroleum refining industry

The chemical industry releases various types of volatile organic compounds (VOCs) into the atmosphere, and the concentration of VOCs emitted from chimneys is regulated worldwide. However, some VOCs such as benzene are highly carcinogenic, while others such as ethylene and propylene may cause secondary air pollution, owing to their high ozone-generating ability. Accordingly, the US EPA(United State, Environment Protect Agency) introduced a fenceline monitoring system that regulates the concentration of VOCs at the boundary of a facility, away from the chimney source. This system was first introduced in the petroleum refining industry, which simultaneously emits benzene, affecting the local community because of its high carcinogenicity, and ethylene, propylene, xylene, and toluene, which have a high photochemical ozone creation potential (POCP). These emissions contribute to air pollution. In Korea, the concentration at the chimney is regulated; however, the concentration at the plant boundary is not considered. In accordance with the EPA regulations, Korea’s petroleum refining industries were identified and the limitations of the Clean Air Conservation Act were studied. The average concentration of benzene at the research facility examined in this study was 8.53 µg/m3, which complied with the benzene action level of 9 µg/m3. However, this value was exceeded at some points along the fenceline, in proximity to the benzene-toluene-xylene (BTX) manufacturing process. The composition ratios of toluene and xylene were 27% and 16%, respectively, which were higher than those of ethylene or propylene. These results suggest that reduction measures in the BTX manufacturing process are necessary. This study shows that legal regulations should enforce reduction measures through continuous monitoring at the fenceline of petroleum refineries in Korea.

Adsorptive interaction between typical VOCs and various topological zeolites: Mixture effect and mechanism

Adsorption is one of the most feasible and effective methods to alleviate the volatile organic compounds (VOCs) pollution. However, the mixture effect and mechanism for competitive adsorption of VOCs on zeolites are barely addressed. In this study, toluene, acetone, and ethyl acetate as prevalent VOCs species were removed by four potential zeolites (13X, USY, Beta, ZSM-5) in both single- and multi-component systems. The structure-property relationship between adsorbate-adsorbent pairs was revealed by X-ray diffraction, scanning electron microscopy, energy dispersive spectrometer, X-ray fluorescence, N2 adsorption and density function theory calculation. The molecular polarity and volatility of VOCs species played key roles in adsorption and the dynamic uptakes were generally listed as follows: ethyl acetate > toluene > acetone. As for the above VOCs mixtures, 13X zeolite selectively adsorbed oxygenated VOCs rather than toluene. In contrast, USY exhibited a preference to trap toluene. Ethyl acetate could be readily enriched by ZSM-5 and Beta selectively. The possible explanations and implications are discussed based on the subtle change in electron density. The results obtained are vital for understanding the mixture effect of VOCs adsorption and may guide the selection of proper adsorbent for real applications.