Low Volatile Organic Compounds Research Articles

Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)

Abstract. During the last few decades, the impact of multiphase chemistry on secondary organic aerosols (SOAs) has been demonstrated to be the key to explaining laboratory experiments and field measurements. However, global atmospheric models still show large biases when simulating atmospheric observations of organic aerosols (OAs). Major reasons for the model errors are the use of simplified chemistry schemes of the gas-phase oxidation of vapours and the parameterization of heterogeneous surface reactions. The photochemical oxidation of anthropogenic and biogenic volatile organic compounds (VOCs) leads to products that either produce new SOA or are taken up by existing aqueous media like cloud droplets and deliquescent aerosols. After partitioning, aqueous-phase processing results in polyols, organosulfates, and other products with a high molar mass and oxygen content. In this work, we introduce the formation of new low-volatility organic compounds (LVOCs) to the multiphase chemistry box model CAABA/MECCA. Most notable are the additions of the SOA precursors, limonene and n-alkanes (5 to 8 C atoms), and a semi-explicit chemical mechanism for the formation of LVOCs from isoprene oxidation in the gas and aqueous phases. Moreover, Henry's law solubility constants and their temperature dependences are estimated for the partitioning of organic molecules to the aqueous phase. Box model simulations indicate that the new chemical scheme predicts the enhanced formation of LVOCs, which are known for being precursor species to SOAs. As expected, the model predicts that LVOCs are positively correlated to temperature but negatively correlated to NOx levels. However, the aqueous-phase processing of isoprene epoxydiols (IEPOX) displays a more complex dependence on these two key variables. Semi-quantitative comparison with observations from the SOAS campaign suggests that the model may overestimate methylbutane-1,2,3,4-tetrol (MeBuTETROL) from IEPOX. Further application of the mechanism in the modelling of two chamber experiments, one in which limonene is consumed by ozone and one in which isoprene is consumed by NO3 shows a sufficient agreement with experimental results within model limitations. The extensions in CAABA/MECCA are transferred to the 3D atmospheric model MESSy for a comprehensive evaluation of the impact of aqueous- and/or aerosol-phase chemistry on SOA at a global scale in a follow-up study.

Tethered balloon system and High-Resolution Mass Spectrometry Reveal Increased Organonitrates Aloft Compared to the Ground Level.

Atmospheric particles play critical roles in climate. However, significant knowledge gaps remain regarding the vertically resolved organic molecular-level composition of atmospheric particles due to aloft sampling challenges. To address this, we use a tethered balloon system at the Southern Great Plains Observatory and high-resolution mass spectrometry to, respectively, collect and characterize organic molecular formulas (MF) in the ground level and aloft (up to 750 m) samples. We show that organic MF uniquely detected aloft were dominated by organonitrates (139 MF; 54% of all uniquely detected aloft MF). Organonitrates that were uniquely detected aloft featured elevated O/C ratios (0.73 ± 0.23) compared to aloft organonitrates that were commonly observed at the ground level (0.63 ± 0.22). Unique aloft organic molecular composition was positively associated with increased cloud coverage, increased aloft relative humidity (∼40% increase compared to ground level), and decreased vertical wind variance. Furthermore, 29% of extremely low volatility organic compounds in the aloft sample were truly unique to the aloft sample compared to the ground level, emphasizing potential oligomer formation at higher altitudes. Overall, this study highlights the importance of considering vertically resolved organic molecular composition (particularly for organonitrates) and hypothesizes that aqueous phase transformations and vertical wind variance may be key variables affecting the molecular composition of aloft organic aerosol.

Cloud response to co-condensation of water and organic vapors over the boreal forest

Abstract. Accounting for the condensation of organic vapors along with water vapor (co-condensation) has been shown in adiabatic cloud parcel model (CPM) simulations to enhance the number of aerosol particles that activate to form cloud droplets. The boreal forest is an important source of biogenic organic vapors, but the role of these vapors in co-condensation has not been systematically investigated. In this work, the environmental conditions under which strong co-condensation-driven cloud droplet number enhancements would be expected over the boreal biome are identified. Recent measurement technology, specifically the Filter Inlet for Gases and AEROsols (FIGAERO) coupled to an iodide-adduct chemical ionization mass spectrometer (I-CIMS), is utilized to construct volatility distributions of the boreal atmospheric organics. Then, a suite of CPM simulations initialized with a comprehensive set of concurrent aerosol observations collected in the boreal forest of Finland during spring 2014 is performed. The degree to which co-condensation impacts droplet formation in the model is shown to be dependent on the initialization of temperature, relative humidity, updraft velocity, aerosol size distribution, organic vapor concentration, and the volatility distribution. The predicted median enhancements in cloud droplet number concentration (CDNC) due to accounting for the co-condensation of water and organics fall on average between 16 % and 22 %. This corresponds to activating particles 10–16 nm smaller in dry diameter that would otherwise remain as interstitial aerosol. The highest CDNC enhancements (ΔCDNC) are predicted in the presence of a nascent ultrafine aerosol mode with a geometric mean diameter of ∼ 40 nm and no clear Hoppel minimum, indicative of pristine environments with a source of ultrafine particles (e.g., via new particle formation processes). Such aerosol size distributions are observed 30 %–40 % of the time in the studied boreal forest environment in spring and fall when new particle formation frequency is the highest. To evaluate the frequencies with which such distributions are experienced by an Earth system model over the whole boreal biome, 5 years of UK Earth System Model (UKESM1) simulations are further used. The frequencies are substantially lower than those observed at the boreal forest measurement site (< 6 % of the time), and the positive values, peaking in spring, are modeled only over Fennoscandia and the western parts of Siberia. Overall, the similarities in the size distributions between observed and modeled (UKESM1) are limited, which would limit the ability of this model, or any model with a similar aerosol representation, to project the climate relevance of co-condensation over the boreal forest. For the critical aerosol size distribution regime, ΔCDNC is shown to be sensitive to the concentrations of semi-volatile and some intermediate-volatility organic compounds (SVOCs and IVOCs), especially when the overall particle surface area is low. The magnitudes of ΔCDNC remain less affected by the more volatile vapors such as formic acid and extremely low- and low-volatility organic compounds (ELVOCs and LVOCs). The reasons for this are that most volatile organic vapors condense inefficiently due to their high volatility below the cloud base, and the concentrations of LVOCs and ELVOCs are too low to gain significant concentrations of soluble mass to reduce the critical supersaturations enough for droplet activation to occur. A reduction in the critical supersaturation caused by organic condensation emerges as the main driver of the modeled ΔCDNC. The results highlight the potential significance of co-condensation in pristine boreal environments close to sources of fresh ultrafine particles. For accurate predictions of co-condensation effects on CDNC, also in larger-scale models, an accurate representation of the aerosol size distribution is critical. Further studies targeted at finding observational evidence and constraints for co-condensation in the field are encouraged.

Molecular-Level Insights into the Relationship between Volatility of Organic Aerosol Constituents and PM2.5 Air Pollution Levels: A Study with Ultrahigh-Resolution Mass Spectrometry.

Volatility of organic aerosols (OAs) significantly influences new particle formation and the occurrence of particulate air pollution. However, the relationship between the volatility of OA and the level of particulate air pollution (i.e., particulate matter concentration) is not well understood. In this study, we compared the chemical composition (identified by an ultrahigh-resolution Orbitrap mass spectrometer) and volatility (estimated based on a predeveloped parametrization method) of OAs in urban PM2.5 (particulate matter with aerodynamic diameter ≤ 2.5 μm) samples from seven German and Chinese cities, where the PM2.5 concentration ranged from a light (14 μg m-3) to heavy (319 μg m-3) pollution level. A large fraction (71-98%) of compounds in PM2.5 samples were attributable to intermediate-volatility organic compounds (IVOCs) and semivolatile organic compounds (SVOCs). The fraction of low-volatility organic compounds (LVOCs) and extremely low-volatility organic compounds (ELVOCs) decreased from clean (28%) to heavily polluted urban regions (2%), while that of IVOCs increased from 34 to 62%. We found that the average peak area-weighted volatility of organic compounds in different cities showed a logarithmic correlation with the average PM2.5 concentration, indicating that the volatility of urban OAs increases with the increase of air pollution level. Our results provide new insights into the relationship between OA volatility and PM pollution levels and deepen the understanding of urban air pollutant evolution.

VOC data-driven evaluation of vehicle cabin odor: from ANN to CNN-BiLSTM.

Emissions of volatile organic compounds (VOCs) in vehicles represent a significant problem, causing unpleasant odors. To mitigate VOCs and odors in vehicles, it is critical to choose interior parts with low odor and VOC emissions. However, prevailing odor evaluation methods are subjective, costly, and potentially harmful to the health of evaluators. In this study, we analyzed 139 automotive interior parts and 92 vehicles, establishing a cost-effective, data-driven method for odor evaluation. The contents of benzene, toluene, ethylbenzene, xylene, styrene, formaldehyde, acetaldehyde, acrolein, and total volatile organic compounds (TVOC) were detected by thermal desorption gas chromatography-mass spectrometry (TD-GC/MS) and high-performance liquid chromatography with an ultraviolet detector (HPLC-UV). Professional odor evaluators assessed the odors, identifying intensity levels from 2.0 to 4.5 in interior parts and 2.5 to 3.5 in whole vehicles. Leveraging this data, we applied four supervised learning algorithms to develop predictive models for the odor intensity of both interior parts and entire vehicles. During model training, we implemented early stopping techniques for the artificial neural network (ANN) and convolutional neural network-bidirectional long short-term memory (CNN-BiLSTM) models, while optimizing the support vector machine (SVM) and extreme gradient boosting (XGBoost) models using the GridSearch algorithm. The evaluation results reveal that the CNN-BiLSTM model performs the best, achieving an average accuracy of 89% for unknown samples within an odor intensity level of 0.5. The root mean square error (RMSE) is 0.24, and the mean absolute error (MAE) is 0.08. The model also underwent a sevenfold cross-validation, achieving an accuracy of 83.43%. Additionally, we employed SHapley Additive exPlanations (SHAP) for the interpretative analysis of the model, which confirmed the consistency of each VOC's odor contribution with human olfactory rules. By predicting odors based on VOCs through supervised learning, this study reduces the costs and enhances the efficiency and applicability of odor assessment across various vehicle interiors.

Simulated phase state and viscosity of secondary organic aerosols over China

Abstract. Secondary organic aerosols (SOAs) can exist in liquid, semi-solid, or amorphous solid states. Chemical transport models (CTMs), however, usually assume that SOA particles are homogeneous and well-mixed liquids, with rapid establishment of gas–particle equilibrium for simulations of SOA formation and partitioning. Missing the information of SOA phase state and viscosity in CTMs impedes accurate representation of SOA formation and evolution, affecting the predictions of aerosol effects on air quality and climate. We have previously developed a parameterization to estimate the glass transition temperature (Tg) of an organic compound based on volatility and to predict viscosity of SOA. In this study, we apply this method to predict the phase state of SOA particles over China in summer of 2018 using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). The simulated Tg of dry SOA (Tg,org) agrees well with the value estimated from ambient volatility measurements at an urban site in Beijing. For the spatial distributions of Tg,org, simulations show that at the surface the values of Tg,org range from ∼287 to 305 K, with higher values in northwestern China, where SOA particles have larger mass fractions of low-volatility compounds. Considering water uptake by SOA particles, the SOA viscosity shows a prominent geospatial gradient in which highly viscous or solid SOA particles are mainly predicted in northwestern China. The lowest and highest SOA viscosity values both occur over the Qinghai–Tibet Plateau, where the solid phase state is predicted over dry and high-altitude areas and the liquid phase state is predicted mainly in the south of the plateau with high relative humidity during the summer monsoon season. Sensitivity simulations show that, including the formation of extremely low-volatility organic compounds, the percent time that a SOA particle is in the liquid phase state decreases by up to 12 % in southeastern China during the simulated period. With an assumption that the organic and inorganic compounds are internally mixed in one phase, we show that the water absorbed by inorganic species can significantly lower the simulated viscosity over southeastern China. This indicates that constraining the uncertainties in simulated SOA volatility distributions and the mixing state of the organic and inorganic compounds would improve prediction of viscosity in multicomponent particles in southeastern China. We also calculate the characteristic mixing timescale of organic molecules in 200 m SOA particles to evaluate kinetic limitations in SOA partitioning. Calculations show that during the simulated period the percent time of the mixing timescale longer than 1 h is >70 % at the surface and at 500 hPa in most areas of northern China, indicating that kinetic partitioning considering the bulk diffusion in viscous particles may be required for more accurate prediction of SOA mass concentrations and size distributions over these areas.

Effect of Relative Humidity on the Rate of New Particle Formation for Different VOCs

Atmospheric new particle formation (NPF) is an important source of aerosol particles and cloud condensation nuclei, which affect both climate and human health. In pristine environments, oxidation of biogenic volatile organic compounds (VOCs) is a major contributor to NPF. However, the impact of relative humidity (RH) on NPF from these precursors remains poorly understood. Herein, we report on NPF, as inferred from measurements of total particle number density with a particle diameter (dp) > 7 nm, from three VOCs (sabinene, α-terpineol, and myrtenol) subjected to dark ozonolysis. From a series of comparative experiments under humid (60% RH) and dry (~0% RH) conditions and a variety of VOC mixing ratios (ξVOC, parts per billion by volume, ppbv), we show varied behavior in NPF at elevated RH depending on the VOC and ξVOC. In general, RH-dependent enhancement of NPF at an ξVOC between <1 ppbv and 20 ppbv was observed for select VOCs. Our results suggest that gaseous water at particle genesis enhances NPF by promoting the formation of low-volatility organic compound gas-phase products (LVOCs). This is supported by measurements of the rate of NPF for α-pinene-derived SOA, where RH had a greater influence on the initial rate of NPF than did ξVOC and ξO3.

Rapid and non-destructive microbial quality prediction of fresh pork stored under modified atmospheres by using selected-ion flow-tube mass spectrometry and machine learning

Volatile organic compounds (VOCs) indicative of pork microbial spoilage can be quantified rapidly at trace levels using selected-ion flow-tube mass spectrometry (SIFT-MS). Packaging atmosphere is one of the factors influencing VOC production patterns during storage. On this basis, machine learning would help to process complex volatolomic data and predict pork microbial quality efficiently. This study focused on (1) investigating model generalizability based on different nested cross-validation settings, and (2) comparing the predictive power and feature importance of nine algorithms, including Artificial Neural Network (ANN), k-Nearest Neighbors, Support Vector Regression, Decision Tree, Partial Least Squares Regression, and four ensemble learning models. The datasets used contain 37 VOCs' concentrations (input) and total plate counts (TPC, output) of 350 pork samples with different storage times, including 225 pork loin samples stored under three high-O2 and three low-O2 conditions, and 125 commercially packaged products. An appropriate choice of cross-validation strategies resulted in trustworthy and relevant predictions. When trained on all possible selections of two high-O2 and two low-O2 conditions, ANNs produced satisfactory TPC predictions of unseen test scenarios (one high-O2 condition, one low-O2 condition, and the commercial products). ANN-based bagging outperformed other employed models, when TPC exceeded ca. 6 log CFU/g. VOCs including benzaldehyde, 3-methyl-1-butanol, ethanol and methyl mercaptan were identified with high feature importance. This elaborated case study illustrates great prospects of real-time detection techniques and machine learning in meat quality prediction. Further investigations on handling low VOC levels would enhance the model performance and decision making in commercial meat quality control.

The search for sparse data in molecular datasets: Application of active learning to identify extremely low volatile organic compounds

The formation of aerosol particles in the atmosphere is driven by the gas to particle conversion of extremely low volatile organic compounds (ELVOC), organic compounds with a particularly low saturation vapor pressure (pSat). Identifying ELVOCs and their chemical structures is both experimentally and theoretically challenging: Measuring the very low pSat of ELVOCs is extremely difficult, and computing pSat for these often large molecules is computationally costly. Moreover, ELVOCs are underrepresented in available datasets of atmospheric organic species, which reduces the value of statistical models built on such data. We propose an active learning (AL) approach to efficiently identify ELVOCs in a data pool of atmospheric organic species with initially unknown pSat. We assess the performance of our AL approach by comparing it to traditional machine learning regression methods, as well as ELVOC classification based on molecular properties. AL proves to be a highly efficient method for ELVOC identification with limitations on the type of ELVOC it can identify. We also show that traditional machine learning or molecular property-based methods can be adequate tools depending on the available data and desired degree of efficiency.

Desorption lifetimes and activation energies influencing gas–surface interactions and multiphase chemical kinetics

Abstract. Adsorption and desorption of gases on liquid or solid substrates are involved in multiphase processes and heterogeneous chemical reactions. The desorption energy (Edes0), which depends on the intermolecular forces between adsorbate and substrate, determines the residence time of chemical species at interfaces. We show how Edes0 and temperature influence the net uptake or release of gas species, the rates of surface–bulk exchange and surface or bulk reactions, and the equilibration timescales of gas–particle partitioning. Using literature data, we derive a parameterization to estimate Edes0 for a wide range of chemical species based on the molecular mass, polarizability, and oxygen-to-carbon ratio of the desorbing species independent of substrate-specific properties, which is possible because of the dominant role of the desorbing species' properties. Correlations between Edes0 and the enthalpies of vaporization and solvation are rooted in molecular interactions. The relation between Edes0 and desorption kinetics reflects the key role of interfacial exchange in multiphase processes. For small molecules and semi-volatile organics (VOC, IVOC, SVOC), Edes0 values around 10–100 kJ mol−1 correspond to desorption lifetimes around nanoseconds to days at room temperature. Even higher values up to years are obtained at low temperatures and for low volatile organic compounds (LVOC, ELVOC/ULVOC) relevant for secondary organic aerosols (SOA). Implications are discussed for SOA formation, gas–particle partitioning, organic phase changes, and indoor surface chemistry. We expect these insights to advance the mechanistic and kinetic understanding of multiphase processes in atmospheric and environmental physical chemistry, aerosol science, materials science, and chemical engineering.

Influence of Thiol-Functionalized Polysilsesquioxane/Phosphorus Flame-Retardant Blends on the Flammability and Thermal, Mechanical, and Volatile Organic Compound (VOC) Emission Properties of Epoxy Resins.

In this study, thiol-functionalized ladder-like polysesquioxanes end-capped with methyl and phenyl groups were synthesized via a simple sol-gel method and characterized through gel permeation chromatography (GPC), Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), and thermogravimetric analysis (TGA). Additionally, epoxy blends of different formulations were prepared. Their structural, flame-retardant, thermal, and mechanical properties, as well as volatile organic compound (VOC) emissions, were determined using differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), TGA, scanning electron microscopy (SEM), limiting oxygen index (LOI), cone calorimetry, and a VOC analyzer. Compared to epoxy blends with flame retardants containing elemental phosphorus alone, those with flame retardants containing elemental phosphorus combined with silicon and sulfur exhibited superior thermal, flame-retardant, and mechanical properties with low VOC emissions. SEM of the residual char revealed a dense and continuous morphology without holes or cracks. In particular, LOI values for the combustion of methyl and phenyl end-capped polysilsesquioxane mixtures were 32.3 and 33.7, respectively, compared to 28.4% of the LOI value for the blends containing only phosphorus compounds. The silicon-sulfur-phosphorus-containing blends displayed reduced flammability concerning the blends using a flame retardant containing only phosphorus. This reflects the cooperative effects of various flame-retardant moieties.

Mesoporous Si-WO3-supported Pt catalysts with high catalytic performance and excellent water resistance for toluene oxidation

Reducing emissions of volatile organic compounds (VOCs) is an integral part of improving the quality of the atmospheric environment. Catalytic oxidation has become an effective means of treating low and medium concentration VOCs exhausts due to its advantages in terms of removal efficiency, energy saving and environmental protection. Due to the unique inherent properties of supported precious metal catalysts, they show good catalytic efficiency in VOCs emission reduction. In this study, the mesoporous Si-WO3 support was first synthesized by the P123-assisted sol-gel method, and the xPt/Si-WO3 catalysts with the actual loadings (x = 0.19, 0.48, and 0.81 wt%) of Pt nanoparticles (NPs) were then obtained, physicochemical properties of these materials were characterized using a variety of techniques, and their catalytic activities and water resistance for the oxidation of toluene were evaluated. The results showed that Pt NPs with an average particle size of 2.3−3.3 nm were highly dispersed on the mesoporous Si-WO3 support, and the 0.81Pt/Si-WO3 sample exhibited the highest catalytic activity for toluene oxidation at a space velocity of 20,000 mL/(g h) (T50% = 167 °C and T90% = 180 °C; specific reaction rate at 160 °C = 8.54 µmol/(gPt s), turnover frequency (TOFPt) at 160 °C = 1.67 × 10−3 s−1, and apparent activation energy = 45 kJ/mol). The good catalytic performance of 0.81Pt/Si-WO3 was associated with its large surface area, well dispersed Pt NPs, high adsorbed oxygen species concentration, large toluene adsorption capacity, and strong interaction between Pt NPs and mesoporous Si-WO3. The 0.81Pt/Si-WO3 sample possessed excellent water resistance, and the introduction of 5 vol% or 10 vol% water vapor to the reaction system enhanced toluene oxidation since part of water vapor participated in the oxidation of toluene. In addition, the toluene oxidation pathway might obey the sequence of (adsorbed toluene + adsorbed oxygen species) → benzyl alcohol → (benzoic acid and benzaldehyde) → maleic anhydride → (carbon dioxide and water).

Investigation on dynamic VOC production from industrial, high solids content emulsion polymerizations

Volatile Organic Compounds (VOC) pose a serious threat to human health and the environment. Unfortunately, many processes from fine chemistry involve VOCs as reagents, solvents, products or by-products. International standards and market requirements keep asking for lower VOC content in commercial goods, with the final aim of VOC-free products. Accomplishing such a task is a challenge because VOCs, due to their high vapour pressure, are hard to remove with traditional industrial methods, such as vacuum stripping or absorption. For this reason, it is important to know and understand how VOCs evolve throughout a chemical reaction. In this field, adhesives, which are usually developed exploiting polymerizations, represent an interesting subject, due to the complexity of their industrial synthesis: VOCs appear as reagents (monomers), conversion enhancers (post-polymerization), and by-products (hydrolysis and small chains). In this work, a study on the evolution and content of VOCs of an industrial recipe involving emulsion polymerizations is carried out. The industrial recipe is characterized by high solids content (about 70% w/w) and is mainly composed of 2-ethylhexyl acrylate (up to 50% w/w), anionic and nonionic surfactants. The evolution of the main VOCs found under different working conditions is discussed. The main VOCs found are acetaldehyde, acetone, t-butanol, vinyl acetate, butanol, methyl-methacrylate, butyl acrylate, 2-ethyl-exyl-alcohol, 2-ethyl-exyl-acetate and 2-ethyl-exyl-acrylate.

In-situ growth of MIL-101(Fe) onto PET base for high-efficiency adsorption of low concentrations benzene series VOCs and easy recycling

With the proliferation of vehicles in households, people are spending more and more time in their cars, so it is important to ensure the air quality and safety of the car. In this research, environmentally friendly, green PET@PDA@MIL-101(Fe) (PPM) was prepared by in-situ solvothermal growth and acid etching methods, which was categorized by SEM, FTIR, XRD, XPS, and BET. PPM was used to adsorb benzene, toluene, and m-xylene at low concentrations. The maximum amount of adsorption of PET@PDA@MIL-101(Fe) (PPM) for benzene, toluene, and m-xylene was 68.72 mg/g, 91.63 mg/g, and 78.47 mg/g respectively. The adsorption process of PPM is well fitted by the pseudo-first-order kinetic model and Langmuir isothermal adsorption model. Furthermore, PPM exhibited excellent toluene removal performance in simulated vehicles and excellent cycling capability in adsorption-desorption experiments. As a result, PPM can be used to treat and manage toluene volatile organic compounds (VOCs) at low concentrations.

Reactive aldehyde chemistry explains the missing source of hydroxyl radicals

Hydroxyl radicals (OH) determine the tropospheric self-cleansing capacity, thus regulating air quality and climate. However, the state-of-the-art mechanisms still underestimate OH at low nitrogen oxide and high volatile organic compound regimes even considering the latest isoprene chemistry. Here we propose that the reactive aldehyde chemistry, especially the autoxidation of carbonyl organic peroxy radicals (R(CO)O2) derived from higher aldehydes, is a noteworthy OH regeneration mechanism that overwhelms the contribution of the isoprene autoxidation, the latter has been proved to largely contribute to the missing OH source under high isoprene condition. As diagnosed by the quantum chemical calculations, the R(CO)O2 radicals undergo fast H-migration to produce unsaturated hydroperoxyl-carbonyls that generate OH through rapid photolysis. This chemistry could explain almost all unknown OH sources in areas rich in both natural and anthropogenic emissions in the warm seasons, and may increasingly impact the global self-cleansing capacity in a future low nitrogen oxide society under carbon neutrality scenarios.

Innovative vs classical methods for drying heterotrophic Chlorella vulgaris: Impact on protein quality and sensory properties

Drying is a necessary step in the microalgae production chain to reduce microbial load and oxidative degradation of the end product. Depending on the differences in applied temperature and treatment time, the process of drying can have a substantial impact on protein quality and aroma, important characteristics determining the incorporation potential in food products. In this study, we compared the drying of heterotrophic Chorella vulgaris with both innovative (agitated thin film drying (ATFD), pulse combustion drying (PCD) and solar drying (SolD)) and commonly used drying techniques (spray drying (SprD) and freeze drying (FD)). To evaluate the impact on protein quality, we evaluated techno-functional properties, in vitro digestibility (INFOGEST) as well as protein denaturation using differential scanning calorimetry (DSC). A sensory analysis was performed by a trained expert panel, combined with headspace solid-phase microextraction (HS-SPME) - gas chromatography-mass spectrometry (GC–MS) to determine volatile organic compounds (VOCs). ATFD was found to increase techno-functional properties such as gelling, water holding and solubility as well as in vitro protein digestibility. These observations could be related to induced cell disruption and protein denaturation by ATFD. Sensory analysis indicated an increased earthy off-flavor after ATFD. Interestingly, the high-temperature PCD led to an increase in cacao odor while low-temperature FD resulted in lower flavor, odors and VOCs. These results demonstrate that protein quality and sensorial properties of C. vulgaris can be steered through the type of drying, which could help in the selection of application-specific drying methods. Overall, this work could promote the incorporation of microalgal single cell proteins in different innovative food products.

Differences in Secondary Organic Aerosol Formation from α-Pinene Photooxidation in a Chamber with Purified Air and Ambient Air as Matrices: Preliminary Results

α-Pinene is a biogenic volatile organic compound (BVOC) that significantly contributes to secondary organic aerosols (SOA) in the atmosphere due to its high emission rate, reactivity, and SOA yield. However, the SOA yield measured in chamber studies from α-pinene photooxidation is limited in a purified air matrix. Assessing SOA formation from α-pinene photooxidation in real urban ambient air based on studies conducted in purified air matrices may be subject to uncertainties. In this study, α-pinene photooxidation and SOA yield were investigated in a smog chamber in the presence of NO and SO2 under purified air and ambient air matrices. With the accumulation of ozone (O3) during the photooxidation, an increasing part of α-pinene was consumed by O3 and finally nearly half of the α-pinene was oxidized by O3, facilitating the production of highly oxidized organic molecules and thereby SOA formation. Although the ambient air we introduced as matrix air was largely clean, with initial organic aerosol mass concentrations of ~1.5 μg m−3, the α-pinene SOA yield in the ambient air matrix was 42.3 ± 5.3%, still higher than that of 32.4 ± 0.4% in the purified air matrix. The chemical characterization of SOA by the high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) revealed that CxHy accounted for 53.7 ± 1.1% of the total signal in the ambient air matrix experiments, higher than 48.1 ± 0.3% in the purified air, while CxHyO and CxHyO>1 together constituted 45.0 ± 0.9% in the ambient air matrix, lower than 50.1 ± 1.0% in the purified air. The O:C ratio in the ambient air matrix experiments was 0.41 ± 0.01, lower than 0.46 ± 0.01 in the purified air. The higher SOA yield of α-pinene in the ambient air matrix compared to that in the purified air matrix was partly due to the presence of initial aerosols in the ambient air, which facilitated the low volatile organic compounds produced from photochemical oxidation to enter the aerosol phase through gas-particle partitioning. The in-situ aerosol acidity calculated by the ISORROPIA-II model in the ambient air matrix experiments was approximately six times higher than that in purified air, and the higher SOA yield in the ambient air matrix experiments might also be attributed to acid-catalyzed SOA formation.

Balancing the "magic triangle" performance of tire rubber nanocomposites with novel low VOC silane coupling agents

Nowadays, coupling agents are still the core technology of the “green tire” industry, which not only effectively weaken the silica network but also enhance the interface interaction between silica and rubber matrix. However, the reaction between the traditional silane coupling agents and the silanol groups on silica surface generates a large amount of volatile organic compounds (VOCs), which can affect the performance of the rubber composites and pollute the environment. In this paper, a series of novel coupling agents with low VOC emission were synthesized by reacting fatty alcohol polyoxyethylene ethers of different polyether lengths (AEOX) with bis-[γ-(triethoxysilyl) propyl]-tetrasulfide TESPT (Si69). The structure of the novel coupling agent was characterized using FT-IR and 1H NMR. Meanwhile, it has been proven through FT-IR, XPS, TGA, and GCMS that the novel coupling agent can react with silica and reduce VOC emissions. Then the novel coupling agent was added into the silica/natural rubber (NR) nanocomposite. The test results of rubber composites showed that the addition of novel coupling agent can significantly enhance the dispersion of silica in the rubber matrix and effectively balance the "magic triangle" performance of tire. As a result, the rolling resistance of the silica/NR composites is reduced by 15.8 %, the wet skid resistance is improved by 14.2 %, and the abrasion resistance is improved by 20.3 %.

Detection of medically relevant volatile organic compounds with graphene field-effect transistors and separated by low-frequency spectral and time signatures.

Exhaled human breath contains a mixture of gases including nitrogen, oxygen, carbon dioxide, water vapour and low molecular weight volatile organic compounds (VOCs). Different VOCs detected in human breath condensate have been recently related to several metabolic processes occurring inside body tissues in the pathological state, as candidate biomarkers for monitoring conditions such as lung injury, airway inflammation, immunity dysfunction, infection, and cancer. Current techniques for detecting these compounds include several types of mass spectroscopy, which are highly costly, time-consuming and dependent on trained personnel for sample analysis. The need for fast and label-free biosensors is paving the way towards the design of novel and portable electronic devices for point-of-care diagnosis with VOCs such as E-noses, and based on the measurement of signal signatures derived from their chemical composition. In this paper, we propose a device for VOC detection that was tested inside a controlled gas flow setup, resorting to graphene field-effect transistors (GFETs). Electrical measurements from graphene directly exposed to nitrogen plus VOC vapours involved cyclic measurements for the variation of graphene's resistance and low-frequency spectral noise in order to obtain distinctive signatures of the tested compounds in the time and frequency domains related, respectively, to Gutmann's theory for donor-acceptor chemical species and spectral sub-band analysis.

Surface engineering of ternary mixed transition metal oxides for highly efficient catalytic oxidation of low concentration VOCs

With the widespread application of waterborne painting process, effective removal technologies for low concentration volatile organic compounds (VOCs) is a major concern of the painting industries due to the low mass transfer efficiency. This work presents a unique approach for the molecular-level preparation of precious-metal-free mixed aliovalent-substituted, CeCuOx binary oxide and NiO-modified yNi/CeCuOx ternary mixed metal oxide catalysts. In addition, the excellent catalytic selectivity (no catalytic activity decreases under 5.0 vol% water vapor) of the catalysts was successfully achieved by microstructures optimization and grafting octadecyltrichlorosilane (OTS). Its catalytic activity in the oxidation of toluene at low concentrations (50 ppm) was studied. The 3Ni/CeCuOx sample exhibits the best performance, which achieve 90 % catalytic oxidation of toluene at 197 °C without using noble metals. This results from that the ternary doping and the growth of NiO increases the specific surface area, active lattice oxygen species, activates molecular oxygen species, and provides more catalytic sites, which improve the adsorption and catalysis of toluene. Furthermore, the catalytic stability of the catalysts is also significantly improved by the addition of the hydrophobic coating. Therefore, the unique catalysts have great potential in practical applications for low concentration VOCs removal of painting industries.