Low Volatile Organic Compounds Research Articles

Dual spatial region flexible chlorine based ionic hypercrosslinked polymer synergistically adsorb formaldehyde and carbon dioxide

Efficient adsorption and purification of low concentration volatile organic compounds (VOCs) and carbon dioxide (CO2) mixture in high-humidity environments remain a daunting challenge for researchers. In this study, a dual spatial region synergistic adsorption strategy was proposed to achieve synchronous and efficient capture of formaldehyde and CO2 on flexible chlorine (Cl) based ionic hypercross-linked polymer (Cl-IHCP). Through the ordered self-assembly of ionic monomers, the array-distributed free Cl, terminal Cl, and pyrrole nitrogen (N) sites were integrated into the skeletal network of Cl-IHCP and formed ultra-microporous environment with two different adsorption regions. Different adsorption regions exhibited varying adsorption affinities for formaldehyde and CO2 molecules on three sites, thereby weakening their competitive adsorption and achieving high adsorption for both. Besides, the strong binding force of formaldehyde and CO2 molecules in different regions makes the skeleton-responsive swelling of Cl-IHCP, and created new adsorption microenvironments for the other adsorbate. This manner considerably enhanced the adsorption capacity of Cl-IHCP for formaldehyde and CO2 in mixed-component, increasing by approximately 45% and 70% respectively compared to single component formaldehyde and CO2. These fascinating properties enabled Cl-IHCP to synergistically adsorb formaldehyde and CO2 mixtures in high humidity environments. This study innovatively proposed a simple and cost-effective strategy for removing VOCs and CO2 under high humidity, providing a feasible solution for green air purification technology.

Ozone source attribution in polluted European areas during summer 2017 as simulated with MECO(n)

Abstract. Emissions of land transport and anthropogenic non-traffic emissions (e.g. industry, households and power generation) are significant sources of nitrogen oxides, carbon monoxide and volatile organic compounds (VOCs). These emissions are important precursors of tropospheric ozone and affect air quality. The contribution of the emission sectors to ozone cannot be measured directly but can only be calculated using sophisticated atmospheric chemistry models. For this study we apply the MECO(n) model system (MESSy-fied ECHAM and COSMO models nested n times) equipped with a source attribution method to investigate the contribution of various sources to ground-level ozone in Europe. Compared to previous source apportionment studies for Europe, for the first time we apply a combined NOx–VOC tagging implemented in an online nested global–regional chemistry–climate model to achieve a finer resolution over central Europe (12 km) but concurrently incorporating the effect of long-range transport. We distinguish 10 different source sectors and 4 geographical source regions, analysing especially the contribution from the land transport sector. Our analysis focuses on large ozone events during summer in four different regions, two major polluted regions (Po Valley and Benelux) and two more remote regions (Iberian Peninsula and Ireland). The analysis concentrates on results for summer 2017, during which measurement campaign EMeRGe took place. Measurement data from this campaign are used for model evaluation. Our analysis shows that European land transport emissions contribute largely (42 % and 44 %, respectively) to ground-level NOy mixing ratios over Benelux and the Po Valley. Due to the overall lower ozone production efficiency over Benelux compared to the Po Valley, however, the contributions to ground-level ozone are larger in the Po Valley (12 %) compared to Benelux (8 %). In line with previous publications using different source apportionment methods, our results underline the large importance of long-range transport of ozone, especially from North America (Benelux, Ireland), but also from Africa (Iberian Peninsula), and provide additional information about the sectoral contribution not available before. Our analysis shows that the contributions of European emissions from land transport and anthropogenic non-traffic sectors strongly increase with increasing values of MDA8 (daily maximum 8 h average) ozone over the Po Valley and in the Benelux region. Accordingly, these two sectors drive large MDA8 values in these regions. Inter-comparisons of results for 2018 and with a coarser model resolution (50 instead of 12 km) show that these results are robust with respect to inter-annual variability and model resolution. Comparing our results with results from other source attribution methods we find that the contributions to ozone from individual sectors, which have large NOx but rather low VOC emissions, are estimated to be lower, if their emissions of NOx and VOCs are regarded concurrently.

Assessment of CPME as Sustainable Low VOC Alternative to Hexane: Optimization of Extraction Efficiency and Bioactive Compound Yield from Fenugreek Seed Oil Using Computational and Experimental Methods.

This study investigates the performance of cyclopentyl methyl ether (CPME) in the extraction of fenugreek seed oil, aiming to replace the conventionally used hexane. The efficiency of this alternative solvent was evaluated first through in silico methods (based on Hansen Solubility Parameters (HSPs) and Conductor-like Screening Model for Real Solvent (COSMO-RS) simulations), followed by experimental studies. Solubility computational predictions analysis revealed that CPME exhibits superior solvation power compared to hexane. Experimentally, CPME demonstrated a significantly higher oil yield (7.23%) compared to hexane (4.25%) and a better retention of beneficial unsaturated fatty acids than hexane. Additionally, the physicochemical properties of oils extracted with CPME showed enhanced oxidative stability, sterol, tocopherol, and phenolic contents, leading to superior antioxidant and antibacterial activities. Importantly, CPME's low volatile organic compound (VOC) emissions further establish it as a more sustainable and environmentally friendly alternative to hexane, aligning with contemporary goals of reducing harmful emissions in extraction processes. Thus, this paper highlights the functional advantages of CPME, focusing on its efficiency, selectivity, and enhanced retention of bioactive compounds, positioning it as a superior extraction solvent for fenugreek seed oil compared to hexane.

Analysis of the source of abnormal odor components in medium-density fiberboard (MDF)

ABSTRACT To investigate the cause of the abnormal odor emitted by medium-density fiberboard (MDF) when formaldehyde-free diphenylmethane diisocyanate (MDI) adhesive is used, a comparative study of three types of MDF was conducted: MDF made with masson pine wood and MDI adhesive (PW-MDI), MDF made with masson pine wood and urea-formaldehyde resin (PW-UF), and MDF made with mixed hardwoods and MDI adhesive (HW-MDI). Volatile organic compounds (VOCs) emitted were collected and analyzed using gas chromatography-mass spectrometry (GC-MS), identifying 86 VOCs. Results reveal that the PW-MDI specimen contains a higher concentration of acid substances, comprising 56% of the specimen. These acid mainly octanoic and nonanoic acids, were the primary contributors to its abnormal odor. In contrast, the PW-UF and HW-MDI specimens were predominantly composed of alcohol substances, accounting for 33% and 36% respectively. Gas chromatography-ion mobility spectrometry (GC-IMS) was used to obtain VOC fingerprints. Analysis revealed that acids and aldehydes are the primary contributors to the relative odor activity value (ROAV). These compounds are known for their abnormal odor that impact the indoor air quality. This research successfully identified the source of the abnormal odor and provided technical support for the effective control of low abnormal odor VOC emissions from MDF.

Enhanced daytime secondary aerosol formation driven by gas–particle partitioning in downwind urban plumes

Abstract. Anthropogenic emissions from city clusters can significantly enhance secondary organic aerosol (SOA) formation in the downwind regions, while the mechanism is poorly understood. To investigate the effect of pollutants within urban plumes on organic aerosol (OA) evolution, a field campaign was conducted at a downwind site of the Pearl River Delta region of China in the fall of 2019. A time-of-flight chemical ionization mass spectrometer coupled with the Filter Inlet for Gases and Aerosols (FIGAERO–CIMS) was used to probe the gas- and particle-phase molecular composition and thermograms of organic compounds. For air masses influenced by urban pollution, strong daytime SOA formation through gas–particle partitioning was observed, resulting in higher OA volatility. The obvious SOA enhancement was mainly attributed to the gas–particle partitioning of high-volatility (semi-volatile organic compounds + intermediate volatility organic compounds + volatile organic compounds, C∗>0.3 µg m−3) organic vapors. Using the equilibrium equation could underestimate the contribution of high-volatility organic vapors, since the volatility of these species in the particle phase was lower than that in the gas phase. We speculated that the elevated NOx concentration could suppress the formation of highly oxidized products, resulting in a smooth increase of low-volatility (extremely low volatility organic compounds + low volatility organic compounds, C∗≤0.3 µg m−3) organic vapors. Evidence has shown that urban pollutants (NOx and VOCs) could enhance the oxidizing capacity, while the elevated VOCs were mainly responsible for promoting daytime SOA formation by increasing the RO2 production rate. Our results highlight the important role of urban anthropogenic pollutants in SOA control in the suburban region.

Nocturnal atmospheric synergistic oxidation reduces the formation of low-volatility organic compounds from biogenic emissions

Abstract. Volatile organic compounds (VOCs) are often subject to synergistic oxidation by different oxidants in the atmosphere. However, the exact synergistic-oxidation mechanism of atmospheric VOCs and its role in particle formation remain poorly understood. In particular, the reaction kinetics of the key reactive intermediates, organic peroxy radicals (RO2), during synergistic oxidation is rarely studied. Here, we conducted a combined experimental and kinetic modeling study of the nocturnal synergistic oxidation of α-pinene (the most abundant monoterpene) by O3 and NO3 radicals as well as its influences on the formation of highly oxygenated organic molecules (HOMs) and particles. We find that in the synergistic O3 + NO3 regime, where OH radicals are abundantly formed via decomposition of ozonolysis-derived Criegee intermediates, the production of CxHyOz HOMs is substantially suppressed compared to that in the O3-only regime, mainly because of the depletion of α-pinene RO2 derived from ozonolysis and OH oxidation by those arising from NO3 oxidation via cross reactions. Measurement–model comparisons further reveal that the cross-reaction rate constants of NO3-derived RO2 with O3-derived RO2 are on average 10–100 times larger than those of NO3-derived RO2 with OH-derived RO2. Despite a strong production of organic nitrates in the synergistic-oxidation regime, the substantial decrease in CxHyOz HOM formation leads to a significant reduction in ultralow- and extremely low-volatility organic compounds, which significantly inhibits the formation of new particles. This work provides valuable mechanistic and quantitative insights into the nocturnal synergistic-oxidation chemistry of biogenic emissions and will help to better understand the formation of low-volatility organic compounds and particles in the atmosphere.

Pinewood VOC emissions protect from oxazolone-induced inflammation and dysbiosis in a mouse model of atopic dermatitis

Pinewood, increasingly used in construction and interior fittings, emits high amounts of volatile organic compounds (VOCs), which tend to accumulate in indoor air. Whether indoor VOCs affect the development of atopic dermatitis (AD) is a matter of debate. We aimed to evaluate the effects of pinewood VOCs on the development of AD-like inflammatory phenotype and linked microbiome alterations, both hallmarks of AD. An oxazolone-induced mouse model of AD was exposed to three different VOC concentrations emitted by pinewood plates throughout the experiment. The disease course and associated immunological and microbiological changes were evaluated. To validate and translate our results to humans, human keratinocytes were exposed to a synthetic pinewood VOCs mixture in an AD environment. Pinewood emitted mainly terpenes, which at a total concentration of 5 mg/m3 significantly improved oxazolone-induced key AD parameters, such as serum total IgE, transepidermal water loss, barrier gene alteration, inflammation, and dysbiosis. Notably, exposure to pinewood VOCs restored the loss of microbial richness and inhibit Staphylococci expansion characteristic of the oxazolone-induced mouse AD model. Most beneficial effects of pinewood VOCs were dose-dependent. In fact, lower (<3 mg/m3) or higher (>10 mg/m3) pinewood VOC levels maintained only limited beneficial effects, such as preserving the microbiome richness or impeding Staphylococci expansion, respectively. In the human in-vitro model, exposure of keratinocytes grown in an AD environment to a pinewood VOCs mixture reduced the release of inflammatory markers. In conclusion, our results indicate that airborne phytochemicals emitted from pinewood have beneficial effects on an AD-like phenotype and associated dysbiosis. These investigations highlight the effects of terpenes as environmental compounds in the prevention and/or control of atopic skin disease.

Comparative Assessment of Insulation Materials for Improving Indoor Air Quality in Building Retrofit

This paper evaluates the impacts of different insulation materials on Indoor Air Quality (IAQ) and occupant health with a focus on the Volatile Organic Compound (VOC) emissions. The main aim is to identify options that minimize exposure rates while improving IAQ and energy in retrofitted buildings. A comprehensive literature review was conducted synthesizing scholarly articles, guidelines from international organizations, and information on pollutants, IAQ standards, and retrofit strategies. The findings show high emission rates for some insulation materials that could negatively affect health. Hemp insulation in contrast was identified as a promising solution exhibiting low VOC emissions compared to other insulation materials. As sustainable construction practices advance, hemp insulation emerges as a viable retrofit strategy for social housing by synergistically addressing performance gaps related to energy conservation, air quality, and thermal comfort. The synthesis of evidence from this paper suggests that, from environmental and public health perspectives, certain insulation materials are preferable for improving IAQ and reducing the risk of exposure to indoor air pollutants in retrofitted buildings.

Differences in development of volatiles and bitter peptides between pre- and post-hydrolysed lactose-free UHT milk during storage

Lactose-hydrolysed UHT milk (LHM) has a limited shelf life, especially due to early browning and off-flavour development. This study aimed to directly compare the development in colour, volatile and bitter peptide formation in pre- (lactase addition prior to UHT treatment) and post-hydrolysed (lactase addition after UHT treatment) milk using three different lactases and stored at 25 or 35 °C for up to one year. Pre-hydrolysed milk exhibited more pronounced browning than post-hydrolysed milk. Furthermore, level of Maillard related compounds like acetic acid and furfural were higher in pre-hydrolysed milk compared to post-hydrolysed milk, whereas post-hydrolysed milk was higher in Strecker aldehyde related volatile organic compounds (VOCs). After storage, level of bitter peptides was higher in post-hydrolysed milk using more impure lactases. Generally, lower VOC concentrations and bitter peptides were observed for LHM produced by more pure lactases suggesting higher purity lactases can aid in the development of ambient long-life LHM.

Natural Marine Precursors Boost Continental New Particle Formation and Production of Cloud Condensation Nuclei.

Marine dimethyl sulfide (DMS) emissions are the dominant source of natural sulfur in the atmosphere. DMS oxidizes to produce low-volatility acids that potentially nucleate to form particles that may grow into climatically important cloud condensation nuclei (CCN). In this work, we utilize the chemistry transport model ADCHEM to demonstrate that DMS emissions are likely to contribute to the majority of CCN during the biological active period (May-August) at three different forest stations in the Nordic countries. DMS increases CCN concentrations by forming nucleation and Aitken mode particles over the ocean and land, which eventually grow into the accumulation mode by condensation of low-volatility organic compounds from continental vegetation. Our findings provide a new understanding of the exchange of marine precursors between the ocean and land, highlighting their influence as one of the dominant sources of CCN particles over the boreal forest.

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 (&lt; 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 &gt;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) &gt; 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 &lt;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.