Quantitative analysis and spatial and temporal distribution of volatile organic compounds in atmospheric air by utilizing drone with miniaturized samplers

Assessment of physicochemical properties of sorbent materials in passive and active sampling systems towards gaseous nitrogen-containing compounds

The adsorption and desorption behavior of volatile nitrogen-containing compounds in vapor phase by solid-phase microextraction Arrow (SPME-Arrow) and in-tube extraction (ITEX) sampling systems, were investigated experimentally using gas chromatography-mass spectrometry. Three different SPME-Arrow coating materials, DVB/PDMS, MCM-41, and MCM-41-TP and two ITEX adsorbents, TENAX-GR and MCM-41-TP were compared to clarify the selectivity of the sorbents towards nitrogen-containing compounds. In addition, saturated vapor pressures for these compounds were estimated, both experimentally and theoretically. In this study, the adsorption of nitrogen-containing compounds on various adsorbents followed the Elovich model well, while a pseudo-first-order kinetics model best described the desorption kinetics. Pore volume and pore sizes of the coating sorbents were essential parameters for the determination of the adsorption performance for the SPME-Arrow sampling system. MCM-41-TP coating with the smallest pore size gave the slowest adsorption rate compared to that of DVB/PDMS and MCM-41 in the SPME-Arrow sampling system. Both adsorbent and adsorbate properties, such as hydrophobicity and basicity, affected the adsorption and desorption kinetics in SPME-Arrow system. The adsorption and desorption rates of studied C₆H₁₅N isomers in the MCM-41 and MCM-41-TP sorbent materials of SPME-Arrow system were higher for dipropylamine and triethylamine (branched amines) than for hexylamine (linear chain amines). DVB/PDMS-SPME-Arrow gave fast adsorption rates for the aromatic-ringed pyridine and o-toluidine. All studied nitrogen-containing compounds demonstrated high desorption rates with DVB/PDMS-SPME-Arrow. Chemisorption and physisorption were the sorption mechanisms in MCM-41- and MCM-41-TP- SPME-Arrow, but additional experiments are needed to confirm this. An active sampling technique ITEX gave comparable adsorption and desorption rates on the selective MCM-41-TP and universal TENAX-GR sorbent materials for all the compounds studied. Vapor pressures of nitrogen-containing compounds were experimentally estimated by using retention index approach and these values were compared with the theoretical ones, calculated using the COnductor-like Screening MOdel for Real Solvent (COSMO-RS) model. Both values agreed well with those found in the literature proving that these methods can be successfully used in predicting VOC's vapor pressures, e.g. for the formation of secondary organic aerosols.

Evaluation of VOCs from fungal strains, building insulation materials and indoor air by solid phase microextraction arrow, thermal desorption-gas chromatography-mass spectrometry and machine learning approaches

Solid phase microextraction Arrow and thermal desorption-gas chromatography-mass spectrometry allowed the collection and evaluation of volatile organic compounds (VOCs) emitted by fungal cultures from building insulation materials and in indoor air. Principal component analysis, linear discriminant analysis and supported vector machine were used for visualization and statistical assessment of differences between samples. In addition, a screening tool based on the soft independent modelling of class analogies (SIMCA) was developed for identification of fungal contamination of indoor air. Ten different fungal strains, incubated under ambient and microaerophilic conditions, were analyzed for time period ranging from 5 to 29 days after inoculation resulting in a total of 140 samples. In addition, the effect of additives on the fungal growing media was studied. The total number of compounds and concentration values were used for the evaluation of the results. Clear differences were observed for VOC profiles emitted by different fungal strains by exploiting long chain alcohols (3-octanol, 1-hexanol and 2-octen-1-ol) and sesquiterpenes (farnesene, cuprene). The analysis of glass-wool and cellulose based building insulation materials (3 samples) gave clear differences, mainly for oxygenated compounds (ethyl acetate and hexanal) and benzenoids (benzaldehyde). Moreover, the comparison of indoor air and insulation materials collected from a house with fungal indoor air problems indicated that 42% of the VOCs were found in both samples. The analysis of 52 indoor air samples demonstrated clear differences in their VOC profiles, especially for hydrocarbons, and between control (44 samples) and indoor air problem houses (8 samples). Finally, the SIMCA model enabled to recognize differences between control and fungi contaminated houses with a prediction capacity over 84%.

Onsite Identification and Spatial Distribution of Air Pollutants Using a Drone-Based Solid-Phase Microextraction Array Coupled with Portable Gas Chromatography-Mass Spectrometry via Continuous-Airflow Sampling

Hazardous air pollutants can be unintentionally and intentionally released in many cases, such as industrial emissions, accidental events, and pesticide application. Under such events, the onsite operation is highly dependent on the molecular composition and spatial distribution of air pollutants in ambient air. However, it is usually difficult for people to reach hazardous and upper sites rapidly. In this work, we designed a new drone-based microextraction sampler array in which a solid-phase microextraction (SPME) fiber was mounted on drones for remote-control sampling at different spaces and was then coupled with a portable gas chromatography-mass spectrometry (PGC-MS) approach for quickly identifying hazardous air pollutants and their spatial distribution in ambient air within minutes. Acceptable analytical performances, including good sensitivity (detection limit at nanogram per liter level), reproducibility (relative standard deviation < 20%, n = 6), analytical speed (single sample within minutes), and excellent linear dynamic response (3 orders of magnitude) were obtained for direct measurement of air samples. The drone-SPME sampling mechanism of air pollutants involving an airflow adsorptive microextraction process was proposed. Overall, this drone-SPME sampling array can access hard-to-reach and dangerous environmental sites and provide air pollution distribution in different spaces, showing versatile potential applications in environmental analysis.

Emission characteristics and ozone formation potentials of VOCs from ultra-low-emission waterborne automotive painting

Automotive painting plants are important emission sources of volatile organic compounds (VOCs) that contribute significantly to ground-level ozone (O₃) pollution in atmosphere. Here, we investigated process-specified emission characteristics of VOCs, without or with advanced adsorption/incineration after-treatments, from an ultra-low-emission (ULE) waterborne painting process in a modernized automotive plant. Overall, more than 80 VOCs species were identified and sorted into seven main categories. In the stack emissions without after-treatments, oxygenated VOCs (alcohols, esters, ketones, ethers, etc.) were found to be the most abundant components (48.8%), followed by aromatic (30.9%), alkanes (16.9%) and alkenes (1.2%). Among the different VOCs species discharged to atmosphere (i.e. after adsorption/incineration after-treatments), aromatics demonstrated a predominant contribution (by 60.6%) to the total O₃ formation potentials (OFPs) despite their relatively lower abundance. Trimethylbenzene was identified to have the highest OFPs, and thus should be controlled with peculiar priority. As compared to traditional organic solvent-based painting process, the ULE waterborne process implemented in the target plant allows to reduce the OFPs from 10.7 mg m^-3 to 3 mg m^-3 (or by 72%). Additional monitoring by unmanned aerial vehicle (over more than 3000 sampling points in the plant) confirmed that the instantaneous concentrations of fugitive VOCs were well below the regulated limit value during typical working and non-working days. These findings may provide important reference for reduction of VOCs emissions and O₃ pollution from automotive painting processes.

Aerial drone furnished with miniaturized versatile air sampling systems for selective collection of nitrogen containing compounds in boreal forest

A wide variety of nitrogen-containing compounds are present in the environment, which contributes to air pollution and new particle formation, for example. These eventually affect human health and the climate. With all this consideration, there is a growing interest in the development of efficient and reliable methods to determine these compounds in the atmosphere. In this study, titanium hydrogen phosphate-modified Mobil Composition of Matter No. 41 was used as sorbent material for in-tube extraction (ITEX) sampling system, to selectively collect nitrogen-containing compounds from natural air samples. The effect of sampling accessories, based on adsorbent coatings (with Tenax-GR as an adsorbent material) and polytetrafluoroethylene filters, was studied to improve the selectivity of the sampling system and to remove particles. Aerial drone with miniaturized air sampling system was employed for the reliable collection of nitrogen-containing compounds in both gas phase and aerosol particles. A total of 170 air samples were collected in July 2020 at the SMEAR II station, Finland to evaluate nitrogen-containing compounds diurnal patterns and vertical profiles (0.25, 5, 50, and 150 m). More than twenty nitrogen-containing compounds, such as aliphatic amines, imines, imidazoles, and pyridines, were identified, quantified or semi-quantified. The average concentrations of detected aliphatic amines at the altitude of 50 m were up to 40.4 ng m^-3 (dimethylamine) in gas phase and 128 ng m^-3 (ethylamine) in aerosol particles. Among nitrogen-containing compounds detected, pyridine gave the highest average concentration of 746 ng m^-3 in gas phase and 644 ng m^-3 in particle phase.