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A known strategy for mitigating the indoor transmission of airborne pathogens, including the SARS-CoV-2 virus, is irradiation by germicidal UV light (GUV). A particularly promising approach is 222 nm light from KrCl excimer lamps (GUV222); this inactivates airborne pathogens, but is thought to be far less harmful to human skin and eyes than longer-wavelength GUV (e.g., 254 nm). However, the potential for GUV222 to affect the composition of indoor air has received little experimental study. Here, we conduct a series of controlled laboratory experiments, carried out in a 150 L Teflon chamber, to examine formation of oxidants and other secondary species by GUV222. We show that GUV222 generates ozone (O3) and hydroxyl radicals (OH), both of which can react with volatile organic compounds to form oxidized volatile organic compounds and secondary organic aerosol particles. Results are consistent with predictions from a simple box model based on known photochemistry. We use this experimentally-validated model to simulate the effect of GUV222 irradiation under more realistic indoor air scenarios, spanning a range of light and ventilation conditions. We demonstrate that under some conditions, GUV222 irradiation can lead to levels of O3, OH, and secondary organic products that are substantially elevated relative to normal indoor conditions, especially when ventilation is low and GUV222 intensity is high. Thus, GUV222 should be used at the lowest intensities possible and in concert with ventilation, decreasing levels of airborne pathogens while mitigating the formation of air pollutants in indoor environments.

Long-term measurements of the composition and mass concentration of particulate matter (PM) are essential for source apportionment, epidemiological studies, and air quality trends. Over the past ten years, the Aerosol Chemical Speciation Monitor (ACSM) has been widely used for long-term, in situ, high time resolution measurements. However, to date there are limited measurements with these instruments in Africa and South/Southeast Asia. The measurements that have been made in these regions suggest the presence of varied and complex sources. Current ACSMs have unit mass resolution (UMR), which impacts detection limits and separation and identification of ions, limiting source apportionment. Here, we present a new instrument, the Time-of-Flight ACSM with eXtended resolution (TOF-ACSM-X) with updated analysis software (Tofware) to allow for high-resolution peak fitting. The TOF-ACSM-X has a mass resolution of ~2000 m/Δm, which is approximately an order of magnitude higher than the other versions of the ACSM. This enhanced resolution improves ammonium detection limits by approximately 2-orders of magnitude, from ~0.200 μg m-3 to ~0.008 μg m-3 (TOF-ACSM versus TOF-ACSM-X, respectively), for 15-minute integration times. Intercomparisons of the TOF-ACSM-X with other measurements show improved performance in source apportionment and elemental analysis.

Weighted positive matrix factorization (PMF) has been used by scientists to find small sets of underlying factors in environmental data. However, as the size of the data has grown, increasing computational costs have made it impractical to use traditional methods for this factorization. In this paper, we present a new weighting method to dramatically decrease computational costs for these traditional algorithms. We then apply this weighting method with the Randomized Hierarchical Alternating Least Squares (RHALS) algorithm to a large environmental dataset, where we show that interpretable factors can be reproduced using these methods. We show this algorithm results in a computational speedup of 38, 67, and 634 compared to the Multiplicative Update (MU), deterministic Hierarchical Alternating Least Squares (HALS), and non-negative Alternating Least Squares (ALS) algorithms, respectively. We also investigate rotational ambiguity in the solution, and present a simple “pulling” method to rotate a set of factors. This method is shown to find alternative solutions, and in some cases, lower the weighted residual error of the algorithm.

The atmospheric oxidation of dimethyl sulfide (DMS) represents a major natural source of atmospheric sulfate aerosols. However, there remain large uncertainties in our understanding of the underlying chemistry that governs the product distribution and sulfate yield from DMS oxidation. Here, chamber experiments were conducted to simulate gas-phase OH-initiated oxidation of DMS under a range of reaction conditions. Most importantly, the bimolecular lifetime (τbi) of the peroxy radical CH3SCH2OO was varied over several orders of magnitude, enabling the examination of the role of peroxy radical isomerization reactions on product formation. An array of analytical instruments was used to measure nearly all sulfur-containing species in the reaction mixture, and results were compared with a near-explicit chemical mechanism. When relative humidity was low, “sulfur closure” was achieved under both high-NO (τbi<0.1 s) and low-NO (τbi>10 s) conditions, though product distributions were substantially different in the two cases. Under high-NO conditions, approximately half the product sulfur was in the particle phase, as methane sulfonic acid (MSA) and sulfate, with most of the remainder as SO2 (which in the atmosphere would eventually oxidize to sulfate or be lost to deposition). Under low-NO conditions, hydroperoxymethyl thioformate (HPMTF, HOOCH2SCHO), formed from CH3SCH2OO isomerization, dominates the sulfur budget over the course of the experiment, suppressing or delaying the formation of SO2 and particulate matter. The isomerization rate constant of CH3SCH2OO at 295 K is found to be 0.13±0.03 s−1, in broad agreement with other recent laboratory measurements. The rate constants for the OH oxidation of key first-generation oxidation products (HPMTF and methyl thioformate, MTF) were also determined (kOH+HPMTF=2.1×10-11 cm3 molec.−1 s−1, kOH+MTF=1.35×10-11 cm3 molec.−1 s−1). Product measurements agree reasonably well with mechanistic predictions in terms of total sulfur distribution and concentrations of most individual species, though the mechanism overpredicts sulfate and underpredicts MSA under high-NO conditions. Lastly, results from high-relative-humidity conditions suggest efficient heterogenous loss of at least some gas-phase products.

The measurements of aerosol particles with a filter inlet for gases and aerosols (FIGAERO) together with a chemical ionisation mass spectrometer (CIMS) yield the overall chemical composition of the particle phase. In addition, the thermal desorption profiles obtained for each detected ion composition contain information about the volatility of the detected compounds, which is an important property for understanding many physical properties like gas–particle partitioning. We coupled this thermal desorption method with isothermal evaporation prior to the sample collection to investigate the chemical composition changes during isothermal particle evaporation and particulate-water-driven chemical reactions in α-pinene secondary organic aerosol (SOA) of three different oxidative states. The thermal desorption profiles of all detected elemental compositions were then analysed with positive matrix factorisation (PMF) to identify the drivers of the chemical composition changes observed during isothermal evaporation. The keys to this analysis were to use the error matrix as a tool to weight the parts of the data carrying most information (i.e. the peak area of each thermogram) and to run PMF on a combined data set of multiple thermograms from different experiments to enable a direct comparison of the individual factors between separate measurements. The PMF was able to identify instrument background factors and separate them from the part of the data containing particle desorption information. Additionally, PMF allowed us to separate the direct desorption of compounds detected at a specific elemental composition from other signals with the same composition that stem from the thermal decomposition of thermally instable compounds with lower volatility. For each SOA type, 7–9 factors were needed to explain the observed thermogram behaviour. The contribution of the factors depended on the prior isothermal evaporation. Decreased contributions from the factors with the lowest desorption temperatures were observed with increasing isothermal evaporation time. Thus, the factors identified by PMF could be interpreted as volatility classes. The composition changes in the particles due to isothermal evaporation could be attributed to the removal of volatile factors with very little change in the desorption profiles of the individual factors (i.e. in the respective temperatures of peak desorption, Tmax). When aqueous-phase reactions took place, PMF was able to identify a new factor that directly identified the ions affected by the chemical processes. We conducted a PMF analysis of the FIGAERO–CIMS thermal desorption data for the first time using laboratory-generated SOA particles. But this method can be applied to, for example, ambient FIGAERO–CIMS measurements as well. There, the PMF analysis of the thermal desorption data identifies organic aerosol (OA) sources (such as biomass burning or oxidation of different precursors) and types, e.g. hydrocarbon-like (HOA) or oxygenated organic aerosol (OOA). This information could also be obtained with the traditional approach, namely the PMF analysis of the mass spectra data integrated for each thermogram. But only our method can also obtain the volatility information for each OA source and type. Additionally, we can identify the contribution of thermal decomposition to the overall signal.

Oxidation flow reactors that use low-pressure mercury lamps to produce hydroxyl (OH) radicals are an emerging technique for studying the oxidative aging of organic aerosols. Here, ozone (O3) is photolyzed at 254 nm to produce O(1D) radicals, which react with water vapor to produce OH. However, the need to use parts-per-million levels of O3 hinders the ability of oxidation flow reactors to simulate NOx-dependent SOA formation pathways. Simple addition of nitric oxide (NO) results in fast conversion of NOx (NO + NO2) to nitric acid (HNO3), making it impossible to sustain NO at levels that are sufficient to compete with hydroperoxy (HO2) radicals as a sink for organic peroxy (RO2) radicals. We developed a new method that is well suited to the characterization of NOx-dependent SOA formation pathways in oxidation flow reactors. NO and NO2 are produced via the reaction O(1D) + N2O→ 2NO, followed by the reaction NO + O3 → NO2+ O2. Laboratory measurements coupled with photochemical model simulations suggest that O(1D) + N2O reactions can be used to systematically vary the relative branching ratio of RO2 + NO reactions relative to RO2 + HO2 and/or RO2 + RO2 reactions over a range of conditions relevant to atmospheric SOA formation. We demonstrate proof of concept using high-resolution time-of-flight chemical ionization mass spectrometer (HR-ToF-CIMS) measurements with nitrate (NO3−) reagent ion to detect gas-phase oxidation products of isoprene and α-pinene previously observed in NOx-influenced environments and in laboratory chamber experiments.