Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 1: Assessing the influence of constrained multi-generational ageing

Multi-generational oxidation of volatile organic compound (VOC) oxidation products can significantly alter the mass, chemical composition and properties of secondary organic aerosol (SOA) compared to calculations that consider only the first few generations of oxidation reactions. However, the most commonly used state-of-the-science schemes in 3-D regional or global models that account for multi-generational oxidation (1) consider only functionalization reactions but do not consider fragmentation reactions, (2) have not been constrained to experimental data and (3) are added on top of existing parameterizations. The incomplete description of multi-generational oxidation in these models has the potential to bias source apportionment and control calculations for SOA. In this work, we used the statistical oxidation model (SOM) of Cappa and Wilson (2012), constrained by experimental laboratory chamber data, to evaluate the regional implications of multi-generational oxidation considering both functionalization and fragmentation reactions. SOM was implemented into the regional University of California at Davis / California Institute of Technology (UCD/CIT) air quality model and applied to air quality episodes in California and the eastern USA. The mass, composition and properties of SOA predicted using SOM were compared to SOA predictions generated by a traditional two-product model to fully investigate the impact of explicit and self-consistent accounting of multi-generational oxidation. Results show that SOA mass concentrations predicted by the UCD/CIT-SOM model are very similar to those predicted by a two-product model when both models use parameters that are derived from the same chamber data. Since the two-product model does not explicitly resolve multi-generational oxidation reactions, this finding suggests that the chamber data used to parameterize the models captures the majority of the SOA mass formation from multi-generational oxidation under the conditions tested. Consequently, the use of low and high NOx yields perturbs SOA concentrations by a factor of two and are probably a much stronger determinant in 3-D models than multi-generational oxidation. While total predicted SOA mass is similar for the SOM and two-product models, the SOM model predicts increased SOA contributions from anthropogenic (alkane, aromatic) and sesquiterpenes and decreased SOA contributions from isoprene and monoterpene relative to the two-product model calculations. The SOA predicted by SOM has a much lower volatility than that predicted by the traditional model, resulting in better qualitative agreement with volatility measurements of ambient OA. On account of its lower-volatility, the SOA mass produced by SOM does not appear to be as strongly influenced by the inclusion of oligomerization reactions, whereas the two-product model relies heavily on oligomerization to form low-volatility SOA products. Finally, an unconstrained contemporary hybrid scheme to model multi-generational oxidation within the framework of a two-product model in which ageing reactions are added on top of the existing two-product parameterization is considered. This hybrid scheme formed at least 3 times more SOA than the SOM during regional simulations as a result of excessive transformation of semi-volatile vapors into lower volatility material that strongly partitions to the particle phase. This finding suggests that these hybrid multi-generational schemes should be used with great caution in regional models

Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model

Multi-generational gas-phase oxidation of organic vapors can influence the abundance, composition and properties of secondary organic aerosol (SOA). Only recently have SOA models been developed that explicitly represent multi-generational SOA formation. In this work, we integrated the statistical oxidation model (SOM) into SAPRC-11 to simulate the multi-generational oxidation and gas/particle partitioning of SOA in the regional UCD/CIT (University of California, Davis/California Institute of Technology) air quality model. In the SOM, evolution of organic vapors by reaction with the hydroxyl radical is defined by (1) the number of oxygen atoms added per reaction, (2) the decrease in volatility upon addition of an oxygen atom and (3) the probability that a given reaction leads to fragmentation of the organic molecule. These SOM parameter values were fit to laboratory smog chamber data for each precursor/compound class. SOM was installed in the UCD/CIT model, which simulated air quality over 2-week periods in the South Coast Air Basin of California and the eastern United States. For the regions and episodes tested, the two-product SOA model and SOM produce similar SOA concentrations but a modestly different SOA chemical composition. Predictions of the oxygen-to-carbon ratio qualitatively agree with those measured globally using aerosol mass spectrometers. Overall, the implementation of the SOM in a 3-D model provides a comprehensive framework to simulate the atmospheric evolution of organic aerosol

Carbon oxysulphide: A novel reagent for the synthesis of 4-amino/anilino-3- aryl/aryloxymethyl/thiophenoxymethyl-1,2,4-triazolin-5-ones and 5-arylamino-2-mercapto-1,3,4-oxadiazoles

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Secondary organic aerosol formation from in-use motor vehicle emissions using a potential aerosol mass reactor.

Secondary organic aerosol (SOA) formation from in-use vehicle emissions was investigated using a potential aerosol mass (PAM) flow reactor deployed in a highway tunnel in Pittsburgh, Pennsylvania. Experiments consisted of passing exhaust-dominated tunnel air through a PAM reactor over integrated hydroxyl radical (OH) exposures ranging from ∼ 0.3 to 9.3 days of equivalent atmospheric oxidation. Experiments were performed during heavy traffic periods when the fleet was at least 80% light-duty gasoline vehicles on a fuel-consumption basis. The peak SOA production occurred after 2-3 days of equivalent atmospheric oxidation. Additional OH exposure decreased the SOA production presumably due to a shift from functionalization to fragmentation dominated reaction mechanisms. Photo-oxidation also produced substantial ammonium nitrate, often exceeding the mass of SOA. Analysis with an SOA model highlight that unspeciated organics (i.e., unresolved complex mixture) are a very important class of precursors and that multigenerational processing of both gases and particles is important at longer time scales. The chemical evolution of the organic aerosol inside the PAM reactor appears to be similar to that observed in the atmosphere. The mass spectrum of the unoxidized primary organic aerosol closely resembles ambient hydrocarbon-like organic aerosol (HOA). After aging the exhaust equivalent to a few hours of atmospheric oxidation, the organic aerosol most closely resembles semivolatile oxygenated organic aerosol (SV-OOA) and then low-volatility organic aerosol (LV-OOA) at higher OH exposures. Scaling the data suggests that mobile sources contribute ∼ 2.9 ± 1.6 Tg SOA yr(-1) in the United States, which is a factor of 6 greater than all mobile source particulate matter emissions reported by the National Emissions Inventory. This highlights the important contribution of SOA formation from vehicle exhaust to ambient particulate matter concentrations in urban areas

Estimates of non-traditional secondary organic aerosols from aircraft SVOC and IVOC emissions using CMAQ

Utilizing an aircraft-specific parameterization based on smog chamber data in the Community Multiscale Air Quality (CMAQ) model with the volatility basis set (VBS), we estimated contributions of non-traditional secondary organic aerosols (NTSOA) for aircraft emissions during landing and takeoff (LTO) activities at the Hartsfield–Jackson Atlanta International Airport. NTSOA, formed from the oxidation of semi-volatile and intermediate volatility organic compounds (S/IVOCs), is a heretofore unaccounted component of fine particulate matter (PM2.5) in most air quality models. We expanded a prerelease version of CMAQ with VBS implemented for the Carbon Bond 2005 (CB05) chemical mechanism to use the Statewide Air Pollution Research Center 2007 (SAPRC-07) chemical mechanism and added species representing aircraft S/IVOCs and corresponding NTSOA oxidation products. Results indicated that the maximum monthly average NTSOA contributions occurred at the airport and ranged from 2.4 ng m−3 (34 % from idle and 66 % from non-idle aircraft activities) in January to 9.1 ng m−3 (33 and 67 %) in July. This represents 1.7 % (of 140 ng m−3) in January and 7.4 % in July (of 122 ng m−3) of aircraft-attributable PM2.5 compared to 41.0–42.0 % from elemental carbon and 42.8–58.0 % from inorganic aerosols. As a percentage of PM2.5, impacts were higher downwind of the airport, where NTSOA averaged 4.6–17.9 % of aircraft-attributable PM2.5 and, considering alternative aging schemes, was as high as 24.0 % – thus indicating the increased contribution of aircraft-attributable SOA as a component of PM2.5. However, NTSOA contributions were generally low compared to smog chamber results, particularly at idle, due to the considerably lower ambient organic aerosol concentrations in CMAQ compared to those in the smog chamber experiments

Modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic models

Laboratory-based studies have shown that combustion sources emit volatile organic compounds that can be photooxidized in the atmosphere to form secondary organic aerosol (SOA). In some cases, this SOA can exceed direct emissions of primary organic aerosol (POA). Jathar et al. (2017a) recently reported on experiments that used an oxidation flow reactor (OFR) to measure the photochemical production of SOA from a diesel engine operated at two different engine loads (idle, load), two fuel types (diesel, biodiesel), and two aftertreatment configurations (with and without an oxidation catalyst and particle filter). In this work, we used two different SOA models, the Volatility Basis Set (VBS) model and the Statistical Oxidation Model (SOM), to simulate the formation and composition of SOA for those experiments. Leveraging recent laboratory-based parameterizations, both frameworks accounted for a semi-volatile and reactive POA; SOA production from semi-volatile, intermediate-volatility, and volatile organic compounds (SVOC, IVOC and VOC); NOx-dependent parameterizations; multigenerational gas-phase chemistry; and kinetic gas–particle partitioning. Both frameworks demonstrated that for model predictions of SOA mass to agree with measurements across all engine load–fuel–aftertreatment combinations, it was necessary to model the kinetically limited gas–particle partitioning in OFRs and account for SOA formation from IVOCs, which were on average found to account for 70&thinsp;% of the model-predicted SOA. Accounting for IVOCs, however, resulted in an average underprediction of 28&thinsp;% for OA atomic O&thinsp;:&thinsp;C ratios. Model predictions of the gas-phase organic compounds (resolved in carbon and oxygen space) from the SOM compared favorably to gas-phase measurements from a chemical ionization mass spectrometer (CIMS), substantiating the semi-explicit chemistry captured by the SOM. Model–measurement comparisons were improved on using SOA parameterizations corrected for vapor wall loss. As OFRs are increasingly used to study SOA formation and evolution in laboratory and field environments, models such as those developed in this work can be used to interpret the OFR data.</p

Emission factor ratios, SOA mass yields, and the impact of vehicular emissions on SOA formation

The underprediction of ambient secondary organic aerosol (SOA) levels by current atmospheric models in urban areas is well established, yet the cause of this underprediction remains elusive. Likewise, the relative contribution of emissions from gasoline- and diesel-fueled vehicles to the formation of SOA is generally unresolved. We investigate the source of these two discrepancies using data from the 2010 CalNex experiment carried out in the Los Angeles Basin (Ryerson et al., 2013). Specifically, we use gas-phase organic mass (GPOM) and CO emission factors in conjunction with measured enhancements in oxygenated organic aerosol (OOA) relative to CO to quantify the significant lack of closure between expected and observed organic aerosol concentrations attributable to fossil-fuel emissions. Two possible conclusions emerge from the analysis to yield consistency with the ambient data: (1) vehicular emissions are not a dominant source of anthropogenic fossil SOA in the Los Angeles Basin, or (2) the ambient SOA mass yields used to determine the SOA formation potential of vehicular emissions are substantially higher than those derived from laboratory chamber studies

Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 2: Assessing the influence of vapor wall losses

The influence of losses of organic vapors to chamber walls during secondary organic aerosol (SOA) formation experiments has recently been established. Here, the influence of such losses on simulated ambient SOA concentrations and properties is assessed in the University of California at Davis / California Institute of Technology (UCD/CIT) regional air quality model using the statistical oxidation model (SOM) for SOA. The SOM was fit to laboratory chamber data both with and without accounting for vapor wall losses following the approach of Zhang et al. (2014). Two vapor wall-loss scenarios are considered when fitting of SOM to chamber data to determine best-fit SOM parameters, one with “low” and one with “high” vapor wall-loss rates to approximately account for the current range of uncertainty in this process. Simulations were run using these different parameterizations (scenarios) for both the southern California/South Coast Air Basin (SoCAB) and the eastern United States (US). Accounting for vapor wall losses leads to substantial increases in the simulated SOA concentrations from volatile organic compounds (VOCs) in both domains, by factors of  ∼  2–5 for the low and  ∼  5–10 for the high scenarios. The magnitude of the increase scales approximately inversely with the absolute SOA concentration of the no loss scenario. In SoCAB, the predicted SOA fraction of total organic aerosol (OA) increases from  ∼  0.2 (no) to  ∼  0.5 (low) and to  ∼  0.7 (high), with the high vapor wall-loss simulations providing best general agreement with observations. In the eastern US, the SOA fraction is large in all cases but increases further when vapor wall losses are accounted for. The total OA ∕ ΔCO ratio captures the influence of dilution on SOA concentrations. The simulated OA ∕ ΔCO in SoCAB (specifically, at Riverside, CA) is found to increase substantially during the day only for the high vapor wall-loss scenario, which is consistent with observations and indicative of photochemical production of SOA. Simulated O : C atomic ratios for both SOA and for total OA increase when vapor wall losses are accounted for, while simulated H : C atomic ratios decrease. The agreement between simulations and observations of both the absolute values and the diurnal profile of the O : C and H : C atomic ratios for total OA was greatly improved when vapor wall-losses were accounted for. These results overall demonstrate that vapor wall losses in chambers have the potential to exert a large influence on simulated ambient SOA concentrations, and further suggest that accounting for such effects in models can explain a number of different observations and model–measurement discrepancies

Ternary Cu2SnS3: synthesis, structure, photoelectrochemical activity, and heterojunction band offset and alignment

Ternary Cu2SnS3 (CTS) is an attractive nontoxic and earth-abundant absorber material with suitable optoelectronic properties for cost-effective photoelectrochemical applications. Herein, we report the synthesis of high-quality CTS nanoparticles (NPs) using a low-cost facile hot injection route, which is a very simple and nontoxic synthesis method. The structural, morphological, optoelectronic, and photoelectrochemical (PEC) properties and heterojunction band alignment of the as-synthesized CTS NPs have been systematically characterized using various state-of-the-art experimental techniques and atomistic first-principles density functional theory (DFT) calculations. The phase-pure CTS NPs confirmed by X-ray diffraction (XRD) and Raman spectroscopy analyses have an optical band gap of 1.1 eV and exhibit a random distribution of uniform spherical particles with size of approximately 15–25 nm as determined from high-resolution transmission electron microscopy (HR-TEM) images. The CTS photocathode exhibits excellent photoelectrochemical properties with PCE of 0.55% (fill factor (FF) = 0.26 and open circuit voltage (Voc) = 0.54 V) and photocurrent density of −3.95 mA/cm2 under AM 1.5 illumination (100 mW/cm2). Additionally, the PEC activities of CdS and ZnS NPs are investigated as possible photoanodes to create a heterojunction with CTS to enhance the PEC activity. CdS is demonstrated to exhibit a higher current density than ZnS, indicating that it is a better photoanode material to form a heterojunction with CTS. Consistently, we predict a staggered type-II band alignment at the CTS/CdS interface with a small conduction band offset (CBO) of 0.08 eV compared to a straddling type-I band alignment at the CTS/ZnS interface with a CBO of 0.29 eV. The observed small CBO at the type-II band aligned CTS/CdS interface points to efficient charge carrier separation and transport across the interface, which are necessary to achieve enhanced PEC activity. The facile CTS synthesis, PEC measurements, and heterojunction band alignment results provide a promising approach for fabricating next-generation Cu-based light-absorbing materials for efficient photoelectrochemical applications