Gabriel Isaacman-VanWertz

The impact of emissions on atmospheric chemistry requires a detailed chemical understanding of their transformation and fate. However, there are many sources of potential uncertainty in modeling the life cycle and transformation of biogenic volatile organic compounds (BVOC). This study investigates the sensitivity of a 0-D box model to several sources of potential uncertainty at a southeastern U.S. forest site over the summer season, including mixing ratios of critical trace oxidants (O3 and NO2), planetary boundary layer height (PBLH), and the factors that control emission rates. Within this framework, our results indicate that the model is relatively insensitive to the tested O3 input. Meanwhile NO2 input, evaluated here as a bounding comparison between rural and urban conditions, produces a substantial effect on modeled BVOC mixing ratios. Differences among currently available PBLH data sets emerged as a major source of overall uncertainty of comparable or greater magnitude than the NO2 bounding test. Daytime and nighttime model-observation correlation and bias varied considerably depending on PBLH data set and compound, with the largest discrepancies and lowest correlations occurring at night, highlighting particular challenges in modeling nocturnal BVOC mixing ratios. Compound-specific biases also varied substantially: isoprene and α-pinene, the two best-studied compounds, showed moderate bias across most scenarios, while sabinene showed substantially larger, consistent underprediction, suggesting poorly constrained emission factors for this compound specifically. These results highlight the sensitivities of this modeling framework to PBLH, oxidant mixing ratios, and emission factor uncertainty, and underscore the value of observationally constraining PBLH and isomer-resolved BVOC mixing ratios to improve current biogenic emissions modeling.

Advancements in observational capabilities have led to exponential increases in the number of compounds measured in air with unknown inhalation exposure guidelines or community health risks. Exposure frameworks try to capture a variety of exposure contexts with a range of guidelines; however, they are largely focused on occupational settings, and the relationship between guidelines is not always clear. Consequently, assessing measured compounds within these guidelines is not straightforward, and the question of whether air is safe is not easily answered. Here, the recommendations and aims of exposure frameworks are reviewed, which inherently drive guidelines and risk tolerance. U.S. and select international ambient air quality and inhalation exposure guidelines are compared, illustrating differences between the exposure frameworks and guidelines. For compounds with available exposure guidelines, this comparison provides order-of-magnitude estimates for protection of public health. To improve on these estimates, exposure frameworks are needed that build on ambient observations, target the most vulnerable community members, and consider real-world exposure durations from days to years.

Chemical characterization of atmospheric organic aerosols using gas chromatography with 70 eV electron ionization mass spectrometry (GC/EI-MS) has been used for decades in advancing molecular marker detection and identification, though primarily through suspect screening and/or targeted analyses. To advance non-targeted analyses of environmental samples, we have catalogued approximately 27 000 mass spectra (MS) of the trimethylsilyl derivatives of semi-volatile organic aerosol (OA) analytes in the open-access University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES). Analytes were observed in ambient samples from the U.S. and the Central Amazon and/or laboratory simulations of secondary OA (SOA) formation. These samples are representative of OA under urban and biomass burning influences as well as SOA derived from biogenic precursors (e.g., isoprene, monoterpenes, sesquiterpenes) and biomass burning intermediates. MS are documented in UCB-GLOBES without regard to known chemical identity, annotated with extensive metadata such as sample source/experimental conditions, any structural information gained from MS analyses, and predicted chemical properties such as average carbon oxidation state and carbon number. UCB-GLOBES MS are compatible for importing into the NIST MS Search program, and we have also provided a Jupyter Notebook for MS visualization and comparisons. We demonstrate the utility of UCB-GLOBES through MS reanalyses of prior analytes observed in ambient data, finding a 20 % reduction in the number of analytes assigned to OA source categories reliant solely on time series correlation and an overall 11 % increase in new MS-based OA source categorization for the Southeast U.S. For 1513 analytes observed previously in the Central Amazon, we found 375 MS matches using UCB-GLOBES vs. 136 MS matches during prior analyses, representing a 14 % gain in newly confirmed or newly categorized OA species. While OA from laboratory oxidation experiments in UCB-GLOBES are highly diverse chemically, on average only 29 % of UCB-GLOBES MS have a mass spectral match to another MS entry in UCB-GLOBES and/or in databases of known compounds (i.e. NIST MS Database, Adams Essential Oil, MANE Flavor and Fragrance Company). This indicates that roughly 70 % of UCB-GLOBES MS are unique thus far, not observed more than once among the laboratory oxidation samples and ambient data in UCB-GLOBES MS. Further, only 18 % can be positively identified using these databases or known authentic standards. This points to a large gap between these laboratory simulations and ambient OA. Overall, the UCB-GLOBES database can be utilized for improving confidence in OA source categorization and/or identification, novel chemical marker discovery, tracking chemical diversity, de novo structure and properties prediction, and improving MS search and matching algorithms. This can ultimately inform future research priorities for the chemical characterization of atmospheric organic samples.

Chemical characterization of atmospheric organic aerosols using gas chromatography with 70 eV electron ionization mass spectrometry (GC/EI-MS) has been used for decades in advancing molecular marker detection and identification, though primarily through suspect screening and/or targeted analyses. To advance non-targeted analyses of environmental samples, we have catalogued approximately 27,000 mass spectra (MS) of semi-volatile organic aerosol (OA) analytes observed in ambient samples from the U.S. and the Central Amazon and/or laboratory simulations of secondary OA (SOA) formation in the open-access University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES). These samples are representative of OA under urban and biomass burning influences as well as SOA derived from biogenic precursors (e.g., isoprene, monoterpenes, sesquiterpenes) and biomass burning intermediates. MS are documented in UCB-GLOBES without regard to known chemical identity, annotated with extensive metadata such as sample source/experimental conditions, structural information gained from MS analyses, and predicted chemical properties such as average carbon oxidation state and carbon number. UCB-GLOBES MS are compatible for importing into NIST MS Search program, and we have also provided a Jupyter Notebook for MS visualization and comparisons. We demonstrate the utility of UCB-GLOBES through MS reanalyses of prior analytes observed in ambient data, finding a 20 % reduction in the number of analytes assigned to OA source categories reliant solely on time series correlation and an overall 11 % increase in new MS-based OA source categorization for the Southeast U.S. For 1,513 analytes observed previously in the Central Amazon, we found 375 MS matches using UCB-GLOBES vs. 136 MS matches during prior analyses, representing a 14 % gain in newly confirmed or newly categorized OA species. While OA from laboratory oxidation experiments in UCB-GLOBES are highly diverse chemically, on average only 29 % of UCB-GLOBES MS have a mass spectral match to another MS entry in UCB-GLOBES and/or in the NIST MS Database. This indicates that roughly 70 % of UCB-GLOBES MS are unique thus far, not observed more than once among the laboratory oxidation samples and ambient data in UCB-GLOBES MS. Further, only 18 % can be positively identified in the NIST MS database or with known authentic standards. This points to a large gap between these laboratory simulations and ambient OA. Overall, the UCB-GLOBES database can be utilized for improving confidence in OA source categorization and/or identification, novel chemical marker discovery, tracking chemical diversity, de novo structure and properties prediction, and improving MS search and matching algorithms. inform future research priorities for the chemical characterization of atmospheric organic samples.

Biomass burning (BB) is a major source of atmospheric particles and trace gases, influencing climate change, air quality, and human health. During the Georgia Wildland-Fire Simulation Experiment, we measured the hygroscopicity (κ) and size-resolved cloud condensation nuclei (CCN) activity of BB particles from controlled burns of fuel beds representative of three ecoregions in Georgia, United States. Primary BB particles were predominantly organic, and photooxidation in an oxidation flow reactor produced secondary organic aerosol (SOA) in a new nucleation mode while transforming primary organic aerosol (POA) into oxidized POA (OPOA) in the pre-existing accumulation mode. We measured hygroscopic growth from 20% to 90% relative humidity using a quartz crystal microbalance and assessed size-resolved CCN activity for particles from 30 to 350 nm at supersaturation between 0.13% and 0.99%. We found that the hygroscopicity parameter of OPOA (κ_OPOA = 0.10–0.19) was higher than that of POA (0.04–0.10), reflecting the influence of heterogeneous oxidation, whereas the hygroscopicity parameter of SOA (κ_SOA = 0.07–0.14) fell between the two. Both fresh and aged BB particles displayed size-dependent κ values and evidence of external mixing, likely because of complex emission characteristics of fuel beds and size-dependent deposition processes. Growth factor-derived and CCN-derived κ values were consistent when accounting for such heterogeneity. A strong positive correlation was found between the mass-averaged κ and O/C ratio, described by the regression κ = 0.31 ± 0.02­(O/C) – 0.05 ± 0.02, which broadly agrees with previous findings for a wide range of laboratory SOA and ambient oxidized organic aerosols. This suggests the potential applicability of a generalized hygroscopicity parameterization across organic aerosols within acceptable uncertainty. Our results highlight the role of BB particles as significant CCN sources during atmospheric aging and emphasize the importance of heterogeneous oxidation in physicochemical evolution of BB particles.

Microfabricated gas chromatographs (µGCs) combine portability, low power demand, and rapid analysis, with the challenge of managing thermal crosstalk, cold spots and inter-device leakage, particularly for low vapor pressure analytes. These non‑isothermal regions cause peak broadening or loss of late‑eluting compounds and typically demand bulky ovens or monolithic integration to overcome. This study addresses these limitations by utilizing finite element analysis (FEA) and infrared micro-thermography to optimize thermal management strategies, including the integration of heated transfer lines and Macor® machinable glass-ceramic spacers for enhanced separation efficiency and stability. FEA simulations revealed steep temperature gradients (over 100 oC across 16mm) in unheated interconnects, which in turn guided in optimizing heater geometry and set-point selection. Infrared micro-thermography confirmed that active heating effectively suppressed cold spots, leading to an isothermal flow path. Considering these observations, the current work integrated actively heated transfer lines between a micropreconcentrator and a Microelectromechanical system (MEMS) separation column to eliminate cold spots and used Macor® machinable glass-ceramic spacers to confine heat and prevent leaks. Gas chromatographic (GC) testing with heated transfer lines demonstrated sharp, undistorted peaks for high‑boiling n‑alkanes, confirming reliable separation up to C30 and validating the effectiveness of the cold‑spot‑free interconnect design. The Macor spacers effectively stabilized inter-junction temperatures, protected adjacent polymeric components, and ensured precise alignment with gas-tight sealing. This strategy establishes a cold spot free interconnect platform for modular µGCs, enabling high boiling analyte recovery without requiring monolithic integration or bulky, energy intensive systems. The approach advances µGC technology toward scalable, energy‑efficient, and field‑deployable chemical sensing, broadening its utility for environmental monitoring, industrial process control, and portable analytical applications.

Chemical characterization of atmospheric organic aerosols using gas chromatography with 70 eV electron ionization mass spectrometry (GC/EI-MS) has been used for decades in advancing molecular marker detection and identification, though primarily through suspect screening and/or targeted analyses. To advance non-targeted analyses of environmental samples, we have catalogued approximately 27,000 mass spectra (MS) of semi-volatile organic aerosol (OA) analytes observed in ambient samples from the U.S. and the Central Amazon and/or laboratory simulations of secondary OA (SOA) formation in the open-access University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES). These samples are representative of OA under urban and biomass burning influences as well as SOA derived from biogenic precursors (e.g., isoprene, monoterpenes, sesquiterpenes) and biomass burning intermediates. MS are documented in UCB-GLOBES without regard to known chemical identity, annotated with extensive metadata such as sample source/experimental conditions, structural information gained from MS analyses, and predicted chemical properties such as average carbon oxidation state and carbon number. UCB-GLOBES MS are compatible for importing into NIST MS Search program, and we have also provided a Jupyter Notebook for MS visualization and comparisons. We demonstrate the utility of UCB-GLOBES through MS reanalyses of prior analytes observed in ambient data, finding a 20 % reduction in the number of analytes assigned to OA source categories reliant solely on time series correlation and an overall 11 % increase in new MS-based OA source categorization for the Southeast U.S. For 1,513 analytes observed previously in the Central Amazon, we found 375 MS matches using UCB-GLOBES vs. 136 MS matches during prior analyses, representing a 14 % gain in newly confirmed or newly categorized OA species. While OA from laboratory oxidation experiments in UCB-GLOBES are highly diverse chemically, on average only 29 % of UCB-GLOBES MS have a mass spectral match to another MS entry in UCB-GLOBES and/or in the NIST MS Database. This indicates that roughly 70 % of UCB-GLOBES MS are unique thus far, not observed more than once among the laboratory oxidation samples and ambient data in UCB-GLOBES MS. Further, only 18 % can be positively identified in the NIST MS database or with known authentic standards. This points to a large gap between these laboratory simulations and ambient OA. Overall, the UCB-GLOBES database can be utilized for improving confidence in OA source categorization and/or identification, novel chemical marker discovery, tracking chemical diversity, de novo structure and properties prediction, and improving MS search and matching algorithms. inform future research priorities for the chemical characterization of atmospheric organic samples.

Electron ionization mass spectrometry (EIMS) has been widely used to measure complex atmospheric and environmental mixtures. The sensitivity of analytes in EIMS is typically obtained through a multipoint calibration curve using commercially available standards, but many analytes of interest do not have pure compounds available, and many samples contain a large fraction of unidentified compounds. To address these limitations in quantification, those analytes are often calibrated using a small number of standards with chemical similarities (e.g., shared functional groups). However, little systematic data are available on the variability of EIMS response factors to environmental analytes. In this work, we compare the EIMS response with a flame ionization detector (FID), a near-universal detector for organics, to quantify the variability in EIMS sensitivity to organics in a complex atmospheric mixture, particularly secondary organic aerosols (SOA). Particle-phase oxidation products from four precursor-oxidant pairs were produced, sampled, and analyzed by gas chromatography using a Thermal Desorption Aerosol Gas Chromatograph (TAG) with simultaneous detection by both FID and EIMS. The signals of FID and EIMS are highly correlated across the chromatogram, and peak areas of individual chromatographic peaks measured by both detectors are also closely correlated. The sensitivity of EIMS varies on average by ∼21% relative to FID for peak-by-peak comparison of oxygenated organic compounds within a complex mixture, suggesting that as long as some information is available about an unknown sample to categorize the analytes in the sample, an EIMS can be treated as a universal detector calibrated using chemically similar analytes.

Removal of gases and particles by precipitation (wet deposition) is a critical process that significantly influences the transport and chemical transformation of atmospheric compounds. However, there are few studies that directly measure or constrain the rates of this process under real-world conditions. This work quantifies the net change in ambient concentrations during precipitation events (removal rates) of gas- and particle-phase organic compounds at a surface site near Manaus, Brazil, during the GoAmazon2014/5 campaign. Removal rates of identified and unknown compounds that have been previously classified into source-based clusters are measured during rain events and categorized based on estimated properties of compounds and clusters. Highly oxygenated gases, such as isoprene oxidation products, are removed during precipitation events with a median removal rate of 0.09 h^–1 and the fastest analyte is removed at a rate of 0.22 h^–1. Removal rates of particle-phase compounds are observed at roughly this median rate, while less soluble gases, such as terpenes, exhibit low removal rates. These results are roughly in agreement with prior theoretical estimates of wet deposition rates for comparable compounds, providing an empirical point of comparison while noting that our metric reflects the net influence of precipitation events rather than wet deposition alone.