About

Gabriel Isaacman-VanWertz is an Associate Professor in the Department of Civil and Environmental Engineering at Virginia Tech and is also the Anthony and Catherine Moraco Endowed Faculty Fellow. His research focuses on organic compounds in the air, specifically how they are emitted, how they transform, and their impacts on health and ecosystems. He is particularly interested in developing new methods to measure and analyze hazardous air pollutants. Isaacman-VanWertz spent the 2023-24 academic year living in Ecuador with his family as a Fulbright Scholar. He has been recognized as a Virginia Tech College of Engineering Dean’s Fellow and Faculty Fellow, and has received early career awards from the National Science Foundation and the Department of Energy. His educational background includes a Ph.D. from the University of California, Berkeley, in Environmental Science, Policy, and Management, and a B.A. from Wesleyan University in Chemistry/Earth and Environmental Science. His professional experience includes postdoctoral research at MIT and faculty positions at Virginia Tech, where he has taught courses such as Introduction to Environmental Engineering and Atmospheric Chemistry.

Selected publications

• Ten questions concerning indoor dust

  Building and Environment · 2025-11-09 · 1 citations

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  PublisherDOI

• Variability in the Universality of Electron Ionization Mass Spectrometry Response to Oxygenates in Complex Environmental Mixtures

  Analytical Chemistry · 2025-12-08

  articleOpen accessSenior authorCorresponding

  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.

  PublisherDOI

• Impacts of Precipitation Events on Concentrations of Oxygenated Gas- and Particle-Phase Compounds Observed in the Amazon

  ACS ES&T Air · 2025-11-06

  articleOpen accessSenior authorCorresponding

  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.

  PublisherDOI

• Quantifying Dissemination of Antibiotic Resistance Genes in Air from a Dairy Farm and Swine Farm

  ACS ES&T Air · 2025-07-18 · 4 citations

  articleOpen access

  Farms are a suspected source of dissemination of antibiotic resistance genes (ARGs) to the atmosphere, but their contribution remains poorly quantified. This study investigated the concentrations, emission rates, and particle size distributions of ARGs in air around a dairy farm and swine farm, as well as in farm wastewater and soil as potential sources, during a yearlong sampling campaign. Analysis targeted genes corresponding to a cross-section of antibiotic classes used in human and veterinary medicine, along with 16S rRNA and intI1 as indicators of total bacterial load and anthropogenic sources of ARGs, respectively. Two approaches were demonstrated for estimating emissions to account for the physical configurations of the farms. A custom sampler that collected size-resolved aerosol particles at a flow rate of 2.25 L/min only when the wind originated from the direction of interest was used to collect aerosol particles near potential sources. At the dairy and swine farms, blaCTX-M1 concentrations varied significantly by sampling location, averaging 102 gene copies per cubic meter (gc m–3) across seasons and peaking at 104 gc m–3 during the summer sampling period. At the swine farm, maximum concentrations reached 105 gc m–3 for intI1, ermF, and qnrA near the buildings’ exhaust fans. Emission rates reached ∼ 105 gc s–1 for some ARGs, including blaCTX-M1, and 106 gc s–1 for intI1. ARGs were predominantly associated with coarse particles (>5 μm) near emission sources and were also present in fine (<1 μm) and accumulation (1–5 μm) mode particles near the source and at downwind locations, indicating potential for inhalation exposure and long-range transport.

  PublisherDOI

• Formation of late-generation atmospheric compounds inhibited by rapid deposition

  Nature Geoscience · 2025-02-17 · 3 citations

  articleOpen accessSenior author

  Reactive organic carbon species are important fuel for atmospheric chemical reactions, including the formation of secondary organic aerosol. However, in parallel to atmospheric oxidation processes, deposition can remove compounds from the atmosphere and impact downstream environments. To understand the impact of deposition on atmospheric oxidation, we present a framework for predicting and visualizing the fate of a molecule on the basis of the physicochemical properties of compounds (Henry’s law constant, vapour pressure and reaction rate constants), which are used to estimate timescales for oxidation and deposition. By implementing our deposition rates in chemical models, we show that deposition substantially suppresses atmospheric reactivity and aerosol formation by removing early-generation products and preventing the formation of large fractions (up to 90%) of downstream, late-generation compounds. Deposition is frequently missing in the laboratory experiments and detailed chemical modelling, which probably biases our understanding of atmospheric composition. Rapid deposition of early-generation oxidation products substantially reduces the formation of late-generation atmospheric compounds, according to a deposition framework based on physicochemical properties and chemical modelling.

  PublisherDOI

• Systematic characterization of unknown compounds via dimensionality reduction of time series

  Aerosol Science and Technology · 2025-01-17 · 1 citations

  articleOpen accessSenior authorCorresponding

  Analysis of ambient aerosols provides valuable insight into particle sources and formation chemistry. However, due to the complexity of atmospheric data and the dynamic nature of aerosol composition, a substantial fraction of data often become discarded by conventional analysis methods. Furthermore, a large fraction of chemical species within those data are unidentifiable due to a lack of matching spectral information, resulting in suboptimal characterization of chemical composition. Previous work has demonstrated techniques for cataloging analytes in a chromatographic dataset by deconvolution of mass spectra, but integration of these analytes throughout a large dataset remains time consuming. Here, we present a method to automatically identify an ion for quantitation for single-ion chromatogram based peak fitting and integration, enabling comprehensive integration of analytes with minimal user interaction. The resulting time series are clustered with a machine-learning based dimensionality reduction technique to systematically investigate the underlying characteristics of the categorized analytes and gain new insights into the chemical composition and physicochemical properties of the unidentifiable analytes. We apply these methods to existing atmospheric datasets collected in Manacapuru, Brazil during the GoAmazon2014/5 campaign to identify new analytes and interpret their variability and transformations in the atmosphere. The analysis results generate 408 time series from cataloged analytes of interest, and the clustering of those time series with spherical k-means results in 8 distinct clusters. We find the analytes form clusters based on their distinct physicochemical properties, demonstrating the method’s ability to systematically identify and selectively filter contaminants and instrumental analytes and characterize the unidentifiable analytes.

  PublisherOA PDFDOI

• Airborne microplastics: An unexpected source of atmospheric brown carbon

  Research Square · 2025-10-27

  preprintOpen access
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• Digital Surface-Enhanced Raman Spectroscopy–Lateral Flow Test Dipstick: Ultrasensitive, Rapid Virus Quantification in Environmental Dust

  Environmental Science & Technology · 2024-03-07 · 34 citations

  articleOpen access

  This study introduces a novel surface-enhanced Raman spectroscopy (SERS)-based lateral flow test (LFT) dipstick that integrates digital analysis for highly sensitive and rapid viral quantification. The SERS-LFT dipsticks, incorporating gold-silver core-shell nanoparticle probes, enable pixel-based digital analysis of large-area SERS scans. Such an approach enables ultralow-level detection of viruses that readily distinguishes positive signals from background noise at the pixel level. The developed digital SERS-LFTs demonstrate limits of detection (LODs) of 180 fg for SARS-CoV-2 spike protein, 120 fg for nucleocapsid protein, and 7 plaque forming units for intact virus, all within <30 min. Importantly, digital SERS-LFT methods maintain their robustness and their LODs in the presence of indoor dust, thus underscoring their potential for accurate and reliable virus diagnosis and quantification in real-world environmental settings.

  PublisherOA PDFDOI

• Quantitative Characterization of the Volatility Distribution of Organic Aerosols in a Polluted Urban Area: Intercomparison Between Thermodenuder and Molecular Measurements

  Journal of Geophysical Research Atmospheres · 2024-02-23 · 7 citations

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  Abstract To quantify the volatility of organic aerosols (OA), a comprehensive campaign was conducted in the Chinese megacity. Volatility distributions of OA and particle‐phase organic nitrate (pON) were estimated based on five methods: (a) empirical method and (b) kinetic model based on the measurement of a thermodenuder (TD) coupled with an aerosol mass spectrometer; (c) Formula‐based SIMPOL model‐driven method; (d) Element‐based estimations using molecular formula measurements of OA; and (e) gas/particle partitioning. Our results demonstrate that the ambient OA volatility distribution shows good agreement between the two heating methods and the formula‐based method when assuming ambient OA was mainly composed of organic nitrate (pON), organic sulfate and acid groups using the SIMPOL model. However, the element‐based method tends to overestimate the volatility of OA compared to the above three methods, suggesting large uncertainties in the parameterizations or in the representativeness of the molecular measurements that need further refinement. The volatility of ambient OA is generally lower than that of the laboratory‐derived secondary OA, emphasizing the impact of aging. A large fraction at the higher and lower volatility ranges (approximately log C* ≤ −9 and ≥2 μg m −3 ) was found for pON, implying the importance of both extremely low volatile and semi‐volatile species. Overall, this study evaluates different methods for volatility estimation and gives new insight into the volatility of OA and pON in urban areas.

  PublisherDOI

• Observation-Constrained Kinetic Modelling of Isoprene SOA Formation in the Atmosphere

  2024-01-15 · 2 citations

  preprintOpen accessCorresponding

  Abstract. Isoprene has the largest global non-methane hydrocarbon emission, and the oxidation of isoprene plays a crucial role in the formation of secondary organic aerosols (SOA). Two primary processes are known to contribute to SOA formation from isoprene oxidation: (1) the reactive uptake of isoprene-derived epoxides on acidic or aqueous particle surfaces and (2) the absorptive gas-particle partitioning of low-volatility oxidation products. In this study, we developed a new multiphase condensed isoprene oxidation mechanism that include these processes with key molecular intermediates and products. The new mechanism was applied to simulate isoprene gas-phase oxidation products and SOA formation from previously published chamber experiments under a variety of conditions and atmospheric observations during the Southern Oxidant and Aerosol Studies (SOAS) field campaign. Our results show that SOA formation from most of the chamber experiments is reasonably reproduced using our mechanism except when the concentration ratios of initial nitric oxide to isoprene exceeds ~2. The SOAS simulations also reasonably agree with the measurements regarding the diurnal pattern and concentrations of different product categories. The molecular compositions of the modelled SOA indicate that multifunctional low-volatility products contribute to isoprene SOA more significantly than previously thought, with a median mass contribution of ~57 % to the total modelled isoprene SOA. This contribution, however, may vary greatly, mainly dependent on the volatility estimation and treatment of particle-phase processes (i.e., photolysis and hydrolysis). Our findings emphasize that the various pathways to produce these low-volatility species should be considered in models to more accurately predict isoprene SOA formation. The new condensed isoprene chemical mechanism can be further incorporated into regional-scale air quality models, such as the Community Multiscale Air Quality Modelling System (CMAQ), to assess isoprene SOA formation on a larger scale.

  PublisherDOI

Awards & honors

• 2024 VT College of Engineering Dean’s Fellow
• 2023 American Association of Aerosol Research Whitby Award,…
• 2023 Fulbright U.S. Scholar Award (Ecuador)
• 2022 VT Engineering Dean’s Award of Excellence: Faculty Fell…
• 2021 Department of Energy Early Career Program Award recipie…