About

Professor Allen Goldstein is a member of the research team at the Department of Environmental Science, Policy, & Management and the Department of Civil and Environmental Engineering at Berkeley. His research focuses on atmospheric chemistry, air pollution, and environmental science, contributing to understanding the chemical processes affecting air quality and climate. As a professor, he is involved in advancing knowledge in these areas through research and collaboration with a diverse team of scientists, postdoctoral researchers, graduate students, and specialists. His work supports efforts to improve air quality and address environmental challenges related to atmospheric composition and pollution.

Research topics

• Environmental science
• Chemistry
• Environmental chemistry
• Computer Science
• Organic chemistry
• Environmental engineering
• Biology
• Chromatography
• Geology
• Information Retrieval
• Geography
• Mathematics
• Data Mining
• Ecology
• Thermodynamics
• Statistics
• Astrophysics
• World Wide Web
• Atmospheric sciences
• Astrobiology
• Programming language
• Database
• Photochemistry
• Petroleum engineering

Selected publications

• UCB-GLOBES: An open-access mass spectral database of identified and unidentified atmospheric organic compounds

  2026-02-05

  articleOpen accessSenior author

  Abstract. 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.

  PublisherOA PDFDOI

• Emission factors and optical properties of black and brown carbon emitted at a mixed-conifer forest prescribed burn

  Atmospheric chemistry and physics · 2026-01-19

  articleOpen access

  Abstract. Prescribed burning is a fuel management practice employed globally that emits carbonaceous aerosols that affect human health and perturb the global climate system. Fuel-based black and brown carbon (BC and BrC) emission factors were calculated from ground and aloft smoke during prescribed burns at a mixed-conifer, montane forest site in the Sierra Nevada in California. BC emission factors were 0.52 ± 0.42 and 1.0 ± 0.48 g kg−1 for the smoldering and flaming combustion phases. Modified combustion efficiency is a poor predictor of BC emission factor, in this study and published literature. We discuss limitations of using generalized BC to PM2.5 mass emission ratios to generate emission inventories; using BC emission factors measured in this study, we recommend BC to PM2.5 ratios of 0.7 % and 9.5 % for the smoldering and flaming combustion in mixed conifer prescribed burns. We apportioned the measured aerosol spectral absorption between BrC and BC and calculated absorption Ångström exponents (AAE) of 6.26 and 0.67, respectively. Using a BrC-specific absorption cross-section, we estimated BC concentrations and a smoldering combustion BrC emission factor of 7.0 ± 2.7 g kg−1, nearly 14 and 7 times greater than the smoldering and flaming BC emission factors. Furthermore, we estimate that BrC would account for 23 % and 82 %, respectively, of the solar radiation absorbed by the smoldering smoke in the atmosphere integrated over the solar spectrum (300–2500 nm) and in the UV spectrum (300–400 nm), indicating that BrC affects tropospheric photochemistry in addition to atmospheric warming.

  PublisherOA PDFDOI

• Design, operation and characterization of a mobile laboratory for community-scale atmospheric research

  2026-03-11

  articleOpen access

  Abstract. Mobile laboratories equipped with research grade instrumentation make it possible to accurately observe fine scale (< 10 m) concentration gradients driven by local emissions, chemistry and meteorology. The flexibility afforded in measurement location makes mobile monitoring well suited to community pollution source characterization and rapid response to natural and anthropogenic situations. However, constructing a platform capable of these measurements requires simultaneous consideration of many engineering challenges and previous examples are rarely documented sufficiently for replication. Here, we present the design process and engineering decisions behind the UC Berkeley Mobile Air Pollution Laboratory (CalMAPLab). Built into a Ford Transit 250 van, the laboratory delivers extensive chemical speciation of air pollution in the gaseous and particulate phases. We characterize the performance of the electrical system, climate control and instrumentation suite for mobile measurements with over 500 hours of test driving. In addition, we introduce a fully open-source data acquisition system with live geospatial visualization that facilitates emissions plume mapping throughout a community. Our presentation of the fully described open design of the facility is intended to provide a transferable blueprint for high performance mobile monitoring in community-scale atmospheric research.

  PublisherOA PDFDOI

• Dramatic Air Quality Improvements after the Complete Electrification of a Commuter Rail System

  Environmental Science & Technology Letters · 2025-04-16 · 2 citations

  articleOpen access

  To limit the impact of climate change, there is an urgent requirement for infrastructure decarbonization and a transition to lower-emission energy systems. This is expected to result in local air quality co-benefits. However, quantification of these benefits through direct observations is often difficult because most transitions involve a gradual technological substitution over years or decades. Here, we report on a unique case study of local air quality improvements resulting from the rapid and complete transition of the Caltrain commuter rail system (California, USA) from diesel to electric operation over 6 weeks in 2024. At two measurement sites within the San Francisco station, concentrations of black carbon particles (BC, a major diesel exhaust constituent) dropped by 1.9 and 0.6 μg m–3. In addition, BC exposure on board the trains decreased on average by 89% and up to 17 μg m–3 per ride, where journey direction, proximity to the locomotive, and number of stops are key factors in rail car pollutant concentrations powered by diesel engines. Given that dozens of similarly equipped, diesel-operated commuter rail systems exist across the U.S., there is substantial potential for air pollution exposure reductions elsewhere through future electrification projects.

  PublisherDOI

• Incorporating Cooking Emissions To Better Simulate the Impact of Zero-Emission Vehicle Adoption on Ozone Pollution in Los Angeles

  Environmental Science & Technology · 2025-03-12 · 3 citations

  articleOpen access

  Despite decades of emission control measures aimed at improving air quality, Los Angeles (LA) continues to experience severe ozone pollution during the summertime. We incorporate cooking volatile organic compound (VOC) emissions in a chemical transport model and evaluate it against observations in order to improve the model representation of the present-day ozone chemical regime in LA. Using this updated model, we investigate the impact of adopting zero-emission vehicles (ZEVs) on ozone pollution with increased confidence. We show that mitigating on-road gasoline emissions through ZEV adoption would benefit both air quality and climate by substantially reducing anthropogenic nitrogen oxides (NOx) and carbon dioxide (CO2) emissions in LA by 28 and 41% during the summertime, respectively. This would result in a moderate reduction of O3 pollution, decreasing the average number of population-weighted O3 exceedance days in August from 9 to 6 days, and would shift the majority of LA, except for the coastline, into a NOx-limited regime. Our results also show that adopting ZEVs for on-road diesel and off-road vehicles would further reduce the number of O3 exceedance days in August to an average of 1 day.

  PublisherOA PDFDOI

• Optimizing the Temperature Sensitivity of the Isoprene Emission Model MEGAN in Different Ecosystems Using a Metropolis-Hastings Markov Chain Monte Carlo Method

  2025-02-05 · 1 citations

  preprintOpen access

  Isoprene is a reactive hydrocarbon emitted to the atmosphere in large quantities by terrestrial vegetation. Annual total isoprene emissions exceed 300 Tg a-1, but emission rates vary widely among plant species and are sensitive to meteorological and environmental conditions including temperature, sunlight, and soil moisture. Due to its high reactivity, isoprene has a large impact on air quality and climate pollutants such as ozone and aerosols. It is also an important sink for the hydroxyl radical which impacts the lifetime of the important greenhouse gas methane along with many other trace gas species. Modelling the impacts of isoprene emissions on atmospheric chemistry and climate requires accurate isoprene emission estimates. These can be obtained using the empirical Model of Emissions of Gases and Aerosols from Nature (MEGAN), but the parameterization of this model is uncertain due in part to limited field observations. In this study, we use ground-based measurements of isoprene concentrations and fluxes from 11 field sites to assess the variability of the isoprene emission temperature response across ecosystems. We then use these observations in a Metropolis-Hastings Markov Chain Monte Carlo (MHMCMC) data assimilation framework to optimize the MEGAN temperature response function. We find that the performance of MEGAN can be significantly improved at several high-latitude field sites by increasing the modelled sensitivity of isoprene emissions to past temperatures. At some sites, the optimized model was nearly 4 times more sensitive to temperature than the unoptimized model. This has implications for air quality modelling in a warming climate.

  PublisherOA PDFDOI

• Emerging drivers of urban aerosol increase global change vulnerability in a US megacity

  npj Climate and Atmospheric Science · 2025-09-30

  articleOpen access

  Abstract Urban aerosol pollution is evolving rapidly with global change and poses significant risks to public health. Measurements and machine learning-enabled chemical analysis of aerosol from a suburb of New York City in 2023 reveal emerging sources and drivers in a modern megacity. Regional wildfire smoke averaged 25% of organic aerosol (OA) mass and drove variability via enhancements of biogenic OA formation within smoke plumes. This biogenic OA contributed 40% of aerosol mass. Urban heatwaves enhanced both biogenic and anthropogenic sources, with ~20% of OA mass exhibiting significant heatwave sensitivity. For the first time, volatile chemical product (VCP) compounds were directly observed, speciated, and characterized in urban aerosol. Contributions to total OA averaged 15%, double the contribution from traffic. Together, this work identifies wildfire smoke, biogenic emissions, heat, and emerging anthropogenic emissions as critical global change vulnerabilities for North American urban aerosol pollution that pose unique challenges for control strategies.

  PublisherOA PDFDOI

• Influence of Cleaning on Indoor Air Concentrations of Volatile and Semivolatile Organic Compounds in Residences

  Environmental Science & Technology · 2025-05-15 · 8 citations

  articleOpen accessSenior authorCorresponding

  Cleaning activities can affect indoor air composition long after the cleaning is completed. Utilizing data from detailed observational monitoring campaigns, conducted over 21 weeks, we explore the influence of cleaning activities in two normally occupied, single-family houses. To study emissions and chemistry, we quantified more than 200 volatile organic compounds (VOCs) using a proton-transfer reaction time-of-flight mass spectrometer and 52 semivolatile organic compounds (SVOCs) using a semivolatile thermal-desorption gas chromatograph. During regular professional home cleaning, we observed postcleaning concentration enhancements in ∼60% of measured VOCs and ∼80% of measured SVOCs. Most of these concentration enhancements were not clearly linked to either primary emission from cleaning products or secondary formation through reactive chemistry. Instead, we infer that shifts in the sorptive properties of indoor surfaces account for most of these observations. Cleaning-associated enhancements mostly ebbed within a few hours, with some VOCs and lower-volatility SVOCs persisting more than 5 h, longer than would be expected for removal of inert species by ventilation. The use of carpet cleaner was associated with direct emission of 2-butoxyethanol, which persisted at elevated concentrations for days after the initial event. Home cleaning is potentially relevant for the health of professional cleaners and residents.

  PublisherDOI

• Inequality in hazardous volatile organic compound (VOC) emissions and concentrations measured over Los Angeles

  2025-03-14

  preprintOpen accessSenior authorCorresponding

  In the United States, PM2.5 and NOx pollution disproportionately burden communities of color and of lower income. However, such information is lacking when it comes to hazardous air pollutants (HAPs) like toxic volatile organic compounds, for which city-wide measurements are more challenging and thus are not available in routine observations.In this study, we use the highest spatially resolved (~2 km) airborne measurements of emissions and concentrations ever reported of HAPs while covering a whole megacity, and combine these observations with US Census information. We observe higher concentrations and emissions of 17 measured HAPs – such as benzene, naphthalene, and p-chlorobenzotrifluoride (PCBTF) – in California-designated Disadvantaged Communities and census tracts with low-income Hispanics and Asians. While concentrations were on average 32 ± 5% higher for low-income Hispanics compared to high-income non-Hispanic whites, emissions were even 107 ± 21% higher - indicating the proximity of low-income Hispanics to localized emission sources. Low-income Hispanics and Asians share an unequal burden from traffic-related emissions, with benzene, nitrogen oxides (NOx ), and carbon monoxide (CO) concentrations up to 60% higher. However, in Disadvantaged Communities and census tracts with large Hispanic populations (>50%), we observe toluene-to-benzene emission ratios above 3, pointing to inequalities in other HAPs primarily caused by non-traffic emission sources such as industry and solvents. In these communities, regulatory inventories also significantly underestimate the observed emissions. We find that efforts to address HAP inequalities and environmental justice concerns in Los Angeles will need to consider contributions from volatile chemical products, which represent a growing source of emissions driving inequalities in impacted communities.

  PublisherDOI

• Comprehensive Fuel and Emissions Measurements Highlight Uncertainties in Smoke Production Using Predictive Modeling Tools

  ACS ES&T Air · 2025-05-09 · 2 citations

  article

  Predictive modeling tools, such as the First Order Fire Effects Model (FOFEM), are used to generate estimates of the effects from wildland fires, including fuel consumption and smoke emissions. Given the use of such models in planning and forecasting for wildland fires, coupled with the adverse health and climate impacts of smoke, there is a need to understand the sensitivity to model inputs and processes, evaluate smoke production, and identify critical uncertainties. In this work, FOFEM was applied to a series of prescribed burns at the Blodgett Forest Research Station (BFRS), a western mixed coniferous forest in northern California, adapted to a frequent low-severity fire regime. We evaluated the sensitivity of predicted smoke emissions to parametric uncertainty in model inputs, including fuel characteristics (composition, loading, and moisture) and emission factors (EFs), and structural uncertainty in the consumption model. The results of the modeling simulations and comparison with a unique and comprehensive suite of fuel and emissions measurements suggest that in this application of FOFEM, fuel loadings based on land cover maps had the highest uncertainty and resulted in the largest sensitivity in predicted smoke emissions. The use of land-cover-based fuel loading values significantly underpredicted gas and particle emissions from the prescribed burns by up to ∼80% for carbon monoxide (CO) and carbon dioxide (CO2) and by up to ∼85% for fine particulate matter (PM2.5). Improvement in the predicted smoke emissions could specifically be achieved by more accurate fuel loading data, particularly for duff and coarse wood, the consumption of which generated the majority of gas (∼50–70%) and particle (∼65%) emissions. For individual gaseous nonmethane organic compounds (NMOCs), predicted emissions were additionally sensitive to uncertainty in EFs, demonstrating that the accurate prediction of these NMOCs requires accurate representation of fuel consumption as well as representative EFs.

  PublisherDOI

Recent grants

• Biogenic Volatile Organic Carbon (VOC) Emission and Organic Aerosol Composition During the Biosphere Effects on Aerosol and Photochemistry Experiment (BEARPEX)

  NSF · $703k · 2009–2012

• Collaborative Research: Investigating Secondary Organic Aerosol (SOA) Formation in Central Los Angeles for Research at the Nexus of Air Quality and Climate Change (CalNex 2010)

  NSF · $254k · 2009–2012

• GoAmazon 2014 Contributions of Biogenic Volatile Organic Compounds to Organic Aerosol Formation in the Presence and Absence of Anthropogenic Pollution

  NSF · $459k · 2013–2018

• NIH Grant R21AR051945

  NIH · $300k · 2008

• NIH Grant R03DE015915

  NIH · $150k · 2007

Frequent coauthors

• J. L. Jiménez

  217 shared

• J. A. de Gouw

  Cooperative Institute for Research in Environmental Sciences

  191 shared

• R. C. Cohen

  University of California, Berkeley

  173 shared

• Pawel K. Misztal

  UK Centre for Ecology & Hydrology

  151 shared

• Gabriel Isaacman‐VanWertz

  Virginia Tech

  149 shared

• D. A. Day

  Cooperative Institute for Research in Environmental Sciences

  146 shared

• David R. Worton

  National Physical Laboratory

  131 shared

• Dylan B. Millet

  106 shared

Labs

• Allen Goldstein LabPI

  Research Team

Education

• PhD, Chemistry

  Harvard University

  1994

• BS, Chemistry

  University of California Santa Cruz

  1989

• BA, Politics

  University of California Santa Cruz

  1989