About

Alex B Guenther is an Associate Professor at UC Irvine, where he has been serving since 2018. He previously held the position of Assistant Professor at UC Irvine from 2012 to 2018. His academic background includes a Ph.D. from Georgia Institute of Technology, where his advisor was L. Gregory Huey, obtained in 2007. He also holds M.S. and B.S. degrees from Seoul National University, completed in 2000 and 1998 respectively. His research focuses on biosphere-atmosphere interactions, contributing to understanding the complex processes that govern atmospheric chemistry and climate. Guenther's work involves leading a team of graduate students and researchers, engaging in field campaigns, projects, and teaching activities related to earth system science. His expertise and leadership in atmospheric sciences are reflected in his role as a principal investigator and his active involvement in the Biosphere Atmosphere Interactions Group at UC Irvine.

Research topics

• Chemistry
• Environmental chemistry
• Atmospheric sciences
• Geography
• Meteorology
• Environmental science
• Ecology
• Organic chemistry
• Environmental engineering
• Geomorphology
• Geology
• Environmental protection

Selected publications

• Global atmospheric methanol emissions inferred from IASI satellite measurements and aircraft data

  Atmospheric chemistry and physics · 2026-04-22

  articleOpen access

  Abstract. We employ an updated retrieval of space-based methanol (CH3OH) column measurements from the Infrared Atmospheric Sounding Interferometer (IASI) and an emission optimisation framework built on the MAGRITTE chemical transport model to assess terrestrial emissions of methanol to the atmosphere between 2008–2019. We first carry out a IASI CH3OH validation study based on concentration measurements from three airborne campaigns, using the model and the IASI averaging kernels to compute aircraft-based columns directly comparable to IASI data. IASI is found to underestimate high columns in the considered region. A linear regression gives ΩIASI=0.46Ωairc+10.6×1015molec.cm-2, with ΩIASI and Ωairc the IASI and aircraft-derived columns, respectively. Inverse modelling of terrestrial methanol emissions using MAGRITTE and bias-corrected IASI columns leads to much-improved overall agreement against in situ measurement campaigns and column data at eight FTIR stations. The optimised global biogenic methanol emissions (∼160Tgyr-1) are 22 %–60 % higher than previous top-down estimates, due to (1) column enhancements caused by the IASI bias-correction and (2) higher dry deposition velocities in the model over land, compared to previous model studies, based on a parametrisation constrained by extensive campaign data. The inversion results are less reliable over boreal forests due to shortcomings of both the bias-correction and the dry deposition scheme over these regions. The optimisation suggests large changes in the distribution and seasonality of emissions. Over tropical ecosystems, radiation and temperature appear to exert a stronger control on biogenic emissions than is currently accounted for in the MEGAN model.

  PublisherDOI

• MEGAN3.2 Prep and Emission Factor Processor

  Zenodo (CERN European Organization for Nuclear Research) · 2026-04-09

  datasetOpen access1st authorCorresponding
  PublisherDOI

• MEGAN3.2 Prep and Emission Factor Processor

  Zenodo (CERN European Organization for Nuclear Research) · 2026-04-09

  datasetOpen access1st authorCorresponding
  PublisherDOI

• Summertime Carbonaceous Aerosol in Interior Versus Coastal Northern Alaska

  Journal of Geophysical Research Atmospheres · 2025-04-19 · 1 citations

  articleOpen access

  Abstract Rapid warming is likely increasing primary production and wildfire occurrence in the Arctic. Projected changes in carbonaceous aerosols during the summer will impact atmospheric chemistry and climate, but our understanding of these processes is limited by sparse observations. Here, we characterize carbonaceous aerosol in Alaska, USA: Toolik Field Station in the Interior and the Atmospheric Radiation Measurement facility at Utqiaġvik on the Arctic coast, during the summers of 2022 and 2023. We estimated PM 2.5 and PM 10 concentrations using laser light scattering (PurpleAir sensors) and examined total carbon (TC) and its organic carbon (OC) and elemental carbon (EC) fractions in total suspended particles (TSP). We investigated the dominant sources of carbonaceous aerosol using air mass backward‐trajectories from the NOAA HYSPLIT model and radiocarbon source apportionment of TC. TC concentrations were about twice as high in the Interior compared to the coast, with contemporary sources dominating at both Toolik (95%–99%) and Utqiaġvik (86%–89%) over minor contributions from fossil sources. Elevated PM, TC, OC, and EC concentrations coincided with major boreal forest fire activity in North America that brought smoke to the region. The radiocarbon signature of EC measured at Toolik during these wildfire events indicated that over 90% of the EC came from contemporary sources. Our measurements demonstrate the potential for Arctic aerosol concentrations to respond significantly to climate warming‐induced changes to the landscape and emphasize the need for continuous atmospheric monitoring to advance our understanding of this rapidly changing environment.

  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

• Development and application of a generalized empirical model of BVOC emission (GEMBE) using observations from four Chinese forests

  Atmospheric Pollution Research · 2025-11-08

  articleSenior author
  PublisherDOI

• Seasonal variations in whole–ecosystem BVOC emissions and ozone fluxes from a tropical rubber tree plantation in China

  Atmospheric Environment · 2025-03-21 · 4 citations

  articleSenior author
  PublisherDOI

• Biogenic and anthropogenic contributions to urban terpenoid fluxes

  2025-06-26

  preprintOpen access

  Abstract. Terpenoids influence atmospheric chemistry through rapid oxidation reactions which form secondary products including ozone and secondary organic aerosols (SOA). The source apportionment of terpenoids is complicated in urban environments because they have biogenic and anthropogenic sources. This study utilizes measured fluxes of isoprene, monoterpenes, and sesquiterpenes with MEGAN, a biogenic emissions model, and FIVE-VCP, an anthropogenic emissions inventory, to characterize urban terpenoid emissions. Volatile organic compound (VOC) mixing ratios were measured using a Vocus proton transfer reaction mass spectrometer (PTR-MS) at the Berkeley Way West (BWW) tower in Berkeley, California from May to November of 2022. Fluxes were calculated using the eddy covariance technique. Median fluxes of isoprene, monoterpenes, and sesquiterpenes were 0.269, 0.182, and 0.013 nmol m-2 s-1 respectively. Terpenoids were 2 % of the measured molar VOC flux, 26 % of OH reactivity, and 21 % of SOA formation potential. The MEGAN isoprene emission factor was 4.56 nmol (m2 leaf area)-1 s-1. MEGAN isoprene fluxes matched the BWW distributions both seasonally and diurnally, while MEGAN monoterpene and sesquiterpene fluxes had a more pronounced seasonal trend and lower morning emissions relative to BWW. Weekday/weekend differences were used to determine if terpenoids had anthropogenic sources. Monoterpene and sesquiterpene fluxes were significantly higher on weekdays (p<0.05), while these differences were not represented in MEGAN or FIVE-VCP. Monoterpenes and sesquiterpenes had lower-bound anthropogenic fractions of 23 % and 24 %. This study presents a detailed analysis of urban terpenoid fluxes and contributes to a better understanding of their sources.

  PublisherOA PDFDOI

• Reducing Long‐Standing Surface Ozone Overestimation in Earth System Modeling by High‐Resolution Simulation and Dry Deposition Improvement

  Journal of Advances in Modeling Earth Systems · 2025-03-01 · 15 citations

  articleOpen access

  Abstract The overestimation of surface ozone concentration in low‐resolution global atmospheric chemistry and climate models has been a long‐standing issue. We first update the ozone dry deposition scheme in both high‐ (0.25°) and low‐resolution (1°) Community Earth System Model (CESM) version 1.3 runs, by adding the effects of leaf area index and correcting the sunlit and shaded fractions of stomatal resistances. With this update, 5‐year‐long summer simulations (2015–2019) using the low‐resolution CESM still exhibit substantial ozone overestimation (by 6.0–16.2 ppbv) over the U.S., Europe, eastern China, and ozone pollution hotspots. The ozone dry deposition scheme is further improved by adjusting the leaf cuticle conductance, reducing the mean ozone bias by 19%, and increasing the model resolution further reduces the ozone overestimation by 43%. We elucidate the mechanism by which model grid spacing influences simulated ozone, revealing distinctive pathways in urban versus rural areas. In rural areas, grid spacing mainly affects daytime ozone levels, where additional NO x emissions from nearby urban areas result in an ozone boost and overestimation in low‐resolution simulations. In contrast, over urban areas, daytime ozone overestimation follows a similar mechanism due to the influence of volatile organic compounds from surrounding rural areas. However, nighttime ozone overestimation is closely linked to weakened NO titration owing to the redistribution of urban NO x to rural areas. Additionally, stratosphere‐troposphere exchange may also contribute to reducing ozone bias in high‐resolution simulations, warranting further investigation. This optimized high‐resolution CESM may enhance understanding of ozone formation mechanisms, sources, and changes in a warming climate.

  PublisherOA PDFDOI

• Two Biogenic Volatile Organic Compound Emission Datasets over Europe Based on Land Surface Modelling and Satellite Data Assimilation

  2025-10-02

  articleOpen access

  Abstract. Biogenic volatile organic compound (BVOC) emissions from vegetation represent a major source of volatile compounds globally and play an important role as precursors for tropospheric ozone. Understanding their emissions is therefore crucial for quantifying the impact of ozone on air quality. We present two datasets of biogenic volatile organic compound emissions that cover the European modelling domain of the Copernicus Atmospheric Monitoring Service at a resolution of 0.1° × 0.1° to support the study of European scale air quality. The compounds included in the dataset follow the VOCs included in the regional atmospheric chemistry model mechanism (RACM). The datasets were produced within the framework of the EU's SEEDS project. We produced each dataset by coupling modelling output variables from the SURFEX land surface model with the MEGAN3.0 BVOC emission model. In one instance, the SURFEX model was run in free-running mode, which we term the open-loop (OL) and in the other case we assimilated satellite observations of leaf area index (LAI), which we term the analysis. The OL and analysis land surface model outputs form the basis for each emission dataset that are called SURFEX-MEGAN3.0 OL and SURFEX-MEGAN3.0 analysis, respectively. The OL dataset is available over a five-year period from 2018–2022 and the analysis dataset is available over the three-year period 2018–2020. SURFEX was run for both the OL and analysis simulations in a configuration that allowed simulated vegetation to respond to variations in meteorology over time to more realistically track vegetation phenology. Evaluation of the land surface model output LAI and root-zone soil moisture (RZSM) showed that the OL and analysis simulations had good skill at tracking temporal changes in both variables, with the analysis performing better in each instance. We perform a variety of evaluations on the isoprene emissions specifically given the importance of this compound for atmospheric chemistry. We evaluated the temporal variability of isoprene emissions in both datasets and found that the majority of the interannual and monthly variability was linked to variability in LAI that in specific cases, like the summer of 2019, could be linked to drought impacts on vegetation growth simulated by SURFEX. We evaluated the daily temporal variability of the OL and analysis isoprene emission datasets against in-situ online observations of isoprene concentrations at 8 sites in western Europe and found moderate to strong correlation between the emissions and observations in almost all location-year pairings. We also evaluated the OL and analysis emission datasets against other published bottom-up isoprene emission datasets over the same European domain used in this study. We found that the SURFEX-MEGAN3.0 OL and analysis isoprene emission datasets lie between the minimum (CAMS-GLOB-BIOv3.1) and maximum (MEGAN-MACC) published emission datasets based on bottom-up approaches. Furthermore, we were able to attribute differences in seasonality between SURFEX-MEGAN3.0 and other emission inventories to differences in the temporal variability of the underlying LAI dataset used to compile them. Overall, our findings show the importance of variability in LAI in controlling isoprene emissions on monthly to annual timescales. Combining this with the demonstrated skill of the emissions in evaluation with independent data, this points towards the value of an Earth-system approach to BVOC emission modelling.

  PublisherOA PDFDOI

Recent grants

• Collaborative Proposal: BEAR-oNS: Biogenic Emissions and Aerosol Response on the North Slope

  NSF · $296k · 2021–2025

• Biogenic Volatile Organic Compound (VOC) Emissions from Managed Landscapes and Their Contribution to Atmospheric Ozone and Aerosol

  NSF · $675k · 2024–2027

• Collaborative Research: Unmanned Aerial Vehicles for Emissions and Chemistry of Volatile Organic Compounds over the Amazon Tropical Forest

  NSF · $413k · 2018–2022

• Atmospheric Biogenic Organic Emissions: Missing Compounds and Unrepresented Processes

  NSF · $615k · 2016–2021

Frequent coauthors

• Thomas Karl

  Universität Innsbruck

  184 shared

• Roger Seco

  Institute of Environmental Assessment and Water Research

  175 shared

• P. C. Harley

  Denver School of Nursing

  157 shared

• J. Greenberg

  NSF National Center for Atmospheric Research

  135 shared

• Detlev Helmig

  NOAA Air Resources Laboratory

  128 shared

• Saewung Kim

  University of California, Irvine

  105 shared

• A. H. Goldstein

  102 shared

• Christine Wiedinmyer

  Cooperative Institute for Research in Environmental Sciences

  102 shared

Labs

• Saewung Kim Dream TeamPI