Abstract. The impact of biomass burning (BB) on the atmospheric burden of volatile organic compounds (VOCs) is highly uncertain. Here we apply the GEOS-Chemchemical transport model (CTM) to constrain BB emissions in the western USA at ∼ 25 km resolution. Across three BB emission inventorieswidely used in CTMs, the inventory–inventory comparison suggests that the totals of 14 modeled BB VOC emissions in the western USA agree with eachother within 30 %–40 %. However, emissions for individual VOCs can differ by a factor of 1–5, driven by the regionally averaged emissionratios (ERs, reflecting both assigned ERs for specific biome and vegetation classifications) across the three inventories. We further evaluate GEOS-Chemsimulations with aircraft observations made during WE-CAN (Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption and Nitrogen) andFIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality) field campaigns. Despite being driven by different global BBinventories or applying various injection height assumptions, the model–observation comparison suggests that GEOS-Chem simulations underpredictobserved vertical profiles by a factor of 3–7. The model shows small to no bias for most species in low-/no-smoke conditions. We thus attribute thenegative model biases mostly to underestimated BB emissions in these inventories. Tripling BB emissions in the model reproduces observed verticalprofiles for primary compounds, i.e., CO, propane, benzene, and toluene. However, it shows no to less significant improvements for oxygenatedVOCs, particularly for formaldehyde, formic acid, acetic acid, and lumped ≥ C3 aldehydes, suggesting the model is missing secondarysources of these compounds in BB-impacted environments. The underestimation of primary BB emissions in inventories is likely attributable tounderpredicted amounts of effective dry matter burned, rather than errors in fire detection, injection height, or ERs, as constrained by aircraftand ground measurements. We cannot rule out potential sub-grid uncertainties (i.e., not being able to fully resolve fire plumes) in the nestedGEOS-Chem which could explain the negative model bias partially, though back-of-the-envelope calculation and evaluation using longer-term groundmeasurements help support the argument of the dry matter burned underestimation. The total ERs of the 14 BB VOCs implemented in GEOS-Chem onlyaccount for half of the total 161 measured VOCs (∼ 75 versus 150 ppb ppm−1). This reveals a significant amount of missing reactiveorganic carbon in widely used BB emission inventories. Considering both uncertainties in effective dry matter burned (× 3) and unmodeledVOCs (× 2), we infer that BB contributed to 10 % in 2019 and 45 % in 2018 (240 and 2040 Gg C) of the total VOC primaryemission flux in the western USA during these two fire seasons, compared to only 1 %–10 % in the standard GEOS-Chem.
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Development of an ecophysiology module in the GEOS-Chem chemical transport model version 12.2.0 to represent biosphere–atmosphere fluxes relevant for ozone air quality
Abstract. Ground-level ozone (O3) is a major air pollutant that adversely affects human health and ecosystem productivity. Removal of troposphericO3 by plant stomatal uptake can in turn cause damage to plant tissues with ramifications for ecosystem and crop health. In manyatmospheric and land surface models, the functionality of stomata opening is represented by a bulk stomatal conductance, which is oftensemi-empirically parameterized and highly fitted to historical observations. A lack of mechanistic linkage to ecophysiological processes such asphotosynthesis may render models inadequate to represent plant-mediated responses of atmospheric chemistry to long-term changes in CO2,climate, and short-lived air pollutant concentrations. A new ecophysiology module was thus developed to mechanistically simulate land−atmosphereexchange of important gas species in GEOS-Chem, a chemical transport model widely used in atmospheric chemistry studies. The implementation not onlyallows for dry deposition to be coupled with plant ecophysiology but also enables plant and crop productivity and functions to respond dynamically toatmospheric chemical changes. We conduct simulations to evaluate the effects of the ecophysiology module on simulated dry deposition velocity andconcentration of surface O3 against an observation-derived dataset known as SynFlux. Our estimated stomatal conductance and dry depositionvelocity of O3 are close to SynFlux with root-mean-squared errors (RMSEs) below 0.3 cm s−1 across different plant functionaltypes (PFTs), despite an overall positive bias in surface O3 concentration (by up to 16 ppbv). Representing ecophysiology wasfound to reduce the simulated biases in deposition fluxes from the prior model but worsen the positive biases in simulated O3concentrations. The increase in positive concentration biases is mostly attributable to the ecophysiology-based stomatal conductance being generallysmaller (and closer to SynFlux values) than that estimated by the prior semi-empirical formulation, calling for further improvements in non-stomataldepositional and non-depositional processes relevant for O3 simulations. The estimated global O3 deposition flux is864 Tg O3 yr−1 with GEOS-Chem, and the new module decreases this estimate by 92 Tg O3 yr−1. Estimated global grossprimary production (GPP) without O3 damage is 119 Pg C yr−1. O3-induced reduction in GPP is 4.2 Pg C yr−1(3.5 %). An elevated CO2 scenario (580 ppm) yields higher global GPP (+16.8 %) and lower global O3depositional sink (−3.3 %). Global isoprene emission simulated with a photosynthesis-based scheme is 317.9 Tg C yr−1, which is31.2 Tg C yr−1 (−8.9 %) less than that calculated using the MEGAN(Model of Emissions of Gases and Aerosols from Nature) emission algorithm. This new model development dynamicallyrepresents the two-way interactions between vegetation and air pollutants and thus provides a unique capability in evaluating vegetation-mediatedprocesses and feedbacks that can shape atmospheric chemistry and air quality, as well as pollutant impacts on vegetation health, especially for anytimescales shorter than the multidecadal timescale.
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- Award ID(s):
- 1848372
- NSF-PAR ID:
- 10432275
- Date Published:
- Journal Name:
- Geoscientific Model Development
- Volume:
- 16
- Issue:
- 9
- ISSN:
- 1991-9603
- Page Range / eLocation ID:
- 2323 to 2342
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/gmd-16-2323-2023
