Abstract. We develop and evaluate a method to estimate O3 deposition and stomatal O3 uptake across networks of eddy covariance flux tower sites where O3 concentrations and O3 fluxes have not been measured. The method combines standard micrometeorological flux measurements, which constrain O3 deposition velocity and stomatal conductance, with a gridded dataset of observed surface O3 concentrations. Measurement errors are propagated through all calculations to quantify O3 flux uncertainties. We evaluate the method at three sites with O3 flux measurements: Harvard Forest, Blodgett Forest, and Hyytiälä Forest. The method reproduces 83 % or more of the variability in daily stomatal uptake at these sites with modest mean bias (21 % or less). At least 95 % of daily average values agree with measurements within a factor of 2 and, according to the error analysis, the residual differences from measured O3 fluxes are consistent with the uncertainty in the underlying measurements. The product, called synthetic O3 flux or SynFlux, includes 43 FLUXNET sites in the United States and 60 sites in Europe, totaling 926 site years of data. This dataset, which is now public, dramatically expands the number and types of sites where O3 fluxes can be used for ecosystem impact studies and evaluation of air quality and climate models. Across these sites, the mean stomatal conductance and O3 deposition velocity is 0.03–1.0 cm s−1. The stomatal O3 flux during the growing season (typically April–September) is 0.5–11.0 nmol O3 m−2 s−1 with a mean of 4.5 nmol O3 m−2 s−1 and the largest fluxes generally occur where stomatal conductance is high, rather than where O3 concentrations are high. The conductance differences across sites can be explained by atmospheric humidity, soil moisture, vegetation type, irrigation, and land management. These stomatal fluxes suggest that ambient O3 degrades biomass production and CO2 sequestration by 20 %–24 % at crop sites, 6 %–29 % at deciduous broadleaf forests, and 4 %–20 % at evergreen needleleaf forests in the United States and Europe.

Abstract. We present in this technical note the research protocol for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This research initiative is divided into two activities, collectively having three goals: (i) to define the current state of the science with respect to representations of wet and especially dry deposition in regional models, (ii) to quantify the extent to which different dry deposition parameterizations influence retrospective air pollutant concentration and flux predictions, and (iii) to identify, through the use of a common set of detailed diagnostics, sensitivity simulations, model evaluation, and reduction of input uncertainty, the specific causes for the current range of these predictions. Activity 1 is dedicated to the diagnostic evaluation of wet and dry deposition processes in regional air quality models (described in this paper), and Activity 2 to the evaluation of dry deposition point models against ozone flux measurements at multiple towers with multiyear observations (to be described in future submissions as part of the special issue on AQMEII4). The scope of this paper is to present the scientific protocols for Activity 1, as well as to summarize the technical information associated with the different dry deposition approaches used by the participating research groups of AQMEII4. In addition to describing all common aspects and data used for this multi-model evaluation activity, most importantly, we present the strategy devised to allow a common process-level comparison of dry deposition obtained from models using sometimes very different dry deposition schemes. The strategy is based on adding detailed diagnostics to the algorithms used in the dry deposition modules of existing regional air quality models, in particular archiving diagnostics specific to land use–land cover (LULC) and creating standardized LULC categories to facilitate cross-comparison of LULC-specific dry deposition parameters and processes, as well as archiving effective conductance and effective flux as means for comparing the relative influence of different pathways towards the net or total dry deposition. This new approach, along with an analysis of precipitation and wet deposition fields, will provide an unprecedented process-oriented comparison of deposition in regional air quality models. Examples of how specific dry deposition schemes used in participating models have been reduced to the common set of comparable diagnostics defined for AQMEII4 are also presented.

Abstract. We present in this technical note the research protocol for Phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This research initiative is divided in two activities, collectively having three goals: (i) to define the current state of the science with respect to representations of wet and especially dry deposition in regional models, (ii) to quantify the extent to which different dry deposition parameterizations influence retrospective air pollutant concentration and flux predictions, and (iii) to identify, through the use of a common set of detailed diagnostics, sensitivity simulations, model evaluation, and reducing input uncertainty, the specific causes for the current range of these predictions. Activity 1 is dedicated to the diagnostic evaluation of wet and dry deposition processes in regional air quality models (described in this paper), and Activity 2 to the evaluation of dry deposition point models against ozone flux measurements at multiple towers with multiyear observations (Part 2). The scope of these papers is to present the scientific protocols for AQMEII4, as well to summarize the technical information associated with the different dry deposition approaches used by the participating research groups of AQMEII4. In addition to describing all common aspects and data used for this multi-model evaluation activity, most importantly, we present the strategy devised to allow a common process-level comparison of dry deposition obtained from models using sometimes very different dry deposition schemes. The strategy is based on adding detailed diagnostics to the algorithms used in the dry deposition modules of existing regional air quality models, in particular archiving land use/land cover (LULC)-specific diagnostics and creating standardized LULC categories to facilitate cross-comparison of LULC-specific dry deposition parameters and processes, as well as archiving effective conductance and effective flux as means for comparing the relative influence of different pathways towards the net or total dry deposition. This new approach, along with an analysis of precipitation and wet deposition fields, will provide an unprecedented process-oriented comparison of deposition in regional air-quality models. Examples of how specific dry deposition schemes used in participating models have been reduced to the common set of comparable diagnostics defined for AQMEII4 are also presented.

Peak levels of ozone (O3)—quantified by concentration metrics such as accumulated O3 exposure over a threshold of 40 ppb (AOT40) and the sigmoidal-weighted cumulative exposure (W126)—have decreased over large parts of the United States and Europe in the last several decades. Past studies have suggested that these improvements in AOT40 and W126 indicate reductions in plant injury, even though it is widely recognized that O3 flux into leaves, not ambient O3 concentration, is the cause of plant damage. Using a new dataset of O3 uptake into plants derived from eddy covariance flux towers, we test whether AOT40, W126, or summer mean O3 are useful indicators of trends in the cumulative uptake of O3 into leaves, which is the phytotoxic O3 dose (POD or PODy, where y is a detoxification threshold). At 32 sites in the United States and Europe, we find that the AOT40 and W126 concentration metrics decreased over 2005–2014 at most sites: 25 and 28 sites, respectively. POD0, however, increased at a majority (18) of the sites. Multiple statistical tests demonstrate that none of the concentration metrics—AOT40, W126, and mean O3—are good predictors of POD0 temporal trends or variability (R2 ≤ 0.15). These results are insensitive to using a detoxification threshold (POD3). The divergent trends for O3 concentration and plant uptake are due to stomatal control of flux, which is shaped by environmental variability and plant factors. As a result, there has been no widespread, clear improvement in POD over 2005–2014 at the sites we can assess. Decreases in concentration metrics, therefore, give an overly optimistic and incomplete picture of the direction and magnitude of O3 impacts on vegetation. Because of this lack of relation between O3 flux and concentration, flux metrics should be preferred over concentration metrics in assessments of plant injury from O3.

No abstract

Abstract. Dry deposition is a key process for surface ozone (O3) removal. Stomatal uptake is a major component of O3 dry deposition, which is parameterized differently in current land surface models and chemical transport models. We developed and used a standalone terrestrial biosphere model, driven by a unified set of prescribed meteorology, to evaluate two widely used dry deposition modeling frameworks, Wesely (1989) and Zhang et al. (2003), with different configurations of stomatal resistance: (1) the default multiplicative method in the Wesely scheme (W89) and Zhang et al. (2003) scheme (Z03), (2) the traditional photosynthesis-based Farquhar–Ball–Berry (FBB) stomatal algorithm, and (3) the Medlyn stomatal algorithm (MED) based on optimization theory. We found that using the FBB stomatal approach that captures ecophysiological responses to environmental factors, especially to water stress, can generally improve the simulated dry deposition velocities compared with multiplicative schemes. The MED stomatal approach produces higher stomatal conductance than FBB and is likely to overestimate dry deposition velocities for major vegetation types, but its performance is greatly improved when spatially varying slope parameters based on annual mean precipitation are used. Large discrepancies were also found in stomatal responses to rising CO2 levels from 390 to 550 ppm: the multiplicative stomatal method with an empirical CO2 response function produces reduction (−35 %) in global stomatal conductance on average much larger than that with the photosynthesis-based stomatal method (−14 %–19 %). Our results show the potential biases in O3 sink caused by errors in model structure especially in the Wesely dry deposition scheme and the importance of using photosynthesis-based representation of stomatal resistance in dry deposition schemes under a changing climate and rising CO2 concentration.

Dry deposition could partially explain the observed response in ambient ozone to extreme hot and dry episodes. We examine the response of ozone deposition to heat and dry anomalies using three long‐term co‐located ecosystem‐scale carbon dioxide, water vapor and ozone flux measurement records. We find that, as expected, canopy stomatal conductance generally decreases during days with dry air or soil. However, during hot days, concurrent increases in non‐stomatal conductance are inferred at all three sites, which may be related to several temperature‐sensitive processes not represented in the current generation of big‐leaf models. This may offset the reduction in stomatal conductance, leading to smaller net reduction, or even net increase, in total deposition velocity. We find the response of deposition velocity to soil dryness may be related to its impact on photosynthetic activity, though considerable variability exists. Our findings emphasize the need for better understanding and representation of non‐stomatal ozone deposition.

Abstract. Ground-level ozone (O3) is a major air pollutant that adversely affects human health and ecosystem productivity. Removal of tropospheric O3 by plant stomatal uptake can in turn cause damage to plant tissues with ramifications for ecosystem and crop health. In many atmospheric and land surface models, the functionality of stomata opening is represented by a bulk stomatal conductance, which is often semi-empirically parameterized and highly fitted to historical observations. A lack of mechanistic linkage to ecophysiological processes such as photosynthesis 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−atmosphere exchange of important gas species in GEOS-Chem, a chemical transport model widely used in atmospheric chemistry studies. The implementation not only allows for dry deposition to be coupled with plant ecophysiology but also enables plant and crop productivity and functions to respond dynamically to atmospheric chemical changes. We conduct simulations to evaluate the effects of the ecophysiology module on simulated dry deposition velocity and concentration of surface O3 against an observation-derived dataset known as SynFlux. Our estimated stomatal conductance and dry deposition velocity of O3 are close to SynFlux with root-mean-squared errors (RMSEs) below 0.3 cm s−1 across different plant functional types (PFTs), despite an overall positive bias in surface O3 concentration (by up to 16 ppbv). Representing ecophysiology was found to reduce the simulated biases in deposition fluxes from the prior model but worsen the positive biases in simulated O3 concentrations. The increase in positive concentration biases is mostly attributable to the ecophysiology-based stomatal conductance being generally smaller (and closer to SynFlux values) than that estimated by the prior semi-empirical formulation, calling for further improvements in non-stomatal depositional and non-depositional processes relevant for O3 simulations. The estimated global O3 deposition flux is 864 Tg O3 yr−1 with GEOS-Chem, and the new module decreases this estimate by 92 Tg O3 yr−1. Estimated global gross primary 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 O3 depositional sink (−3.3 %). Global isoprene emission simulated with a photosynthesis-based scheme is 317.9 Tg C yr−1, which is 31.2 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 dynamically represents the two-way interactions between vegetation and air pollutants and thus provides a unique capability in evaluating vegetation-mediated processes and feedbacks that can shape atmospheric chemistry and air quality, as well as pollutant impacts on vegetation health, especially for any timescales shorter than the multidecadal timescale.