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Dry deposition of ozone is an important sink of ozone in near surface air. When dry deposition occurs through plant stomata, ozone can injure the plant, altering water and carbon cycling and reducing crop yields. Quantifying both stomatal and nonstomatal uptake accurately is relevant for understanding ozone's impact on human health as an air pollutant and on climate as a potent short-lived greenhouse gas and primary control on the removal of several reactive greenhouse gases and air pollutants. Robust ozone dry deposition estimates require knowledge of the relative importance of individual deposition pathways, but spatiotemporal variability in nonstomatal deposition is poorly understood. Here we integrate understanding of ozone deposition processes by synthesizing research from fields such as atmospheric chemistry, ecology, and meteorology. We critically review methods for measurements and modeling, highlighting the empiricism that underpins modeling and thus the interpretation of observations. Our unprecedented synthesis of knowledge on deposition pathways, particularly soil and leaf cuticles, reveals process understanding not yet included in widely-used models. If coordinated with short-term field intensives, laboratory studies, and mechanistic modeling, measurements from a few long-term sites would bridge the molecular to ecosystem scales necessary to establish the relative importance of individual deposition pathways and the extent to which they vary in space and time. Our recommended approaches seek to close knowledge gaps that currently limit quantifying the impact of ozone dry deposition on air quality, ecosystems, and climate.

There are myriad connections between air pollution and terrestrial ecosystems, but for many of the associated important elements and processes there is limited process understanding and hence predictive ability. Building [...]

Agricultural soils containing nitrogen‐rich fertilizers are a substantial source of reactive nitrogen to the atmosphere with potential to impact air quality. One form of reactive nitrogen, nitrogen oxides (NOx = NO + NO2), are a harmful air pollutant and form secondary pollutants, including particulate matter (PM) and ozone (O3). Soil nitrogen oxide emissions (SNOx) are heavily influenced by environmental conditions, however the understanding of the influence of environmental drivers on the behavior of SNOx is limited. Here, we implement a modified soil moisture‐dependent SNOx parameterization into the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem) and investigate the impact on regional air quality in the central U.S. Evaluating against TROPOspheric Monitoring Instrument (TROPOMI) column NO2 observations, WRF‐Chem columns better capture the TROPOMI column magnitudes earlier in the growing season when using the updated SNOx parametrization, with modeled column bias improved to −1.1% over the most heavily fertilized regions. Evaluating against Environmental Protection Agency (EPA) surface NO2 observations, the relationship between surface NO2 and soil moisture is better represented in agriculturally‐dominant regions when using the updated parameterization, with greatest surface NO2 concentrations at moderate soil moisture and lower concentrations at wetter or drier soil conditions. In simulations, these SNOx lead to increased O3 in select urban regions, with more than double the occurrences of O3 exceeding the EPA 8‐hr O3 standard of 70 ppb. Plain Language Summary: In cropland areas where large quantities of fertilizers are commonly used, emissions of nitrogen oxides (NOx) from soils can significantly impact air quality. While harmful on its own, NOx contributes to the formation of additional harmful air pollutants like particulate matter and ozone, posing risks to human and environmental health. Our understanding of the factors influencing soil NOx emissions remains limited. In this study, we integrated a new approach for estimating soil NOx emissions into a regional atmospheric model, with a focus on soil moisture impacts. By comparing model results with satellite and surface observations, we found that this new approach better captures the magnitudes and distribution of NOx concentrations, particularly in agricultural areas. Our simulations suggest that soil NOx emissions can exacerbate urban air pollution as well, increasing the frequency of pollutant levels surpassing regulatory standards. Additionally, we show that surface observations of NOx in cropland regions display a distinct relationship with soil moisture, with largest concentrations at moderate soil moisture values, as opposed to wet or dry conditions. Key Points: Simulated NO2 column bias is reduced over U.S. cropland in mid‐April to mid‐July when using a soil moisture‐dependent soil NOx schemeSurface air quality sites near cropland show higher NO2 at moderate soil moisture, and lower NO2 at relatively wet and dry soil moistureCropland soil NO emissions increase simulated surface O3 concentrations in downwind urban areas [ABSTRACT FROM AUTHOR]

Anemophilous (wind‐driven) pollen is one type of primary biological aerosol particle, which can rupture under high humidity conditions and form smaller sub‐pollen particles (SPPs). Both pollen and SPPs can reach the upper troposphere under convective conditions, acting as cloud condensation nuclei (CCN) and ice nucleating particles (INPs), thus influencing cloud formation and precipitation. However, the impacts of these biological aerosols on cold cloud formation and local climate remain unclear as there are large uncertainties on their emission flux and ice nucleating abilities. Here, we incorporate pollen emission and rupture processes in the Weather Research and Forecasting Model with Chemistry (WRF‐Chem) simulations and update the Morrison microphysics scheme within WRF‐Chem using aerosol‐aware INP parameterizations to account for pollen in addition to other anthropogenic and biogenic aerosol. INP parameterizations for pollen and SPP are derived from laboratory experiments. When including pollen rupture rates as observed in a series of chamber studies, SPP concentrations increase, leading to an increase of cloud ice and water by up to 50% and potentially extending the duration of the convective system. Among all simulated hydrometeors, graupel and raindrops exhibit the largest enhancements from the inclusion of SPPs, with intensifying precipitation at the backside of the convective system and a greater spatial extent. Sensitivity simulations indicate that SPPs have a greater effect on cloud microphysical processes than whole pollen grains, and further observational evidence is needed to constrain these processes. Plain Language Summary: Pollen grains are emitted by vegetation and carry the reproductive material of plants. Under certain conditions (e.g., high humidity, lightning), pollen grains can rupture to form smaller sub‐pollen particles (SPPs). Both intact pollen grain and SPPs have been observed to influence the formation of cloud liquid droplets and ice crystals, potentially impacting cloud properties and precipitation. In this study, we include pollen emission and pollen‐cloud interactions into a meteorology‐chemistry model and investigate the effects of pollen grains and SPPs on a strong thunderstorm event associated with a mesoscale convective system. We find that SPPs have a greater impact than whole pollen grains on the convective system properties by increasing cloud ice and water content, facilitating the transition of cloud droplets and ice into graupel, and ultimately intensifying precipitation. These changes alter the impact of the convective system, leading to an extension of the storm width and lengthening of its duration. Key Points: Sub‐pollen particles (SPPs) enhance cloud microphysical processes more than intact pollen grainsSPPs influence the spatial extent and vertical structure of convective systemsSimulated SPP impacts are intensified when incorporating laboratory measured pollen rupture rates [ABSTRACT FROM AUTHOR]

Intensive air quality measurements made from June 22-25, 2011 in the outflow of the Dallas-Fort Worth (DFW) metropolitan area are used to evaluate nitrous acid (HONO) sources and sinks. A two-layer box model was developed to assess the ability of established and recently identified HONO sources and sinks to reproduce observations of HONO mixing ratios. A baseline model scenario includes sources and sinks established in the literature and is compared to scenarios including three recently identified sources: volatile organic compound-mediated conversion of nitric acid to HONO (S1), biotic emission from the ground (S2), and re-emission from a surface nitrite reservoir (S3). For all mechanisms, ranges of parametric values span lower- and upper-limit values. Model outcomes for 'likely' estimates of sources and sinks generally show under-prediction of HONO observations, implying the need to evaluate additional sources and variability in estimates of parameterizations, particularly during daylight hours. Monte Carlo simulation is applied to model scenarios constructed with sources S1-S3 added independently and in combination, generally showing improved model outcomes. Adding sources S2 and S3 (scenario S2/S3) appears to best replicate observed HONO, as determined by the model coefficient of determination and residual sum of squared errors (r2 = 0.55 ± 0.03, SSE = 4.6 × 106 ± 7.6 × 105 ppt2). In scenario S2/S3, source S2 is shown to account for 25% and 6.7% of the nighttime and daytime budget, respectively, while source S3 accounts for 19% and 11% of the nighttime and daytime budget, respectively. However, despite improved model fit, there remains significant underestimation of daytime HONO; on average, a 0.15 ppt/s unknown daytime HONO source, or 67% of the total daytime source, is needed to bring scenario S2/S3 into agreement with observation. Estimates of 'best fit' parameterizations across lower to upper-limit values results in a moderate reduction of the unknown daytime source, from 0.15 to 0.10 ppt/s.

Abstract Rapid and broad-scale forest mortality associated with recent droughts, rising temperature, and insect outbreaks has been observed over western North America (NA). Climate models project additional future warming and increasing drought and water stress for this region. To assess future potential changes in vegetation distributions in western NA, the Community Earth System Model (CESM) coupled with its Dynamic Global Vegetation Model (DGVM) was used under the future A2 emissions scenario. To better span uncertainties in future climate, eight sea surface temperature (SST) projections provided by phase 3 of the Coupled Model Intercomparison Project (CMIP3) were employed as boundary conditions. There is a broad consensus among the simulations, despite differences in the simulated climate trajectories across the ensemble, that about half of the needleleaf evergreen tree coverage (from 24% to 11%) will disappear, coincident with a 14% (from 11% to 25%) increase in shrubs and grasses by the end of the twenty-first century in western NA, with most of the change occurring over the latter half of the twenty-first century. The net impact is a ~6 GtC or about 50% decrease in projected ecosystem carbon storage in this region. The findings suggest a potential for a widespread shift from tree-dominated landscapes to shrub and grass-dominated landscapes in western NA because of future warming and consequent increases in water deficits. These results highlight the need for improved process-based understanding of vegetation dynamics, particularly including mortality and the subsequent incorporation of these mechanisms into earth system models to better quantify the vulnerability of western NA forests under climate change.