The Pleim–Xiu land surface model, Pleim surface layer scheme, and Asymmetric Convective Model (version 2) are now options in version 3.0 of the Weather Research and Forecasting model (WRF) Advanced ...Research WRF (ARW) core. These physics parameterizations were developed for the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) and have been used extensively by the air quality modeling community, so there was a need based on several factors to extend these parameterizations to WRF. Simulations executed with the new WRF physics are compared with simulations produced with the MM5 and another WRF configuration with a focus on the replication of near-surface meteorological conditions and key planetary boundary layer features. The new physics in WRF is recommended for retrospective simulations, in particular, those used to drive air quality simulations. In the summer, the error of all variables analyzed was slightly lower across the domain in the WRF simulation that used the new physics than in the similar MM5 configuration. This simulation had an even lower error than the other more common WRF configuration. For the cold season case, the model simulation was not as accurate as the other simulations overall, but did well in terms of lower 2-m temperature error in the western part of the model domain (plains and Rocky Mountains) and most of the Northeast. Both MM5 and the other WRF configuration had lower errors across much of the southern and eastern United States in the winter. The 2-m water vapor mixing ratio and 10-m wind were generally well simulated by the new physics suite in WRF when contrasted with the other simulations and modeling studies. Simulated planetary boundary layer features were compared with both wind profiler and aircraft observations, and the new WRF physics results in a more precise wind and temperature structure not only in the stable boundary layer, but also within most of the convective boundary layer. These results suggest that the WRFperformance is now at or above the level of MM5. It is thus recommended to drive future air quality applications.
The Community Multiscale Air Quality (CMAQ) model version 5.3 (CMAQ53), released to the public in August 2019 and followed by version 5.3.1 (CMAQ531) in December 2019, contains numerous science ...updates, enhanced functionality, and improved computation efficiency relative to the previous version of the model, 5.2.1 (CMAQ521). Major science advances in the new model include a new aerosol module (AERO7) with significant updates to secondary organic aerosol (SOA) chemistry, updated chlorine chemistry, updated detailed bromine and iodine chemistry, updated simple halogen chemistry, the addition of dimethyl sulfide (DMS) chemistry in the CB6r3 chemical mechanism, updated M3Dry bidirectional deposition model, and the new Surface Tiled Aerosol and Gaseous Exchange (STAGE) bidirectional deposition model. In addition, support for the Weather Research and Forecasting (WRF) model's hybrid vertical coordinate (HVC) was added to CMAQ53 and the Meteorology-Chemistry Interface Processor (MCIP) version 5.0 (MCIP50). Enhanced functionality in CMAQ53 includes the new Detailed Emissions Scaling, Isolation and Diagnostic (DESID) system for scaling incoming emissions to CMAQ and reading multiple gridded input emission files. Evaluation of CMAQ531 was performed by comparing monthly and seasonal mean daily 8 h average (MDA8) O
and daily PM
values from several CMAQ531 simulations to a similarly configured CMAQ521 simulation encompassing 2016. For MDA8 O
, CMAQ531 has higher O
in the winter versus CMAQ521, due primarily to reduced dry deposition to snow, which strongly reduces wintertime O
bias (2-4 ppbv monthly average). MDA8 O
is lower with CMAQ531 throughout the rest of the year, particularly in spring, due in part to reduced O
from the lateral boundary conditions (BCs), which generally increases MDA8 O
bias in spring and fall ( 0.5 μg m
). For daily 24 h average PM
, CMAQ531 has lower concentrations on average in spring and fall, higher concentrations in summer, and similar concentrations in winter to CMAQ521, which slightly increases bias in spring and fall and reduces bias in summer. Comparisons were also performed to isolate updates to several specific aspects of the modeling system, namely the lateral BCs, meteorology model version, and the deposition model used. Transitioning from a hemispheric CMAQ (HCMAQ) version 5.2.1 simulation to a HCMAQ version 5.3 simulation to provide lateral BCs contributes to higher O
mixing ratios in the regional CMAQ simulation in higher latitudes during winter (due to the decreased O
dry deposition to snow in CMAQ53) and lower O
mixing ratios in middle and lower latitudes year-round (due to reduced O
over the ocean with CMAQ53). Transitioning from WRF version 3.8 to WRF version 4.1.1 with the HVC resulted in consistently higher (1.0-1.5 ppbv) MDA8 O
mixing ratios and higher PM
concentrations (0.1-0.25 μg m
) throughout the year. Finally, comparisons of the M3Dry and STAGE deposition models showed that MDA8 O
is generally higher with M3Dry outside of summer, while PM
is consistently higher with STAGE due to differences in the assumptions of particle deposition velocities to non-vegetated surfaces and land use with short vegetation (e.g., grasslands) between the two models. For ambient NH
, STAGE has slightly higher concentrations and smaller bias in the winter, spring, and fall, while M3Dry has higher concentrations and smaller bias but larger error and lower correlation in the summer.
Per- and polyfluoroalkyl substances (PFASs) have been released into the environment for decades, yet contributions of air emissions to total human exposure, from inhalation and drinking water ...contamination via deposition, are poorly constrained. The atmospheric transport and fate of a PFAS mixture from a fluoropolymer manufacturing facility in North Carolina were investigated with the Community Multiscale Air Quality (CMAQ) model applied at high resolution (1 km) and extending ∼150 km from the facility. Twenty-six explicit PFAS compounds, including GenX, were added to CMAQ using current best estimates of air emissions and relevant physicochemical properties. The new model, CMAQ-PFAS, predicts that 5% by mass of total emitted PFAS and 2.5% of total GenX are deposited within ∼150 km of the facility, with the remainder transported out. Modeled air concentrations of total GenX and total PFAS around the facility can reach 24.6 and 8500 ng m–3 but decrease to ∼0.1 and ∼10 ng m–3 at 35 km downwind, respectively. We find that compounds with acid functionality have higher deposition due to enhanced water solubility and pH-driven partitioning to aqueous media. To our knowledge, this is the first modeling study of the fate of a comprehensive, chemically resolved suite of PFAS air emissions from a major manufacturing source.
We examine the potential impacts of two additional sulfate production pathways using the Community Multiscale Air Quality modeling system. First we evaluate the impact of the aqueous-phase oxidation ...of S(IV) by nitrogen dioxide using two published rate constants, differing by 1–2 orders of magnitude. The reaction with alternate high and low rate constants enhances monthly mean wintertime sulfate by 4–20% and 0.4–1.2% respectively. The reaction does not significantly impact summertime sulfate. The higher sulfate predictions in winter compare better with the observed data as the model tends to underpredict sulfate concentrations both in winter and summer. We also investigate the potential impact of the gas-phase oxidation of sulfur dioxide by the Stabilized Criegee Intermediate (SCI) using a recently measured rate constant for its reaction with sulfur dioxide. Model results indicate that the gas-phase oxidation of sulfur dioxide by the SCI does not significantly affect sulfate concentrations due to the competing reaction of the SCI with water vapor. The current estimate of the rate constant for the SCI reaction with water vapor is too high for the SCI reaction with sulfur dioxide to significantly affect sulfate production. However, a sensitivity analysis using a lower rate constant for the water vapor reaction suggests that the SCI reaction with sulfur dioxide could potentially enhance sulfate production in the model. Further study is needed to accurately measure the rate constants of the aqueous-phase oxidation of S(IV) by nitrogen dioxide and the gas-phase reaction of the SCI with water vapor.
► Examine the impact of aqueous-phase oxidation of S(IV) by NO2 on sulfate. ► The aqueous-phase oxidation of S(IV) by NO2 increases mean winter sulfate by 4–20%. ► The aqueous-phase oxidation of S(IV) by NO2 does not increase summer sulfate. ► Examine the impact of SO2 oxidation by Stabilized Criegee Intermediate on sulfate. ► The SO2 oxidation by Stabilized Criegee Intermediate does not enhance sulfate.
The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of ...Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O
) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM
) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O
mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM
bias (PM
is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O
and PM
on average in January and July. Overall, the seasonal variation in simulated PM
generally improves in CMAQv5.1 (when considering all model updates), as simulated PM
concentrations decrease in the winter (when PM
is generally overestimated by CMAQ) and increase in the summer (when PM
is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O
mean bias, as O
tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O
is low); however, O
correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NO
(NO + NO
), VOC and SO
(SO
+ SO
) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O
due to large, widespread reductions in observed emissions.
The fourth phase of the Air Quality Model Evaluation
International Initiative (AQMEII4) is conducting a diagnostic
intercomparison and evaluation of deposition simulated by regional-scale air
quality ...models over North America and Europe. In this study, we analyze
annual AQMEII4 simulations performed with the Community Multiscale Air
Quality Model (CMAQ) version 5.3.1 over North America. These simulations
were configured with both the M3Dry and Surface Tiled Aerosol and Gas
Exchange (STAGE) dry deposition schemes available in CMAQ. A comparison of
observed and modeled concentrations and wet deposition fluxes shows that the
AQMEII4 CMAQ simulations perform similarly to other contemporary
regional-scale modeling studies. During summer, M3Dry has higher ozone
(O3) deposition velocities (Vd) and lower mixing ratios than STAGE
for much of the eastern US, while the reverse is the case over eastern
Canada and along the US West Coast. In contrast, during winter STAGE has higher
O3 Vd and lower mixing ratios than M3Dry over most of the
southern half of the modeling domain, while the reverse is the case for much
of the northern US and southern Canada. Analysis of the diagnostic
variables defined for the AQMEII4 project, i.e., grid-scale and land-use-specific effective conductances and deposition fluxes for the major dry deposition pathways, reveals generally higher summertime stomatal and
wintertime cuticular grid-scale effective conductances for M3Dry and
generally higher soil grid-scale effective conductances (for both vegetated
and bare soil) for STAGE in both summer and winter. On a domain-wide basis,
the stomatal grid-scale effective conductances account for about half of the
total O3 Vd during daytime hours in summer for both schemes.
Employing land-use-specific diagnostics, results show that daytime Vd varies
by a factor of 2 between land use (LU) categories. Furthermore, M3Dry vs. STAGE
differences are most pronounced for the stomatal and vegetated soil pathway
for the forest LU categories, with M3Dry estimating larger effective
conductances for the stomatal pathway and STAGE estimating larger effective
conductances for the vegetated soil pathway for these LU categories. Annual
domain total O3 deposition fluxes differ only slightly between M3Dry
(74.4 Tg yr−1) and STAGE (76.2 Tg yr−1), but pathway-specific fluxes to
individual LU types can vary more substantially on both annual and seasonal
scales, which would affect estimates of O3 damage to sensitive
vegetation. A comparison of two simulations differing only in their LU
classification scheme shows that the differences in LU cause seasonal mean
O3 mixing ratio differences on the order of 1 ppb across large portions
of the domain, with the differences generally being largest during summer and in
areas characterized by the largest differences in the fractional coverages
of the forest, planted and cultivated, and grassland LU categories. These
differences are generally smaller than the M3Dry vs. STAGE differences
outside the summer season but have a similar magnitude during summer.
Results indicate that the deposition impacts of LU differences are caused
by differences in the fractional coverages and spatial distributions of
different LU categories and the characterization of these categories
through variables like surface roughness and vegetation fraction in lookup
tables used in the land surface model and deposition schemes. Overall, the
analyses and results presented in this study illustrate how the diagnostic
grid-scale and LU-specific dry deposition variables adopted for AQMEII4 can
provide insights into similarities and differences between the CMAQ M3Dry
and STAGE dry deposition schemes that affect simulated pollutant budgets and
ecosystem impacts from atmospheric pollution.
Accurate regional air pollution simulation relies strongly on the accuracy of the mesoscale meteorological simulation used to drive the air quality model. The framework of the Air Quality Model ...Evaluation International Initiative (AQMEII), which involved a large international community of modeling groups in Europe and North America, offered a unique opportunity to evaluate the skill of mesoscale meteorological models for two continents for the same period. More than 20 groups worldwide participated in AQMEII, using several meteorological and chemical transport models with different configurations. The evaluation has been performed over a full year (2006) for both continents. The focus for this particular evaluation was meteorological parameters relevant to air quality processes such as transport and mixing, chemistry, and surface fluxes. The unprecedented scale of the exercise (one year, two continents) allowed us to examine the general characteristics of meteorological models’ skill and uncertainty. In particular, we found that there was a large variability between models or even model versions in predicting key parameters such as surface shortwave radiation. We also found several systematic model biases such as wind speed overestimations, particularly during stable conditions. We conclude that major challenges still remain in the simulation of meteorology, such as nighttime meteorology and cloud/radiation processes, for air quality simulation.
► Simulation of weather conditions for regional air quality prediction. ► Evaluation of an ensemble of mesoscale simulations for air quality. ► Intercomparison of weather models for air quality over North Atlantic and Europe.
Per- and polyfluoroalkyl substances (PFAS) are a large class of human-made compounds that have contaminated the global environment. One environmental entry point for PFAS is via atmospheric emission. ...Air releases can impact human health through multiple routes, including direct inhalation and contamination of drinking water following air deposition. In this work, we convert the reference dose (RfD) underlying the United States Environmental Protection Agency's GenX drinking water Health Advisory to an inhalation screening level and compare to predicted PFAS and GenX air concentrations from a fluorochemical manufacturing facility in Eastern North Carolina. We find that the area around the facility experiences ~15 days per year of GenX concentrations above the inhalation screening level we derive. We investigate the sensitivity of model predictions to assumptions regarding model spatial resolution, emissions temporal profiles, and knowledge of air emission chemical composition. Decreasing the chemical specificity of PFAS emissions has the largest impact on deposition predictions with domain-wide total deposition varying by as much as 250 % for total PFAS. However, predicted domain-wide mean and median air concentrations varied by <18 % over all scenarios tested for total PFAS. Other model features like emission temporal variability and model spatial resolution had weaker impacts on predicted PFAS deposition.
Display omitted
•We extrapolate a GenX Inhalation Screening Level from the US EPA's Reference Dose.•Modeled GenX near-source concentrations exceed this level (7.5 ng/m3) ~15 days/yr.•Chemical speciation of PFAS emissions is critical for accurate model predictions.
It is well established that there are a number of different classifications and sources of uncertainties in environmental modeling systems. Air quality models rely on two key inputs, namely, ...meteorology and emissions. When using air quality models for decision making, it is important to understand how uncertainties in these inputs affect the simulated concentrations. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. Most studies explore this uncertainty by running different meteorological models or the same model with different physics options and in some cases combinations of different meteorological and air quality models. While these have been shown to be useful techniques in some cases, we present a technique that leverages the initial condition perturbations of a weather forecast ensemble, namely, the Short‐Range Ensemble Forecast system to drive the four‐dimensional data assimilation in the Weather Research and Forecasting (WRF)‐Community Multiscale Air Quality (CMAQ) model with a key focus being the response of ozone chemistry and transport. Results confirm that a sizable spread in WRF solutions, including common weather variables of temperature, wind, boundary layer depth, clouds, and radiation, can cause a relatively large range of ozone‐mixing ratios. Pollutant transport can be altered by hundreds of kilometers over several days. Ozone‐mixing ratios of the ensemble can vary as much as 10–20 ppb or 20–30% in areas that typically have higher pollution levels.
Key Points
Ensemble FDDA results in large spread in meteorology and chemistry solutions
Key boundary layer variables like PBL height and radiation have significant variability
The uncertainty injected by ensemble FDDA caused large deviations in trajectories within a few days
Using lightning flash data from the National Lightning Detection Network with an updated lightning nitrogen oxides (NO
) emission estimation algorithm in the Community Multiscale Air Quality (CMAQ) ...model, we estimate the hourly variations in lightning NO
emissions for the summer of 2011 and simulate its impact on distributions of tropospheric ozone (O
) across the continental United States. We find that typical summer-time lightning activity across the U.S. Mountain West States (MWS) injects NO
emissions comparable to those from anthropogenic sources into the troposphere over the region. Comparison of two model simulation cases with and without lightning NO
emissions show that significant amount of ground-level O
in the MWS during the summer can be attributed to the lightning NO
emissions. The simulated surface-level O
from a model configuration incorporating lightning NO
emissions showed better agreement with the observed values than the model configuration without lightning NO
emissions. The time periods of significant reduction in bias in simulated O
between these two cases strongly correlate with the time periods when lightning activity occurred in the region. The inclusion of lightning NO
increased daily maximum 8 h O
by up to 17 ppb and improved model performance relative to measured surface O
mixing ratios in the MWS region. Analysis of model results in conjunction with lidar measurements at Boulder, Colorado during July 2014 corroborated similar impacts of lightning NO
emissions on O
emissions estimated for other summers is comparable to the 2011 air quality. The magnitude of lightning NO
estimates suggesting that summertime surface-level O
levels in the MWS region could be significantly influenced by lightning NO
.
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