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Organic nitrates contribute significantly to the total organic aerosol burden. However, the formation and loss mechanisms of particulate organic nitrates (PONs) remain poorly understood. In this study, with the CMAQ modeling system, we implement a detailed biogenic volatile organic carbon gas phase oxidation mechanism and an explicit representation of multiphase organic nitrate formation and loss, including both aqueous-phase uptake and vapor-pressure driven partitioning into organic aerosol as well as condensed-phase reactions. We find vapor-pressure dependent partitioning is the leading mechanism for formation of PONs and hydrolysis is a major loss mechanism for PON resulting in substantial amounts of organic aerosol that originate as an organic nitrate. Partitioning and hydrolysis together can produce high concentrations (up to 5 μg/m3) of PON-derived aerosols over the southeast United States. The main source of PON-derived aerosols is monoterpene nitrates that have been chemically processed to lose their nitrate functionality through aqueous chemistry. In contrast, the major portion of aqueous aerosol and in-cloud PON, which retains its nitrate moiety, are soluble isoprene nitrates. We evaluate the model using the observations from the Southern Oxidant and Aerosol Study (SOAS) campaign in the Southeast US in summer 2013 and show implementing aerosol-phase pathways for organic nitrates dramatically improves the magnitude of total alkyl nitrates (ANs) in CMAQ. The contribution of PONs to the total ANs at the SOAS site is estimated to be ~20%, a value in the range of the measurements. The predicted AN composition is shifted from monoterpene to isoprene and anthropogenic organic nitrates.

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/iodine chemistry; updated simple halogen chemistry; addition of dimethyl sulfide (DMS) chemistry in the CB6r3 chemical mechanism; updated M3Dry bi-directional deposition model; and the new Surface Tiled Aerosol and Gaseous Exchange (STAGE) bi-directional deposition model. In addition, support for the Weather Research and Forecasting (WRF) model's hybrid vertical coordinate (HVC) system 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 CMAQ53 was performed by comparing monthly and seasonal mean daily 8-hr average (MDA8) O3 and PM2.5 values from several CMAQ531 simulations to a similarly configured CMAQ521 simulation encompassing 2016. For MDA8 O3, CMAQ531 has higher O3 in the winter versus CMAQ521, due primarily to reduced dry deposition to snow, which strongly reduces wintertime O3 bias. MDA8 O3 is lower with CMAQ531 throughout the rest of the year, particularly in spring, due in part to reduced O3 from the lateral boundary conditions (BCs), which generally increases MDA8 O3 bias in spring and fall. For daily 24-hr average PM2.5, CMAQ531 has lower concentrations on average in spring and fall, higher concentrations in summer, and similar concentrations in winter as CMAQ521, which slightly increases bias in spring and fall and reduces bias in summer. Comparisons isolating updates to several specific aspects of the modeling system, namely the lateral BCs, meteorology model version, and the deposition model used, were also performed. 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 O3 mixing ratios in the regional CMAQ simulation in higher latitudes during winter (due to the decreased O3 dry deposition to snow in CMAQ53) and lower O3 mixing ratios in mid and lower latitudes year-round (due to reduced O3 over the ocean with CMAQ53). Transitioning from WRF version 3.8 to WRF version 4.1.1 with the HVC system resulted in consistently higher (1.0-1.5 ppbv) MDA8 O3 mixing ratios and higher PM2.5 concentrations (0.1-0.25 µg m-3) throughout the year. Finally, comparisons of the M3Dry and STAGE deposition models showed that MDA8 O3 is generally higher with M3Dry outside of summer, while PM2.5 is consistently higher with STAGE due to differences in the assumptions of particle deposition velocities to some surfaces between the two models. For ambient NH3, 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. [ABSTRACT FROM AUTHOR]

We present the development of a multiphase adjoint for the Community Multiscale Air Quality (CMAQ) model, a widely used chemical transport model. The adjoint provides location- and time-specific gradients that can be used in various applications such as backward sensitivity analysis, source attribution, optimal pollution control, data assimilation and inverse modeling. The science processes of the CMAQ model include gas-phase chemistry, aerosols, cloud chemistry and dynamics, diffusion and advection. Discrete adjoints are implemented for all the science processes, with an additional continuous adjoint for advection. The development of discrete adjoints is assisted with Algorithmic Differentiation (AD) tools. Particularly, the Kinetic PreProcessor (KPP) is implemented for gas-phase and aqueous chemistry, and two different automatic differentiation tools are used for other processes such as clouds, aerosols, diffusion, and advection. The continuous adjoint of advection is developed manually. For adjoint validation, the brute-force or Finite Difference Method (FDM) is implemented process by process with box- or column-model simulations. Due to the inherent limitations of the FDM caused by numerical round-off errors, the Complex Variable Method (CVM) is adopted where necessary. The adjoint model often shows better agreement with the CVM than with the FDM. The adjoints of all science processes compare favorably with the FDM/CVM. In an example application of the full, multiphase adjoint model, we provide the first estimates of how emissions of PM2.5 affect public health across the US. [ABSTRACT FROM AUTHOR]

Acidity, defined as pH, is a central component of aqueous chemistry. In the atmosphere, the acidity of condensed phases (aerosol particles, cloud water, and fog droplets) governs the phase partitioning of semi-volatile gases such as HNO3, NH3, and HCl, as well as chemical reaction rates. It has implications for the atmospheric lifetime of pollutants, deposition, and human health. Despite its fundamental role in atmospheric processes, only recently has this field seen a growth in the number of studies on particle acidity. Even with this growth, many fine particle pH estimates must be based on thermodynamic model calculations since no operational techniques exist for direct measurements. Current information indicates acidic fine particles are ubiquitous, but observationally-constrained pH estimates are limited in spatial and temporal coverage. Clouds and fogs are also generally acidic, but to a lesser degree than particles, and have a range of pH that is quite sensitive to anthropogenic emissions of sulfur and nitrogen oxides, as well as ambient ammonia. Historical measurements indicate that cloud and fog droplet pH has changed in recent decades in response to controls on anthropogenic emissions, while the limited trend data for aerosol particles indicates acidity may be relatively constant due to the semi-volatile nature of the key acids and bases and buffering in particles. This paper reviews and synthesizes the current state of knowledge on the acidity of atmospheric condensed phases, specifically particles and cloud droplets. It includes recommendations for estimating acidity and pH, standard nomenclature, a synthesis of current pH estimates based on observations, and new model calculations on the local and global scale. [ABSTRACT FROM AUTHOR]

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multi-pollutant air quality modeling system developed and maintained by the U.S. 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 which incorporates a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include 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 generally result in greater afternoon and early evening mixing in the model, times when the model historically underestimates mixing. The result is higher ozone (O3) mixing ratios on average due to reduced NO titration and lower fine particulate matter (PM2.5) 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 O3 mixing ratios, primarily due to reduced cloudiness and reduced attenuation of photolysis in the model. Updates to the aerosol chemistry results in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing PM2.5 bias, while updates to the gas chemistry result in generally increased O3 in January and July (small) and slightly higher PM2.5 concentrations on average in both January and July. Overall, seasonal variation in simulated PM2.5 generally improves in the new model version, as concentrations decrease in the winter (when PM2.5 is overestimated by CMAQ v5.0.2) and increase in the summer (when PM2.5 is underestimated by CMAQ v5.0.2). Ozone mixing ratios are higher on average with v5.1 versus v5.0.2, resulting in higher O3 mean bias, as O3 tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O3 is low), however both the error and correlation are largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios showed that v5.1 tends to be slightly more responsive to reductions in NOx (NO + NO2), VOC and SOx (SO2 + SO4) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O3 due to large, widespread reductions in observed emissions. Finally, the computational efficiency of the model was significantly improved in v5.1, which keeps runtimes similar to v5.0.2 despite the added complexity to the model. [ABSTRACT FROM AUTHOR]