A database and tool for boundary conditions for regional air quality modeling: description and evaluation

Transported air pollutants receive increasing attention as regulations tighten and global concentrations increase. The need to represent international transport in regional air quality assessments requires improved representation of boundary concentrations. Currently available observations are too sparse vertically to provide boundary information, particularly for ozone precursors, but global simulations can be used to generate spatially and temporally varying lateral boundary conditions (LBC). This study presents a public database of global simulations designed and evaluated for use as LBC for air quality models (AQMs). The database covers the contiguous United States (CONUS) for the years 2001–2010 and contains hourly varying concentrations of ozone, aerosols, and their precursors. The database is complemented by a tool for configuring the global results as inputs to regional scale models (e.g., Community Multiscale Air Quality or Comprehensive Air quality Model with extensions). This study also presents an example application based on the CONUS domain, which is evaluated against satellite retrieved ozone and carbon monoxide vertical profiles. The results show performance is largely within uncertainty estimates for ozone from the Ozone Monitoring Instrument and carbon monoxide from the Measurements Of Pollution In The Troposphere (MOPITT), but there were some notable biases compared with Tropospheric Emission Spectrometer (TES) ozone. Compared with TES, our ozone predictions are high-biased in the upper troposphere, particularly in the south during January. This publication documents the global simulation database, the tool for conversion to LBC, and the evaluation of concentrations on the boundaries. This documentation is intended to support applications that require representation of long-range transport of air pollutants

A comparison of atmospheric composition using the Carbon Bond and Regional Atmospheric Chemistry Mechanisms

We incorporate the recently developed Regional Atmospheric Chemistry Mechanism (version 2, RACM2) into the Community Multiscale Air Quality modeling system for comparison with the existing 2005 Carbon Bond mechanism with updated toluene chemistry (CB05TU). Compared to CB05TU, RACM2 enhances the domain-wide monthly mean hydroxyl radical concentrations by 46% and nitric acid by 26%. However, it reduces hydrogen peroxide by 2%, peroxyacetic acid by 94%, methyl hydrogen peroxide by 19%, peroxyacetyl nitrate by 40%, and organic nitrate by 41%. RACM2 enhances ozone compared to CB05TU at all ambient levels. Although it exhibited greater overestimates at lower observed concentrations, it displayed an improved performance at higher observed concentrations. The RACM2 ozone predictions are also supported by increased ozone production efficiency that agrees better with observations. Compared to CB05TU, RACM2 enhances the domain-wide monthly mean sulfate by 10%, nitrate by 6%, ammonium by 10%, anthropogenic secondary organic aerosols by 42%, biogenic secondary organic aerosols by 5%, and in-cloud secondary organic aerosols by 7%. Increased inorganic and organic aerosols with RACM2 agree better with observed data. Any air pollution control strategies developed using the two mechanisms do not differ appreciably

Understanding the impact of recent advances in isoprene photooxidation on simulations of regional air quality

The CMAQ (Community Multiscale Air Quality) us model in combination with observations for INTEX-NA/ICARTT (Intercontinental Chemical Transport Experiment–North America/International Consortium for Atmospheric Research on Transport and Transformation) 2004 are used to evaluate recent advances in isoprene oxidation chemistry and provide constraints on isoprene nitrate yields, isoprene nitrate lifetimes, and NO_x recycling rates. We incorporate recent advances in isoprene oxidation chemistry into the SAPRC-07 chemical mechanism within the US EPA (United States Environmental Protection Agency) CMAQ model. The results show improved model performance for a range of species compared against aircraft observations from the INTEX-NA/ICARTT 2004 field campaign. We further investigate the key processes in isoprene nitrate chemistry and evaluate the impact of uncertainties in the isoprene nitrate yield, NO_x (NO_x = NO + NO_2) recycling efficiency, dry deposition velocity, and RO_2 + HO_2 reaction rates. We focus our examination on the southeastern United States, which is impacted by both abundant isoprene emissions and high levels of anthropogenic pollutants. We find that NO_x concentrations increase by 4–9% as a result of reduced removal by isoprene nitrate chemistry. O3 increases by 2 ppbv as a result of changes in NO_x. OH concentrations increase by 30%, which can be primarily attributed to greater HO_x production. We find that the model can capture observed total alkyl and multifunctional nitrates (∑ANs) and their relationship with O_3 by assuming either an isoprene nitrate yield of 6% and daytime lifetime of 6 hours or a yield of 12% and lifetime of 4 h. Uncertainties in the isoprene nitrates can impact ozone production by 10% and OH concentrations by 6%. The uncertainties in NO_x recycling efficiency appear to have larger effects than uncertainties in isoprene nitrate yield and dry deposition velocity. Further progress depends on improved understanding of isoprene oxidation pathways, the rate of NOx recycling from isoprene nitrates, and the fate of the secondary, tertiary, and further oxidation products of isoprene

Evaluation of simulated photochemical partitioning of oxidized nitrogen in the upper troposphere

Regional and global chemical transport models underpredict NOx (NO + NO2) in the upper troposphere where it is a precursor to the greenhouse gas ozone. The NOx bias has been shown in model evaluations using aircraft data (Singh et al., 2007) and total column NO2 (molecules cm−2) from satellite observations (Napelenok et al., 2008). The causes of NOx underpredictions have yet to be fully understood due to the interconnected nature of simulated emission, transport, and chemistry processes. Recent observation-based studies, in the upper troposphere, identify chemical rate coefficients as a potential source of error (Olson et al., 2006; Ren et al., 2008). Since typical chemistry evaluation techniques are not available for upper tropospheric conditions, this study develops an evaluation platform from in situ observations, stochastic convection, and deterministic chemistry. We derive a stochastic convection model and optimize it using two simulated datasets of time since convection, one based on meteorology, and the other on chemistry. The chemistry surrogate for time since convection is calculated using seven different chemical mechanisms, all of which predict shorter time since convection than our meteorological analysis. We evaluate chemical simulations by inter-comparison and by pairing results with observations based on NOx:HNO3, a photochemical aging indicator. Inter-comparison reveals individual chemical mechanism biases and recommended updates. Evaluation against observations shows that all chemical mechanisms overpredict NOx removal relative to long-lived methanol and carbon monoxide. All chemical mechanisms underpredict observed NOx by at least 30%, and further evaluation is necessary to refine simulation sensitivities to initial conditions and chemical rate uncertainties

Evaluation of simulated photochemical partitioning of oxidized nitrogen in the upper troposphere

Regional and global chemical transport models underpredict NO<sub>x</sub> (NO + NO<sub>2</sub>) in the upper troposphere where it is a precursor to the greenhouse gas ozone. The NO<sub>x</sub> bias has been shown in model evaluations using aircraft data (Singh et al., 2007) and total column NO<sub>2</sub> (molecules cm<sup>−2</sup>) from satellite observations (Napelenok et al., 2008). The causes of NO<sub>x</sub> underpredictions have yet to be fully understood due to the interconnected nature of simulated emission, transport, and chemistry processes. Recent observation-based studies, in the upper troposphere, identify chemical rate coefficients as a potential source of error (Olson et al., 2006; Ren et al., 2008). Since typical chemistry evaluation techniques are not available for upper tropospheric conditions, this study develops an evaluation platform from in situ observations, stochastic convection, and deterministic chemistry. We derive a stochastic convection model and optimize it using two simulated datasets of time since convection, one based on meteorology, and the other on chemistry. The chemistry surrogate for time since convection is calculated using seven different chemical mechanisms, all of which predict shorter time since convection than our meteorological analysis. We evaluate chemical simulations by inter-comparison and by pairing results with observations based on NO<sub>x</sub>:HNO<sub>3</sub>, a photochemical aging indicator. Inter-comparison reveals individual chemical mechanism biases and recommended updates. Evaluation against observations shows that all chemical mechanisms overpredict NO<sub>x</sub> removal relative to long-lived methanol and carbon monoxide. All chemical mechanisms underpredict observed NO<sub>x</sub> by at least 30%, and further evaluation is necessary to refine simulation sensitivities to initial conditions and chemical rate uncertainties

Sensitivity of northeastern US surface ozone predictions to the representation of atmospheric chemistry in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMMv1.0)

Chemical mechanisms describe how emissions of gases and particles evolve in the atmosphere and are used within chemical transport models to evaluate past, current, and future air quality. Thus, a chemical mechanism must provide robust and accurate predictions of air pollutants if it is to be considered for use by regulatory bodies. In this work, we provide an initial evaluation of the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMMv1.0) by assessing CRACMMv1.0 predictions of surface ozone (O3) across the northeastern US during the summer of 2018 within the Community Multiscale Air Quality (CMAQ) modeling system. CRACMMv1.0 O3 predictions of hourly and maximum daily 8 h average (MDA8) ozone were lower than those estimated by the Regional Atmospheric Chemistry Mechanism with aerosol module 6 (RACM2_ae6), which better matched surface network observations in the northeastern US (RACM2_ae6 mean bias of +4.2 ppb for all hours and +4.3 ppb for MDA8; CRACMMv1.0 mean bias of +2.1 ppb for all hours and +2.7 ppb for MDA8). Box model calculations combined with results from CMAQ emission reduction simulations indicated a high sensitivity of O3 to compounds with biogenic sources. In addition, these calculations indicated the differences between CRACMMv1.0 and RACM2_ae6 O3 predictions were largely explained by updates to the inorganic rate constants (reflecting the latest assessment values) and by updates to the representation of monoterpene chemistry. Updates to other reactive organic carbon systems between RACM2_ae6 and CRACMMv1.0 also affected ozone predictions and their sensitivity to emissions. Specifically, CRACMMv1.0 benzene, toluene, and xylene chemistry led to efficient NOx cycling such that CRACMMv1.0 predicted controlling aromatics reduces ozone without rural O3 disbenefits. In contrast, semivolatile and intermediate-volatility alkanes introduced in CRACMMv1.0 acted to suppress O3 formation across the regional background through the sequestration of nitrogen oxides (NOx) in organic nitrates. Overall, these analyses showed that the CRACMMv1.0 mechanism within the CMAQ model was able to reasonably simulate ozone concentrations in the northeastern US during the summer of 2018 with similar magnitude and diurnal variation as the current operational Carbon Bond (CB6r3_ae7) mechanism and good model performance compared to recent modeling studies in the literature.</p

Intracellular Phospholipase A1 and Acyltransferase, Which Are Involved in Caenorhabditis elegans Stem Cell Divisions, Determine the sn-1 Fatty Acyl Chain of Phosphatidylinositol

Phosphatidylinositol (PI) is unique in the abundance of stearic acid at the sn-1 position. This fatty acid is thought to be incorporated through fatty acid remodeling. Here, we identified a phospholipase and acyltransferases involved in the fatty acid remodeling at the sn-1 position of PI and provide a link between the sn-1 fatty acid of PI and asymmetric cell division

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosenbrock solver (Rodas3) to integrate the stiff system of ordinary differential equations (ODEs) that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds. CMAQ's standard cloud chemistry module (AQCHEM) is structurally limited to the treatment of a simple chemical mechanism. This work advances our ability to test and implement more sophisticated aqueous chemical mechanisms in CMAQ and further investigate the impacts of microphysical parameters on cloud chemistry. Box model cloud chemistry simulations were performed to choose efficient solver and tolerance settings, evaluate the implementation of the KPP solver, and assess the direct impacts of alternative solver and kinetic mass transfer on predicted concentrations for a range of scenarios. Month-long CMAQ simulations for winter and summer periods over the US reveal the changes in model predictions due to these cloud module updates within the full chemical transport model. While monthly average CMAQ predictions are not drastically altered between AQCHEM and AQCHEM − KMT, hourly concentration differences can be significant. With added in-cloud secondary organic aerosol (SOA) formation from biogenic epoxides (AQCHEM − KMTI), normalized mean error and bias statistics are slightly improved for 2-methyltetrols and 2-methylglyceric acid at the Research Triangle Park measurement site in North Carolina during the Southern Oxidant and Aerosol Study (SOAS) period. The added in-cloud chemistry leads to a monthly average increase of 11–18 % in cloud SOA at the surface in the eastern United States for June 2013