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At least 109 records · Page 6

Lightning NOx Statistics Derived by NASA Lightning Nitrogen Oxides Model (LNOM) Data Analyses

What is the LNOM? The NASA Marshall Space Flight Center (MSFC) Lightning Nitrogen Oxides Model (LNOM) [Koshak et al., 2009, 2010, 2011; Koshak and Peterson 2011, 2013] analyzes VHF Lightning Mapping Array (LMA) and National Lightning Detection Network(TradeMark) (NLDN) data to estimate the lightning nitrogen oxides (LNOx) produced by individual flashes. Figure 1 provides an overview of LNOM functionality. Benefits of LNOM: (1) Does away with unrealistic "vertical stick" lightning channel models for estimating LNOx; (2) Uses ground-based VHF data that maps out the true channel in space and time to < 100 m accuracy; (3) Therefore, true channel segment height (ambient air density) is used to compute LNOx; (4) True channel length is used! (typically tens of kilometers since channel has many branches and "wiggles"); (5) Distinction between ground and cloud flashes are made; (6) For ground flashes, actual peak current from NLDN used to compute NOx from lightning return stroke; (7) NOx computed for several other lightning discharge processes (based on Cooray et al., 2009 theory): (a) Hot core of stepped leaders and dart leaders, (b) Corona sheath of stepped leader, (c) K-change, (d) Continuing Currents, and (e) M-components; and (8) LNOM statistics (see later) can be used to parameterize LNOx production for regional air quality models (like CMAQ), and for global chemical transport models (like GEOS-Chem).

Koshak, William↗

The Seasonal and Interannual Variability of the Budgets of N2O and CCl3F

The 6-year wind archives from the Goddard Institute for Space Studies/Global Climate-Middle Atmosphere Model (GISS/GCMAM) were in- put to the GISS/Harvard/Irvine Chemical Transport Model (G/H/I CTM) to study the seasonal and interannual variability of the budgets and distributions of nitrous oxide (N2O) and trichlorofluoromethane (CCl3F), with the corresponding chemical loss frequencies recycled and boundary conditions kept unchanged from year to year. The effects of ozone feedback and quasi-biennial oscillation (QBO) were not included. However, the role of circulation variation in driving the lifetime variability is investigated. It was found that the global loss rates of these tracers are related to the extratropical planetary wave activity, which drives the tropical upward mass flux. For N2O, a semiannual signal in the loss rate variation is associated with the interhemispheric asymmetry in the upper stratospheric wave activity. For CCl3F, the semiannual signal is weaker, associated with the comparatively uniform wave episodes in the lower stratosphere. The loss rates lag behind the wave activity by about 1-2 months. The interannual variation of the GCM generated winds drives the interannual variation of the annually averaged lifetime. The year-to-year variations of the annually averaged lifetimes can be about 3% for N2O and 4% for CCl3F.

Wong, Sun↗

Modelling stratospheric polar ozone using objective analysis

We have studied the development of the austral ozone hole using a 3-D spectral chemical transport model at R15 resolution for the period 15th September to 15th October, 1991. The model is driven by objectively analyzed wind fields obtained from the Canadian Meteorological Center and uses the chemical module developed by Kaminski (1992). Although extensive processing of NO(y) and Cl(x) occurs within the model, the ozone hole that develops appears shallow and ephemeral. Analysis of the results indicate that the meridional transport of ozone is sufficient to overwhelm the substantial chemical depletion that does occur. We suggest that the low resolution objectively analyzed data used is unable to capture the essential isolated nature of the vortex.

Sandilands, J. W.↗

Simulation of radon-222 with the GEOS-Chem global model: Emissions, seasonality, and convective transport

Radon-222 (222Rn) is a short-lived radioactive gas naturally emitted from land surface, and has long been used to assess convective transport in atmospheric models. In this study, we simulate 222Rn using the GEOS-Chem chemical transport model with aims to improve our understanding of 222Rn emissions and surface concentration seasonality, and to characterize convective transport associated with two Goddard Earth Observing System (GEOS) meteorological products, MERRA and GEOS-FP. We evaluate four available 222Rn emission scenarios by comparing model results with surface observations at 51 global surface sites. The default emission scenario in GEOS-Chem yields a moderate agreement with global surface observations (< 70% data within a factor of 2) and a large underestimate of wintertime surface 222Rn concentrations at Northern Hemisphere mid- and high-latitudes due to an oversimplified formulation of 222Rn emission fluxes (1 atom cm-2 s-1 over land with a reduction by a factor of 3 under freezing conditions). We compose a new global 222Rn emission scenario based on Zhang et al. (2011) and show its potential to improve simulated surface 222Rn concentrations and seasonality. The regional components of this emission scenario include spatially and temporally varying emission fluxes derived from previous measurements of soil radium content and soil exhalation models, which are key factors to 222Rn emission flux rates. However, large model underestimates of surface 222Rn concentrations still exist in Asia, suggesting unusually high regional 222Rn emissions. We propose a conservative up-scaling factor of 1.2 for 222Rn emission fluxes in China, as also constrained by the observed deposition fluxes of 210Pb (decay daughter of 222Rn). With this modification, the model shows better agreement with the observations in Europe and North America (>80% data within a factor of 2), and reasonable agreement in Asia (close to 70%). Further constraints on 222Rn emissions would require additional observations of surface 222Rn concentrations and emission fluxes in central U.S., Canada, Africa, and Asia. We also compare and assess convective transport in model simulations driven by MERRA and GEOS-FP using observed 222Rn vertical profiles during northern mid-latitude summertime and from two short-term airborne campaigns. While the simulations with both GEOS products are able to capture the observed vertical gradient of 222Rn concentrations in the lower troposphere (0-4 km), neither correctly represents the level of convective detrainment, resulting in biases in the middle and upper troposphere. Compared to GEOS-FP, MERRA leads to stronger convective transport of 222Rn, which is partially compensated by its weaker large-scale vertical advection, resulting in similar global vertical distributions of 222Rn concentrations between the two simulations.

Zhang, Bo↗

A Multimodel Assessment of the Influence of Regional Anthropogenic Emission Reductions on Aerosol Direct Radiative Forcing and the Role of Intercontinental Transport

In this study, we assess changes of aerosol optical depth (AOD) and direct radiative forcing (DRF) in response to the reduction of anthropogenic emissions in four major pollution regions in the Northern Hemisphere by using results from nine global models in the framework of the Hemispheric Transport of Air Pollution (HTAP). DRF at top of atmosphere (TOA) and surface is estimated based on AOD results from the HTAP models and AOD-normalized DRF (NDRF) from a chemical transport model. The multimodel results show that, on average, a 20% reduction of anthropogenic emissions in North America, Europe, East Asia, and South Asia lowers the global mean AOD (all-sky TOA DRF) by 9.2% (9.0%), 3.5% (3.0%), and 9.4% (10.0%) for sulfate, particulate organic matter (POM), and black carbon (BC), respectively. Global annual average TOA all-sky forcing efficiency relative to particle or gaseous precursor emissions from the four regions (expressed as multimodel mean +/- one standard deviation) is -3.5 +/-0.8, -4.0 +/- 1.7, and 29.5+/-18.1mW / sq m per Tg for sulfate (relative to SO2), POM, and BC, respectively. The impacts of the regional emission reductions on AOD and DRF extend well beyond the source regions because of intercontinental transport (ICT). On an annual basis, ICT accounts for 11 +/- 5% to 31 +/- 9% of AOD and DRF in a receptor region at continental or subcontinental scale, with domestic emissions accounting for the remainder, depending on regions and species. For sulfate AOD, the largest ICT contribution of 31 +/- 9% occurs in South Asia, which is dominated by the emissions from Europe. For BC AOD, the largest ICT contribution of 28 +/- 18% occurs in North America, which is dominated by the emissions from East Asia. The large spreads among models highlight the need to improve aerosol processes in models, and evaluate and constrain models with observations.

Europe↗

Historical total ozone radiative forcing derived from CMIP6 simulations

Radiative forcing (RF) time series for total ozone from 1850 up to the present day are calculated based on historical simulations of ozone from 10 climate models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition, RF is calculated for ozone fields prepared as an input for CMIP6 models without chemistry schemes and from a chemical transport model simulation. A radiative kernel for ozone is constructed and used to derive the RF. The ozone RF in 2010 (2005–2014) relative to 1850 is 0.35 W m -2 [0.08–0.61] (5–95% uncertainty range) based on models with both tropospheric and stratospheric chemistry. One of these models has a negative present-day total ozone RF. Excluding this model, the present-day ozone RF increases to 0.39 W m -2 [0.27–0.51] (5–95% uncertainty range). The rest of the models have RF close to or stronger than the RF time series assessed by the Intergovernmental Panel on Climate Change in the fifth assessment report with the primary driver likely being the new precursor emissions used in CMIP6. The rapid adjustments beyond stratospheric temperature are estimated to be weak and thus the RF is a good measure of effective radiative forcing.

54 ENVIRONMENTAL SCIENCES↗

Historical Total Ozone Radiative Forcing Derived from CMIP6 Simulations

Radiative forcing (RF) time series for total ozone from 1850 up to present-day are calculated based on historical simulations of ozone from 10 climate models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition, RF is calculated for ozone fields prepared as input for CMIP6 models without chemistry schemes and from a chemical transport model simulation. A radiative kernel for ozone is constructed and used to derive the RF. The ozone RF in 2010 (200530 -2014) relative to 1850 is 0.35 W m-2 [0.08 to 0.61] (5-95% uncertainty range) based on models with both tropospheric and stratospheric chemistry. One of these models has a negative present-day total ozone RF. Excluding this model, the present-day ozone RF increases to 0.39 W m-2 [0.27 to 0.51] (533 - 95% uncertainty range). The rest of the models have RF close to or stronger than the RF time series assessed by the Intergovernmental Panel on Climate Change in the fifth assessment report with the primary driver likely being the new precursor emissions used in CMIP6. The rapid adjustments beyond stratospheric temperature are estimated to be weak and thus the RF is a good measure of effective radiative forcing.

ozone↗

Automated Machine Learning to Evaluate the Information Content of Tropospheric Trace Gas Columns for Fine Particle Estimates Over India: A Modeling Testbed

India is largely devoid of high-quality and reliable on-the-ground measurements of fine particulate matter (PM 2.5 ). Ground-level PM 2.5 concentrations are estimated from publicly available satellite Aerosol Optical Depth (AOD) products combined with other information. Prior research has largely overlooked the possibility of gaining additional accuracy and insights into the sources of PM using satellite retrievals of tropospheric trace gas columns. We evaluate the information content of tropospheric trace gas columns for PM 2.5 estimates over India within a modeling testbed using an Automated Machine Learning (AutoML) approach, which selects from a menu of different machine learning tools based on the data set. We then quantify the relative information content of tropospheric trace gas columns, AOD, meteorological fields, and emissions for estimating PM 2.5 over four Indian sub-regions on daily and monthly time scales. Our findings suggest that, regardless of the specific machine learning model assumptions, incorporating trace gas modeled columns improves PM 2.5 estimates. We use the ranking scores produced from the AutoML algorithm and Spearman’s rank correlation to infer or link the possible relative importance of primary versus secondary sources of PM 2.5 as a first step toward estimating particle composition. Our comparison of AutoML-derived models to selected baseline machine learning models demonstrates that AutoML is at least as good as user-chosen models. The idealized pseudo-observations (chemical-transport model simulations) used in this work lay the groundwork for applying satellite retrievals of tropospheric trace gases to estimate fine particle concentrations in India and serve to illustrate the promise of AutoML applications in atmospheric and environmental research.

Machine learning↗

Global Simulations of Phase State and Equilibration Time Scales of Secondary Organic Aerosols with GEOS-Chem

The phase state of secondary organic aerosols (SOA) can range from liquid through amorphous semisolid to glassy solid, which is important to consider as it influences various multiphase processes including SOA formation and partitioning, multiphase chemistry, and cloud activation. In this study, we simulate the glass transition temperature and viscosity of SOA over the globe using the global chemical transport model, GEOS-Chem. The simulated spatial distributions show that SOA at the surface exist as liquid over equatorial regions and oceans, semisolid in the midlatitude continental regions, and glassy solid over lands with low relative humidity. The predicted SOA viscosities are mostly consistent with the available measurements. In the free troposphere, SOA particles are mostly predicted to be semisolid at 850 hPa and glassy solid at 500 hPa, except over tropical regions including Amazonia, where SOA are predicted to be low viscous. Phase state also exhibits seasonal variation with a higher frequency of semisolid and solid particles in winter compared to warmer seasons. We calculate equilibration time scales of SOA partitioning (τ eq ) and effective mass accommodation coefficient (α eff ), indicating that τ eq is shorter than the chemical time step of GEOS-Chem of 20 min and αeff is close to unity for most locations at the surface level, supporting the application of equilibrium SOA partitioning. However, τ eq is prolonged and α eff is lowered over drylands and most regions in the upper troposphere, suggesting that kinetically limited growth would need to be considered for these regions in future large-scale model studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combining Machine Learning and Numerical Simulation for High-Resolution PM2.5 Concentration Forecast

Forecasting ambient PM2.5 concentrations with spatiotemporal coverage is key to alerting decision-makers of pollution episodes and preventing detrimental public exposure, especially in regions with limited ground air monitoring stations. The existing methods either rely on chemical transport models (CTMs) to forecast spatial distribution of PM2.5 with nontrivial uncertainty or statistical algorithms to forecast PM2.5 concentration time-series at air monitoring locations without continuous spatial coverage. In this study, we developed a PM2.5 forecast framework by combining the robust Random Forest algorithm with a publicly accessible global CTM forecast product – NASA’s Goddard Earth Observing System “Composition Forecasting” (GEOS-CF), providing spatiotemporally continuous PM2.5 concentration forecasts for the next five days at a 1-km spatial resolution. Our forecast experiment was conducted for a region in Central China including the populous and polluted Fenwei Plain. The forecast for the next two days had overall validation R2 of 0.76 and 0.64, respectively; the R2 was around 0.5 for the following three forecast days. Spatial cross-validation showed similar validation metrics. Our forecast model, with validation normalized mean bias close to zero, substantially reduced the large biases in GEOS-CF. The proposed framework requires minimal computational resources compared to running CTMs at urban scales, enabling near-real-time PM2.5 forecast in resource-restricted environments.

PM2.5↗

Southern Hemisphere Carbon Monoxide Inferannual Variability Observed by Terra/Measurement of Pollution in the Troposphere (MOPITT)

Biomass burning is an annual occurrence in the tropical southern hemisphere (SH) and represents a major source of regional pollution. Vegetation fires emit carbon monoxide (CO), which due to its medium lifetime is an excellent tracer of tropospheric transport. CO is also one of the few tropospheric trace gases currently observed from satellite and this provides long-term global measurements. In this paper, we use the 5 year CO data record from the Measurement Of Pollution In The Troposphere (MOPITT) instrument to examine the inter-annual variability of the SH CO loading and show how this relates to climate conditions which determine the intensity of fire sources. The MOPITT observations show an annual austral springtime peak in the SH zonal CO loading each year with dry-season biomass burning emissions in S. America, southern Africa, the Maritime Continent, and northwestern Australia. Although fires in southern Africa and S. America typically produce the greatest amount of CO, the most significant inter-annual variation is due to varying fire activity and emissions from the Maritime Continent and northern Australia. We find that this variation in turn correlates well with the El Nino Southern Oscillation precipitation index. Between 2000 and 2005, emissions were greatest in late 2002 and an inverse modeling of the MOPITT data using the MOZART chemical transport model estimates the southeast Asia regional fire source for the year August 2002 to September 2003 to be 52 Tg CO. Comparison of the MOPITT retrievals and NOAA surface network measurements indicate that the latter do not fully capture the inter-annual variability or the seasonal range of the CO zonal average concentration due to biases associated with atmospheric and geographic sampling.

Edwards, D. P.↗

The Ozone Budget in the Upper Troposphere from Global Modeling Initiative (GMI)Simulations

Ozone concentrations in the upper troposphere are influenced by in-situ production, long-range tropospheric transport, and influx of stratospheric ozone, as well as by photochemical removal. Since ozone is an important greenhouse gas in this region, it is particularly important to understand how it will respond to changes in anthropogenic emissions and changes in stratospheric ozone fluxes.. This response will be determined by the relative balance of the different production, loss and transport processes. Ozone concentrations calculated by models will differ depending on the adopted meteorological fields, their chemical scheme, anthropogenic emissions, and treatment of the stratospheric influx. We performed simulations using the chemical-transport model from the Global Modeling Initiative (GMI) with meteorological fields from (It)h e NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM), (2) the atmospheric GCM from NASA's Global Modeling and Assimilation Office(GMAO), and (3) assimilated winds from GMAO . These simulations adopt the same chemical mechanism and emissions, and adopt the Synthetic Ozone (SYNOZ) approach for treating the influx of stratospheric ozone -. In addition, we also performed simulations for a coupled troposphere-stratosphere model with a subset of the same winds. Simulations were done for both 4degx5deg and 2degx2.5deg resolution. Model results are being tested through comparison with a suite of atmospheric observations. In this presentation, we diagnose the ozone budget in the upper troposphere utilizing the suite of GMI simulations, to address the sensitivity of this budget to: a) the different meteorological fields used; b) the adoption of the SYNOZ boundary condition versus inclusion of a full stratosphere; c) model horizontal resolution. Model results are compared to observations to determine biases in particular simulations; by examining these comparisons in conjunction with the derived budgets, we may pinpoint deficiencies in the representation of chemical/dynamical processes.

Rodriquez, J.↗

Photolysis Controls Atmospheric Budgets of Biogenic Secondary Organic Aerosol

Secondary organic aerosol (SOA) accounts for a large fraction of tropospheric particulate matter. While SOA production rates and mechanisms have been extensively investigated, loss pathways remain uncertain. Most large-scale chemistry and transport models account for mechanical deposition of SOA, but not chemical losses, such as photolysis. There is also a paucity of laboratory measurements of SOA photolysis, which limits how well photolytic losses can be modeled. Here we show, through a combined experimental and modeling approach, that photolytic loss of SOA mass significantly alters SOA budget predictions. Using environmental chamber experiments, we find that SOA produced from several biogenic volatile organic compounds (VOCs) undergoes photolysis-induced mass loss at rates between 0 and 2.2% ± 0.4% of nitrogen dioxide (NO 2 ) photolysis, equivalent to average atmospheric lifetimes as short as 10 hours. We incorporate our photolysis rates into a regional chemical transport model to test the sensitivity of predicted SOA mass concentrations to photolytic losses. The addition of photolysis at rates consistent with our experimental conditions causes a ~50% reduction in biogenic SOA loadings over the Amazon, indicating that photolysis exerts a substantial control over the atmospheric SOA lifetime, with a likely dependence upon SOA molecular composition and thus production mechanisms.

54 ENVIRONMENTAL SCIENCES↗

Elevated Ozone in the Troposphere over the Atlantic and Pacific Oceans in the Northern Hemisphere

Tropospheric column ozone (TCO) is derived from differential measurements of total column ozone from Nimus-7 and Earth Probe TOMS, and stratospheric column ozone from the Microwave Limb Sounder instrument on the Upper Atmospheric Research Satellite. It is shown that TCO during summer months over the Atlantic and Pacific Oceans at northern mid-latitudes is about the same (50-60 Dobson Units) as over the continents of North America, Europe and Asia, where surface emissions of nitrogen oxides from industrial sources, biomass and biofuel burning and biogenic emissions are significantly larger. This nearly uniform zonal variation in TCO is modulated by surface topography of the Rocky and Himalayan mountains and Tibetan Plateau where TCO is reduced by 20-30 Dobson Units. The zonal characteristics of TCO derived from satellite measurements are well simulated by a global chemical transport model called MOZART-2 (Model of Ozone and Related Chemical Tracers, version 2). The model results are analyzed to delineate the relative importance of various processes contributing to observed zonal characteristics of TCO, and they are shown that the surface emission of NOx contributes about 50% of the TCO at northern mid-latitudes, especially over the continents of North America, Europe and Asia. The result of TCO derived from TOMS and the analysis from MOZART-2 indicate that TCO is a very useful tool to study tropospheric O3 pollution resulting from surface emissions of pollutants.

Chandra, S.↗

Elevated Tropospheric Ozone over the Atlantic

Tropospheric column ozone (TCO) is derived from differential measurements of TOMS total column ozone and Microwave Limb Sounder stratospheric column ozone. It is shown that TCO during summer months over the Atlantic and Pacific Oceans in northern midlatitudes is about the same (50 to 60 Dobson Units) as over the continents of North America, Europe, and Asia, where surface emissions of nitrogen oxides from industrial sources, biomass and biofuel burning and biogenic emissions are significantly larger. This nearly uniform zonal variation in TCO is modulated by surface topography of the Rocky and Himalayan mountains, and Tibetan plateau where TCO is reduced by 20 to 30 Dobson Units. The zonal variation in TCO is well simulated by a global chemical transport model called MOZART-2 (Model of Ozone and Related Chemical Tracers, version 2). The model results are analyzed to delineate the relative importance of various processes contributing to observed zonal characteristics of TCO.

Chandra, S.↗

Dust Modeling with GEOS-Chem: Evidence for Acidic Uptake on Dust Surfaces during INTEX-B

We use measurements of aerosol ion composition and size made from the DC8 aircraft during the 2006 INTEX-B airborne campaign to identify mineral dust signatures, and look for evidence for interaction of dust with acidic components. Coating of dust with sulfate or nitrate favors the role of dust particles as cloud condensation nucleii, can promote further uptake of SO2 and N2O5, can impact NOx/HNO3 partitioning, and can shift sulfate or nitrate towards larger sizes, affecting atmospheric lifetimes for both aerosol and gas components. Mineral dust had a pervasive presence on flights made during the Northern Pacific deployment of the INTEX-B mission. We use scatter plots of ion mixing ratios with Na+ and Ca(2+) to distinguish sea salt and mineral components of the aerosol distribution, respectively. Positive correlations of non-sea-salt sulfate and nitrate with calcium indicate that the dusty air stream is associated with polluted air masses. Sulfate-ammonium scatter plots indicate sulfate to be primarily in the form of (NH4)2SO4. A positive correlation between Ca(2+) and NO-, but little evidence of NH4NO3, suggests that NO3- may be associated with mineral dust surfaces. 3-d model simulations conducted with the GEOS-Chem chemical transport model indicate that transpacific transport from East Asia was principally responsible for the dust observed from the aircraft over the Pacific. We compare the aerosol component relationships in the model with those observed. Uptake of sulfate and nitrate on the dust is not yet represented in the model.

Fairlie, T. Duncan↗

HEMCO v1.0: A Versatile, ESMF-Compliant Component for Calculating Emissions in Atmospheric Models

We describe the Harvard-NASA Emission Component version 1.0 (HEMCO), a stand-alone software component for computing emissions in global atmospheric models. HEMCO determines emissions from different sources, regions, and species on a user-defined grid and can combine, overlay, and update a set of data inventories and scale factors, as specified by the user through the HEMCO configuration file. New emission inventories at any spatial and temporal resolution are readily added to HEMCO and can be accessed by the user without any preprocessing of the data files or modification of the source code. Emissions that depend on dynamic source types and local environmental variables such as wind speed or surface temperature are calculated in separate HEMCO extensions. HEMCO is fully compliant with the Earth System Modeling Framework (ESMF) environment. It is highly portable and can be deployed in a new model environment with only few adjustments at the top-level interface. So far, we have implemented HEMCO in the NASA Goddard Earth Observing System (GEOS-5) Earth system model (ESM) and in the GEOS-Chem chemical transport model (CTM). By providing a widely applicable framework for specifying constituent emissions, HEMCO is designed to ease sensitivity studies and model comparisons, as well as inverse modeling in which emissions are adjusted iteratively. The HEMCO code, extensions, and the full set of emissions data files used in GEOS-Chem are available at http: //wiki.geos-chem.org/HEMCO.

GEOS-5↗

Formaldehyde Production from Isoprene Oxidation Across NOx Regimes

The chemical link between isoprene and formaldehyde (HCHO) is a strong, non-linear function of NOx (= 27 NO + NO2). This relationship is a linchpin for top-down isoprene emission inventory verification from orbital HCHO column observations. It is also a benchmark for overall mechanism performance with regard to VOC oxidation. Using a comprehensive suite of airborne in situ observations over the Southeast U.S., we quantify HCHO production across the urban-rural spectrum. Analysis of isoprene and its major first-generation oxidation products allows us to define both a "prompt" yield of HCHO (molecules of HCHO produced per molecule of freshly-emitted isoprene) and the background HCHO mixing ratio (from oxidation of longer-lived hydrocarbons). Over the range of observed NOx values (roughly 0.1 - 2 ppbv), the prompt yield increases by a factor of 3 (from 0.3 to 0.9), while background HCHO increases by more than a factor of 2 (from 1.5 to 3.3 ppbv). We apply the same method to evaluate the performance of both a global chemical transport model (AM3) and a measurement-constrained 0-D chemical box model. Both models reproduce the NOx dependence of the prompt HCHO yield, illustrating that models with updated isoprene oxidation mechanisms can adequately capture the link between HCHO and recent isoprene emissions. On the other hand, both models under-estimate background HCHO mixing ratios, suggesting missing HCHO precursors, inadequate representation of later-generation isoprene degradation and/or under-estimated hydroxyl radical concentrations. Moreover, we find that the total organic peroxy radical production rate is essentially independent of NOx, as the increase in oxidizing capacity with NOx is largely balanced by a decrease in VOC reactivity. Thus, the observed NOx dependence of HCHO mainly reflects the changing fate of organic peroxy radicals.

VOC↗