Showing papers by "Manish Shrivastava published in 2015"

Global transformation and fate of SOA: Implications of low-volatility SOA and gas-phase fragmentation reactions

Abstract: Secondary organic aerosols (SOA) are large contributors to fine-particle loadings and radiative forcing but are often represented crudely in global models. We have implemented three new detailed SOA treatments within the Community Atmosphere Model version 5 (CAM5) that allow us to compare the semivolatile versus nonvolatile SOA treatments (based on some of the latest experimental findings) and to investigate the effects of gas-phase fragmentation reactions. The new treatments also track SOA from biomass burning and biofuel, fossil fuel, and biogenic sources. For semivolatile SOA treatments, fragmentation reactions decrease the simulated annual global SOA burden from 7.5 Tg to 1.8 Tg. For the nonvolatile SOA treatment with fragmentation, the burden is 3.1 Tg. Larger differences between nonvolatile and semivolatile SOA (up to a factor of 5) exist in areas of continental outflow over the oceans. According to comparisons with observations from global surface Aerosol Mass Spectrometer measurements and the U.S. Interagency Monitoring of Protected Visual Environments (IMPROVE) network measurements, the FragNVSOA treatment, which treats SOA as nonvolatile and includes gas-phase fragmentation reactions, agrees best at rural locations. Urban SOA is underpredicted, but this may be due to the coarse model resolution. All three revised treatments show much better agreement with aircraft measurements of organic aerosols (OA) over the North American Arctic and sub-Arctic in spring and summer, compared to the standard CAM5 formulation. This is mainly due to the oxidation of SOA precursor gases from biomass burning, not included in standard CAM5, and long-range transport of biomass burning OA at high altitudes. The revised model configurations that include fragmentation (both semivolatile and nonvolatile SOA) show much better agreement with MODerate resolution Imaging Spectrometers (MODIS) aerosol optical depth data over regions dominated by biomass burning during the summer compared to standard CAM5, and predict biomass burning and biofuel as the largest global source of OA, followed by biogenic and fossil fuel sources. The large contribution of biomass burning OA in the revised treatments is supported by these measurements, but the emissions and aging of SOA precursors and POA are uncertain, and need further investigation. The nonvolatile and semivolatile configurations with fragmentation predict the direct radiative forcing of SOA as −0.5 W m−2 and −0.26 W m−2 respectively, at top of the atmosphere, which are higher than previously estimated by most models, but in reasonable agreement with a recent constrained modeling study. This study highlights the importance of improving process-level representation of SOA in global models.

A new WRF-Chem treatment for studying regional-scale impacts of cloud processes on aerosol and trace gases in parameterized cumuli

Abstract: . A new treatment of cloud effects on aerosol and trace gases within parameterized shallow and deep convection, and aerosol effects on cloud droplet number, has been implemented in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.2.1 that can be used to better understand the aerosol life cycle over regional to synoptic scales. The modifications to the model include treatment of the cloud droplet number mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convective cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. These changes have been implemented in both the WRF-Chem chemistry packages as well as the Kain–Fritsch (KF) cumulus parameterization that has been modified to better represent shallow convective clouds. Testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS). The simulation results are used to investigate the impact of cloud–aerosol interactions on regional-scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column-integrated BC can be as large as −50% when cloud–aerosol interactions are considered (due largely to wet removal), or as large as +40% for sulfate under non-precipitating conditions due to sulfate production in the parameterized clouds. The modifications to WRF-Chem are found to account for changes in the cloud droplet number concentration (CDNC) and changes in the chemical composition of cloud droplet residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to the latest version of WRF-Chem, and it is anticipated that they will be included in a future public release of WRF-Chem.

Modeling particle nucleation and growth over northern California during the 2010 CARES campaign

Abstract: . Accurate representation of the aerosol lifecycle requires adequate modeling of the particle number concentration and size distribution in addition to their mass, which is often the focus of aerosol modeling studies. This paper compares particle number concentrations and size distributions as predicted by three empirical nucleation parameterizations in the Weather Research and Forecast coupled with chemistry (WRF-Chem) regional model using 20 discrete size bins ranging from 1 nm to 10 μm. Two of the parameterizations are based on H2SO4, while one is based on both H2SO4 and organic vapors. Budget diagnostic terms for transport, dry deposition, emissions, condensational growth, nucleation, and coagulation of aerosol particles have been added to the model and are used to analyze the differences in how the new particle formation parameterizations influence the evolving aerosol size distribution. The simulations are evaluated using measurements collected at surface sites and from a research aircraft during the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted in the vicinity of Sacramento, California. While all three parameterizations captured the temporal variation of the size distribution during observed nucleation events as well as the spatial variability in aerosol number, all overestimated by up to a factor of 2.5 the total particle number concentration for particle diameters greater than 10 nm. Using the budget diagnostic terms, we demonstrate that the combined H2SO4 and low-volatility organic vapor parameterization leads to a different diurnal variability of new particle formation and growth to larger sizes compared to the parameterizations based on only H2SO4. At the CARES urban ground site, peak nucleation rates are predicted to occur around 12:00 Pacific (local) standard time (PST) for the H2SO4 parameterizations, whereas the highest rates were predicted at 08:00 and 16:00 PST when low-volatility organic gases are included in the parameterization. This can be explained by higher anthropogenic emissions of organic vapors at these times as well as lower boundary-layer heights that reduce vertical mixing. The higher nucleation rates in the H2SO4-organic parameterization at these times were largely offset by losses due to coagulation. Despite the different budget terms for ultrafine particles, the 10–40 nm diameter particle number concentrations from all three parameterizations increased from 10:00 to 14:00 PST and then decreased later in the afternoon, consistent with changes in the observed size and number distribution. We found that newly formed particles could explain up to 20–30 % of predicted cloud condensation nuclei at 0.5 % supersaturation, depending on location and the specific nucleation parameterization. A sensitivity simulation using 12 discrete size bins ranging from 1 nm to 10 μm diameter gave a reasonable estimate of particle number and size distribution compared to the 20 size bin simulation, while reducing the associated computational cost by ~ 36 %.