Adjoint sensitivity of global cloud droplet number to aerosol and dynamical parameters

We present the development of the adjoint of a comprehensive cloud droplet formation parameterization for use in aerosol-cloud-climate interaction studies. The adjoint efficiently and accurately calculates the sensitivity of cloud droplet number concentration (CDNC) to all parameterization inputs (e.g., updraft velocity, water uptake coefficient, aerosol number and hygroscopicity) with a single execution. The adjoint is then integrated within three dimensional (3-D) aerosol modeling frameworks to quantify the sensitivity of CDNC formation globally to each parameter. Sensitivities are computed for year-long executions of the NASA Global Modeling Initiative (GMI) Chemical Transport Model (CTM), using wind fields computed with the Goddard Institute for Space Studies (GISS) Global Circulation Model (GCM) II', and the GEOS-Chem CTM, driven by meteorological input from the Goddard Earth Observing System (GEOS) of the NASA Global Modeling and Assimilation Office (GMAO). We find that over polluted (pristine) areas, CDNC is more sensitive to updraft velocity and uptake coefficient (aerosol number and hygroscopicity). Over the oceans of the Northern Hemisphere, addition of anthropogenic or biomass burning aerosol is predicted to increase CDNC in contrast to coarse-mode sea salt which tends to decrease CDNC. Over the Southern Oceans, CDNC is most sensitive to sea salt, which is the main aerosol component of the region. Globally, CDNC is predicted to be less sensitive to changes in the hygroscopicity of the aerosols than in their concentration with the exception of dust where CDNC is very sensitive to particle hydrophilicity over arid areas. Regionally, the sensitivities differ considerably between the two frameworks and quantitatively reveal why the models differ considerably in their indirect forcing estimates

Formation of semivolatile inorganic aerosols in the Mexico City Metropolitan Area during the MILAGRO campaign

One of the most challenging tasks for chemical transport models (CTMs) is the prediction of the formation and partitioning of the major semi-volatile inorganic aerosol components (nitrate, chloride, ammonium) between the gas and particulate phases. In this work the PMCAMx-2008 CTM, which includes the recently developed aerosol thermodynamic model ISORROPIA-II, is applied in the Mexico City Metropolitan Area in order to simulate the formation of the major inorganic aerosol components. The main sources of SO2 (such as the Miguel Hidalgo Refinery and the Francisco Perez Rios Power Plant) in the Mexico City Metropolitan Area (MCMA) are located in Tula, resulting in high predicted PM1 (particulate matter with diameter less than 1 µm) sulfate concentrations (over 25 µg m-3) in that area. The average predicted PM1 nitrate concentrations are up to 3 µg m-3 (with maxima up to 11 µg m-3) in and around the urban center, mostly produced from local photochemistry. The presence of calcium coming from the Tolteca area (7 µg m-3) as well as the rest of the mineral cations (1 µg m-3 potassium, 1 µg m-3 magnesium, 2 µg m-3 sodium, and 3 µg m-3 calcium) from the Texcoco Lake resulted in the formation of a significant amount of aerosol nitrate in the coarse mode with concentrations up to 3 µg m-3 over these areas. PM1-10 (particulate matter with diameter between 1 and 10 µm) chloride is also high and its concentration exceeds 2 µg m-3 in Texcoco Lake. PM1 ammonium concentrations peak at the center of Mexico City (2 µg m-3) and the Tula vicinity (2.5 µg m-3). The performance of the model for the major inorganic PM components (sulfate, ammonium, nitrate, chloride, sodium, calcium, and magnesium) is encouraging. At the T0 measurement site, located in the Mexico City urban center, the average measured values of PM1 sulfate, nitrate, ammonium, and chloride are 3.5 µg m-3, 3.5 µg m-3, 2.1 µg m-3, and 0.36 µg m-3, respectively. The corresponding predicted values are 3.7 µg m-3, 2.7 µg m-3, 1.7 µg m-3, and 0.25 µg m-3. High sulfate concentrations are associated with the transport of sulfate from the Tula vicinity, while in periods where southerly winds are dominant; the concentrations of sulfate are low. The underprediction of nitrate can be attributed to the underestimation of OH levels by the model during the early morning. Ammonium is sensitive to the predicted sulfate concentrations and the nitrate levels. The performance of the model is also evaluated against measurements taken from a suburban background site (T1) located north of Mexico City. The average predicted PM2.5 (particulate matter with diameter less than 2.5 µm) sulfate, nitrate, ammonium, chloride, sodium, calcium, and magnesium are 3.3, 3.2, 1.4, 0.5, 0.3, 1.2, and 0.15 µg m-3, respectively. The corresponding measured concentrations are 3.7, 2.9, 1.5, 0.3, 0.4, 0.6, and 0.15 µg m-3. The overprediction of calcium indicates a possible overestimation of its emissions and affects the partitioning of nitric acid to the aerosol phase resulting occasionally in an overprediction of nitrate. Additional improvements are possible by improving the performance of the model regarding the oxidant levels, and revising the emissions and the chemical composition of the fugitive dust. The hybrid approach in which the mass transfer to the fine aerosol is simulated using the bulk equilibrium assumption and to the remaining aerosol sections using a dynamic approach, is needed in order to accurately simulate the size distribution of the inorganic aerosols. The bulk equilibrium approach fails to reproduce the observed coarse nitrate and overpredicts the fine nitrate. Sensitivity tests indicate that sulfate concentration in Tula decreases by up to 0.5 µg m-3 after a 50% reduction of SO2 emissions while it can increase by up to 0.3 µg m-3 when NOx emissions are reduced by 50%. Nitrate concentration decreases by up to 1 µg m-3 after the 50% reduction of NOx or NH3 emissions. Ammonium concentration decreases by up to 1 µg m-3, 0.3 µg m-3, and 0.1 µg m-3 after the 50% reduction of NH3, NOx, and SO2 emissions, respectively.Seventh Framework Programme (European Commission) (MEGAPOLI Grant agreement no.: 212520)National Institutes of Health (U.S.) (NSF (ATM-0528227

Firm quality or market sentiment : what matters more for IPO investors?

This paper investigates the investment decisions of IPO investors when equipped with information on both the quality of the firm and the market sentiment. Unique regulatory provisions allow IPO investors in India to have access to the independent assessment of firm quality and information on the participation of other investors, including institutional investors. At the same time, an active grey market reveals market sentiment before the application for subscription is closed. The results, which are robust to alternative model specifications, suggest that the institutional investors' decision is guided almost exclusively by firm quality while the retail investors' decision to participate in IPOs is strongly influenced by market sentiment, even in a highly transparent market where both sets of information are freely available

Sources and production of organic aerosol in Mexico City: insights from the combination of a chemical transport model (PMCAMx-2008) and measurements

Urban areas are large sources of organic aerosols and their precursors. Nevertheless, the contributions of primary (POA) and secondary organic aerosol (SOA) to the observed particulate matter levels have been difficult to quantify. In this study the three-dimensional chemical transport model PMCAMx-2008 is used to investigate the temporal and geographic variability of organic aerosol in the Mexico City Metropolitan Area (MCMA) during the MILAGRO campaign that took place in the spring of 2006. The organic module of PMCAMx-2008 includes the recently developed volatility basis-set framework in which both primary and secondary organic components are assumed to be semi-volatile and photochemically reactive and are distributed in logarithmically spaced volatility bins. The MCMA emission inventory is modified and the POA emissions are distributed by volatility based on dilution experiments. The model predictions are compared with observations from four different types of sites, an urban (T0), a suburban (T1), a rural (T2), and an elevated site in Pico de Tres Padres (PTP). The performance of the model in reproducing organic mass concentrations in these sites is encouraging. The average predicted PM[subscript 1] organic aerosol (OA) concentration in T0, T1, and T2 is 18 μg m[superscript −3], 11.7 μg m[superscript −3], and 10.5 μg m[superscript −3] respectively, while the corresponding measured values are 17.2 μg m[superscript −3], 11 μg m[superscript −3], and 9 μg m[superscript −3]. The average predicted locally-emitted primary OA concentrations, 4.4 μg m[superscript −3] at T0, 1.2 μg m[superscript −3] at T1 and 1.7 μg m[superscript −3] at PTP, are in reasonably good agreement with the corresponding PMF analysis estimates based on the Aerosol Mass Spectrometer (AMS) observations of 4.5, 1.3, and 2.9 μg m[superscript −3] respectively. The model reproduces reasonably well the average oxygenated OA (OOA) levels in T0 (7.5 μg m[superscript −3] predicted versus 7.5 μg m[superscript −3] measured), in T1 (6.3 μg m[superscript −3] predicted versus 4.6 μg m[superscript −3] measured) and in PTP (6.6 μg m[superscript −3] predicted versus 5.9 μg m[superscript −3] measured). The rest of the OA mass (6.1 μg m[superscript −3] and 4.2 μg m[superscript −3] in T0 and T1 respectively) is assumed to originate from biomass burning activities and is introduced to the model as part of the boundary conditions. Inside Mexico City (at T0), the locally-produced OA is predicted to be on average 60 % locally-emitted primary (POA), 6 % semi-volatile (S-SOA) and intermediate volatile (I-SOA) organic aerosol, and 34 % traditional SOA from the oxidation of VOCs (V-SOA). The average contributions of the OA components to the locally-produced OA for the entire modelling domain are predicted to be 32 % POA, 10 % S-SOA and I-SOA, and 58 % V-SOA. The long range transport from biomass burning activities and other sources in Mexico is predicted to contribute on average almost as much as the local sources during the MILAGRO period.European UnionSeventh Framework Programme (European Commission) (Grant agreement no.: 212520)National Science Foundation (U.S.) (ATM 0732598)Molina Center for Energy and the EnvironmentNational Science Foundation (U.S.) (ATM 0528227)National Science Foundation (U.S.) (ATM 0810931

Simulations of organic aerosol concentrations in Mexico City using the WRF-CHEM model during the MCMA-2006/MILAGRO campaign

Organic aerosol concentrations are simulated using the WRF-CHEM model in Mexico City during the period from 24 to 29 March in association with the MILAGRO-2006 campaign. Two approaches are employed to predict the variation and spatial distribution of the organic aerosol concentrations: (1) a traditional 2-product secondary organic aerosol (SOA) model with non-volatile primary organic aerosols (POA); (2) a non-traditional SOA model including the volatility basis-set modeling method in which primary organic components are assumed to be semi-volatile and photochemically reactive and are distributed in logarithmically spaced volatility bins. The MCMA (Mexico City Metropolitan Area) 2006 official emission inventory is used in simulations and the POA emissions are modified and distributed by volatility based on dilution experiments for the non-traditional SOA model. The model results are compared to the Aerosol Mass Spectrometry (AMS) observations analyzed using the Positive Matrix Factorization (PMF) technique at an urban background site (T0) and a suburban background site (T1) in Mexico City. The traditional SOA model frequently underestimates the observed POA concentrations during rush hours and overestimates the observations in the rest of the time in the city. The model also substantially underestimates the observed SOA concentrations, particularly during daytime, and only produces 21% and 25% of the observed SOA mass in the suburban and urban area, respectively. The non-traditional SOA model performs well in simulating the POA variation, but still overestimates during daytime in the urban area. The SOA simulations are significantly improved in the non-traditional SOA model compared to the traditional SOA model and the SOA production is increased by more than 100% in the city. However, the underestimation during daytime is still salient in the urban area and the non-traditional model also fails to reproduce the high level of SOA concentrations in the suburban area. In the non-traditional SOA model, the aging process of primary organic components considerably decreases the OH levels in simulations and further impacts the SOA formation. If the aging process in the non-traditional model does not have feedback on the OH in the gas-phase chemistry, the SOA production is enhanced by more than 10% compared to the simulations with the OH feedback during daytime, and the gap between the simulations and observations in the urban area is around 3 μg m[superscript −3] or 20% on average during late morning and early afternoon, within the uncertainty from the AMS measurements and PMF analysis. In addition, glyoxal and methylglyoxal can contribute up to approximately 10% of the observed SOA mass in the urban area and 4% in the suburban area. Including the non-OH feedback and the contribution of glyoxal and methylglyoxal, the non-traditional SOA model can explain up to 83% of the observed SOA in the urban area, and the underestimation during late morning and early afternoon is reduced to 0.9 μg m[superscript −3] or 6% on average. Considering the uncertainties from measurements, emissions, meteorological conditions, aging of semi-volatile and intermediate volatile organic compounds, and contributions from background transport, the non-traditional SOA model is capable of closing the gap in SOA mass between measurements and models.National Science Foundation (U.S.). Atmospheric Chemistry Program (ATM-0528227)National Science Foundation (U.S.). Atmospheric Chemistry Program (ATM-0810931)Molina Center for Energy and the Environmen

arteriovenous access graft infection standards of reporting and implications for comparative data analysis

Abstract There is presently a lack of organization and standardized reporting schema for arteriovenous graft (AVG) infections. The purpose of this paper is to evaluate the various types of treatment modalities for access site infections through an analysis of current publications on AVG. Key proposals are made to support standardization in a data-driven manner to make infection reporting more uniform and thereby facilitate more meaningful comparisons between various dialysis modalities and AVG technologies

Evaluation of the volatility basis-set approach for the simulation of organic aerosol formation in the Mexico City metropolitan area

New primary and secondary organic aerosol modules have been added to PMCAMx, a three dimensional chemical transport model (CTM), for use with the SAPRC99 chemistry mechanism based on recent smog chamber studies. The new modeling framework is based on the volatility basis-set approach: both primary and secondary organic components are assumed to be semivolatile and photochemically reactive and are distributed in logarithmically spaced volatility bins. This new framework with the use of the new volatility basis parameters for low-NOx [low - NO subscript x] and high-NOx [high - NO subscript x] conditions tends to predict 4–6 times higher anthropogenic SOA concentrations than those predicted with older generation of models. The resulting PMCAMx-2008 was applied in Mexico City Metropolitan Area (MCMA) for approximately a week during April of 2003. The emission inventory, which uses as starting point the MCMA 2004 official inventory, is modified and the primary organic aerosol (POA) emissions are distributed by volatility based on dilution experiments. The predicted organic aerosol (OA) concentrations peak in the center of Mexico City reaching values above 40 μg [mu g] m−3 [m superscript -3]. The model predictions are compared with Aerosol Mass Spectrometry (AMS) observations and their Positive Matrix Factorization (PMF) analysis. The model reproduces both Hydrocarbon-like Organic Aerosol (HOA) and Oxygenated Organic Aerosol (OOA) concentrations and diurnal profiles. The small OA underprediction during the rush hour periods and overprediction in the afternoon suggest potential improvements to the description of fresh primary organic emissions and the formation of the oxygenated organic aerosols respectively, although they may also be due to errors in the simulation of dispersion and vertical mixing. However, the AMS OOA data are not specific enough to prove that the model reproduces the organic aerosol observations for the right reasons. Other combinations of contributions of primary, aged primary, and secondary organic aerosol production rates may lead to similar results. The model results suggest strongly that during the simulated period transport of OA from outside the city was a significant contributor to the observed OA levels. Future simulations should use a larger domain in order to test whether the regional OA can be predicted with current SOA parameterizations. Sensitivity tests indicate that the predicted OA concentration is especially sensitive to the volatility distribution of the emissions in the lower volatility bins.Seventh Framework Programme (European Commission)European UnionMEGAPOLI (Project) (Grant agreement no. 212520)Molina Center for Energy and the EnvironmentUnited States. National Oceanic and Atmospheric Administration. Office of Global Programs (Grant NA08OAR4310565)National Science Foundation (U.S.) (Grant ATM-0528634)National Science Foundation (U.S.) (Grant ATM-0528227)United States. Dept. of Energy. Office of Biological and Environmental Research. Atmospheric Science Program (DEFG0208ER64627

Quantifying uncertainties due to chemistry modelling – evaluation of tropospheric composition simulations in the CAMS model (cycle 43R1)

We report on an evaluation of tropospheric ozone and its precursor gases in three atmospheric chemistry versions as implemented in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS), referred to as IFS(CB05BASCOE), IFS(MOZART) and IFS(MOCAGE). While the model versions were forced with the same overall meteorology, emissions, transport and deposition schemes, they vary largely in their parameterisations describing atmospheric chemistry, including the organics degradation, heterogeneous chemistry and photolysis, as well as chemical solver. The model results from the three chemistry versions are compared against a range of aircraft field campaigns, surface observations, ozone-sondes and satellite observations, which provides quantification of the overall model uncertainty driven by the chemistry parameterisations. We find that they produce similar patterns and magnitudes for carbon monoxide (CO) and ozone (O3), as well as a range of non-methane hydrocarbons (NMHCs), with averaged differences for O3 (CO) within 10&thinsp;% (20&thinsp;%) throughout the troposphere. Most of the divergence in the magnitude of CO and NMHCs can be explained by differences in OH concentrations, which can reach up to 50&thinsp;%, particularly at high latitudes. There are also comparatively large discrepancies between model versions for NO2, SO2 and HNO3, which are strongly influenced by secondary chemical production and loss. Other common biases in CO and NMHCs are mainly attributed to uncertainties in their emissions. This configuration of having various chemistry versions within IFS provides a quantification of uncertainties induced by chemistry modelling in the main CAMS global trace gas products beyond those that are constrained by data assimilation.</p