Benjamin N. Murphy
United States Environmental Protection Agency
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Featured researches published by Benjamin N. Murphy.
Atmospheric Chemistry and Physics | 2016
Havala O. T. Pye; Benjamin N. Murphy; Lu Xu; Nga L. Ng; Annmarie G. Carlton; Hongyu Guo; Rodney J. Weber; Petros Vasilakos; K. Wyat Appel; Sri Hapsari Budisulistiorini; Jason D. Surratt; Athanasios Nenes; Weiwei Hu; Jose L. Jimenez; Gabriel Isaacman-VanWertz; Pawel K. Misztal; Allen H. Goldstein
Organic compounds and liquid water are major aerosol constituents in the southeast United States (SE US). Water associated with inorganic constituents (inorganic water) can contribute to the partitioning medium for organic aerosol when relative humidities or organic matter to organic carbon (OM/OC) ratios are high such that separation relative humidities (SRH) are below the ambient relative humidity (RH). As OM/OC ratios in the SE US are often between 1.8 and 2.2, organic aerosol experiences both mixing with inorganic water and separation from it. Regional chemical transport model simulations including inorganic water (but excluding water uptake by organic compounds) in the partitioning medium for secondary organic aerosol (SOA) when RH > SRH led to increased SOA concentrations,· particularly at night. Water uptake to the organic phase resulted in even greater SOA concentrations as a result of a positive feedback in which water uptake increased SOA, which further increased aerosol water and organic aerosol. Aerosol properties· such as the OM/OC and hygroscopicity parameter (κorg), were captured well by the model compared with measurements during the Southern Oxidant and Aerosol Study (SOAS) 2013. Organic nitrates from monoterpene oxidation were predicted to be the least water-soluble semivolatile species in the model, but most biogenically derived semivolatile species in the Community Multiscale Air Quality (CMAQ) model were highly water soluble and expected to contribute to water-soluble organic carbon (WSOC). Organic aerosol and SOA precursors were abundant at night, but additional improvements in daytime organic aerosol are needed to close the model–measurement gap. When taking into account deviations from ideality, including both inorganic (when RH > SRH) and organic water in the organic partitioning medium reduced the mean bias in SOA for routine monitoring networks and improved model performance compared to observations from SOAS. Property updates from this work will be released in CMAQ v5.2.
Environmental Science & Technology | 2012
Heber J. Chacon-Madrid; Benjamin N. Murphy; Spyros N. Pandis; Neil M. Donahue
We use a two-dimensional volatility basis set (2D-VBS) box model to simulate secondary organic aerosol (SOA) mass yields of linear oxygenated molecules: n-tridecanal, 2- and 7-tridecanone, 2- and 7-tridecanol, and n-pentadecane. A hybrid model with explicit, a priori treatment of the first-generation products for each precursor molecule, followed by a generic 2D-VBS mechanism for later-generation chemistry, results in excellent model-measurement agreement. This strongly confirms that the 2D-VBS mechanism is a predictive tool for SOA modeling but also suggests that certain important first-generation products for major primary SOA precursors should be treated explicitly for optimal SOA predictions.
Science of The Total Environment | 2014
A. G. Megaritis; Benjamin N. Murphy; Pavan N. Racherla; Peter J. Adams; Spyros N. Pandis
The global-regional climate-air pollution modeling system (GRE-CAPS) was applied over the eastern United States to study the impact of climate change on the concentration and deposition of atmospheric mercury. Summer and winter periods (300 days for each) were simulated, and the present-day model predictions (2000s) were compared to the future ones (2050s) assuming constant emissions. Climate change affects Hg(2+) concentrations in both periods. On average, atmospheric Hg(2+) levels are predicted to increase in the future by 3% in summer and 5% in winter respectively due to enhanced oxidation of Hg(0) under higher temperatures. The predicted concentration change of Hg(2+) was found to vary significantly in space due to regional-scale changes in precipitation, ranging from -30% to 30% during summer and -20% to 40% during winter. Particulate mercury, Hg(p) has a similar spatial response to climate change as Hg(2+), while Hg(0) levels are not predicted to change significantly. In both periods, the response of mercury deposition to climate change varies spatially with an average predicted increase of 6% during summer and 4% during winter. During summer, deposition increases are predicted mostly in the western parts of the domain while mercury deposition is predicted to decrease in the Northeast and also in many areas in the Midwest and Southeast. During winter mercury deposition is predicted to change from -30% to 50% mainly due to the changes in rainfall and the corresponding changes in wet deposition.
Journal of Geophysical Research | 2015
Benjamin N. Murphy; Jan Julin; Ilona Riipinen; Annica M. L. Ekman
The difficulty in assessing interactions between atmospheric particles and clouds is due in part to the chemical complexity of the particles and to the wide range of length and timescales of processes occurring simultaneously during a cloud event. The new Cloud-Resolving Model with Organics (CRM-ORG) addresses these interactions by explicitly predicting the formation, transport, uptake, and re-release of surrogate organic compounds consistent with the volatility basis set framework within a nonhydrostatic, three-dimensional cloud-resolving model. CRM-ORG incorporates photochemical production, explicit condensation/evaporation of organic and inorganic vapors, and a comprehensive set of four different mechanisms describing particle formation from organic vapors and sulfuric acid. We simulate two deep convective cloud events over the Amazon rain forest in March 1998 and compare modeled particle size distributions with airborne observations made during the time period. The model predictions agree well with the observations for Aitken mode particles in the convective outflow (10-14 km) but underpredict nucleation mode particles by a factor of 20. A strong in-cloud particle formation process from organic vapors alone is necessary to reproduce even relatively low ultrafine particle number concentrations (similar to 1500 cm(-3)). Sensitivity tests with variable initial aerosol loading and initial vertical aerosol profile demonstrate the complexity of particle redistribution and net gain or loss in the cloud. In-cloud particle number concentrations could be enhanced by as much as a factor of 3 over the base case simulation in the cloud outflow but were never reduced by more than a factor of 2 lower than the base. Additional sensitivity cases emphasize the need for constrained estimates of surface tension and affinity of organic vapors to ice surfaces. When temperature-dependent organic surface tension is introduced to the new particle formation mechanisms, the number concentration of particles decreases by 60% in the cloud outflow. These uncertainties are discussed in light of the other prominent challenges for understanding the interactions between organic aerosols and clouds. Recommendations for future theoretical, laboratory, and field work are proposed.
Atmospheric Chemistry and Physics | 2018
Lu Xu; Havala O. T. Pye; Jia He; Yunle Chen; Benjamin N. Murphy; Nga L. Ng
Atmospheric organic aerosol (OA) has important impacts on climate and human health but its sources remain poorly understood. Biogenic monoterpenes and sesquiterpenes are important precursors of secondary organic aerosol (SOA), but the amounts and pathways of SOA generation from these precursors are not well constrained by observations. We propose that the less-oxidized oxygenated organic aerosol (LO-OOA) factor resolved from positive matrix factorization (PMF) analysis on aerosol mass spectrometry (AMS) data can be used as a surrogate for fresh SOA from monoterpenes and sesquiterpenes in the southeastern US. This hypothesis is supported by multiple lines of evidence, including lab-in-the-field perturbation experiments, extensive ambient ground-level measurements, and state-of-the-art modeling. We performed lab-in-the-field experiments in which the ambient air is perturbed by the injection of selected monoterpenes and sesquiterpenes, and the subsequent SOA formation is investigated. PMF analysis on the perturbation experiments provides an objective link between LO-OOA and fresh SOA from monoterpenes and sesquiterpenes as well as insights into the sources of other OA factors. Further, we use an upgraded atmospheric model and show that modeled SOA concentrations from monoterpenes and sesquiterpenes could reproduce both the magnitude and diurnal variation of LO-OOA at multiple sites in the southeastern US, building confidence in our hypothesis. We estimate the annual average concentration of SOA from monoterpenes and sesquiterpenes in the southeastern US to be roughly 2 μg m-3.
International Technical Meeting on Air Pollution Modelling and its Application | 2016
K. Wyat Appel; Sergey L. Napelenok; Christian Hogrefe; George Pouliot; Kristen M. Foley; Shawn J. Roselle; Jonathan E. Pleim; Jesse O. Bash; Havala O. T. Pye; Nicholas Heath; Benjamin N. Murphy; Rohit Mathur
A new version of the Community Multiscale Air Quality (CMAQ) model, version 5.2 (CMAQv5.2), is currently being developed, with a planned release date in 2017. The new model includes numerous updates from the previous version of the model (CMAQv5.1). Specific updates include a new windblown dust scheme; updates to the organic aerosol treatment; updates to the atmospheric chemistry, including the Carbon-Bond 6 chemical mechanism; and various updates to the cloud treatment in the model. In addition, a new lightning assimilation scheme has been implemented in WRF, the meteorological driver for the CMAQ simulations, which greatly improves the placement and intensity of precipitation, which in turn results in improved CMAQ performance. Comparisons between CMAQv5.1 and v5.2 show that ozone (O3) mixing ratios generally increase in the summer with CMAQv5.2, which results in increased bias, while fine particulate matter (PM2.5) concentrations also increase in the summer, which results in decreased bias.
Environmental Science & Technology | 2009
Benjamin N. Murphy; Spyros N. Pandis
Atmospheric Chemistry and Physics | 2012
Benjamin N. Murphy; Neil M. Donahue; C. Fountoukis; M. Dall'Osto; Colin D. O'Dowd; Astrid Kiendler-Scharr; Spyros N. Pandis
Atmospheric Chemistry and Physics | 2011
Benjamin N. Murphy; Neil M. Donahue; Christos Fountoukis; Spyros N. Pandis
Atmospheric Chemistry and Physics | 2013
Benjamin N. Murphy; Neil M. Donahue; Allen L. Robinson; Spyros N. Pandis