Mathematical modeling of acid deposition due to radiation fog

A Lagrangian model has been developed to study acidic deposition due to radiation fog. The model couples submodels describing the development and dissipation of radiation fog, the gas-phase chemistry and transfer, and the aqueous-phase chemistry. The model is applied to a radiation fog episode in Bakersfield in the San Joaquin Valley of California over the period January 4–5, 1985. Model predictions for temperature profile, fog development, liquid water content, gas-phase concentrations of SO_2, HNO_3, and NH_3, pH, aqueous-phase concentrations of SO_4^(2−), NH_4^+, and NO_3^−, and finally deposition rates of the above ions are compared with the observed values. The deposition rates of the major ions are predicted to increase significantly during the fog episode, the most notable being the increase of sulfate deposition. Pathways for sulfate production that are of secondary importance in a cloud environment may become significant in a fog. Expressing the mean droplet settling velocity as a function of liquid water content is found to be quite influential in the model's predictions

Aerosol production and growth in the marine boundary layer

The dependence of cloud condensation nuclei (CCN) production on the marine dimethylsulfide (DMS) flux is modeled with a dynamic description of the gas, aerosol, and aqueous phase processes in a closed air parcel. The results support the conclusion reached in previous work with a steady state model that an approximately linear dependence exists between CCN concentration and DMS flux under typical remote marine conditions. This linearity does not hold for low DMS fluxes (the threshold is typically near 2.5 μmol m^(−2) day^(−1)) because the seasalt particles heterogeneously convert the available SO_2 to sulfate inhibiting the creation of new particles. The conditions under which this linear relationship holds are investigated by a series of sensitivity studies, focusing particular attention on the impact of the timing and frequency of cloud events. We consider the regimes of the model's semiempirical parameters, showing that the uncertainty associated with two such parameters, namely, the nucleation rate scaling factor and the sulfuric acid accommodation coefficient, is sufficient to change the predicted CCN production due to DMS from over 300 cm^(−3) day^(−1) to none. This sensitivity accounts for most of the range of results predicted by previous models of the DMS-CCN system

Special issue of \u3ci\u3eAtmospheric Environment\u3c/i\u3e on findings from EPA’s Particulate Matter Supersites Program

In July 1997, the US Environmental Protection Agency (EPA) issued new National Ambient Air Quality Standards (NAAQS) for fine particulate matter (PM2.5, atmospheric particles with aerodynamic diameters less than 2.5 μm). The PM2.5 NAAQS was developed by the EPA based on the results of numerous epidemiological studies that found persistent associations between outdoor concentrations of particulate matter (PM) and significant adverse health effects. However, considerable uncertainty existed concerning mechanisms by which various classes of particles might cause adverse health effects, as well as more detailed information on the composition and concentrations of ambient fine PM, that would be critical in implementing the new standards

The relationship between DMS flux and CCN concentration in remote marine regions

The relationship between the steady state cloud condensation nuclei (CCN) concentration and the dimethylsulfide (DMS) emission flux in remote marine regions is investigated by modeling the principal gas-, aerosol-, and aqueous-phase processes in the marine boundary layer (MBL). Results are in reasonable quantitative agreement with the available measurements of DMS, SO_2, H_2SO_4, CCN, and condensation nuclei (CN) concentrations in remote marine regions of the globe and suggest that indeed DMS plays a major role in the particle dynamics of the MBL. For sufficiently low DMS fluxes practically all the SO_2 produced by DMS photooxidation is predicted to be heterogeneously converted to sulfate in sea-salt aerosol particles. For DMS fluxes higher than approximately 2.5 μmole m^(−2)d^(−1) a linear relationship is found to exist between the CCN number concentration and the DMS flux

ATMOSPHERIC AEROSOL SOURCE-RECEPTOR RELATIONSHIPS: THE ROLE OF COAL-FIRED POWER PLANTS

This report describes the technical progress made on the Pittsburgh Air Quality Study (PAQS) during the period of August 2001 through January of 2002. The major activity during this project period was the continuation of the ambient monitoring effort. Work also progressed on organizing the upcoming source characterization effort, and there was continued development of several three-dimensional air quality models. The first PAQS data analysis workshop for the project was held at Carnegie Mellon in December 2001. Two new instruments were added to site during this project period: a single particle mass spectrometer and an in situ VOC instrument. The single particle mass spectrometer has been deployed since the middle of September and has collected more than 150 days of data. The VOC instrument was only deployed during the intensive sampling period. Several instruments experienced operational issues during this project period. The overall data recovery rate for the project has been high

Cardiopulmonary Mortality and Fine Particulate Air Pollution by Species and Source in a National U.S. Cohort

The purpose of this study was to estimate cardiopulmonary mortality associations for long-term exposure to PM2.5 species and sources (i.e., components) within the U.S. National Health Interview Survey cohort. Exposures were estimated through a chemical transport model for six species (i.e., elemental carbon (EC), primary organic aerosols (POA), secondary organic aerosols (SOA), sulfate (SO4), ammonium (NH4), nitrate (NO3)) and five sources of PM2.5 (i.e., vehicles, electricity-generating units (EGU), non-EGU industrial sources, biogenic sources (bio), “other” sources). In single-pollutant models, we found positive, significant (p < 0.05) mortality associations for all components, except POA. After adjusting for remaining PM2.5 (total PM2.5 minus component), we found significant mortality associations for EC (hazard ratio (HR) = 1.36; 95% CI [1.12, 1.64]), SOA (HR = 1.11; 95% CI [1.05, 1.17]), and vehicle sources (HR = 1.06; 95% CI [1.03, 1.10]). HRs for EC, SOA, and vehicle sources were significantly larger in comparison to those for remaining PM2.5 (per unit μg/m3). Our findings suggest that cardiopulmonary mortality associations vary by species and source, with evidence that EC, SOA, and vehicle sources are important contributors to the PM2.5 mortality relationship. With further validation, these findings could facilitate targeted pollution regulations that more efficiently reduce air pollution mortality.This publication was developed as part of the Center for Air, Climate, and Energy Solutions (CACES), which was supported under Assistance Agreement No. R835873 awarded by the U.S. Environmental Protection Agency. It has not been formally reviewed by EPA. The views expressed in this document are solely those of authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. We also acknowledge support from the European Union’s Horizon 2020 Research and Innovation project REMEDIA under grant agreement No 874753.Peer Reviewed"Article signat per 13 autors/es:" Zachari A. Pond, Carlos S. Hernandez, Peter J. Adams, Spyros N. Pandis, George R. Garcia, Allen L. Robinson, Julian D. Marshall, Richard Burnett, Ksakousti Skyllakou, Pablo Garcia Rivera, Eleni Karnezi, Carver J. Coleman, C. Arden Pope III"Postprint (author's final draft

Organic aerosol in the summertime southeastern United States: components and their link to volatility distribution, oxidation state and hygroscopicity

The volatility distribution of the organic aerosol (OA) and its sources during the Southern Oxidant and Aerosol Study (SOAS; Centreville, Alabama) was constrained using measurements from an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and a thermodenuder (TD). Positive matrix factorization (PMF) analysis was applied on both the ambient and thermodenuded high-resolution mass spectra, leading to four factors: more oxidized oxygenated OA (MO-OOA), less oxidized oxygenated OA (LO-OOA), an isoprene epoxydiol (IEPOX)-related factor (isoprene-OA) and biomass burning OA (BBOA). BBOA had the highest mass fraction remaining (MFR) at 100 °C, followed by the isoprene-OA, and the LO-OOA. Surprisingly the MO-OOA evaporated the most in the TD. The estimated effective vaporization enthalpies assuming an evaporation coefficient equal to unity were 58 ± 13 kJ mol^(−1) for the LO-OOA, 89 ± 10 kJ mol^(−1) for the MO-OOA, 55 ± 11 kJ mol^(−1) for the BBOA, and 63 ± 15 kJ mol^(−1) for the isoprene-OA. The estimated volatility distribution of all factors covered a wide range including both semi-volatile and low-volatility components. BBOA had the lowest average volatility of all factors, even though it had the lowest O  :  C ratio among all factors. LO-OOA was the more volatile factor and its high MFR was due to its low enthalpy of vaporization according to the model. The isoprene-OA factor had intermediate volatility, quite higher than suggested by a few other studies. The analysis suggests that deducing the volatility of a factor only from its MFR could lead to erroneous conclusions. The oxygen content of the factors can be combined with their estimated volatility and hygroscopicity to provide a better view of their physical properties

The influence of the addition of isoprene on the volatility of particles formed from the photo-oxidation of anthropogenic–biogenic mixtures

In this study, we investigate the influence of isoprene on the volatility of secondary organic aerosol (SOA) formed during the photo-oxidation of mixtures of anthropogenic and biogenic precursors. The SOA particle volatility was quantified using two independent experimental techniques (using a thermal denuder and the Filter Inlet for Gas and Aerosols iodide high-resolution time-of-flight Chemical Ionisation Mass Spectrometer – FIGAERO-CIMS) in mixtures of α-pinene/isoprene, o-cresol/isoprene, and α-pinene/o-cresol/isoprene. Single-precursor experiments at various initial concentrations and results from previous α-pinene/o-cresol experiments were used as a reference. The oxidation of isoprene did not result in the formation of detectable SOA particle mass in single-precursor experiments. However, isoprene-derived products were identified in the mixed systems, likely due to the increase in the total absorptive mass. The addition of isoprene resulted in mixture-dependent influence on the SOA particle volatility. Isoprene made no major change to the volatility of α-pinene SOA particles, though changes in the SOA particle composition were observed and the volatility was reasonably predicted based on the additivity. Isoprene addition increased o-cresol SOA particle volatility by ∼5/15 % of the total mass/signal, respectively, indicating a potential to increase the overall volatility that cannot be predicted based on the additivity. The addition of isoprene to the α-pinene/o-cresol system (i.e. α-pinene/o-cresol/isoprene) resulted in slightly fewer volatile particles than those measured in the α-pinene/o-cresol systems. The measured volatility in the α-pinene/o-cresol/isoprene system had an ∼6 % higher low volatile organic compound (LVOC) mass/signal compared to that predicted assuming additivity with a correspondingly lower semi-volatile organic compound (SVOC) fraction. This suggests that any effects that could increase the SOA volatility from the addition of isoprene are likely outweighed by the formation of lower-volatility compounds in more complex anthropogenic–biogenic precursor mixtures. Detailed chemical composition measurements support the measured volatility distribution changes and showed an abundance of unique-to-the-mixture products appearing in all the mixed systems accounting for around 30 %–40 % of the total particle-phase signal. Our results demonstrate that the SOA particle volatility and its prediction can be affected by the interactions of the oxidized products in mixed-precursor systems, and further mechanistic understanding is required to improve their representation in chemical transport models.</p