Timothy M. VanReken

Cloud condensation nucleus activation properties of biogenic secondary organic aerosol

monoterpenes (a-pinene, b-pinene, limonene, and D 3 -carene) and one terpenoid alcohol (terpinene-4-ol). In each case the aerosol formation was driven by the reaction of ozone with the biogenic precursor. The SOA produced in each experiment was allowed to age for several hours, during which CCN concentrations were periodically measured at four supersaturations: S = 0.27%, 0.32%, 0.54%, and 0.80%. The calculated relationships between particle dry diameter and critical supersaturation were found to fall in the range of previously reported data for single-component organic aerosols; of the systems studied, a-pinene SOA was the least CCN active, while limonene SOA exhibited the strongest CCN activity. Interestingly, the inferred critical supersaturation of the SOA products was considerably more sensitive to particle diameter than was found in previous studies. Furthermore, the relationships between particle size and critical supersaturation for the monoterpene SOA shifted considerably over the course of the experiments, with the aerosol becoming less hygroscopic over time. These results are consistent with the progressive oligomerization of the SOA.

Aerosol-cloud drop concentration closure in warm cumulus

Our understanding of the activation of aerosol particles into cloud drops during the formation of warm cumulus clouds presently has a limited observational foundation. Detailed observations of aerosol size and composition, cloud microphysics and dynamics, and atmospheric thermodynamic state were collected in a systematic study of 21 cumulus clouds by the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft during NASAs Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL-FACE). An “aerosol-cloud” closure study was carried out in which a detailed cloud activation parcel model, which predicts cloud drop concentration using observed aerosol concentration, size distribution, cloud updraft velocity, and thermodynamic state, is evaluated against observations. On average, measured droplet concentration in adiabatic cloud regions is within 15% of the predictions. This agreement is corroborated by independent measurements of aerosol activation carried out by two cloud condensation nucleus (CCN) counters on the aircraft. Variations in aerosol concentration, which ranged from 300 to 3300 cm^(−3), drives large microphysical differences (250–2300 cm^(−3)) observed among continental and maritime clouds in the South Florida region. This is the first known study in which a cloud parcel model is evaluated in a closure study using a constraining set of data collected from a single platform. Likewise, this is the first known study in which relationships among aerosol size distribution, CCN spectrum, and cloud droplet concentration are all found to be consistent with theory within experimental uncertainties much less than 50%. Vertical profiles of cloud microphysical properties (effective radius, droplet concentration, dispersion) clearly demonstrate the boundary layer aerosols effect on cloud microphysics throughout the lowest 1 km of cloud depth. Onboard measurements of aerosol hygroscopic growth and the organic to sulfate mass ratio are related to CCN properties. These chemical data are used to quantify the range of uncertainty associated with the simplified treatment of aerosol composition assumed in the closure study.

Toward aerosol/cloud condensation nuclei (CCN) closure during CRYSTAL‐FACE

concentrations were 233 cm 3 (at S = 0.2%) and 371 cm 3 (at S = 0.85%). Three flights during the experiment differed from this general trend; the aerosol sampled during the two flights on 18 July was more continental in character, and the observations on 28 July indicate high spatial variability and periods of very high aerosol concentrations. This study also includes a simplified aerosol/CCN closure analysis. Aerosol size distributions were measured simultaneously with the CCN observations, and these data are used to

Use of in situ cloud condensation nuclei, extinction, and aerosol size distribution measurements to test a method for retrieving cloud condensation nuclei profiles from surface measurements

If the aerosol composition and size distribution below cloud are uniform, the vertical profile of cloud condensation nuclei concentration can be retrieved entirely from surface measurements of CCN concentration and particle humidification function and surface-based retrievals of relative humidity and aerosol extinction or backscatter. This provides the potential for long-term measurements of CCN concentrations near cloud base. We have used a combination of aircraft, surface in situ, and surface remote sensing measurements to test various aspects of the retrieval scheme. Our analysis leads us to the following conclusions. The retrieval works better for supersaturations of 0.1% than for 1% because CCN concentrations at 0.1% are controlled by the same particles that control extinction and backscatter. If in situ measurements of extinction are used, the retrieval explains a majority of the CCN variance at high supersaturation for at least two and perhaps five of the eight flights examined. The retrieval of the vertical profile of the humidification factor is not the major limitation of the CCN retrieval scheme. Vertical structure in the aerosol size distribution and composition is the dominant source of error in the CCN retrieval, but this vertical structure is difficult to measure from remote sensing at visible wavelengths.

Characterization of ambient aerosol from measurements of cloud condensation nuclei during the 2003 Atmospheric Radiation Measurement Aerosol Intensive Observational Period at the Southern Great Plains site in Oklahoma

Measurements were made by a new cloud condensation nuclei (CCN) instrument (CCNC3) during the Atmospheric Radiation Measurement (ARM) Programs Aerosol Intensive Observational Period (IOP) in May 2003 in Lamont, Oklahoma. An inverse aerosol/CCN closure study is undertaken, in which the predicted number concentration of particles available for activation (N_P) at the CCNC3 operating supersaturations is compared to that observed (N_O). N_P is based on Kohler Theory, with assumed and inferred aerosol composition and mixing state, and the airborne aerosol size distribution measured by the Caltech Dual Automatic Classified Aerosol Detector (DACAD). An initial comparison of N_O and N_P, assuming the ambient aerosol is pure ammonium sulfate ((NH_4)_2SO_4), results in closure ratios (N_P/N_O) ranging from 1.18 to 3.68 over the duration of the IOP, indicating that the aerosol is less hygroscopic than (NH_4)_2SO_4. N_P and N_O are found to agree when the modeled aerosol population has characteristics of an external mixture of particles, in which insoluble material is preferentially distributed among particles with small diameters (<50 nm) and purely insoluble particles are present over a range of diameters. The classification of sampled air masses by closure ratio and aerosol size distribution is discussed in depth. Inverse aerosol/CCN closure analysis can be a valuable means of inferring aerosol composition and mixing state when direct measurements are not available, especially when surface measurements of aerosol composition and mixing state are not sufficient to predict CCN concentrations at altitude, as was the case under the stratified aerosol layer conditions encountered during the IOP.

Cloud Formation in the Plumes of Solar Chimney Power Generation Facilities: A Modeling Study

The solar chimney power facility has the potential to become a valuable technology for renewable energy production. Its financial viability depends on a thorough understanding of the processes affecting its performance, particularly because of the large startup costs associated with facility design and construction. This paper describes the potential impacts on plant capacity resulting from cloud formation within or downwind of the solar chimney. Several proposed modifications to the basic concept of the solar chimney power facility have the potential to cause significant additions of water vapor to the air passing through the collector. As the air continues up through and out of the chimney, this excess water can condense to form cloud. This possibility is explored using a cloud parcel model initialized to simulate the range of expected operating conditions for a proposed solar chimney facility in southwestern Australia. A range of temperatures and updraft velocities is simulated for each of four seasonal representations and three levels of water vapor enhancement. Both adiabatic environments and the effects of entrainment are considered. The results indicate that for very high levels of water vapor, enhancement cloud formation within the chimney is likely; at more moderate levels of water vapor enhancement, the likelihood of plume formation is difficult to fully assess as the results depend strongly on the choice of entrainment rate. Finally, the impacts of these outcomes on facility capacity are estimated.

SOA Formation Potential of Emissions from Soil and Leaf Litter

Soil and leaf litter are significant global sources of small oxidized volatile organic compounds, VOCs (e.g., methanol and acetaldehyde). They may also be significant sources of larger VOCs that could act as precursors to secondary organic aerosol (SOA) formation. To investigate this, soil and leaf litter samples were collected from the University of Idaho Experimental Forest and transported to the laboratory. There, the VOC emissions were characterized and used to drive SOA formation via dark, ozone-initiated reactions. Monoterpenes dominated the emission profile with emission rates as high as 228 μg-C m(-2) h(-1). The composition of the SOA produced was similar to biogenic SOA formed from oxidation of ponderosa pine emissions and α-pinene. Measured soil and litter monoterpene emission rates were compared with modeled canopy emissions. Results suggest surface soil and litter monoterpene emissions could range from 12 to 136% of canopy emissions in spring and fall. Thus, emissions from leaf litter may potentially extend the biogenic emissions season, contributing to significant organic aerosol formation in the spring and fall when reduced solar radiation and temperatures reduce emissions from living vegetation.

Factors contributing to elevated concentrations of PM2.5 during wintertime near Boise, Idaho

Wintertime chemical composition of water–soluble particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) was monitored in the Treasure Valley region near Boise, Idaho. Aerosol was sampled using a Particle Into Liquid Sampler (PILS) and subsequently analyzed using ion exchange chromatography and a total organic carbon analyzer. During the two–month sampling campaign, the region experienced varying meteorological regimes, with an extended atmospheric stagnation event towards the end of the study. For all of the weather regimes, water–soluble PM2.5 was dominated by organic material, but particulate nitrate showed the greatest variation over time. These variations in particulate nitrate concentration were found to be dependent on the time of day, nitrogen oxides (NOX) concentrations, and relative humidity. The increases in particulate nitrate did not correlate with an equivalent molar increase of ammonium concentration, ruling out solid ammonium nitrate formation as the dominant source. Instead, our analysis using an online aerosol thermodynamic model suggests that the condensation of gas phase nitric acid was possible within the meteorological conditions experienced during the study. In running this model, atmospheric chemical and physical parameters close to those observed during the study were used as model input. The simulation was run for three different scenarios, representing the different meteorological regimes experienced during the study. From the simulation particulate nitrate concentration was highest during cold and humid nights. Currently this region is in attainment with the National Ambient Air Quality Standards (NAAQS) for PM2.5; however, with the projected increase in population and economic growth, and the subsequent increase in NOX emissions, these episodic increases in particulate nitrate have the potential of pushing the area to non–attainment status.

Application of the Wind Erosion Prediction System in the AIRPACT Regional Air Quality Modeling Framework

Abstract. Wind erosion of soil is a major concern of the agricultural community, as it removes the most fertile part of the soil and thus degrades soil productivity. Furthermore, dust emissions due to wind erosion degrade air quality, reduce visibility, and cause perturbations to regional radiation budgets. PM 10 emitted from the soil surface can travel hundreds of kilometers downwind before being deposited back to the surface. Thus, it is necessary to address agricultural air pollutant sources within a regional air quality modeling system in order to forecast regional dust storms and to understand the impact of agricultural activities and land-management practices on air quality in a changing climate. The Wind Erosion Prediction System (WEPS) is a new tool in regional air quality modeling for simulating erosion from agricultural fields. WEPS represents a significant improvement, in comparison to existing empirical windblown dust modeling algorithms used for air quality simulations, by using a more process-based modeling approach. This is in contrast with the empirical approaches used in previous models, which could only be used reliably when soil, surface, and ambient conditions are similar to those from which the parameterizations were derived. WEPS was originally intended for soil conservation applications and designed to simulate conditions of a single field over multiple years. In this work, we used the EROSION submodel from WEPS as a PM 10 emission module for regional modeling by extending it to cover a large region divided into Euclidean grid cells. The new PM 10 emission module was then employed within a regional weather and chemical transport modeling framework commonly used for comprehensive simulations of a wide range of pollutants to evaluate overall air quality conditions. This framework employs the Weather Research and Forecasting (WRF) weather model along with the Community Multi-scale Air Quality (CMAQ) model to treat ozone, particulate matter, and other air pollutants. To demonstrate the capabilities of the WRF/EROSION/CMAQ dust modeling framework, we present here results from simulations of dust storms that occurred in central and eastern Washington during 4 October 2009 and 26 August 2010. Comparison of model results with observations indicates that the modeling framework performs well in predicting the onset and timing of the dust storms and the spatial extent of their dust plumes. The regional dust modeling framework is able to predict elevated PM 10 concentrations hundreds of kilometers downwind of erosion source regions associated with the windblown dust, although the magnitude of the PM 10 concentrations are extremely sensitive to the assumption of surface soil moisture and model wind speeds. Future work will include incorporating the full WEPS model into the regional modeling framework and targeting field measurements to evaluate the modeling framework more extensively.

Modeling the Effects on Energy and Carbon Dioxide from the Use of Recycled Asphalt Pavement in Hot Mix Asphalt

ABSTRACT The transportation sector greatly influence the sustainable development of a society, contributing to pollution from vehicular emissions, global warming, consumption of energy resources, disturbance of natural space from infrastructure construction, and noise pollution. With an increased awareness of sustainable development, more recycled materials are being used for infrastructure construction. However, there is a lack of quantitative evaluation of how energy use and greenhouse gas emission are impacted by the use of recycled materials. Such an evaluation is critical for a comprehensive analysis of the effects of using recycled materials in pavement design. This study develops a mathematical model to quantify the impact of using recycled asphalt pavement in hot mix asphalt on energy consumption and greenhouse gas emission. The energy use and greenhouse gas emissions are affected by the RAP content in HMA, the moisture in the RAP, and the HMA discharge temperature. It was found that it takes more energy to dry/heat HMA with a low percentage of RAP than HMA with only virgin aggregate, while the opposite is true at high RAP percentage. After accounting for the amount of energy used in transporting and processing HMA, and the calorific energy of HMA, the use of RAP in HMA results in reduced energy consumption at all levels of RAP percentage, moisture content, and HMA discharge temperature. For low level of RAP content in HMA, the use of RAP in HMA increases CO2 emissions, while at high RAP content levels CO2 emissions decreases