Kerry E. Kelly

Real-Time Measurements of Jet Aircraft Engine Exhaust

Abstract Particulate-phase exhaust properties from two different types of ground-based jet aircraft engines—high-thrust and turboshaft—were studied with real-time instruments on a portable pallet and additional time-integrated sampling devices. The real-time instruments successfully characterized rapidly changing particulate mass, light absorption, and polycyclic aromatic hydrocarbon (PAH) content. The integrated measurements included particulate-size distributions, PAH, and carbon concentrations for an entire test run (i.e., “run-integrated” measurements). In all cases, the particle-size distributions showed single modes peaking at 20–40nm diameter. Measurements of exhaust from high-thrust F404 engines showed relatively low-light absorption compared with exhaust from a turboshaft engine. Particulate-phase PAH measurements generally varied in phase with both net particulate mass and with light-absorbing particulate concentrations. Unexplained response behavior sometimes occurred with the real-time PAH analyzer, although on average the real-time and integrated PAH methods agreed within the same order of magnitude found in earlier investigations.

Receptor model source attributions for Utah's Salt Lake City airshed and the impacts of wintertime secondary ammonium nitrate and ammonium chloride aerosol

Communities along Utahs Wasatch Front are currently developing strategies to reduce daily average PM2.5 levels to below National Ambient Air Quality Standards during wintertime persistent stable atmospheric conditions, or cold-air pools. Speciated PM2.5 data from the Wasatch Front airshed indicate that wintertime exceedances of the PM2.5 standard are mainly driven by high levels of ammonium nitrate. Stable wintertime conditions foster the formation of ammonium nitrate aerosol when sufficient sources of NOx, ammonia, and oxidative capacity exist. However, this work demonstrates that secondary ammonium chloride aerosol can also be a significant source of secondary wintertime PM2.5 if sufficient sources of atmospheric chlorine exist. Two factor analysis techniques, positive matrix factorization (PMF) and Unmix, were used to identify contributors to PM2.5 at three monitoring stations along Utahs Wasatch Front: Bountiful, Lindon, and Salt Lake City. The monitoring data included chemically speciated PM2.5 data for 227, 227, and 429 days at each location, respectively, during the period from May 2007 through May 2011. PMF identified 10–12 factors and Unmix identified 4–5 factors for each of the locations. The wintertime PMF and Unmix results showed large contributions from secondary PM2.5 when PM2.5 concentrations exceeded 20 μg/m3. PMF identified both ammonium nitrate and ammonium chloride aerosol as significant secondary contributors to PM2.5 (10–15% of total PM2.5 from ammonium chloride) during wintertime pollution episodes. Subsequent ion balance analysis of the monitoring data confirmed the presence of significant ammonium chloride aerosol on these highly polluted days at all three monitoring sites. The directly emitted primary PM2.5 portions of the source attribution results were further compared to county-level emissions inventories and showed generally good agreement for Salt Lake City and Lindon during wintertime except for wood smoke and fugitive dust, which have higher contributions in the receptor modeling results than in the emissions inventories. Implications: The study suggests that secondary ammonium chloride aerosol can be a significant source of wintertime PM2.5 in an ammonia-rich environment, like the Wasatch Front airshed, if sufficient sources of atmospheric chlorine exist. During wintertime, cold-air-pool events, the source attribution results generally agree with the county emission inventories with the exception of wood smoke and cooking sources. At the Salt Lake City monitoring station, the estimated contributions from wood smoke and cooking are nearly double those of the corresponding inventory, suggesting that they are nearly as important as gasoline emissions.

Simulation of the evolution of particle size distributions in a vehicle exhaust plume with unconfined dilution by ambient air

Abstract Over the past several years, numerous studies have linked ambient concentrations of particulate matter (PM) to adverse health effects, and more recent studies have identified PM size and surface area as important factors in determining the health effects of PM. This study contributes to a better understanding of the evolution of particle size distributions in exhaust plumes with unconfined dilution by ambient air. It combines computational fluid dynamics (CFD) with an aerosol dynamics model to examine the effects of different streamlines in an exhaust plume, ambient particle size distributions, and vehicle and wind speed on the particle size distribution in an exhaust plume. CFD was used to calculate the flow field and gas mixing for unconfined dilution of a vehicle exhaust plume, and the calculated dilution ratios were then used as input to the aerosol dynamics simulation. The results of the study show that vehicle speed affected the particle size distribution of an exhaust plume because increasing vehicle speed caused more rapid dilution and inhibited coagulation. Ambient particle size distributions had an effect on the smaller sized particles (∼10 nm range under some conditions) and larger sized particles (>2 μm) of the particle size distribution. The ambient air particle size distribution affects the larger sizes of the exhaust plume because vehicle exhaust typically contains few particles larger than 2 μm. Finally, the location of a streamline in the exhaust plume had little effect on the particle size distribution; the particle size distribution along any streamline at a distance x differed by less than 5% from the particle size distributions along any other streamline at distance x.

Characterization of Exhaust Particles from Military Vehicles Fueled with Diesel, Gasoline, and JP-8

Abstract Diluted exhaust from selected military aircraft ground-support equipment (AGE) was analyzed for particulate mass, elemental carbon (EC) and organic carbon (OC), SO4 2−, and size distributions. The experiments occurred at idle and load conditions and utilized a chassis dynamometer. The selected AGE vehicles operated on gasoline, diesel, and JP-8. These military vehicles exhibited concentrations, size distributions, and emission factors in the same range as those reported for nonmilitary vehicles. The diesel and JP-8 emission rates for PM ranged from 0.092 to 1.1 g/kg fuel. The EC contributed less and the OC contributed more to the particulate mass than reported in recent studies of vehicle emissions. Overall, the particle size distribution varied significantly with engine condition, with the number of accumulation mode particles and the count median diameter (CMD) increasing as engine load increased. The SO4 2− analyses showed that the distribution of SO4 2− mass mirrored the distribution of particle mass.

Black carbon and polycyclic aromatic hydrocarbon emissions from vehicles in the United States-Mexico border region: pilot study.

The investigators developed a system to measure black carbon (BC) and particle-bound polycyclic aromatic hydrocarbon (PAH) emission factors during roadside sampling in four cities along the United States–Mexico border, Calexico/Mexicali and El Paso/Juárez. The measurement system included a photoacoustic analyzer for BC, a photoelectric aerosol sensor for particle-bound PAHs, and a carbon dioxide (CO2) analyzer. When a vehicle with measurable emissions passed the system probe, corresponding BC, PAH, and CO2 peaks were evident, and a fuel-based emission factor was estimated. A picture of each vehicle was also recorded with a digital camera. The advantage of this system, compared with other roadside methods, is the direct measurement of particulate matter components and limited interference from roadside dust. The study revealed some interesting trends: Mexican buses and all medium-duty trucks were more frequently identified as high emitters of BC and PAH than heavy-duty trucks or passenger vehicles. In addition, because of the high daily mileage of buses, they are good candidates for additional study. Mexican trucks and buses had higher average emission factors compared with U.S. trucks and buses, but the differences were not statistically significant. Few passenger vehicles had measurable BC and PAH emissions, although the highest emission factor came from an older model passenger vehicle licensed in Baja California.

Determining the effect of species composition on temperature fields of tank flames using real-time holographic interferometry

Interference fringe fields and the visible flame field of a 50 mm diameter n-hexane tank flame were simultaneously measured using a real-time holographic interferometer with special image optics. An inhouse developed image processing method was applied to the holographic images to calculate the interference fringe order profiles. The effect of species composition on temperature profiles was studied by considering three different cases: using the measured species profiles, using an overall reaction mechanism based on stoichiometric combustion, and by assuming that the flame consists of hot air. The results show that species composition has the largest effect on temperature fields in regions near the flame axis at lower axial distances. In the region of the plume zone, the flame consists primarily of hot air due to the increase in total entrained air.

Low-Wind/High Particulate Matter Episodes in the Calexico/Mexicali Region

Abstract The U.S. Environmental Protection Agency (EPA) currently classifies Imperial County, CA, as a nonattainment area for PM10 (particulate matter [PM] ≤ 10 μm in diameter), and this region suffers from high rates of chronic bronchitis and childhood asthma. Although high annual and daily average PM levels can have negative health and economic effects, recent studies have identified an association between adverse health effects and short-term PM spikes of tens of micrograms per cubic meter. This study identified PM episodes in Calexico/Mexicali that involve PM concentration spikes with concentrations up to 10 times greater than those reported to cause adverse health effects. These episodes appear to be relatively common during the winter months, are associated with wind speeds below 2 m/sec and stable boundary level heights below 500 m, and can comprise a large portion of the 24-hr PM levels. The organic composition of the PM10 samples collected during the low-wind/high-PM episodes differed from that collected at other times. However, a preliminary source attribution identified only one significant difference between the source classes: agricultural burning accounted for 6.7% of organic-fraction PM10 for low-wind/high-PM episodes versus 0.25% at other times. This preliminary source attribution also revealed that motor vehicles were the most important relative contributor to organic PM10.

Using a Continuous Time Lag to Determine the Associations between Ambient PM2.5 Hourly Levels and Daily Mortality

Abstract The authors are interested in understanding the possible association between exposure to short-term fine particulate matter (PM2.5) peaks that have changing physical characteristics throughout the day and observable health outcomes (daily mortality). To this end, modern statistical methods are used here that allow for a continuous time lag between hourly PM2.5 mass concentration and daily mortality. The functional linear regression model was used to study how hourly PM2.5 mass of past days continuously influences the daily mortality count of the current day. Using a Poisson likelihood with the canonical link, the authors found that a 10μg/m3 increase in the hourly PM2.5 above the hourly average is associated with 1.7% (0.1, 3.4), 2.4% (1.2, 3.7), 1.6% (0.6, 2.7), and 0.8% (–0.2, 1.8) higher risk of mortality on the same day, next day, 2 days, and 3 days later, respectively. The increase in relative risk is statistically significant for lags of 0–2 days, but not at lag 3. The highest association between PM2.5 mass concentration and daily mortality was found to occur in the morning when both mass and PM number concentrations peak at approximately 8:00 a.m. (lag of 15, 39, and 63 hr). This morning time interval corresponds to automobile traffic rush hour that coincides with a morning atmospheric inversion that traps high concentrations of nanoparticles.

Coupling between Chemical and Meteorological Processes under Persistent Cold-Air Pool Conditions: Evolution of Wintertime PM2.5 Pollution Events and N2O5 Observations in Utah’s Salt Lake Valley

The Salt Lake Valley experiences severe fine particulate matter pollution episodes in winter during persistent cold-air pools (PCAPs). We employ measurements throughout an entire winter from different elevations to examine the chemical and dynamical processes driving these episodes. Whereas primary pollutants such as NOx and CO were enhanced twofold during PCAPs, O3 concentrations were approximately threefold lower. Atmospheric composition varies strongly with altitude within a PCAP at night with lower NOx and higher oxidants (O3) and oxidized reactive nitrogen (N2O5) aloft. We present observations of N2O5 during PCAPs that provide evidence for its role in cold-pool nitrate formation. Our observations suggest that nighttime and early morning chemistry in the upper levels of a PCAP plays an important role in aerosol nitrate formation. Subsequent daytime mixing enhances surface PM2.5 by dispersing the aerosol throughout the PCAP. As pollutants accumulate and deplete oxidants, nitrate chemistry becomes less active during the later stages of the pollution episodes. This leads to distinct stages of PM2.5 pollution episodes, starting with a period of PM2.5 buildup and followed by a period with plateauing concentrations. We discuss the implications of these findings for mitigation strategies.

Predicting emissions from oil and gas operations in the Uinta Basin, Utah

ABSTRACT In this study, emissions of ozone precursors from oil and gas operations in Utah’s Uinta Basin are predicted (with uncertainty estimates) from 2015–2019 using a Monte-Carlo model of (a) drilling and production activity, and (b) emission factors. Cross-validation tests against actual drilling and production data from 2010–2014 show that the model can accurately predict both types of activities, returning median results that are within 5% of actual values for drilling, 0.1% for oil production, and 4% for gas production. A variety of one-time (drilling) and ongoing (oil and gas production) emission factors for greenhouse gases, methane, and volatile organic compounds (VOCs) are applied to the predicted oil and gas operations. Based on the range of emission factor values reported in the literature, emissions from well completions are the most significant source of emissions, followed by gas transmission and production. We estimate that the annual average VOC emissions rate for the oil and gas industry over the 2010–2015 time period was 44.2E+06 (mean) ± 12.8E+06 (standard deviation) kg VOCs per year (with all applicable emissions reductions). On the same basis, over the 2015–2019 period annual average VOC emissions from oil and gas operations are expected to drop 45% to 24.2E+06 ± 3.43E+06 kg VOCs per year, due to decreases in drilling activity and tighter emission standards. Implications: This study improves upon previous methods for estimating emissions of ozone precursors from oil and gas operations in Utah’s Uinta Basin by tracking one-time and ongoing emission events on a well-by-well basis. The proposed method has proven highly accurate at predicting drilling and production activity and includes uncertainty estimates to describe the range of potential emissions inventory outcomes. If similar input data are available in other oil and gas producing regions, then the method developed here could be applied to those regions as well.