David W. DuBois

Long-Term Efficiencies of Dust Suppressants to Reduce PM10 Emissions from Unpaved Roads

A 14-month study was undertaken to assess the long-term efficiencies of four dust suppressants (i.e., biocatalyst stabilizer, polymer emulsion, petroleum emulsion with polymer, and nonhazardous crude-oil-containing materials) to reduce the emission of PM10 from public unpaved roads. PM10 emission rates were calculated for each test section and for an untreated section for comparison purposes. Emission rates were determined from PM10 concentrations measured from 1.25 m to 9 m upwind and downwind of the road and above its surface. Calculated emission factors ranged between zero and 1,361 g-PM10/vehicle kilometer traveled (VKT) (average uncertainty = ±35 g-PM10/ VKT) for the four types applied. One week after application, suppressant efficiencies ranged between 33% and 100% for the four types applied. After 8-12 months of exposure to weathering and 4,900-6,400 vehicle passes, the suppressant efficiencies ranged from zero to 95%. Roadway surface properties associated with low-emitting, well-suppressed surfaces are (1) surface silt loading and (2) strength and flexibility of suppressant material as a surface layer or cover. Suppressants that create surface conditions resistant to brittle failure are less prone to deterioration and more likely to increase long-term reduction efficiency for PM10 emissions on unpaved roads.

Air pollution and hospital emergency room and admissions for cardiovascular and respiratory diseases in Doña Ana County, New Mexico.

INTRODUCTION Doña Ana County in New Mexico regularly experiences severe air pollution episodes associated with windblown dust and fires. Residents of Hispanic/Latino origin constitute the largest population group in the region. We investigated the associations of ambient particulate matter and ozone with hospital emergency room and admissions for respiratory and cardiovascular visits in adults. METHODS We used trajectories regression analysis to determine the local and regional components of particle mass and ozone. We applied Poisson generalized models to analyze hospital emergency room visits and admissions adjusted for pollutant levels, humidity, temperature and temporal and seasonal effects. RESULTS We found that the sources within 500km of the study area accounted for most of particle mass and ozone concentrations. Sources in Southeast Texas, Baja California and Southwest US were the most important regional contributors. Increases of cardiovascular emergency room visits were estimated for PM10 (3.1% (95% CI: -0.5 to 6.8)) and PM10-2.5 (2.8% (95% CI: -0.2 to 5.9)) for all adults during the warm period (April-September). When high PM10 (>150μg/m(3)) mass concentrations were excluded, strong effects for respiratory emergency room visits for both PM10 (3.2% (95% CI: 0.5-6.0)) and PM2.5 (5.2% (95% CI: -0.5 to 11.3)) were computed. CONCLUSIONS Our analysis indicated effects of PM10, PM2.5 and O3 on emergency room visits during the April-September period in a region impacted by windblown dust and wildfires.

Soil humic-like organic compounds in prescribed fire emissions using nuclear magnetic resonance spectroscopy.

Here we present the chemical characterization of the water-soluble organic carbon fraction of atmospheric aerosol collected during a prescribed fire burn in relation to soil organic matter and biomass combustion. Using nuclear magnetic resonance spectroscopy, we observed that humic-like substances in fire emissions have been associated with soil organic matter rather than biomass. Using a chemical mass balance model, we estimated that soil organic matter may contribute up to 41% of organic hydrogen and up to 27% of water-soluble organic carbon in fire emissions. Dust particles, when mixed with fresh combustion emissions, substantially enhances the atmospheric oxidative capacity, particle formation and microphysical properties of clouds influencing the climatic responses of atmospheric aeroso. Owing to the large emissions of combustion aerosol during fires, the release of dust particles from soil surfaces that are subjected to intense heating and shear stress has, so far, been lacking.

Regional Source Identification Using Lagrangian Stochastic Particle Dispersion and HYSPLIT Backward-Trajectory Models

ABSTRACT The main objective of this study was to investigate the capabilities of the receptor-oriented inverse mode Lagrangian Stochastic Particle Dispersion Model (LSPDM) with the 12-km resolution Mesoscale Model 5 (MM5) wind field input for the assessment of source identification from seven regions impacting two receptors located in the eastern United States. The LSPDM analysis was compared with a standard version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) single-particle backward-trajectory analysis using inputs from MM5 and the Eta Data Assimilation System (EDAS) with horizontal grid resolutions of 12 and 80 km, respectively. The analysis included four 7-day summertime events in 2002; residence times in the modeling domain were computed from the inverse LSPDM runs and HYPSLIT-simulated backward trajectories started from receptor-source heights of 100, 500, 1000, 1500, and 3000 m. Statistics were derived using normalized values of LSPDM- and HYSPLIT-predicted residence times versus Community Multiscale Air Quality model-predicted sulfate concentrations used as baseline information. From 40 cases considered, the LSPDM identified first- and second-ranked emission region influences in 37 cases, whereas HYSPLIT-MM5 (HYSPLIT-EDAS) identified the sources in 21 (16) cases. The LSPDM produced a higher overall correlation coefficient (0.89) compared with HYSPLIT (0.55–0.62). The improvement of using the LSPDM is also seen in the overall normalized root mean square error values of 0.17 for LSPDM compared with 0.30–0.32 for HYSPLIT. The HYSPLIT backward trajectories generally tend to underestimate near-receptor sources because of a lack of stochastic dispersion of the backward trajectories and to overestimate distant sources because of a lack of treatment of dispersion. Additionally, the HYSPLIT backward trajectories showed a lack of consistency in the results obtained from different single vertical levels for starting the backward trajectories. To alleviate problems due to selection of a backward-trajectory starting level within a large complex set of 3-dimensional winds, turbulence, and dispersion, results were averaged from all heights, which yielded uniform improvement against all individual cases. IMPLICATIONS Backward-trajectory analysis is one of the standard procedures for determining the spatial locations of possible emission sources affecting given receptors, and it is frequently used to enhance receptor modeling results. This analysis simplifies some of the relevant processes such as pollutant dispersion, and additional methods have been used to improve receptor-source relationships. A methodology of inverse Lagrangian stochastic particle dispersion modeling was used in this study to complement and improve standard backward-trajectory analysis. The results show that inverse dispersion modeling can identify regional sources of haze in national parks and other regions of interest.

Evaluation of Regional-Scale Receptor Modeling

Abstract The ability of receptor models to estimate regional contributions to fine particulate matter (PM2.5) was assessed with synthetic, speciated datasets at Brigantine National Wildlife Refuge (BRIG) in New Jersey and Great Smoky Mountains National Park (GRSM) in Tennessee. Synthetic PM2.5 chemical concentrations were generated for the summer of 2002 using the Community Multiscale Air Quality (CMAQ) model and chemically speciated PM2.5 source profiles from the U.S. Environmental Protection Agency (EPA)’s SPECIATE and Desert Research Institute’s source profile databases. CMAQ estimated the “true” contributions of seven regions in the eastern United States to chemical species concentrations and individual source contributions to primary PM2.5 at both sites. A seven-factor solution by the positive matrix factorization (PMF) receptor model explained approximately 99% of the variability in the data at both sites. At BRIG, PMF captured the first four major contributing sources (including a secondary sul-fate factor), although diesel and gasoline vehicle contributions were not separated. However, at GRSM, the resolved factors did not correspond well to major PM2.5 sources. There were no correlations between PMF factors and regional contributions to sulfate at either site. Unmix produced five- and seven-factor solutions, including a secondary sulfate factor, at both sites. Some PMF factors were combined or missing in the Unmix factors. The trajectory mass balance regression (TMBR) model apportioned sulfate concentrations to the seven source regions using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) trajectories based on Meteorological Model Version 5 (MM5) and Eta Data Simulation System (EDAS) meteorological input. The largest estimated sulfate contributions at both sites were from the local regions; this agreed qualitatively with the true regional apportionments. Estimated regional contributions depended on the starting elevation of the trajectories and on the meteorological input data.

Spatial Variability of Unpaved Road Dust PM10 Emission Factors near El Paso, Texas

Abstract The testing re-entrained aerosol kinetic emissions from roads technique is compared with distance-based emission factors (EFs; g/VKT) measured downwind of a dirt road by using towers instrumented with real-time meteorological and particle sensors at multiple heights. The emission potential (EP), defined as the EF divided by the vehicle speed (m/sec), and weight index permits the inter-comparison of emissions from multiple roadways surveyed by the TRAKER vehicle. A survey of 72 km of un-paved roads on the Ft. Bliss Military Base near El Paso, Texas, indicated that 60% of all measured EPs fell between 6.7 (g/VKT)/(m/sec) and 9.6 (g/VKT)/(m/sec). The EP measured across the base was ~50% lower than those collected in the vicinity of the instrumented towers. This implies that EFs measured for other vehicles on the same test section should be reduced by 50% to more accurately represent EFs for the entire military base. Using geographic information system-based soil maps, the inferred EFs are related to differences in soil types over the survey area. Variations among five different soil types accounted for <10% of variation in EP. Individual measurements using the testing re-entrained aerosol kinetic emissions from roads technique did show larger spatial variations in EP; however, these were not effectively captured by the soil classifications, partly because of the comparatively coarse spatial classification used in the soil survey data.

Fine particulate matter and visibility in the Lake Tahoe Basin: Chemical characterization, trends, and source apportionment

Speciated PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm) data has been collected for about 20 yr (1990–present) at a rural location in the Lake Tahoe Basin (Bliss State Park) and about 15 yr (1989–2004) at an urban site in South Lake Tahoe. The Bliss State Park site is representative of the Desolation Wilderness, a Class I air quality area with visibility protection under the Clean Air Act. Carbonaceous aerosol dominated reconstructed fine mass at both sites, with 58% at Bliss State Park (BLIS) and 68% at South Lake Tahoe (SOLA). Fine mass at SOLA is 2.5 times that at BLIS, mainly due to enhanced organic and elemental carbon (OC and EC). SOLA experiences a winter peak in PM2.5 mainly due to OC and EC from residential wood combustion, whereas BLIS experiences a summer peak in PM2.5 mainly due to OC and EC from wildfires. Carbonaceous aerosol dominates visibility impairment, causing about ½ the reconstructed aerosol light extinction at BLIS and 70% at SOLA. Trend analysis (1990–2009) showed statistically significant decreases in aerosol extinction at BLIS on 20% best and 60% middle visibility days and statistically insignificant upward trends on 20% worst days. SOLA (1990–2003) showed statistically significant decreases in aerosol extinction for all day categories, driven by decreasing OC and EC. From the regional haze rule baseline period of 2000–2004 until 2005–2009, BLIS saw 20% best days improving and 20% worst days getting worse due to increased wildfire effects. Receptor modeling was performed using positive matrix factorization (PMF) and chemical mass balance (CMB). It confirmed that (1) biomass burning dominanted PM2.5 sources at both sites with increasing importance over time; (2) low combustion efficiency burning accounts for most of the biomass burning contribution; (3) road dust and traffic contributions were much higher at SOLA than at BLIS; and (4) industrial combustion and salting were minor sources. Implications: Visibility on the 20% worst visibility days decreased at Bliss State Park, which represents the Desolation and Mokelumne Wilderness Class I areas. This decrease in visibility, contrary to Regional Haze Rule requirements, was mainly due to increased wildfire activity. Increased sulfate-caused light extinction on worst visibility days may be due to long-range transport from Asia. These factors may make it difficult to achieve reasonable progress toward the national visibility goal. Methods need to be developed to account for the effect of wildfires and intercontinental transport when evaluating progress toward the national goal. Supplemental Materials: Supplemental materials are available for this article. Go to the publishers online edition of the Journal of the Air & Waste Management Association for details of the receptor modeling, including the average and signal-to-noise ratio (SNR) of PM2.5 mass and chemical concentrations for the 3 PMF modeling groups, PMF factor profiles, and sensitivity test results for the EV-CMP modeling.

Wind-mediated horseweed (Conyza canadensis) gene flow: pollen emission, dispersion, and deposition.

Abstract Horseweed (Conyza canadensis) is a problem weed in crop production because of its evolved resistance to glyphosate and other herbicides. Although horseweed is mainly self-pollinating, glyphosate-resistant (GR) horseweed can pollinate glyphosate-susceptible (GS) horseweed. To the best of our knowledge, however, there are no available data on horseweed pollen production, dispersion, and deposition relative to gene flow and the evolution of resistance. To help fill this knowledge gap, a 43-day field study was performed in Champaign, Illinois, USA in 2013 to characterize horseweed atmospheric pollen emission, dispersion, and deposition. Pollen concentration and deposition, coupled with atmospheric data, were measured in a source field (180 m by 46 m) and its surrounding areas up to 1 km downwind horizontally and up to 100 m vertically. The source strength (emission rate) ranged from 0 to 140 pollen grains per plant per second (1170 to 2.1×106 per plant per day). For the life of the study, the estimated number of pollen grains generated from this source field was 10.5×1010 (2.3×106 per plant). The release of horseweed pollen was not strongly correlated to meteorological data and may be mainly determined by horseweed physiology. Horseweed pollen reached heights of 80 to100 m, making long-distance transport possible. Normalized (by source data) pollen deposition with distance followed a negative-power exponential curve. Normalized pollen deposition was 2.5% even at 480 m downwind from the source edge. Correlation analysis showed that close to or inside the source field at lower heights (≤3 m) vertical transport was related to vertical wind speed, while horizontal pollen transport was related to horizontal wind speed. High relative humidity prevented pollen transport at greater heights (3–100 m) and longer distances (0–1000 m) from the source. This study can contribute to the understanding of how herbicide-resistance weeds or invasive plants affect ecology through wind-mediated pollination and invasion.

Short communication: Development of a geospatial screening tool to identify source areas of windblown dust

Soil properties and air-mass backward trajectories were integrated into a geographical information systems (GIS) tool to identify geographical regions that were likely to have significant influence on dust concentrations at Class I national parks and wilderness areas in US. The Windblown Dust Index (WDI) was introduced by spatial analysis of wind erosion and land use/land cover data for North America to identify potential area sources of windblown dust. The spatial probability density maps of backward trajectories were utilized to determine the number of trajectory points that passed near a grid cell at speeds higher than a specified threshold value. Analysis of data for the Salt Creek and White Mountain wilderness areas highlighted the significant potential of both local and regional sources of windblown dust at the two sites, with evidence for seasonal variation. These data are useful in evaluating the importance of windblown dust source areas and developing cost-effective targeted studies and/or mitigation strategies.

The effect of anthropogenic volatile organic compound sources on ozone in Boise, Idaho

Environmental context Volatile organic compounds are precursors of ozone, a pollutant with adverse environmental effects. It is important to determine the associations between the various sources of volatile organic compounds and ozone levels because emission controls are based on sources. We estimated the contributions of specific sources of volatile organic compounds on ozone levels using both measurements and statistical models, and found that traffic is the largest source even in events when wildfire smoke is present. Abstract Here, we present the application of a tiered approach to apportion the contributions of volatile organic compound (VOC) sources on ozone (O3) concentrations. VOCs from acetylene to n-propylbenzene were measured at two sites at Boise, Idaho, using an online pneumatically focussed gas chromatography system. The mean 24-h concentrations of individual VOCs varied from 0.4ppbC (parts per billion carbon) for 1-butene to 23.2ppbC for m- and p-xylene. The VOC sources at the two monitoring sites were determined by positive matrix factorisation. They were attributed to: (i) liquefied petroleum and natural gas (LPG/NG) emissions; (ii) fugitive emissions of olefins from fuel and solvents; (iii) fugitive emissions of aromatic VOCs from area sources and (iv) vehicular emissions. Vehicle exhausts accounted for 36 to 45% of VOCs followed by LPG/NG and fugitive emissions of aromatic VOCs. Evaluation of photochemical changes showed that the four separate VOC sources were identified by PMF rather than different stages of photochemical processing of fresh emissions. The contributions of VOC sources on daily 8-h maximum O3 concentrations measured at seven locations in the metropolitan urban area were identified by regression analysis. The four VOC sources added, on average, 6.4 to 16.5 parts per billion by volume (ppbv) O3, whereas the unexplained (i.e. intercept) O3 was comparable to non-wildfire policy-relevant background O3 levels in the absence of all anthropogenic emissions of VOC precursors in North America for the region. Traffic was the most significant source influencing O3 levels contributing up to 32ppbv for days with O3 concentrations higher than 75ppbv.