Mechanistic Pathway of Carbon Monoxide Off-Gassing from Wood Pellets

The off-gassing of carbon monoxide (CO) from stored wood pellets has been identified as a significant problem, potentially resulting in adverse occupational and residential exposures. The mechanism for the production of CO from wood pellets has not been fully identified. In this study, a multiple step process has been hypothesized. The reaction is initiated by the autoxidation of unsaturated compounds, including fatty acids and terpenes, by molecular oxygen. As a byproduct of these reactions, hydroxyl radicals are formed. Then, the bulk of CO results from the reactions of hemicellulose and hydroxyl radicals. To understand the mechanistic pathway of CO off-gassing, a number of experiments were conducted in which CO was measured and evolved organic compounds were analyzed using gas chromatography–mass spectrometry (GC–MS). These studies identified a number of short- and long-chain aldehydes from the evolved gases that indicates the autoxidation mechanism. However, there is insufficient mass of these unsaturated compounds in wood to support the observed mass of off-gassed CO. However, autoxidation would form hydroxyl radicals. The role of hydroxyl radicals was investigated using a radical scavenger, and its role in CO production was confirmed. Thus, if the autoxidation initiation can be eliminated, then CO off-gassing from pellets would be substantially reduced. Destruction of the reactive compounds with ozone led to a suppression of CO formation, suggesting an approach to process the wood fiber that would result in low or no CO emission wood pellets

Multilinear Model for Spatial Pattern Analysis of the Measurement of Haze and Visual Effects Project

A multilinear model was developed for the analysis of the spatial patterns and possible sources affecting haze and its visual effects in the southwestern United States. The data from the project Measurement of Haze and Visual Effects (MOHAVE) collected during the late winter and mid-summer of 1992 at the monitoring sites in four states (i.e., California, Arizona, Nevada and Utah) were used in the study. The three-way data array was analyzed by a four-product-term model. This study makes a direct effort to include wind patterns as a component in the model in order to obtain the information of the spatial patterns of source contributions. The solution is computed using the conjugate gradient algorithm with applied non-negativity constraints. For the winter data set, reasonable solutions contained six sources and six wind patterns. The analysis of summer data required seven sources and seven wind patterns. The ME results are compared to the prior single-species empirical orthogonal function analysis results and prior work describing the transport pathways

Locating and Quantifying PCB Sources in Chicago: Receptor Modeling and Field Sampling

Potential source contribution function (PSCF) modeling using polychlorinated biphenyl (PCB) concentrations measured in the Chicago area resolved three PCB source sectors. They were (i) the direction northwest of Chicago, (ii) the direction southwest of Chicago, and (iii) the south side of Chicago in the neighborhood of Lake Calumet. The area south of Chicago was further examined by taking upwind/downwind samples near a landfill and sludge drying beds. Results identified the sludge drying beds and a large landfill as PCB sources to the atmosphere. Another PCB source identified in Chicago was a transformer storage yard. This site had the highest upwind/downwind concentration increments in this study (downwind PCB concentrations were more than 5 times those in the upwind air). These PCB sources were characterized in terms of inventories, emission rates, contributions, and PCB congener profiles (fingerprints). Preliminarily results indicate that the sludge may emit up to 90 kg/yr of PCBs to the air. This amount is probably not a significant contribution of PCBs to the Chicago atmosphere on the basis of dispersion modeling results and a simple box model

Source Apportionment and Spatial Distributions of Coarse Particles During the Regional Air Pollution Study

To identify the coarse particle sources and to estimate the variability in their contributions to coarse particle mass (CPM) concentrations across the St. Louis metropolitan area, positive matrix factorization (PMF) was applied to historic ambient coarse particle compositional data from 10 Regional Air Pollution Study/Regional Air Monitoring System (RAPS/RAMS) monitoring sites in St. Louis. Coarse particles in this study had aerodynamic sizes between 2.4 and 20 µm. The sources were qualitatively identified, and the source contributions were quantitatively estimated. Nine sources were identified for 8 of the 10 sampling sites (except rural sites 122 and 124) including soil, cement kiln/quarry, iron and steel, motor vehicle, incinerator, pigment plant, primary/secondary lead smelter, zinc smelter, and copper production, respectively. At site 122, five sources were identified as soil, cement kiln/quarry, motor vehicle, incinerator, and zinc smelter. At site 124, six sources were identified as soil, cement kiln/quarry, motor vehicle, incinerator, primary/secondary lead smelter, and zinc smelter. Soil was the largest coarse particle source across the study area (6.15 µg/m3, 29.3%). Cement kiln/quarry, iron and steel, and motor vehicle sources were the other large contributions to the coarse particles mass (5.27 µg/m3, 25.1%; 3.53 µg/m3, 16.8%; 2.72 µg/m3, 12.9%). The results of this study suggest there can be significant potential for exposure misclassification in time-series epidemiologic studies when regressing health outcomes against source contributions if they were to be estimated at a single central monitoring site

Secondary Organic Aerosol from Ozonolysis of Biogenic Volatile Organic Compounds: Chamber Studies of Particle and Reactive Oxygen Species Formation

The formation of secondary organic aerosol (SOA) produced from α-pinene, linalool, and limonene by ozonolysis was examined using a dynamic chamber system that allowed the simulation of ventilated indoor environments. Experiments were conducted at typical room temperatures and air exchange rates. Limonene ozonolysis produced the highest SOA mass concentrations and linalool the lowest with α-pinene being intermediate. Simplified empirical modeling simulations were conducted to provide insights into reaction chemistry. Assessment of variability of particle-bound reactive oxygen species (ROS) may be important in the understanding of health effects associated with particulate matter. The ROS intensities defined as ROS/SOA mass were found to be moderately correlated with the SOA densities. Greater ROS intensities were observed for the cases where ozone was in excess. ROS intensities approached a relatively constant value in the region where ozone was in deficit. The estimated initial ROS half-life time was approximately 6.5 h at room temperature suggesting the time sensitivity of ROS measurements. The ROS formed from terpenoid ozonolysis could be separated into three categories: short-lived/high reactive/volatile, semivolatile/relatively stable and nonvolatile/low reactive species based on ROS measurements under various conditions. Such physical characterization of the ROS in terms of reactivity and volatility provides some insights into the nature of ROS

Atmospheric Mercury (Hg) in the Adirondacks: Concentrations and Sources

Hourly averaged gaseous elemental Hg (GEM) concentrations and hourly integrated reactive gaseous Hg (RGM), and particulate Hg (HgP) concentrations in the ambient air were measured at Huntington Forest in the Adirondacks, New York from June 2006 to May 2007. The average concentrations of GEM, RGM, and HgP were 1.4 ± 0.4 ng m−3, 1.8 ± 2.2 pg m−3, and 3.2 ± 3.7 pg m−3, respectively. RGM represents P represents P were measured during winter and summer whereas the lowest mean concentrations were measured during spring and fall. Significant diurnal patterns were apparent in warm seasons for all species whereas diurnal patterns were weak in cold seasons. RGM was better correlated with ozone concentration and temperature in both warm (ρ RGM - ozone = 0.57, p RGM - temperature = 0.62, p RGM - ozone= 0.48, p = 0.002; ρ RGM - temperature = 0.54, p = 0.011) than the other species. Potential source contribution function (PSCF) analysis was applied to identify possible Hg sources. This method identified areas in Pennsylvania, West Virginia, Ohio, Kentucky, Texas, Indiana, and Missouri, which coincided well with sources reported in a 2002 U.S. mercury emissions inventory

Locating and Quantifying PCB Sources in Chicago: Receptor Modeling and Field Sampling

Potential source contribution function (PSCF) modeling using polychlorinated biphenyl (PCB) concentrations measured in the Chicago area resolved three PCB source sectors. They were (i) the direction northwest of Chicago, (ii) the direction southwest of Chicago, and (iii) the south side of Chicago in the neighborhood of Lake Calumet. The area south of Chicago was further examined by taking upwind/downwind samples near a landfill and sludge drying beds. Results identified the sludge drying beds and a large landfill as PCB sources to the atmosphere. Another PCB source identified in Chicago was a transformer storage yard. This site had the highest upwind/downwind concentration increments in this study (downwind PCB concentrations were more than 5 times those in the upwind air). These PCB sources were characterized in terms of inventories, emission rates, contributions, and PCB congener profiles (fingerprints). Preliminarily results indicate that the sludge may emit up to 90 kg/yr of PCBs to the air. This amount is probably not a significant contribution of PCBs to the Chicago atmosphere on the basis of dispersion modeling results and a simple box model

Characterization of Emissions from Grass Pellet Combustion

Emission factors of pollutants from combustion of five different types of grass pellets with ash content ranging from 3% to 13% were measured and compared to a premium type wood pellet with ash content 0.6% at low and high loads, respectively. The effects of fuel properties on the grass pellet combustion emissions were also studied. Criteria pollutants including PM_2.5, NO_<i>x</i>, SO₂, and CO were continuously monitored using an EPA CTM-039 dilution sampling system. PM₁₀ emissions from grass combustion were found to be higher when compared to wood pellet emissions at both low and high loads (26–40 and 36–60 mg MJ^–1, respectively). The PM_2.5 emissions were strongly correlated to the ash content of the fuel (<i>R</i>² = 0.939). CO emissions were found to be higher for grass combustion indicating an incomplete combustion. PM_2.5 samples collected on Teflon and quartz substrates were analyzed for ions and trace elements. About 60–75% of the PM_2.5 fraction was recovered that included K of about 20–30%, sulfate about 16–25%, and chloride of about 10–15%. Semivolatile organic compounds collected on quartz and polyurethane foam (PUF) were also analyzed for molecular markers, PAHs and PCDD/Fs. PAH emissions were strongly correlated to the CO (<i>r</i>² = 0.80). The PCDD/F emissions were clearly a function of chlorine content of the fuel (<i>r</i>² = 0.98). A strong correlation exists between emitted levoglucosan and PM_2.5 indicating levoglucosan, a molecular marker for cellulose combustion (<i>r</i>² = 0.87). All of the emissions were found to be higher for grass pellets compared to wood pellets and are higher at high loads than at low loads

Advanced Factor Analysis of Spatial Distributions of PM_2.5 in the Eastern United States

This work analyzes PM2.5 24-h average concentrations measured every third day at over 300 locations in the eastern United States during 2000. The non-negative factor analytic model, Positive Matrix Factorization, has been enhanced by modeling the dependence of PM2.5 concentra tions on temperature, humidity, pressure, ozone concentrations, and wind velocity vectors. The model comprises 12 general factors, augmented by 5 urban-only factors intended to represent excess concentration present in urban locations only. The computed factor components or concentration fields are displayed as concentration maps, one for each factor, showing how much each factor contributes to the average concentration at each location. The factors are also displayed as flux maps that illustrate the spatial movement of PM2.5 aerosol, thus enabling one to pinpoint potential source areas of PM2.5. The quality of the results was investigated by examining how well the model reproduces especially high concentrations of PM2.5 on specific days at specific locations. Delimiting the spatial extent of all such factors that exhibit a clear regional maximum surrounded by an almost-zero outer domain lowered the uncertainty in the computed results

Advanced Factor Analysis of Spatial Distributions of PM_2.5 in the Eastern United States

This work analyzes PM2.5 24-h average concentrations measured every third day at over 300 locations in the eastern United States during 2000. The non-negative factor analytic model, Positive Matrix Factorization, has been enhanced by modeling the dependence of PM2.5 concentra tions on temperature, humidity, pressure, ozone concentrations, and wind velocity vectors. The model comprises 12 general factors, augmented by 5 urban-only factors intended to represent excess concentration present in urban locations only. The computed factor components or concentration fields are displayed as concentration maps, one for each factor, showing how much each factor contributes to the average concentration at each location. The factors are also displayed as flux maps that illustrate the spatial movement of PM2.5 aerosol, thus enabling one to pinpoint potential source areas of PM2.5. The quality of the results was investigated by examining how well the model reproduces especially high concentrations of PM2.5 on specific days at specific locations. Delimiting the spatial extent of all such factors that exhibit a clear regional maximum surrounded by an almost-zero outer domain lowered the uncertainty in the computed results