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John G Watson

Publications and source records attributed to John G Watson.

17 recordsLinked to original sources

Source profiles for industrial, mobile, and area sources in the Big Bend Regional Aerosol Visibility and Observational study.

Representative PM2.5 and PM10 source emissions were sampled in Texas during the Big Bend Regional Aerosol Visibility and Observa (BRAVO) study. Chemical source profiles for elements, ions, and carbon fractions of 145 samples are reported for paved and unpaved road dust, soil dust, motor vehicle exhaust, vegetative burning, four coal-fired power stations, an oil refinery catalytic cracker, two cement kilns, and residential meat cooking. Several samples were taken from each emitter and source type, and these were averaged by source type, and in source subgroups based on commonality of chemical composition. The standard deviation represents the variability of the chemical mass fractions. BRAVO profiles differed in some respects from profiles measured elsewhere. High calcium abundances in geological dust, high selenium abundances in coal-fired power stations, and high antimony abundances in oil refinery catalytic cracker emissions were found. Abundances of eight thermally evolved carbon fractions [Atmos. Environ. 28 (15) (1994) 2493] differ among combustion sources, and a Monte Carlo simulation demonstrates that these differences are sufficient to differentiate among several carbon-emitters.

Air Pollutants↗

On-road measurement of automotive particle emissions by ultraviolet lidar and transmissometer: instrument.

A novel vehicle emissions remote sensing system (VERSS) for the on-road measurement of fuel-based particulate matter (PM) emission factors is described. This system utilizes two complementary PM channels using an ultraviolet Lidar and transmissometer for the measurement of PM mass column content behind a passing vehicle. Ratioing the PM mass column content with the carbon mass column content, simultaneously measured with infrared absorption, yields the fuel-based PM mass emission factor. The transmissometer directly yields PM extinction coefficients without calibration, while the Lidar measurement of PM backscatter coefficients is calibrated through laboratory measurements of gases with well-known backscatter coefficients. The PM mass column content is calculated from these extinction and backscatter coefficients with the help of mass backscatter and extinction efficiencies obtained from theoretical calculations. This novel VERSS has been used extensively in a major air quality study, and example data are presented.

Air Pollutants↗

Emissions from charbroiling and grilling of chicken and beef.

Emission rates for fine particle (<2.5 microm) mass (PM2.5), carbon (organic/elemental), inorganic ions (SO4(2-), NO3-, NH4+), elements (primarily metals), and speciated organic compounds are reported for charbroiling hamburger, steak, and chicken. The PM2.5 rates for charbroiling meats ranged from 4.4 to 11.6 g/kg of uncooked meat in this study. No mass-emission rates are available from grilling, but the speciated organic data are available for these samples. Emission rates varied by type of appliance, meat, meat-fat content, and cooking conditions. High-fat hamburger cooked on an underfired charbroiler emitted the highest amount of PM2.5. The emissions were almost exclusively composed of organic carbon, with small amounts of elements and inorganic ions. Water-soluble K+ and Cl-, which are used as indicators of wood smoke in source apportionment studies, were also present in meat-cooking emissions. The speciated organic compounds that were measured include polycyclic aromatic hydrocarbons (PAHs), cholesterol, and the long-chain gamma-lactones. Charbroiling emissions yielded an average of approximately 3-5 times more PAHs, approximately 20 times more cholesterol, and approximately 10 times more lactones than grilling. These data were utilized in the ambient source apportionment analysis for the 1997 Northern Front Range Air Quality Study source apportionment.

Air Pollutants↗

Air pollution and heart rate variability among the elderly in Mexico City.

BACKGROUND: Suspended particles and ozone have been associated with varying degrees of cardiac autonomic dysfunction. METHODS: In Mexico City, residents from a nursing home underwent heart rate variability analysis every other day for 3 months. Indoor and outdoor PM2.5 (particulate matter less than 2.5 mm in diameter) were measured daily at the nursing home. Levels of ozone and other atmospheric pollutants were obtained from a nearby automated monitoring station. RESULTS: Of the initial 42 screened participants, 34 (81%) were followed during the study period. The 24-hour average levels of indoor PM2.5 ranged from 15 to 67 micro g/m3, and outdoor PM2.5 ranged from 9 to 87 micro g/m3. Daily 1-hour maximum ozone levels ranged from 47 to 228 ppb. After adjusting for age and heart rate, we observed a strong decrease in the high frequency component of heart rate variability and the average 24-hour concentrations of PM2.5. Participants with hypertension had considerably larger reductions in their HF-HRV (high frequency-heart rate variability) component in relation to both ozone and PM2.5 exposure. CONCLUSIONS: Our results suggest that ambient levels of PM2.5 and ozone can reduce the high-frequency component of heart rate variability in elderly subjects living in Mexico City and that subjects with underlying hypertension are particularly susceptible to this effect.

Aged↗

Chemical composition of PM2.5 and PM10 in Mexico City during winter 1997.

PM2.5 and PM10 were measured over 24-h intervals at six core sites and at 25 satellite sites in and around Mexico City from 23 February to 22 March 1997. In addition, four 6-h samples were taken each day at three of the core sites. Sampling locations were selected to represent regional, central city, commercial, residential, and industrial portions of the city. Mass and light transmission concentrations were determined on all of the samples, while elements, ions and carbon were measured on approximately two-thirds of the samples. PM10 concentrations were highly variable, with almost three-fold differences between the highest and lowest concentrations. Fugitive dust was the major cause of PM10 differences, although carbon concentrations were also highly variable among the sampling sites. Approximately 50% of PM10 was in the PM2.5 fraction. The majority of PM mass was comprised of carbon, sulfate, nitrate, ammonium and crustal components, but in different proportions on different days and at different sites. The largest fine-particle components were carbonaceous aerosols, constituting approximately 50% of PM2.5 mass, followed by approximately 30% secondary inorganic aerosols and approximately 15% geological material. Geological material is the largest component of PM10, constituting approximately 50% of PM10 mass, followed by approximately 32% carbonaceous aerosols and approximately 17% secondary inorganic aerosols. Sulfate concentrations were twice as high as nitrate concentrations. Sulfate and nitrate were present as ammonium sulfate and ammonium nitrate. Approximately two-thirds of the ammonium sulfate measured in urban areas appears to have been transported from regions outside of the study domain, rather than formed from emissions in the urban area. Diurnal variations are apparent, with two-fold increases in concentration from night-time to daytime. Morning samples had the highest PM2.5 and PM10 mass, secondary inorganic aerosols and carbon concentrations, probably due to a shallow surface inversion and rush-hour traffic.

Aerosols↗

Chapter one: exposure measurements.

Determining human exposure to suspended particulate concentrations requires measurements that quantify different particle properties in microenvironments where people live, work, and play. Particle mass, size, and chemical composition are important exposure variables, and these are typically measured with time-integrated samples on filters that are later submitted to laboratory analyses. This requires substantial sample handling, quality assurance, and data reduction. Newer technologies are being developed that allow in-situ, time-resolved measurements for mass, carbon, sulfate, nitrate, particle size, and other variables. These are large measurement systems that are more suitable for fixed monitoring sites than for personal applications. Human exposure studies need to be designed to accomplish specific objectives rather than to serve too many purposes. Resources need to be divided among study design, field sampling, laboratory analysis, quality assurance, data management, and data analysis phases. Many exposure projects allocated too little to the non-measurement activities.

Air Pollutants↗

Designing monitoring networks to represent outdoor human exposure.

Measurements of outdoor human exposure to suspended particulate matter (PM) are always constrained by available resources. An effective network design requires tradeoffs between variables measured, the number of sampling locations, sample duration, and sampling frequency. Sampling sites are needed to represent neighborhood and urban spatial scales with minimal influences from nearby sources. Although most PM measurements for determining compliance with standards are taken over 24-h periods every third to sixth day, outdoor human exposure assessment requires measurements taken continuously throughout the day, preferably over durations of 1 h or less. More detailed particle size and chemistry data are also desirable, as smaller size fractions and specific chemicals may be better indicators of adverse health effects than total mass samples.

Air Pollutants↗

Receptor modeling application framework for particle source apportionment.

Receptor models infer contributions from particulate matter (PM) source types using multivariate measurements of particle chemical and physical properties. Receptor models complement source models that estimate concentrations from emissions inventories and transport meteorology. Enrichment factor, chemical mass balance, multiple linear regression, eigenvector. edge detection, neural network, aerosol evolution, and aerosol equilibrium models have all been used to solve particulate air quality problems, and more than 500 citations of their theory and application document these uses. While elements, ions, and carbons were often used to apportion TSP, PM10, and PM2.5 among many source types, many of these components have been reduced in source emissions such that more complex measurements of carbon fractions, specific organic compounds, single particle characteristics, and isotopic abundances now need to be measured in source and receptor samples. Compliance monitoring networks are not usually designed to obtain data for the observables, locations, and time periods that allow receptor models to be applied. Measurements from existing networks can be used to form conceptual models that allow the needed monitoring network to be optimized. The framework for using receptor models to solve air quality problems consists of: (1) formulating a conceptual model; (2) identifying potential sources; (3) characterizing source emissions; (4) obtaining and analyzing ambient PM samples for major components and source markers; (5) confirming source types with multivariate receptor models; (6) quantifying source contributions with the chemical mass balance; (7) estimating profile changes and the limiting precursor gases for secondary aerosols; and (8) reconciling receptor modeling results with source models, emissions inventories, and receptor data analyses.

Air Pollutants↗

Monitoring of particulate matter outdoors.

Recent studies of the size and composition of atmospheric particulate matter (PM) have demonstrated the usefulness of separating atmospheric PM into its fine and coarse components. The need to measure the mass and composition of fine and coarse PM separately has been emphasized by research in exposure, epidemiology, and toxicology of atmospheric PM. This paper provides a background on the size distribution and properties of PM relevant to the differences between fine and coarse particles. Various decisions that must be made when deciding how to separate, collect, and measure PM are discussed. Techniques for monitoring fine and coarse particles, including the US Federal Reference Method for PM2.5 and several techniques for PM10-2.5, are presented. Problems encountered in collecting semivolatile PM and in weighing atmospheric PM collected on a filter are described. Continuous monitoring methods for PM mass and for PM components (carbon, nitrate, and sulfate) are described and brief descriptions are given of analytical techniques for the chemical characterization of collected PM. This information should be especially useful for environmental workers familiar with monitoring methods for total suspended particles or PM10 but who will need to measure PM2, and PM10-2.5 in the future.

Air Pollutants↗

Comparability between PM2.5 and particle light scattering measurements.

Particle light scattering and PM2.5 (particles with aerodynamic diameters less than 2.5 microm) concentration data from air quality studies conducted over the past ten years were examined. Fine particle scattering efficiencies were determined from statistical relationships among measured light scattering and fine and coarse mass concentrations. The resulting fine particle scattering efficiencies ranged from 1.7 m2 g(-1) at Meadview in the Grand Canyon to over 5 m2 g(-1) in Mexico City. Most of the derived line scattering efficiencies were centered around 2 m2 g(-1), which is considerably lower than most values reported from previous studies.

Air Movements↗

Spatial differences in outdoor PM10 mass and aerosol composition in Mexico City.

Twenty-five MiniVol samplers were operated throughout the Mexico City metropolitan region from February 22 through March 22, 1997, to evaluate the variability of PM10 concentrations and composition. The highest PM10 concentrations were found in neighborhoods with unpaved or dirty roads, and elements related to crustal material were the main cause of differences from nearby (<200 m) monitors that were not adjacent to the roadbed. SO4(2-) concentrations were homogeneous across the city. SO4(2-) measured at the city boundaries was about two-thirds of the concentrations measured within the urbanized area, indicating that most SO4(2-) is of regional origin. Elemental carbon (EC) and organic carbon (OC) concentrations were highly variable, with higher concentrations in areas that had high diesel traffic and older vehicles. Spatial correlations among PM10 concentrations were high, even though absolute concentrations were variable, indicating a common effect of meteorology on the concentration or dispersion of local emissions.

Aerosols↗

Visibility: science and regulation.

The 1999 Regional Haze Rule provides a context for this review of visibility, the science that describes it, and the use of that science in regulatory guidance. The scientific basis for the 1999 regulation is adequate. The deciview metric that tracks progress is an imperfect but objective measure of what people see near the prevailing visual range. The definition of natural visibility conditions is adequate for current planning, but it will need to be refined as visibility improves. Emissions from other countries will set achievable levels above those produced by natural sources. Some natural events, notably dust storms and wildfires, are episodic and cannot be represented by annual average background values or emission estimates. Sulfur dioxide (SO2) emission reductions correspond with lower sulfate (SO4(2-)) concentrations and visibility improvements in the regions where these have occurred. Non-road emissions have been growing more rapidly than emissions from other sources, which have remained stable or decreased since 1970. Simpler models representing transport, limiting precursor pollutants, and gas-to-particle equilibrium should be used to understand where and when emission reductions will be effective, rather than large complex models that have insufficient input and validation measurements. Examples of model-based source attribution show large differences among estimates from various modeling systems and with ambient measurements.

Air Pollutants↗

Particle size relationships at the Fresno Supersite.

Aerosol size distributions are presented for a winter intensive study at the Fresno Supersite. The size distributions were consistent with and predictive for continuous PM2.5 measured by beta attenuation. They varied temporally with respect to source type and intensity, with the smallest mean diameters associated with high NOx concentrations during weekday morning rush hours. Conversely, small and large particle and black carbon (BC) concentrations were higher during Sunday and weekday evenings in response to traffic and residential wood combustion emissions. Ambient PM2.5 light scattering (Bsp) was precisely but systematically underestimated during winter, probably because of heating in the sample shelter.

Aerosols↗

Evaluation of OC/EC speciation by thermal manganese dioxide oxidation and the IMPROVE method.

Ambient particulate samples are routinely analyzed for organic and elemental carbon (OC/EC) using either thermal manganese dioxide oxidation (TMO) or thermal volatilization-pyrolysis correction methods, such as the Interagency Monitoring of PROtected Visual Environments (IMPROVE) method with correction by reflectance, or a variation of the National Institute of Occupational Safety and Health (NIOSH) Method 5040 using thermal optical transmittance (TOT). With TMO, EC is modeled after the oxidation properties of submicron graphite and needle coke by MnO2, and is the fraction of total carbon (TC) that is not oxidized at >525 degrees C. In thermal volatilization methods, EC is the fraction of TC that accounts for the light extinction properties of the sample at the start of analysis. Chow et al. (2001) compared IMPROVE and NIOSH methods implemented on the same instrument using 60 samples of various types and found that NIOSH EC was lower than IMPROVE. This study compares total, organic, and elemental carbon measurements from the TMO and IMPROVE thermal optical reflectance (TOR) methods using a sample set consisting of 60 IMPROVE nonurban, 16 Korean urban, 10 Hong Kong urban, and 14 synthetic carbon black samples.

Carbon↗