Reconciliation and interpretation of Big Bend National Park particulate sulfur source apportionment: results from the Big Bend Regional Aerosol and Visibility Observational Study--part I

The Big Bend Regional Aerosol and Visibility Observational (BRAVO) study was an intensive monitoring study from July through October 1999 followed by extensive assessments to determine the causes and sources of haze in Big Bend National Park, located in Southwestern Texas. Particulate sulfate compounds are the largest contributor of haze at Big Bend, and chemical transport models (CTMs) and receptor models were used to apportion the sulfate concentrations at Big Bend to North American source regions and the Carbón power plants, located 225 km southeast of Big Bend in Mexico. Initial source attribution methods had contributions that varied by a factor of > or =2. The evaluation and comparison of methods identified opposing biases between the CTMs and receptor models, indicating that the ensemble of results bounds the true source attribution results. The reconciliation of these differences led to the development of a hybrid receptor model merging the CTM results and air quality data, which allowed a nearly daily source apportionment of the sulfate at Big Bend during the BRAVO study. The best estimates from the reconciliation process resulted in sulfur dioxide (SO2) emissions from U.S. and Mexican sources contributing approximately 55% and 38%, respectively, of sulfate at Big Bend. The distribution among U.S. source regions was Texas, 16%; the Eastern United States, 30%; and the Western United States, 9%. The Carbón facilities contributed 19%, making them the largest single contributing facility. Sources in Mexico contributed to the sulfate at Big Bend on most days, whereas contributions from Texas and Eastern U.S. sources were episodic, with their largest contributions during Big Bend sulfate episodes. On the 20% of the days with the highest sulfate concentrations, U.S. and Mexican sources contributed approximately 71% and 26% of the sulfate, respectively. However, on the 20% of days with the lowest sulfate concentrations, Mexico contributed 48% compared with 40% for the United States.     

Analysis and simulation of wintertime light scattering by the urban aerosol in Dallas-Fort Worth

Wintertime atmospheric light scattering in Dallas, TX, was estimated through the use of aerosol models. Input data for the aerosol models were provided by measurements of aerosol chemistry, physical particle size distributions, and distributions of particulate sulfur by particle size, and by predictions by an atmospheric simulation model. Light scattering measurements provided a basis for testing the aerosol models. The SCAPE thermodynamic equilibrium model was used to estimate the amount of liquid water associated with particles and the ELSIE Mie scattering model was applied to estimate the resulting light scattering. The calculations were based on aerosol properties measured in Dallas during December 1994 and February 1995, and changes in scattering due to hypothetical changes in the aerosol were predicted. The predicted light scattering was compared to scattering measured by an Optec nephelometer; agreement was within 20% in every case.     

Use of Project MOHAVE perfluorocarbon tracer data to evaluate source and receptor models

Project MOHAVE was a major monitoring, modeling, and data analysis study whose objectives included the estimation of the contributions of the Mohave Power Project (MPP) and other sources to visibility impairment in the southwestern United States, in particular at Grand Canyon National Park. A major element of Project MOHAVE was the release of perfluorocarbon tracers at MPP and other locations during 50-day summer and 30-day winter intensive study periods. Tracer data (from about 30 locations) were sequestered until several source and receptor models were used to predict tracer concentrations. None of the models was successful in predicting the tracer concentrations; squared correlation coefficients between predicted and measured tracer were all less than 0.2, and most were less than 0.1.     

Modeling of potential power plant plume impacts on Dallas-Fort Worth visibility

During wintertime, haze episodes occur in the Dallas-Ft. Worth (DFW) urban area. Such episodes are characterized by substantial light scattering by particles and relatively low absorption, leading to so-called "white haze." The objective of this work was to assess whether reductions in the emissions of SO2 from specific coal-fired power plants located over 100 km from DFW could lead to a discernible change in the DFW white haze. To that end, the transport, dispersion, deposition, and chemistry of the plume of a major power plant were simulated using a reactive plume model (ROME). The realism of the plume model simulations was tested by comparing model calculations of plume concentrations with aircraft data of SF6 tracer concentrations and ozone concentrations. A second-order closure dispersion algorithm was shown to perform better than a first-order closure algorithm and the empirical Pasquill-Gifford-Turner algorithm. For plume impact assessment, three actual scenarios were simulated, two with clear-sky conditions and one with the presence of fog prior to the haze. The largest amount of sulfate formation was obtained for the fog episode. Therefore, a hypothetical scenario was constructed using the meteorological conditions of the fog episode with input data values adjusted to be more conducive to sulfate formation. The results of the simulations suggest that reductions in the power plant emissions lead to less than proportional reductions in sulfate concentrations in DFW for the fog scenario. Calculations of the associated effects on light scattering using Mie theory suggest that reduction in total (plume + ambient) light extinction of less than 13% would be obtained with a 44% reduction in emissions of SO2 from the modeled power plant.     

Assessment of the Nested Grid Model Estimates for Driving Regional Visibility Models in the Southwestern United States

ABSTRACT

The Nested Grid Model (NGM) is a primitive-equation meteorological model that is routinely exercised over North America for forecasting purposes by the National Meteorological Center. While prognostic meteorological models are being increasingly used to drive air quality models, their use in conducting annual simulations requires significant resources. NGM estimates of wind fields and other meteorological variables provide an attractive alternative since they are typically archived and readily available for an entire year. Preliminary evaluation of NGM winds during the summer of 1992 for application to the region surrounding the Grand Canyon National Park showed serious shortcomings. The NGM winds along the borders between California, Arizona and Mexico tend to be northwesterly with a speed of about 6 m/sec, while the observed flow is predominantly southerly at about 2-5 m/sec. The mesoscale effect of a thermal low pressure area over the highly heated Southern California and western Arizona deserts does not appear to be represented by the NGM because of its coarse resolution and the use of sparse observations in that region. Tracer simulations and statistical evaluation against special high resolution observations of winds in the southwest United States clearly demonstrate the northwest bias in NGM winds and its adverse effect on predictions of an air quality model. The “enhanced” NGM winds, in which selected wind observations are incorporated in the NGM winds using a diagnostic meteorological model provide additional confirmation on the primary cause of the northwest bias. This study has demonstrated that in situations where limited resources prevent the use of prognostic meteorological models, previously archived coarse resolution wind fields in which additional observations are incorporated to correct known biases provide an attractive option.     

Guidance for the performance evaluation of three-dimensional air quality modeling systems for particulate matter and visibility

Guidance for the performance evaluation of three-dimensional air quality modeling systems for particulate matter and visibility is presented. Four levels are considered: operational, diagnostic, mechanistic, and probabilistic evaluations. First, a comprehensive model evaluation should be conducted in at least two distinct geographical locations and for several meteorological episodes. Next, streamlined evaluations can be conducted for other similar applications if the comprehensive evaluation is deemed satisfactory. In all cases, the operational evaluation alone is insufficient, and some diagnostic evaluation must always be carried out. Recommendations are provided for designing field measurement programs that can provide the data needed for such model performance evaluations.     

Study of the relationship of distant SO2 emissions to Dallas-Fort Worth winter haze

A study was conducted to estimate the changes in wintertime visual air quality in Dallas-Fort Worth (DFW) that might occur due to proposed reductions in SO2 emissions at two steam electric generating plants in eastern Texas, each over 100 km from the city. To provide information for designing subsequent investigations, the haze was characterized broadly during the first year of the study. Meteorological data acquired then demonstrated that, during haze episodes, emissions from only one of the two plants were likely to be transported directly to DFW. Therefore, the second year of the study was centered on just one of the power plants. Air quality was then characterized within the urban area and at rural locations that would be upwind and downwind of the plant during transport to DFW. An instrumented aircraft measured plume dispersion and the air surrounding the plume on selected days. A mathematical model was used to predict the change that would occur in airborne particulate matter concentrations in DFW if SO2 emissions were reduced to reflect the proposed limitations. The contribution of particles in the atmosphere to light extinction was estimated, and simulated photographs were produced to illustrate the visibility changes. The study concluded that the proposed emission reductions would, at most, subtly change perceived wintertime visibility.     

Natural background visibility and regional haze goals in the Southeastern United States

The goal of the regional haze mitigation program in the United States is to attain "natural conditions" in national parks and wilderness areas by 2064. Results of research investigations on background concentrations of sea salt and biogenic organic matter, of episodic Saharan and Asian dust, and of carbon from natural fires were reviewed to provide a basis for making site-specific estimates of what the concentrations of atmospheric fine particulate matter components might be under natural conditions in the Southeastern United States. Based on this review, rough estimates were made of potential contributions of these aerosol components to natural background visibility. Natural organic particles were the dominant influence on the rate of visibility improvement required to reach natural conditions at an inland, mountainous location, and organic particles and sea salt were the dominant influences on the rate at a coastal location. African dust also had a large episodic effect, but the current regulatory approach is not designed to address episodic background variations. Insufficient data exist to quantify the contributions of wildfires with any detail, although global air pollution modeling provides insight, and their emissions can be locally dominant. Conservative regional refinements to the default natural background estimates do not greatly alter the region-wide rates of reduction of ambient particulate matter concentrations that will be needed to accomplish the first phase of the regional haze program. However, refinements at specific Class I areas may have considerable influence on defining the nature (magnitude and spatial and temporal distribution) of local emission reduction efforts there.     

An Analysis of Visual Range in the Eastern United States Under Different Meteorological Regimes

ABSTRACT

The issue of fine particle (PM₂₅) exposures and their potential health effects is a focus of scientific research because of the recently promulgated National Ambient Air Quality Standard for PM_{2 5}. Before final implementation, the health and exposure basis for the standard will be reviewed by the U.S. Environmental Protection Agency within the next five years. As part of this process, it is necessary to understand total particle exposure issues and to determine the relative importance of the origin of PM_{2 5} exposure in various micro-environments. The results presented in this study examine emissions of fine particles from a previously uncharacterized indoor source: the residential vacuum cleaner. Eleven standard vacuum cleaners were tested for the emission rate of fine particles by their individual motors and for their efficiency in collecting laboratory-generated fine particles. An aerosol generator was used to introduce fine potassium chloride (KC1) particles into the vacuum cleaner inlet for the collection efficiency tests. Measurements of the motor emissions, which include carbon, and the KCl aerosol were made using a continuous HIAC/Royco 5130A light-scattering particle detector. All tests were conducted in a metal chamber specifically designed to completely contain the vacuum cleaner and operate it in a stationary position. For the tested vacuum cleaners, fine particle motor emissions ranged from 9.6 x 10⁴ to 3.34 x 10⁸ particles/min, which were estimated to be 0.028 to 176 mg/min for mass emissions, respectively. The vast majority of particles released were in the range of 0.3-0.5 mm in diameter. The lowest particle emission rate was obtained for a vacuum cleaner that had a high efficiency (HEPA) filter placed after the vacuum cleaner bag and the motor within a sealed exhaust system. This vacuum cleaner removed the KC1particles that escaped the vacuum cleaner bag and the particles emitted by the motor. Results obtained for the KC1 collection efficiency tests show >99% of the fine particles were captured by the two vacuum cleaners that used a HEPA filter. A series of tests conducted on two vacuum cleaners found that the motors also emitted ultra-fine particles above 0.01 mm in diameter at rates of greater than 10⁸ ultra-fine particles/CF of air. The model that had the best collection efficiency for fine particles also reduced the ultra-fine particle emissions by a factor of 1 x 10³.