Reconciliation and interpretation of the Big Bend National Park light extinction source apportionment: results from the Big Bend Regional Aerosol and Visibility Observational Study--part II

The recently completed Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study focused on particulate sulfate source attribution for a 4-month period from July through October 1999. A companion paper in this issue by Schichtel et al. describes the methods evaluation and results reconciliation of the BRAVO Study sulfate attribution approaches. This paper summarizes the BRAVO Study extinction budget assessment and interprets the attribution results in the context of annual and multiyear causes of haze by drawing on long-term aerosol monitoring data and regional transport climatology, as well as results from other investigations. Particulate sulfates, organic carbon, and coarse mass are responsible for most of the haze at Big Bend National Park, whereas fine particles composed of light-absorbing carbon, fine soils, and nitrates are relatively minor contributors. Spring and late summer through fall are the two periods of high-haze levels at Big Bend. Particulate sulfate and carbonaceous compounds contribute in a similar magnitude to the spring haze period, whereas sulfates are the primary cause of haze during the late summer and fall period. Atmospheric transport patterns to Big Bend vary throughout the year, resulting in a seasonal cycle of different upwind source regions contributing to its haze levels. Important sources and source regions for haze at Big Bend include biomass smoke from Mexico and Central America in the spring and African dust during the summer. Sources of sulfur dioxide (SO2) emissions in Mexico, Texas, and in the Eastern United States all contribute to Big Bend haze in varying amounts over different times of the year, with a higher contribution from Mexican sources in the spring and early summer, and a higher contribution from U.S. sources during late summer and fall. Some multiple-day haze episodes result from the influence of several source regions, whereas others are primarily because of emissions from a single source region.     

Marine debris contamination along undeveloped tropical beaches from northeast Brazil

We hypothesize that floating debris leaving polluted coastal bays accumulate on nearby pristine beaches. We examined composition, quantities and distribution of marine debris along approximately 150 km of relatively undeveloped, tropical beaches in Costa do Dendê (Bahia, Brazil). The study site is located south of Salvador City, the largest urban settlement from NE Brazil. Strong spatial variations were observed. Plastics accounted for 76% of the sampled items, followed by styrofoam (14%). Small plastic fragments resultant from the breakdown of larger items are ubiquitous all over the area. Because the dominant littoral drift in Bahia is southward, average beach debris densities (9.1 items/m) along Costa do Dendê were threefold higher than densities previously observed north of Salvador City. River-dominated and stable beaches had higher debris quantities than unstable, erosional beaches. Areas immediately south of the major regional embayments (Camamu and Todos os Santos) were the preferential accumulation sites, indicating that rivers draining populous areas are the major source of debris to the study site. Our results provide baseline information for future assessments. Management actions should focus on input prevention at the hydrographic basin level rather than on cleaning services on beaches.     

Analysis and Simulation of Wintertime Light Scattering by the Urban Aerosol in Dallas-Fort Worth

ABSTRACT

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 nephelom-eter; agreement was within 20% in every case.     

Study of the Relationship of Distant SO2 Emissions to Dallas-Fort Worth Winter Haze

ABSTRACT

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.     

Modeling of Potential Power Plant Plume Impacts on Dallas-Fort Worth Visibility

ABSTRACT

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.     

Use of Project MOHAVE Perfluorocarbon Tracer Data to Evaluate Source and Receptor Models

ABSTRACT

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.     

Spatial memory, habitat auto-facilitation and the emergence of fractal home range patterns

Animals interact with their habitat in a manner which involves both negative and positive feedback mechanisms. We apply a specific modeling approach, “multi-scaled random walk”, for the scenario where a spatially explicit positive feedback process emerges from a combination of a spatial memory-dependent tendency to return to familiar patches and a consequently objective or subjective improvement of the quality of these patches (habitat auto-facilitation). In addition to the potential for local resource improvement from physically altering a patch, primarily known from the ecology of grazing ungulates, auto-facilitation from site fidelity may also embed more subtle subjective, individual-specific advantages from patch familiarity. Under the condition of resource superabundance, fitness gain from intra-home range patch fidelity creates a self-reinforcing use of the preferred patches on expense of a broader foraging in a priori equally favorable patches. Through this process, our simulations show that a spatially fractal dispersion of accumulated locations of the individual will emerge under the given model assumptions. Based on a conjecture that intra-home range patch fidelity depends on spatial memory we apply the multi-scaled random walk model to construct a spatially explicit habitat suitability parameter H_ij, which quantifies the dispersion of the generally most constraining resource from the individual's perspective. An intra-home range set of observed H-scores, H_obs, can then be estimated from a simple 2-scale calculation that is derived from the local dispersion of fixes. We show how the spatially explicit habitat utilization index H_obs not necessarily correlates positively with the local density fluctuations of fixes. The H-index solves some well-known problems from using the pattern of local densities of telemetry fixes - the classic utilization distribution - as a proxy variable for relative intra-home range habitat quality and resource selection. A pilot study on a set of telemetry fixes collected from a herd of free-ranging domestic sheep with overlapping summer home ranges illustrates how the H-index may be estimated and interpreted as a first-level approach towards a more extensive analysis of intra-home range habitat resource availability and patch preferences. Spatial memory in combination with site fidelity requires a modeling framework that explicitly describes the property of positive feedback mechanism under auto-facilitation in a spatio-temporally explicit manner.