Critique of “Precipitation in Light Extinction Reconstruction” by P.A. Ryan

Abstract

The goal of the Regional Haze Rule (RHR) is to return visibility in class I areas (CIAs) to natural levels, excluding weather-related events, by 2064. Whereas visibility, the seeing of scenic vistas, is a near instantaneous and sight-path-dependent phenomenon, reasonable progress toward the RHR goal is assessed by tracking the incremental changes in 5-yr average visibility. Visibility is assessed using a haze metric estimated from 24-hr average aerosol measurements that are made at one location representative of the CIA. It is assumed that, over the 5-yr average, the aerosol loadings and relative humidity along all of the site paths are the same and can be estimated from the 24-hr measurements. It is further assumed that any time a site path may be obscured by weather (e.g., clouds and precipitation), there are other site paths within the CIA that are not. Therefore, when calculating the haze metric, sampling days are not filtered for weather conditions. This assumption was tested by examining precipitation data from multiple monitors for four CIAs. It is shown that, in general, precipitation did not concurrently occur at all monitors for a CIA, and precipitation typically occurred 3-8 hr or less in a day. In a recent paper in this journal, Ryan asserts that the haze metric should include contributions from precipitation and conducted a quantitative assessment incorrectly based on the assumption that the Optec NGN-2 nephelometer measurements include the effects of precipitation. However, these instruments are programmed to shut down during rain events, and any data logged are in error. He further assumes that precipitation occurs as often on the haziest days as the clearest days and that precipitation light scattering (bprecip) is independent of geographic location and applied an average bprecip derived for Great Smoky Mountains to diverse locations including the Grand Canyon. Both of these assumptions are shown to be in error.     

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.     

Group navigation and the "many-wrongs principle" in models of animal movement

Traditional studies of animal navigation over both long and short distances have usually considered the orientation ability of the individual only, without reference to the implications of group membership. However, recent work has suggested that being in a group can significantly improve the ability of an individual to align toward and reach a target direction or point, even when all group members have limited navigational ability and there are no leaders. This effect is known as the "many-wrongs principle" since the large number of individual navigational errors across the group are suppressed by interactions and group cohesion. In this paper, we simulate the many-wrongs principle using a simple individual-based model of movement based on a biased random walk that includes group interactions. We study the ability of the group as a whole to reach a target given different levels of individual navigation error, group size, interaction radius, and environmental turbulence. In scenarios with low levels of environmental turbulence, simulation results demonstrate a navigational benefit from group membership, particularly for small group sizes. In contrast, when movement takes place in a highly turbulent environment, simulation results suggest that the best strategy is to navigate as individuals rather than as a group.     

Preliminary on-road measurement of the effect of oxygenated fuel on CO emissions near Las Vegas, Nevada

A preliminary measurement of an oxygenated fuel effect for in-use vehicles travelling at freeway speed was conducted near Las Vegas, NV, in January 1991 and May 1992. The experimental design was based on two principal factors: (1) the large volume of traffic that visits Las Vegas from Southern California on three-day holiday weekends and (2) the fact that, at the time of the study, the Las Vegas area used oxygenated fuels in the winter and Southern California did not. Measurements were conducted at carefully selected sites 20 km southwest of Las Vegas near Sloan, NV, and were accomplished with the Fuel Efficiency Automoblie Test (FEAT) remote sensor developed at the University of Denver. The January 1991 measurements were made during the Las Vegas oxyfuel season, while the May 1992 control measurements were made outside the oxyfuel season. Over 24,500 individual CO concentrations were measured; registration data from over 5,500 of these vehicles were obtained from the license plate numbers. After corrections for differences in velocity and mean age, the Las Vegas outbound (oxyfuel) CO emissions on Monday morning of the January holiday weekend showed a difference of -18% +/- 11% compared to the inbound (non-oxyfuel) CO emissions on Friday evening preceding the holiday weekend.     

Revised algorithm for estimating light extinction from IMPROVE particle speciation data

The Interagency Monitoring of Protected Visual Environments (IMPROVE) particle monitoring network consists of approximately 160 sites at which fine particulate matter (PM2.5) mass and major species concentrations and course particulate matter (PM10) mass concentrations are determined by analysis of 24-hr duration sampling conducted on a 1-day-in-3 schedule A simple algorithm to estimate light extinction from the measured species concentrations was incorporated in the 1999 Regional Haze Rule as the basis for the haze metric used to track haze trends. A revised algorithm was developed that is more consistent with the recent atmospheric aerosol literature and reduces bias for high and low light extinction extremes. The revised algorithm differs from the original algorithm in having a term for estimating sea salt light scattering from Cl(-) ion data, using 1.8 instead of 1.4 for the mean ratio of organic mass to measured organic carbon, using site-specific Rayleigh scattering based on site elevation and mean temperature, employing a split component extinction efficiency associated with large and small size mode sulfate, nitrate and organic mass species, and adding a term for nitrogen dioxide (NO2) absorption for sites with NO2 concentration information. Light scattering estimates using the original and the revised algorithms are compared with nephelometer measurements at 21 IMPROVE monitoring sites. The revised algorithm reduces the underprediction of high haze periods and the overprediction of low haze periods compared with the performance of the original algorithm. This is most apparent at the hazier monitoring sites in the eastern United States. For each site, the PM10 composition for days selected as the best 20% and the worst 20% haze condition days are nearly identical regardless of whether the basis of selection was light scattering from the original or revised algorithms, or from nephelometer-measured light scattering.     

Watershed-Based Survey Designs

Watershed-based sampling design and assessment tools help serve the multiple goals for water quality monitoring required under the Clean Water Act, including assessment of regional conditions to meet Section 305(b), identification of impaired water bodies or watersheds to meet Section 303(d), and development of empirical relationships between causes or sources of impairment and biological responses. Creation of GIS databases for hydrography, hydrologically corrected digital elevation models, and hydrologic derivatives such as watershed boundaries and upstream–downstream topology of subcatchments would provide a consistent seamless nationwide framework for these designs. The elements of a watershed-based sample framework can be represented either as a continuous infinite set defined by points along a linear stream network, or as a discrete set of watershed polygons. Watershed-based designs can be developed with existing probabilistic survey methods, including the use of unequal probability weighting, stratification, and two-stage frames for sampling. Case studies for monitoring of Atlantic Coastal Plain streams, West Virginia wadeable streams, and coastal Oregon streams illustrate three different approaches for selecting sites for watershed-based survey designs.     

Application of the Tracer-Aerosol Gradient Interpretive Technique to Sulfur Attribution for the Big Bend Regional Aerosol and Visibility Observational Study

Abstract

A simple data analysis method called the Tracer-Aerosol Gradient Interpretive Technique (TAGIT) is used to attribute particulate S and SO₂ at Big Bend National Park in Texas and nearby areas to local and regional sources. Particulate S at Big Bend is of concern because of its effects on atmospheric visibility. The analysis used particulate S, SO₂ , and perfluorocarbon tracer data from six 6-hr sampling sites in and near Big Bend National Park. The data were collected in support of the Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study; the field portion was conducted from July through October 1999. Perfluorocarbon tracer was released continuously from a tower at Eagle Pass, TX, approximately 25 km northeast of two large coal-fired power plants (Carbon I and II) in Coahuila, Mexico, and approximately 270 km east-southeast of Big Bend National Park.

The perfluorocarbon tracer did not properly represent the location of the emissions from the Carbon power plants for individual 6-hr sampling periods and attributed only 3% of the particulate S and 27% of the SO₂ at the 6-hr sites in and near Big Bend to sources represented by the tracer. An alternative approach using SO₂ to tag “local” sources such as the Carbon plants attributed 10% of the particulate S and 75% of the SO2 at the 6-hr sites to local sources. Based on these two approaches, most of the regional (65–86%) and a small fraction (19–31%) of the local SO₂ was converted to particulate S. The analysis implies that substantial reductions in particulate S at Big Bend National Park cannot be achieved by only reducing emissions from the Carbon power plants; reduction of emissions from many sources over a regional area would be necessary.     

Biological Integrity in Mid-Atlantic Coastal Plains Headwater Streams

The objective of this study was to assess the applicability of using landscape variables in conjunction with water quality and benthic data to efficiently estimate stream condition of select headwater streams in the Mid-Atlantic Coastal Plains. Eighty-two streams with riffle sites were selected from eight-two independent watersheds across the region for sampling and analyses. Clustering of the watersheds by landscape resulted in three distinct groups (forest, crop, and urban) which coincided with watersheds dominant land cover or use. We used non-parametric analyses to test differences in benthos and water chemistry between groups, and used regression analyses to evaluate responses of benthic communities to water chemistry within each of the landscape groups. We found that typical water chemistry measures associated with urban runoff such as specific conductance and dissolved chloride were significantly higher in the urban group. In the crop group, we found variables commonly associated with farming such as nutrients and pesticides significantly greater than in the other two groups. Regression analyses demonstrated that the numbers of tolerant and facultative macroinvertebrates increased significantly in forested watersheds with small shifts in pollutants, while in human use dominated watersheds the intolerant macroinvertebrates were more sensitive to shifts in chemicals present at lower concentrations. The results from this study suggest that landscape based clustering can be used to link upstream landscape characteristics, water chemistry and biotic integrity in order to assess stream condition and likely cause of degradation without the use of reference sites. Notice: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.     

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.     

Application of the tracer-aerosol gradient interpretive technique to sulfur attribution for the big bend regional aerosol and visibility observational study

A simple data analysis method called the Tracer-Aerosol Gradient Interpretive Technique (TAGIT) is used to attribute particulate S and SO2 at Big Bend National Park in Texas and nearby areas to local and regional sources. Particulate S at Big Bend is of concern because of its effects on atmospheric visibility. The analysis used particulate S, SO2, and perfluorocarbon tracer data from six 6-hr sampling sites in and near Big Bend National Park. The data were collected in support of the Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study; the field portion was conducted from July through October 1999. Perfluorocarbon tracer was released continuously from a tower at Eagle Pass, TX, approximately 25 km northeast of two large coal-fired power plants (Carbon I and II) in Coahuila, Mexico, and approximately 270 km east-southeast of Big Bend National Park. The perfluorocarbon tracer did not properly represent the location of the emissions from the Carbon power plants for individual 6-hr sampling periods and attributed only 3% of the particulate S and 27% of the SO2 at the 6-hr sites in and near Big Bend to sources represented by the tracer. An alternative approach using SO2 to tag "local" sources such as the Carbon plants attributed 10% of the particulate S and 75% of the SO2 at the 6-hr sites to local sources. Based on these two approaches, most of the regional (65-86%) and a small fraction (19-31%) of the local SO2 was converted to particulate S. The analysis implies that substantial reductions in particulate S at Big Bend National Park cannot be achieved by only reducing emissions from the Carbon power plants; reduction of emissions from many sources over a regional area would be necessary.