Ecosystem Viable Yields

The World Summit on Sustainable Development (Johannesburg, 2002) encouraged the application of the ecosystem approach by 2010. However, at the same summit, the signatory States undertook to restore and exploit their stocks at maximum sustainable yield (MSY), a concept and practice without ecosystemic dimension, since MSY is computed species by species, on the basis of a monospecific model. Acknowledging this gap, we propose a definition of “ecosystem viable yields” (EVY) as yields compatible (a) with biological safety levels (over which biomasses can be maintained for all times) and (b) with an ecosystem dynamics. The difference from MSY is that this notion is not based on equilibrium but on viability theory, which offers advantages for robustness. For a generic class of multispecies models with harvesting, we provide explicit expressions for the EVY. We apply our approach to the anchovy–hake couple in the Peruvian upwelling ecosystem.     

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.     

Translocation trisomy 21 in CVS not found in embryoblast: Three different cell lines in CVS,amnion- and placental culture

Chorionic villus samples from a healthy pregnant female were obtained for first-trimester prenatal diagnosis. A translocation trisomy 21 was diagnosed. A consecutive amniocentesis revealed a normal male karyotype. At term a healthy boy was born. Cytogenetic analysis from cord blood showed a regular karyotype of 46,XY, whereas in term placenta a pathological karyotype of 47,XY,+mar was found.     

Evaluation of low wind modeling approaches for two tall-stack databases

The performance of the AERMOD air dispersion model under low wind speed conditions, especially for applications with only one level of meteorological data and no direct turbulence measurements or vertical temperature gradient observations, is the focus of this study. The analysis documented in this paper addresses evaluations for low wind conditions involving tall stack releases for which multiple years of concurrent emissions, meteorological data, and monitoring data are available. AERMOD was tested on two field-study databases involving several SO₂ monitors and hourly emissions data that had sub-hourly meteorological data (e.g., 10-min averages) available using several technical options: default mode, with various low wind speed beta options, and using the available sub-hourly meteorological data. These field study databases included (1) Mercer County, a North Dakota database featuring five SO₂ monitors within 10 km of the Dakota Gasification Company’s plant and the Antelope Valley Station power plant in an area of both flat and elevated terrain, and (2) a flat-terrain setting database with four SO₂ monitors within 6 km of the Gibson Generating Station in southwest Indiana. Both sites featured regionally representative 10-m meteorological databases, with no significant terrain obstacles between the meteorological site and the emission sources. The low wind beta options show improvement in model performance helping to reduce some of the overprediction biases currently present in AERMOD when run with regulatory default options. The overall findings with the low wind speed testing on these tall stack field-study databases indicate that AERMOD low wind speed options have a minor effect for flat terrain locations, but can have a significant effect for elevated terrain locations. The performance of AERMOD using low wind speed options leads to improved consistency of meteorological conditions associated with the highest observed and predicted concentration events. The available sub-hourly modeling results using the Sub-Hourly AERMOD Run Procedure (SHARP) are relatively unbiased and show that this alternative approach should be seriously considered to address situations dominated by low-wind meander conditions.

Implications: AERMOD was evaluated with two tall stack databases (in North Dakota and Indiana) in areas of both flat and elevated terrain. AERMOD cases included the regulatory default mode, low wind speed beta options, and use of the Sub-Hourly AERMOD Run Procedure (SHARP). The low wind beta options show improvement in model performance (especially in higher terrain areas), helping to reduce some of the overprediction biases currently present in regulatory default AERMOD. The SHARP results are relatively unbiased and show that this approach should be seriously considered to address situations dominated by low-wind meander conditions.     

Emissions Variability Processor (EMVAP): Design,evaluation, and application

Emissions of pollutants such as SO₂ and NOx from external combustion sources can vary widely depending on fuel sulfur content, load, and transient conditions such as startup, shutdown, and maintenance/malfunction. While monitoring will automatically reflect variability from both emissions and meteorological influences, dispersion modeling has been typically conducted with a single constant peak emission rate. To respond to the need to account for emissions variability in addressing probabilistic 1-hr ambient air quality standards for SO₂ and NO₂, we have developed a statistical technique, the Emissions Variability Processor (EMVAP), which can account for emissions variability in dispersion modeling through Monte Carlo sampling from a specified frequency distribution of emission rates. Based upon initial AERMOD modeling of from 1 to 5 years of actual meteorological conditions, EMVAP is used as a postprocessor to AERMOD to simulate hundreds or even thousands of years of concentration predictions. This procedure uses emissions varied hourly with a Monte Carlo sampling process that is based upon the user-specified emissions distribution, from which a probabilistic estimate can be obtained of the controlling concentration. EMVAP can also accommodate an advanced Tier 2 NO₂ modeling technique that uses a varying ambient ratio method approach to determine the fraction of total oxides of nitrogen that are in the form of nitrogen dioxide. For the case of the 1-hr National Ambient Air Quality Standards (NAAQS, established for SO₂ and NO₂), a “critical value” can be defined as the highest hourly emission rate that would be simulated to satisfy the standard using air dispersion models assuming constant emissions throughout the simulation. The critical value can be used as the starting point for a procedure like EMVAP that evaluates the impact of emissions variability and uses this information to determine an appropriate value to use for a longer term (e.g., 30-day) average emission rate that would still provide protection for the NAAQS under consideration. This paper reports on the design of EMVAP and its evaluation on several field databases that demonstrate that EMVAP produces a suitably modest overestimation of design concentrations. We also provide an example of an EMVAP application that involves a case in which a new emission limitation needs to be considered for a hypothetical emission unit that has infrequent higher-than-normal SO₂ emissions.

ImplicationsEmissions of pollutants from combustion sources can vary widely depending on fuel sulfur content, load, and transient conditions such as startup and shutdown. While monitoring will automatically reflect this variability on measured concentrations, dispersion modeling is typically conducted with a single peak emission rate assumed to occur continuously. To realistically account for emissions variability in addressing probabilistic 1-hr ambient air quality standards for SO₂ and NO₂, the authors have developed a statistical technique, the Emissions Variability Processor (EMVAP), which can account for emissions variability in dispersion modeling through Monte Carlo sampling from a specified frequency distribution of emission rates.     

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.