Supply curves for using powder river basin coal to reduce sulfur emissions

Supply curves were prepared for coal-fired power plants in the contiguous United States switching to Wyoming's Powder River Basin (PRB) low-sulfur coal. Up to 625 plants, representing approximately 44% of the nameplate capacity of all coal-fired plants, could switch. If all switched, more than dollars 8.8 billion additional capital would be required and the cost of electricity would increase by up to dollars 5.9 billion per year, depending on levels of plant derating. Coal switching would result in sulfur dioxide (SO2) emissions reduction of 4.5 million t/yr. Increase in cost of electricity would be in the range of 0.31-0.73 cents per kilowatt-hour. Average cost of S emissions reduction could be as high as dollars 1298 per t of SO2. Up to 367 plants, or 59% of selected plants with 32% of 44% nameplate capacity, could have marginal cost in excess of dollars 1000 per t of SO2. Up to 73 plants would appear to benefit from both a lowering of the annual cost and a lowering of SO2 emissions by switching to the PRB coal.     

Complications with using ratios for environmental data: comparing enantiomeric ratios (ERs) and enantiomer fractions (EFs)

Complications arise when ratios are used to present environmental data because ratios are an unbounded, multiplicative scale that can lead to asymmetrical (skewed) data distributions. Enantiomeric ratios (ERs), historically used in discussions of chiral signatures, often are published as mean ER+/-single-value standard deviation. Application of statistical summaries, such as the widely used sample mean and standard deviation, to skewed ratio data is misleading and often inappropriate. Comparison of statistically summarized ER and enantiomer fraction (EF) data (which are based on a bounded, additive scale) for a range of hypothetical values reveals substantial discrepancies when conversion between ER and EF formats is used. These discrepancies are largest when the ratio data are greater than one and have large variability, because the data are more skewed. In many cases, the use of fractions instead of ratios can help to minimize misrepresentation of environmental data, including chiral data. The use of nonparametric statistical summaries, e.g., median and percentiles, provides a more robust indicator of the typical value and spread for both ER and EF data.     

A new approach to quantifying and comparing vulnerability to drought

In this study we develop an “inference modeling” approach to compare and analyze how different disciplines (economics, political science, and behavioral science/environmental psychology) estimate vulnerability to drought. It is thought that a better understanding of these differences can lead to a synthesis of insights from the different disciplines and eventually to more comprehensive assessments of vulnerability. The new methodology consists of (1) developing inference models whose variables and assertions incorporate qualitative knowledge about vulnerability, (2) converting qualitative model variables into quantitative indicators by using fuzzy set theory, (3) collecting data on the values of the indicators from case study regions, (4) inputting the regional data to the models and computing quantitative values for susceptibility. The methodology was applied to three case study regions (in India, Portugal and Russia) having a range of socio-economic and water stress conditions. In some cases the estimates of susceptibility were surprisingly similar, in others not, depending on the factors included in the disciplinary models and their relative weights. A new approach was also taken to testing vulnerability parameters by comparing estimated water stress against a data set of drought occurrences based on media analysis. The new methodologies developed in this paper provide a consistent basis for comparing differences between disciplinary perspectives, and for identifying the importance of the differences.

Prompt detection of alpha particles from 210Po: another clue to the origin of rock varnish?

Alpha particles have been measured coming from the surfaces of rocks covered with dark red-brown rock varnish, as well as rocks that appear to have little, if any, varnish. A pronounced peak at 5.3 MeV indicates the presence of 210Po, a short-lived natural-radioactive element. Surface activities for 33 samples range from 0.008 Bq/cm2 to 0.065 Bq/cm2. It is estimated that this nuclide is concentrated 10(11) times in these paper-thin coatings above its concentration in ground-level air. Gamma rays from the decay of 137Cs, a product of testing nuclear weapons some 50 years ago, were also detected. Analysis of samples of varnish stripped from the rock revealed traces of 239,240Pu and 238Pu. The presence of all of these isotopes strongly supports the theory that varnish films derive their building blocks from the atmosphere and, with time, all rocks in arid environments will become coated.     

Preliminary evaluation of the Community Multiscale Air Quality model for 2002 over the Southeastern United States

The Visibility Improvement State and Tribal Association of the Southeast (VISTAS) is one of five Regional Planning Organizations that is charged with the management of haze, visibility, and other regional air quality issues in the United States. The VISTAS Phase I work effort modeled three episodes (January 2002, July 1999, and July 2001) to identify the optimal model configuration(s) to be used for the 2002 annual modeling in Phase II. Using model configurations recommended in the Phase I analysis, 2002 annual meteorological (Mesoscale Meterological Model [MM5]), emissions (Sparse Matrix Operator Kernal Emissions [SMOKE]), and air quality (Community Multiscale Air Quality [CMAQ]) simulations were performed on a 36-km grid covering the continental United States and a 12-km grid covering the Eastern United States. Model estimates were then compared against observations. This paper presents the results of the preliminary CMAQ model performance evaluation for the initial 2002 annual base case simulation. Model performance is presented for the Eastern United States using speciated fine particle concentration and wet deposition measurements from several monitoring networks. Initial results indicate fairly good performance for sulfate with fractional bias values generally within +/-20%. Nitrate is overestimated in the winter by approximately +50% and underestimated in the summer by more than -100%. Organic carbon exhibits a large summer underestimation bias of approximately -100% with much improved performance seen in the winter with a bias near zero. Performance for elemental carbon is reasonable with fractional bias values within +/- 40%. Other fine particulate (soil) and coarse particular matter exhibit large (80-150%) overestimation in the winter but improved performance in the summer. The preliminary 2002 CMAQ runs identified several areas of enhancements to improve model performance, including revised temporal allocation factors for ammonia emissions to improve nitrate performance and addressing missing processes in the secondary organic aerosol module to improve OC performance.     

Particle size measurements of automotive diesel emissions

The automative diesel engine has long been acknowledged as being “dirtier” than the spark ignition engine and its particulate emissions may be carcinogenic. Possible solutions to the diesel emission problem are combustion modification or aftertreatment devices. Selection of candidate aftertreatment devices requires knowledge of the physical and chemical properties of the particles, including particle morphology, size distribution, mass concentration and emission rates in the exhaust gas stream. The study reported here represents the first of a series of experiments designed to characterize the exhaust emissions and test various aftertreatment devices. This paper deals only with the particulate characterization phase of the program. Results of size distribution, particle concentration and mass emission rate measurements for a 5.71 displacement Oldsmobile diesel engine are given for a variety of engine operating conditions.     

Spatial patterns of forest characteristics in the western United States derived from inventories.

In the western United States, forest ecosystems are subject to a variety of forcing mechanisms that drive dynamics, including climate change, land-use/land-cover change, atmospheric pollution, and disturbance. To understand the impacts of these stressors, it is crucial to develop assessments of forest properties to establish baselines, determine the extent of changes, and provide information to ecosystem modeling activities. Here we report on spatial patterns of characteristics of forest ecosystems in the western United States, including area, stand age, forest type, and carbon stocks, and comparisons of these patterns with those from satellite imagery and simulation models. The USDA Forest Service collected ground-based measurements of tree and plot information in recent decades as part of nationwide forest inventories. Using these measurements together with a methodology for estimating carbon stocks for each tree measured, we mapped county-level patterns across the western United States. Because forest ecosystem properties are often significantly different between hardwood and softwood species, we describe patterns of each. The stand age distribution peaked at 60-100 years across the region, with hardwoods typically younger than softwoods. Forest carbon density was highest along the coast region of northern California, Oregon, and Washington and lowest in the arid regions of the Southwest and along the edge of the Great Plains. These results quantify the spatial variability of forest characteristics important for understanding large-scale ecosystem processes and their controlling mechanisms. To illustrate other uses of the inventory-derived forest characteristics, we compared them against examples of independently derived estimates. Forest cover compared well with satellite-derived values when only productive stands were included in the inventory estimates. Forest types derived from satellite observations were similar to our inventory results, though the inventory database suggested more heterogeneity. Carbon stocks from the Century model were in good agreement with inventory results except in the Pacific Northwest and part of the Sierra Nevada, where it appears that harvesting and fire in the 20th century (processes not included in the model runs) reduced measured stand ages and carbon stocks compared to simulations.     

Kinship,reproductive strategies and social dynamics of yellow-bellied marmots

Summary Social behavior of yellow-bellied marmots was observed for three years in colonies where kinship was known and for one year in a high elevation colony where harems were contiguous. Social dynamics of yellow-bellied marmots is dependent on kinship, group composition, and age-sex classes. This pattern is a consequence of the reproductive strategies of males and females. Females behave cohesively toward sisters or daughters, but not with sons and agonistically toward other females. Males generally behave amicably toward females and agonistically toward males, including their sons. Thus, reproductive strategies limit nepotism. This behavior is consistent with a population process in which sons typically disperse as yearlings. At least some of the variation in the expected patterns of social behaviors is attributable to individual differences. Because male and female reproductive strategies differ, a marmot population consists of two social subsystems. The female unit is the closely-related kin group which may also be a burrow group. The male unit is a harem which usually consists of two or more competing female kin groups.     

Computational fluid dynamics analysis of the effects of reactor configuration on disinfection efficiency.

The efficacy of disinfection processes in water purification systems is governed by several key factors, including reactor hydraulics, disinfectant chemistry, and microbial inactivation kinetics. The objective of this work was to develop a computational fluid dynamics (CFD) model to predict velocity fields, mass transport, chlorine decay, and microbial inactivation in a continuous flow reactor. The CFD model was also used to evaluate disinfection efficiency in alternative reactor designs. The CFD reactor analysis demonstrates that disinfection efficiency is affected by both kinetics and mixing state (i.e., degree of micromixing or segregation). Residence time distributions (RTDs) derived from tracer analysis do not describe intrinsic mixing conditions. The CFD-based disinfection models account for reactor mixing patterns by resolution of the reactor velocity field and thus provide a better prediction of microbial inactivation than models that use an RTD.