OPTIMIZATION OF INTERMITTENT PUMPING SCHEDULES FOR AQUIFER REMEDIATION USING A GENETIC ALGORITHM1

ABSTRACT: Using a genetic algorithm (GA), optimal intermittent pumping schedules were established to simulate pump‐and‐treat remediation of a contaminated aquifer with known hydraulic limitations and a water miscible contaminant, located within the Duke Forest in Durham, North Carolina. The objectives of the optimization model were to minimize total costs, minimize health risks, and maximize the amount of contaminant removed from the aquifer. Stochastic ground water and contaminant transport models were required to provide estimates of contaminant concentrations at pumping wells. Optimization model simulations defined a tradeoff curve between the pumping cost and the amount of contaminant extracted from the aquifer. For this specific aquifer/miscible contaminant combination, the model simulations indicated that pump‐and‐treat remediation using intermittent pumping schedules for each pumping well produced significant reductions in predicted contaminant concentrations and associated health risks at a reasonable cost, after a remediation time of two years.     

Rodent predation on hibernating peacock and small tortoiseshell butterflies

Insects that hibernate as adults have a life span of almost a whole year. Hence, they must have extraordinary adaptations for adult survival. In this paper, we study winter survival in two butterflies that hibernate as adults and have multimodal anti-predator defences—the peacock, Inachis io, which has intimidating eyespots that are effective against bird predation, and the small tortoiseshell, Aglais urticae, which does not have an effective secondary defence against birds. We assessed predation on wild butterflies hibernating in the attic of an unheated house, as well as survival of individually marked butterflies placed by hand on different sites in the attic. Our objectives were to assess (1) the number of butterflies that were killed during hibernation, (2) whether survival differed between butterfly species, and (3) how predation was related to hibernation site and the identity of the predator. There was a strong pulse of predation during the first 2 weeks of hibernation: 58% of A. urticae and 53% of I. io were killed during this period. Thereafter, predation decreased and butterfly survival equalled 98% during the final 16 weeks of hibernation. There was no difference in survival between the two butterfly species, but predation was site-specific and more pronounced under light conditions in locations accessible to a climbing rodent, such as the common yellow-necked mouse, Apodemus flavicollis. We contend that small rodents are likely important predators on overwintering butterflies, both because rodents are active throughout winter when butterflies are torpid and because they occur at similar sites.     

Development of Criteria for Siting Air Monitoring Stations

A critical problem arises if one attempts to compare data from air monitoring stations in different cities, because there are so many differences in monitoring site locations. Some air monitoring stations are on the 6 th and 8 th floors of tall buildings in downtown areas; some are at ground level beside streets with heavy traffic; some are in residential areas with little traffic or industry; and some are in suburban or nonurban areas. Unfortunately, there is ample evidence that the location of a monitoring station relative to nearby sources (such as highways) affects the values observed at the station, particularly for carbon monoxide and other vehicular pollutants. Thus, a standardized system of site selection, such as the one proposed here, appears essential to improve the comparability and meaningfulness of data obtained from different air monitoring stations throughout the Nation.     

A Physical Explanation of the Lognormality of Pollutant Concentrations

Investigators In different environmental fields have reported that the concentrations of various measured substances have frequency distributions that are lognormal, or nearly so. That is, when the logarithms of the observed concentrations are plotted as a frequency distribution, the resulting distribution is approximately normal, or Gaussian, over much of the observed range. Examples include radionuclides in soil, pollutants in ambient air, Indoor air quality, trace metals In streams, metals in biological tissue, calcium In human remains. The ubiquity of the lognormal distribution in environmental processes is surprising and has not been adequately explained, since common processes in nature (for example, computation of the mean and the analysis of error) usually give rise to distributions that are normal rather than lognormal. This paper takes the first step toward explaining why lognormal distributions can arise naturally from certain physical processes that are analogous to those found in the environment. In this paper, these processes are treated mathematically, and the results are illustrated in a laboratory beaker experiment that Is simulated on the computer.     

A Combined Ca(OH)2/NH3 Flue Gas Desulfurization Process for High Sulfur Coal: Results of a Pilot Plant Study

The removal of SO₂ with atomization of a slaked lime slurry and supplemental injection of gaseous NH₃ were tested in a conventional spray dryer/baghouse system for SO₂ concentrations of 2000 ppm and 3000 ppm and a 30° F approach to saturation. Results at 3000 ppm of SO₂ showed an average SO₂ removal efficiency of 90.3 percent at a combined stoichiometric ratio of 0.95-1.10 and an average overall sorbent utilization of 91.6 percent. The overall molal ratio of NH₃/SO₂ reaction was found to be 2:1 under the test conditions Particle size analyses, and EP toxicity tests were conducted on the products of the reactions.     

Carbon Monoxide Exposures Inside an Automobile Traveling on an Urban Arterial Highway

Carbon monoxide (CO) exposures were measured inside a motor vehicle during 88 standardized drives on a major urban arterial highway, El Camino Real (traffic volume of 30,500-45,000 vehicles per day), over a 13-1/2 month period. On each trip (lasting between 31 and 61 minutes), the test vehicle drove the same 5.9-mile segment of roadway in both directions, for a total of 11.8 miles, passing through 20 intersections with traffic lights (10 in each direction) in three California cities (Menlo Park, Palo Alto, and Los Altos). Earlier tests showed that the test vehicle was free of CO intrusion. For the 88 trips, the mean CO concentration was 9.8 ppm, with a standard deviation of 5.8 ppm. Of nine covariates that were examined to explain the variability in the mean CO exposures observed on the 88 trips (ambient CO at two fixed stations, atmospheric stability, seasonal trend function, time of day, average surrounding vehicle count, trip duration, proportion of time stopped at lights, and instrument type), a fairly strong seasonal trend was found. A model consisting of only a single measure of traffic volume and a seasonal trend component had substantial predictive power (R² = 0.68); by contrast, the ambient CO levels, although partially correlated with average exposures, contributed comparatively little predictive power to the model. The CO exposures experienced while drivers waited at the red lights at an intersection ranged from 6.8 to 14.9 ppm and differed considerably from intersection to intersection. A model also was developed to relate the short-term variability of exposures to averaging time for trip times ranging from 1 to 20 minutes using a variogram approach to deal with the serial autocorrelation. This study shows: (1) the mass balance equation can relate exterior CO concentrations as a function of time to interior CO concentrations; (2) CO exposures on urban arterial highways vary seasonally; (3) momentary CO exposures experienced behind red lights vary with the intersection; and (4) an averaging time model can simulate exposures during short trips (20 minutes or less) on urban arterial highways.     

An Environmental Decision-Making Tool for Evaluating Ground-Level Ozone-Related Health Effects

Abstract

A computer model called the Ozone Risk Assessment Model (ORAM) was developed to evaluate the health effects caused by ground-level ozone (O₃) exposure. ORAM was coupled with the U.S. Environmental Protection Agency’s (EPA) Third-Generation Community Multiscale Air Quality model (Models-3/CMAQ), the state-of-the-art air quality model that predicts O₃ concentration and allows the examination of various scenarios in which emission rates of O₃ precursors (basically, oxides of nitrogen [NO_x] and volatile organic compounds) are varied. The principal analyses in ORAM are exposure model performance evaluation, health-effects calculations (expected number of respiratory hospital admissions), economic valuation, and sensitivity and uncertainty analysis through a Monte Carlo simulation. As a demonstration of the system, ORAM was applied to the eastern Tennessee region, and the entire O₃ season was simulated for a base case (typical emissions) and three different emission scenarios. The results indicated that a synergism occurs when reductions in NO_x emissions from mobile and point sources were applied simultaneously. A 12.9% reduction in asthma hospital admissions is expected when both mobile and point source NO_x emissions are reduced (50 and 70%, respectively) versus a 5.8% reduction caused by mobile source and a 3.5% reduction caused by point sources when these emission sources are reduced individually.     

Farm, land, and soil nitrogen budgets for agriculture in Europe calculated with CAPRI

We calculated farm, land, and soil N-budgets for countries in Europe and the EU27 as a whole using the agro-economic model CAPRI. For EU27, N-surplus is 55 kg N ha⁻¹ yr⁻¹ in a soil budget and 65 kg N₂O–N ha⁻¹ yr⁻¹ and 67 kg N ha⁻¹ yr⁻¹ in land and farm budgets, respectively. NUE is 31% for the farm budget, 60% for the land budget and 63% for the soil budget. NS values are mainly related to the excretion (farm budget) and application (soil and land budget) of manure per hectare of total agricultural land. On the other hand, NUE is best explained by the specialization of the agricultural system toward animal production (farm NUE) or the share of imported feedstuff (soil NUE). Total N input, intensive farming, and the specialization to animal production are found to be the main drivers for a high NS and low NUE.     

Does Including Soil Moisture Observations Improve Operational Streamflow Forecasts in Snow‐Dominated Watersheds?

Changing climate and growing water demand are increasing the need for robust streamflow forecasts. Historically, operational streamflow forecasts made by the Natural Resources Conservation Service have relied on precipitation and snow water equivalent observations from Snow Telemetry (SNOTEL) sites. We investigate whether also including SNOTEL soil moisture observations improve April‐July streamflow volume forecast accuracy at 0, 1, 2, and 3‐month lead times at 12 watersheds in Utah and California. We found statistically significant improvement in 0 and 3‐month lead time accuracy in 8 of 12 watersheds and 10 of 12 watersheds for 1 and 2‐month lead times. Surprisingly, these improvements were insensitive to soil moisture metrics derived from soil physical properties. Forecasts were made with volumetric water content (VWC) averaged from October 1 to the forecast date. By including VWC at the 0‐month lead time the forecasts explained 7.3% more variability and increased the streamflow volume accuracy by 8.4% on average compared to standard forecasts that already explained an average 77% of the variability. At 1 to 3‐month lead times, the inclusion of soil moisture explained 12.3‐26.3% more variability than the standard forecast on average. Our findings indicate including soil moisture observations increased statistical streamflow forecast accuracy and thus, could potentially improve water supply reliability in regions affected by changing snowpacks.     

Wood bison population recovery and forage availability in northwestern Canada

Forage availability was assessed to determine sustainable stocking rates for eight broadly defined vegetation types (Treed Uplands, Treed Lowlands, Mixed Tall Shrub/Sedge, Closed-canopied Willow, and Open-canopied Willow, Meadow, Wetland Grass, Wetland Sedge) for use by wood bison (Bison bison athabascae), a threatened subspecies, in the Canadian boreal forest of northern Alberta. Clip plots (n=108) were used to sample peak availability of herbs and current annual growth of Salix spp. in late summer. Graminoid wetlands dominated by Carex atherodes, Carex aquatilis, Carex utriculata, Scolochloa festucacea, or Calamagrostis stricta produced 1975-4575 kg ha(-1) of fair to good quality forage, whereas treed stands produced < 250 kg ha(-1) of forb-dominated forage (>85% content), which was below a published 25% foraging efficiency threshold of 263 kg ha(-1) for bison. Upland forests that dominate the region produced < or = 1 animal unit day (AUD) of forage per hectare in summer. Most forest understory plants were of poor forage value, suggesting the potential sustainable stocking rate of such areas was actually < or = 0.3 AUD ha(-1), with even lower rates during winter due to snow cover. Herbaceous wetlands contained approximately 78 AUD ha(-1) of forage, but were considered largely unavailable in summer because of flooding and soft organic soils that make access difficult. Conversion of prime foraging habitat to agricultural land, forest expansion due to fire control, and a warmer and wetter climatic regime after the mid-1900s likely contributed to a regional reduction in carrying capacity. It is hypothesized that substantial recovery of the wood bison population toward historical levels will be constrained in northern Alberta by the availability of summer forage, and the limited extent of graminoid wetlands that provide winter foraging habitat.