Application of encapsulation (pH-sensitive polymer and phosphate buffer macrocapsules): a novel approach to remediation of acidic ground water

Macrocapsules, composed of a pH-sensitive polymer and phosphate buffer, offer a novel remediation alternative for acidic ground waters. To test their potential effectiveness, laboratory experiments were carried out followed by a field trial within a coal pile runoff (CPR) acidic contaminant plume. Results of traditional limestone and macrocapsule treatments were compared in both laboratory and field experiments. Macrocapsules were more effective than limestone as a passive treatment for raising pH in well water from 2.5 to 6 in both laboratory and field experiments. The limestone treatments had limited impact on pH, only increasing pH as high as 3.3, and armoring by iron was evident in the field trial. Aluminum, iron and sulfate concentrations remained relatively constant throughout the experiments, but phosphate increased (0.15-32 mg/L), indicating macrocapsule release. This research confirmed that macrocapsules may be an effective alternative to limestone to treat highly acidic ground water.     

Microbial degradation of pharmaceuticals in estuarine and coastal seawater

Microbial degradation rates were measured for 19 pharmaceuticals in estuarine and coastal surface water samples. Antipyrine, carbamazepine, cotinine, sulfamethoxazole, and trimethoprim were the most refractory (half-lives, t_1/2 = 35 to >100 days), making them excellent candidates for wastewater tracers. Nicotine, acetaminophen, and fluoxetine were labile across all treatments (t_1/2 = 0.68-11 days). Caffeine, diltiazem, and nifedipine were also and relatively labile in all but one of the treatments (t_1/2 = 3.5-13 days). Microbial degradation of caffeine was further confirmed by production ¹⁴CO₂. The fastest decay of non-refractory compounds was always observed in more sewage-affected Jamaica Bay waters. Degradation rates for the majority of these pharmaceuticals are much slower than reported rates for small biomolecules, such as glucose and amino acids. Batch sorption experiments indicate that removal of these soluble pharmaceuticals from the water column to sediments is a relatively insignificant removal process in these receiving waters.     

Duration and characteristics of metal price cycles

This paper addresses the fluctuations in real metal prices: are they simply random variations or do they display some degree of cyclicality? This study identifies peaks and troughs in the inflation adjusted prices for 14 metals, using monthly average data from January 1947 through December 2007. Duration dependence testing, which is performed on the expansions, contractions, and full cycles, finds many cases in which the duration of these phases are not purely random and have some degree of cyclicality. Additional characterization show that contractions generally persist longer than expansions (in contrast to macroeconomic cycles) that long-term real prices have been trendless, and that the amplitude of price changes over the phases has little regularity. For those performing this type of analysis, the appendices explain the procedures for dating turning points and assessing duration dependence.     

Confronting environmental pressure,environmental quality and human health impact indicators of priority air emissions

This paper evaluates the ranking of 21 priority air pollutants with three indicator schemes: environmental pressure indicator (EPI), environmental quality indicator (EQI), and human health effect indicator (HEI). The EPI and EQI compare the emissions and concentrations with the target emissions and target concentrations, respectively. The HEI comprehends the steps from cause (i.e. national emissions) to effect (i.e. human health effects), and is the total human health burden, expressed in Disability Adjusted Life Years per year of exposure (DALYs year^?1). We estimated a health burden in the Netherlands of 41 × 10³ DALYs year^?1 caused by Dutch air emissions of PM10 and its precursors in the year 2003. The burden due to 17 carcinogenic substances emitted to air, was much lower (140 DALYs year^?1). In contrast, when the same substances were evaluated regarding environmental pressure and environmental quality, carbon tetrachloride (pressure) and benzo[a]pyrene (quality) were of highest importance, whereas the importance of PM10 was substantially lower. This result is remarkable, because for the majority of substances evaluated, the target concentrations and target emissions are based on preventing human health damage. The differences in relevance are explained by the different weighting of interests in the indicators. The HEI is based on concentration–response relations, whereas the EPI and EQI also depend on other, policy-based, principles and on technical feasibility. Therefore, to effectively prioritize emission reduction measures in policy-making, substances should not only be evaluated as to whether emission targets and environmental quality targets are reached, but they should be evaluated regarding their human health impact as well. In this context, the HEI is a suitable indicator to evaluate the human health impact.     

Modeling watershed-scale effectiveness of agricultural best management practices to reduce phosphorus loading

Planners advocate best management practices (BMPs) to reduce loss of sediment and nutrients in agricultural areas. However, the scientific community lacks tools that use readily available data to investigate the relationships between BMPs and their spatial locations and water quality. In rural, humid regions where runoff is associated with saturation-excess processes from variable source areas (VSAs), BMPs are potentially most effective when they are located in areas that produce the majority of the runoff. Thus, two critical elements necessary to predict the water quality impact of BMPs include correct identification of VSAs and accurate predictions of nutrient reduction due to particular BMPs. The objective of this research was to determine the effectiveness of BMPs using the Variable Source Loading Function (VSLF) model, which captures the spatial and temporal evolutions of VSAs in the landscape. Data from a long-term monitoring campaign on a 164-ha farm in the New York City source watersheds in the Catskills Mountains of New York state were used to evaluate the effectiveness of a range of BMPs. The data spanned an 11-year period over which a suite of BMPs, including a nutrient management plan, riparian buffers, filter strips and fencing, was installed to reduce phosphorus (P) loading. Despite its simplicity, VSLF predicted the spatial distribution of runoff producing areas well. Dissolved P reductions were simulated well by using calibrated reduction factors for various BMPs in the VSLF model. Total P losses decreased only after cattle crossings were installed in the creek. The results demonstrated that BMPs, when sited with respect to VSAs, reduce P loss from agricultural watersheds, providing useful information for targeted water quality management.     

Cross-Boundary Coordination on Forested Landscapes: Investigating Alternatives for Implementation

Cross-boundary coordination is a tool for ecosystem management whereby landowners voluntarily coordinate management practices toward economic and/or ecological landscape-scale outcomes (e.g., fiber, invasive species control, habitat). Past research indicates that it may be particularly applicable on landscapes that include small forest landholdings. To explore alternatives by which coordination might occur, we conducted seven focus groups with landowners (n = 51) who actively manage their forests in southwest Wisconsin and northeast Iowa. Focus group participants were presented with three hypothetical alternatives to coordinate with their neighbors; landowners could self-organize, work with a natural resource professional (i.e., forester), or work with an organization to complete a cross-boundary practice. In this article, we focus on the latter two alternatives and the role of two social theories—principal-agent and cooperation—in explaining landowners’ evaluations of these alternatives. Key findings are that (1) cross-boundary coordination has the potential to alleviate problems between landowners and resource professionals inherent to their typical working relationship, and (2) social relationships are a major factor contributing to landowners’ willingness to participate. We posit that cross-boundary coordination offers a non-economic incentive for landowners to work together as it may reduce the uncertainty associated with hiring a resource professional. At the same time, professionals can provide a bridging function among landowners who are unacquainted. To achieve these outcomes and expand the adoption of cross-boundary coordination, we suggest four guidelines. First, foster dialogue among landowners toward shared cognition and oversight. Second, match landowners’ practices and objectives such that there are clear benefits to all. Third, develop relationships through low risk activities where possible. Fourth, do not expect on-going commitments.

Making Consistent IUCN Classifications under Uncertainty

Abstract: The World Conservation Union (IUCN) defined a set of categories for conservation status supported by decision rules based on thresholds of parameters such as distributional range, population size, population history, and risk of extinction. These rules have received international acceptance and have become one of the most important decision tools in conservation biology because of their wide applicability, objectivity, and simplicity of use. The input data for these rules are often estimated with considerable uncertainty due to measurement error, natural variation, and vagueness in definitions of parameters used in the rules. Currently, no specific guidelines exist for dealing with uncertainty. Interpretation of uncertain data by different assessors may lead to inconsistent classifications because attitudes toward uncertainty and risk may have an important influence on the classification of threatened species. We propose a method of dealing with uncertainty that can be applied to the current IUCN criteria without altering the rules, thresholds, or intent of these criteria. Our method propagates the uncertainty in the input parameters and assigns the evaluated species either to a single category (as the current criteria do) or to a range of plausible categories, depending on the nature and extent of uncertainties.     

Application of Ecological Classification and Predictive Vegetation Modeling to Broad-Level Assessments of Ecosystem Health

The Little Missouri National Grasslands (LMNG) of western North Dakota support the largest permitted cattle grazing use within all lands administered by the USDA, Forest Service, as well as critical habitat for many wildlife species. This fact, coupled with the need to revise current planning direction for range allotments of the LMNG, necessitated that a broad-level characterization of ecosystem integrity and resource conditions be conducted across all lands within the study area (approximately 800,000 hectares) in a rapid and cost-effective manner. The approach taken in this study was based on ecological classifications, which effectively utilized existing field plot data collected for a variety of previous inventory objectives, and their continuous spatial projection across the LMNG by maps of both existing and potential vegetation. These two map themes represent current and reference conditions (existing vs. potential vegetation); their intersection allowed us to assign various ecological status ratings (i.e., ecosystem integrity and resource condition) based on the degree of departure between current and reference conditions. In this paper, we present a brief review of methodologies used in the development of ecological classifications, and also illustrate their application to assessments of rangeland health through selected maps of ecological status ratings for the LMNG.     

Satellite detection of land-use change and effects on regional forest aboveground biomass estimates

We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg.ha(-1), dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data and land-cover map (University of Maryland) from Advanced Very High Resolution Radiometer (AVHRR) and 2001 products from Moderate Resolution Imaging Spectroradiometer (MODIS) at 1-km resolution for the region; and 30-m resolution land-cover maps from the National Land Cover Data (NLCD) for a subarea to conduct nine simulations to address our questions. Sensitivity analysis showed that (1) AVHRR data tended to underestimate AGB density by 11%, on average, compared to that estimated using MODIS data; (2) regional mean AGB density increased slightly from 124 (1992) to 126 Mg ha(-1) (2001) by 1.6%; (3) a substantial decrease in total forest AGB across the region was detected, from 2,507 (1992) to 1,961 Tg (2001), an annual rate of -2.4%; and (4) in the subarea, while NLCD-based estimates suggested a 26% decrease in total AGB from 1992 to 2001, AVHRR/MODIS-based estimates indicated a 36% increase. The major source of uncertainty in change detection of total forest AGB over large areas was due to area differences from using land-cover maps produced by different sources. Scaling up 30-m land-cover map to 1-km resolution caused a mean difference of 8% (in absolute value) in forest area estimates at the county-level ranging from 0 to 17% within a 95% confidence interval.