Lagoon-biogas emissions and carbon balance estimates of a swine production facility

Gaseous emissions from animal manure storage facilities can contribute to global greenhouse gas inventories. Biogas fluxes were measured for one year from a 2-ha anaerobic lagoon that received waste from a 10500-head swine (Sus scrofa) finishing operation in southwestern Kansas. During 2001, ebullition of biogas was measured continuously by using floating platforms equipped with gas-collection domes. Periodically, the composition of the biogas was determined by using gas chromatography. Detailed records of feed quality and quantity and animal weights and gains also were obtained to determine the carbon budget of the facility (barns and lagoon). Flux of biogas was very seasonal, with peak emission (18.7 mol m(-2) d(-1)) occurring in early June. Nearly 50% of the annual biogas losses occurred during a 30-d period beginning on day of year (DOY) 146. Flux patterns suggest that the start of the high biogas production period was governed by temperature, while the decline in production in mid-June was caused by substrate limitations. Average biogas composition was 0.71 L CH4 L(-1). The quantity of CH4 released from the lagoon was 86.3 Mg yr(-1), which represents about 38 g of CH4 per kg of animal weight gain. The average flux density of biogas from the lagoon was 382 mol m(-2) yr(-1) or 728 mol yr(-1) per resident animal where the resident animal population was 10500. Flux rates of CH4 were 1.7 to 3.4 times less than predictions made with Intergovernmental Panel on Climate Change (IPCC) models. Additional research is needed on the carbon budgets of other animal feeding operations so that better estimates of greenhouse gas emissions can be determined.     

Modelling soil series data to facilitate targeted habitat restoration: a polytomous logistic regression approach

Habitat restoration at a landscape scale is becoming increasingly important in environmental management. In this context, geographical information systems are well suited as they can store and integrate many of the abiotic and biotic criteria used to assess the ecological worth of a site. However, this capacity can be limited by the availability or suitability of spatial data sets. A classic example of the latter case is the National Soil Map of England and Wales, which groups soils of a varied nature into associations. Consequently the national soil map has proved to be a poor predictor of habitat suitability. Using polytomous logistic regression we put forward a method for separating soil associations into their constituent soils within the Chilterns Natural Area. This approach used soil association, aspect, slope and relative height as variables for this analysis. Whilst the model's performance is likely to have been limited by the accuracy of the soil association data set, a predictive accuracy of between 47 and 65% is sufficient to facilitate better targeting of habitat restoration when combined with other abiotic factors such as climate and topography.     

The ironic compatibility of recycling practice and UK government policy

On the face of it, the 1990s have marked the transformation of the UK's waste management policy. A commitment to waste minimisation and recycling, within the terms of the internationally accepted waste hierarchy, have replaced an almost complacent defence of landfill. However, aside from the dramatic transformation of the vocabulary, the reality of local authority waste disposal has, with a few notable exceptions, been characterised more by continuity than revolution. This article suggests that the modesty of local authority recycling is best explained through an appreciation of what can be described as recycling practice. Recycling in the UK has taken a distinctive form comprising: environmentalism, entrepreneurialism and policy advocacy. The components of this practice explain both the successes and failures of local authority recycling. Despite its oppositional roots, the Conservative Government found 'recycling practice' conducive to their reliance upon a mix of aspirational targets and market-based instruments (MBIs). Advice circulated as guidance to local authorities emphasised viability as the principal criterion of scheme assessment and in such a way sustained the limited scale and ambitions of recycling practice.     

Evaluation of the available air pollution control technologies for achievement of the MACT requirements in the newly implemented new source performance standards (NSPS) and emission guidelines (EG) for hospital and medical/infectious waste incinerators

After many years of research and debate, in August of 1997 the United States Environmental Protection Agency (EPA) issued New Source Performance Standards (NSPS) and Emission Guidelines (EG) for medical/infectious waste incinerators in the United States. These new emissions and operational standards establish considerably more restrictive limitations on air emissions for medical/infectious waste incinerators and will undoubtedly have a significant impact on the over 2300 hospitals presently operating an incinerator on-site. This paper will explore the options available to these facilities, and those facilities which may be considering installation of an incinerator, relative to achieving compliance with the NSPS and EG for medical/infectious waste incinerators.     

Application Of Artificial Neural Network Models To Analyse The Relationships Between Gammarus pulex L. (Crustacea, Amphipoda) And River Characteristics

This study aimed at analysing the relationship between river characteristics and abundance of Gammarus pulex. To this end, four methods which can identify the relative contribution and/or the contribution profile of the input variables in neural networks describing the habitat preferences of this species were compared: (i) the ‘PaD‘ (‘Partial Derivatives‘) method consists of a calculation of the partial derivatives of the output in relation to the input variables; (ii) the ‘Weights‘method is a computation using the connection weights of the backpropagation Artificial Neural Networks; (iii) the ‘Perturb‘method analyses the effect of a perturbation of the input variables on the output variable; (iv) the ‘Profile‘ method is a successive variation of one input variable while the others are kept constant at a fixed set of values. The dataset consisted of 179 samples, collected over a three-year period in the Zwalm river basin in Flanders, Belgium. Twenty-four environmental variables as well as the log-transformed abundance of Gammarus pulex were used in this study. The different contribution methods gave similar results concerning the order of importance of the input variables. Moreover, the stability of the methods was confirmed by gradually removing variables. Only in a limited number of cases a shift in the relative importance of the remaining input variables could be observed. Nevertheless, differences in sensitivity and stability of the methods were detected, probably as a result of the different calculation procedures. In this respect, the ‘PaD‘method made a more severe discrimination between minor and major contributing environmental variables in comparison to the ‘Weights‘, ‘Profile‘ and ‘Perturb‘ methods. From an ecological point of view, the input variables ‘Ammonium‘ and to a smaller extent ‘COD‘, were selected by these methods as dominant river characteristics for the prediction of the abundance of Gammarus pulex in this study area.     

Monitoring of krypton-85 activity in the atmosphere around Prague

The results of measurements of Krypton-85 (⁸⁵Kr) concentrations in the ground-level air of Prague between 1983 and 1992 are presented and time-related changes analysed. The long-term trend in activity level of ⁸⁵Kr has been steadily increasing with a growth rate of 0.04 Bq.m^–3 (STP) per year. Some peaks of ⁸⁵Kr activity were observed due to the influence of undispersed radioactive plumes coming from distant sources. Short-term variations within a typical range of concentrations from 0.61 to 1.25 Bq.m^–3 (STP) were found to be seasonally dependent, with the maximum occurring in spring.     

A Decision Support Framework for Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers–Pressures–States–Impacts–Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.     

Daily Updating of Operational Statistical Seasonal Water Supply Forecasts for the western U.S.1

Abstract: Official seasonal water supply outlooks for the western United States are typically produced once per month from January through June. The Natural Resources Conservation Service has developed a new outlook product that allows the automated production and delivery of this type of forecast year‐round and with a daily update frequency. Daily snow water equivalent and water year‐to‐date precipitation data from multiple SNOTEL stations are combined using a statistical forecasting technique (“Z‐Score Regression”) to predict seasonal streamflow volume. The skill of these forecasts vs. lead‐time is comparable to the official published outlooks. The new product matches the intra‐monthly trends in the official forecasts until the target period is partly in the past, when the official forecasts begin to use information about observed streamflows to date. Geographically, the patterns of skill also match the official outlooks, with highest skill in Idaho and southern Colorado and lowest skill in the Colorado Front Range, eastern New Mexico, and eastern Montana. The direct and frequent delivery of objective guidance to users is a significant new development in the operational hydrologic seasonal forecasting community.     

Nitrogen Content of Letharia vulpina Tissue from Forests of the Sierra Nevada, California: Geographic Patterns and Relationships to Ammonia Estimates and Climate

Nitrogen (N) pollution is a growing concern in forests of the greater Sierra Nevada, which lie downwind of the highly populated and agricultural Central Valley. Nitrogen content of Letharia vulpina tissue was analyzed from 38 sites using total Kjeldahl analysis to provide a preliminary assessment of N deposition patterns. Collections were co-located with plots where epiphytic macrolichen communities are used for estimating ammonia (NH₃) deposition. Tissue N ranged from 0.6% to 2.11% with the highest values occurring in the southwestern Sierra Nevada (range: 1.38 to 2.11). Tissue N at 17 plots was elevated, as defined by a threshold concentration of 1.03%. Stepwise regression was used to determine the best predictors of tissue N from among a variety of environmental variables. The best model consisted only of longitude (r ² = 0.64), which was reflected in the geographic distribution of tissue values: the southwestern Sierra Nevada, the high Sierras near the Tahoe Basin, and the Modoc Plateau, are three apparent N hotspots arranged along the tilted north–south axis of the study area. Withholding longitude and latitude, the best regression model suggested that NH₃ estimates and annual number of wetdays interactively affect N accumulation (r ² = 0.61; % N ∼ NH₃ + wetdays + (NH₃ × wetdays)). We did not expect perfect correspondence between tissue values and NH₃ estimates since other N pollutants also accumulate in the lichen thallus. Additionally, other factors potentially affecting N content, such as growth rate and leaching, were not given full account.