Application of tracer ratio and inverse dispersion methods with boat-based plume measurements to estimate ammonia emissions from seabird colonies

Ammonia emissions from two contrasting seabird colonies in Scotland were measured, based on the determination of atmospheric concentrations downwind of the colonies. Atmospheric concentrations of ammonia (NH₃) across the downwind plume were compared with the inverse application of a Gaussian dispersion model (ID) to calculate the modelled NH₃ emission that would generate the measured cross-wind-integrated plume concentration. In parallel, a tracer gas (sulphur hexafluoride, SF₆) was released from the colonies with air samples taken to allow determination of SF₆ concentrations. On the basis of the known emission rate of SF₆, the magnitude of ammonia emissions was estimated by the cross-wind-integrated tracer ratio (TR) of NH₃/SF₆ concentrations. Coupled with data on annual bird attendance, the measurements indicate annual emissions from the Isle of May and the Bass Rock of 18 and 132 tonnes NH₃-N year^–1, respectively. The measured NH₃ emissions were compared with estimates of seabird nitrogen excretion to estimate the proportion of excreted N that is volatilised as NH₃ (F_Nr). The emission estimates of the two methods compared favourably, giving 4 and 6 kg NH₃-N h^–1 (F_Nr = 15%) for the Isle of May for the ID and TR methods, respectively, and 21 and 25 kg NH₃-N h^–1 (F_Nr = 50%) for the Bass Rock for the ID and TR methods, respectively. The results provide the first measurement-based estimates to allow regional up scaling of ammonia emissions from seabirds.     

Enzyme-Retted Flax Fiber and Recycled Polyethylene Composites

Municipal solid wastes generated each year contain potentially useful and recyclable materials for composites. Simultaneously, interest is high for the use of natural fibers, such as flax (Linum usitatissimum L.), in composites thus providing cost and environmental benefits. To investigate the utility of these materials, composites containing flax fibers with recycled high density polyethylene (HDPE) were created and compared with similar products made with wood pulp, glass, and carbon fibers. Flax was either enzyme- or dew-retted to observe composite property differences between diverse levels of enzyme formulations and retting techniques. Coupling agents would strengthen binding between fibers and HDPE but in this study fibers were not modified in anyway to observe mechanical property differences between natural fiber composites. Composites with flax fibers from various retting methods, i.e., dew- vs. enzyme-retting, behaved differently; dew-retted fiber composites resulted in both lower strength and percent elongation. The lowest level of enzyme-retting and the most economical process produces composites that do not appear to differ from the highest level of enzyme-retting. Flax fibers improved the modulus of elasticity over wood pulp and HDPE alone and were less dense than glass or carbon fiber composites. Likely, differences in surface properties of the various flax fibers, while poorly defined and requiring further research, caused various interactions with the resin that influenced composite properties.     

Mechanical and Barrier Properties of Biodegradable Films Made from Chitosan and Poly (Lactic Acid) Blends

Biodegradable film blends of chitosan with poly(lactic acid) (PLA) were prepared by solution mixing and film casting. The main goal of these blends is to improve the water vapor barrier of chitosan by blending it with a hydrophobic biodegradable polymer from renewable resources. Mechanical properties of obtained films were assessed by tensile test. Thermal properties, water barrier properties, and water sensitivity were studied by differential scanning calorimeter analysis, water vapor permeability measurements, and surface-angle contact tests, respectively. The incorporation of PLA to chitosan improved the water barrier properties and decreased the water sensitivity of chitosan film. However, the tensile strength and elastic modulus of chitosan decreased with the addition of PLA. Mechanical and thermal properties revealed that chitosan and PLA blends are incompatible, consistent with the results of Fourier transform infrared (FTIR) analysis that showed the absence of specific interaction between chitosan and PLA.     

Radiogenic Lead Isotopes and Time Stratigraphy in the Hudson River, New York

Radionuclide, radiogenic lead isotope and trace metal analyses on fine-grained sediment cores collected along 160 km of the upper and tidal Hudson River were used to examine temporal trends of contaminant loadings and to develop radiogenic lead isotopes both as a stratigraphic tool and as tracers for resolving decadal particle transport fluxes. Very large inputs of Cd, Sb, Pb, and Cr are evident in the sediment record, potentially from a single manufacturing facility. The total range in radiogenic lead isotope ratios observed in well-dated cores collected about 24 km downstream of the plant is large (e.g., maximum difference in ²⁰⁶Pb/²⁰⁷Pb is 10%), characterized by four major shifts occurring in the 1950s, 1960s, 1970s and 1980s. The upper Hudson signals in Cd and radiogenic lead isotopes were still evident in sediments collected 160 km downstream in the tidal Hudson. The large magnitude and abrupt shifts in radiogenic lead isotope ratios as a function of depth provide sensitive temporal constraints that complement information derived from radionuclide analyses to significantly improve the precision of dating assignments. Application of a simple dilution model to data from paired cores suggests much larger sediment inputs in one section of the river than previously reported, suggesting particle influxes to the Hudson have been underestimated.     

A framework for multi-level stakeholder studies in response to global change

Global change, as a process of large-scale environmental effects, and globalisation, as a change in peoples' livelihoods and consumption patterns, will impact communities increasingly in the years to come. Given these pressures, stakeholder consultations and broader stakeholder-centred activities that look at how people are affected by and able to adapt to change become crucial. Stakeholder consultations have been advanced, for instance, in Integrated Assessment activities which include several disciplines and stakeholder participation. Yet, thus far, such consultations have typically taken the form of direct group discussions, in which the differences in the way scientists and other stakeholders communicate are often underestimated. This paper suggests that there is a need to go beyond stakeholder dialogue to focus on the complex institutional factors that shape stakeholders' understandings and actions on multiple levels. Stakeholder studies would thus include not only direct consultation but also a social analysis of the vulnerabilities and adaptive capacities of regional and local institutions and livelihoods.     

Environmental Ethics Beyond Principle? The Case for a Pragmatic Contextualism

Many nonanthropocentric environmental ethicists subscribe to a ``principle-ist' approach to moral argument, whereby specific natural resource and environmental policy judgments are deduced from the prior articulation of a general moral principle. More often than not, this principle is one requiring the promotion of the intrinsic value of nonhuman nature. Yet there are several problems with this method of moral reasoning, including the short-circuiting of reflective inquiry and the disregard of the complex nature of specific environmental problems and policy arguments. In the present paper, we advance an alternative, pragmatic contextualist approach to environmental ethics, one grounded in the moral theory of John Dewey. We present the results of an empirical study of public environmental ethics and natural resource management attitudes to support our position, and we conclude with a few recommendations for future inquiry in the field of environmental ethics.     

Effect of selected and non-selected urban waste compost on the initial growth of corn

Brazil produces approximately 242,000 t of waste per day, 76% of it being dumped outdoors and only 0.9% recycled, including composting, which is an alternative still little known in Brazil. In search of a better destination for residues produced by domestic activities, composting stands as a feasible alternative. Organic compost from waste may be used for various purposes, among which are soil recovery, commercial production, pastures, lawns and reforestry and agriculture. However, the quality of the compost determines the growth and the development of plants. The effect of compost made from urban waste on corn plant (Zea mays L.) growth was investigated. Two types of compost were used: the selected compost (SC), produced from organic waste selectively collected; and the non-selected compost (NSC), taken from a 15-year-old cell from the Canabrava land-fill, located in Salvador, Bahia, Brazil (altitude 51 m, 12°22′–13°08′S, 38°08′–38°47′W). Corn was seeded in polyethylene pots, with soil-compost mixing substrate in the proportion of 0, 15, 30, 45 and 60 t ha⁻¹ equivalent doses. Chemical analyses of the compost and growth properties of the plant like chlorophyll content; height and stem diameter; aerial and radicular dry biomasses, were used to evaluate compost quality. Plants cultivated with SC presented a superior gain, being of 52.5% in stem diameter, 71.1 and 81.2% in root and stem biomasses, respectively. Chlorophyl content alterations were observed in plants from treatments using 30 t compost ha⁻¹ dose onwards. Conventional and multivariate statistical methods were used to evaluate these results. The beneficial action of organic compost in plant growth was confirmed with this research.     

TEMPORAL CHANGES IN THE YADKIN RIVER FLOW VERSUS SUSPENDED SEDIMENT CONCENTRATION RELATIONSHIP1

ABSTRACT: Dynamic linear models (DLM) and seasonal trend decomposition (STL) using local regression, or LOESS, were used to analyze the 50‐year time series of suspended sediment concentrations for the Yadkin River, measured at the U.S. Geological Survey station at Yadkin College, North Carolina. A DLM with constant trend, seasonality, and a log₁₀ streamflow regressor provided the best model to predict monthly mean log₁₀ suspended sediment concentrations, based on the forecast log likelihood. Using DLM, there was evidence (odds approximately 69:1) that the log₁₀ streamflow versus log₁₀ suspended sediment concentration relationship has changed, with an approximate 20 percent increase in the log₁₀ streamflow coefficient over the period 1981 to 1996. However, sediment concentrations in the Yadkin River have decreased during the decade of the 1990s, which has been accompanied by a concomitant increase in streamflow variability. Although STL has been shown to be a versatile trend analysis technique, DLM is shown to be more suitable for discovery and inference of structural changes (trends) in the model coefficient describing the relationship between flow and sediment concentration.     

ENHANCING FECAL COLIFORM TOTAL MAXIMUM DAILY LOAD MODELS THROUGH BACTERIAL SOURCE TRACKING1

ABSTRACT: Surface water impairment by fecal coliform bacteria is a water quality issue of national scope and importance. In Virginia, more than 400 stream and river segments are on the Commonwealth's 2002 303(d) list because of fecal coliform impairment. Total maximum daily loads (TMDLs) will be developed for most of these listed streams and rivers. Information regarding the major fecal coliform sources that impair surface water quality would enhance the development of effective watershed models and improve TMDLs. Bacterial source tracking (BST) is a recently developed technology for identifying the sources of fecal coliform bacteria and it may be helpful in generating improved TMDLs. Bacterial source tracking was performed, watershed models were developed, and TMDLs were prepared for three streams (Accotink Creek, Christians Creek, and Blacks Run) on Virginia's 303(d) list of impaired waters. Quality assurance of the BST work suggests that these data adequately describe the bacteria sources that are impairing these streams. Initial comparison of simulated bacterial sources with the observed BST data indicated that the fecal coliform sources were represented inaccurately in the initial model simulation. Revised model simulations (based on BST data) appeared to provide a better representation of the sources of fecal coliform bacteria in these three streams. The coupled approach of incorporating BST data into the fecal coliform transport model appears to reduce model uncertainty and should result in an improved TMDL.     

AN EVALUATION OF THE AVAILABLE TECHNIQUES FOR ESTIMATING MISSING FECAL COLIFORM DATA1

ABSTRACT: This paper presents the findings of a study aimed at evaluating the available techniques for estimating missing fecal coliform (FC) data on a temporal basis. The techniques investigated include: linear and nonlinear regression analysis and interpolation functions, and the use of artificial neural networks (ANNs). In all, seven interpolation, two regression, and one ANN model structures were investigated. This paper also investigates the validity of a hypothesis that estimating missing FC data by developing different models using different data corresponding to different dynamics associated with different trends in the FC data may result in a better model performance. The FC data (counts/100 ml) derived from the North Fork of the Kentucky River in Kentucky were employed to calibrate and validate various models. The performance of various models was evaluated using a wide variety of standard statistical measures. The results obtained in this study are able to demonstrate that the ANNs can be preferred over the conventional techniques in estimating missing FC data in a watershed. The regression technique was not found suitable in estimating missing FC data on a temporal basis. Further, it has been found that it is possible to achieve a better model performance by first decomposing the whole data set into different categories corresponding to different dynamics and then developing separate models for separate categories rather than developing a single model for the composite data set.