Statistical analyses of regional surface water quality in southeastern Ontario

Historical records from Ontario's Provincial Water Quality Monitoring Network (PWQMN) for rivers and streams were analyzed to assess the feasibility of mapping regional water quality patterns in southeastern Ontario which spans two major geologic zones, the Precambrian Shield and the St. Lawrence Lowlands, thus serving as a paradigm for much of Ontario. Despite biases toward the populated Lowlands and associated pollution problems, general spatial trends are evident via the analysis of intervariable relations, individual parameter maps and multivariate analysis. Using a robust algorithm designed to identify outliers and abstract underlying bivariate relations, a linear regional hardness-alkalinity relation was derived, where most anomalies proved to be mine drainage impacted sites. Regionally, multivariate ordination reveals that central tendencies of common indicators of ionic strength and nutrient richness correlate positively and that site clusters broadly reflect the transition from oligotrophic Shield waters to eutrophic conditions of heavily agricultural Lowland streams. Results suggest that on the Shield more precisely delineated aquatic regions may be realized by applying GIS to integrate river and synoptic lake survey data. Further synthesis with bedrock and surficial geology, physiography, pedology and other temporally invariant spatial attributes should yield regional patterns of background quality from which locally attainable water objectives might be defined. Additional synoptic surveys of sedimentary Lowland streams may be required as most available sites relflect anthropogenic pollution.     

Robust graphical methods for diagnosing trend in irregularly spaced water quality time series

Graphical methods can play an important role in the reliable assessment of trends in typically ill behaved river quality data series both as diagnostic tools and as visual corroborative evidence when assumptions required for formal statistical tests are not met. Robust, graphically-oriented trend diagnosis procedures are presented for data series characterized by nonnormal populations, uneven time spacing, nonmonotonic trend and other factors which can create serious problems for standard parametric time series methods. Cleveland's robust locally weighted regression (RLWR) developed for investigating nonlinearity in x-y scatterplots is adapted as a robust/resistant smoothing filter for the analysis of irregular time series comprising quantitative observations. Low powered RLWR trend lines reveal temporally local phenomena, e.g. abrupt jumps (often associated with point source impacts) and periodicities, while higher powered RLWR yields smooth lines characterizing medium and longer term trends. Simple variants of Tukey smoothing concepts are developed for series with censored observations. Applications to Ontario river quality series reveal that graphical evidence is frequently sufficient to obviate the need for formal trend testing. The methods are generally applicable to most time series.     

The macro implications of a complete transformation of U.S. agricultural production to organic farming practices

A national interregional linear programming model of U.S. agriculture is used to evaluate and compare two conventional and three organic production alternatives. The objective is to estimate the effects on production, supply prices, land use, farm income, and export potential, of a complete transformation of U.S. agriculture to organic practices. Crop yields and production costs are estimated for 150 producing regions for seven crops under both conventional and organic methods. Results indicate that compared with conventional methods, widespread organic farming leads to a decrease in total production, lower export potential, higher supply prices, higher value of production, lower costs of production, and higher net farm income. The United States domestic crop demand can be met with organic methods, but would be more expensive. Some interregional shifts in crop production would also occur.     

Effects of Vertical Temperature Difference on Soiling Index

Changes in contaminant levels at monitoring stations do not necessarily represent changes in emission levels, since variations in meteorological parameters determine the transport and diffusion of contaminants between sources and receptors. To estimate annual changes in emission levels, and thus of control program effectiveness, the meteorological stratification of data was employed to provide “comparable days.”

For San Francisco Bay Area photochemical oxidant data, simple criteria based on maximum temperature and on height of inversion base were selected. Temperature provided a readily available integrated index of solar energy input and of ventilation, while the inversion data added a vertical dilution factor.

An earlier study, employing only the temperature criteria, showed that oxidant levels on comparable warm days had nearly doubled from 1954 through 1962. The current study of oxidant data for 1962 through 1969 shows a gradual rise through 1965, and a sharp reversal in 1966, when for the first time a simultaneous decrease was noted at each benchmark station. Data through 1969 show that average oxidant levels have been maintained at this 25% lower plateau, with minor fluctuations at individual stations.

The general improvement in air quality since 1965 is attributed to the reduction of reactive organics emitted from stationary and automotive sources.     

Mold spore penetration through wall service outlets: a pilot study

A pilot study was conducted to estimate fungal spore penetration for wall service outlets subjected to a constant air pressure. During the laboratory experiment, a wall chamber was fabricated, and telephone, electrical, and cable service outlets were installed. Penicillium chrysogenum spores were aerosolized into the chamber that was held under pressure. Spores that penetrated the outlets were funneled into an impinger for microscopic enumeration. Thirty trials were conducted for each of the five outlets (N?= 150), and the wall chamber was decontaminated between trials. Results of an analysis of variance suggest wall service outlets allow spore penetration. The penetration factor for the telephone outlet was significantly greater than all other outlets (p?< 0.05), and there was no difference in penetration between electrical outlets with and without plugs. Penetration factor differences were attributed to air leakage rates across the outlets. Due to the experimental design and equipment limitations, further research is needed to support these findings.     

Adaptive Management: From More Talk to Real Action

The challenges currently facing resource managers are large-scale and complex, and demand new approaches to balance development and conservation goals. One approach that shows considerable promise for addressing these challenges is adaptive management, which by now is broadly seen as a natural, intuitive, and potentially effective way to address decision-making in the face of uncertainties. Yet the concept of adaptive management continues to evolve, and its record of success remains limited. In this article, we present an operational framework for adaptive decision-making, and describe the challenges and opportunities in applying it to real-world problems. We discuss the key elements required for adaptive decision-making, and their integration into an iterative process that highlights and distinguishes technical and social learning. We illustrate the elements and processes of the framework with some successful on-the-ground examples of natural resource management. Finally, we address some of the difficulties in applying learning-based management, and finish with a discussion of future directions and strategic challenges.     

Sustainability Assessment for Agriculture Scenarios in Europe’s Mountain Areas: Lessons from Six Study Areas

Sustainability assessment (SA) is a holistic and long-range strategic instrument capable of assisting policy-making in electing, and deciding upon, future development priorities. The outcomes of an SA process become more relevant and strengthened when conducted with multi-stakeholder engagement, which provides for multiple dialogues and perspectives. This was the object of research of the SA team in the context of BioScene (Scenarios for Reconciling Biodiversity Conservation with Declining Agriculture Use in Mountain Areas in Europe), a three-year project (2002–2005) funded by the European Union 5th Framework Program, which aimed to investigate the implications of agricultural restructuring and decline for biodiversity conservation in the mountain areas of Europe, using three distinct methodological streams: the ecological, the socio-economic, and the SA approaches. The SA approach drew on the previous two to assess the importance for biodiversity management of different scenarios of agri-environmental change and rural policy in six countries (France, Greece, Norway, Slovakia, Switzerland, and the United Kingdom), develop causal chains, include stakeholder views, and identify potential contributions for, or conflicts with, sustainability. This article tells how SA was used, what sustainability meant in each study area through different objectives of sustainability considered, discusses the methods used in SA, and the benefits arising. The SA was conducted by a team independent of any study area, who developed and oversaw the application of the SA methodology, assisting national teams, and developing a cross-country understanding of the sustainability of proposed scenarios in the different geographical and social contexts, and their implications for policy-making. Finally, it reflects on the persistent challenges of interdisciplinary research, compounded by multi-cultural teams, and concludes on the BioScene’s lessons for the further development and application of SA.

An Intelligent Emissions Controller for Fuel Lean Gas Reburn in Coal-Fired Power Plants

ABSTRACT

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NO_x) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NO_x reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach.

Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NO_x emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.     

COMPARISON OF RESERVOIR LINEAR OPERATION RULES USING LINEAR AND DYNAMIC PROGRAMMING1

ABSTRACT: Mathematical optimization techniques are used to study the operation and design of a single, multi-purpose reservoir system. Optimal monthly release policies are derived for Hoover Reservoir, located in Central Ohio, using chance-constrained linear programming and dynamic programming-regression methodologies. Important characteristics of the former approach are derived, discussed, and graphically illustrated using Hoover Reservoir as a case example. Simulation procedures are used to examine and compare the overall performance of the optimal monthly reservoir release policies derived under the two approaches. Results indicate that, for the mean detention time and the corresponding safe yield target water supply release under existing design of Hoover Reservoir, the dynamic programming policies produce lower average annual losses (as defined by a two-sided quadratic loss function) while achieving at least as high reliability levels when compared to policies derived under the chance-constrained linear programming method. In making this comparison, the reservoir release policies, although not identical, are assumed to be linear. This restricted form of the release policy is necessary to make the chance-constrained programming method mathematically tractable.