Heriberto Cabezas

Pollution prevention with chemical process simulators: the generalized waste reduction (WAR) algorithm—full version

A general theory for the flow and the generation of potential environmental impact through a chemical process has been developed. The theory defines six potential environmental impact indexes that characterize the generation of potential impact within a process, and the output of potential impact from a process. The indexes are used to quantify pollution reduction and to develop pollution reducing changes to process flow sheets using process simulators. The potential environmental impacts are calculated from stream mass flow rates, stream composition, and a relative potential environmental impact score for each chemical present. The chemical impact scores include a comprehensive set of nine effects ranging from ozone depletion potential to human toxicity and ecotoxicity. The resulting waste reduction methodology or WAR algorithm is illustrated with two case studies using the chemical process simulator Chemcad III (Use does not imply USEPA endorsement or approval of Chemcad III).

Designing sustainable processes with simulation: the waste reduction (WAR) algorithm

Abstract The WAR algorithm, a methodology for determining the potential environmental impact (PEI) of a chemical process, is presented with modifications that account for the PEI of the energy consumed within that process. From this theory, four PEI indexes are used to evaluate the environmental friendliness of a process design. These indexes are used in a comparative manner in the process design stage to help minimize the environmental impact of that process. Eight PEI categories (four global and four toxicological) are used in the evaluation of the PEI indexes. Details for relating these categories to known or measured quantities are also presented. An illustrative case study is presented which provide an example for the intended use of the WAR algorithm within the scope of process design and simulation.

The waste reduction (WAR) algorithm : environmental impacts, energy consumption, and engineering economics

A general theory known as the waste reduction (WAR) algorithm has been developed to describe the flow and the generation of potential environmental impact through a chemical process. The theory defines indexes that characterize the generation and the output of potential environmental impact from a process. The existing theory has been extended to include the potential environmental impact of the energy consumed in a chemical process. Energy will have both an environmental impact as well as an economic impact on process design and analysis. Including energy into the analysis of environmental impact is done by re-writing the system boundaries to include the power plant which supplies the energy being consumed by the process and incorporating the environmental effects of the power plant into the analysis. The effect of this addition on the original potential impact indexes will be discussed. An extensive engineering economic evaluation has been included in the process analysis which inherently contains the cost of the consumed energy as an operating cost. A case study is presented which includes a base process design and two modifications to the base design. Each design is analyzed from an economic perspective and an environmental impact perspective. The environmental impact analysis is partitioned into the impacts of the non-product streams and the impacts of the energy generation/consumption process. The comparisons of these analysis procedures illustrate the consequences for decision making in the design of environmentally friendly processes.

Pollution prevention with chemical process simulators: The generalized waste reduction (WAR) algorithm

A general theory for the flow and the generation of potential environmental impact through a chemical process has been developed. The theory defines six potential impact indexes that characterize the generation of potential impact within a process, and the output of potential impact from a process. The indexes are used to quantify and to guide pollution reduction with changes to process flow sheets using process simulators. The potential environmental impacts are calculated from stream mass flow rates, stream composition, and a relative potential impact score for each chemical present. The chemical impact scores include a comprehensive set of nine effects ranging from ozone depletion potential to human toxicity and ecotoxicity. The resulting Waste Reduction methodology or WAR Algorithm is illustrated with a case study using the chemical process simulator Chemcad III (Does not imply USEPA endorsement of Chemcad III).

Towards a theory of sustainable systems

Abstract While there is tremendous interest in sustainability, a fundamental theory of sustainability does not exist. We present our efforts at constructing a theory from Information Theory and Ecological Models. We discuss the state of complex systems that incorporate ecological and other components in terms of dynamic behavior in a phase space defined by the system state variables. From sampling the system trajectory, a distribution function for the probability of observing the system in a given state is constructed, and an expression for the Fisher information is derived. Fisher information is the maximum amount of information available from a set of observations, in this case, states of the system. Fisher information is a function of the variability of the observations such that low variability leads to high Fisher information and high variability leads to low Fisher information. Systems in stable dynamic states have constant Fisher information. Systems losing organization migrate toward higher variability and lose Fisher information. Self-organizing systems decrease their variability and acquire Fisher information. These considerations lead us to propose a sustainability hypothesis: “sustainable systems do not lose or gain Fisher information over time.” We illustrate these concepts using simulated ecological systems in stable and unstable states, and we discuss the underlying dynamics.

Theory of phase formation in aqueous two-phase systems

Currently there are a number of different mathematical models for phase equilibria in aqueous two-phase systems available. This diversity can create some confusion for model users, since most models seem to perform reasonably well. Choosing a model, thus, becomes rather a difficult task. In trying to address this problem, the principal models and the relevant theory available are reviewed. A discussion of osmotic viral expansions, lattice theory, group contribution, scaling ideas, excluded volume, electrostatics and other modeling approaches is presented. The strengths of the different approaches are critically evaluated and suggestions offered. Choosing a model, however, requires sophistication because each model is typically best at representing only a few particular aspects of system behavior, and the intended use of the model must be considered. Some suggestions for future work are also given.

A new framework for urban sustainability assessments: Linking complexity,information and policy

Abstract Urban systems emerge as distinct entities from the complex interactions among social, economic and cultural attributes, and information, energy and material stocks and flows that operate on different temporal and spatial scales. Such complexity poses a challenge to identify the causes of urban environmental problems and how to address them without causing greater deterioration. Planning has traditionally focused on regulating the location and intensity of urban activities to avoid environmental degradation, often based on assumptions that are rarely revisited and producing ambiguous effects. The key intellectual challenge for urban policy-makers is a fuller understanding of the complexity of urban systems and their environment. We address this challenge by developing an assessment framework with two main components: (1) a simple agent-based model of a hypothetical urbanizing area that integrates data on spatial economic and policy decisions, energy and fuel use, air pollution emissions and assimilation, to test how residential and policy decisions affect urban form, consumption and pollution; (2) an information index to define the degree of order and sustainability of the hypothetical urban system in the different scenarios, to determine whether specific policy and individual decisions contribute to the sustainability of the entire urban system or to its collapse.

Detection and Assessment of Ecosystem Regime Shifts from Fisher Information

Ecosystem regime shifts, which are long-term system reorganizations, have profound implications for sustainability. There is a great need for indicators of regime shifts, particularly methods that are applicable to data from real systems. We have developed a form of Fisher information that measures dynamic order in complex systems. Here we propose the use of Fisher information as a means of: (1) detecting dynamic regime shifts in ecosystems, and (2) assessing the quality of the shift in terms of intensity and pervasiveness. Intensity is reflected by the degree of change in dynamic order, as determined by Fisher information, and pervasiveness is a reflection of how many observable variables are affected by the change. We present a new robust methodology to calculate Fisher information from time series field data. We demonstrate the use of Fisher information to detect regime shifts on a model for a shallow lake. Next, we use Fisher information to analyze marine ecosystem response to physical changes using real time-series data of a coastal marine ecosystem, the North Pacific Ocean.

Evaluating the sustainability of a regional system using Fisher information in the San Luis Basin, Colorado

This paper describes the theory, data, and methodology necessary for using Fisher information to assess the sustainability of the San Luis Basin (SLB) regional system over time. Fisher information was originally developed as a measure of the information content in data and is an important method in information theory. Our adaptation of Fisher information provides a means of monitoring the variables of a system to characterize dynamic order, and, therefore, its regimes and regime shifts. This work is part of the SLB Sustainability Metrics Project, which aimed to evaluate movement over time towards or away from regional sustainability. One of the key goals of this project was to use readily available data to assess the sustainability of the system including its environmental, social and economic aspects. For this study, Fisher information was calculated for fifty-three variables which characterize the consumption of food and energy, agricultural production, environmental characteristics, demographic properties and changes in land use for the SLB system from 1980 to 2005. Our analysis revealed that while the system displayed small changes in dynamic order over time with a slight decreasing trend near the end of the period, there is no indication of a regime shift. Therefore, the SLB system is stable with very slight movement away from sustainability in more recent years.

Development of a multidisciplinary approach to assess regional sustainability

There are a number of established, scientifically supported metrics of sustainability. Many of the metrics are data-intensive and require extensive effort to collect data and compute the metrics. Moreover, individual metrics do not capture all aspects of a system that are relevant to sustainability. A pilot project was initiated to create an approach to measure, monitor, and maintain prosperity and environmental quality of a regional system. The goal was to produce a straightforward, inexpensive methodology that is simple to use and interpret. This requires historical data be readily accessible, metrics must be applicable to the relevant scale, and results must meet the needs of decision-makers. Because sustainability is a multidimensional concept, the research group consisted of a multidisciplinary team that identified the major components of an environmental system. We selected metrics to capture the multidimensionality of sustainability in environmental systems and included: (1) emergy to capture the quality-normalized flow of energy through the system; (2) ecological footprint to capture the impact of humans on the system; (3) green net regional product to estimate human prosperity and well being within the system; and (4) Fisher information to capture the dynamic order of the system. We were able to compute metrics for a test geographic region using existing datasets. Preliminary analysis indicates that each metric reveals a somewhat different trend. These preliminary findings support the idea that characterization of sustainability requires a multidisciplinary approach and demonstrate the need to measure multiple aspects of an environmental system.