A multi-objective location-allocation optimization for sustainable management of municipal solid waste

The location problem of treatment and service facilities in municipal solid waste (MSW) management system is of significant importance due to the socioeconomic and environmental concerns. The consideration of waste treatment costs, environmental impact, greenhouse gas (GHG) emissions, social fairness as well as other relevant aspects should be simultaneously taken into account when a MSW management system is planned. Development of sophisticated decision support tools for planning MSW management system in an economic-efficient and environmental friendly manner is therefore important. In this paper, a general multi-objective location-allocation model for optimally managing the interactions among those conflicting factors in MSW management system is proposed. The model is comprised of a three-stage conceptual framework and a mixed integer mathematical programming. The inclusion of environmental impact and GHG emission objectives push the output of the model tightening toward more environmentally friendly and sustainable solutions in MSW management. The application of this model is demonstrated through an illustrative example, and the computational efficiency of the programming is also tested through a set of incremental parameters. Latter in this paper, a comparison with previous case studies of MSW system design is presented in order to show the applicability and adaptability of the generic model in practical decision-making process, and the perspectives of future study are also discussed.     

Application of modeling and simulation tools in costs and pollution monitoring

This paper presents the development and application of process modeling and simulation tools to aid in the monitoring and measuring of pollution from industry, and investigate a plant's overall performance. A case study of a generic reduction plant is investigated, taking into account the underlying principles that determine the amount of fluoride emissions released from the plant's processes. The simulation study includes the investigation of the gas cleaning system within the plant, such as the system's operating relationships between the scrubbing efficiency, wear of the scrubber filter bags, maintenance costs and its response to the change of scrubbing circulation. Two sets of simulation runs are performed to seek a balance for the plant's overall system performance, taking into account environmental issues (fluoride emissions) and cost. The final simulation result demonstrates that cost savings can be achieved when the plant operates in a cleaner manner.     

Risk-based economic decision analysis of remediation options at a PCE-contaminated site

Remediation methods for contaminated sites cover a wide range of technical solutions with different remedial efficiencies and costs. Additionally, they may vary in their secondary impacts on the environment i.e. the potential impacts generated due to emissions and resource use caused by the remediation activities. More attention is increasingly being given to these secondary environmental impacts when evaluating remediation options. This paper presents a methodology for an integrated economic decision analysis which combines assessments of remediation costs, health risk costs and potential environmental costs. The health risks costs are associated with the residual contamination left at the site and its migration to groundwater used for drinking water. A probabilistic exposure model using first- and second-order reliability methods (FORM/SORM) is used to estimate the contaminant concentrations at a downstream groundwater well. Potential environmental impacts on the local, regional and global scales due to the site remediation activities are evaluated using life cycle assessments (LCA). The potential impacts on health and environment are converted to monetary units using a simplified cost model.A case study based upon the developed methodology is presented in which the following remediation scenarios are analyzed and compared: (a) no action, (b) excavation and off-site treatment of soil, (c) soil vapor extraction and (d) thermally enhanced soil vapor extraction by electrical heating of the soil. Ultimately, the developed methodology facilitates societal cost estimations of remediation scenarios which can be used for internal ranking of the analyzed options. Despite the inherent uncertainties of placing a value on health and environmental impacts, the presented methodology is believed to be valuable in supporting decisions on remedial interventions.     

A Knowledge-Based Systems Approach to Design of Spatial Decision Support Systems for Environmental Management

/ This paper describes a framework for designing spatial decision support systems for environmental management using a knowledge-based systems approach. An architecture for knowledge-based spatial decision supportsystems (KBSDSS) is presented that integrates knowledge-based systems with geographical information systems (GIS) and other problem-solving techniques. A method based on spatial influence diagrams is developed for representation of environmental problems. The spatial influence diagram provides an interface through which knowledge-based systems techniques can be applied to build capabilities for problem formulation, automated design, and execution of a solution process. In addition to the flexibility and developmental advantages of knowledge-based systems, the KBSDSS incorporates expert knowledge to provide assistance for structuring spatial influence diagrams and executing a solution process that automatically integrates the GIS, data base, knowledge base, and different types of models. The framework is illustrated with a system, known as the Islay Land Use Decision Support System (ILUDSS), designed to assist planners in strategic planning of land use for the development of the island of Islay, off the west coast of Scotland.KEY WORDS: Geographical information systems; Spatial decision support systems; Knowledge-based systems; Spatial influence diagrams; Environmental management     

Two-stage vertex analysis method for planning electric power systems with greenhouse gas abatement consideration

This study presents a two-stage vertex analysis (TSVA) method for the planning of electric power systems (EPS) under uncertainty. TSVA has advantages in comparison to other optimization techniques. Firstly, TSVA can incorporate greenhouse gas (GHG) abatement policies directly into its optimization process, and, secondly, it can readily integrate inherent system uncertainties expressed as fuzzy sets and probability distributions directly into its modeling formulation and solution procedure. The TSVA method is applied to a case study of planning EPS and it is demonstrated how the TSVA efficiently identify optimal electricity-generation schemes that could help to minimize system cost under different GHG-abatement considerations. Different combinative considerations on the uncertain inputs lead to varied system costs and GHG emissions. Results reveal that the total electricity supply will rise up along with the time period due to the increasing demand and, at the same time, more non-fossil fuels should be used to satisfy the increasing requirement for GHG mitigation. Moreover, uncertainties in connection with complexities in terms of information quality (e.g., capacity, efficiency, and demand) result in changed electricity-generation patterns, GHG-abatement amounts, as well as system costs. Minimax regret (MMR) analysis technique is employed to identify desired alternative that reflects compromises between system cost and system-failure risk.     

Decision making under uncertainty in case of soil remediation

Decisions on soil remediation are one of the most difficult management issues of municipal and state agencies. The assessment of contamination is uncertain, the costs of remediation are high, and the impacts on the environment are multiple. This paper presents a general, transparent, and consistent method for decision making among the remediation alternatives. Soil washing, phytoremediation, and no remediation are exemplarily considered. Multi-criteria utility functions including (a) the cost of remediation (b) the impact on human health and agricultural productivity, and (c) the economic gain after remediation are constructed using probability density functions representing contamination for all site coordinates. Herewith, the probability of different types of (i) correct decisions such as a hit or a true rejection and (ii) erroneous decisions such as a false alarm or miss are examined. The decision theoretic model is applied to a case study on heavy metal contaminated soil. This case study reveals the non-linear structure of multi-criteria-decision making. The case study shows that the geostatistical uncertainties of the log-normal distributed soil contamination must be taken into account: When uncertainties are not considered and the utilities are assessed according to the estimated value for a spatial unit, only few (N=26) spatial units result where the utility score of the alternative soil washing are higher than the utility score to the no remediation alternative. However, when taking into account geostatistical uncertainties of the log-normal soil distribution this number is about ten times greater (N=237). Furthermore, the use of 'maximizing expected utility' as decision rule is critical in that it may lead to a high probability of misses.     

Feasibility of geographic information systems approach for natural resource management

Geographic information systems (GIS) technology is altering the work environment for planning and decision-making tasks. This article is an account of a resource application that make use of the GIS technology. It provides some cost estimates and reasons for the fairly slow development toward an integrated resource data base for environmental planning and management. It tries to identify some of the constraints of such an integrated data-base approach toward environmental assessment.     

Use of contract models to improve environmental outcomes in transport infrastructure construction

The type of contract model may have a significant influence on achieving project objectives, including environmental and climate change goals. This research investigates non-standard contract models impacting greenhouse gas emissions (GHG) in transport infrastructure construction in Australia. The research is based on the analysis of two case studies: an Early Contractor Involvement (ECI) contract and a Design and Construct (D&C) contract with GHG reduction requirements embedded in the contractor selection. Main findings support the use of ECIs for better integrating decisions made during the planning phase with the construction activities, and improve environmental outcomes while achieving financial and time savings.     

Price-based vs. quantity-based environmental regulation under Knightian uncertainty: an info-gap robust satisficing perspective

Conventional wisdom among environmental economists is that the relative slopes of the marginal social benefit and marginal social cost functions determine whether a price-based or quantity-based environmental regulation leads to higher expected social welfare. We revisit the choice between price-based vs. quantity-based environmental regulation under Knightian uncertainty; that is, when uncertainty cannot be modeled with known moments of probability distributions. Under these circumstances, the policy objective cannot be to maximize the expected net benefits of emissions control. Instead, we evaluate an emissions tax and an aggregate abatement standard in terms of maximizing the range of uncertainty under which the welfare loss from error in the estimates of the marginal benefits and costs of emissions control can be limited. The main result of our work is that the same criterion involving the relative slopes of the marginal benefit and cost functions determines whether price-based or quantity-based control is more robust to unstructured uncertainty. Hence, not only does the relative slopes criterion lead to the policy that maximizes the expected net benefits of control under structured uncertainty, it also leads to the policy that maximizes robustness to unstructured uncertainty.     

Natural environmental impact assessment: A rational approach

A method is presented which combines environmental indices and estimates of inputs from various land uses to aid in environmental impact assessments. Unweighted pair/group cluster analyses are used to obtain relationships between easily observable environmental indices, such as vegetation types, soils, and geology, based on their mutual recurrence. These relationships are shown by using an ordination technique which shows the nature of complex impacts on a natural system. Results are used to develop anenvironmental effects sequence diagram based on known scientific and engineering principles and observed natural relationships. The diagram may be used in conjunction with land use data to estimate the possible magnitude of impacts on the pre-existing system which may result from such land use. Several examples are developed which quantify inputs from various land uses and which compare them with environmental inputs including point source and non-point source liquid and atmospheric emmissions, land modifications, and resource consumption. Known average values are used and a separate comparison is made in describing the vast differences between the project phases of construction versus longterm operation. A hypothetical environmental impact assessment is given for a small residential development in Chambers County, Texas, U.S. of A.     

A fresh look at the benefits and costs of the US acid rain program

The US Acid Rain Program (Title IV of the 1990 Clean Air Act Amendments) has achieved substantial reductions in emissions of sulfur dioxide (SO2) and nitrogen oxides (NOx) from power plants in the United States. We compare new estimates of the benefits and costs of Title IV to those made in 1990. Important changes in our understanding of and ability to quantify the benefits of Title IV have occurred. Benefits to human health now take a much higher profile because the contribution of SO2 and NOx emissions to the formation of fine particulate (PM2.5) is substantial, and evidence of the harmful human health effects of PM2.5 has emerged in the last 15 years. New estimates of the health benefits of PM2.5 reductions are the largest category of quantified health and environmental benefits and total over 100 billion US dollars annually for 2010 when the program is expected to be fully implemented. Although important uncertainties exist in any specific estimate of the benefits, even if the estimates were calculated using more limiting assumptions and interpretations of the literature they would still substantially exceed the costs. Estimates of annualized costs for 2010 are about 3 billion US dollars, which is less than half of what was estimated in 1990. Research since 1990 also suggests that environmental problems associated with acid deposition and nitrogen deposition are more challenging to resolve than originally thought and will require larger reductions in emissions to reverse. The greater than expected benefits to human health, the greater vulnerability of natural resources and ecosystems, and the lower than expected costs all point to the conclusion that further reductions in SO2 and NOx emissions from power plants beyond those currently required by Title IV are warranted.     

Bidirectional visibility

The percentage of the cross-sectional area of two objects (e.g., vehicles, hikers, or animals) that can be seen from each of their locations in a forested area is generally not the same. There is a directionality to the visibility between them. This is due to the relative positions and sizes of the vegetation and other view-blocking features between the objects. An analytical technique has been developed to help understand bidirectional visibility. Its use entails the construction of a visibility diagram containing the basic visibility information between observers in a given setting. An example is presented showing the use of the visibility diagram to determine visibility between two moving observers in a forested environment. The diagram is also used to determine the differences in the percentage each observer has of the other's visible cross-sectional area (bidirectional visibility). A discussion of the application of the technique in the planning or development of new facilities, as well as in forest and wildlife management, is provided.     

A multi-period optimization model for energy planning with CO2 emission consideration

A novel deterministic multi-period mixed-integer linear programming (MILP) model for the power generation planning of electric systems is described and evaluated in this paper. The model is developed with the objective of determining the optimal mix of energy supply sources and pollutant mitigation options that meet a specified electricity demand and CO₂ emission targets at minimum cost. Several time-dependent parameters are included in the model formulation; they include forecasted energy demand, fuel price variability, construction lead time, conservation initiatives, and increase in fixed operational and maintenance costs over time. The developed model is applied to two case studies. The objective of the case studies is to examine the economical, structural, and environmental effects that would result if the electricity sector was required to reduce its CO₂ emissions to a specified limit.     

USE OF FIRST-ORDER UNCERTAINTY ANALYSIS TO OPTIMIZE SUCCESSFUL STREAM WATER QUALITY SIMULATION1

ABSTRACT: A first-order uncertainty technique is developed to quantify the relationship between field data collection and a modeling exercise involving both calibration and subsequent verification. A simple statistic (LTOTAL) is used to quantify the total likelihood (probability) of successfully calibrating and verifying the model. Results from the first-order technique are compared with those from a traditional Monte Carlo simulation approach using a simple Streeter-Phelps dissolved oxygen model. The largest single difference is caused by the filtering or removal of unrealistic outcomes within the Monte Carlo framework. The amount of bias inherent in the first-order approach is also a function of the magnitude of input variability and sampling location. The minimum bias of the first-order technique is approximately 20 percent for a case involving relatively large uncertainties. However the bias is well behaved (consistent) so as to allow for correct decision making regarding the relative efficacy of various sampling strategies. The utility of the first-order technique is demonstrated by linking data collection costs with modeling performance. For a simple and inexpensive project, a wise and informed selection resulted in an LTOTAL value of 86 percent, while an uninformed selection could result in an LTOTAL value of only 55 percent.     

Environmental Assessment Framework for Policy Applications: Life Cycle Assessment,External Costs and Multi-criteria Analysis

The paper presents a framework for the analysis of external costs of environmental burdens, namely an impact pathway analysis, often coupled with the inventory stage of life cycle assessment (LCA). The ground rule is: quantify as much as possible in terms of burdens (pollutant emissions, etc.), impacts, and their monetary equivalent, then use multi-criteria analysis (MCA) for any remaining impacts that are considered to be too uncertain or defy quantification through to monetization. Although MCA could be used directly on estimates of burdens or impacts, monetary valuation provides a mechanism for consistent weighting of impacts categories based on assessment of public preference. Further advantages of extending LCA through detailed impact assessment combined with monetary valuation are that it greatly simplifies MCA by combining a large number of different environmental impact categories, thereby avoiding an unmanageably large number of criteria, and also facilitates cost benefit analysis (CBA). The risks are noted of inappropriate use of the tools or interpretation/use of the results, and recommendations are made for improved practice. These points are illustrated with examples. The key messages are: (1) that policies should be targeted correctly to give a clear signal which source of a burden should be reduced by how much; (2) that analysts should take into account the needs of policy makers and the link between the analysis and possible policy applications; and (3) that current LCA practice gives limited guidance in both areas, largely through a lack of consideration of the relative and absolute importance of different types of impact. However, this is precisely the strength of external costs analysis, particularly when used with MCA.     

Economic and Environmental Analysis of Retrofitting a Large Office Building with Energy-Efficient Lighting Systems

An evaluation of the economic and environmental costs and benefits that would result if the Zorinsky Federal Building, located in Omaha, Nebraska, USA, converted its current lighting system to a more energy-efficient system (i.e., joined the EPA's Green Lights Program) was conducted. Lighting accounts for 20–25 percent of all electricity sold in the United States. Costs considered in the study included the cost of retrofitting the building's existing lighting system and the cost of disposal of the current lamps and ballast fixtures. Benefits included a reduction of electric utility costs and a reduction of emissions of SO₂, NO _x , CO₂, and CO from electric utility power plants. Environmental and health issues for air pollutant emissions were also addressed. The results showed that significant reductions in utility bills as well as reductions in air emissions would result from a major building converting to a more energy efficient lighting system. The results showed that conversion of this large building would reduce SO₂ emissions by 14.6 tons/yr and NO _x emissions by 6.3 tons/yr. In addition, the conversion would reduce annual energy costs by approximately $114,000.     

Applying Multi-attribute Utility Theory to Decision Making in Environmental Planning: A Case Study of the Electric Utility in Korea

This paper applies the multi-attribute utility theory (MAUT) to obtaining value judgments concerning the significance of environmental impacts to achieve integration of environmental concerns at an early stage of planning, using the electric utility of Korea as a specific case study. An environmental multi-attribute index is constructed as a multi-attribute utility function, based on value judgments provided by a group of experts related to electric utility and a decision maker from Korea Electric Power Corporation (KEPCO). The societal values are derived from examining trade-offs between environmentalindex and money. The implications of the results for KEPCO are also discussed. We found that the work and results can provide valuable insights and decision opportunities for major decision making in environmental planning facing KEPCO.     

Optimization of regional economic and environmental systems under fuzzy and random uncertainties

Environmental problems associated with socio-economic development have been growing concerns faced by many regional and/or national authorities. However, effective planning may encounter difficulties since uncertainties existing in a number of impact factors and pollution-related processes are often not well acknowledged and reflected. This study advances an interval-fuzzy chance-constrained programming (IFCP) method for planning regional economic and environmental systems, where uncertainties presented as intervals, fuzzy sets and probability distributions can be tackled. The developed method is applied to a real-world case for economic and environmental planning in the New Binhai District in the Municipality of Tianjin, China. Two scenarios based on multiple environmental constraints are examined. The results can help identify desired alternatives for planning regional development strategies, where compromised schemes are provided under an integrated consideration of economic efficiency and environmental protection under multiple uncertainties.     

River Basin Export Reduction Optimization Support Tool; a tool to screen options for reducing nutrient loads while minimizing cost

Excess loading of nitrogen and phosphorus to river networks causes environmental harm, but reducing loads from large river basins is difficult and expensive. We developed a new tool, the River Basin Export Reduction Optimization Support Tool (RBEROST) to identify the least-cost combinations of management practices that will reduce nutrient loading to target levels in downstream and mid-network waterbodies. We demonstrate the utility of the tool in a case study in the Upper Connecticut River Basin in New England, USA. The total project cost of optimized lowest-cost plans ranged from $18.0 million to $41.0 million per year over 15 years depending on user specifications. Plans include both point source and non-point source management practices, and most costs are associated with urban stormwater practices. Adding a 2% margin of safety to loading targets improved the estimated probability of success from 37.5% to 99%. The large spatial scale of RBEROST, and the consideration of both point and non-point source contributions of nutrients, make it well suited as an initial screening tool in watershed planning.     

CO2 emissions reduction from the power system in India

The power system in India accounts for nearly one-third of CO₂ emissions of the country as a whole. A comparison of some of the technical options to reduce CO₂ emissions is presented in this paper. A linear programming framework is used to simulate the integrated optimal operation of the three regional grids, and it is shown that such operations lead to lower fuel costs and to lower CO₂ emissions. The same framework is used to see how a rise in thermal efficiency translates into a CO₂ emissions reduction. Reduced fuel requirements also lead to reductions in other pollutants ie SO₂, NO_x and fly ash. The reductions in CO₂ emissions and other pollutants are at far lower cost in the case of integrated optimal operations as compared to reductions due to gas fuelled generation or thermal efficiency improvements. However, thermal efficiency improvements under optimal integrated operations result in much higher reductions in operating costs, coal consumption and total emissions of all pollutants.