Land Cover Changes as a Result of Environmental Restrictions on Nitrate Leaching in Dairy Farming

Nitrate leaching forms an important environmental problem because it causes pollution of groundwater and surface water, and adds to already problematic eutrophication. This study analyses the impact of reductions in nitrate leaching on land cover decisions of dairy farms, of which the activities make an important contribution to nitrate leaching. As the level of nitrate leaching depends on groundwater depth as well as on the supply of nitrogen, spatial variation in groundwater levels will cause a spatial variation in land cover under restrictions on nitrate leaching. A non-linear partial optimisation model for the economic and ecological aspects of the problem were used to show how land cover and dairy farms' financial balances change when nitrate losses are reduced. The model is spatially explicit, and describes nitrate leakage and yields of maize and grass as a function of groundwater depth, including the effects of various grazing systems. The model analyses the decisions of a risk neutral agent who minimises costs under the following constraints: (i) production, feed requirements and mass balances for fodder; (ii) constraints for nitrate leaching. Economic costs are attributed to increased costs of fodder and processing of manure when nitrate restrictions are tightened. An important result of the study is the variation in compliance costs and land cover for maize and grass production brought about by spatial variation in groundwater depth. While the effects are negligible for some shallow groundwater classes, it is extremely difficult in other classes – if not impossible – to obtain the EU standard of maximum admissible losses of 34 kg N ha^–1 at low costs. The study shows an important reduction in land cover by maize.     

Spending Environmental Expenditure More Effectively: A Case Study from Brisbane, Australia

Growing urbanisation causes pressures on many environmental assets such as groundwater systems, waterways, atmosphere, ecosystems and others. To manage and mitigate the negative effects of these pressures, environmental programs are typically launched, which comprise of eligible projects in different affected locations. The implementation of individual projects has a cost. However, due to budget constraints, most frequently not all suggested projects can be implemented which makes necessary to choose a subset. In this paper, we use a cost utility approach and a subsequent combinatorial optimisation based on metaheuristics to determine a project portfolio which returns a maximum aggregated utility while keeping the budget constraint. To ensure that the mutual exclusiveness of projects at one particular site is guaranteed, we further developed the employed metaheuristics. We apply this approach within a waterway health program in a river catchment in Brisbane, Australia, and compare its results to a commonly used selection process that does not involve combinatorial optimisation. We find that the use of combinatorial optimisation leads to a considerable improvement of the selection process and can help to more effectively allocate environmental expenditure.     

Health effects and social costs of particulate pollution – a case study for Oslo

This study analyses health damages from particulate pollution and the corresponding social costs. The analyses, which are based on transferring dose–response functions to Norway, is made within an integrated approach, where the economic impacts of the health damages are handled separately from the non‐economic welfare effects. We find that the social costs of health damages in Oslo are significant, and that the non‐economic welfare effects clearly dominate the cost figure.     

A multi-scale metrics approach to forest fragmentation for Strategic Environmental Impact Assessment

Forests are becoming severely fragmented as a result of land development. South Korea has responded to changing community concerns about environmental issues. The nation has developed and is extending a broad range of tools for use in environmental management. Although legally mandated environmental compliance requirements in South Korea have been implemented to predict and evaluate the impacts of land-development projects, these legal instruments are often insufficient to assess the subsequent impact of development on the surrounding forests. It is especially difficult to examine impacts on multiple (e.g., regional and local) scales in detail. Forest configuration and size, including forest fragmentation by land development, are considered on a regional scale. Moreover, forest structure and composition, including biodiversity, are considered on a local scale in the Environmental Impact Assessment process. Recently, the government amended the Environmental Impact Assessment Act, including the SEA, EIA, and small-scale EIA, to require an integrated approach. Therefore, the purpose of this study was to establish an impact assessment system that minimizes the impacts of land development using an approach that is integrated across multiple scales.This study focused on forest fragmentation due to residential development and road construction sites in selected Congestion Restraint Zones (CRZs) in the Greater Seoul Area of South Korea. Based on a review of multiple-scale impacts, this paper integrates models that assess the impacts of land development on forest ecosystems. The applicability of the integrated model for assessing impacts on forest ecosystems through the SEIA process is considered.On a regional scale, it is possible to evaluate the location and size of a land-development project by considering aspects of forest fragmentation, such as the stability of the forest structure and the degree of fragmentation. On a local scale, land-development projects should consider the distances at which impacts occur in the vicinity of the forest ecosystem, and these considerations should include the impacts on forest vegetation and bird species. Impacts can be mitigated by considering the distances at which these influences occur. In particular, this paper presents an integrated environmental impact assessment system to be applied in the SEIA process. The integrated assessment system permits the assessment of the cumulative impacts of land development on multiple scales.     

Assessing disproportionate costs to achieve good ecological status of water bodies in a Mediterranean river basin

Water management is becoming increasingly important as the demand for water grows, diversifies, and includes more complex environmental concerns. The Water Framework Directive (WFD) seeks to achieve a good ecological status for all European Community water bodies by 2015. To achieve this objective, economic consideration of water management must be given to all decision-making processes. Exemption (time or level of stringency) from the objectives of the EU Directive can be justified by proving that the cost of implementing measures is disproportionate to the benefits. This paper addresses the issue of disproportionate costs through a cost-benefit analysis (CBA). To predict the costs, the function costs method is used. The quantification of environmental benefits is more complex, because they are not determined by the market. As an alternative to stated preference methods, we use the distance function approach to estimate the environmental benefits of improving water quality. We then apply this methodological approach to a Mediterranean River Basin in Spain. The results show that the achievement of good status could not be rejected based on the criterion of disproportionate costs in this river basin. This paper illustrates that CBA is a useful tool to inform policy and decision making. Furthermore, it is shown that economics, particularly the valuation of environmental benefits, plays a crucial role in fulfilling the environmental objectives of the WFD.     

Regulation of pesticide discharge into surface and groundwater under uncertainty: A model for environmental risk‐profitability tradeoffs and policy selection

The presence of contaminants in environmental media as well as the desire to maintain a high level of economic activity has led to an important and difficult decision‐making problem for both public policy decision makers and the general public. In one sense, all of the interested parties are likely to be concerned about the potential health risks posed by the presence of contaminants in environmental media and the need to design/implement policies for their mitigation and/or removal. At the same time, however, there also appear to be concerns about the cost of these policies. These costs could be measured in terms of the potential losses in economic activity that are likely to occur when a policy is adopted. The policy can be selected from a range of alternatives, with the choice being driven in part by the stakeholders represented in the policy decision problem. In this case, two general goals might be considered: minimizing environmental risk and minimizing the economic impact of the policy considered. These two objectives are likely to be viewed as conflicting goals, and the nature of the tradeoffs between them must be taken into account in the policy selection process. This paper presents the development of a zero–one weighted goal programming model that can be used to select a preferred policy that minimizes surface and groundwater contamination as well as the economic costs of environmental policy selection. A safety rule model is developed first and then extended to the zero–one weighted goal programming formulation. The stochastic aspects of these structures are emphasized throughout. The paper also addresses a number of issues related to implementation of the model.     

A Robust Optimization Model for an Invasive Species Management Problem

Invasive species pose a significant threat to global biodiversity. Managing invasive species often involves modeling the species’ spread pattern, estimating control costs and damage costs due to the invasion, designing control efforts, and accounting for uncertainties in model parameters. Dealing with uncertainty is arguably the most important part of the process, since biological, environmental, and economic factors can cause parameter values to vary greatly. Managers need decision tools that are robust to such limited or variable information. Here, we present a robust spatial optimization model to select treatment sites in a way that maximally reduces the size of an invasive population, given a constraint on financial resources. We develop an integer programming model that includes population dynamics and management costs over space and time. The model incorporates uncertainty in the available budget and the invasive spread rate as sets of discrete scenarios to determine a robust, cost-effective management plan in a novel way.     

Cost-Benefit Analysis and the environment: The time horizon is of the essence

Cost-Benefit Analysis is a key tool for evaluating welfare gains or losses from an investment. It is now well established that environmental impacts are crucial to consider the full welfare implications of a project. Debate has focussed on approaches to improve the valuation of environmental impacts, and controversy in the discounting of future impacts to present values. The issue of the time horizon of analysis is frequently overlooked. The framing of the time horizon has major implications, as environmental costs and benefits often accrue in the long-term. The technical aspects of setting the time horizon are reviewed, along with updates to practice guidance, noting the longer time horizons now becoming typical. It is demonstrated that the time horizon can have a considerable impact on results, even more substantial than the discount rate. While uncertainty is noted as a technical challenge to longer-term analysis, the use of scenarios and sensitivity testing are noted as an appropriate response. For projects with long-term environmental effects, such as those related to air pollution, climate change and ecosystem damages, it is recommended to use timescales of 100+ years for economic evaluation of the impact. Failing to fully capture these long-term welfare gains and losses will distort analysis with a bias towards those projects that are more carbon-intensive, or environmentally damaging. Such a bias would undermine not only the evaluation, but welfare and sustainable development in general.     

Evaluation of a real-time monitoring system for river quality — a trade-off between risk attitudes,costs, and uncertainty

Uncertainty is definitely one of the key topics in environmental assessment and management. Typically, attempts to reduce uncertainty are subject to expenses. But how to compare and trade-off expenses and the reduced uncertainty? They only seldom allow the use of a single unit. Instead, the whole analysis and decision procedure is very subjective. This paper presents one approach to handle such problems, namely the combined use of Bayesian influence diagrams, and probabilistic risk attitude analysis. The approach was used in the evaluation of three alternatives for a real time river water quality forecasting system. A trade-off analysis of risk attitudes, costs and uncertainty indicated the levels of socioeconomic utility required for investments in the respective systems, and accordingly illuminated the impact of the uncertainties involved on inference and decision-making with various risk attitudes and discount rates.     

An evaluation of a risk-based environmental regulation in Brazil: Limitations to risk management of hazardous installations

The environmental regulation of hazardous projects with risk-based decision-making processes can lead to a deficient management of human exposure to technological hazards. Such an approach for regulation is criticized for simplifying the complexity of decisions involving the economic, social, and environmental aspects of the installation and operation of hazardous facilities in urban areas. Results of a Brazilian case study indicate that oil and gas transmission pipelines may represent a threat to diverse communities if the relationship between such linear projects and human populations is overlooked by regulatory bodies. Results also corroborate known challenges to the implementation of EIA processes and outline limitations to an effective environmental and risk management. Two preliminary topics are discussed to strengthen similar regulatory practices. Firstly, an effective integration between social impact assessment and risk assessment in EIA processes to have a more comprehensive understanding of the social fabric. Secondly, the advancement of traditional management practices for hazardous installations to pursue a strong transition from assessment and evaluation to management and control and to promote an effective interaction between land-use planning and environmental regulation.     

Indifference curves as a tool for environment impact assessment

Use of indifference curves, defined as functionality between development index and pollution load to evaluate environmental impact, is proposed. Existing Battelle environmental evaluation methodology is subjective in its approach. The use of indifference curves lends a more objective approach to environment assessment methodology. The extent of environmental damage we are prepared to accept, for a development, can be explained by Willingness to Pay and Willingness to Accept approach. The application of proposed approach has been demonstrated taking an example of Power plant set up in forest area. The curves clearly show that cost of EMP considering mitigation of ecological damage is higher than the EMP mitigating impacts of air and water pollution only. The example stresses the need for willingness to accept along with willingness to pay.     

A risk-based screening approach for prioritizing contaminants and exposure pathways at Superfund sites

Contamination at Superfund sites can involve mixtures of chemicals and radionuclides in a variety of environmental media. Determining priorities for evaluation and remediation of various contaminants is an important part of the initial phases of any site investigation. An effective screening analysis at the beginning of the project can help by identifying both those situations in need of immediate remedial attention and those which require further sampling and evaluation. The screening approach discussed here is made up of two sets of calculations designed to provide upper- and lower-bound estimates of health risk to individuals likely to receive the highest exposures. This approach allows rapid identification of contaminants which pose a negligible risk and can be assigned a low priority for remedial attention or which pose a substantial risk and should be given the highest priority for appropriate remediation efforts. Contaminants designated as neither high- nor low-priority should be investigated in more detail prior to making decisions regarding the need for or method of remediation. The utility of this approach has already been demonstrated in the evaluation of contamination in the Clinch and Tennessee River systems originating from historical operations of atomic weapons and energy research facilities near Oak Ridge, Tennessee.     

Assessing the social cost of housing projects on the built environment: Analysis and monetization of the adverse impacts incurred on the neighbouring communities

Construction projects generate serious environmental adverse impacts on the adjacent residents. All those harmful consequences and damages that third parties or the community sustain due to the implementation of construction processes are called social costs. Although, the presence of social costs is widely mentioned in the literature, in the projects' initial cost estimation practices, the social costs are not estimated and included. Whereas since these costs are not compensated, problems can be emerged by the community. It is a truism that the majority of the models proposed to quantify the social costs have been concentrated on construction, repair, and maintenance of the infrastructure projects namely; utilities, roads, and highways. On the other hand, up to the present, a limited number of attempts has been made to quantify residential housing construction associated social costs. Thus, this research aims to expand and/or contribute to the existing body of knowledge via estimating how much social cost society surrounding residential housing construction sites are subjected to. For this purpose, a social cost estimation model is developed to assist industry professionals on how to estimate social costs in residential construction projects. The social cost estimation model is developed to provide guidance for phase by phase monetization of the residential construction associated social costs. In this paper, the model proposed for social cost estimation is validated via a case study in Turkey.     

Optimized contaminated land investigation at minimum overall cost to achieve fitness-for-purpose

A methodology for optimized contaminated land investigation (OCLI) is described that balances the uncertainty of measurements against the cost of taking the measurements and the financial losses that may arise from misclassification of the land. Uncertainty from the sources of both field sampling and chemical analysis is estimated using existing techniques, based on the taking of duplicated samples. The actual costs of sampling and analysis and the expected costs that could arise from either 'false positive' or 'false negative' classification of areas of land were estimated. A loss function was constructed that calculates the expectation of financial loss that will arise for a given uncertainty of measurement. The function shows a clear minimum value of cost at an optimal value of uncertainty. Application of this OCLI technique to two case studies demonstrated this minimum value. Below the optimum value of uncertainty, the costs increased due to higher measurement costs. Above the optimum, the costs increased due to increasing risk of factors such as unnecessary remediation or potential litigation over undetected contamination. Many areas for further development of OCLI are identified, but the technique is demonstrated as a useful new approach to judging fitness-for-purpose of such measurements.     

IFTCIP: An Integrated Optimization Model for Environmental Management under Uncertainty

In this study, an interval-fuzzy two-stage chance-constrained integer programming (IFTCIP) method is developed for supporting environmental management under uncertainty. The IFTCIP improves upon the existing interval, fuzzy, and two-stage programming approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly incorporated within a general mixed integer linear programming framework. It has advantages in uncertainty reflection, policy investigation, risk assessment, and capacity-expansion analysis in comparison to the other optimization methods. Moreover, it can help examine the risk of violating system constraints and the associated consequences. The developed method is applied to the planning for facility expansion and waste-flow allocation within a municipal solid waste management system. Violations of capacity constraints are allowed under a range of significance levels, which reflects tradeoffs between the system cost and the constraint-violation risk. The results indicate that reasonable solutions for both binary and continuous variables have been generated under different risk levels. They are useful for generating desired decision alternatives with minimized system cost and constraint-violation risk under various environmental, economic, and system-reliability conditions. Generally, willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a lower risk will run into a higher system cost.     

The value of long-term environmental monitoring programs: an Ohio River case study

As a subset of environmental monitoring, fish sampling programs have been an important part of assessing the potential impacts of water withdrawals and effluent discharges on fish populations for many years. New environmental regulations often require that adverse environmental impacts to fish populations be minimized. Without long-term field data, population evaluations may incorrectly indicate adverse impacts where none exist or no impact where one is likely to occur. Several electric utility companies have funded the Ohio River Ecological Research Program, which has been in existence for over 40 years and consists of fish, habitat, and water quality studies at multiple power plant sites on the mainstem Ohio River. Sampling includes seasonal night-time electrofishing and daytime beach seining at three upstream and three downstream locations near each plant. The long-term nature of the program allows for the establishment of aquatic community indices to support evaluations of technology performance, the collaborative development of compliance metrics, and the assessment of fish population trends. Studies have concluded that the Ohio River fish community has improved in response to better water quality and that power plant fish entrainment and impingement and thermal discharges have had little or no measureable impact. Through collaboration and the use of long-term data, $6.3 million in monitoring costs have been saved during recent fish impingement studies. The ability to access a multiyear fish abundance database, with its associated data on age, growth, and fecundity, improves the quality of such evaluations and reduces the need for extensive field sampling at individual locations.     

Water quality assessment programs in Australia deciding what to measure,and how and where to use bioindicators

Effective water quality assessment programs require the formulation of common objectives between managers who are making decisions and scientists who are obtaining the information on which those decisions are to be made. The data collected must be apropriate for use in the decision making process. After the objectives have been formulated a number of testable hypotheses can be proposed and evaluated in terms of what information is required for decision making.From a management perspective it is important to know if an impact occurs and what management strategy to adopt to reduce or eliminate the impact. When bioaccumulators are used to indicate environmental quality the organisms proposed need to be fully evaluated before being used. Communities, which are often used to assess levels of impact, have the capacity to assimilate pollutants and they will function under pollutant stress. Thus managers need to make value judgements about when a community structure or function has shifted from acceptable to adverse. Bioassays in which the effects of pollutants on growth, biochemistry and behaviour are measured, give an indication of the sub-lethal effects of a pollutant, but it is difficult to set meaningful levels that are not to be exceeded for use by managers.Difficulties in using chemical and biological data mainly arise from a lack of appreciation of environmental heterogeneity. The data obtained must meet the needs for statistically testing hypotheses. Before programs can be designed to meet statistical needs the potential sources of variability must be considered. Once the minimum differences that are seen as important have been determined, the number of replicates needed can be calculated. Data verification is also needed, as if the validity of data is questioned, so will any decisions that have been made based on those data. Finally programs should be designed to minimize the sampling effort/cost to meet the objectives.     

Environmental Information, Asymmetric Information, and Financial Markets: A Game-Theoretic Approach

This paper examines the problem of asymmetric information in financial markets due to a lack of essential environmental information. The literature indicates that asymmetric information generates various problems for the actors of financial markets such as incomplete information for investment decisions and lending procedures, misallocation of financial market funds, the underestimating of stock price securities, and poor environmental risk management choices. To this end, this paper develops a game-theoretic approach to examine both the persistent nature of asymmetric information caused by the absence of accurate environmental information and to indicate how a well-organized, trustworthy, internationally agreed auditing accounting certification scheme could play a critical role in limiting the magnitude of this problem.     

Designing a graph-based approach to landscape ecological assessment of linear infrastructures

The development of major linear infrastructures contributes to landscape fragmentation and impacts natural habitats and biodiversity in various ways. To anticipate and minimize such impacts, landscape planning needs to be capable of effective strategic environmental assessment (SEA) and of supporting environmental impact assessment (EIA) decisions. To this end, species distribution models (SDMs) are an effective way of making predictive maps of the presence of a given species. In this paper, we propose to combine SDMs and graph-based representation of landscape networks to integrate the potential long-distance effect of infrastructures on species distribution. A diachronic approach, comparing distribution before and after the linear infrastructure is constructed, leads to the design of a species distribution assessment (SDA), taking into account population isolation. The SDA makes it possible (1) to estimate the local variation in probability of presence and (2) to characterize the impact of the infrastructure in terms of global variation in presence and of distance of disturbance. The method is illustrated by assessing the impact of the construction of a high-speed railway line on the distribution of several virtual species in Franche-Comté (France). The study shows the capacity of the SDA to characterize the impact of a linear infrastructure either as a research concern or as a spatial planning challenge. SDAs could be helpful in deciding among several scenarios for linear infrastructure routes or for the location of mitigation measures.     

Health risk assessment for toxic emissions from a manufacturing facility

This paper presents the risk associated with the release of toxic chemicals from a manufacturing facility, following the State of California's approach to risk assessment. The facility emits five toxic substances from eight stacks. The building downwash is considered during dispersion calculations. The zone of impact, identified using a risk criteria (i.e. excess cancer risk of 10 in a million), is located in the southeast quandrant from the plant. The size of the impact area is 3.3 km². The cancer and non-cancer effects are considered for chromium (VI), benzene, formaldehyde, gasoline vapors, methylene chloride, and selenium using the California Air Pollution Control Officers Association Guidelines. No significant non-cancer effects are found due to the emissions. The maximum calculated risk is 1.197×10^-5 and is an extremely conservative value. Analysis shows that the use of realistic assumptions for exposure duration and unit risk factors during the risk calculations could reduce the zone of impact to 0 km².