Value of information analysis: the state of application

The value of information (VoI) is a decision analytic method for quantifying the potential benefit of additional information in the face of uncertainty. This paper reviews the prevalence of VoI applications reported in the peer-reviewed literature from the years 1990–2011. We categorize papers’ applications across the types of uncertainties considered, modeling choices, and contexts of social importance (such as health care and environmental science). We obtain and analyze statistics on the range of applications and identify trends and patterns in them, and conclude with an interpretation of what these mean for researchers and practitioners as they pursue new efforts. Key results include a substantial increase over the last 20 years in published papers utilizing VoI, particularly in the medical field. Nineteen trends in VoI applications from the period of 1990–2000 to 2001–2011 were found to be at least weakly significant. Beyond simple trends, some characteristics of VoI usage depend on the area of application, and in some cases, certain sets of characteristics tend to be found together.     

Opportunity cost based analysis of corporate eco-efficiency: A methodology and its application to the CO2-efficiency of German companies

In this paper, we propose the return-to-cost-ratio (RCR) as an alternative approach to the analysis of operational eco-efficiency of companies based on the notion of opportunity costs. RCR helps to overcome two fundamental deficits of existing approaches to eco-efficiency. (1) It translates eco-efficiency into managerial terms by applying the well-established notion of opportunity costs to eco-efficiency analysis. (2) RCR allows to identify and quantify the drivers behind changes in corporate eco-efficiency. RCR is applied to the analysis of the CO₂-efficiency of German companies in order to illustrate its usefulness for a detailed analysis of changes in corporate eco-efficiency as well as for the development of effective environmental strategies.     

A distance-based uncertainty analysis approach to multi-criteria decision analysis for water resource decision making

The choice among alternative water supply sources is generally based on the fundamental objective of maximising the ratio of benefits to costs. There is, however, a need to consider sustainability, the environment and social implications in regional water resources planning, in addition to economics. In order to achieve this, multi-criteria decision analysis (MCDA) techniques can be used. Various sources of uncertainty exist in the application of MCDA methods, including the selection of the MCDA method, elicitation of criteria weights and assignment of criteria performance values. The focus of this paper is on the uncertainty in the criteria weights. Sensitivity analysis can be used to analyse the effects of uncertainties associated with the criteria weights. Two existing sensitivity methods are described in this paper and a new distance-based approach is proposed which overcomes limitations of these methods. The benefits of the proposed approach are the concurrent alteration of the criteria weights, the applicability of the method to a range of MCDA techniques and the identification of the most critical criteria weights. The existing and proposed methods are applied to three case studies and the results indicate that simultaneous consideration of the uncertainty in the criteria weights should be an integral part of the decision making process.     

The development and application of a multilevel decision analysis model for the remediation of contaminated groundwater under uncertainty

A study was initiated which combined elements of stochastic hydrology, risk assessment, simulation modeling, cost analysis and decision making to define the optimum remediation choice(s) for a Superfund site in the southern United States. The effort focused upon the premise that groundwater remediation is inherently complex due to uncertainties in the geological matrix as well as in contaminant concentrations at points of compliance and/or exposure. The technical analyst should supply the decision maker with estimates of these uncertainties as well as the cost penalties required to reduce them to manageable levels. Monte Carlo transport modeling was employed to define the probability of contaminant excursions from the site, while geostatistical simulation identified a joint plume configuration and its attendant probability. Bayesian modeling was used to define the worth of additional data. These individual components were combined within a Decision Model to identify optimum remediation configurations for a given levels of risk tolerance which could be supplied by the decision maker or affected community. Sensitivity analyses were conducted to define ranges over which the decision would not be affected by variation in the respective decision parameter.     

Value of information analysis for adequate monitoring of carbon dioxide storage in geological reservoirs under uncertainty

As monitoring is essential for the proper management of geological storage of carbon dioxide (CO₂), the ability to value information from monitoring is indispensable to adequately design a monitoring program. It is necessary to judge whether the expected improvement in management is worth the cost of monitoring. The value of information (VOI) is closely related to the possible increase in expected utility gained by gathering the information, the concept of which can be applied to such judgement. Although VOI analysis has been extensively studied in the context of decision analysis, its application to the management of carbon dioxide capture and storage (CCS) operations is rare. This paper introduces and discusses the methodology of VOI analyses in the context of monitoring CO₂ storage. A motivating problem with discrete probabilities is used to illustrate the concept of VOI. It is demonstrated that information is not always of value; for information to be worthwhile, monitoring under uncertainty must satisfy certain conditions. This concept is then extended to continuous probability distributions. The effects of prior uncertainty and information reliability on the VOI are examined. It is shown that an excessive improvement in information accuracy yields little value and that the optimal level of reliability can be inferred. VOI analyses provide quantitative insights into the value of information-gathering activities and therefore can be an objective means to adequately design and impartially justify a monitoring program.     

A practical real option methodology for the evaluation of farm-in/out joint venture agreements in mineral exploration

Although the “real option valuation” (ROV) methodology offers extremely valuable insights in optimising investment decisions in the face of uncertainty, its practical acceptance in the mining industry has until recently been slow because of its perceived computational complexity. Recent conceptual advances in the use of binomial lattices and software developments in the areas of decision trees and dynamic programming, have significantly simplified ROV analysis and made it of practical application in day-to-day financial evaluations and decisions involving uncertainty. This paper provides general background on the ROV methodology and an example of how a typical farm-in/out agreement, as a preliminary to the establishment of a joint venture (JV), can be valued as a series of sequential and compound real options. For illustrative and quality assurance purposes, a simple farm-in/out agreement is valued from the point of view of the party acquiring equity in the project (the farm-inee) using two distinct methods, i.e. (a) a binomial lattice and (b) a decision tree in combination with binomial stochastic processes, in both cases neutralising risk using the user-friendly “risk-neutral probability”. The fact that exactly the same ROV is obtained by both methods provides confidence in the modified decision tree approach, which opens up the capacity to value the more complex sequential/compound real options inherent in real-life farm-in/out agreements. The model is then modified to incorporate a number of realistic contractual conditions often encountered in typical exploration and mining farm-in/out deals. The paper demonstrates how the increased complexity of the model can be relatively easily addressed using a decision tree with dynamic programming capability.     

Alternative approaches to dealing with respondent uncertainty in contingent valuation: a comparative analysis

Several strategies have been proposed to deal with response uncertainty in contingent valuation. One approach, often applied to address issues of hypothetical bias, recodes and/or reweights responses according to stated levels of certainty but so far few analyses compare alternative recoding and reweighting strategies. We explore the choice among alternative strategies that exploit a numerical certainty scale obtained from a follow-up to the payment question in a valuation survey about a whale conservation program. Two novel variations of previously followed approaches perform best on our dataset in terms of the efficiency of estimates. The first one uses an exponential transformation of the numerical certainty scale as a weight in the willingness to pay regression. The other one is based on constructing a continuous willingness to pay variable with the highly certain "yes" and "no" original responses to the payment question as extreme values and with mid-point values that correspond to the original "don't know" responses. We find, though, that the effect of using different treatment strategies on mean willingness to pay is rarely statistically significant and we fail to detect a consistent effect on the efficiency of the estimation regardless of the strategy applied.     

Stockpiles of obsolete pesticides and cleanup priorities: A methodology and application for Tunisia

Obsolete pesticides have accumulated in almost every developing country or economy in transition over the past several decades. Concerned about the risks these chemicals pose to nearby residents, public health and environmental authorities are eager to reduce health threats by removing and decontaminating stockpile sites. However, there are many sites, cleanup can be costly, and public resources are scarce, so decision makers need to set priorities. Under these conditions, it seems sensible to develop a methodology for prioritizing sites and treating them sequentially, as budgetary resources permit.This paper presents a new methodology that develops a cleanup priority index for 1915 metric tons of obsolete pesticide formulations at 197 stockpile sites in Tunisia. The approach integrates information on populations at risk, their proximity to stockpiles, and the relative toxic hazards of the stockpiles. What emerges from the Tunisia results is a strategy for sequentially addressing all 197 sites to rapidly reduce potential health damage in a cost-effective way.     

A methodology to estimate the denitrifying capacity of a riparian wetland

Numerous studies have shown that riparian wetlands can play an important role in reducing nitrate concentrations before the ground water discharges into streams. Denitrification has been identified as an important process for this removal. Several approaches have been proposed to predict the denitrifying removal capacity of a riparian wetland, but no widely used tool exists to precisely quantify this capacity at the landscape scale. We propose such a methodology based on modeling the spatial variation of soil-water interactions in the entire riparian wetland. Mean values of denitrification enzyme activity (DEA) within three soil-denitrifying classes were 604, 212, and 24 ng N g(-1) h(-1) for Classes 3, 2, and 1, respectively. The study area, having a ground surface of about 15000 m2, was underlain by an aquifer with a calculated volume of 60000 m3, less than 10000 m3 of which corresponded to active denitrifying horizons (Classes 2 and 3). By volume, approximately 30% of Class 3 and 70% of Class 2 were interacting with ground water. The denitrifying removal capacity of our wetland was calculated to be about 1.8 kg N m(-2) yr(-1). The calculated denitrifying capacity of our site was less than expected. This is due to the fact that not all ground water interacts with the horizons having the highest denitrifying capacity. Thus, we show that whatever the system is, specific local pedological and hydrogeological conditions and their interactions are paramount in controlling the denitrification process.     

A comparative analysis of methods to represent uncertainty in estimating the cost of constructing wastewater treatment plants

Prediction of construction cost of wastewater treatment facilities could be influential for the economic feasibility of various levels of water pollution control programs. However, construction cost estimation is difficult to precisely evaluate in an uncertain environment and measured quantities are always burdened with different types of cost structures. Therefore, an understanding of the previous development of wastewater treatment plants and of the related construction cost structures of those facilities becomes essential for dealing with an effective regional water pollution control program. But deviations between the observed values and the estimated values are supposed to be due to measurement errors only in the conventional regression models. The inherent uncertainties of the underlying cost structure, where the human estimation is influential, are rarely explored. This paper is designed to recast a well-known problem of construction cost estimation for both domestic and industrial wastewater treatment plants via a comparative framework. Comparisons were made for three technologies of regression analyses, including the conventional least squares regression method, the fuzzy linear regression method, and the newly derived fuzzy goal regression method. The case study, incorporating a complete database with 48 domestic wastewater treatment plants and 29 industrial wastewater treatment plants being collected in Taiwan, implements such a cost estimation procedure in an uncertain environment. Given that the fuzzy structure in regression estimation may account for the inherent human complexity in cost estimation, the fuzzy goal regression method does exhibit more robust results in terms of some criteria. Moderate economy of scale exists in constructing both the domestic and industrial wastewater treatment plants. Findings indicate that the optimal size of a domestic wastewater treatment plant is approximately equivalent to 15,000 m3/day (CMD) and higher in Taiwan. Yet the optimal size of an industrial wastewater treatment plant could fall in between 6000 CMD and 20,000 CMD.     

Process design for the environment: A multi-objective framework under uncertainty

Designing chemical processes for the environment requires consideration of several indexes of environmental impact including ozone depletion, global warming potentials, human and aquatic toxicity, photochemical oxidation, and acid rain potentials. Current methodologies, such as the generalized waste reduction algorithm (WAR), provide a first step towards evaluating these impacts. However, to address the issues of accuracy and the relative weights of these impact indexes, one must consider the problem of uncertainties. Environmental impacts must also be weighted and balanced against other concerns, such as their cost and long-term sustainability. These multiple, often conflicting, goals pose a challenging and complex optimization problem, requiring multi-objective optimization under uncertainty. This paper will address the problem of quantifying and analyzing the various objectives involved in process design for the environment. Towards this goal, we proposed a novel multi-objective optimization framework under uncertainty. This framework is based on new and efficient algorithms for multi-objective optimization and for uncertainty analysis. This approach finds a set of potentially optimal designs where trade-offs can be explicitly identified, unlike cost-benefit analysis, which deals with multiple objectives by identifying a single fundamental objective and then converting all the other objectives into this single currency. A benchmark process for hydrodealkylation (HDA) of toluene to produce benzene modeled in the ASPEN simulator is used to illustrate the usefulness of the approach in finding environmentally friendly and cost-effective designs under uncertainty.     

Quantifying sources of climate uncertainty to inform risk analysis for climate change decision-making

Quantitative estimates of future climate change and its various impacts are often based on complex climate models which incorporate a number of physical processes. As these models continue to become more sophisticated, it is commonly assumed that the latest generation of climate models will provide us with better estimates of climate change. Here, we quantify the uncertainty in future climate change projections using two multi-model ensembles of climate model simulations and divide it into different components: internal, scenario and model. The contributions of these sources of uncertainty changes as a function of variable, temporal and spatial scale and especially lead time in the future. In the new models, uncertainty intervals for each of the components have increased. For temperature, importance of scenario uncertainty is the largest over low latitudes and increases nonlinearly after the mid-century. It has a small importance for precipitation simulations on all time scales, which hampers estimating the effect which any mitigation efforts might have. In line with current state-of-the-art adaptation approaches, we argue that despite these uncertainties climate models can provide useful information to support adaptation decision-making. Moreover, adaptation decisions should not be postponed in the hope that future improved scientific understanding will result in more accurate predictions of future climate change. Such simulations might not become available. On the contrary, while planning adaptation initiatives, a rational framework for decision-making under uncertainty should be employed. We suggest that there is an urgent need for continued development and use of improved risk analysis methods for climate change adaptation.     

A new method for predicting vegetation distributions using decision tree analysis in a geographic information system

Decision tree analysis was used to predict the distribution of forest communities in an area on the south coast of New South Wales, Australia. The analysis was carried out using a geographical information system environmental data base of those topographic and geological variables thought to influence the distribution of vegetation and derived from cartographic sources. The resulting maps of forest communities are of a resolution sufficient to delimit individual forest stands and contain much ecological information.     

The use of guide to the expression of uncertainty in measurement for uncertainty management in National Greenhouse Gas Inventories

Research basis for annual greenhouse gases (GHG) emissions assessment is national and branch statistics data. Quality and confidence of greenhouse gases inventory through assessment methodologies, preparation procedures and processing of data is confirm. Request at National Greenhouse Gases Inventory which contain assessment and analyses uncertainty elements on Intergovernmental Panel on Climate Change-GPG 2000 and IPCC 2006 are determine. Main approaches for uncertainty assessment in environmental and metrological guides are considered. The algorithm of expressing uncertainty and scheme for estimating uncertainty according to GPG 2000 and IPCC 2006 are proposed. The use approaches GUM 1993 for uncertainty assessment for greenhouse gases inventory are proposed.     

Sediment phosphorus extractants for phosphorus-31 nuclear magnetic resonance analysis: a quantitative evaluation

The influence of pre-extractant, extractant, and post-extractant on total extracted amounts of P and organic P compound groups measured with 31P nuclear magnetic resonance (31P-NMR) in lacustrine sediment was examined. The main extractants investigated were sodium hydroxide (NaOH) and sodium hydroxide ethylenediaminetetraacetic acid (NaOH-EDTA) with bicarbonate buffered dithionite (BD) or EDTA as pre-extractants. Post extractions were conducted using either NaOH or NaOH-EDTA, depending on the main extractant. Results showed that the most efficient combination of extractants for total P yield was NaOH with EDTA as pre-extractant, yielding almost 50% more than the second best procedure. The P compound groups varying the most between the different extraction procedures were polyphosphates and pyrophosphates. NaOH with BD as pre-extractant was the most efficient combination for these compound groups.     

The value of site-specific information and the environment: technology adoption and pesticide use under uncertainty

Remote sensing technology offers an opportunity to significantly increase the amount of site-specific information about field characteristics such as pest populations. Coupled with variable rate application technologies, this added information has the potential to provide environmental benefits through reduced pesticide applications. However, producers face a complicated adoption decision because output prices and crop yields are uncertain. A model is developed to examine the potential value of remote sensing information to pesticide applications in an option-value framework under uncertainty. Simulations suggest that remote sensing information could decrease pesticide use, but uncertainty and irreversibility are likely to limit technological adoption by farmers. Potential cost-share subsidies are discussed.     

A methodology for evaluating environmental planning systems: A case study of Canada

Sustainable environmental management is contingent on having an effective environmental planning system. A new methodology for designing and evaluating environmental planning systems is described and applied to a case study evaluation of the Canadian environmental planning process. The methodology is based on eight international best practice principles for environmental planning and 45 indicators. The research illustrates the benefits of the evaluation methodology in identifying how to improve environmental planning systems to achieve desired results. The methodology is applicable to a wide variety of jurisdictions.     

Towards a national reference center for environmental information in The Netherlands: A review

For improvement of the accessibility and use of environmental information a prototype national reference center (CIMI) was constructed in the Netherlands in 1986. Target groups were identified on the basis of an analysis of the demand side. They were questioned about their needs in the field of environmental information. On the basis of these experiences an automated integrated system has been built that is composed of subsystems for reference to expertise in organizations (specialisms), literature, research, and databases of site-specific data. This system is also equipped with a thesaurus. The system has been tested and examined in several ways. The outcome of these independent tests and investigations confirm the usefulness of this center for information transfer. The reference center can be helpful in providing overviews on and structuring of environmental information in the Netherlands. The results of the activities have been presented in several ways and were described extensively in a number of reports.     

Land application of phosphorus-laden sludge: a feasibility analysis

An investigation was conducted to examine aerobic digestion of the phosphorus-laden sludge produced at the Regina Wastewater Treatment Plant and feasibility of land use of this sludge combined with the dewatered anaerobically digested primary sludge from this plant. Experimental studies showed that aerobic digestion can be employed for the stabilization of the chemical sludge. Results of the feasibility analysis showed that mixing the two digested sludges met the heavy metal criteria set by various guidelines for agricultural use, presented the advantage of an increased concentration of nutrients and a decreased concentration of heavy metals, and a longer useful life of the agricultural site compared to using dewatered anaerobically digested primary sludge alone. Land application of the mixed digested sludges would be a more appropriate method of sludge disposal compared to the present practice of landfilling the dewatered sludge and lagooning the chemical sludge.