Representing uncertainty in climate change scenarios: a Monte-Carlo approach

Climate change impact assessment is subject to a range of uncertainties due to both incomplete and unknowable knowledge. This paper presents an approach to quantifying some of these uncertainties within a probabilistic framework. A hierarchical impact model is developed that addresses uncertainty about future greenhouse gas emissions, the climate sensitivity, and limitations and unpredictability in general circulation models. The hierarchical model is used in Bayesian Monte-Carlo simulations to define posterior probability distributions for changes in seasonal-mean temperature and precipitation over the United Kingdom that are conditional on prior distributions for the model parameters. The application of this approach to an impact model is demonstrated using a hydrological example. This revised version was published online in July 2006 with corrections to the Cover Date.     

Agent-based integrated assessment modelling: the example of climate change

Current approaches to deal with the socio-economic implications of climate change rely heavily on economic models that compare costs and benefits of different measures. We show that the theoretical foundations underpinning current approaches to economic modelling of climate change are inappropriate for the type of questions that are being asked. We argue therefore that another tradition of modelling, social simulation, is more appropriate in dealing with the complex environmental problems we face today.     

growing pains: a conceptual framework for considering integrated assessments

Policy concerns related to the environment have grown in the past decadesfrom relatively local and well-defined problems to increasingly complex andglobal issues. With this has grown the need to develop the capacity tointegrate, reconcile, organize, and communicate knowledge across scientificdisciplines, as well as to make this knowledge available and useful for policy-makers. One response to this has been the growing field ofIntegrated Assessment (IA). Our goal in this paper is to reflect on the purpose and valueof IA in principle. We propose a conceptual framework within whichindividual IA studies, and the practice of IA as a whole, can be placed andevaluated. The framework addresses both the integrative nature of IAs andtheir policy usefulness, including a self-awareness of their role and capabilities. We illustrate several stages in the evolution of integrated assessments: fromlinear to more complex chains of analysis, from non-adaptive to perfectly-adaptive to realistically-adaptive agents, from simplistic to sophisticated to pluralistic consideration of alternative underlying development paths, from strictly quantitative to quantitative and qualitative analyses, from science-driven to policy-driven, and from analyses that dictate to users to those that involvethose users in the actual assessment process. By so doing, we argue for botha richer form and process of IA. Ultimately, we feel that it may also benecessary to reconsider the framing of the questions that IAs have been askedto address, perhaps leading to the consideration of the use of other forms of mandated science.     

Canadian insights: The challenges of an integrated environmental assessment framework

The paper draws results from a review of literature to examine the strengths and weaknesses of the integrated environmental assessment framework in Canada with respect to the inclusion of health impact assessment. Insights include the legislative nature, rigid structure and priority for the natural environment that may restrict progress and the pool of government agencies that need to be convinced of the benefits of health impact assessment that may provide a strong structure for compliance in the long term.     

An integrated assessment modeling framework for assessing primary and secondary impacts from carbon dioxide stabilization scenarios

As the nations of the world negotiate future controls on greenhouse gas emissions, a critical environmental policy issue becomes understanding the multiple environmental consequences of these controls. Here we describe an integrated assessment model for quantifying multiple environmental impacts of large-scale environmental initiatives and apply this model to climate change mitigation. Our analysis shows that reductions in global warming will be accompanied by reductions in ozone depletion, acid rain and mercury emissions, and desulfurization waste generation. We also conclude that the largest collateral benefits from reducing global climate change may be in the developing world. This result is critical since it is the developing nations who ultimately control the long-term success of any climate stabilization strategy. This revised version was published online in July 2006 with corrections to the Cover Date.     

INASUD project findings on integrated assessment of climate policies

This communication summarizes the main findings of INASUD, an European-wide research project on integrated assessment of climate policies. The project aimed at improving the framing of climate policy analysis through the parallel use of various existing integrated assessment models. It provides a comprehensive examination of the link between uncertainty regarding damages and inertia in economic systems. Results show that the Kyoto targets and timing are consistent with the precautionary principle but offers little insurance for longer-term climate protection. Flexibility mechanisms offer potentials for cooperation with developing countries, and are necessary to tap the environmental and economic benefits of joint carbon and sulfur emissions abatement.     

Coupling climate and economic models in a cost-benefit framework: A convex optimisation approach

In this paper, we present a general method, based on a convex optimisation technique, that facilitates the coupling of climate and economic models in a cost-benefit framework. As a demonstration of the method, we couple an economic growth model à la Ramsey adapted from DICE-99 with an efficient intermediate complexity climate model, C-GOLDSTEIN, which has highly simplified physics, but fully 3-D ocean dynamics. As in DICE-99, we assume that an economic cost is associated with global temperature change: this change is obtained from the climate model, which is driven by the GHG concentrations computed from the economic growth path. The work extends a previous paper in which these models were coupled in cost-effectiveness mode. Here we consider the more intricate cost-benefit coupling in which the climate impact is not fixed a priori. We implement the coupled model using an oracle-based optimisation technique. Each model is contained in an oracle, which supplies model output and information on its sensitivity to a master program. The algorithm Proximal-ACCPM guarantees the convergence of the procedure under sufficient convexity assumptions. Our results demonstrate the possibility of a consistent, cost-benefit, climate-damage optimisation analysis with a 3-D climate model.     

Modeling economy-wide climate change impacts on Egypt: A case for an integrated approach

This study looks at the role of biophysical sectors and world markets on an integrated economic assessment of climate change impacts on Egypt. Using the outcome from Global Circulation Models (GCMs) and a global model of world food trade (the Basic Linked System; BLS) — changes in crop yields; crop water demands; water and land resource availability; and world market prices were applied to a dynamic, computable general equilibrium model of Egypt (the Standard National Model of the BLS). Modeling results consistently showed that the net effect of climate change on the macro indicator of per capita GDP was not great — regardless of the level of integration. This outcome was only realized through autonomous economic adjustments which implied significant socio-economic and structural change. Including or excluding certain biophysical sectors and world markets influenced the development path and the nature of the autonomous adjustments. The importance of a particular biophysical sector or of world markets was also dependent upon the specific climate change scenario.     

On the representation of impact in integrated assessment models of climate change

The paper provides an overview of attempts to represent climate change impact in over twenty integrated assessment models (IAMs) of climate change. Focusing on policy optimization IAMs, the paper critically compares modeling solutions, discusses alternatives and outlines important areas for improvement. Perhaps the most crucial area of improvement concerns the dynamic representation of impact, where more credible functional forms need to be developed to express time‐dependent damage as a function of changing socio‐economic circumstances, vulnerability, degree of adaptation, and the speed as well as the absolute level of climate change.     

Environmental water demand assessment under climate change conditions

Measures taken to cope with the possible effects of climate change on water resources management are key for the successful adaptation to such change. This work assesses the environmental water demand of the Karkheh river in the reach comprising Karkheh dam to the Hoor-al-Azim wetland, Iran, under climate change during the period 2010–2059. The assessment of the environmental demand applies (1) representative concentration pathways (RCPs) and (2) downscaling methods. The first phase of this work projects temperature and rainfall in the period 2010–2059 under three RCPs and with two downscaling methods. Thus, six climatic scenarios are generated. The results showed that temperature and rainfall average would increase in the range of 1.7–5.2 and 1.9–9.2%, respectively. Subsequently, flows corresponding to the six different climatic scenarios are simulated with the unit hydrographs and component flows from rainfall, evaporation, and stream flow data (IHACRES) rainfall-runoff model and are input to the Karkheh reservoir. The simulation results indicated increases of 0.9–7.7% in the average flow under the six simulation scenarios during the period of analysis. The second phase of this paper’s methodology determines the monthly minimum environmental water demands of the Karkheh river associated with the six simulation scenarios using a hydrological method. The determined environmental demands are compared with historical ones. The results show that the temporal variation of monthly environmental demand would change under climate change conditions. Furthermore, some climatic scenarios project environmental water demand larger than and some of them project less than the baseline one.     

Participatory integrated assessment of adaptation to climate change in Alpine tourism and mountain agriculture

Winter tourism and mountain agriculture are the most important economic sectors in a major part of the Swiss Alps. Both are highly sensitive to changing climatic conditions. In the framework of the CLEAR project, results from climate impact research in the field of tourism and agricultural production were used to investigate the perception of climatic change by stakeholders and to assess possible adaptations. We used a participatory integrated assessment (PIA) to involve the knowledge, values and experiences of the various social actors in tourism and agriculture (e.g., skiers, tourism managers, farmers) in the research process. Whereas climate change may have various severe direct impacts on the tourism industry, depending on the region, agricultural production may generally benefit from changed climatic conditions. But because of the dependence of farmers on “off-farm” income, the loss due to declining winter tourism in specific areas may cause more important indirect effects. However, the two sectors may adapt actively by choosing from a variety of strategies, and the loss of income from the tourism industry may support the re-evaluation of the various functions agriculture plays in mountain regions, beyond the production of food. The study demonstrates the suitability of the PIA approach to elucidate the interactions between different stakeholders and their perception of the climate change phenomena. A similar participatory approach could be a useful tool to transfer research results and expert knowledge to the political process addressing adaptations to climate change. This revised version was published online in July 2006 with corrections to the Cover Date.     

An integrated assessment model for cross-country pipelines

The cross-country petroleum pipelines are environmentally sensitive because they traverse through varied terrain covering crop fields, forests, rivers, populated areas, desert, hills and offshore. Any malfunction of these pipelines may cause devastating effect on the environment. Hence, the pipeline operators plan and design pipelines projects with sufficient consideration of environment and social aspects along with the technological alternatives. Traditionally, in project appraisal, optimum technical alternative is selected using financial analysis. Impact assessments (IA) are then carried out to justify the selection and subsequent statutory approval. However, the IAs often suggest alternative sites and/or alternate technology and implementation methodology, resulting in revision of entire technical and financial analysis. This study addresses the above issues by developing an integrated framework for project feasibility analysis with the application of analytic hierarchy process (AHP), a multiple attribute decision-making technique. The model considers technical analysis (TA), socioeconomic IA (SEIA) and environmental IA (EIA) in an integrated framework to select the best project from a few alternative feasible projects. Subsequent financial analysis then justifies the selection. The entire methodology has been explained here through a case application on cross-country petroleum pipeline project in India.     

Rural poverty driven soil degradation under climate change: the sensitivity of the disposition towards the Sahel Syndrome with respect to climate

Starting from the basic assumption of the syndrome concept that essentially all of the present problematic civilization–nature interactions on the global scale can be subdivided into a limited number of typical patterns, the analysis of the response of these patterns (syndromes) to climate change can make a major contribution to climate impact research, surmounting the difficulties of more common sectoral ceteris paribus impact studies with respect to their systemic integration. In this paper we investigate in particular the influence of climate on the regional proneness or disposition towards one of the most important syndromes with respect to famines and malnutrition, the Sahel Syndrome. It describes the closely interlinked natural and socioeconomic aspects of rural poverty driven degradation of soil and vegetation on marginal sites. Two strategies of global climate impact assessment on a spatial 0.5°×0.5° grid were pursued: (a) As a measure for the climate sensitivity of the regional proneness, the absolute value of the gradient of the disposition with respect to the global field of 3} 12 monthy normals of temperature, irradiation and precipitation is calculated. (b) The disposition was evaluated for two different climate forecasts under doubled atmospheric CO₂ concentration. For both strategies two new quantitative global models were incorporated in a fuzzy-logic-based algorithm for determining the disposition towards the Sahel Syndrome: a neural-net-based model for plant productivity and a waterbalance model which calculates surface runoff considering vertical and lateral fluxes, both driven by the set of 36 monthly climatological normals and designed to allow very fast global numerical evaluation.Calculation (b) shows that the change in disposition towards the Sahel Syndrome crucially depends on the chosen climate forecast, indicating that the disagreement of climate forecasts is propagated to the impact assessment of the investigated socio-economic pattern. On the other hand the regions with a significant increase in disposition in at least one of the climate scenario-based model runs form a subset of the regions which are indicated by the local climate sensitivity study (a) as highly sensitive – illustrating that the gradient measure applied here provides a resonable way to calculate an upper limit or worst case of negative climate impact. This method is particularly valuable in the case of uncertain climate predictions as, e.g., for the change in precipitation patterns.     

Scientist–stakeholder collaboration in integrated assessment of climate change: lessons from a case study of Northwest Canada

Research on the climate change issue has generally focused on uncertainties in climate projections and calculation of mitigation costs. Most integrated assessment (IA) efforts have been directed at the mitigation component. The problem of climate change, however, is really about the potential effects on ecosystems, resources, and societies that depend on them. As illustrated by experiences from the Mackenzie Basin Impact Study, a case study from Northwest Canada, these effects will be unique to each region and country. Many of these will be indirect, including region specific thresholds, vulnerabilities and adaptations which may not be included in sectoral analyses. Science can define some of the “What if” aspects of climate change, but the regional “So what” and “What should be done” questions are largely unanswered and subject to intense debate in various political fora. IA needs to recognize the multiobjective and multistakeholder aspects of vulnerabilities, risks, and potential responses to climate change. IA could provide a more holistic analysis of the regional impacts dimension of climate change by including both modeling and non‐modeling approaches, and incorporating institutional and stakeholder issues that do not readily lend themselves to economic analyses.     

An approach to deal with uncertainty in energy and environmental planning: the MARKAL case

This paper presents a new concept to include uncertainty management in energy and environmental planning models developed in algebraic modeling languages. SETSTOCH is a tool for linking algebraic modeling languages with specialized stochastic programming solvers. Its main role is to retrieve from the modeling language a dynamically ordered core model (baseline scenario) that is sent automatically to the stochastic solver. The case presented herein concerns such a study realized with the IEAMARKAL model used by many research teams around the world.     

Small drinking water systems under spatiotemporal water quality variability: a risk-based performance benchmarking framework

Traditional approaches for benchmarking drinking water systems are binary, based solely on the compliance and/or non-compliance of one or more water quality performance indicators against defined regulatory guidelines/standards. The consequence of water quality failure is dependent on location within a water supply system as well as time of the year (i.e., season) with varying levels of water consumption. Conventional approaches used for water quality comparison purposes fail to incorporate spatiotemporal variability and degrees of compliance and/or non-compliance. This can lead to misleading or inaccurate performance assessment data used in the performance benchmarking process. In this research, a hierarchical risk-based water quality performance benchmarking framework is proposed to evaluate small drinking water systems (SDWSs) through cross-comparison amongst similar systems. The proposed framework (R _WQI framework) is designed to quantify consequence associated with seasonal and location-specific water quality issues in a given drinking water supply system to facilitate more efficient decision-making for SDWSs striving for continuous performance improvement. Fuzzy rule-based modelling is used to address imprecision associated with measuring performance based on singular water quality guidelines/standards and the uncertainties present in SDWS operations and monitoring. This proposed R _WQI framework has been demonstrated using data collected from 16 SDWSs in Newfoundland and Labrador and Quebec, Canada, and compared to the Canadian Council of Ministers of the Environment WQI, a traditional, guidelines/standard-based approach. The study found that the R _WQI framework provides an in-depth state of water quality and benchmarks SDWSs more rationally based on the frequency of occurrence and consequence of failure events.     

An ecological framework for resource management in British Columbia

British Columbia's landmass encompasses a complex diversity of ecosystems as a result of its diverse physiography, geology and climate. Resource planners and managers, depending upon their management objectives, use ecological information at different scales, from the very broad regional level to the local or site-specific level. The Ecoregion Classification and the Biogeoclimatic Ecosystem Classification systems provide the means for resource managers and others in British Columbia concerned with the environment to understand, manage, and communicate about the diverse ecosystems of the province.This paper outlines this multi-level regional ecological classification and describes how it is being applied by resource managers from various resource agencies and organizations responsible for forest, wildlife and habitat management in British Columbia.     

Modeling distribution changes of vegetation in China under future climate change

Climatic change will result in great changes in vegetation. In this paper, a biogeographical model, the BIOME1, was used to predict potential vegetation distribution in China under climate change. Firstly, the BIOME1 was validated according to the climate–vegetation relationships in China. Kappa statistics showed that the validated BIOME1 was able to capture the geographical patterns of vegetation more accurately. Then, the validated BIOME1 was used to predict the distribution of vegetation of China under two climatic scenarios produced by a Regional Circulation Model, RegCM2/CN. The simulation results showed obvious northward shifts of the boreal, temperate deciduous and evergreen and tropical forests, a large expansion of tropical dry forest/savanna and reduction of tundra on the Tibetan Plateau. Three vulnerable regions sensitive to climate changes are pointed out, i.e., Northern China, the Tibetan Plateau and Southwestern China (mainly Hengduan Mountains in Yunnan Province and west of Sichuan Province). In recent decades, China has experienced dramatic industrialization and population growth, which exert strong pressure on the environment of China. The consequences of climate changes warrant more attention for maintaining a sustainable environment for China.     

Health,safety and environmental unit performance assessment model under uncertainty (case study: steel industry)

Performance assessment is a critical objective of management systems. As a result of the non-deterministic and qualitative nature of performance indicators, assessments are likely to be influenced by evaluators’ personal judgments. Furthermore, in developing countries, performance assessments by the Health, Safety and Environment (HSE) department are based solely on the number of accidents. A questionnaire is used to conduct the study in one of the largest steel production companies in Iran. With respect to health, safety, and environment, the results revealed that control of disease, fire hazards, and air pollution are of paramount importance, with coefficients of 0.057, 0.062, and 0.054, respectively. Furthermore, health and environment indicators were found to be the most common causes of poor performance. Finally, it was shown that HSE management systems can affect the majority of performance safety indicators in the short run, whereas health and environment indicators require longer periods of time. The objective of this study is to present an HSE-MS unit performance assessment model in steel industries. Moreover, we seek to answer the following question: what are the factors that affect HSE unit system in the steel industry? Also, for each factor, the extent of impact on the performance of the HSE management system in the organization is determined.