Some argue that a declining discount rate, which attaches increasing weight to the welfare of future generations, better reflects empirical data on individual preferences and is in agreement with various theoretical results Dasgupta ; Heal ; Newell and Pizer ; Pearce et al. Although full hyperbolic discounting has not been supported by policy makers, there is a move toward declining discount rates driven by the dynamic uncertainty of future events Pearce et al.
Declining discount rates imply, for example, discounting benefits and costs that occur over the next 30 years at one rate, followed by a lower rate for benefits and costs that occur over the following 30 years and so on. As an alternative to explicit discounting, some efforts instead use time horizons for certain terms, producing the odd result where consequences i. Others argue that the various components common to co-benefits modeling should be discounted at different rates Brouwer et al.
Discount rates and their associated assumptions should be explicitly addressed in co-benefits research. For a particular intervention with both climate and health effects, rates must be specified for the costs of intervention U. Where available, locally estimated discount rates that reflect the specific values of affected populations should ideally be used.
Examining the implications of declining rates HM Treasury would also be worthwhile. Evaluating mitigation options using decision analysis. Accounting for potential health impacts of mitigation strategies is important, but many impacts unrelated to health exist, and policy makers require that alternative mitigation strategies be evaluated on the basis of many criteria simultaneously Konidari and Mavrakis ; Swart et al.
Valuation methods capable of considering trade-offs among multiple cost and benefit criteria under uncertainty are thus more likely to be policy relevant.
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To that end, the quantitative information on health criteria must be considered alongside nonhealth criteria, including economic growth, environmental sustainability, political acceptability, cost and financing considerations, expediency, and equity issues. Each of these can in turn be divided into detailed subcriteria, resulting in a deep hierarchical structure that defies single-criterion analytical approaches.
For example, a cost and financing criterion could have subcriteria that include implementation costs, health services costs from changes in disease burden, opportunity costs of capital or land, and so forth. The performance of a mitigation strategy is unlikely to be positive or negative across all such criteria, and comparing short-term performance on certain criteria to long-term performance can raise important ethical questions—such as how should policy makers treat a renewable energy strategy that lowers short-term economic growth and is thus temporarily detrimental to health because of reduced employment , but increases net health over the long-term from reduced pollutant emissions?
Other ethical questions are raised by the fact that multiple criteria can at times represent competing stakeholder interests, such as a policy substituting active transport for single-occupancy vehicle use that reduces health costs while also decreasing revenues in the automotive sector. The importance of consistent summary measures. Decision makers manage considerable complexity in part by determining which criteria are most relevant.
At the same time, having a few summary or principal measures that are used consistently to assess different strategies greatly improves comparability.
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For example, a common measure for evaluating and comparing health co-benefits across alternative mitigation strategies and across countries is the health burden DALYs avoided, expressed per unit population size and per MtCO 2 saved Smith and Haigler Another useful and widely used measure is the net cost per ton of GHG emissions reduced. Many of the relevant outcomes, including health impacts, can, in principle, be converted into a monetary cost Creutzig and He These costs can then be added to, or netted out, from the direct costs of the mitigation measures, giving a net cost figure per ton reduced.
In calculating the measure, analysts face the problems described above e. Multicriteria decision analysis MCDA. Several decision analytical methods can be used to compare and evaluate alternative mitigation options in terms of their health and nonhealth impacts. These include traditional cost—benefit and cost-effectiveness methods used for environmental interventions Haller et al. Because the impacts of mitigation are often multidimensional, more complex measures—and analytical methods—are needed for evaluating trade-offs.
MCDA approaches have been used for this purpose in some policy areas, and their application to climate change policies is gaining momentum Bell et al. There are unresolved issues in the application of MCDA methods to valuation of mitigation strategies. Traditional MCDA assumes that all criteria are evaluated at the same point in time.
Economics of global warming
When comparing mitigation strategies where health is one of the criteria, assigning a relative weight to the health co-benefits criterion can be difficult because the immediate reduction in hazardous exposures does not often produce immediate health benefits Jarrett et al. This time course can be very different from those of the impacts of other criteria. In addition, because uncertainty increases into the future, issues surrounding attitudes toward risk in the presence of uncertainty and time preference become intertwined, complicating discount rate choices Traeger Strategies to extend the model domain and policy utility.
Future directions for modeling co-benefits include enhancing policy relevance, addressing policy resistance, and characterizing implementation including diffusions of new behaviors and technical shifts. Literature in recent years with respect to policy relevance highlights the importance of iteration between scientists and policy makers in developing usable science Dilling and Lemos RISA works with diverse user communities to advance contextual understanding of adaptation policy and management decisions; to develop knowledge on impacts, vulnerabilities, and potential response options; and to facilitate decision support tool development NOAA Such an approach also may be particularly well suited to facilitating mitigation policy decisions.
Systems dynamics methods Sterman alone or in concert with other approaches such as discrete event simulation Brailsford et al. Many health co-benefit analyses characterize the health impacts of societal changes, such as widespread adoption of active transport policies or significant shifts in consumption of animal products, without a detailed consideration of how implementation might occur e. Approaches such as agent-based modeling can help characterize diffusions of such innovations within populations and the role of organizations in catalyzing and maintaining significant policy shifts Bonabeau Estimating the health impacts of GHG mitigation strategies is a complex process that brings together disparate disciplines.
Because all models are simplifications that involve assumptions, are subject to many uncertainties, and capture a subset of interactions, modeling health co-benefits requires systematic consideration of the suitability of model assumptions, of what should be included and excluded from the model framework, and how uncertainty should be treated. The ultimate goal of modeling is policy utility, and it is important for modelers to iteratively engage policy makers actively in their work. Despite the challenges, there is a great need for information on the health implications of mitigation strategies, particularly given the urgency of bringing mitigation strategies into practice and the early accrual of ancillary health impacts of these strategies.
Here we have reviewed some of the challenges and controversies in modeling health co-benefits and co-harms, and some approaches to increase their utility. Recommendations to improve such models include the following:. Modeling health co-benefits should be done in concert with policy makers from the start, and should focus on potentially feasible interventions based on policy-maker consultation; identification of policy-relevant outcomes; and incorporation, where needed, of methods to evaluate potential policy resistance.
Model scoping should include consultation with policy makers and scientists from a range of disciplines to ensure that a full complement of potential impact pathways is considered. Focusing on domains and channels wherein modeling was used to affect policy may increase the potential utility of modeling efforts.
Initial stages of analysis should identify the full range of potential positive and negative pathways to health impacts within predefined boundaries, as well as the critical uncertainties in these causal pathways, while making explicit the criteria used to determine which exposure—outcome relationships are included in the model. The assessment of the strength of evidence for exposure—outcome relationships and parameters should use systematic review Moher et al.
The period over which the mitigation and health impacts are analyzed must be carefully assessed, both in relation to the time course between implementation of mitigation and consequent impacts, and in relation to time preferences for specific outcomes and the associated choice of discount rates. Uncertainty in modeling results should be characterized explicitly, using quantitative and qualitative methods as appropriate. Both parametric and structural uncertainties should be considered, and at a minimum, single and when possible multivariate deterministic sensitivity analyses should be carried out.
Scientists modeling health co-benefits should explicitly consider consulting with or including decision analysis experts to ensure that the results are useful in formal decision analysis processes. Such collaboration should be initiated at the inception of the modeling effort and should anticipate the ultimate application of the modeling results.
By improving the quality and rigor of health co-benefits analyses, critical decisions regarding climate mitigation strategies can be informed by health impact estimates, aiding policy makers in their efforts to maximize GHG mitigation potential while simultaneously improving health. Brown, who made possible this collaboration by sponsoring a United States—United Kingdom workshop on research on the health impacts of climate change mitigation strategies. The funders had no role in the analysis, decision to publish, or preparation of the manuscript.
The authors declare they have no actual or potential competing financial interests. National Center for Biotechnology Information , U. Journal List Environ Health Perspect v. Environ Health Perspect. Published online Feb Justin V. Remais , 1 Jeremy J. Hess , 1, 2 Kristie L. Ebi , 3 Anil Markandya , 4 John M. Jeremy J. Kristie L. John M. Author information Article notes Copyright and License information Disclaimer.
Corresponding author. Address correspondence to J. Telephone: E-mail: ude. Received Mar 2; Accepted Feb Copyright notice. Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
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Abstract Background: Policy decisions regarding climate change mitigation are increasingly incorporating the beneficial and adverse health impacts of greenhouse gas emission reduction strategies. Table 1 Summary of major health drivers and outcomes modified by select mitigation strategies. Open in a separate window. Figure 1. Key Modeling Issues Health co-benefits models typically begin with a mapping exercise that proceeds to a more formal mathematical model describing relationships between model components and outcomes of interest.
Table 2 Time lags over which the health co-benefits accrue for the mitigation strategies explored in recent health effects of mitigation modeling studies. Table 3 The types of downstream uncertainties in recent health effects of mitigation modeling studies. Addressing Key Science Policy and Decision Support Issues Co-benefits models are generally intended to inform the policy-making process, including modeling carried out in response to a specific policy question under consideration by a particular governing body.
Conclusions and Recommendations Estimating the health impacts of GHG mitigation strategies is a complex process that brings together disparate disciplines. Recommendations to improve such models include the following: Modeling health co-benefits should be done in concert with policy makers from the start, and should focus on potentially feasible interventions based on policy-maker consultation; identification of policy-relevant outcomes; and incorporation, where needed, of methods to evaluate potential policy resistance.
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Research Presentation Economic implications of limiting global temperature at 1. Emulators to explore economic impact of climate change under numerous scenario combinations. AgMIP Phase 2, 2nd round core scenario results overview and some insights. Economic assessment of effectiveness of shifting working time to offset the impact of labor capacity reduction due to climate change.
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