Health co-benefits and the development of climate change mitigation policies in the European Union

The 2015 Paris Agreement requires increasingly ambitious emissions reduction efforts from its member countries. Accounting for ancillary positive health outcomes (health co-benefits) that result from implementing climate change mitigation policies can provide Parties to the Paris Agreement with a sound rationale for introducing stronger mitigation strategies. Despite this recognition, a knowledge gap exists on the role of health co-benefits in the development of climate change mitigation policies. To address this gap, the case study presented here investigates the role of health co-benefits in the development of European Union (EU) climate change mitigation policies through analysis and consideration of semi-structured interview data, government documents, journal articles and media releases. We find that while health co-benefits are an explicit consideration in the development of EU climate change mitigation policies, their influence on final policy outcomes has been limited. Our analysis suggests that whilst health co-benefits are a key driver of air pollution mitigation policies, climate mitigation policies are primarily driven by other factors, including economic costs and energy implications.

Key policy insights

• Health co-benefits are quantified and monetized as part of the development of EU climate change mitigation policies but their influence on the final policies agreed upon is limited.

• Barriers, such as the immediate economic costs associated with climate action, inhibit the influence of health co-benefits on the development of mitigation policies.

• Health co-benefits primarily drive the development of EU air pollution mitigation policies.

• The separation of responsibility for GHG and non-GHG emissions across Directorate Generals has decoupled climate change and air pollution mitigation policies, with consequences for the integration of health co-benefits in climate policy.

     

Context and climate change: an integrated assessment for Barrow, Alaska

An intensive approach to Barrow, Alaska’s adaptations to climate change and variability during recent decades suggests reconsideration of the interconnected roles of science, policy, and decision-making structures. First, profound uncertainties are inherent in unique interactions among the many natural and human factors affecting Barrow’s vulnerability. Science cannot significantly reduce these uncertainties through extensive approaches, but intensive approaches can reconstruct and update local trends, clarify the underlying dynamics, and harvest experience for policy purposes. Second, sound policies to reduce Barrow’s vulnerability to coastal erosion and flooding must incorporate these profound uncertainties and the multiple values of the community. Minimizing vulnerability to climate change is only one of the community’s interests, and must compete with other interests for limited time, attention, funds and other resources. Third, the community itself is in the best position to understand its own context, to decide on sound policies, and to take responsibility for those decisions. In short, local context matters in science, policy, and decision-making structures for adaptation to climate change and variability. Overall, cognitive constraints may be the most important human dimension of climate change. Factoring the global problem into more tractable local problems would make the most of our cognitive capacity.     

Economics of climate change mitigation forest policy scenarios for Ukraine

Abstract

This article reveals the contribution of woodland expansion in Ukraine to climate change mitigation policies. The opportunities for climate change mitigation of three policy scenarios: (1) carbon storage in forests, (2) carbon storage and additional wood-for-fuel substitution, and (3) carbon storage with additional sink policy for wood products, are investigated by using a simulation technique, in combination with cost—benefit analysis. The article concludes that the Ukraine's forests and their expansion offer a low-cost opportunity for carbon sequestration. Important factors that influence the results are the discount rate and the time horizon considered in the models. The findings provide evidence that the storage climate change mitigation forest policy scenario is most viable for the country, under the assumptions considered in this research.     

The benefits of climate change mitigation in integrated assessment models: the role of the carbon cycle and climate component

Integrated Assessment Models (IAMs) are an important tool to compare the costs and benefits of different climate policies. Recently, attention has been given to the effect of different discounting methods and damage estimates on the results of IAMs. One aspect to which little attention has been paid is how the representation of the climate system may affect the estimated benefits of mitigation action. In that respect, we analyse several well-known IAMs, including the newest versions of FUND, DICE and PAGE. Given the role of IAMs in integrating information from different disciplines, they should ideally represent both best estimates and the ranges of anticipated climate system and carbon cycle behaviour (as e.g. synthesised in the IPCC Assessment reports). We show that in the longer term, beyond 2100, most IAM parameterisations of the carbon cycle imply lower CO₂ concentrations compared to a model that captures IPCC AR4 knowledge more closely, e.g. the carbon-cycle climate model MAGICC6. With regard to the climate component, some IAMs lead to much lower benefits of mitigation than MAGICC6. The most important reason for the underestimation of the benefits of mitigation is the failure in capturing climate dynamics correctly, which implies this could be a potential development area to focus on.     

A wedge-based approach to estimating health co-benefits of climate change mitigation activities in the United States

While it has been recognized that actions reducing greenhouse gas (GHG) emissions can have significant positive and negative impacts on human health through reductions in ambient fine particulate matter (PM_2.5) concentrations, these impacts are rarely taken into account when analyzing specific policies. This study presents a new framework for estimating the change in health outcomes resulting from implementation of specific carbon dioxide (CO₂) reduction activities, allowing comparison of different sectors and options for climate mitigation activities. Our estimates suggest that in the year 2020, the reductions in adverse health outcomes from lessened exposure to PM_2.5 would yield economic benefits in the range of $6 to $30 billion (in 2008 USD), depending on the specific activity. This equates to between $40 and $198 per metric ton of CO₂ in health benefits. Specific climate interventions will vary in the health co-benefits they provide as well as in potential harms that may result from their implementation. Rigorous assessment of these health impacts is essential for guiding policy decisions as efforts to reduce GHG emissions increase in scope and intensity.     

Effectiveness and efficiency of climate change mitigation in a technologically uncertain World

Following a multi-scenario framework based on the technology assumptions proposed by the 27th Energy Modeling Forum (EMF-27), our analysis focuses on analyzing the impacts of key technology assumptions on climate policies, including the interdependencies of different technological options. Each scenario may be considered as either a possible state of nature upon which one has no influence, each scenario thus dictating the availability (or non availability) of some subset of the technology groups, or as an opportunity for society, by its own actions and policies, to influence the availability of said technology group. The main insights obtained from the assessment show the prominent role of bioenergy as a means to abate greenhouse gas emissions, irrespective of other technological developments, while the role of the other technologies (wind and solar, carbon capture and sequestration, nuclear) are more dependent of one another. It appears that CCS may play a sort of “backstop” role: it compensates for a lower contribution of solar and wind, or of nuclear. This means that an increased social acceptability of one (or all) of these three sets of technology should be at the heart of future climate policies. The costs caused by the adaptation of electricity networks to accommodate a high fraction of intermittent sources would deserve more attention in future research.     

Link between climate change mitigation and resource efficiency: A UK case study

This paper provides an in-depth analysis of the links between dematerialisation and climate change mitigation. Methods used for material flow analyses (MFA) within the wider context of industrial ecology (which includes a focus on all resource flows in an economy, not purely material tonnage) tend to focus either on detoxification and pollution reduction or dematerialisation and resource productivity. An environmentally extended input–output (EEIO) model incorporates both aspects, which need to be dealt with when looking at how to meet challenging greenhouse gas (GHG) emission targets. The approach understands both production systems and consumption patterns and has the ability through scenarios to analyse the (GHG) effectiveness of a wide range of material efficiency options. This analysis adopts an environmentally extended input–output approach to assess the role of material efficiency measures in reducing UK GHG emissions by 2050. A method for projecting the variables and parameters in the model, including the supply of and demand for materials and products, is presented and applied to investigate thirteen material efficiency strategies in the UK.     

Energy-intensive manufacturing sectors in China: policy priorities for achieving climate mitigation and energy conservation targets

In this study, a long-range energy alternative planning (LEAP) model was built to evaluate the relative priority of three kinds of policies expected to be implemented for the energy-intensive manufacturing sectors (EIMS) in China to achieve CO₂ mitigation and energy conservation targets. These policies encourage (1) the use of more electricity instead of coal; (2) the continuous improvement of energy efficiency; and (3) a shift to other less energy-demanding sectors. The results indicate that the policy of shifting economic activity from the EIMS to other sectors is most helpful for China to achieve its targets of mitigating CO₂ emissions and conserving energy. Encouraging the EIMS to use more electricity can help China to achieve a higher proportion of non-fossil-fuel based energy in its overall primary energy consumption. No single policy will allow China to achieve all the targets, emphasizing the need for an integrated policy design that combines all types of policies.

Key policy insights

• The policy of encouraging a shift to less energy intensive industries should receive the highest priority in aiming to peak China's energy-related CO₂ emissions as early as possible, and lower overall CO₂ emissions, coal consumption and primary energy consumption in the long run.

• Encouraging a shift to electricity should go hand-in-hand with greater energy efficiency, otherwise such a policy cannot help China significantly reduce energy-related CO₂ emissions.

• Encouraging the EIMS to use more electricity should receive the highest priority in helping China achieve a higher proportion of non-fossil-fuel based energy in its overall primary energy consumption.

     

A new scenario framework for climate change research: the concept of shared climate policy assumptions

The new scenario framework facilitates the coupling of multiple socioeconomic reference pathways with climate model products using the representative concentration pathways. This will allow for improved assessment of climate impacts, adaptation and mitigation. Assumptions about climate policy play a major role in linking socioeconomic futures with forcing and climate outcomes. The paper presents the concept of shared climate policy assumptions as an important element of the new scenario framework. Shared climate policy assumptions capture key policy attributes such as the goals, instruments and obstacles of mitigation and adaptation measures, and introduce an important additional dimension to the scenario matrix architecture. They can be used to improve the comparability of scenarios in the scenario matrix. Shared climate policy assumptions should be designed to be policy relevant, and as a set to be broad enough to allow a comprehensive exploration of the climate change scenario space.     

Integrated assessment of biomass supply and demand in climate change mitigation scenarios

Biomass is often seen as a key component of future energy systems as it can be used for heat and electricity production, as a transport fuel, and a feedstock for chemicals. Furthermore, it can be used in combination with carbon capture and storage to provide so-called “negative emissions”. At the same time, however, its production will require land, possibly impacting food security, land-based carbon stocks, and other environmental services. Thus, the strategies adopted in the supply, conversion, and use of biomass have a significant impact on its effectiveness as a climate change mitigation measure. We use the IMAGE 3.0 integrated assessment model to project three different global, long term scenarios spanning different socioeconomic futures with varying rates of population growth, economic growth, and technological change, and investigate the role of biomass in meeting strict climate targets. Using these scenarios we highlight different possibilities for biomass supply and demand, and provide insights on the requirements and challenges for the effective use of this resource as a climate change mitigation measure. The results show that in scenarios meeting the 1.5 °C target, biomass could exceed 20% of final energy consumption, or 115–180 EJ_Prim/yr in 2050. Such a supply of bioenergy can only be achieved without extreme levels land use change if agricultural yields improve significantly and effective land zoning is implemented. Furthermore, the results highlight that strict mitigation targets are contingent on the availability of advanced technologies such as lignocellulosic fuels and carbon capture and storage.     

Role of renewable energy in climate mitigation: a synthesis of recent scenarios

The role of renewable energy in climate change mitigation is explored through a review of 162 recent medium- to long-term scenarios from 15 large-scale, energy-economic and integrated assessment models. The current state of knowledge from this community is assessed and its implications drawn for the strategic context in which policymakers and other decision-makers might consider renewable energy. The scenario set is distinguished from previous ones in that it contains more detailed information on renewable deployment levels. All the scenarios in this study were published during or after 2006. Within the context of a large-scale assessment, the analysis is guided primarily by four questions. What sorts of future levels of renewable energy deployment are consistent with different CO₂ concentration goals? Which classes of renewable energy will be the most prominent energy producers and how quickly might they expand production? Where might an expansion in renewable energy occur? What is the linkage between the costs of mitigation and an expansion of renewable energy?     

气候变化综合评估模型的损失函数研究进展

该研究从综合评估模型(IAM)的模型耦合视角出发,介绍了当前损失函数的研究进展,主要从损失函数的构建方法、损失函数与IAM气候模块和经济模块的耦合以及IAM与气候模式的耦合角度分析了损失函数的耦合功能及其存在的科学问题,探讨了损失函数的改进方向。通过文献梳理发现,损失函数的构建方法上,主要采用专家判断法、元分析法和统计学方法,但各有优缺点;与气候模式的耦合功能上,损失函数多以温升为气候变化因素,降水等气候变化信息无法表达,且由全球尺度的年平均值进行标定,不能体现区域的差异和季节的变化,无法直接描述极端气候事件造成的巨大损失;与经济模块的耦合功能上,基于生产部门的损失函数缺乏间接损失评估功能,缺乏对经济增长的动态影响机制。针对上述IAM中气候变化对经济影响的反馈机制的不足,需重点从细化区域气候变化因素影响和细分经济产业部门两个方向重构损失函数,紧密连接气候模式与经济模块,全面评估气候变化经济损失,并需要从技术上解决损失函数在耦合经济模块与气候模式时出现的时空尺度不匹配问题,最终为IAM与气候模式甚至地球系统模式的耦合提供重要的解决方案。     

Three dilemmas in the integrated assessment of climate change

Conclusions These three dilemmas embody the hardest, most important, and most enduring problems of doing assessment well. None admits simple, obvious solutions. Each can be managed better or worse for any particular assessment endeavor, but doing better requires clear understanding of the purpose of the endeavor. What ways of combining different pieces of disciplinary knowledge, of making projections, and of pursuing policy relevance are more or less appropriate will differ, depending on whether a project seeks to characterize uncertainties and gaps in knowledge; to advise a particular policy choice; to support dialog among policy actors; or to facilitate inquiry into relevant values or goals. Evaluation of the relative emphasis, the methods, and the process of an assessment can only be done relative to some such purpose.Of course, some pitfalls may be so serious as to thwart any purpose, as Risbey et al.'s discussion of the global modeling movement reminds us. The global models' most obvious pitfalls — inadequate treatment of uncertainty, neglect of economic adjustment, excessive confidence in predictions — have largely been seen and avoided by the current assessment community (though there may be more to be learned even here). But on the subtler questions of how assessment or modeling can contribute most usefully to policy, little progress has been made since the 1970s. Consequently, though assessment has advanced in many ways since then, IA remains at risk of suffering the same fate as the global models: a cycle of early enthusiasm, followed by a reaction of frustration and excessive, undeserved rejection.Current endeavors in IA have made substantial contributions to identifying and prioritizing knowledge needs, less to informing specific policy choice. Further progress cannot be guided by a single canonical view of what assessment should be and do, but will proceed incrementally down multiple paths. Several paths currently appear promising: analytic approaches to better represent multiple actors, diverse preferences, and multiple valued outcomes; better representation and application of uncertainty, including diverse expert opinion; novel methods to link assessment with policy communities; and broader participation in assessment teams and explicit focus on negotiating and elaborating pragmatic, viable critical standards. Risbey et al.'s call to develop institutions for critical reflection, mutual learning, and self-improvement will be crucial in developing and evaluating the progress made down these paths.Morgan and Dowlatabadi's checklist for desiderata of IA is a good starting point for a conversation about assessment standards, to which I would propose a few extensions and elaborations. First, there should be not just multiple assessments, but multiple assessment projects using diverse collections of methods and approaches. Second, assessment projects should explore novel methods for connecting their work with the policy community. Third, the approach should be iterative not just within each project, but across assessment projects and between them and the policy community. Fourth, assessors should not be embarrassed by, or seek to disguise, results that are merely illustrative, non-authoritative, and suggestive; these should be acknowledged as such, and the vigorous questioning and critique that will come, including partisan critique, accepted. Do not seek to avoid criticism by mumbling. An important limit to this checklist approach is suggested, though, by the way various writers have groped to define assessment standards by analogy to other domains, revealing how limited is our understanding of how to evaluate assessment. Risbey et al. refer to connoisseurship, as if assessment is like fine wine; Clark and Majone (1985) refer to artistic criticism, as if assessment is like opera singing. If these analogies are appropriate, then pursuing a single set of critical standards for assessment is at least premature, possibly erroneous. Rather, there should be a diversity of approaches, perhaps so broad that no single set of criteria for excellence could be defined. The pragmatic middle way between the too-limiting application of a single set of standards, and an anarchic refusal to evaluate, will have to be negotiated, defined, and improved incrementally.     

CO2 emission clusters within global supply chain networks: Implications for climate change mitigation

Production and consumption of goods and services are interlinked through complex global supply-chain networks; so are the greenhouse gas emissions associated with them. Using a model that represents global supply-chain networks, we identified supply-chain clusters with high CO₂ emissions within more than 300 million individual supply chains. We distinguished 4756 significant CO₂ clusters and found that in 2008, global supply-chain networks associated with U.S. transport equipment and construction demand included relatively large CO₂ clusters in China, accounting for 17% and 10%, respectively, of the U.S. CO₂ footprint. Of added importance is the fact that these two clusters in China had annual growth rates of 42% and 58%, respectively, during the period 1995–2008. Our results show the importance for climate policy of monitoring these CO₂ clusters that dominate CO₂ emissions in global supply chains, and they offer insights on where climate policy can be effectively directed.     

On the added value of regional climate modeling in climate change assessment

Regional climate models represent a promising tool to assess the regional dimension of future climate change and are widely used in climate impact research. While the added value of regional climate models has been highlighted with respect to a better representation of land-surface interactions and atmospheric processes, it is still unclear whether radiative heating implies predictability down to the typical scale of a regional climate model. As a quantitative assessment, we apply an optimal statistical filter to compare the coherence between observed and simulated patterns of Mediterranean climate change from a global and a regional climate model. It is found that the regional climate model has indeed an added value in the detection of regional climate change, contrary to former assumptions. The optimal filter may also serve as a weighting factor in multi-model averaging.     

Confronting the challenge of integrated assessment of climate adaptation: a conceptual framework

Key limitations of integrated assessment models (IAMs) are their highly stylized and aggregated representation of climate damages and associated economic responses, as well as the omission of specific investments related to climate change adaptation. This paper proposes a framework for modeling climate impacts and adaptation that clarifies the relevant research issues and provides a template for making improvements. We identify five desirable characteristics of an ideal integrated assessment modeling platform, which we elaborate into a conceptual model that distinguishes three different classes of adaptation-related activities. Based on these elements we specify an impacts- and adaptation-centric IAM, whose optimality conditions are used to highlight the types of functional relationships necessary for realistic representations of adaptation-related decisions, the specific mechanisms by which these responses can be incorporated into IAMs, and the ways in which the inclusion of adaptation is likely to affect the simulations’ results.     

Including animal to plant protein shifts in climate change mitigation policy: a proposed three-step strategy

Strong and rapid greenhouse gas (GHG) emission reductions, far beyond those currently committed to, are required to meet the goals of the Paris Agreement. This allows no sector to maintain business as usual practices, while application of the precautionary principle requires avoiding a reliance on negative emission technologies. Animal to plant-sourced protein shifts offer substantial potential for GHG emission reductions. Unabated, the livestock sector could take between 37% and 49% of the GHG budget allowable under the 2°C and 1.5°C targets, respectively, by 2030. Inaction in the livestock sector would require substantial GHG reductions, far beyond what are planned or realistic, from other sectors. This outlook article outlines why animal to plant-sourced protein shifts should be taken up by the Conference of the Parties (COP), and how they could feature as part of countries’ mitigation commitments under their updated Nationally Determined Contributions (NDCs) to be adopted from 2020 onwards. The proposed framework includes an acknowledgment of ‘peak livestock’, followed by targets for large and rapid reductions in livestock numbers based on a combined ‘worst first’ and ‘best available food’ approach. Adequate support, including climate finance, is needed to facilitate countries in implementing animal to plant-sourced protein shifts.

Key policy insights

• Given the livestock sector’s significant contribution to global GHG emissions and methane dominance, animal to plant protein shifts make a necessary contribution to meeting the Paris temperature goals and reducing warming in the short term, while providing a suite of co-benefits.

• Without action, the livestock sector could take between 37% and 49% of the GHG budget allowable under the 2°C and 1.5°C targets, respectively, by 2030.

• Failure to implement animal to plant protein shifts increases the risk of exceeding temperate goals; requires additional GHG reductions from other sectors; and increases reliance on negative emissions technologies.

• COP 24 is an opportunity to bring animal to plant protein shifts to the climate mitigation table.

• Revised NDCs from 2020 should include animal to plant protein shifts, starting with a declaration of ‘peak livestock’, followed by a ‘worst first’ replacement approach, guided by ‘best available food’.

     

Attitudes toward climate change mitigation policies: a review of measures and a construct of policy attitudes

Research on policy support or public acceptability of climate change policies is proliferating. There is, however, a great diversity in how these evaluative responses have been defined, operationalized, and measured across studies. In order to shed some light on this subject, we reviewed 118 studies published over the last 15 years aiming at measurement of policy acceptability, acceptance, support, and other responses to climate change mitigation policies. We found that conceptual vagueness and weak theoretical embedding are pervasive in the field, which leads to uncertainty over what is being measured, ambiguity of policy recommendations, and difficulties in comparing empirical results. In response, we propose a construct of policy attitudes as an overarching concept comprising the diversity of measures and constructs already in use. The purpose of the construct is to serve as a common basis for operationalization and survey design. In order to inform policy makers, researchers should be clear in how they formulate surveys with a focus on questions of importance to research and policy-making.

Key policy insights

• Acceptability, acceptance, and support are defined as distinct and possibly empirically distinguishable classes of responses evaluating a policy proposal. These responses are expressions of underlying policy attitudes.

• People may respond to policies in other ways as well, including lack of interest.

• There is no popularity threshold for a policy to be safe to implement, but instead it is a matter of identifying the conditions of policy support or other responses.

• Results obtained using different measures of mitigation policy attitudes vary widely with respect to the characteristics of the policy in question and the measured response. Thus, great care must be taken when designing surveys and interpreting their results.