Mitigation vs. Adaptation: Analytic Models for Policy Assessment

We suggest analytic economic-environmental models that aim to investigate the multi-faced interplay between economic production, industrial pollution, and environmental protection. The considered static and dynamic optimization problems assess a country’s sustainable environmental policy that involves the optimal combination of adaptation and mitigation strategies. A qualitative analysis of obtained solutions leads to relevant conclusions about the ranges of economic-environmental parameters, in which the adaptation and mitigation are viable policy options.     

A new model for climate system analysis: Outline of the model and application to palaeoclimate simulations

We present a new reduced-form model for climate system analysis. This model, called CLIMBER-2 (for CLIMate and BiosphERe, level 2), fills the current gap between simple, highly parameterized climate models and computationally expensive coupled models of global atmospheric and oceanic circulation. We outline the basic assumptions implicit in CLIMBER-2 and we present examples of climate system analysis including a study of atmosphere–ocean interaction during the last glacial maximum, an analysis of synergism between various components of the climate system during the mid-Holocene around 6000 years ago, and a transient simulation of climate change during the last 8000 years. These studies demonstrate the feasibility of a computationally efficient analysis of climate system dynamics which is a prerequisite for future climate impact research and, more generally, Earth system analysis, i.e., the analysis of feedbacks between our environment and human activities.     

Analysis of the decision-support function of policy assessment in real-world policy making in the field of poverty and social inequalities. Case study on migrant integration policies in the Brussels-Capital Region

Despite its high potential to support decision-making, the role of policy assessment in real-world policy making in the field of poverty and social inequalities remains largely questioned. In this study, we analyse policy assessment's role in a context of real-world policymaking, by means of a case study on a legislative proposal on integration policy for immigrant newcomers in the Brussels-Capital Region, for which we evaluate the potential effects on poverty and social inequalities. We first analyse the policy process surrounding the policy proposal – a process that is often treated as a black box within policy assessment research. Understanding the factors that influence and determine the decision-making process, enables us to gain insight into the potential decision-support function(s). Second, we develop an approach to policy assessment that aims to fully exploit its potential to contribute to the functions of both instrumental and conceptual learning. For this purpose, we propose to introduce the approach of realist evaluation and to focus on evaluating the underlying policy intervention theory from the perspective of poverty and social inequalities. Finally, we illustrate this new approach and its added value by applying it to the legislative proposal on integration policy and analyse its contribution to policy-oriented learning.     

Approaches for performing uncertainty analysis in large-scale energy/economic policy models

A number of key policy insights have emerged from the application of large-scale economic/energy models, such as integrated assessment models for climate change. These insights have been particularly powerful in those instances when they are shared by all or most of the existing models. On the other hand, some results and policy recommendations obtained from integrated assessment models vary widely from model to model. This can limit their usability for policy analysis. The differences between model results are mostly due to different underlying assumptions about exogenous processes, about endogenous processes and the dynamics among them, differences in value judgments, and different approaches for simplifying model structure for computational purposes. Uncertainty analyses should be performed for the dual purpose of clarifying the uncertainties inherent in model results and improving decision making under uncertainty. This paper develops a unifying framework for comparing the different types of uncertainty analyses through their objective functions, categorizes types of uncertainty analyses that can be performed on large models, and compares different approaches to uncertainty analysis by explaining underlying assumptions, suitability for different model types, and advantages and disadvantages. The appendix presents a summary of integrated assessment models for climate change that explicitly account for uncertainty.     

A review of EIAs on trade policy in China: Exploring the way for economic policy EIAs

During the discussion on the “Environmental Protection Law Amendment (draft)” in 2011, it was decided to drop the proposed clauses related to environmental impact assessments (EIAs) on policy, which means that there remained no provisions for policy EIAs, and China's strategic environmental assessment system stayed limited to the planning level. However, considering that economic policy making is causing significant direct and indirect environmental problems and that almost every aspect of governmental policy has an economic aspect, EIAs on economic policies are of the utmost urgency. The purpose of this study is to review the EIA work that has been carried out on trade policy in China through four case studies, and illustrate how trade policy EIAs can be helpful in achieving better environmental outcomes in the area of trade. Through the trade policy EIA case studies we try to argue for the feasibility of conducting EIAs on economic policies in China. We also discuss the implications of the case studies from the point of view of how to proceed with EIAs on economic policy and how to promote their practice.     

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.     

Uncertainty in Integrated Assessment Models of Climate Change: Alternative Analytical Approaches

Uncertainty plays a key role in the economics of climate change, and research on this topic has led to a substantial body of literature. However, the discussion on the policy implications of uncertainty is still far from being settled, partly because the uncertainty of climate change comes from a variety of sources and takes diverse forms. To reflect the multifaceted nature of climate change uncertainty better, an increasing number of analytical approaches have been used in the studies of integrated assessment models of climate change. The employed approaches could be seen as complements rather than as substitutes, each of which possesses distinctive strength for addressing a particular type of problems. We review these approaches—specifically, the non-recursive stochastic programming, the real option analysis, and the stochastic dynamic programming—their corresponding literatures and their respective policy implications. We also identify the current research gaps associated with the need for further developments of new analytical approaches.     

Integrated assessment modeling of global climate change: Transparent rational tool for policy making or opaque screen hiding value‐laden assumptions?

One of the principal tools used in the integrated assessment (IA) of environmental science, technology and policy problems is integrated assessment models (IAMs). These models are often comprised of many sub‐models adopted from a wide range of disciplines. A multi‐disciplinary tool kit is presented, from which three decades of IA of global climatic change issues have tapped. A distinction between multi‐ and inter‐disciplinarity is suggested, hinging on the synergistic value added for the latter. Then, a hierarchy of five generations of IAMs are proposed, roughly paralleling the development of IAMs as they incorporated more components of the coupled physical, biological and social scientific disciplines needed to address a “real world” problem like climatic change impacts and policy responses. The need for validation protocols and exploration of predictability limits is also emphasized. The critical importance of making value‐laden assumptions highly transparent in both natural and social scientific components of IAMs is stressed, and it is suggested that incorporating decision‐makers and other citizens into the early design of IAMs can help with this process. The latter could also help IA modelers to offer a large range of value‐containing options via menu driven designs. Examples of specific topics which are often not well understood by potential users of IAMs are briefly surveyed, and it is argued that if the assumptions and values embedded in such topics are not made explicit to users, then IAMs, rather than helping to provide us with refined insights, could well hide value‐laden assumptions or conditions. In particular, issues of induced technological change, timing of carbon abatement, transients, surprises, adaptation, subjective probability assessment and the use of contemporary spatial variations as a substitute for time evolving changes (what I label “ergodic economics”) are given as examples of problematic issues that IA modelers need to explicitly address and make transparent if IAMs are to enlighten more than they conceal. A checklist of six practices which might help to increase transparency of IAMs is offered in the conclusions. Incorporation of decision‐makers into all stages of development and use of IAMs is re‐emphasized as one safeguard against misunderstanding or misrepresentation of IAM results by lay audiences.     

Environmental impact of Information Communication Technology: A review of econometric assessment methods,influential mechanism,and influential direction

In recent decades, the rapid development of the global society and economy has brought serious environmental problems, such as air pollution, greenhouse effect, and ecosystem degradation, all of which have attracted wide attention. Simultaneously, the use of Information Communication Technology (ICT) has been on the rise since the 1980s, which stimulates the growth of the economy and has a certain degree of impact on the ecological environment. Accordingly, the scientific community's interest in assessing this impact has grown considerably, and econometric methods are widely used as evaluation tools. However, the research results are often different in different regions, periods, environmental proxies, and ICT. Some studies indicate that the development of ICT is beneficial to environmental improvement, while others state that it is not. Therefore, a comprehensive analysis of the methods, mechanisms, and relative policy suggestions of this topic is desiderated. To address this gap, this paper carries out a systematic literature review of the usage of econometric methods in the assessment of the environmental impact of ICT. Among the 472 articles retrieved from scientific literature databases, 46 met the inclusion criteria and were analyzed in detail. This study aims to provide scholars with a mental picture of the current state of scientific research, identify the factors that influence the direction of ICT's impact on the environment, and enable future researchers to use more reliable and accurate estimation methods. The methods used in selected articles were divided into two main groups (i.e., time series models and panel data models), and panel data models were further subdivided into five categories. The detailed flow of these methods is summarized, and new advanced pre-test methods and estimators are highlighted. Furthermore, the analysis also indicates that among all the countries and regions involved in the selected articles, there is a non-strict inverted U-shaped curve between the level of socio-economic development and the direction of the impact of ICT on the environment. Finally, current research challenges are discussed, and potential directions for future research on this topic are also projected.     

Mainstreaming ecosystem services in European policy impact assessment

The concept of ecosystem services as developed for the Millennium Ecosystem Assessment (MA) is currently the most extensive, international, scientific concept dealing with the interaction between the world's ecosystems and human well-being. The fundamental asset is seen in the relevancy of the concept at the science–policy interface. Albeit, the mainstreaming of ecosystem services into policy making requires a framework that allows the transition of the scientific concept into the rationale of policy making. We hypothesize that the procedure of policy impact assessment is a suitable venue for this transition. This brings up two questions: 1) where in the process of policy impact assessment can ecosystem services be mainstreamed? 2) How can the impact on ecosystem services properly be accounted for? In this paper we distinguish two groups of policy cases: explicit cases directly addressing ecosystem services, and implicit cases of policies that follow other purposes but may have unintended impacts on ecosystem services as a side effect. The second group covers a wide range of policies for which we set out a framework for mainstreaming of ecosystem services. The framework is exemplary designed for the instrument of ex-ante impact assessment at European policy making level. We reveal that the two concepts of the MA and of the European policy impact assessment are indeed compatible, which makes the integration of the ecosystem service concept possible. We conclude that the linkage of the scientifically validated concept of ecosystem services with the policy concept of impact assessment has the potential of improving the credibility of the latter.     

Behavioural determinants of an individual's intention to adapt to climate change: Both internal and external perspectives

Climate change has had a significant negative impact on socio-economic factors and the earth's ecology. To cope with climate change, many countries have employed various policies and measures to reduce damage due to climate change. For individual residents, adaptation behaviour is vital for reducing individual welfare losses. This research analysed how psychological determinants and other external factors influence residents' intention to adapt to climate change. We proposed an extended protection motivation theory (PMT) model, developed a reliable scale and conducted a nationwide field survey. We interviewed 1402 residents in 29 provinces, and 874 valid questionnaires were collected, providing data that were used in a structural equation model. The results show that our model can serve as a reliable framework for analysing the determinants of residents' intention to adapt to climate change. Policy is the most important factor for stimulating the formation of residents' adaptation intention. Risk appraisals and adaptation appraisals have positive and significant impacts on the intention of residents to adopt climate change adaptation behaviour. Information and climate perception do not directly influence residents' behavioural intentions but indirectly affect their intentions through the process of risk appraisal and adaptation appraisal. Corresponding policy suggestions are made that may be helpful for the formulation of adaptation policies.     

Assessing the impact of emissions trading scheme on low-carbon technological innovation: Evidence from China

A global consensus on carbon emission reductions has been reached for combating climate change. The Chinese government has clearly stated that it is necessary to make full use of market means to improve the level of environmental governance. Emissions trading scheme (ETS) is a typical market means to accelerate low-carbon economic transition. Low-carbon technological innovation is one of the key factors affecting carbon emissions. However, literature on the relationship between ETS and low-carbon technological innovation is relatively scarce at present. This study assesses the effect of pilot ETSs on low-carbon technological innovation, and a difference in differences (DID) model is adopted to analyze China's provincial panel data from 2003 to 2017. The results indicate that China's pilot ETSs can significantly promote low-carbon technological innovation, and changing the window period, PSM-DID and placebo test all verify the robustness of this finding. The dynamic effect test reveals that China's pilot ETSs will gradually increase the effect on low-carbon technological innovation over time. The heterogeneity analysis shows that the effect of China's pilot ETSs on low-carbon technological innovation is more obvious in Guangdong, Hubei, Tianjin and Chongqing. The mechanism analysis suggests that marketization degree and green consumption concept can positively moderate the impact of China's pilot ETSs on low-carbon technological innovation, and industrial structure upgrading plays a positive mediating role between China's pilot ETSs and low-carbon technological innovation. This study is conducive to assessing the policy effectiveness of China's pilot ETSs and provides an empirical evidence for promoting the development of the carbon emissions trading market.     

Confronting Management Challenges in Highly Uncertain Natural Resource Systems: a Robustness–Vulnerability Trade-off Approach

This paper presents a framework for the study of policy implementation in highly uncertain natural resource systems in which uncertainty cannot be characterized by probability distributions. We apply the framework to parametric uncertainty in the traditional Gordon–Schaefer model of a fishery to illustrate how performance can be sacrificed (traded-off) for reduced sensitivity and hence increased robustness, with respect to model parameter uncertainty. With sufficient data, our robustness–vulnerability analysis provides tools to discuss policy options. When less data are available, it can be used to inform the early stages of a learning process. Several key insights emerge from this analysis: (1) the classic optimal control policy can be very sensitive to parametric uncertainty, (2) even mild robustness properties are difficult to achieve for the simple Gordon–Schaefer model, and (3) achieving increased robustness with respect to some parameters (e.g., biological parameters) necessarily results in increased sensitivity (decreased robustness) with respect to other parameters (e.g., economic parameters). We thus illustrate fundamental robustness–vulnerability trade-offs and the limits to robust natural resource management. Finally, we use the framework to explore the effects of infrequent sampling and delays on policy performance.     

How Cost-Effective is a Mixed Policy Targeting the Management of Three Agricultural N-pollutants?

This paper assesses the cost-effectiveness of a mixed policy in attempts to reduce the presence of three nitrogen pollutants: NO ₃, N ₂O, and NH ₃. The policy under study combines a tax on nitrogen input and incentives promoting perennial crops assumed to require low input. We show that the mixed policy improves the cost-effectiveness of regulation with regard to nitrates, whereas no improvement occurs, except for a very low level of subsidy in some cases, for gas pollutants. A quantitative analysis provides an assessment of impacts in terms of land use, farmers’ income, and nitrogen losses throughout France and at river-basin scale.     

Application of a checklist for quality assistance in environmental modelling to an energy model

Large, complex energy models present considerable challenges to develop and test. Uncertainty assessments of such models provide only partial guidance on the quality of the results. We have developed a model quality assistance checklist to aid in this purpose. The model checklist provides diagnostic output in the form of a set of pitfalls for the model application. The checklist is applied here to an energy model for the problem of assessing energy use and greenhouse gas emissions. Use of the checklist suggests that results on this issue are contingent on a number of assumptions that are highly value-laden. When these assumptions are held fixed, the model is deemed capable of producing moderately robust results of relevance to climate policy over the longer term. Checklist responses also indicate that a number of details critical to policy choices or outcomes on this issue are not captured in the model, and model results should therefore be supplemented with alternative analyses.     

The precautionary principle stimulus for solutions- and alternatives-based environmental policy

The precautionary principle is increasingly discussed in debates over appropriate measures to address complex and uncertain risks. The principle has generally been defined as having two main components: preventive action in the face of uncertainty and reversing the burden of proof. In isolation, these two components would suggest that precaution is primarily reactive to potential problems rather than proactive. More recent statements have suggested that thorough assessment of alternatives is critical to the effective implementation of the precautionary principle. Alternatives assessment—also referred to as options analysis and facility planning—redirects environmental science and policy debates from characterizing problems to identifying solutions. In this commentary, we examine the rationale for a focus on alternatives assessment in implementing the precautionary principle. We examine methods and examples of alternatives assessment, as well as opportunities for the principle's integration in environmental policy. We argue that a greater focus on alternatives assessment can enhance the ability of decision makers to make truly precautionary decisions, stimulate innovation toward sustainable production, and more effectively place burdens on to those creating risks. Such a focus forms an essential component of a shift from “problem-based” environmental policy to “solutions-based” policy. This shift requires adequate research resources, tools, and a government commitment to a new paradigm of environmental protection. We conclude that we will only reach the goal of sustainable production if we change our environmental protection focus from figuring out how bad the situation will be to seeking alternatives to problematic activities and designing the conditions for a more sustainable future.     

Marginal Abatement Costs and Marginal Welfare Costs for Greenhouse Gas Emissions Reductions: Results from the EPPA Model

Marginal abatement cost (MAC) curves, relationships between tonnes of emissions abated and the CO₂ (or greenhouse gas (GHG)) price, have been widely used as pedagogic devices to illustrate simple economic concepts such as the benefits of emissions trading. They have also been used to produce reduced-form models to examine situations where solving the more complex model underlying the MAC is difficult. Some important issues arise in such applications: (1) Are MAC relationships independent of what happens in other regions?, (2) are MACs stable through time regardless of what policies have been implemented in the past?, and (3) can one approximate welfare costs from MACs? This paper explores the basic characteristics of MAC and marginal welfare cost (MWC) curves, deriving them using the MIT Emissions Prediction and Policy Analysis model. We find that, depending on the method used to construct them, MACs are affected by policies abroad. They are also dependent on policies in place in the past and depend on whether they are CO₂-only or include all GHGs. Further, we find that MACs are, in general, not closely related to MWCs and therefore should not be used to derive estimates of welfare change. We also show that, as commonly constructed, MACs may be unreliable in replicating results of the parent model when used to simulate GHG policies. This is especially true if the policy simulations differ from the conditions under which the MACs were simulated.     

Syndromes of Global Change: a qualitative modelling approach to assist global environmental management

A novel transdisciplinary approach to investigate Global Change (GC) is presented. The approach rests on the decomposition of the intrigue dynamics of GC into patterns of civilization–nature interactions (syndromes) by an iterative scientific process of observations, data and system theoretical analyses, and modelling attempts. We illustrate the approach by a detailed analysis of the Sahel Syndrome, which describes the rural poverty driven overuse of natural resources. The investigation is performed by (i) identifying relevant symptoms and interlinkages which are characteristics for this pattern, and (ii) a qualitative model representing the internal dynamics of the essential flywheel. The geographical patchwork of the regions affected by the syndrome which is obtained by global data analysis, proves the high global relevance of this pattern. The qualitative model is employed for an evaluation of basic policy strategies debated in the context of rural poverty driven environmental degradation. It turns out that a mixed policy of combating poverty and introducing soil preserving agricultural techniques and practices is most promising to tackle the syndrome dynamics.     

HIA, the next step: Defining models and roles

If HIA is to be an effective instrument for optimising health interests in the policy making process it has to recognise the different contests in which policy is made and the relevance of both technical rationality and political rationality. Policy making may adopt a rational perspective in which there is a systematic and orderly progression from problem formulation to solution or a network perspective in which there are multiple interdependencies, extensive negotiation and compromise, and the steps from problem to formulation are not followed sequentially or in any particular order. Policy problems may be simple with clear causal pathways and responsibilities or complex with unclear causal pathways and disputed responsibilities. Network analysis is required to show which stakeholders are involved, their support for health issues and the degree of consensus.From this analysis three models of HIA emerge. The first is the phases model which is fitted to simple problems and a rational perspective of policymaking. This model involves following structured steps. The second model is the rounds (Echternach) model that is fitted to complex problems and a network perspective of policymaking. This model is dynamic and concentrates on network solutions taking these steps in no particular order. The final model is the “garbage can” model fitted to contexts which combine simple and complex problems. In this model HIA functions as a problem solver and signpost keeping all possible solutions and stakeholders in play and allowing solutions to emerge over time. HIA models should be the beginning rather than the conclusion of discussion the worlds of HIA and policymaking.