Integrated Assessment Modeling for Global Climate Change: An Infinite Horizon Optimization Viewpoint

In this paper one uses an infinite time horizon optimal control paradigm to deal with three important issues in global climate change integrated assessment, namely the equitable treatment of all the generations involved, the representation of technical progress, and the uncertainty concerning technological progress and climate change processes. The notion of economic sustainability is associated with the concept of turnpike in infinite horizon optimization models. The issue of deciding on the proper discount rate is addressed in this context and a method is proposed to reconcile long term sustainability and short term time preference for current generations. One also formulates a model where environmental damage and/or technical progress are represented as stochastic jump processes. One calls this random evolution a mode switching process. In this context, sustainability is represented by a family of turnpikes, and the economy will be driven from one steady state to the other as the modes switch. These concepts are illustrated on the DICE model and their possible implementation in other types of integrated assessment models is discussed.     

A Flexible Global Warming Index for Use in an Integrated Approach to Climate Change Assessment

Global Warming Potential (GWP) is an index used to measure the cumulative radiative forcing of a tonne of greenhouse house gas (GHG) relative to that of a ‘reference’ gas (CO₂). Under the Kyoto Protocol, GWP can be used as a fixed index to govern the trade-off between different GHGs in a multi-gas approach to GHGs abatement. The use of fixed GWPs has been criticized for not being very cost effective compared to the use of some flexible indices. To gain wider acceptance, however, a flexible index must also prove to be easy to use, and the economic gains from its adoption must be significant. In this paper, we develop a flexible index based on the concept of marginal rather than cumulative or average global warming potentials. These marginal global warming potentials (MGWPs) can be endogenously determined within a climate model given a particular climate objective based on radiative forcing level. The MGPWs are then linked to the marginal abatement costs of the GHGs, which are also endogenously determined within an economic model. When the two concepts are linked in this way, the result is a cost-effective way of achieving a particular climate change objective with multigas abatement. We show that the savings in costs when using this flexible MGPWs can be significant, and more importantly, they are not uniformly distributed across different regions.

The Benefits of Cooperation Under Uncertainty: the Case of Climate Change

This article presents an analysis of the behaviour of countries defining their climate policies in an uncertain context. The analysis is made using the S-CWS model, a stochastic version of an integrated assessment growth model. The model includes a stochastic definition of the climate sensitivity parameter. We show that the impact of uncertainty on policy design critically depends on the shape of the damage function. We also examine the benefits of cooperation in the context of uncertainty: We highlight the existence of an additional benefit of cooperation, namely risk reduction.     

Improving Efficiency Of Uncertainty Analysis In Complex Integrated Assessment Models: The Case Of The Rains Emission Module

Abstact Ever since the Regional Acidification Information and Simulation Model (RAINS) has been constructed, the treatment of uncertainty has remained an issue of major interest. In a recent review of the model performed for the Clean Air for Europe (CAFE) programme of the European Commission, a more systematic and structured uncertainty analysis has been recommended. This paper aims at contributing to the scientific debate how this can be achieved. Because of its complex structure on the one hand and limited research resources (time, computational capacities) on the other hand a full-blown uncertainty analysis in RAINS is hardly feasible. Therefore, all types of uncertainty require more efficient ways for uncertainty analysis. With respect to parameter uncertainty, we propose to focus research efforts for uncertainty analysis on key parameters. Among different approaches to select key parameters that have been discussed in the literature screening methods seem to be particularly appropriate for complex, deterministic Integrated Assessment models such as RAINS. Surprisingly, in Integrated Assessment modelling for air pollution problems of screening design have not been taken up so far. As a case study we consider the emission module of RAINS. We show that its structure allows for a straightforward and effective screening procedure     

Human Capital,Innovation, and Climate Policy: an Integrated Assessment

This paper looks at the interplay between human capital and innovation when climate and educational policies are implemented. Following recent empirical studies, human capital and general purpose research and development (R&D) are introduced in an integrated assessment model used to study the dynamics of climate change mitigation. Our results suggest that climate policy stimulates general purpose as well as clean R&D but reduces the incentive to invest in human capital formation. Both innovation and human capital have a scale effect, which increases pollution, as well as a technique effect, which saves emissions for each unit of output produced. While the energy-saving effect prevails when innovation increases, human capital is pollution-using, also because of the gross complementarity between the labor and energy input. When the role of human capital is the key input in the production of general purpose and energy knowledge is accounted for, the crowding-out of education induced by climate policy is mitigated, though not completely offset. By contrast, a policy mix that combines educational as well as climate objectives offsets the human capital crowding-out, at moderate and short-term costs. Over the long run, the policy mix leads to global welfare gains.     

气候变化下的新疆生态环境脆弱性评价

选取了脆弱性、适应能力作为影响新疆生态环境脆弱性的条件层,进一步筛选出海拔、地质环境、沙尘暴、人口密度、降水量、植被类型、生态保护政策7个因子作为成因指标层,并用专家打分法对每个指标赋予权重。将研究区剖分成195个评价单元格,借助G玛强大的数据管理功能,建立与空间数据和属性数据相互关联的生态环境脆弱性数据库;首次采用模糊数学层次分析法作为新疆生态环境脆弱性等级计算的数学模型,计算出新疆生态环境脆弱性等级,并借助CIS进行成果表达。     

Assessment of Climate Change Effects on Canada's National Park System

To estimate the magnitude of climate change anticipated forCanada's 38 National Parks (NPs) and Park Reserves, seasonaltemperature and precipitation scenarios were constructed for 2050and 2090 using the Canadian Centre for Climate Modelling andAnalysis (CCCma) coupled model (CGCM1). For each park, we assessed impacts on physical systems, species, ecosystems andpeople. Important, widespread changes relate to marine andfreshwater hydrology, glacial balance, waning permafrost, increased natural disturbance, shorter ice season, northern andupward altitudinal species and biome shifts, and changed visitation patterns. Other changes are regional (e.g., combinedEast coast subsidence and sea level rise increase coastal erosionand deposition, whereas, on the Pacific coast, tectonic upliftnegates sea level rise). Further predictions concern individualparks (e.g., Unique fens of Bruce Peninsular NP will migratelakewards with lowered water levels, but structural regulation of Lake Huron for navigation and power generation would destroythe fens). Knowledge gaps are the most important findings. Forexample: we could not form conclusions about glacial massbalance, or its effects on rivers and fjords. Likewise, for theEast Coast Labrador Current we could neither estimate temperature and salinity effects of extra iceberg formation, nor the further effects on marine food chains, and breeding park seabirds. We recommend 1) Research on specific large knowledge gaps; 2) Climate change information exchange with protected area agencies in other northern countries; and 3) incorporating climate uncertainty into park plans and management. We discuss options for a new park management philosophy in the face of massive change and uncertainty.     

Integrated Environmental Assessment of the Mid-Atlantic Region with Analytical Network Process

A decision analysis method for integrating environmental indicators was developed. This was a combination of Principal Component Analysis (PCA) and the Analytic Network Process (ANP). Being able to take into account the interdependency among variables, the method was capable of ranking ecosystems in terms of environmental conditions and suggesting cumulative impacts across a large region. Using data on land cover, population, roads, streams, air pollution, and topography of the Mid-Atlantic Region of the United States, we were able to point out areas which were in relatively poor condition and/or vulnerable to future deterioration regarding various environmental aspects. The method offered an easy and comprehensive way to combine the strengths of conventional multivariate statistics (PCA) and decision-making science tool (ANP) for integrated environmental assessment.     

Meat,Dairy and Climate Change: Assessing the Long-Term Mitigation Potential of Alternative Agri-Food Consumption Patterns in Canada

We use a newly developed model of the entire Canadian energy system (TIMES-Canada) to assess the climate change mitigation potential of different agri-food consumption patterns in Canada. For this, our model has been extended by disaggregating the agricultural demand sector into individual agri-food demands to allow for a more in-depth analysis. Besides a business-as-usual (baseline) scenario, we have constructed four different agri-food scenarios to assess the viability of reducing Canadian meat and dairy consumption in order to diminish Canada’s agricultural sector energy consumption and greenhouse gas (GHG) emissions. Our policy scenarios progressively restrict the consumption of different meat and dairy agricultural products until the year 2030. Our results suggest that the implementation of a meat and dairy consumption reduction policy would lead to a 10 to 40 % reduction in agricultural GHG emissions, depending on the severity of the scenario. This translates to a 1 to 3 % decrease in total Canadian GHG emissions by the year 2030. Besides these environmental benefits, health benefits associated with a reduction in meat and dairy consumption (as inferred from other studies) are presented as an additional source of motivation for implementing such a policy in Canada.     

Comparative Assessment of Climate Change Scenarios Based on Aquatic Food Web Modeling

In the years 2004 and 2005, we collected samples of phytoplankton, zooplankton, and macroinvertebrates in an artificial small pond in Budapest (Hungary). We set up a simulation model predicting the abundances of the cyclopoids, Eudiaptomus zachariasi, and Ischnura pumilio by considering only temperature and the abundance of population of the previous day. Phytoplankton abundance was simulated by considering not only temperature but the abundances of the three mentioned groups. When we ran the model with the data series of internationally accepted climate change scenarios, the different outcomes were discussed. Comparative assessment of the alternative climate change scenarios was also carried out with statistical methods.     

Spatial Validation of Land Use Change Models Using Multiple Assessment Techniques: A Case Study of Transition Potential Models

Using land use and cover change (LUCC) models for the urban growth planning, environmental assessment, and decision-making needs the establishment of an appropriate level of confidence in their performance. The objective of this research is to explore the importance of using multiple assessment techniques in order to fairly evaluate the performance of land use models. An application is conducted by using the Land Change Modeler for Ecological Sustainability (LCM) which is an empirical and transition potential model. LCM is applied to model the agricultural to developed areas transition in Rennes metropolitan area (France). The land demand is estimated using the Markov Chain model; whereas, the transition potential map is implemented using the Multi-Layer Perceptron Neural Network (MLP) method based on historical changes and driving variables. The model performance is assessed based on a variety of the most commonly used validation techniques. At the study area level, the correctness and disagreement analysis shows that LCM performs better at predicting the amount than the allocation of developed areas. Additionally, landscape metrics reveal that LCM tends to predict a fragmented urban form, which seems evident because of the large number of the individual urban patches. At the municipality level, the error budget analysis shows that the model performance, which varies highly between different subareas, needs to be improved. Moreover, the cross-tabulation between the transition potential map and both the observed and the predicted agricultural to developed areas transitions reveals that the order of the transition potential values does not perfectly fit the observed change; whereas, the predicted change is not solely limited to areas with high potential.     

Climate Change and Climate Variability: Adaptations to Reduce Adverse Health Impacts

Global climate change is likely to have a range of consequences for human health as a result of disturbance or weakening of the biosphere's natural or human-managed life support systems. The full range of potential human health impacts of global climate change is diverse and would be distributed differentially spatially and over time. Changes in the mortality toll of heatwaves and changes in the distribution of vector-borne infectious diseases may occur early. The public health consequences of sea level rise and of regional changes in agricultural productivity may not occur (or become apparent) for several decades. Vulnerability is a measure of both sensitivity to climate change and the ability to adapt in anticipation of, or in response to, its impacts. The basic modes of adaptation to climate-induced health hazards are biological, behavioural and social. Adaptation can be undertaken at the individual, community and whole-population levels. Adaptive strategies should not introduce new health hazards. Enhancement of the acknowledged public health infrastructure and intervention programmes is essential to reduce vulnerability to the health impacts of climate change. In the longer-term, fundamental improvements in the social and material conditions of life and in the reduction of inequalities within and between populations are required for sustained reduction in vulnerability to environmental health hazards.     

A General Equilibrium Assessment of Climate Change Impacts on Swiss Winter Tourism with Adaptation

Winter alpine tourism has been repeatedly identified as one of the economic sectors most at risk from climate change in Switzerland. However, all of the costs that have been estimated so far for the Swiss tourism sector are, to some extent, misleading as they do not, or only partially, incorporate adaptation possibilities and general equilibrium effects. We attempt to fill this gap using a computable general equilibrium model that is specifically designed for the purposes of this research. Our modeling efforts first consist in creating a tourism sector with a part of it being dependent on snow. We also carefully model the snowmaking technology. Using climate change scenarios on future snow cover, we analyze their impacts on the Swiss ski industry. We find welfare effects for the Swiss economy ranging from − 23 to 113 million CHF in 2050. This range arises from the use of various assumptions concerning adaptation possibilities. We also show that geographical substitutions between international ski destinations have large positive effects for Switzerland. From a more general perspective, our results exemplify the risks of estimating the consequences of climate change based only on domestic impacts of climate change with no adaptation being implemented.

     

Managing Uncertainty in Risk-Based Corrective Action Design: Global Sensitivity Analysis of Contaminant Fate and Exposure Models Used in the Dose Assessment

A variance-based global sensitivity analysis (GSA) was applied to the dose assessment model used in the risk-based corrective action methodology of environmental risk analysis to identify key sources of variability and uncertainty and quantify the relative contribution of these sources to the variance of estimated dose. GSA was performed applying extended Fourier amplitude sensitivity test technique. The soil-to-air contaminant transport pathway within an inhalation exposure scenario was addressed. Three persistent semi-volatile carcinogenic chemicals, including polychlorinated biphenyls, benzo(a)pyrene, and 2,3,7,8-tetrachlorodibenzo-p-dioxin, were chosen as contaminants of concern.     

Climate Change: Use of Non-Homogeneous Poisson Processes for Climate Data in Presence of a Change-Point

Environmental Modeling & Assessment - In this study, non-homogeneous Poisson processes (NHPP) are used to analyze climate data. The data were collected over a certain period time and consist of...