Marco A. Janssen

This study argues that scholars and policy-makers need to understand environmental activists better to bridge the gap between growing activism and policy. Conventional wisdom is that environmental activists generally support stronger climate policies. But there is still little understanding about diversity of views within activist groups when it comes to specific policies, and existing studies indicate that their views are not uniform, which can weaken their impact as a group. Activists might unite to demand change, but not necessarily agree on details of the desired change. Exploring the differences within the group, this paper focuses on how to nudge those who already share favorable attitudes towards policies that mitigate climate change. The motivation has been to see, in presence of general support for stronger environmental policies, whether this support could be channeled into more specific policies. We first take on a methodological challenge to construct an index of environmental predisposition. Then drawing from existing social-behavioral scholarship, we analyze results of an experimental survey with select treatments previously reported as promising. In November and December 2019, we collected responses from 119 participants at the Fridays for Future demonstrations in Germany. The results indicate that there are indeed important differences within the group, and nudging effects exist even in this rather strongly predisposed group, with participants assigned to the experimental group showing higher levels of support for the introduction of a carbon tax that is traditionally seen as a difficult policy to gain widespread public support. We find that those who score neither too high nor too low are more likely to respond to nudging. Yet, the effects vary for general outcomes such as policy support, behavioral intentions, and environmental citizenship. Overall, the findings show the value of understanding the heterogeneity of individual views within environmental movements better and directing interventions in large resource systems such as climate to specific issues and target groups for accelerating transformations towards sustainability.

The unprecedented use of Earth’s resources by humans, in combination with increasing natural variability in natural processes over the past century, is affecting the evolution of the Earth system. To better understand natural processes and their potential future trajectories requires improved integration with and quantification of human processes. Similarly, to mitigate risk and facilitate socio-economic development requires a better understanding of how the natural system (e.g. climate variability and change, extreme weather events, and processes affecting soil fertility) affects human processes. Our understanding of these interactions and feedback between human and natural systems has been formalized through a variety of modelling approaches. However, a common conceptual framework or set of guidelines to model human–natural-system feedbacks is lacking. The presented research lays out a conceptual framework that includes representing model coupling configuration in combination with the frequency of interaction and coordination of communication between coupled models. Four different approaches used to couple representations of the human and natural system are presented in relation to this framework, which vary in the processes represented and in the scale of their application. From the development and experience associated with the four models of coupled human–natural systems, the following eight lessons were identified that if taken into account by future coupled human–natural-systems model developments may increase their success: (1) leverage the power of sensitivity analysis with models, (2) remember modelling is an iterative process, (3) create a common language, (4) make code open-access, (5) ensure consistency, (6) reconcile spatio-temporal mismatch, (7) construct homogeneous units, and (8) incorporating feedback increases non-linearity and variability. Following a discussion of feedbacks, a way forward to expedite model coupling and increase the longevity and interoperability of models is given, which suggests the use of a wrapper container software, a standardized applications programming interface (API), the incorporation of standard names, the mitigation of sunk costs by creating interfaces to multiple coupling frameworks, and the adoption of reproducible workflow environments to wire the pieces together.

The rapid environmental changes currently underway in many dry regions of the world, and the deep uncertainty about their consequences, underscore a critical challenge for sustainability: how to maintain cooperation that ensures the provision of natural resources when the benefits of cooperating are variable, sometimes uncertain, and often limited. In this work, we present the case of a group of rural communities in a semi-desert region of Chile, where cooperation in the form of labor-sharing has helped maintain higher agriculture yields, group cohesion, and identity. Today, these communities face the challenge of adapting to recurrent droughts, extreme rainfall, and desertification. We formulated an agent-based model to investigate the consequences of regional climate changes on the fate of these labor-exchange institutions. The model, implemented in the framework of prospect theory, simulates the economic decisions of households to engage, or not, in labor-sharing agreements under different scenarios of water supply, water variability, and socio-environmental risk. Results show that the number of fulfilled labor-sharing agreements is reduced by water scarcity and environmental variability. More importantly, defections that involve non-fulfillment of these agreements are more likely to emerge at the intermediate level of environmental variability and water supply stress. These results underscore the need for environmental policy instruments that consider the effects of regional climate changes on the social dynamics of these communities.

The planetary boundary framework constitutes an opportunity for decision makers to define climate policy through the lens of adaptive governance. Here, we use the DICE model to analyze the set of adaptive climate policies that comply with the two planetary boundaries related to climate change: (1) staying below a CO₂ concentration of 550 ppm until 2100 and (2) returning to 350 ppm in 2100. Our results enable decision makers to assess the following milestones: (1) a minimum of 33% reduction of CO₂ emissions by 2055 in order to stay below 550 ppm by 2100 (this milestone goes up to 46% in the case of delayed policies); and (2) carbon neutrality and the effective implementation of innovative geoengineering technologies (10% negative emissions) before 2060 in order to return to 350 ppm in 2100, under the assumption of getting out of the baseline scenario without delay. Finally, we emphasize the need to use adaptive path-based approach instead of single point target for climate policy design.

Improving the adaptive capacity of small-scale irrigation systems to the impacts of climate change is crucial for food security in Asia. This study analyzes the capacity of small-scale irrigation systems dependent on the Asian monsoon to adapt to variability in river discharge caused by climate change. Our study is motivated by the Pumpa irrigation system, a small-scale irrigation system located in Nepal that is a model for this type of system. We developed an agent-based model in which we simulated the decisions farmers make about the irrigation strategy to use according to available water flow. Given the uncertainty associated with how climate change may affect the Asian monsoon, we simulated the performance of the system under different projections of climate change in the region (increase and decrease in rainfall, reduction and expansion of the monsoon season, and changes in the timing of the onset of the monsoon). Accordingly to our simulations, farmers might need to adapt to rainfall intensification and a late onset in the monsoon season. The demands for collective action among farmers (e.g. infrastructure repair, meetings, decisions, etc.) might increase considerably due to climate change. Although our model suggests that investment in new infrastructure might increase the performance of the system under some climate change scenarios, the high inequality among farmers when water availability is reduced might hinder the efficiency of these measures due to a reduction of farmers’ willingness to cooperate. Our modeling exercise helps to hypothesize about the most sensitive climate change scenarios for smallscale irrigation farming in Nepal and helps to frame a discussion of some possible solutions and fundamental trade-offs in the process of adaptation to improve for food and water security under climate change.

Keywords: Adaptation; Agent-based model; Climate change; Common-pool resources; Irrigation systems; Resilience

A sequential optimization approach is applied to optimize the behavior of a complex dynamical system. It sequentially solves a large set of mathematical equations and next optimizes the behavior of a reduced-system, fixing certain variables of the larger original problem. These two steps are repeated till convergence occurs. The approach is applied to the problem of identifying response strategies for climate change caused by antropogenic emissions of different trace gases. The convergence properties are analyzed for this example.

Keywords: Sequential optimization; Sequential reduced-system programming; Dynamical system.

This article describes a greenhouse gas (GHG) emissions scenario for a world that chooses collectively and effectively to pursue service-oriented economic prosperity while taking into account equity and environmental concerns, but without policies directed at mitigating climate change. After peaking around 2050 at 2.2 times the 1990 level of primary energy use, a number of factors lead to a primary energy use rate at the end of the next century that is only 40% higher than the 1990 rate. Among these factors are a stabilizing (and after 2050, declining) population, convergence in economic productivity, dematerialization and technology transfer, and high-tech innovations in energy use and supply. Land use-related emissions show a similar trend. Total CO₂ emissions peak at 12.8 CtC/yr around 2040, after which they start falling off. Other GHG emissions show a similar trend. The resulting CO₂-equivalent concentration continues to rise to about 600 ppmv in 2100. Present understanding of climate change impacts suggest that even in this world of high-tech innovations in resource use in combination with effective global governance and concern about equity and environment issues, climate policy is needed if mankind is to avoid dangerous interference with the climate system.

In this paper, we present results of simulationexperiments with the TIME-model on the issue ofmitigation strategies with regard to greenhouse gases.The TIME-model is an integrated system dynamics worldenergy model that takes into account the fact that the systemhas an inbuilt inertia and endogenouslearning-by-doing dynamics, besides the more commonelements of price-induced demand response and fuelsubstitution. First, we present four scenarios tohighlight the importance of assumptions on innovationsin energy technology in assessing the extent to whichCO2 emissions have to be reduced. The inertia ofthe energy system seems to make a rise ofCO2 emissions in the short term almostunavoidable. It is concluded that for the populationand economic growth assumptions of the IPCC IS92ascenario, only a combination of supply- anddemand-side oriented technological innovations incombination with policy measures can bring the targetof CO2-concentration stabilization at 550 ppmv bythe year 2100 within reach. This will probably beassociated with a temporary increase in the overallenergy expenditures in the world economy. Postponingthe policy measures will be more disadvantageous,and less innovation in energy technology will happen.

Many uncertainties and controversies surround the future of the global energy system. The Targets Image Energy (TIME) model of which a concise description is given, is used to explore the consequences of divergent assumptions about some uncertain and controversial issues. The IPCC-IS92a Conventional Wisdom scenario is used as a reference and, in combination with two other scenarios, discussed in the context of other recently published global energy scenarios.

Keywords: Global energy scenarios; Energy modelling; Climate change.

Global modeling has been used for decades to assess the possible futures of humanity and the global environment. However, these models do not always satisfactorily include the adaptive characteristics of systems. In this article, a general approach is used to simulate change and transition at a macrolevel due to adaptation at a microlevel. Tools from complex adaptive systems research are used to simulate the microlevel and consequently determine parameter values of the equation-based macrolevel model. Two case studies that applied this approach are reviewed. The first study assessed the efficacy of efforts to control malaria, whereas the second study used an integrated model to construct climate change scenarios by using various possible views on the nature of the climate system.

Key words: complex adaptive systems; global change; climate change; malaria; multiagent modeling; adaptation; coevolution; genetic algorithms.

To evaluate possible futures with regard to economy, energy and climate, a multi-agent modelling approach is used. Agents hold different perspectives on how the world functions (worldview) and how it should be managed (management style) and this is implemented in a simple dynamic model of the economy-energy-climate system. Each perspective is supported by a proportion of the agents, but this proportion changes in response to observations about the real world. In this way the totality of agents learn from their observations. It is concluded that this approach is a good illustration of how adaptive behavior can be included in global change modelling. Some exploratory experiments are done to address the consequences of surprises.

Keywords: Global change; Integrated assessment modeling; Perspectives; Multi-agent modeling.

Workers at the Dutch National Institute of Public Health and the Environment (RIVM) have recently developed a new comput­ er tool called the Interactive Scenario Scanner (ISS). The tool enables users to interactively construct global greenhouse gas emission scenarios and evaluate their likely climate change impacts. In this way, the tool can be used to support a dialogue between scientists and policy makers on scenario development and help in selecting scenarios to be analysed with more sophisticated modelling tools, like RIVM’s IMAGE 2 model.

As the resistance of the malaria parasite to antimalarial drugs continues to increase, as does that of the malarial mosquito to insecticides, the efficacy of efforts to control malaria in many tropical countries is diminishing. This trend, together with the projected consequences of climate change, may prove to exacerbate substantially the significance of malaria in the coming decades.

In this article we introduce the use of an evolutionary modeling approach to simulate the adaptation of mosquitoes and parasites to the available pesticides and drugs. By coupling genetic algorithms with a dynamic malaria-epidemiological model, we derive a complex adaptive system capable of simulating adapting and evolving processes within both the mosquito and the parasite populations.

This approach is used to analyze malaria management strategies appropriate to regions of higher and lower degrees of endemicity. The results suggest that adequate use of insecticides and drugs may reduce the occurrence of malaria in regions of low endemicity, although increased efforts would be necessary in the event of a climate change. However, our model indicates that in regions of high endemicity the use of insecticides and drugs may lead to an increase in incidence due to enhanced resistance development. Projected climate change, on the other hand, may lead to a limited reduction of the occurrence of malaria due to the presence of a higher percentage of immune persons in the older age class.

We regard the global climate system as a controlled dynamic system, with controls corresponding to economic activities causing emissions of greenhouse gases. Previous optimization studies for climate change have used descriptions of the environmental system which are found to be too unrepresentative of what is known in the scientific community. In this paper an approach is applied which tries to include a more sophisticated model of the environmental system. The resulting continuous dynamic control problem is solved by the application of a set of non-linear optimization techniques to find optimal response strategies to maximize the discounted sum of future consumption while adhering to certain environmental constraints.

Keywords: Non-linear optimization; CO2; Climate change.

The development of climate change response strategies is expected to remain an important issue in the next few decades. The use of optimization techniques might serve as a helpful guide in this process. Although, in recent years, a number of studies have focused on optimization techniques, the optimization models do not fully employ the dynamics of climatic and economic systems. In this paper a heuristic is introduced that combines an integrated simulation model and an optimization technique (local search). This approach may be considered as a first step towards a more comprehensive and systematic analysis of climate change response strategies in a dynamic setting described by a simulation model. Results of a number of experiments in which the heuristic is applied to the integrated global assessment model TARGETS are discussed.

Cultural perspectives play an important role in framing international climate policy. The concept we have introduced is designed to enable quantification of the influence of such cultural perspectives on the allocation of fossil CO2 emission rights. A model is presented which allocates future emission rights to world regions. An emission budget which incorporates an historical component is defined for the specific period which is required if climate change policy targets are to be met. Allocation of the budget to regions is based on a weighted mix of indicators such as population size, GNP and energy consumption. Subtracting historical emissions results in future regional emission rights. Uncertainties in the selection of parameter values for the model and in generating scenarios of future developments are here regarded as being related to cultural perspectives. We have assumed that cultural perspectives can be quantified by reference to distributions of preferred parameter values and preferred future scenarios. Distributions of regional emission rights biased towards preferred allocations as determined by the perspectives can thus be described. In fact, the proposed approach envisages an uncertainty analysis based on the characteristics of cultural perspectives.

Keywords: Climate change; CO2; Cultural perspectives; Allocation of emission rights.

The feasibility of an effective international response to anticipated climate change is dependent on the recognition of the present and historical inequities between developing and industrialized countries. Developing countries should be enabled and supported to continue their development towards higher standards of living in a fashion that is consistent with the sustainability of the global biosphere. This paper evaluates long-term climate strategies by which the burden of mitigating climate change by controlling CO2 emissions is shared equitably. Here we use as a possible criterion of equity, that every human being, past or future, is allowed to emit the same carbon quotum on an annual basis, which, as a theoretical concept, could provide for intergenerational and international equity throughout the world. In order to do this we first define the global carbon budget as the cumulated CO2 emissions over the period 1800 till 2100, from 1990 described by an emission scenario. This budget determines the permitted CO2 emissions per capita using past and future population estimates. Next, we introduce the concept of ’emission debt’, defined by the difference between the cumulated allowed CO2 emissions, based on the permitted emission quota per capita, and the actual historical CO2 emissions. Finally the remaining carbon budget, described as the global carbon budget (1800-2100) minus the actual cumulated CO2 emissions (1800-1990) is allocated to the different world regions, taking into account the regional past CO2 emissions. This gives the future emission quota per capita. The results show that past industrialisation has coincided with a large relative contribution of the rich regions to the rise in CO2 concentration, an estimated 40 per cent for the European Community and North America, which have built up an emission debt of 36 GtC and 75 GtC, respectively, using recent World Bank projections of population growth. The developing countries, however, have built up an emission credit of 24 GtC. These regional emisson debts and credits increase the future per capita budget for the developing regions till 0.2-0.8 ton C/cap yearly, whereas North America and the EC end up with a negative future carbon budget of 0.4 to 1.5 ton C/cap yearly. Even if the IPCC Business-as-Usual scenario is considered as reference, the future emission quota of most industrialized countries are lower than their present per capita emissions, i.e, North America has a negative future carbon budget of 0.3 tC/cap yearly.

Keywords: future emissions allocation; carbon dioxide; CO2; carbon emissions; emission debt; global carbon budget; global warming; Integrated Model to Assess the Greenhouse Effect; IMAGE; sustainable climate strategies; sustainable temperature targets; sustainability; sustainable development.

Our understanding of human behavior is limited and consequently lacks a standard formal model of human behavior that could represent relevant behavior in social-ecological systems. In this paper we explore the consequences of alternative behavioral models using a simple dynamic system of agents of harvesting daisies in the well-known Daisyworld model. We explore the consequences of different behavioral assumptions and derive optimal tax policies that lead to sustainable outcomes for each of the theories.

Addressing global change demands an integrative consideration of interactions between humans and the environment on a world wide scale. An assimilative integrated system approach seems to be appropriate for investigation of this complex global problem. In this paper an integrated modeling approach is proposed that is based on an evolutionary view on global change. A case study is worked out where images of the future using a multi-agent model are assessed, and where agents differ in their world view and thus also in their preferred management style. The perspective of agents may change due to new information they derive from the system. A simple model is constructed to illustrate the consequences of this approach on climate change scenarios.

Human activities change the environment on a global level. Global modelling is used to derive insights in the interactions between humans and their environment. However, the possibility to validate those global models is limited. In fact, too little information is available, many subjective assumptions are made and a single model cannot cover all relevant scale levels and processes. These limitations already appeared in the early seventies. Current global modelling activities still deal with the same dilemma’s, often in the same way as the strongly criticised world models of the early seventies. We sketch some recent developments which can help to manage the persistent dilemma’s. We focus on the use of different modelling paradigms and on the use of different world views to analyse the consequences of subjective assumptions to be made in global models.

Keywords: global modelling, validation, complexity, uncertainty.

The safe landing analysis has been devel­ oped to link short-term greenhouse gas emission targets to longer-term climate protection goals. The analysis was applied to the climate policy goals proposed by the European Union. This application and sev­eral presentations of the analysis during the negotiations on the Kyoto Protocol led to critical but constructive discussions. In this paper we discuss some of the key questions such as policy relevance, scien­tific credibility, use and adequacy of global indicators todetermine impact levels, tech­nological feasibility and economic aspects. The results from the safe landing analysis were generally accepted by the policy community because it bridges the gap between policy needs and the under­standing derived from complex but scienti­fically rigorous integrated assessment models.The selected indicators of the safe landing analysis are evaluated. It is shown that the indicators describing rates of change are as important for defining impacts and response policies as those describing only cumulative or absolute change. Lower levels of climatic change generally coincide with lower impact levels. However, only the lowest rates and levels of climate change allow natural eco­systems to adapt. It is further shown that the level of additional energy expenditures needed to meet such low impact levels strongly depends on the assumed techno­logical development rates.

The objective of this paper is to demonstrate a methodology whereby reductions of greenhouse gas emissions can be allocated on a regional level with minimal deviation from the “business as usual emission scenario”. The methodology developed employs a two stage optimization process utilizing techniques of mathematical programming. The stage one process solves a world emission reduction problem producing an optimal emission reduction strategy for the world by maximizing an economic utility function. Stage two addresses a regional emission reduction allocation problem via the solution of an auxiliary optimization problem minimizing disruption from the above business as usual emission strategies. Our analysis demonstrates that optimal CO2 emission reduction strategies are very sensitive to the targets placed on CO2 concentrations, in every region of the world. It is hoped that the optimization analysis will help decision-makers narrow their debate to realistic environmental targets.