What role do climate considerations play in consumption of red meat in Norway?

Reducing emissions of greenhouse gases is facilitated by changes in several consumption activities, such as food choices. This paper examines factors explaining red meat consumption in Norway, especially the role of climate concerns. The paper adds to our knowledge as most existing analyses of (red) meat consumption focus on health and animal welfare issues. Moreover, it expands our understanding by drawing on perspectives from both institutional and social psychological theory, including variables emphasizing the social dynamics behind consumption decisions. The study is based on data from a survey of 2000 people aged 18 years or older conducted in 2018. The data are analyzed using structural equation modelling. We find that there is a strong pro-meat culture in Norway, currently rather weakly influenced by climate concerns – specifically, personal norms and social pressures focused on reducing climate impacts. Instead, habits, beliefs about the qualities of red meat (being tasteful, nutritious, healthy) and social norms supporting red meat consumption are the three most important factors explaining the variation observed. Gender and income also influence red meat consumption, but less than found in other studies. The paper discusses policy implications of these findings, including for taxation, point-of-sale information and communicative processes to support changes in the perceptions of what could be a new “normal” diet.     

Biomass strategies for climate policies?

Abstract

This paper discusses the results of the BEAP linear programming model that has been developed to study the optimal use of biomass and land for greenhouse gas emission reduction, notably the competition between food production, biomass production for energy and materials and afforestation. The model results suggest up to 100 EJ biomass use in case of global policies (about 20% of global primary energy use). The biomass is used for industrial and residential heating, transportation fuels and as a feedstock for plastics. In the electricity markets competing emission reduction options are more cost-effective than biomass. In case the Kyoto protocol is continued beyond 2010 the developed countries can rely in 2020–2030 on afforestation and land use change credits from developing countries, without any major use of other emission reduction strategies. However, in case of a planning perspective of more than half a century bioenergy is preferred instead of afforestation. The results indicate a limited impact on global agricultural trade, but food demand may be affected by CO₂ policies.     

What spatial scales are believable for climate model projections of sea surface temperature?

Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (<8°). Our findings suggest that output from current generation ESMs is not yet suitable for making sub-regional projections of change in coral bleaching frequency and other marine processes linked to SST warming.     

What role for social–ecological systems research in governing global teleconnections?

The paper considers the extent to which social–ecological systems research might contribute to an improved understanding of the social and environmental impacts of teleconnections inherent in economic globalisation. Recognising the importance and specificity of regional interconnections, wherein actions in certain parts of the world impact quite specifically on the sustainability of certain other spatially distant places and systems, the paper reflects on the social and environmental implications of increasingly interconnected agri-food systems and intersecting global commodity chains. Key elements of social–ecological systems approaches, which have purported relevance to research on globalisation, are critically examined, and aspects of social–ecological systems thinking that pose challenges for its application in this context are considered. Wider implications and limitations of social–ecological systems approaches to research and practice in (global) governance for sustainability are discussed. The general conclusion is that social–ecological systems research may offer insights into the governance of social and environmental impacts of agri-food systems and other complex systems at certain scales. However, the formal utility of concepts like resilience, vulnerability and adaptability becomes considerably less clear as research turns to analyses of larger, complex, globally teleconnected systems, where the main contribution of such concepts may lie in their metaphorical appeal to important aspects of interconnectivity and interdependence.     

A role for icebergs in the 8.2 ka climate event

We investigate the potential role of icebergs in the 8.2 ka climate event, using a coupled climate model equipped with an iceberg component. First, we evaluate the effect of a large iceberg discharge originating from the decaying Laurentide ice sheet on ocean circulation, compared to a release of an identical volume of freshwater alone. Our results show that, on top of the freshwater effect, a large iceberg discharge facilitates sea-ice growth as a result of lower sea-surface temperatures induced by latent heat of melting. This causes an 8% increased sea-ice cover, 5% stronger reduction in North Atlantic Deep Water production and 1°C lower temperature in Greenland. Second, we use the model to investigate the effect of a hypothetical two-stage lake drainage, which is suggested by several investigators to have triggered the 8.2 ka climate event. To account for the final collapse of the ice-dam holding the Laurentide Lakes we accompany the secondary freshwater pulse in one scenario with a fast 5-year iceberg discharge and in a second scenario with a slow 100-year iceberg discharge. Our experiments show that a two-stage lake drainage accompanied by the collapsing ice-dam could explain the anomalies observed around the 8.2 ka climate event in various climate records. In addition, they advocate a potential role for icebergs in the 8.2 ka climate event and illustrate the importance of latent heat of melting in the simulation of climate events that involve icebergs. Our two-stage lake drainage experiments provide a framework in the discussion of two-stage lake drainage and ice sheet collapse.     

What explains public support for climate policies? A review of empirical and experimental studies

The lack of broad public support prevents the implementation of effective climate policies. This article aims to examine why citizens support or reject climate policies. For this purpose, we provide a cross-disciplinary overview of empirical and experimental research on public attitudes and preferences that has emerged in the last few years. The various factors influencing policy support are divided into three general categories: (1) social-psychological factors and climate change perception, such as the positive influences of left-wing political orientation, egalitarian worldviews, environmental and self-transcendent values, climate change knowledge, risk perception, or emotions like interest and hope; (2) the perception of climate policy and its design, which includes, among others, the preference of pull over push measures, the positive role of perceived policy effectiveness, the level of policy costs, as well as the positive effect of perceived policy fairness and the recycling of potential policy revenues; (3) contextual factors, such as the positive influence of social trust, norms and participation, wider economic, political and geographical aspects, or the different effects of specific media events and communications. Finally, we discuss the findings and provide suggestions for future research.

Policy relevance

Public opinion is a significant determinant of policy change in democratic countries. Policy makers may be reluctant to implement climate policies if they expect public opposition. This article seeks to provide a better understanding of the various factors influencing public responses to climate policy proposals. Most of the studied factors include perceptions about climate change, policy and its attributes, all of which are amenable to intervention. The acquired insights can thus assist in improving policy design and communication with the overarching objective to garner more public support for effective climate policy.     

International low carbon technology transfer: Do intellectual property regimes matter?

Transfer of low carbon technologies to developing countries has been recognized as important in global efforts to limit climate change. Yet the mechanics of international technology transfer, especially around intellectual property rights, have remained a controversial issue in international negotiations. Using a new dataset on international partnerships in China and India in three key low carbon technologies—solar photovoltaics, electric vehicles, and coal gasification/integrated gasification combined cycle—and complementary expert interviews we study the dynamics of the transfer of intellectual property and the underlying drivers that guide the development of business strategies and partnerships in the context of transitioning intellectual property regimes in emerging markets. We find that weak intellectual property regimes are indeed a hindrance to the diffusion of certain classes of low carbon technologies: (i) for cutting-edge technologies, (ii) for fully-embodied (explicitly codified) technologies, and (iii) for small firms. However, we also find that intellectual property issues do not represent a barrier to the diffusion of the relatively mature and low to medium cost low carbon technologies that are materially (at scale) most important for carbon dioxide emissions reduction in the short to medium term. Competitive technology supply, shifting market dynamics, and increasingly vigorous domestic innovation coupled with mechanisms and opportunities to structure credible intellectual property deals allow for the diffusion of key low carbon technologies to occur within the context of existing business, political, and institutional structures.     

Subjective measures of climate resilience: What is the added value for policy and programming?

Subjective approaches to resilience measurement are gaining traction as a complementary approach to the standard frameworks that typically contain objective measures. Proponents suggest that subjective approaches may add value to existing measures in three areas: by improving our understanding of the drivers of resilience, reducing the questionnaire burden on respondents, and potentially offering more valid cross-cultural comparisons. This perspective assesses the potential, evidence and uncertainties around each of these claims, drawing from decades of research using subjective techniques in the wellbeing and psychological resilience literatures. Overall we find that subjective approaches can theoretically add value in each of these three areas. However the design of appropriate indicators must proceed with specificity and rigour for subjective measures to add value to programming and policy for climate resilience.     

How harmful are restrictions on adapting to climate change?

The dominant assumption in economic models of climate policy remains that adaptation will be implemented in an optimal manner. There are, however, several reasons why optimal levels of adaptation may not be attainable. This paper investigates the effects of suboptimal levels of adaptation caused by different types of adaptation restrictions, on the composition and level of climate change costs and on welfare. We find that especially restrictions to the effectiveness of adaptation at more extreme levels of climate change can be very harmful. Furthermore we show that the potential of mitigation to offset suboptimal adaptation varies from being essential in case adaptation becomes ineffective at higher temperature increases, to being largely ineffective in case of short-term inaction. However, in all cases the short-term recommendation is to increase mitigation levels slightly above what is normally recommended, and to keep mitigation policies flexible enough to be able to respond when adaptation restrictions become more prominent. It is clear that by reducing adaptation restrictions, in combination with adjusting the optimal level of mitigation may keep the costs of adaptation restrictions limited, and thus generally it is very harmful to ignore existing restrictions on adaptation when devising (efficient) climate policies.     

What determines perceived value of seasonal climate forecasts? A theoretical analysis

Seasonal forecasts have potential value as tools for the management of risks due to inter-annual climate variability and iterative adaptation to climate change. Despite their potential, forecasts are not widely used, in part due to poor performance and lack of relevance to specific users’ decision problems, and in part due to a variety of economic and behavioural factors. In this paper a theoretical model of perceived forecast value is proposed and applied to a stylized portfolio-type decision problem with wide applicability to actual forecast users, with a view to obtaining a more complete picture of the determinants of perceived value. The effects of user wealth, risk aversion, and perceived forecast trustworthiness, and presentational parameters, such as the position of forecast parameter categories, and the size of probability categories, on perceived value is investigated. Analysis of the model provides several strong qualitative predictions of how perceived forecast value depends on these factors. These predictions may be used to generate empirical hypotheses which offer the chance of evaluating the model's assumptions, and suggest several means of improving understanding of perceived value based on qualitative features of the results.     

The impact of future climate change on West African crop yields: What does the recent literature say?

In West Africa, agriculture, mainly rainfed, is a major economic sector and the one most vulnerable to climate change. A meta-database of future crop yields, built up from 16 recent studies, is used to provide an overall assessment of the potential impact of climate change on yields, and to analyze sources of uncertainty.Despite a large dispersion of yield changes ranging from −50% to +90%, the median is a yield loss near −11%. This negative impact is assessed by both empirical and process-based crop models whereas the Ricardian approach gives very contrasted results, even within a single study. The predicted impact is larger in northern West Africa (Sudano-Sahelian countries, −18% median response) than in southern West Africa (Guinean countries, −13%) which is likely due to drier and warmer projections in the northern part of West Africa. Moreover, negative impacts on crop productivity increase in severity as warming intensifies, with a median yield loss near −15% with most intense warming, highlighting the importance of global warming mitigation.The consistently negative impact of climate change results mainly from the temperature whose increase projected by climate models is much larger relative to precipitation change. However, rainfall changes, still uncertain in climate projections, have the potential to exacerbate or mitigate this impact depending on whether rainfall decreases or increases. Finally, results highlight the pivotal role that the carbon fertilization effect may have on the sign and amplitude of change in crop yields. This effect is particularly strong for a high carbon dioxide concentration scenario and for C3 crops (e.g. soybean, cassava). As staple crops are mainly C4 (e.g. maize, millet, sorghum) in WA, this positive effect is less significant for the region.     

What will a new generation of world climate research and computing facilities bring to climate long-term predictions?

Based on issues recently raised on the future of climate science, I present here a critical discussion which embraces the crucial aspects of the communication between climate scientists and laypersons, of the role confusing statements may exert on possible advancements in climate research, and of scientific priorities in climate science. I start distinguishing between different applications of climate models and identifying confusing uses of the words ??prediction?? and ??projection?? in recent discussions on climate modeling. Numerical models like those used in climate simulations are not assimilable to truly theories, nor can obtained results be considered as truly experimental evidences. Hence, it is hard to envisage the feasibility of crucial experiments through climate models. Increasing model resolution and complexity, although undoubtedly helpful for many applications related to a deeper understanding of the complex climate system and to substantial improvement of short-term forecasts, is not destined to change this fundamental limitation, to tackle the impossibility of predicting prominent climate forcings and to facilitate result comparisons against observations. Finally, as an example describing possible alternative resource allocations, I propose to devote more energy to strengthen the observational part of climate research, to focus on midterm forecasts, and to implement a new employment policy for climate scientists. In particular, through an increased and truly global in situ and remote sensing climate observing network, crucial experiments could emerge to challenge the fundamental basis of the conjecture of a great anthropogenic climate change, which, as known, is largely based on high climate sensitivities simulated by numerical models.     

What are robust strategies in the face of uncertain climate threshold responses?

We use an integrated assessment model of climate change to analyze how alternative decision-making criteria affect preferred investments into greenhouse gas mitigation, the distribution of outcomes, the robustness of the strategies, and the economic value of information. We define robustness as trading a small decrease in a strategy’s expected performance for a significant increase in a strategy’s performance in the worst cases. Specifically, we modify the Dynamic Integrated model of Climate and the Economy (DICE-07) to include a simple representation of a climate threshold response, parametric uncertainty, structural uncertainty, learning, and different decision-making criteria. Economic analyses of climate change strategies typically adopt the expected utility maximization (EUM) framework. We compare EUM with two decision criteria adopted from the finance literature, namely Limited Degree of Confidence (LDC) and Safety First (SF). Both criteria increase the relative weight of the performance under the worst-case scenarios compared to EUM. We show that the LDC and SF criteria provide a computationally feasible foundation for identifying greenhouse gas mitigation strategies that may prove more robust than those identified by the EUM criterion. More robust strategies show higher near-term investments in emissions abatement. Reducing uncertainty has a higher economic value of information for the LDC and SF decision criteria than for EUM.     

What makes internationally-financed climate change adaptation projects focus on local communities? A configurational analysis of 30 Adaptation Fund projects

There is much scholarly and policy interest in the role that international finance could play in closing the financing gap for community adaptation initiatives. Despite the interest, the overall amount of international adaptation finance that has reached local recipients remains low. What makes internationally-financed climate change adaptation projects focus on investment at the community level is particularly poorly understood. This study systematically assesses conditions that influence the focus on vulnerable local communities in internationally-financed adaptation projects. Using the Adaptation Fund (AF) under the Kyoto Protocol as the case study, we apply fuzzy-set Qualitative Comparative Analysis (QCA) to analyze 30 AF projects to identify specific configurations of conditions that lead to a stronger or weaker community focus in project design. We find that the absence of high exposure to projected future climate risks is a necessary condition for a weaker community focus in AF projects. Three configurations of sufficient conditions are identified that lead to a stronger community focus. They involve the contextual factors of projected future climate risks, civil society governance, and access modality to AF financing. In particular, AF projects with a stronger community focus are stimulated by the sole presence of higher exposure to projected future climate risks in a group of countries, and by the complementary roles of civil society governance and the access modality to the AF in others. These findings contribute new insights on how to enhance local inclusiveness of global climate finance.