• Energy Research

Abstract Enhancing energy efficiency is an important goal of climate change mitigation policies. Promoting energy efficiency projects in developing countries has faced several barriers, preventing optimal investments. One of the main barriers has been the lack of internationally recognized indices to compare projects across countries. In this era of global political turbulence and a looming trade-war that will likely lead to unjustified tariffs, it is critical to provide publicly available robust indices for investors. We construct the Energy Efficiency Country Attractiveness Index to evaluate countries' competitiveness in terms of energy efficiency potentials and related investment risks to aid investment decision-making in the oil and gas sector. Our index includes 30 indicators congregated in four pillars covering political, economic, social and technological factors, combined by means of Fuzzy measures and Choquet integral according to the preferences of a panel of experts. Although experts consider the economic and technological factors as the most important elements affecting investment in the energy related projects and they are moderately tolerant following disjunctive behaviour in dealing with the political, economic, social, and technological criteria, squared correlation analysis shows that, at least for OPEC countries, the political pillar is the crucial one in shaping the composite index.

AbstractIt is generally accepted that climate change is having a negative impact on food security. However, most of the literature variously focuses on the complex and many mechanisms linking climate stressors; the links with food production or productivity rather than food security; and future rather than current effects. In contrast, we investigate the extent to which current changes in food insecurity can be plausibly attributed to climate change. We combine food insecurity data for 83 countries from the FAO food insecurity experience scale (FIES) with reanalysed climate data from ERA5-Land, and use a panel data regression with time-varying coefficients. This framework allows us to estimate whether the relationship between food insecurity and temperature anomaly is changing over time. We also control for Human Development Index, and drought measured by six-month Standardized Precipitation Index. Our empirical findings suggest that for every 1 $$^{\circ }\hbox {C}$$∘Cof temperature anomaly, severe global food insecurity has increased by 1.4% (95% CI 1.3–1.47) in 2014 but by 1.64% (95% CI 1.6–1.65) in 2019. This impact is higher in the case of moderate to severe food insecurity, with a 1 $$^{\circ }\hbox {C}$$∘Cincrease in temperature anomaly resulting in a 1.58% (95% CI 1.48–1.68) increase in 2014 but a 2.14% (95% CI 2.08–2.20) increase in 2019. Thus, the results show that the temperature anomaly has not only increased the probability of food insecurity, but the magnitude of this impact has increased over time. Our counterfactual analysis suggests that climate change has been responsible for reversing some of the improvements in food security that would otherwise have been realised, with the highest impact in Africa. Our analysis both provides more evidence of the costs of climate change, and as such the benefits of mitigation, and also highlights the importance of targeted and efficient policies to reduce food insecurity. These policies are likely to need to take into account local contexts, and might include efforts to increase crop yields, targeted safety nets, and behavioural programs to promote household resilience.

Record-breaking temperatures were recorded across the globe in 2023. Without climate action, adverse climate-related health impacts are expected to worsen worldwide, affecting billions of people. Temperatures in Europe are warming at twice the rate of the global average, threatening the health of populations across the continent and leading to unnecessary loss of life. The Lancet Countdown in Europe was established in 2021, to assess the health profile of climate change aiming to stimulate European social and political will to implement rapid health-responsive climate mitigation and adaptation actions. In 2022, the collaboration published its indicator report, tracking progress on health and climate change via 33 indicators and across five domains.

Abstract Background In the past decades, climate change has been impacting human lives and health via extreme weather and climate events and alterations in labour capacity, food security, and the prevalence and geographical distribution of infectious diseases across the globe. Climate change and health indicators (CCHIs) are workable tools designed to capture the complex set of interdependent interactions through which climate change is affecting human health. Since 2015, a novel sub-set of CCHIs, focusing on climate change impacts, exposures, and vulnerability indicators (CCIEVIs) has been developed, refined, and integrated by Working Group 1 of the “Lancet Countdown: Tracking Progress on Health and Climate Change”, an international collaboration across disciplines that include climate, geography, epidemiology, occupation health, and economics. Discussion This research in practice article is a reflective narrative documenting how we have developed CCIEVIs as a discrete set of quantifiable indicators that are updated annually to provide the most recent picture of climate change’s impacts on human health. In our experience, the main challenge was to define globally relevant indicators that also have local relevance and as such can support decision making across multiple spatial scales. We found a hazard, exposure, and vulnerability framework to be effective in this regard. We here describe how we used such a framework to define CCIEVIs based on both data availability and the indicators’ relevance to climate change and human health. We also report on how CCIEVIs have been improved and added to, detailing the underlying data and methods, and in doing so provide the defining quality criteria for Lancet Countdown CCIEVIs. Conclusions Our experience shows that CCIEVIs can effectively contribute to a world-wide monitoring system that aims to track, communicate, and harness evidence on climate-induced health impacts towards effective intervention strategies. An ongoing challenge is how to improve CCIEVIs so that the description of the linkages between climate change and human health can become more and more comprehensive.

Climate change has emerged as a growing threat to the European economy, whose economic losses are relevant for global growth. Rising temperatures and worsening extreme events are expected to affect climate-vulnerable sectors. Due to the economic integration within the European Union (EU), these impacts will likely have spillover effects and feedback loops to and from other regions. This study uses spatial econometrics to account for the interdependencies between the subnational EU regions to estimate the future impacts of changes in temperature on sectoral labour productivity under the Paris Agreement. The study confirms the presence of spatial spillover effects of climate change, and finds that observations at the economy-wide level of a non-linear, concave and single-peaked relationship between temperature and productivity do not always hold true at the sectoral level.

Abstract The impact of climate change on economic growth has been the subject of numerous studies in recent years, with macro-econometric analyses estimating the effect of rising temperatures on gross domestic product (GDP) growth rates at the country-level. However, the distributional impact of warming on inequality and poverty at the micro-level remains relatively unexplored. In this paper, we investigate the relationship between temperature and inequality in South Africa at the national and sub-national level. Our analysis reveals a significant ∪ -shaped relationship between temperature and inequality indices, with inequality lowest at moderate temperatures (11 ∘C–18 ∘C) and increasing sharply as temperatures increase. We find that the optimal temperatures are lower for inequality measures than for income levels. This indicates that substantial increases in inequality are expected at higher temperatures compared to growth impacts. This effect is particularly noticeable for the poorer segments of the population, whose productivity and wages decline as temperatures increase, while the impact on the richer segments is less significant due to their greater adaptive capacity. In terms of mechanisms, we find that agricultural households are more likely to experience an increase in inequality due to warming. Our findings suggest that global warming has two adverse effects on hot countries: reducing average growth and increasing inequality. We compare the outcomes of the moderate RCP6.0 scenario to a reference scenario without warming and find that by the end of the century, the Gini coefficient in South Africa is expected to increase by 3–6 points, resulting in a potential welfare loss of approximately 50% when combined with the impact of warming on GDP (which alone can reach up to 43% by 2100 in South Africa). Our findings highlight the importance of investigating the distributional effects of climate change at the micro-level, particularly in low- or middle-income countries where vulnerable populations are more susceptible to its impacts.

Although our knowledge of climate change impacts on energy systems has increased substantially over the past few decades, there remains a lack of comprehensive overview of impacts across spatial scales. Here, we analyse results of 220 studies projecting climate impacts on energy systems globally and at the regional scale. Globally, a potential increase in cooling demand and decrease in heating demand can be anticipated, in contrast to slight decreases in hydropower and thermal energy capacity. Impacts at the regional scale are more mixed and relatively uncertain across regions, but strongest impacts are reported for South Asia and Latin America. Our assessment shows that climate impacts on energy systems at regional and global scales are uncertain due partly to the wide range of methods and non-harmonized datasets used. For a comprehensive assessment of climate impacts on energy, we propose a consistent multi-model assessment framework to support regional-to-global-scale energy planning.