Although effects on labour is one of the most tangible and attributable climate impact, our quantification of these effects is insufficient and based on weak methodologies. Partly, this gap is due to the inability to resolve different impact channels, such as changes in time allocation (labour supply) and slowdown of work (labour productivity). Explicitly resolving those in a multi-model inter-comparison framework can help to improve estimates of the effects of climate change on labour effectiveness. In this empirical, multi-model study, we used a large collection of micro-survey data aggregated to subnational regions across the world to estimate new, robust global and regional temperature and wet-bulb globe temperature exposure-response functions (ERFs) for labour supply. We then assessed the uncertainty in existing labour productivity response functions and derived an augmented mean function. Finally, we combined these two dimensions of labour into a single compound metric (effective labour effects). This combined measure allowed us to estimate the effect of future climate change on both the number of hours worked and on the productivity of workers during their working hours under 1·5°C, 2·0°C, and 3·0°C of global warming. We separately analysed low-exposure (indoors or outdoors in the shade) and high-exposure (outdoor in the sun) sectors. We found differentiated empirical regional and sectoral ERF's for labour supply. Current climate conditions already negatively affect labour effectiveness, particularly in tropical countries. Future climate change will reduce global total labour in the low-exposure sectors by 18 percentage points (range -48·8 to 5·3) under a scenario of 3·0°C warming (24·8 percentage points in the high-exposure sectors). The reductions will be 25·9 percentage points (-48·8 to 2·7) in Africa, 18·6 percentage points (-33·6 to 5·3) in Asia, and 10·4 percentage points (-35·0 to 2·6) in the Americas in the low-exposure sectors. These regional effects are projected to be substantially higher for labour outdoors in full sunlight compared with indoors (or outdoors in the shade) with the average reductions in total labour projected to be 32·8 percentage points (-66·3 to 1·6) in Africa, 25·0 percentage points (-66·3 to 7·0) in Asia, and 16·7 percentage points (-45·5 to 4·4) in the Americas. Both labour supply and productivity are projected to decrease under future climate change in most parts of the world, and particularly in tropical regions. Parts of sub-Saharan Africa, south Asia, and southeast Asia are at highest risk under future warming scenarios. The heterogeneous regional response functions suggest that it is necessary to move away from one-size-fits-all response functions to investigate the climate effect on labour. Our findings imply income and distributional consequences in terms of increased inequality and poverty, especially in low-income countries, where the labour effects are projected to be high. COST (European Cooperation in Science and Technology).

This review analyses global or near-global estimates of population exposure to sea-level rise (SLR) and related hazards, followed by critically examining subsequent estimates of population migration due to this exposure. Our review identified 33 publications that provide global or near-global estimates of population exposure to SLR and associated hazards. They fall into three main categories of exposure, based on definitions in the publications: (i) the population impacted by specified levels of SLR; (ii) the number of people living in floodplains that are subject to coastal flood events with a specific return period; and (iii) the population living in low-elevation coastal zones. Twenty of these 33 publications discuss connections between population migration and SLR. In our analysis of the exposure and migration data, we consider datasets, analytical methods, and the challenges of estimating exposure to SLR followed by potential human migration. We underscore the complex connections among SLR, exposure to its impacts, and migration. Human mobility to and from coastal areas is shaped by diverse socioeconomic, demographic, institutional, and political factors; there may be ‘trapped’ populations as well as those who prefer not to move for social, cultural, and political reasons; and migration can be delayed or forestalled through other adaptive measures. While global estimates of exposed and potentially migrating populations highlight the significant threats of SLR for populations living in low-lying areas at or near coastlines, further research is needed to understand the interactions among localised SLR and related hazards, social and political contexts, adaptation possibilities, and potential migration and (im)mobility decision-making.

It 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 $$^{\circ }\hbox {C}$$∘C of 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 $$^{\circ }\hbox {C}$$∘C increase 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.

In 2023, a series of climatological and political events unfolded, partly driving forward the global climate and health agenda while simultaneously exposing important disparities and vulnerabilities to climate-related events. On the policy front, a significant step forward was marked by the inaugural Health Day at COP28, acknowledging the profound impacts of climate change on health. However, the first-ever Global Stocktake showed an important gap between the current progress and the targets outlined in the Paris Agreement, underscoring the urgent need for further and decisive action. From a Latin American perspective, some questions arise: How do we achieve the change that is needed? How to address the vulnerabilities to climate change in a region with long-standing social inequities? How do we promote intersectoral collaboration to face a complex problem such as climate change? The debate is still ongoing, and in many instances, it is just starting.