Social media data shed light on air-conditioning interest of heat-vulnerable regions and sociodemographic groups.

Cooling homes with air conditioners is a vital adaptation approach, but the wider adoption of air conditioners can increase hydrofluorocarbon emissions that have high global warming potential and carbon emissions as a result of more fossil energy consumption. The scale and scope of future cooling demand worldwide are, however, uncertain because the extent and drivers of air-conditioning adoption remain unclear. Here, using 2021 and 2022 Facebook and Instagram data from 113 countries, we investigate the usability of social media advertising data to address these data gaps in relation to the drivers of air-conditioning adoption. We find that social media data might represent air-conditioning purchasing trends. Globally, parents of small children and middle-aged, highly educated married or cohabiting males tend to express greater interest in air-conditioning adoption. In regions with high heat vulnerability yet little empirical data on cooling demand (e.g., the Middle East and North Africa), these sociodemographic factors play a more prominent role. These findings can strengthen our understanding of future cooling demand for more sustainable cooling management.

Response to comment on "Fairness considerations in global mitigation investments".

We welcome the analysis of Semieniuk et al. (1) as an additional sensitivity to illustrate a more extreme distribution of regional contributions to climate mitigation investments that supports our main conclusion regarding the North-South divide in mitigation investment capabilities. In response to Semieniuk et al. we would like to first point out that, in defining the required global mitigation investments for the 2020 to 2030 period, our study relies on the estimates in the sixth assessment report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) WGIII (2). These are based on diverse sources and underlying models that to varying degrees reflect regional differences in technology costs and consider both purchasing power parity (PPP) and market exchange rates (MERs). We use these IPCC estimates as a starting point and focus entirely on the question of how much of the needed regional investments, given different fairness considerations, should be financed from sources within a region.

Fairness considerations in global mitigation investments.

Current mitigation finance flows are inadequate and unfair.

Estimating global economic well-being with unlit settlements.

It is well established that nighttime radiance, measured from satellites, correlates with economic prosperity across the globe. In developing countries, areas with low levels of detected radiance generally indicate limited development - with unlit areas typically being disregarded. Here we combine satellite nighttime lights and the world settlement footprint for the year 2015 to show that 19% of the total settlement footprint of the planet had no detectable artificial radiance associated with it. The majority of unlit settlement footprints are found in Africa (39%), rising to 65% if we consider only rural settlement areas, along with numerous countries in the Middle East and Asia. Significant areas of unlit settlements are also located in some developed countries. For 49 countries spread across Africa, Asia and the Americas we are able to predict and map the wealth class obtained from ~2,400,000 geo-located households based upon the percent of unlit settlements, with an overall accuracy of 87%.

Guidelines for Modeling and Reporting Health Effects of Climate Change Mitigation Actions.

BACKGROUND: Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers. OBJECTIVE: The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions. METHODS: An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies. RESULTS: The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting. DISCUSSION: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice. https://doi.org/10.1289/EHP6745.

A high-resolution gridded dataset to assess electrification in sub-Saharan Africa.

Spatially explicit data on electricity access and use are essential for effective policy-making and infrastructure planning in low-income, data-scarce regions. We present and validate a 1-km resolution electricity access dataset covering sub-Saharan Africa built on gridded nighttime light, population, and land cover data. Using light radiance probability distributions, we define electricity consumption tiers for urban and rural areas and estimate the by-tier split of consumers living in electrified areas. The approach provides new insight into the spatial distribution and temporal evolution of electricity access, and a measure of its quality beyond binary access. We find our estimates to be broadly consistent with recently published province- and national-level statistics. Moreover, we demonstrate consistency between the estimated electricity access quality indicators and survey-based consumption levels defined in accordance with the World Bank Multi-Tier Framework. The dataset is readily reproduced and updated using an open-access scientific computing framework. The data and approach can be applied for improving the assessment of least-cost electrification options, and examining links between electricity access and other sustainable development objectives.

Outlook for modern cooking energy access in Central America.

The Central American nations of Guatemala, Honduras and Nicaragua are among the poorest in the Americas. While the fraction of population dependent on solid fuels has declined in these nations over the last 25 years, the number of people using them has risen. Here, we first assess current patterns of cooking energy use in these nations. We then apply a discrete model of household cooking choices and demand to simulate future pathways of clean cooking uptake and the outlook for achieving target 7.1 of the Sustainable Development Goals (SDG), which aims to ensure universal access to affordable, reliable and modern energy services by 2030. We find that by 2030, ensuing income growth is likely to enable 90% of urban populations in these nations to switch to using modern cooking energy services. However, without supporting policies, between 40% to 50% of rural Guatemalans and Hondurans, while over two-thirds of rural Nicaraguans, are likely to find clean fuels or stoves unaffordable in 2030. A targeted subsidy on modern fuels, like liquid petroleum gas (LPG), is the most effective policy mechanism we studied that could provide such support. A 50% subsidy policy on LPG targeted to the rural and urban poor population could, by 2030, make cooking with LPG affordable to an additional 7.3 million people in these countries. We estimate that such a policy would cost about $250 million per year and would have negligible greenhouse gas emissions impacts. Such a policy could also have significant health benefits, preventing about 8,890 premature deaths annually from reduced exposure to cooking-related household pollution in 2030.

Demographic change and carbon dioxide emissions.

Relations between demographic change and emissions of the major greenhouse gas carbon dioxide (CO(2)) have been studied from different perspectives, but most projections of future emissions only partly take demographic influences into account. We review two types of evidence for how CO(2) emissions from the use of fossil fuels are affected by demographic factors such as population growth or decline, ageing, urbanisation, and changes in household size. First, empirical analyses of historical trends tend to show that CO(2) emissions from energy use respond almost proportionately to changes in population size and that ageing and urbanisation have less than proportional but statistically significant effects. Second, scenario analyses show that alternative population growth paths could have substantial effects on global emissions of CO(2) several decades from now, and that ageing and urbanisation can have important effects in particular world regions. These results imply that policies that slow population growth would probably also have climate-related benefits.

Global demographic trends and future carbon emissions.

Substantial changes in population size, age structure, and urbanization are expected in many parts of the world this century. Although such changes can affect energy use and greenhouse gas emissions, emissions scenario analyses have either left them out or treated them in a fragmentary or overly simplified manner. We carry out a comprehensive assessment of the implications of demographic change for global emissions of carbon dioxide. Using an energy-economic growth model that accounts for a range of demographic dynamics, we show that slowing population growth could provide 16-29% of the emissions reductions suggested to be necessary by 2050 to avoid dangerous climate change. We also find that aging and urbanization can substantially influence emissions in particular world regions.