Energy poverty reflects a lack of adequate, reliable, and affordable energy for lighting, cooking, heating, and other daily activities necessary for welfare and economic development. It is inextricably linked to economic deprivation and social inequity, but energy poverty can also be exacerbated by infrastructural decay and service disruptions. Energy poverty can have broad societal impacts, contributing to poor health and education outcomes, deforestation, and climate change. These consequences are likely even more severe for socially vulnerable and economically disadvantaged groups.
Historically, data collection efforts around energy have focused on identifying access to electricity, relying on government estimates or self-reported data from representative surveys and censuses. But variations in definitions, sampling procedures, and survey timing make it difficult to consistently compare progress across different regions and over time. For example, the International Energy Agency (IEA) estimated that 72.8% of the world population had access to electricity in 2000, but the World Bank now estimates that 78.2% of the world had access in that year. In Ethiopia, the World Bank reports an increase in access from 42.9% to 48.1% from 2016 to 2019, but Demographic and Health Surveys (DHS) reported household access rates of only 25.6% and 35.0% in those same years.
Given the fragmented, incomplete, and often politicized nature of energy data, there is a need for more independent and harmonized modalities of data collection. Sensor technologies are filling in some of these measurement gaps. Smart meters can enable real-time tracking of voltage and consumption at the household level. In Ghana and India, small network-connected voltage detectors track power supply quality and outages at low cost. Earth observation data, in particular nighttime imagery from the DMSP-OLS (Defense Meteorological Satellite Program Operational Linescan System) and VIIRS-DNB (Visible Infrared Imaging Radiometer Suite Day/Night Band) sensors, can be used to infer electricity usage from light output. The virtue of remote sensing techniques is that they rely on data that are directly comparable and consistently measured with high spatial resolution and complete geographic coverage (see Levin et al. for a thorough review).
Our result
Leveraging computational analysis of remotely sensed data captured over nearly 3,000 nights, we generate indicators of electricity poverty at the settlement level and over time. We demonstrate the reliability and validity of these classifications against ground-based surveys at multiple scales. At least 1.18 billion are energy poor across the developing world, revealing no statistical evidence of electricity usage from space.
That total is 60% higher than the official global estimate of 733 million lacking electricity access, indicating that far more work is needed to address energy justice and equity gaps. Most of the energy poor live in areas that are more remote, less densely populated, and more rugged than energyabundant areas. These methods provide new tracking and monitoring capabilities in the global effort to ensure affordable, reliable, and sustainable energy for all.
Excerpt of: “Lost in the dark: A survey of energy poverty from space”. Min et al., Joule 8, 1–17, July 17, 2024
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