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Guinea-Bissau Access to clean fuels and technologies for cooking, urban (% of urban population)
What is Guinea-Bissau's access to clean fuels and technologies for cooking, urban (% of urban population)? As of 2023, it's 1.5 (share) of urban population, down from 2.6 (share) of urban population in 2014.
| Label | Access to clean fuels and technologies for cooking, urban (% of urban population) |
|---|---|
| 2014 | 2.6 (share) of urban population |
| 2015 | 2.5 (share) of urban population |
| 2016 | 2.4 (share) of urban population |
| 2017 | 2.3 (share) of urban population |
| 2018 | 2.3 (share) of urban population |
| 2019 | 2.1 (share) of urban population |
| 2020 | 2 (share) of urban population |
| 2021 | 1.9 (share) of urban population |
| 2022 | 1.7 (share) of urban population |
| 2023 | 1.5 (share) of urban population |
Data Source: World Bank and Wantstats Repository
Guinea-Bissau Access to clean fuels and technologies for cooking, urban (% of urban population): Key Points
- Take Guinea-Bissau's access to clean fuels and technologies for cooking, urban at face value first: 1.50 % (share) of urban population as of 2023, versus 2.60 % (share) of urban population when the series starts in 2014, a 42% fall.
- 2015-2017: drifts lower, 2.30 % (share) of urban population (-12%).
- 2018: sits at 2.30 % (share) of urban population, near enough unchanged.
- 2019-2023: falls away sharply to 1.50 % (share) of urban population (-35%).
- 2022: The standout year. Value drops from 1.90 to 1.70 % (share) of urban population (~11%) — nothing else in the series moves this fast.
- Where it lands: 1.50 % (share) of urban population in 2023, a 42.3% drop from the 2014 starting line.
Reading A Clean Downtrend
It's rare for a national indicator to move the same direction for 10 consecutive years without interruption. When it does, there's almost always a specific, identifiable cause behind it.
This chart is a starting point, not a conclusion. Guinea-Bissau's access to clean fuels and technologies for cooking, urban numbers here are worth cross-checking against at least one other source or comparator before they inform any real decision.
As with almost all cross-national statistical series, this one blends real survey years with modeled estimates for the gaps — the year-to-year precision is lower than the chart's smooth line suggests.
Urban-only data like this rarely tells the whole national story on its own. Pull up the rural version alongside it — the gap between the two is often more informative than either number alone.
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