Value-added panel of the World Bank's World Development Indicators (keyless API v2, CC BY 4.0): renewable energy share of total final energy consumption, population-weighted PM2.5 exposure (GBD 2023) and forest area share of land for ~200 economies, 1990-2023, with derived sustainability signals — 10-year pillar changes, within-year pillar ranks, and WHO air-quality-guideline exceedance flags for PM2.5 (guideline 5 ug/m3, interim target 1 at 35 ug/m3). The global sustainability layer for climate, energy and land models; joins on economy_code with the catalog's other World Bank panels.

Source: World Bank sustainability intelligence
Rows: 7,297
Columns: 17
Source cadence: Yearly
Last refreshed: Oct 7, 2026
Theme: environment

Column	Type	Description
economy_code	string	ISO 3166-1 alpha-3 economy code (World Bank API field countryiso3code).
economy_name	string	Economy name as published by the World Bank API.
region	string	World Bank region (API field region.value).
income_group	string	World Bank income group (API field incomeLevel.value).
year	integer	Reference year (1990-2023; the renewable series lags by vintage — 2021 is its last broadly covered year).
renewable_share_pct	float	Renewable energy consumption as a share of total final energy consumption (WDI indicator EG.FEC.RNEW.ZS, sourced from IEA energy statistics and UN energy statistics). Traditional biomass counts, so a high share can reflect traditional bioenergy use rather than modern renewables alone. (unit: % of total final energy consumption)
pm25_exposure	float	Population-weighted mean annual exposure to ambient PM2.5 pollution (WDI indicator EN.ATM.PM25.MC.M3, from the Global Burden of Disease Study 2023, IHME). The average exposure level of a nation's population to suspended particles under 2.5 microns. (unit: micrograms per cubic meter)
forest_share_pct	float	Forest area as a share of total land area (WDI indicator AG.LND.FRST.ZS, from FAOSTAT). Natural or planted stands of trees at least 5 metres tall; excludes agroforestry and urban trees. (unit: % of land area)
renewable_change_10y_pp	float	Trailing 10-year change of the renewable share, in percentage points; null when the base year is absent. (unit: pp)
pm25_change_10y	float	Trailing 10-year change of PM2.5 exposure; null when the base year is absent. (unit: micrograms per cubic meter)
forest_change_10y_pp	float	Trailing 10-year change of the forest share, in percentage points; null when the base year is absent. (unit: pp)
renewable_rank	integer	Rank of renewable_share_pct within the year (1 = highest renewable share); null where the share is null. (unit: rank)
pm25_rank	integer	Rank of pm25_exposure within the year (1 = highest exposure, worst air quality); null where exposure is null. (unit: rank)
forest_rank	integer	Rank of forest_share_pct within the year (1 = most forested); null where the share is null. (unit: rank)
pm25_guideline_exceed_flag	integer	1 when pm25_exposure exceeds the WHO 2021 annual air-quality guideline of 5 ug/m3; null where exposure is null.
pm25_it1_exceed_flag	integer	1 when pm25_exposure exceeds the WHO 2021 interim target 1 of 35 ug/m3; null where exposure is null.
row_hash	string	Deterministic 12-hex row identity hash (economy_code\|year).

First 10 sample rows — a preview, not the complete dataset.

economy_code	economy_name	region	income_group	year	renewable_share_pct	pm25_exposure	forest_share_pct	renewable_change_10y_pp	pm25_change_10y	forest_change_10y_pp	renewable_rank	pm25_rank	forest_rank	pm25_guideline_exceed_flag	pm25_it1_exceed_flag	row_hash
ABW	Aruba	Latin America & Caribbean	High income	1,990	0.3	—	2.333	—	—	—	179	—	152	—	—	59b9939dea0e
ABW	Aruba	Latin America & Caribbean	High income	1,991	0.2	—	2.333	—	—	—	183	—	156	—	—	8b0f0923d7fa
ABW	Aruba	Latin America & Caribbean	High income	1,992	0.2	—	2.333	—	—	—	184	—	174	—	—	eec2dc95462f
ABW	Aruba	Latin America & Caribbean	High income	1,993	0.2	—	2.333	—	—	—	184	—	178	—	—	c1b01e146fee
ABW	Aruba	Latin America & Caribbean	High income	1,994	0.2	—	2.333	—	—	—	183	—	178	—	—	117ee27173fe
ABW	Aruba	Latin America & Caribbean	High income	1,995	0.2	—	2.333	—	—	—	186	—	178	—	—	65a5a89d7667
ABW	Aruba	Latin America & Caribbean	High income	1,996	0.2	—	2.333	—	—	—	186	—	178	—	—	7a4774a17ae4
ABW	Aruba	Latin America & Caribbean	High income	1,997	0.2	—	2.333	—	—	—	185	—	178	—	—	448a9f868f2c
ABW	Aruba	Latin America & Caribbean	High income	1,998	0.2	—	2.333	—	—	—	185	—	178	—	—	6cfd8415793a
ABW	Aruba	Latin America & Caribbean	High income	1,999	0.2	—	2.333	—	—	—	185	—	178	—	—	450f0cef38ca

Oct 7, 2026Current
20261007T082351Z-f2a4ece5dd19 · sha256 f2a4ece5dd19…
7,297 rows · first snapshot

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/wb_sustainability_intel/eco_sustainability_panel" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/wb_sustainability_intel/eco_sustainability_panel").json()
print(ds["title"], ds["rows"], "rows")

# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
    print(row)

API endpoint: https://datazimuts.com/v1/datasets/wb_sustainability_intel/eco_sustainability_panel

Tip: fetch /llms.txt for the full machine-readable catalog.

Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.

Cite this snapshot

Pinned to snapshot 20261007T082351Z-f2a4ece5dd19 and its content hash, so readers get exactly the data you used.

APA

World Bank sustainability intelligence. (2026). World Bank sustainability panel (renewables, PM2.5, forest) [Data set, snapshot 20261007T082351Z-f2a4ece5dd19, sha256 f2a4ece5dd19]. Datazimuts. Retrieved 2026-10-07, from https://datazimuts.com/en/datasets/wb_sustainability_intel/eco_sustainability_panel?snapshot=20261007T082351Z-f2a4ece5dd19

BibTeX

@misc{dz_wb_sustainability_intel_eco_sustainabili_f2a4ece5,
  title        = {{World Bank sustainability panel (renewables, PM2.5, forest)}},
  author       = {{World Bank sustainability intelligence}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/wb_sustainability_intel/eco_sustainability_panel?snapshot=20261007T082351Z-f2a4ece5dd19}},
  note         = {Snapshot 20261007T082351Z-f2a4ece5dd19, sha256 f2a4ece5dd19c8baff5ec3d553d2ce430b4d0bb33a5a2486ae1e476163086cc7; accessed 2026-10-07}
}

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<iframe src="https://datazimuts.com/embed/chart?dataset=wb_sustainability_intel%2Feco_sustainability_panel&lang=en&theme=auto&snapshot=20261007T082351Z-f2a4ece5dd19&x=year&y=year&agg=avg" title="World Bank sustainability panel (renewables, PM2.5, forest)" width="100%" height="380" style="border:0" loading="lazy"></iframe>

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