• About

home / cloud_regions

cloud_regions_metadata

27 rows where year = 2020

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: wt-region-id, provider-cfe-hourly

Link rowid ▼ year cloud-provider cloud-region cfe-region em-zone-id wt-region-id location geolocation provider-cfe-hourly provider-cfe-annual power-usage-effectiveness water-usage-effectiveness provider-carbon-intensity-market-annual provider-carbon-intensity-average-consumption-hourly grid-carbon-intensity-average-consumption-annual grid-carbon-intensity-marginal-consumption-annual grid-carbon-intensity-average-production-annual grid-carbon-intensity total-ICT-energy-consumption-annual total-water-input renewable-energy-consumption renewable-energy-consumption-goe renewable-energy-consumption-ppa renewable-energy-consumption-onsite
260 260 2020 Google Cloud asia-east1 Taiwan TW TW Taiwan   0.18       0 540                      
261 261 2020 Google Cloud asia-east2 Hong Kong HK HK Hong Kong   0.0       0 453                      
262 262 2020 Google Cloud asia-northeast1 Tokyo JP-TK JP_TK Tokyo   0.12       0 554                      
263 263 2020 Google Cloud asia-northeast2 Kansai JP-KN JP_KN Osaka   0.0       0 442                      
264 264 2020 Google Cloud asia-northeast3 South Korea KR KOR Seoul   0.31       0 457                      
265 265 2020 Google Cloud asia-south1 Maharashtra IN-MH IND Mumbai   0.12       0 721                      
266 266 2020 Google Cloud asia-south2 Uttar Pradesh IN-UP IND Delhi   0.0       0 657                      
267 267 2020 Google Cloud asia-southeast1 Singapore SG SGP Singapore   0.04       0 493                      
268 268 2020 Google Cloud asia-southeast2 Indonesia ID ID Jakarta   0.0       0 647                      
269 269 2020 Google Cloud australia-southeast1 New South Wales AUS-NSW NEM_NSW Sydney   0.11       0 727                      
270 270 2020 Google Cloud australia-southeast2 Victoria AUS-VIC NEM_VIC Melbourne   0.0       0 691                      
271 271 2020 Google Cloud europe-central2 Poland PL PL Warsaw   0.0       0 622                      
272 272 2020 Google Cloud europe-north1 Belgium BE BE Finland   0.94       0 133                      
273 273 2020 Google Cloud europe-west1 Great Britain GB UK Belgium   0.79       0 212                      
274 274 2020 Google Cloud europe-west2 Germany DE DE London   0.59       0 231                      
275 275 2020 Google Cloud europe-west3 Netherlands NL NL Frankfurt   0.63       0 293                      
276 276 2020 Google Cloud europe-west4 Switzerland CH CH Netherlands   0.6       0 410                      
277 277 2020 Google Cloud europe-west6 North Italy IT IT Zurich   0.0       0 87                      
278 278 2020 Google Cloud northamerica-northeast1 Quebec CA-QC HQ Montréal   0.0       0 27                      
279 279 2020 Google Cloud southamerica-east1 Central Brazil BR-CS BRA São Paulo   0.88       0 103                      
280 280 2020 Google Cloud us-central1 MISO US-MIDW-MISO MISO_MASON_CITY Iowa   0.93       0 454                      
281 281 2020 Google Cloud us-east1 SC US-CAR-SC SC South Carolina   0.27       0 480                      
282 282 2020 Google Cloud us-east4 PJM US-MIDA-PJM PJM_DC Northern Virginia   0.58       0 361                      
283 283 2020 Google Cloud us-west1 BPA US-NW-BPAT BPA Oregon   0.9       0 78                      
284 284 2020 Google Cloud us-west2 CAISO US-CAL-CISO LDWP Los Angeles   0.54       0 253                      
285 285 2020 Google Cloud us-west3 PACE US-NW-PACE PACE Salt Lake City   0.28       0 533                      
286 286 2020 Google Cloud us-west4 NVE US-NW-NEVP NEVP Las Vegas   0.19       0 455                      

Advanced export

JSON shape: default, array, newline-delimited

CSV options:

CREATE TABLE "cloud_regions_metadata" (
   [year] INTEGER,
   [cloud-provider] TEXT,
   [cloud-region] TEXT,
   [cfe-region] TEXT,
   [em-zone-id] TEXT,
   [wt-region-id] TEXT,
   [location] TEXT,
   [geolocation] TEXT,
   [provider-cfe-hourly] FLOAT,
   [provider-cfe-annual] FLOAT,
   [power-usage-effectiveness] FLOAT,
   [water-usage-effectiveness] FLOAT,
   [provider-carbon-intensity-market-annual] INTEGER,
   [provider-carbon-intensity-average-consumption-hourly] INTEGER,
   [grid-carbon-intensity-average-consumption-annual] INTEGER,
   [grid-carbon-intensity-marginal-consumption-annual] FLOAT,
   [grid-carbon-intensity-average-production-annual] INTEGER,
   [grid-carbon-intensity] INTEGER,
   [total-ICT-energy-consumption-annual] INTEGER,
   [total-water-input] INTEGER,
   [renewable-energy-consumption] INTEGER,
   [renewable-energy-consumption-goe] INTEGER,
   [renewable-energy-consumption-ppa] INTEGER,
   [] INTEGER,
   [renewable-energy-consumption-onsite] INTEGER
);
Powered by Datasette · Queries took 63.755ms