Electricity Maps calculates time- and location-specific electricity signals, including consumption-based carbon intensity, that organizations can use to measure emissions and schedule flexible demand. It does not automatically optimize electricity use: a separate system must be able to delay, relocate, throttle, or otherwise control the workload.
What Electricity Maps calculates
Electricity Maps exposes grid data through its map, datasets, API, and specialized endpoints. Its signals include electricity mix and flows, load, prices, carbon intensity, carbon-free-energy percentage, and renewable percentage. The default carbon-intensity signal is expressed in grams of carbon-dioxide equivalent per kilowatt-hour consumed (gCO₂eq/kWh) and combines a flow-traced consumption mix with technology-specific life-cycle emission factors. The API signal documentation describes the available measures and units.
- Generation mix describes electricity produced by technologies in a zone.
- Consumption mix attributes electricity to the zone’s consumers, accounting for imports and exports through flow tracing.
- Carbon intensity estimates emissions associated with that electricity mix per kWh.
- Carbon-free percentage counts qualifying carbon-free sources; it is not the same as renewable percentage.
- Renewable percentage describes the renewable share, which is not interchangeable with carbon intensity. A grid can include nuclear power that lowers carbon intensity without being counted as renewable, or have a high renewable share while still using fossil generation.
These average, attributional signals should not be mistaken for marginal emissions: the emissions associated with adding or removing one more unit of electricity. An average can support footprint measurement or broad scheduling, while marginal data may be more relevant to a decision about incremental load. Do not interpret Electricity Maps’ default signal as marginal unless the particular endpoint and methodology explicitly say so.
Why consumption-based intensity differs from local generation
A generation-only figure asks how carbon-intensive the electricity produced inside a boundary was. A consumption-based, flow-traced figure asks what mix is attributed to electricity consumed there, including power crossing grid boundaries. If a zone imports electricity, a measure based only on its own generators can miss emissions associated with the electricity available to local consumers.
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Electricity Maps characterizes its methodology as attributional, location-based, and consumption-based. In this context, location-based means the signal reflects the physical grid rather than a customer’s power-purchase contracts or traded certificates. That makes it useful for operational decisions about electricity on the grid, but it does not make it equivalent to every corporate Scope 2 accounting method or a market-based calculation. Electricity Maps’ methodology explains these boundaries.
How the carbon-intensity calculation works
- Collect grid inputs. The service gathers generation, interconnection-flow, load, and other grid data from official or authoritative sources.
- Harmonize the inputs. Source formats, units, time intervals, and geographic boundaries are standardized.
- Estimate gaps when needed. Some source values may be delayed or unavailable, so a value can be modeled or inferred rather than directly reported.
- Trace electricity flows. The system attributes electricity moving through interconnected grids to consumption zones.
- Apply emission factors. The flow-traced technology mix is matched with technology-specific factors.
- Aggregate and publish. Results are made available by zone and time interval through the map, API, datasets, and specialized endpoints.
A conceptual representation is:
carbon intensity = Σ(consumption-attributed electricity from technology i × emission factor i) ÷ total electricity consumed
This is a simplified model, not a complete description of Electricity Maps’ proprietary implementation. The factor choice matters: lifecycle includes emissions associated with construction, fuel extraction, operation, and end-of-life stages; direct focuses on operational emissions from generation. The API uses life-cycle factors by default. Comparing a life-cycle figure with a direct-emissions figure can produce different results without indicating a data-quality error. The API getting-started guide documents these choices.
How organizations can use the signal
The practical loop is to measure electricity use, retrieve carbon intensity by location and time, identify flexible demand, shift or sequence that demand, and then verify energy use and emissions afterward. Potential uses include batch data processing, machine-learning training, rendering, simulations, backups, archival jobs, software builds, electric-vehicle charging, industrial or commercial flexible loads, cloud-region selection, data-center planning, and emissions dashboards.
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Electricity Maps advertises data-center-specific queries and a carbon-aware optimizer endpoint as well as past, real-time, historical, and forecast data. Those capabilities provide a signal or recommendation; an organization still needs an actuation layer. An API cannot by itself move a workload, guarantee a service-level objective, reschedule a customer transaction, or change the physical source of power. The platform API page describes its data and use-case endpoints.
Using the Electricity Maps API
The current Developer Hub documents API v4. A representative historical query for Germany is:
curl "https://api.electricitymaps.com/v4/carbon-intensity/past?zone=DE&datetime=2026-07-28T07:00Z"
-H "auth-token: my-api-token"Use a valid API token in place of the example value. The example datetime is a historical query timestamp, not a claim about current conditions. The API reference documents parameters including zone, lat, lon, dataCenterProvider, dataCenterRegion, datetime, start, end, temporalGranularity, emissionFactorType, flowTraced, and disableEstimations.
Documented granularities include 5-minute, 15-minute, hourly, daily, monthly, quarterly, and yearly intervals, but not every signal or endpoint supports every interval. Verify support for the particular zone and endpoint before relying on it. For historical range requests, the documented limit is 10 days (240 hours) per hourly request and up to 100 days per daily request; longer periods require multiple requests.
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Choose the right geography and settings
- Map the actual site or cloud region to a zone. Use the finest reliable zone available rather than assuming a country-level average represents a particular facility. A cloud region and a country are not necessarily the same geographic unit.
- Select the factor basis deliberately. Choose lifecycle or direct factors according to the decision and keep that choice consistent when comparing results.
- Decide whether flow tracing and estimates are appropriate. The API exposes
flowTracedanddisableEstimations; make the settings part of the documented methodology. - Request the relevant signal and interval. Use forecast data for scheduling ahead and historical or observed data for later evaluation, while checking endpoint availability and timestamps.
- Store the decision inputs. Retain the interval timestamp, retrieval time, zone, factor type, flow-tracing setting, returned estimate metadata, measured energy, and outcome.
For privacy-sensitive coordinate mapping, Electricity Maps documents an offline zone-finder option that maps coordinates to zones without sending the coordinates to its servers. The getting-started guide covers this option and response metadata.
Build scheduling logic around constraints, not just the lowest number
A simple scheduler could compare candidate execution intervals and choose the one with the lowest forecast intensity, but a production system needs more than that ranking. It must first define the workload’s deadline and flexible window, then apply constraints such as compute capacity, electricity price, reliability, latency, data residency, and transfer energy or cost.
for interval in candidate_intervals:
signal[interval] = get_carbon_intensity(
zone=zone,
datetime=interval,
emission_factor_type="lifecycle",
flow_traced=True
)
eligible = [interval for interval in candidate_intervals
if meets_deadline(interval)
and meets_capacity_and_policy_rules(interval)]
best_interval = min(eligible, key=lambda interval: signal[interval])
run_workload(best_interval)This illustrates a decision pattern, not a complete production implementation. The system should define fallback behavior if a forecast is missing, a value is estimated, coverage is incomplete, the API is unavailable, the workload misses its execution window, or a move would violate latency or data-residency requirements. It should also decide how to handle an interval with a lower carbon signal but a higher price or insufficient capacity.
How to estimate and audit emissions savings
A basic attributional estimate for shifting a flexible workload is:
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- Various Monitoring Parameters: The power meter plug can monitor the power (W), energy (kWh), volts, amps, hertz, power factor, cost, minimum and maximum power (W), cumulative days and time of your appliances. By switching 7 display modes, you can easily know the various parameters while the appliance is working. The home energy monitor can also calculate and display how much power your appliance uses and how much electricity bill it cost in cumulative time
- Upgraded LCD display: With large screen size 2.36 inch x 1.85 inch, clearer monitor backlit, our electrical usage monitor can display the data clearer and more visible no matter day or night. 180°full wide viewing angles is great for reading and recording the data in any angles. No need to stand on the front of the display and bend over to read the numbers
- Adjustable Backlight Time: Our upgraded watt meter has 5 options of backlight time. The default backlight time duration is 10 minutes(bL-0). If you want to change the backlight time, you can press and hold "UP" and "DOWN" button at the same time to enter backlight time setting, then press "UP" and "DOWN" to select the backlight time (bL-0 =10 minutes, bL-1=1 hour, bL-2=4 hours, bL-3=8 hours, bL-4=always on), finally press the "COST" to save the backlight time settings
- Overload protection: When the power of the appliance exceeds the overload power, the LCD will display “OVERLOAD” to warn the user. All the buttons will quit working and can only be workable when you lower or remove the load power. The default overload power is 3680W and is adjustable from 0 to 3680W. In general, you need to set the overload power to 1800W before using. Just press the "function" button for more than 3 seconds to enter the setting
- Data Memory Function: The wattage meter will record your power consumption data when you remove it from socket, or remove appliances from the electricity monitor. You can directly see the last data when you use it next time. This function can also automatically save the data when there is a sudden power failure
estimated avoided emissions = workload energy (kWh) × [intensity at original interval − intensity at selected interval]
This estimates a difference under the selected accounting method; it does not prove that total physical grid emissions fell by that amount. For an auditable evaluation, record:
- actual workload electricity use in kWh;
- the original and selected time intervals and locations;
- the intensity values used when the scheduling decision was made;
- whether values were forecast, estimated, or subsequently revised;
- the emission-factor choice and flow-tracing setting;
- additional energy for networking, cooling, or migration;
- workload completion, latency, reliability, and service-level effects;
- possible rebound or congestion effects and the accounting boundary.
Keeping the value and metadata used at decision time is important: a later revised observation may differ from the forecast that caused the workload to move.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the signal does not establish
- A lower location-based intensity does not show that the customer caused new renewable generation, uses dedicated renewable power, or has lower market-based Scope 2 emissions.
- An attributed reduction is not proof that grid-wide emissions fell by the same quantity, or that marginal emissions were lower.
- A lower-carbon location is not automatically better after considering water, transmission, hardware, or embodied emissions.
- A carbon signal does not establish that a workload can move without reliability, privacy, latency, data-sovereignty, or regulatory consequences.
- A broad zone value may not represent local transmission constraints or conditions at a particular facility.
Load shifting can move emissions rather than eliminate them. A delayed workload may run during a more constrained interval, draw power when prices are higher, consume extra energy through cooling or data transfer, or compete with other flexible loads. Location shifting also has costs and trade-offs, including cloud-region prices, application replication, and resilience design.
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How Electricity Maps compares with other options
The right choice depends on geography, required signal, and whether the goal is a general-purpose scheduler or reporting within one cloud. The figures and capabilities below reflect the cited product documentation; confirm availability and terms for the intended use before adopting a service.
| Option | Documented focus | Potential fit | Limit to consider |
|---|---|---|---|
| Electricity Maps | Standardized grid signals, including consumption-based flow-traced intensity, multiple signals, and data-center queries. | Multi-country or global applications that combine grid data with their own scheduling or load controls. | Requires a separate actuation layer; check exact zone, endpoint, data freshness, and commercial terms. |
| Singularity Energy Grid Carbon API | U.S. and parts of Canada; documentation describes generated, consumed, and marginal carbon-intensity signals, with forecasts. | U.S.-focused projects that need balancing-authority detail or marginal-intensity options. | Less suitable when broad international coverage from one provider is required. Documentation and the product page describe coverage and capabilities. |
| Google Cloud Carbon Footprint | Google Cloud reporting by project, product, and region, with location-based and market-based views. | Existing Google Cloud customers seeking cloud emissions reporting and reduction guidance. | It is not a general-purpose, multi-cloud global grid API. Google says the service is provided at no charge to Google Cloud customers; BigQuery export can incur normal storage and query charges. See Google Cloud Carbon Footprint. |
| Utility, ISO, or internally assembled data | Depends on the sources and method selected by the organization. | Teams with a narrow geography and the capacity to manage source-specific integrations. | Standardization, flow tracing, estimation, and maintenance become the organization’s responsibility. |
A cloud provider’s dashboard can be simpler for reporting within that provider. A grid-data API is more useful when a team wants to build its own scheduler, compare providers, combine emissions data with prices, or operate across cloud ecosystems.
When Electricity Maps is a good fit
Consider it when standardized signals across multiple grid zones, consumption-based flow tracing, multiple electricity measures, or lifecycle/direct factor selection are important to the application. It is less compelling when the use case is confined to one U.S. balancing authority and specifically requires marginal emissions, when facility-level meter data is essential, when market-based Scope 2 accounting is the goal, or when workloads cannot move under the organization’s latency, privacy, and residency rules.
Electricity Maps’ pricing help article, dated March 3, 2026, lists a 14-day API trial without payment information, real-time carbon intensity at €6,000 per year, and carbon-free-energy percentage at €4,500 per year; it says forecasts and configurations such as finer granularity, extended history, or multi-region coverage can have custom pricing. Check the current terms for the required signals and coverage. Pricing and custom options.
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