GCRI · Energy Nexus
Industrial energy systems
Industry is one of the largest users of final energy, much of it as high-temperature heat for steel, cement, chemicals, glass and paper, and as feedstock that becomes part of the product. Industrial sites are also flexible loads, major hazard sites and nodes in supply chains. This page sets out how industrial demand develops, how decarbonisation pathways change it, and what evidence ministries, regulators, operators and lenders use.
Industrial energy systems on the record.
Industrial energy systems: how the risk develops.
Industrial demand and resource pathways. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Process heat is hard to replace
Steel, cement and chemicals need high-temperature heat and chemical reactions that electricity alone cannot always provide. Pathways run through electrification, hydrogen, biomass, carbon capture and process change, each at a different stage of maturity.
Feedstocks and materials
Ammonia, plastics and steel use fossil fuels as feedstock as well as fuel. Low-carbon routes depend on electrolysers, batteries, magnets and grid equipment that need critical minerals whose production and processing are concentrated in few countries.
Industry and the grid
Electrified industry raises demand and needs new grid connections; flexible industrial loads can also support the grid by reducing consumption at peaks. Some processes cannot stop safely, so unplanned loss of power damages plant and product.
Shocks travel through supply chains
A gas price spike can curtail fertiliser and chemical production, which then reaches food, water treatment chemicals and medicines. Industrial energy is one of the channels through which an energy shock becomes a shortage of goods.
Energy now in Europe.
Night lights, population density and land cover over Europe, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Energy now, for this page
About this layer
- Evidence
- Observed
- Source
- VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
- Provider
- NASA LAADS DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite radiance, corrected for moonlight and atmosphere
- Newest at build
- 2026-10-12
- Resolution
- about 500 m grid
- Uncertainty
- Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest month GIBS publishes)
- Source
- MERRA-2 (NASA GMAO / GES DISC)
- Provider
- NASA GMAO / GES DISC
- Licence
- NASA open data
- Vintage
- monthly; Reanalysis model; latest month GIBS publishes
- Newest at build
- 2026-07-01
- Resolution
- about 2 km grid
- Uncertainty
- Reanalysis model estimate of monthly mean incoming sunlight over land; an indicator of solar resource, not a site yield assessment.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- VIIRS NOAA-20 (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite retrieval; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 1 km grid
- Uncertainty
- Satellite skin temperature of the ground on the day shown, an indicator of cooling demand; not air temperature or a heat warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Energy now, framed on Europe.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA/NOAA VIIRS · NASA JPL OPERA DIST-ALERTSources and licences
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- MERRA-2 reanalysis, NASA Global Modeling and Assimilation Office; distributed by the NASA GES DISC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Observed (EO): NASA/NOAA VIIRS (Suomi NPP). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Past year, daily temperature (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change Service information 2026.
- Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (10 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Incoming sunlight at the surface over land, monthly mean: MERRA-2, NASA GMAO / GES DISC · July 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Land surface temperature, day: VIIRS NOAA-20, NASA LANCE · 13 Oct 2026
Industry links energy to materials, water and local safety.
| Domain | How it couples here | What to watch |
|---|---|---|
| Food | Ammonia for fertiliser is among the largest industrial uses of natural gas. See food, water and energy. | Ammonia plant curtailment in gas shortages |
| Water | Process water and cooling make industry a large withdrawer in some basins. | Industrial abstraction permits |
| Health | Major-accident hazards near communities are governed by regimes such as the EU Seveso III Directive. | Sites under major-hazard regimes |
| Biodiversity | Emissions and effluent affect air, rivers and coasts. | Pollutant release registers |
The IEA’s Energy Technology Perspectives 2023 sets out the supply chains of clean energy technologies and the energy demand of heavy industry. Process safety follows risk-based process safety practice, as documented by the Center for Chemical Process Safety.
Dispatch and adequacy.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Dispatch and adequacy
Industrial energy systems · Day ahead · Control area 2
Generation mix, day ahead
- Thermal
- Wind and solar
- Hydro
Margins
available vs required
Storage and flexibility
| ST-1 | Battery | 27 | 107 | Limited |
| PH-2 | Pumped hydro | 52 | 411 | Available |
| DR-East | Demand response | n/a | 40 | Contracted |
Industrial energy evidence.
Industrial energy studies are designed for the Global Sector Risk and Resilience series. Plant data stay confidential to operators; public outputs show aggregated or permitted results. Process safety lessons and curtailment records are the most useful contributions.
A cascade through interdependent networks.
A hazard footprint takes out co-located assets in every layer; fragmentation, dependency between layers and overload of the survivors then spread the failure. The 3D view separates the layers by depth. Teaching model with stated illustrative values, not a prediction. The map on this page shows Europe; the model itself is not tied to a place.
Controls
- Assets per layer
- 18
- Hazard footprint
- 8% of area
- Assets that depend on another layer
- 60%
- Spare capacity (tolerance)
- 30%
Readouts
- Assets hit by the hazard
- 19%
- Assets still working
- 22%
- Amplification of the initial damage
- 4.2 times
- Steps to settle
- 4
Numbers, methods and sources
| Step | Power working (%) | Gas working (%) | Telecoms working (%) |
|---|---|---|---|
| 0 | 83 | 78 | 83 |
| 1 | 50 | 56 | 72 |
| 2 | 28 | 44 | 50 |
| 3 | 17 | 33 | 28 |
| 4 | 17 | 33 | 17 |
Methods
- Interdependent networks Buldyrev and others (2010), Catastrophic cascade of failures in interdependent networks, Nature 464
- Overload cascades Motter and Lai (2002), Physical Review E 66
- Betweenness load Brandes (2001), Journal of Mathematical Sociology 25
- Multilayer networks Kivela and others (2014), Journal of Complex Networks 2
- Infrastructure interdependencies Rinaldi, Peerenboom and Kelly (2001), IEEE Control Systems 21(6)
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- Major roads Natural Earth
- Railways Natural Earth
- Seaports Natural Earth
- Airports Natural Earth
- Urban extents Natural Earth
- Night lights tonight, outages (VIIRS Day/Night Band) NASA/NOAA VIIRS (Suomi NPP) · register nasa.gibs.context-live-layers
- Natural events (NASA EONET) NASA EONET · register nasa.eonet.events
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Energy Nexus in Foundry
- Tested at Energy Nexus in Universe
- Codified in Energy and Critical Infrastructure in Standards
- Published in Energy Nexus in Reports
- Taught in Faculty of Infrastructure, Energy and Industry in Academy
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Industrial final energy consumption by fuel | petajoules | annual | National energy balances | Published statistics |
| Energy intensity of industrial output | megajoules per unit of value added or per tonne of product | annual | Energy balances and production statistics | ESTIMATED |
| Process heat demand by temperature band | petajoules per band | periodic study | Industrial surveys and models | MODELLED |
| Verified emissions of large installations | tonnes of carbon dioxide equivalent | annual | Emissions trading and reporting schemes | Published statistics |
| Industrial demand response capacity | megawatts | annual | Operator and aggregator registers | REPORTED |
| Critical mineral supply concentration | dimensionless concentration index | annual | Production statistics by country | ESTIMATED |
Model industrial energy systems as a system. Run the cascade.
Assembled from the Nexus Standards area profile Energy risk standards: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Heatwave
- Windstorm
- Widespread power outage (set off downstream)
- Large forest disturbance (set off downstream)
- Wildfire (set off downstream)
- Extreme fire weather (set off downstream)
- Heat-driven grid stress (set off downstream)
- Agricultural drought (set off downstream)
- Flash drought (set off downstream)
- Snow drought (set off downstream)
- Ground-level ozone episode (set off downstream)
- Meteorological drought (set off downstream)
- Extreme night-time heat (set off downstream)
- Lake and river heatwave (set off downstream)
- Cooling-water curtailment of power plants (set off downstream)
- Heat-induced track buckling (set off downstream)
- Shoreline ice shove (set off downstream)
- Seiche (set off downstream)
Systems and couplings
- Energy risk standards
- Water risk standards Common driver
- Critical infrastructure and critical entities Cascade
- Climate risk standards Feedback
- Space weather, spectrum and timing risk standards Common driver
Controls
NS-0Constitution and principlesNS-1The UNI and the artefact catalogue (grammar v0.2: domain, sector, region and environment segments)NS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-H84Hazard family: Energy system instability and shortfall (NHS-1 infra.energy)NRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)NRS-U8Universe platform profile: Energy NexusNRS-H48Hazard family: Utility and communication network outage (NHS-1 infra.utilities)NRS-H109Hazard family: Energy-transition technology failures (NHS-1 tech.energy-transition)NRS-H54Hazard family: Signal and platform disruption (NHS-1 cyber.platform)
Observation
- Global Power Plant Database (listed for reference)
- NASA Black Marble night-time lights (VNP46) (listed for reference)
- Ember electricity data (listed for reference)
- ENTSO-E Transparency Platform (listed for reference)
- EIA Open Data API (listed for reference)
- Proportion of population with access to electricity
- Renewable energy share in total final energy consumption
- Number of disruptions to basic services attributed to disasters
- Damage to critical infrastructure attributed to disasters
Example geography
- Europe: 113 hexagonal cells
- Surface air temperature, daytime (AIRS), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| Eurostat energy balances | Industrial energy use by sub-sector and fuel for European countries | Free reuse, attribution |
| EU emissions trading verified emissions and the Industrial Emissions Portal (EEA) | Verified emissions and pollutant releases of large installations | Free reuse, attribution |
| EPA Greenhouse Gas Reporting Program (FLIGHT) | Facility-level emissions in the United States | Public domain |
| USGS Mineral Commodity Summaries | Production and reserves of minerals used in energy technologies | Public domain |
| IEA Energy Efficiency Indicators | End-use energy consumption and intensity by industrial sub-sector | IEA terms; highlights free |
| Global Energy Monitor trackers (steel, cement, coal, gas) | Plant-level industrial and fuel infrastructure | Free and open, attribution |
The sector signature of industrial energy systems.
The sectors industrial energy systems touches and how strongly they depend on each other: what a study has to observe and model together.
Signature
Energy and its partners
Energy gives power for transport and telecoms to infrastructure (0.8), pumping and treatment to water (0.5) and fertiliser, machinery and cold chains to food (0.5).
W · E · I · F · H · B
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.46 share of total
Strongest relations in play
- Energy → Infrastructure · power for transport and telecoms0.8
- Water → Energy · cooling water and hydropower0.6
- Water → Food · irrigation0.8
- Infrastructure → Water · pipes, dams and treatment works0.6
Who decides, and what the evidence serves.
Energy Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Industry and energy ministries | Which decarbonisation pathways to support for each industrial sub-sector | Pathway scenarios with technology readiness and costs stated |
| Transmission and distribution operators | Where and when to reinforce the grid for electrified industrial clusters | Connection request pipelines; demand pathways by cluster |
| Trade, competition and economic security authorities | Which energy and mineral dependencies expose essential production | Supply concentration indicators and dependency maps |
| Industrial operators and lenders | How energy price and supply shocks affect the viability of a site | Price transmission traces, flexibility options, labelled site evidence |
Outputs this topic produces
- Industrial demand pathways by sub-sector with technology assumptions stated
- Supply-chain dependency maps from energy to essential goods
- Critical mineral exposure briefs
- Flexibility and grid connection scenarios for electrified industrial clusters
How industrial energy systems is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
System model
The couplings between the systems in industrial energy systems: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
What experts ask about industrial energy.
- Which industrial processes can be electrified, which need hydrogen or other fuels, and which need new chemistry?
- How would new industrial loads affect local grids, gas networks and water supply?
- How much industrial demand could shift in time to support the grid, and at what cost to production?
- What process safety risks do new fuels, carriers and storage introduce?
Drivers of industrial energy change.
Industrial plants run for decades and invest in long cycles, so change tends to come at major refurbishment points. Energy prices, carbon policy, customer demand for lower-emission products and the availability of infrastructure all shape when and how plants change.
Temperature requirements
Processes above several hundred degrees are harder to electrify with current technology than low-temperature heat, which heat pumps can supply.
Chemistry, not just fuel
In steel and chemicals, carbon and hydrogen are reactants. Changing them changes the process, not only the energy supply.
Concentrated loads
Electrified industrial sites can require new high-voltage connections and long lead times.
How industrial pathways are studied.
- 01
Process modelling
Mass and energy balances of specific processes. These are reliable for known technologies and uncertain for those still at pilot scale.
- 02
Pathway and system models
Optimisation models study combinations of technologies and infrastructure over decades. They are sensitive to assumed costs and adoption rates.
- 03
Process safety analysis
Hazard identification and consequence analysis, grounded in process and industrial safety engineering, for hydrogen, ammonia and other carriers.
- 04
Site data
Detailed industrial energy data is commercially sensitive and often aggregated, which limits local analysis.
How it is studied, and what the methods cannot say.
- 01Energy generation, storage and grid technologyWeather-driven generation profiles · Storage technology comparisonApplied here
- 02Materials science and chemistryBattery chemistry and thermal runaway · Ageing and corrosion of grid assetsApplied here
- 03Optimisation and operations researchCapacity expansion planning · Unit commitment and dispatch · Restoration sequencingApplied here
- 04Process and industrial safety engineeringNatural hazards triggering accidents · Layers of protection reviewApplied here
- 05Network science and contagionInterdependency mapping · Cascades on multilayer networks · Criticality rankingApplied here
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
Why is industrial heat hard to decarbonise?
How can industry help the grid?
Why do critical minerals belong on an energy page?
Is hydrogen the answer for heavy industry?
Can industry help balance the grid?
Does Energy Nexus assess individual plants?
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