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Industrial energy and water

Industry is a large user of energy, heat and water, and its demand shapes grids, water resources and emissions. Efficiency, electrification, heat pumps, hydrogen and water recycling can change that footprint, while energy price shocks and droughts can stop production. This page sets out how industrial energy and water use work, how they are measured, and what evidence serves the firms, regulators and planners involved.

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01Register

Industrial energy and water on the record.

DossierG-P14 · topic
  1. 01In briefDefinition and scope
  2. 02The question4 mechanisms
  3. 03Key terms3
  4. 04FieldH3 field plate
  5. 05Indicators6
  6. 06PipelineRun graph
  7. 07Sources5
  8. 08Decision holders3
  9. 09Methods4
02The question

Industrial energy and water: how the risk develops.

Resource needs, utility interdependence. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

Mechanism

Heat dominates industrial energy

Much industrial energy is used as heat, at temperatures from low to very high. High-temperature heat is the hardest to electrify.

Mechanism

Price shocks hit energy-intensive sectors

Steel, chemicals, cement, glass and paper are sensitive to energy prices. Sharp rises can curtail production and shift it elsewhere.

Mechanism

Water is a production input

Cooling, processing and cleaning use large volumes of water. Drought and competing demands can force cutbacks.

Mechanism

Efficiency has many small parts

Motors, compressed air, steam systems and heat recovery offer savings that add up but are often overlooked without energy management.

03Geography

Water now in Germany.

Night lights, flood water, population density and true-colour imagery over Germany, from NASA GIBS. Each layer carries its own date.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 4

Water now, for this page

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.

Water now, framed on Germany. Layers as NASA publishes them, each with its own date.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA HLS S30Sources 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 H3 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 H3 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 H3 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 H3 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 H3 cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • GPM IMERG precipitation, NASA Precipitation Processing System; distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • SMAP Level 4 soil moisture and snow mass, NASA Global Modeling and Assimilation Office; distributed by the NASA National Snow and Ice Data Center DAAC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 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 H3 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 H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 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.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Live: NASA EONET Events are indicative, not authority warnings.
  • Observed (EO): NASA HLS S30 (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).
  • River discharge forecast, 30 days with range (GloFAS via Open-Meteo): Contains modified Copernicus Emergency Management Service information 2026; not a flood warning.
  • 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 (14 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
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026
  • Root-zone soil moisture, 0 to 100 cm: SMAP Level 4, NASA NSIDC DAAC · 11 Oct 2026

04Across the Nexus

Industry is a major user of energy and water.

Findings are designed for the Global Sector Risk and Resilience series. Energy management follows ISO 50001 (2018); emissions controls follow the EU Industrial Emissions Directive and its BAT references.

  • Plant energy and water data.
  • Efficiency programme evaluations.
05Console

Energy and circularity board, in outline.

The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.

Energy and circularity board

Industrial energy and water · Industrial park A · Year 2

On planGCRI · Advanced Industry and Robotics

Material flows

  • Recycled
  • Recovered
  • Landfill

Targets

Waste recycled51% of 70% requiredWater reused27% of 50% requiredEnergy from renewables31% of 60% required
Energy and circularity board: the screen's structure, terms and states for Industrial energy and water.Placeholder names and illustrative values; a design, not a record or a live system.
06Indicators

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.

IndicatorUnitCadenceSource typeLabel
Industrial final energy consumptionpetajoules by sectorannualEnergy balancesPublished statistics
Energy intensity of industryenergy per unit of value addedannualEnergy and economic statisticsESTIMATED
Industrial water withdrawalcubic metresannualWater statisticsPublished statistics
Share of electricity in industrial energypercentannualEnergy balancesPublished statistics
Firms with an ISO 50001 energy management certificatecountannualCertification statisticsREPORTED
Production curtailed due to energy or water constraintseventsper eventIndustry and news reportsREPORTED
07Simulator

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 Germany; 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
7 %
Assets still working
17 %
Amplification of the initial damage
11.3 times
Steps to settle
3
Numbers, methods and sources
StepWater working (%)Power working (%)Telecoms working (%)
08989100
1444489
2171739
317033

Methods

  1. Interdependent networks Buldyrev and others (2010), Catastrophic cascade of failures in interdependent networks, Nature 464
  2. Overload cascades Motter and Lai (2002), Physical Review E 66
  3. Betweenness load Brandes (2001), Journal of Mathematical Sociology 25
  4. Multilayer networks Kivela and others (2014), Journal of Complex Networks 2
  5. Infrastructure interdependencies Rinaldi, Peerenboom and Kelly (2001), IEEE Control Systems 21(6)
  6. Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualizing uncertainty about the future, Science 333
  7. 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

08Canvas

From sources to decisions.

The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.

Pipeline canvas · Industrial energy and water as a run graphDesign, not a record
Industrial energy and water: the risk management process, scope to reviewScope, context and criteria set the frame; risks are identified, analysed and evaluated against criteria; treatment follows; monitoring and review and communication run across every step, and the process is recorded and reported. Design of the process, not a record of a run.

Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.

09Twin and cascade simulator

Model industrial energy and water as a system. Run the cascade.

Assembled from the Nexus Standards area profile Industry and manufacturing: 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.

Hazards

  • Natech event
  • Dam failure
  • River flood (set off downstream)
  • Flash flood (set off downstream)
  • Mass displacement (set off downstream)
  • Chemical spill or leak (set off downstream)
  • Emergency-response overload (set off downstream)
  • Widespread power outage (set off downstream)
  • Water supply shortfall (set off downstream)
  • Toxic gas release (set off downstream)
  • Industrial fire (set off downstream)

Controls

  • NS-0 Constitution and principles
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NS-12 Software, model and AI/ML artifacts (supply chain, model cards, dataset sheets)
  • NRS-H60 Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)
  • NRS-H50 Hazard family: Industrial and process accidents (NHS-1 infra.industrial)
  • NRS-H109 Hazard family: Energy-transition technology failures (NHS-1 tech.energy-transition)
  • NRS-X10 Chemical, industrial, nuclear and radiological safety
  • NRS-H54 Hazard family: Signal and platform disruption (NHS-1 cyber.platform)
  • NRS-K14 Domain pack profile: Manufacturing industrial (DOMAIN-014)

Observation

  • eMARS Major Accident Reporting System (listed for reference)
  • World Development Indicators (listed for reference)
  • ILOSTAT (listed for reference)
  • Manufacturing value added as a proportion of GDP and per capita
  • CO2 emission per unit of value added
  • Manufacturing, value added (% of GDP)
  • Direct economic loss to all other damaged or destroyed productive assets attributed to disasters

Example geography

  • The Strait of Malacca: 227 H3 hexagons at resolution 4
  • Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
  • Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
  • Rain rate, last half hour (IMERG), NASA GIBS
  • Surface soil moisture (SMAP), NASA GIBS
10Sources

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.

SourceWhat it givesLicence class
IEA World Energy Balances and industry trackingIndustrial energy use by sector and fuelLicence per product (to check)
FAO AQUASTATWater withdrawal by sectorOpen, FAO terms
Eurostat energy statisticsFinal energy consumption in industryOpen, Eurostat reuse policy
ISO Survey of management system certificatesISO 50001 certification countsPublic, ISO terms
Industrial decarbonisation roadmaps from governmentsPlans and data for heavy industryPublic records, licence per government
11Nexus signature

The nexus signature of industrial energy and water.

The sectors industrial energy and water touches and how strongly they depend on each other: what a study has to observe and model together.

Select corners · hover lines6 / 15 relations

Signature

Water and Energy

Water gives energy cooling water and hydropower (0.6): the strongest relations between the sectors this subject joins.

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
Teaching values for a typical city-region, not measurements for any place. Coupling is the summed strength of the relations in play, as a share of all fifteen.
12Decisions

Who decides, and what the evidence serves.

Advanced Industry and Robotics prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

Who decidesThe questionEvidence this page serves
Industrial firmsWhich efficiency, electrification and water measures to invest inOption analyses; profiles
Energy and water regulatorsHow to plan supply for industrial demandProfiles and exposure evidence
Industry ministriesHow to support energy-intensive sectors through transitionExposure assessments

Outputs this topic produces

  • Industrial energy and water profiles by sector
  • Heat decarbonisation option analyses
  • Energy price exposure assessments
  • Water risk reviews for industrial clusters
13Methods and evidence

How industrial energy and water 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 and water: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.

++−++IndustryWorkTradeCommunitiesEconomyR reinforcingB balancing
Causal loop diagram from the page's systems; signs show the direction of influence. Illustrative structure for a system dynamics or network model, not estimated couplings.
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
14Core questions

What experts ask.

  1. 01

    How much does production depend on each utility?

    Which processes stop, and how quickly, when power, gas, steam or water is interrupted.

  2. 02

    How do plants affect shared resources?

    How industrial demand and discharges affect grids, rivers and aquifers used by others.

  3. 03

    What does decarbonization change?

    How electrification and new fuels shift dependence from fuels to grids.

  4. 04

    How do droughts and heat affect industry?

    Cooling limits, water rights and discharge temperature constraints.

15Mechanisms

What drives the risk.

Energy-intensive processes such as steel, cement, chemicals, glass and paper depend on high-temperature heat and continuous operation. Interruptions can damage equipment and create unsafe conditions during shutdown and restart.

Water is used for cooling, processing, cleaning and steam. In drought, intake may be restricted; in heat, discharge temperatures may exceed permit limits. Plants and power stations on the same river compete for the same resource.

Electrification of industrial heat and the use of hydrogen shift dependence onto power grids and new infrastructure, raising questions about grid capacity and reliability.

Industrial demand also supports utility systems. Large consumers can provide flexibility to grids, and industrial symbiosis lets one plant's waste heat or water serve another.

16Methods and limits

How evidence is gathered, and where it stops.

Method or dataWhat it showsIts limit
Energy and water auditsSite consumption by processSnapshot of current operations
Utility dependency mappingWhich processes rely on which suppliesBackup durations often assumed
Catchment and grid modelsCompetition for shared resourcesRegional data may be coarse
Scenario analysisEffects of curtailment and price shocksDepends on scenario design
17Methods

How it is studied, and what the methods cannot say.

  1. Energy generation, storage and grid technologyProcess heat options · Waste heat recovery · Supply security for energy-intensive plantsApplied here
    Canonical · STEM Commons
  2. Optimization and operations researchProduction scheduling · Energy-aware operations · Buffer and spare sizingApplied here
    Canonical · STEM Commons
  3. Water and environmental engineeringEmission control selection · Industrial wastewater treatment · Community exposure monitoringApplied here
    Canonical · STEM Commons
  4. Sensors, IoT and observation networksCondition monitoring · In-line quality inspection · Securing connected sensorsApplied here
    Canonical · STEM Commons
18Sources

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.

19Questions

Questions and answers.

Why is industrial heat hard to decarbonise?
Because many processes need very high temperatures that are difficult to supply with electricity or heat pumps, requiring other options such as hydrogen or new processes.
What is energy intensity?
Energy used per unit of economic output, which falls as efficiency improves or the economy shifts to less energy-intensive activities.
What is ISO 50001?
An international standard setting requirements for an energy management system that helps organizations improve energy performance.
Why does shutdown create safety risk?
Because processes move through unusual states during shutdown and restart, when many process safety incidents occur.
Does the platform advise on energy procurement?
No. It publishes research on dependencies and resilience and advises on no contract or supplier.
What is industrial symbiosis?
Exchanging waste heat, water or by-products between neighbouring facilities, reducing resource use and creating shared dependencies.
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