CCS Cluster Scenario

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CO₂ Sources

Ship/Pipeline Transport

Injection

Storage

CCSCarbon Dioxide Capture and Storage ClusterCluster = Short name of our project.
In the project‘s CCS cluster scenario, we consider a regional cluster of CO2 emitters whose captured CO2 streams are fed in pipeline network totalling 19.7 Mio t per year.
ScenarioIn the project’s CCS cluster scenario, CO2 streams are fed in a pipeline collection network and then transported by a trunk line (onshore and offshore sections) for offshore geological storage

+++++ How pure do CO₂ streams have to be for accessing CO₂ transport and storage networks? +++++ See results from CLUSTER project in this webtool. +++++ What can be the impacts of temporally variable CO₂ stream composition and mass flow rates on CO₂ transport, injection and storage? ++++ Click on any element of the CCS chain for more information. +++++

CCS Cluster Scenario - CO₂ Sources

↩Start

Click on any plant for more information

CO₂ Sources in CCS Cluster Scenario

CO₂ sources: 7 power plants (fuelled by lignite, hard coal or natural gas) & 4 industrial plants (cement plants, refinery, iron and steel mill)
Selected plant mix corresponds to the emissions‘ ratio of the respective plant categories within the energy and industry sectors in
Germany (as of 2016)Deutsche Emissionshandelsstelle (DEHSt): Treibhausgasemissionen 2016
.

∑ = 19.7 Mio t CO₂ (incl. impurities) captured from CO₂ sources considered in our regional cluster.
Considered capture technologies are post-combustion
capture (
PCCPCC: Separation of CO2 from a (waste/flue/process) gas stream after the CO2-generating process, here: amine-scrubbing
), pre-combustion capture (
PreCCPreCC: Reacting fuel to form a syngas made up of CO2, CO and H2 and removal of CO2 before H2 (and CO) is burnt; here: integrated coal gasification combined cycle, IGCC
) and oxyfuel technology (
OxyOxy: Combustion in a mixture of O2 (instead of air) and recycled flue gas followed by a purification of the captured CO2 stream
). Different plants of the same category in the cluster may be equipped with different capture technologies.

↩CO₂ Sources

Glossary

Energy Scenarios in CCS Cluster

Power plants’ annual operational loads were modelled according to
real electricity production dataElectricity production data from European Network of Transmission System Operators for Electricity (ENTSO-E) @ www.entsoe.eu and European Energy Exchange (EEX) Transparency Platform @ www.eex-transparency.com
in Germany in 2016 with a share of electricity production from renewable energy sources in the total electricity production of 29% (= reference scenario).
Refinery and iron and steel mill: constant operation, cement plants: shut-down period in winter, constant operation during the rest of the year on all scenarios.
Plants‘ operational loads result in plant-specific variable mass flow rates of captured
CO₂ streamsCO2 streams: A CO2 stream is a stream of substances that results from CO2 capture processes and that consists overwhelmingly of CO2 – cf. Directive 2009/31/EC.
that are fed into the collection pipeline network.
→
mass flow ratesTotal mass flow rates of CO2 streams containing CO2 and impurities are termed pipeline mass flow rates
in pipeline network vary throughout the year – see example in figure.
Other energy scenarios set up consider a fuel shift ( = scenario No Lignite) or a higher share of electricity produced from renewable energy sources (= scenarios RE45% and RE80%).

Energy Scenario RE29%

In this energy scenario, power plants‘ annual operational loads were defined based on real
real electricity production dataElectricity production data from European Network of Transmission System Operators for Electricity (ENTSO-E) @ www.entsoe.eu and European Energy Exchange (EEX) Transparency Platform @ www.eex-transparency.com
in Germany in 2016 (as hourly averages).
Resulting
mass flow ratesTotal mass flow rates of CO2 streams containing CO2 and impurities are termed pipeline mass flow rates
in pipeline network were highly variable throughout the year reflecting daily, weekly and seasonal trends – see example in figure.

Scenario Parameters & Results
Pipeline Mass Flow Rate @ Trunk Line Entry	Ø Min. Max.	2197 t/h 1033 t/h 3195 t/h
Fuel Mix
Share of Renewable Energy (RE) Sources

Energy Scenario No Lignite

In this energy scenario, lignite-fired power plants (from scenario RE29%) are substituted by two hard coal fired and one natural power plant (labelled as HC Oxy2, HC PCC2 and NGCC PCC3).
In scenario No Lignite,
mass flow ratesTotal mass flow rates of CO2 streams containing CO2 and impurities are termed pipeline mass flow rates
in the pipeline network were highly variable throughout the year. The average total mass flow rate in the trunk line was significantly lower than in scenario RE29%.

Scenario Parameters & Results
Pipeline Mass Flow Rate @ Trunk Line Entry	Ø Min. Max.	1981 t/h 810 t/h 2876 t/h
Fuel Mix
Share of Renewable Energy (RE) Sources

Energy Scenario RE45%

In this energy scenario, the assumed energy demand is the same as in scenario RE29%. Operational loads of power plants were adapted to an overall electricity production from renewable energy sources of 45% (assuming the same temporal RE electricity production characteristics as in scenario RE29%, but with capacity growth).
In scenario RE45%,
mass flow ratesTotal mass flow rates of CO2 streams containing CO2 and impurities are termed pipeline mass flow rates
in the pipeline network are even more variable throughout the year than in scenario RE29% - see example in figure.

Scenario Parameters & Results
Pipeline Mass Flow Rate @ Trunk Line Entry	Ø Min. Max.	2023 t/h 604 t/h 3186 t/h
Fuel Mix
Share of Renewable Energy (RE) Sources

Energy Scenario RE80%

In this energy scenario, the assumed energy demand is the same as in scenario RE29%. Operational loads of power plants were adapted to an overall electricity production from renewable energy sources of 80% (assuming the same temporal RE electricity production characteristics as in scenario RE29%, but with capacity growth).
In scenario RE80%,
mass flow ratesTotal mass flow rates of CO2 streams containing CO2 and impurities are termed pipeline mass flow rates
in the pipeline network are even more variable throughout the year than in scenario RE29% - see example in figure.

Scenario Parameters & Results
Pipeline Mass Flow Rate @ Trunk Line Entry	Ø Min. Max.	1347 t/h 604 t/h 3130 t/h
Fuel Mix
Share of Renewable Energy (RE) Sources

↩CO₂ Sources

Glossary

CO₂ Avoidance Costs in CCS Cluster

Power plants: CO₂ avoidance costs are calculated as the additional costs (per ton of CO₂ avoided) of CO₂ capture implementation. Power plants’ avoidance costs strongly depend on each plant’s modelled number of full load hours (
FLHFull load hours: Fictive number of hours in full load operation per year that would result in the same amount of impure CO₂ per year.
) – see also CO₂ avoidance costs for each plant in the different energy scenarios.
Industrial plants: CO₂ avoidance costs are defined as the additional costs for CO₂ capture (per ton of CO₂ captured) at each plant. Note that the operational behaviour of industrial plants is the same in all energy scenarios – in consequence their CO₂ avoidance costs don’t vary between the energy scenarios.

CO₂ Avoidance Costs in Scenario RE29%

In all energy scenarios, power plants are deployed according to the merit order, i.e. plants with the lowest electricity production costs (
LCoELCoE: natural gas fired plants > hard coal-fired plants > lignite-fired plants
) come online first to meet the electricity demand.
Due to their small number of full load hours (
FLHFull load hours: Fictive number of hours in full load operation per year that would result in the same amount of impure CO₂ per year.
), natural gas fired power plants have the highest CO₂ avoidance costs.
The very high number of full load hours (
FLHFull load hours: Fictive number of hours in full load operation per year that would result in the same amount of impure CO₂ per year.
) of the industrial plants reduces their CO₂ avoidance costs relative to the power plants having smaller numbers of full load hours.

CO₂ Avoidance Costs in Scenario NoLignite

In this energy scenario, all three lignite fired power plants (in scenario RE29%) are substituted by two hard coal fired and one natural gas fired power plant (labelled as HC Oxy2, HC PCC2 and NGCC PCC3) .
As in the other energy scenarios, power plants with the lowest electricity production costs (
LCoELCoE: natural gas fired plants > hard coal-fired plants > lignite-fired plants
) come online first to meet the electricity demand.
The very small number of full load hours (
FLHFull load hours: Fictive number of hours in full load operation per year that would result in the same amount of impure CO₂ per year.
) of natural gas fired power plants leads to their very high CO₂ avoidance costs (in particular of plant NGCC PCC3).
The very high number of full load hours (
FLHFull load hours: Fictive number of hours in full load operation per year that would result in the same amount of impure CO₂ per year.
) of the industrial plants reduces their CO₂ avoidance costs relative to the power plants having smaller numbers of full load hours.

CO₂ Avoidance Costs in Scenario RE45%

In all energy scenarios, power plants with the lowest electricity production costs (
LCoELCoE: natural gas fired plants > hard coal-fired plants > lignite-fired plants
) come online first to meet the electricity demand.
Due to their small number of full load hours (
FLHFull load hours: Fictive number of hours in full load operation per year that would result in the same amount of impure CO₂ per year.
), natural gas fired power plants have the highest CO₂ avoidance costs.
The very high number of full load hours (
FLHFull load hours: Fictive number of hours in full load operation per year that would result in the same amount of impure CO₂ per year.
) of the industrial plants reduces their CO₂ avoidance costs relative to the power plants having smaller numbers of full load hours.

CO₂ Avoidance Costs in Scenario RE80%

In all energy scenarios, power plants with the lowest electricity production costs (
LCoELCoE: natural gas fired plants > hard coal-fired plants > lignite-fired plants
) come online first to meet the electricity demand.
Due to their small number of full load hours (
FLHFull load hours: Fictive number of hours in full load operation per year that would result in the same amount of impure CO₂ per year.
), natural gas fired power plants have the highest CO₂ avoidance costs.
The very high number of full load hours (
FLHFull load hours: Fictive number of hours in full load operation per year that would result in the same amount of impure CO₂ per year.
) of the industrial plants reduces their CO₂ avoidance costs relative to the power plants having smaller numbers of full load hours.

↩CO₂ Sources

Click for details on Ship Transport

CCS Cluster Scenario - Pipeline Transport

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Variable CO₂ Stream Compositions & Mass Flow Rates in Pipeline Network

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↩Pipeline Transport

Overview: Acid Formation, Reactive Wetting and Material Selection

When different impurities are present in the CO₂ stream (1), they may react with each other forming new impurities such as nitric acid and sulfuric acid (2).
Depending on pressure (p = 7-15 MPa) and temperature (here T = 283 and 278 K in onshore and offshore parts of trunk line, respectively), these acids can condense and form highly acidic droplets on the pipeline wall (3).
If the droplets spread and stay on the pipeline wall, reactive wetting may occur involving corrosion of the pipeline wall (4). For further details klick the boxes below.

↩Pipeline Transport

Costs of Pipeline Transport

The composition of the CO₂ stream influences the stream’s thermophysical properties such as density and viscosity. In turn, pipeline design parameters (and thus costs) are affected by CO₂ stream composition. In our energy scenarios, this impact was small, i.e. costs for the transport of impure and pure CO₂ (given as sum of capital and operating expenditures CAPEX and OPEX, respectively) were very similar.
In each energy scenario, mass flow rates and their variabilities control pipeline capacity utilisation - the higher the capacity utilisation over the year the lower the transport costs (compare, e.g., specific transport costs in scenarios RE29% and RE80%). Designing the trunk line to accommodate 90% of the maximum flow rate and including an onshore interim storage for peak shaving and buffering decreases annual trunk line capital costs, but increases its operational costs in all scenarios.
Overall, in all scenarios transport costs depended more on the transport concept and the degree of capacity utilisation than on the CO₂ purity.

↩Pipeline Transport

CCS Cluster Scenario - Ship Transport

↩Start

Case 1: 1 Mt/year (pure CO₂)

Case 2: 20 Mt/year (pure CO₂ scenario RE29%)

Ship Transport - Logistics

Ship transport of CO₂ is foreseen at low temperatures (here: T = 223 K) to minimise CO₂ vapour pressure. Thus, CO₂ coming from the trunk line (T = 288 K) must be liquefied prior to ship transport.
Coupling the continuous CO₂ supply by pipeline to the discontinuous ship transport requires implementation of an interim storage facility (e.g. an onshore tank).
Timetables for the two cases shown only depended on the ratio of the overall amount of CO₂ transported to the net capacity of the transport components - irrespective of CO₂ stream composition.

↩ Ship Transport

CO₂ Liquefaction for Ship Transport –
Energy Demand

As open processes were found not suitable for the liquefaction of impure CO₂, optimisation of closed-cycle processes (2-stage and 3-stage) was considered in detail for different CO₂ purities.
CO₂ streams from pre-combustion capture
(
Selexol processSelexol Process: CO2 capture by physical absorption in a solvent consisting of a mixture of polyethelyene glycol and dimethylethers (= SelexolTM)
) have a higher vapour pressure at the foreseen transport temperature (due to their relatively high H₂ content) that would require thicker tank walls thereby increasing costs.
Minimum specific energy demands were generally lower employing a 3-stage liquefaction rather than a 2-stage process. Employing a two-phase expander or a liquid-phase expander in combination with an aftercooler and a flash tank for the refrigeration cycle leads to the strongest reduction in the specific energy demand. The achievable reduction of energy demand also depended on CO₂ stream composition as shown in the figure.

↩ Ship Transport

Costs of Ship-Based CO₂ Transport

In the scenario, ship transport over a distance of 100 km was considered.
Costs of ship-based CO₂ transport were calculated as levelised costs of transport
(
LCoTLevelised costs of transportation (LCoT) = LCoTCAPEX + LCoTOPEX i.e. sum of capital and operating expenditures per ton of CO₂ transported. Specific capital expenditures are calculated as the annuity of invest costs depreciated over 20 years using an interest rate of 8%. Specific operating expenditures comprise maintenance, fuel, energy and other operating costs.
) for two cases - the transport of pure CO₂ (1 Mt/year) and impure CO₂ (20 Mt/year) considering CO₂ liquefaction, interim storage (onshore tank), ship loading and transport and CO₂ injection using submerged turret loading.
As in both cases CO₂ transport is accomplished using two ships, specific transport costs are significantly lower in the 20 Mt/year case than in the 1 Mt/year case due to economies of scale.

↩Ship Transport

CCS Cluster Scenario - Injection

↩Start

Generic Offshore Storage Site

A geological model for the fictive injection and storage site was set up from data of a generalised structural model of the Central German North Sea Sector (from literature) using stochastically assigned lithological sequences and rock parameter values. In our scenario, injection is performed in two sandstone layers (P1 and P2 in rocks of
Mittlerer BuntsandsteinThe term Buntsandstein refers to a sequence of rock strata with a thickness of up to several hundred meters and an age of 251 und 243 Mio years. It comprises mainly sandstones, siltstones and claystones as well as salt deposits. Rock strata belonging to the Buntsandstein can be further subdivided in the Unterer, Mittlerer and Oberer Buntsandstein.
) in an anticlinal structure (at centre of model section shown). Note, that these sandstone layers comprise highly porous and highly permeable rocks very favourable for CO₂ injection and storage. These assigned porosity and permeability values are NOT representative for sandstones of
Mittlerer BuntsandsteinThe term Buntsandstein refers to a sequence of rock strata with a thickness of up to several hundred meters and an age of 251 und 243 Mio years. It comprises mainly sandstones, siltstones and claystones as well as salt deposits. Rock strata belonging to the Buntsandstein can be further subdivided in the Unterer, Mittlerer and Oberer Buntsandstein.
in the entire North German Basin.
For injection of the entire amount of impure CO₂ captured annually from all emitters in scenario RE29%, five such storage sites are needed with four injection wells each. CLICK HERE to learn more about the effect of varying injection rates.

↩Injection

Injection Scenarios – Impact of Variable Injection Rates

Scenario A:	Constant mass flow rate of 450 t/h (for injection of 1/5 of total annual amount);
Scenario B:	Variable mass flow rate (fluctuations according to energy scenario RE29%)
Scenario C:	Cyclically fluctuating mass flow rate (e.g. from ship transport supply)

In all injection scenarios, modelled reservoir pressure increased rapidly, leveling to constant values after about one year.
For assessing potential impacts of temporally variable injection rates on barrier rock integrity, a “safety factor” was introduced (= ratio of minimum stress in rock to pore fluid pressure).
Only in scenario B, calculated safety factors temporally dropped below the safety factor threshold value (SF_crit) indicating a potential for tensile failure within the barrier rock in these time periods..

↩Injection Details

Wellbore Cements

The cement system Variodur 50 (Dyckerhoff AG, CEM III) is compatible with CO₂, chlorides and sulfates. It cures by hydration involving e.g. calcium silicate hydrate formation:

2 (3CaO·SiO₂) + 6 H₂O → 3 CaO·2 SiO₂·3 H₂O + 3 Ca(OH)₂
Measured compressive strengths of all modified and/or treated Variodur 50 samples followed values of untreated reference samples irrespective of production and hydration conditions or subsequent alteration by impure CO₂ at simulated reservoir temperature and pressure. Overall, no impact of impure CO₂ on the geomechanical cement properties was evident.
As an innovative alternative approach, a wollastonite-based cement system was investigated that cures by reaction of wollastonite and CO₂ in aqueous solution:

CaSiO₃ + CO₂ → CaCO₃ + SiO₂ (amorph)

Yield of wollastonite carbonation was T-dependent. At T = 333 K nearly complete carbonation occured within 24 h at CO₂ pressures ≥ 0.1 MPa. Addition of impurities (SO₂ and NO₂ 70 ppm_v each) and presence of brine
(250 g salt per litre) had no impact on the carbonate yield.

↩Injection

Injection Costs

For our scenario, injection wells were designed according to standards by the American Petroleum Institute (API). For example, CO₂-compatible steels L80-9Cr or L80-13Cr were considered for tubing and casing at packer and below.
Estimated capital expenditures for one vertical offshore injection well totalled about 30.4 Mio. € comprising drilling and well completion costs (50%), platform costs (32%) and material costs (18%). This resulted in specific invest costs of about 1 €/t CO₂ in our scenario RE29%.
After ship transport (at T = 223 K), liquefied CO₂ must be heated e.g. to 278 K prior to injection to avoid hydrate formation. This can be done on the ship or using a permanently installed platform. For an injection from the ship using a submerged turret system, specific capital costs of 0.5 €/t CO₂ are estimated in our scenario RE29% with operating costs of about 0.2 €/t CO₂.

↩Injection

CCS Cluster Scenario - Storage

↩Start

Behaviour of CO₂ and Impurities in Storage Reservoir

CO₂ migration with time in the storage reservoir was followed by simulating gas saturations. The zone in which the injected CO₂ has displaced most of the formation water (indicated by a gas saturation > 0.9) is termed „dry-out zone“. In general, CO₂ migration depends on various factors such as injection regime, CO₂ stream fluid properties and reservoir rock properties.
In the storage reservoir, impurities may
i) be transported with the migrating CO₂ phase,
ii) diffuse within the CO₂ phase,
iii) dissolve in the formation water,
iv) react with formation water and/or reservoir rocks
(click on arrow button for for details)

depending, among other things, on the compositions of CO₂ stream, formation water and reservoir rocks.

↩Storage

SO₂ Dissolution - Solubility, Speciation and Kinetics

When in contact with formation water, impurities contained in the CO₂ stream may dissolve in the formation water. How much of each impurity dissolves in the formation water depends on

i) each impurity‘s solubility at the prevailing conditions (pressure, temperature, salinity),
ii) each impurity’s dissolution kinetics,
iii) the migration of the CO₂ plume,
iv) reactions of each impurity within the formation water (= speciation).
Reactions of dissolved impurities in the formation water shift the initial phase equilibrium, so that the overall amount of impurity in the formation water is increased.

For example, potentially occurring speciation reactions of SO₂ include

i) hydration and acid formation: SO₂ + H₂O → "H₂SO₃"
ii) dissociation: "H₂SO₃" → H⁺ + HSO₃^-
iii) disproportionation: 4 SO₂ + 4 H₂O → 3 H⁺ + 3 HSO₄^- + H₂S or
iv) oxidation: 2 SO₂ + O₂ + 2 H₂O → 2 H⁺ + 2 HSO₄^-

↩Storage

Costs of geological storage of CO₂

In the cost estimation for the geological storage of CO₂ not only the operational phase, but also the exploratory and preparatory phases were considered.
To accommodate the entire amount of impure CO₂ captured annually from the emitters in scenario RE29%, five storage sites are needed with four injection wells each. This results in specific total injection and storage costs of 2.4 € per ton of impure CO₂ over the entire injection period of 30 years.
Overall, storage costs are highly site-specific and depend on various factors such as water depth, platform type (if any), amount of already existing site data, well design, rock properties (injectivity).
For less favourable porosities and permeabilities than those assumed in scenario RE29%, a higher number of injection wells and/or storage sites are needed for injecting the same amount of impure CO₂ annually, thereby increasing costs.

Estimated Capital Expenditures	per Well or Site / Mio €	in Scenario RE29% / Mio €
Seismic site investigation, exploration well (drilling), well/injectivity tests		≈ 100
Monitoring (seismic survey every three years)		67
Injection well (drilling and completion, material, drilling platform)	30.4 per well	608 (20 wells)
Injection platform	32.5-42.9 per site	163-215 (5 storage sites)
Underwater equipment	29 per site	145 (5 storage sites)
Licenses & concessions		3
Engineering design		3.5
Total		≈ 1100

Estimated Operational Expenditures	Mio €
Injection platforms (30 years)	330

↩Storage

How pure do CO₂ streams have to be for accessing CO₂ transport and storage networks?

⇒ CLUSTER project team recommends to
define “reasonable minimum composition thresholds“

that CO₂ streams should meet for assessing CO₂ pipeline networks
(cf. EU CCS DirectiveEU CCS Directive = Directive 2009/31/EC on the geological storage of carbon dioxide stating that “…. Pipelines for CO2 transport should, where possible, be designed so as to facilitate access of CO2 streams meeting reasonable minimum composition thresholds….)

by...

For more information, see www.bgr.bund.de/CLUSTER-EN

↩Start

Lignite-fired Power Plant

Plant Type	Power Plant
Fuel	Lignite
Capture Technology	Oxyfuel
Used Abbreviation	Lignite Oxy
Block Size	445.9 MW_net
Feed-in Character	Variable: 0; 50-100%
Pipeline Mass Flow Rate	0-452.16 t/h
CO₂ Stream Composition in %

Lignite-fired Power Plant

Plant Type	Power Plant
Fuel	Lignite
Capture Technology	Post-Combustion Capture (PCC)
Used Abbreviation	Lignite PCC
Block Size	395.7 MW_net
Feed-in Character	Variable: 0; 50-100%
Pipeline Mass Flow Rate	0-445.68 t/h
CO₂ Stream Composition in %

Lignite-fired Power Plant

Plant Type	Power Plant
Fuel	Lignite
Capture Technology	Pre Combustion
Used Abbreviation	Lignite PreCC
Block Size	324.0 MW_net
Feed-in Character	Variable: 0; 50-100%
Pipeline Mass Flow Rate	0-312.48 t/h
CO₂ Stream Composition in %

Natural Gas-fired Power Plant

Plant Type	Power Plant
Fuel	Natural Gas
Capture Technology	Post-Combustion Capture (PCC)
Used Abbreviation	NGCC PCC1
Block Size	633.5 MW_net
Feed-in Character	Variable: 0; 40-100%
Pipeline Mass Flow Rate	0-225.72 t/h
CO₂ Stream Composition in %

Natural Gas-fired Power Plant

Plant Type	Power Plant
Fuel	Natural Gas
Capture Technology	Post-Combustion Capture (PCC)
Used Abbreviation	NGCC PCC2
Block Size	633.5 MW_net
Feed-in Character	Variable: 0; 40-100%
Pipeline Mass Flow Rate	0-225.72 t/h
CO₂ Stream Composition in %

Refinery

Plant Type	Refinery
Capture Technology	Post-Combustion Capture (PCC)
Used Abbreviation	Ref. PCC
Block Size	30 000 t crude oil/d
Feed-in Character	Constant: 100%
Pipeline Mass Flow Rate	245.52 t/h
CO₂ Stream Composition in %

Hard Coal-fired Power Plant

Plant Type	Power Plant
Fuel	Hard Coal
Capture Technology	Oxyfuel
Used Abbreviation	Hard Coal Oxy (HC Oxy)
Block Size	431.9 MW_net
Feed-in Character	Variable: 0; 30-100%
Pipeline Mass Flow Rate	0-384.84 t/h
CO₂ Stream Composition in %

Hard Coal-fired Power Plant

Plant Type	Power Plant
Fuel	Hard Coal
Capture Technology	Post-Combustion Capture (PCC)
Used Abbreviation	Hard Coal PCC (HC PCC)
Block Size	431.9 MW_net
Feed-in Character	Variable: 0; 30-100%
Pipeline Mass Flow Rate	0-379.44 t/h
CO₂ Stream Composition in %

Iron and Steel Mill

Plant Type	Iron and Steel Mill
Capture Technology	Post-Combustion Capture (PCC)
Used Abbreviation	Steel PCC
Block Size	6850 t crude steel/d
Feed-in Character	Constant: 100%
Pipeline Mass Flow Rate	358.92 t/h
CO₂ Stream Composition in %

Cement Plant

Plant Type	Cement Plant
Capture Technology	Oxyfuel
Used Abbreviation	Cem. Oxy
Block Size	3000 t clinker/d
Feed-in Character	Constant: 0 or 100%
Pipeline Mass Flow Rate	95.76 t/h
CO₂ Stream Composition in %

Cement Plant

Plant Type	Cement Plant
Capture Technology	Post-Combustion Capture (PCC)
Used Abbreviation	Cem. PCC
Block Size	3000 t clinker/d
Feed-in Character	Constant: 0 or 100%
Pipeline Mass Flow Rate	109.8 t/h
CO₂ Stream Composition in %