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2020
Economic and Environmental
Impact of Coal Washing in India
Prepared for:
NITI Aayog, Government of India
By:
The Energy and Resources Institute, New
Delhi
241271/2020/Infra-E
490 ii
Table of Contents
Table of Contents ............................................................................................................................... ii
List of Tables ........................................................................................................................................ v
List of figures ..................................................................................................................................... vi
Chapter 1: About the study ............................................................................................................... 1
1.1 Introduction ............................................................................................................................... 1
1.2 Relevance of value chain assessment of use of unwashed vs. washed coal for power
generation .......................................................................................................................................... 4
1.3 Terms of reference/Objectives ..................................................................................................... 5
Chapter 2: Framework for integrated assessment ......................................................................... 6
2.1 The overall assessment framework ............................................................................................. 6
2.2 Economic impact assessment framework ................................................................................... 6
2.2.1 Coal Washing .......................................................................................................................... 6
2.2.2 Transportation ....................................................................................................................... 7
2.2.3 Plant Operations .................................................................................................................... 7
2.3 Environmental benefits assessment from use of washed coal ..................................................... 8
Chapter 3: Coal Washing Technology (Practice and Policies) .................................................. 10
3.1 Coal Washing Technologies ................................................................................................... 10
3.1.1 Wet Beneficiation technologies ....................................................................................... 11
3.1.2 Dry beneficiation technologies ........................................................................................ 13
3.1.3 Global Washing technology ............................................................................................. 14
3.2 Global benchmarks and coal washing .................................................................................. 15
3.3 Coal washing in India .............................................................................................................. 16
3.3.1 Reject utilization: Technology and Practices in India ........................................................... 17
3.4 Pricing of thermal coal and regulations– Global vs India .................................................. 18
Chapter 4: Economic Impact Assessment of use of washed coal for Power Generation ..... 21
4.1 Introduction ............................................................................................................................. 21
4.2 Grade wise coal GCV, its ROM cost and ash content ........................................................ 22
4.2.1 Relation between ash content and GCV of coal .................................................................. 22
4.2.2 Cost of coal washing ............................................................................................................ 23
4.3 Relation between Ash percentage and clean coal yield at different level of washing .. 26
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4.4 Rationale for selection of coal grade for baseline analysis................................................ 27
4.5 Washing Cost including impact of yield of clean coal ...................................................... 28
4.6 Transportation ......................................................................................................................... 28
4.7 Cost- Build Up (Landed Cost of coal- washed upto 34% and 32% ash content) ........... 30
4.8 Economic impact of use of washed coal over unwashed coal at power station ............ 30
4.8.1 Technical efficiency improvement ....................................................................................... 31
4.8.2 Simulation Study for typical 500 MW unit ........................................................................... 31
4.8.3 Economic impact on variable cost of power plant .............................................................. 33
4.9 Net economic impact per unit of variable cost (ECR) of electricity generation w.r.t
distance of coal transportation ..................................................................................................... 35
4.9.1 Results for net impact on variable cost with distance of washing for various grade of coal
...................................................................................................................................................... 35
4.10 Sensitivity Analysis ................................................................................................................ 36
4.11 Comparison of change in ECR of some of power plants with theoretical ECR change ............. 38
4.12 Economic Impact on Fixed cost of Power plant ........................................................................ 41
4.12.1 Coal Washing and emission standard ................................................................................ 41
4.13 Coal blending versus washing of coal ........................................................................................ 42
4.14 Case study: Market potential of reject based electricity generation from FBC plants ............. 44
Chapter 5: Environmental Impact Assessment of Coal Washing, use of Washed Coal for
Power Generation and Rejects ....................................................................................................... 46
5.1 Environmental Impact associated with coal washery operations ............................................. 46
5.1.1 Effluent Water and its environmental impact ..................................................................... 46
5.1.2 Theoretical Analysis of Electricity consumption and CO2 impacts ................................ 47
5.2 Environmental benefits from the use of washed coal for power generation ................. 46
5.2.1 Environmental benefit from the reduction in carbon emissions ......................................... 49
5.2.2 Social cost of carbon and the incremental environmental benefits .................................... 51
5.3 Comparative environmental impact assessment of use of washery rejects in CBFC vis-à-vis
their use in TPS.................................................................................................................................. 51
5.4 Study Methodology ................................................................................................................... 52
5.3.1 Detailed approach for emission estimation for scenarios ................................................... 53
5.3.2 Key assumptions .................................................................................................................. 54
5.5 Comparative analysis of environmental impacts across scenarios ........................................... 54
5.5.1 Comparative assessment of CO2 emissions ........................................................................ 55
5.5.2 Comparative assessment of PM emissions .......................................................................... 55
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5.5.3 Sensitivity tests and analysis ................................................................................................ 56
5.5.4 Environmental Impact of rejects used in unregulated sector ............................................. 57
5.5.5 Conclusion ............................................................................................................................ 57
5.6 Other anticipated benefits .......................................................................................................... 58
5.6.1 Reduced fugitive emissions during transportation .............................................................. 58
5.6.2 Reduced fly ash .................................................................................................................... 58
Chapter 6: Summary ......................................................................................................................... 59
Annexure I (Economic Assessment): An Integrated value chain framework and economic
impacts from use of washed coal ................................................................................................. 64
Annexure II: case study by CMPDI & NPC at Satpura thermal power plant ..................................... 65
Annexure III: Latest CEA case study .................................................................................................. 66
Annexure IV: Cost heads from mine to power plant for different grades and levels of washing for
plants situated at 1000km from washeries ...................................................................................... 67
Annexure V: Unit size wise illustration of impact on variable cost due to coal washing of G13 coal
washed upto 34% .............................................................................................................................. 68
Annexure VI: Case study of reject generation from different washeries, its utilization and
contribution to emissions ................................................................................................................. 69
Annexure VII: Sensitivity analysis of the reject quality parameters on emissions in different
utilization scenarios .......................................................................................................................... 70
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List of Tables
Table 1: Old and new environmental norms for thermal power stations ..................................... 1
Table 2: Country-wise coal washing technologies in practice ...................................................... 14
Table 3: Country-wise ash content and energy Content of thermal coal .................................... 15
Table 4: Applicable technology as per NGMI rating (Mahavir Coal washery, 2015) .............. 17
Table 5: Global experience in coal pricing to reduce the negative externalities ........................ 19
Table 6: Cost components in capital costs and its respective share in percentage .................... 24
Table 7: A sample calculation used in model has been presented for G13 coal .................................. 28
Table 8: Annual transportation benefits due to use of washed coal in a 500 MW unit. ...................... 29
Table 9: Coal cost build up for raw and washed coal (in Rs/Ton) ............................................... 30
Table 10: Unit size wise classification of coal based capacity ....................................................... 31
Table 11: Change in variable cost due to APC, Heat Rate, GCV and Higher coal Cost ............. 34
Table 12: Change in variable cost due to Transportation, Taxes, ROM and cleaning cost ......... 34
Table 20: Net incremental environmental benefit (in Rs/kWh) .................................................... 51
Table 22: Coal consumption & Electricity Generation for S1, S2 & F1 scenarios ................................. 54
Table 23: Scenario results for emissions ........................................................................................... 54
Table 24: Sensitivity Parameters ....................................................................................................... 56
Table 25: Sensitivity analysis ............................................................................................................. 56
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List of figures
Figure 1: Status of ESP implementation in the country ................................................................... 2
Figure 2: Overall methodology to assess CO2 emissions under each scenario ............................ 9
Figure 3: Relation between Ash% and GCV of coal developed using CMPDI data - TERI
analysis (left), Relation used by NIT Rourkela study (right) ....................................................... 23
Figure 4: Composition of operating costs for a typical dense media separation equipped
washery ............................................................................................................................................... 25
Figure5: Clean coal yield w.r.t ash percentage of input ROM coal - TERI analysis................... 26
Figure 6: Grade-Wise Coal Production (2017-18) ................................................................................. 27
Figure 7: Subsidiary-wise coal production (2017-18) ........................................................................... 27
Figure 8: Impact on variable cost of power plant for using washing coal upto 34% and 32%
ash ........................................................................................................................................................ 36
Figure 9: Change in Variable cost of power generation w.r.t surface transportation, yields, and
distance between washery and power plant ........................................................................................ 37
Figure 10: Coal consumption in 2018 under each scenario ............................................................ 50
Figure 11: CO2 emissions in 2018 under each scenario .................................................................. 50
Figure 12: Scenario Description ............................................................................................................ 53
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1
Chapter 1: About the study
1.1 Introduction
Electricity plays an extremely important role for sustaining economic growth, social
development and welfare of a nation. Coal based electricity is a dominant source of
electricity generation in India and is expected to remain the primary source of electricity in
the short to medium term.
Use of coal at the same time raises environmental concerns. The impacts of increased coal
utilisation will have increased environmental impacts from emissions of air pollutants
during coal mining, coal transportation and coal combustion, contamination of the surface
and ground water, forest loss due to mining, etc.
In order to address the environmental challenges, Ministry of Environment Forest and
Climate Change under the ‚Environment (Protection) Amendment Rules, 2015’’ specified
revised limits in respect of four pollutants as well as specific water consumption for power
stations. The existing stations as well as new stations including upcoming stations were
required to comply with the new standards within 2 years of issue of notification i.e. by 7
December 2017. Table 1 presents the summary of the old and new emission norms.
Table 1: Old and new environmental norms for thermal power stations
Category PM
(mg/Nm3)
SOX
(mg/Nm3)
NOx
(mg/Nm3)
Old
Norms
TPPs greater than 210 MW 350 None None
TPPs with less than 210 MW 150
New
Norms
TPSs (Units) Installed
Before 31.12.03
100 600 (For < 500 MW Unit) 600
TPPs between 31.12.03 to 31.12.16 50 200(For => 500 MW Unit) 300
From 01.01.17 30 100 100
Source: MoEFCC (2015)
1
Notification with regard to water consumption include:
1. All plants with once through cooling (OTC) shall install cooling tower and achieve specific water
consumption (SWC) up to maximum of 3.5 m
3
/MWh within a period of 2 years from the date of
publication of the notification.
2. All CT-based plants reduce SWC up to maximum of 3.5 m
3
/MWh within a period of 2years from
the date of publication of the notification.
1
http://www. indiaenvironmentportal.org.in/files/file/Moef%20 notification%20-%20gazette.pdf
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3. New plants to be installed after 1 January 2017 shall have to meet SWC up to maximum of
2.5m
3
/MWh and achieve zero waste water discharge.
The new notification implies huge investment on retrofitting and adding new pollution
control technologies particularly to address the new PM and SOx emission norms. The
status with regard to the implementation is still unclear. Till 2019, Electrostatic Precipitators
(ESPs) in plants with aggregate capacity of 66 GW had either been upgraded or were
planned to be upgraded, out of which 3.3 GW was in National Capital Region (NCR) while
remaining 62.7 GW was across rest of India. ESP installation in nearly 2.4 GW of TPPs in
Delhi NCR had been awarded. For the rest of India, ESP implementation plan was available
for 61 GW of TPPs as presented in figure 1
2
.
Figure 1: Status of ESP implementation in the country
An alternative cost effective route often professed is promotion of use of washed coal. It has
come up in various pilot research analysis (Prasad, 2019) undertaken in the past that
increased use of washed coal helps in reducing costs, improves environmental loads and
also increases efficiency of pollution control devices.
MoEF&CC has issued a few notifications to mandate use of the washed coal although the
guidelines have been revised periodically as provided in Box 1. However, MoEF&CC in its
recent notification dated 21
st
May, 2020 has amended its earlier notification regarding use of
coal with ash content less than 34%. The new notification allows use of unwashed coal by
thermal power plants, without stipulations of ash content or distance.
2
https://www.teriin.org/sites/default/files/2020-02/emissions-control-thermal-power.pdf
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Box 1: MoEF&CC few notifications to mandate use of the washed coal
In 2001, MOEF&CC issued the first set of regulations that mandated use of 34% ash
content washed coal if transported more than 1,000 km or if burned in
environmentally sensitive areas.
oPower plants using Fluidized Bed Combustion (CFBC, PFBC & AFBC) and Integrated
Gasification Combined Cycle combustion technologies were exempted to use beneficiated coal
irrespective of their locations.
In November 2014 directive for supplying coal of not more than 34% ash content for
TPPs located beyond 750 km from the pithead with effect from January 1, 2015 and
those located beyond 500 km from the pithead with effect from June 5, 2016.
oFurther, the notification mandated that all new (as well as expansion) opencast projects of 2.5
million tonnes per annum (mtpa) and above capacity, which are not linked to pithead power
stations, should be designed with integrated washeries.
The domestic production of coal in India is dominated by non-coking coal and the reserves
of coking coal are limited. The total coal consumption in India was 968 MT in 2018-19, out of
which domestically produced 69 MT (7.1%) was coking coal, 715MT (74%) non-coking coal
and 183 MT (19%)imported coal, which is coking coal (Ministry of Coal, Annual report,
2019-20
3
).
Indian coal is characterized having high ash content and low heat value in nature compared
to coals of US or Australian origin. More than 90 percent of coal mined in India is produced
from opencast mines contributing to inert contamination. Run of mine (ROM) coal extracted
from opencast mines in India typically has ash contents in the range of 35 percent to as high
as 50%, low and reducing calorific value (2500-4500 kcal/kg). Presence of high ash content
is reported to lead to faster wear and tear of power plant components, difficulty in
pulverisation, poor emissivity and flame temperature, low radiative transfer, generation of
excessive amounts of fly-ash containing large amounts of un-burnt carbon, etc. Further,
transportation of high-ash coal across long distances leads to increased cost because large
quantities of non-combustible inert materials are also transported. It also leads to increased
freight service demand causing excess pressure on the rail transportation. Transportation of
inert materials also lead to additional consumption of energy due to rail and road
transportation contributing to emission of carbon-dioxide (CO2) and other green-house
gases (GHG) from the mode of transport (rail and road) (Prasad, 2019).
Review of studies brings out that coal washing lead to higher quality fuel with better heat
value (could increase thermal efficiencies by as much as 4%-5% on existing pulverized coal-
fired boilers with an accompanying reduction of CO2 emissions), reduces fuel quantity
3
https://coal.nic.in/sites/upload_files/coal/files/coalupload/AnnualReport2019-20/Chapter6-en.pdf
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requirements (handled and transported) and cost of transportation for the same energy
value, enhances utilization of installed generation capacity, reduces capital expenditure in
the power plant, , reduces ash volume in both pre-combustion and post combustion stages,
and also reduces land requirement for ash disposal (particular in newer plants) (Criag D.
Zamuda and Mark A. Sharpe 2007).
The benefits summarized in the in the EIA Guidance Manual – Coal Washeries published by
MoEF&CC in 2010 are presented below.
Increased generation efficiency, mainly due to the reduction in energy loss as inert
material passes through the combustion process
Increased plant availability
Reduced investment costs
Reduced operation and maintenance (O&M) costs due to less wear and reduced costs
for fuel and ash handling
Energy conservation in the transportation sector and lower transportation costs
Less impurities and improved coal quality
Reduced load on the air pollution control system; and
Reduction in the amount of solid waste that has to be disposed off
In the presence of these possible benefits, thermal power stations (TPSs) have the following
options that allow a power station to follow new environment norms:
1. By coal washing alone, if possible.
2. By coal washing and smaller retrofit/new pollution control equipment.
3. Only by bigger retrofit / new pollution control equipment.
1.2 Relevance of value chain assessment of use of unwashed vs.
washed coal for power generation
The use of washed coal in India is still limited despite the benefits stated and supportive and
mandatory policy interventions being in place for over two decades. This limited rate of
establishment of coal washeries is often related to many economic, environmental and
financial issues but one of the major issues is the perception that coal washing increases the
cost of electricity generation which adversely impacts the plants using washed coal in merit
order scheduling.
Based on discussion with key stakeholders and experts, trade in coal is based on coal
preparation after mining that include washing post which the prices are fixed. Currently
India’s leading coal mining company Coal India Limited (CIL) offers both Run of Mine
(RoM) coal as well as prepared/washed coal. It was reported that despite India’s switching
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over to fully variable Gross Calorific Value (GCV) based grading of thermal coals from the
earlier Useful Heat Value (UHV) system, the enhancement of the heat value/reduction of ash
in coals after washing (of below G10 grade i.e. G11 to G17) is not off-setting the cost of
washing and the economics is not favourable to coal companies. Because of this many power
plants do not prefer using washed coal.
It is extremely important to acknowledge here that there are significant variations with
regard to plant capacity, vintages, coal quality usage, and location of power stations from
mining and washing sites, etc. Such complexities in the Indian power sector call for
development of an integrated value chain framework and plant specific data analysis using
that framework which will help in improved understanding of the impacts of use of washed
coal over unwashed coal. Such an assessment will help in developing an implementation
strategy of possible use of washed coal for all TPSs in India that is economically feasible and
environmentally viable.
1.3 Terms of reference/Objectives
In line with the above discussion, the study aims to:
Assess technological impact of coal washing
Assess economic impact of coal washing on power generation
Assess environmental impact of use of washed coal; (including environmental and
economic impact of coal transportation in respect of raw coal and washed coal from
coal mine to power plant)
Explore the rationale for fixing threshold limit of maintaining 34% ash content in coal
for transportation beyond 500 km limit
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6
Chapter 2: Framework for integrated
assessment
2.1 The overall assessment framework
Economic activities, particularly when it is linked to use of natural resources, not only have
benefits but also costs linked to environment. Such costs may arise during the extraction
phase as well as during the use phase of natural resources. In case of coal based power
generation, there are potential benefits and adverse environmental impacts along the use of
the unwashed coal vis-à-vis washed coal based value chain of electricity generation. With
reference to objective and scope, the study has been divided into (i) economic and (ii)
environmental impact assessment along the aforementioned coal based value chains.
2.2 Economic impact assessment framework
The impact of costs and benefits of coal washing for power generation is based on the value
chain impact analysis. The associated costs and benefits are estimated for the shift from raw
coal usage to washed coal usage at the power plant end. Economic impact is traced and
measured by coal supply chains from mining, washing, transportation, and especially in the
process of power generation.
In order to have a good understanding and analysis of the costs and benefits across the
value chain, the relationship needs to capture the current/existing practices among each
activity along the value chain, which is developed using secondary as well as primary data
from the key stakeholders. Further, the economic analysis is based on technical evaluation
and an integrated framework consisting of specific elements of the system is developed and
demonstrated for the use of washed coal to the amount and proportion of costs in each value
addition activity.
Economic evaluation of beneficiated coal is based on the results from improved coal quality
and reduced ash content and detailed analysis is provided in Chapter 4. This chapter deals
with economic impacts of coal washing up to 34 percent and 32 percent and presents the
cost of coal beneficiation and its implications on transportation, cost build-up of landed coal
to power plant, impact on variable cost of electricity generation for different capacity sizes,
impact on fixed cost of power plants which were in pipeline as per National Electricity Plan
(NEP). Economic assessment of the coal washing includes examining technical and
economic parameters as under.
2.2.1 Coal Washing
The coal washing process depends on a number of factors, mainly the washability
characteristics of input coal, ash content and moisture requirement of output coal, capital
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and operational costs, etc. The cost components associated with economics of coal washing
are :
Capital cost- cost towards design & engineering, civil works, plant and machinery,
etc.
Operational cost - salary & wages, consumables like water, energy, lubricants,
magnetite, maintenance consumables, and washery overhauling charge,
administrative expenses and miscellaneous charges, etc.
Rebate on washery rejects.
2.2.2 Transportation
The benefit due to washed coal transportation depends on the distance of the power station
from the loading point of mines/washery. The coal beneficiation process results in GCV
improvement of coal which in turn leads to reduction of coal requirement to generate same
quantum of electricity as well as savings in coal transportation cost.
2.2.3 Plant Operations
When the low ash coal is used for power generation, it impacts the technical operating
parameters which results in decrease in operating costs and are reflected in the variable cost
component of tariff. The incremental benefits from use of washed coal leading to better unit
heat rate, improved aux. power consumption on the variable cost have been analysed on
three variants of unit size of power plant i.e. 660MW (super-critical), 500MW and 300 MW
(sub-critical). The three important aspects in this context are as under.
Fixed costs: The impact on fixed cost due to reduction in capital requirement for a power
plant operating on washed coal can only be seen for the new power plants proposed.
Improvement in capital cost of power plant, designed for usage of washed coal, is
considered for overall impacts in fixed cost. Also, there will be additional benefits by use of
washed coal such as reduction in land requirement for ash disposal for power plant using
34% ash coal instead of 41%
4
.
Variable costs: Improved quality coal will lead to reduced coal consumption, improved heat
rate, reduced auxiliary power consumption (APC), higher availability and life of equipment
etc., to support unit generation.
Pollution Control Equipment (PCE) requirement: In order to comply with the new
emission limits, Electrostatic Precipitator (ESP) retrofitting, new installation of Flue Gas
Desulfurization (FGD) units and De-NOx systems are required. The impact of washed coal
on emissions estimated using secondary literature.
4
https://www.orfonline.org/wp-content/uploads/2017/07/ORF_Report_CoalBeneficiation_FinalForUpload.pdf
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2.3 Environmental benefits assessment from use of washed coal
The environmental benefits in this study have been assessed from the reduced CO2
emissions from the use of washed coal over the current mix of coal usage to produce the
same level of electricity generated in 2018. Current practices majorly include consumption of
raw coal and small share of blended and beneficiated coal. Out of the total 1,303 TWh of
electricity generated in 2018, 985 TWh was from coal based power plants. The total coal
consumption to produce 985 TWh of electricity was considered under the three scenarios to
assess CO2 emission. Improvement in specific coal consumption due to washing of coal has
been considered to estimate coal consumption and CO2 emissions across scenarios. The three
different scenarios are described as:
BAU scenario (S1): The actual coal consumption of 2018 is used to estimate the
overall CO2 emissions from coal based thermal power generation. The ash content
data of coal is available at the power plant use end which represents mixture of raw
coal, blended coal and washed coal.
Washed Coal Scenario (34%)(S2): In this scenario, all the TPSs currently using
higher than 34% washed coal (including blended coal) shift to coal containing 34%
ash irrespective of plant capacity and the distance; while other power stations using
coal having less than 34% ash content continue with that mix. The improvement in
ash content also leads to improvement in specific coal consumption.
Washed Coal Scenario (30%) (S3): All the TPSs switch to coal having 30% ash; while
other power stations using coal having less than 30% ash content continue with the
mix, and the specific coal consumption is improved w.r.t ash content reduction.
The installed capacity and the electricity generation remains the same, however the specific
coal consumption to produce them varies under the three scenarios which finally leads to a
difference in the total coal consumption and thus CO2 emissions at the country level.
The overall methodology used to assess the CO2 emissions under the three scenarios is given
in Figure 2.
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Installed
capacity
(2018)
Electricity
generation
(2018)
Specific coal
consumption
CO2 emissions
Plant specific
assessment
of coal
reduction
S1 S2 S3 S2
Figure 2: Overall methodology to assess CO2 emissions under each scenario
Once the CO2 emissions are estimated under each scenario for 2018, the cost of climate
change due to emission of CO2was estimated as part of the study using the social cost of
carbon based on estimates presented in (Nordhaus, 2017). Social cost of carbon
(SCC)represents the economic cost caused due to an additional tonne of CO2 emissions or its
equivalent in the atmosphere. Though various models are used to estimate the monetary
value associated with the cost of CO2 emissions, using multiple assumptions, this study uses
the estimates from Nordhaus (2017), which uses the DICE (Dynamic Integrated model of
Climate and the Economy) framework. Therefore, due to the reduced CO2 emissions under
each scenario, a gap could be estimated leading to an incremental environmental benefit.
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10
Chapter 3: Coal Washing Technology
(Practice and Policies)
The global coal washing technologies as well as the technologies used in India are presented
in this chapter on the basis of secondary research and stakeholder consultation. Coal
preparation process includes a range of methods such as (a) crushing; (b) screening into
different size fractions; (c) washing (physical, chemical and mechanical); (d) dewatering; (e)
thermal drying (f) blending (g) waste disposal, designed for a specific particle size range
such as coarse (>10mm), medium (>1mm), fine (1-0.15mm) and ultra-fine <0.15mm). Coal
beneficiation starts with preparation process by crushing and screening of ROM coal, which
removes some of the in-organic material. Coal is then advanced for washing process which
predominantly involves using water and mechanical techniques to remove the impurities
(mainly minerals, ash and sulphur -to some extent) from raw coal. As a result, the process
improves the heat content of coal on weight basis.
The choice of technology and process design for the beneficiation depends on a number of
factors such as (IEA Clean coal centre, 2017):
1. Washability characteristics of the raw coal feedstock
2. Percentage fines content of the ROM coal, which is dependent on the extraction
technique, and results in carbon losses
3. Assessment of coal quality over a longer period
4. Market, regulatory and taxation environment
5. Capital and operating costs for the selected coal preparation plant (CPP) design;
6. Projected value of the separated coal products
7. Cost of waste treatment and disposal.
These factors may vary from country to country and hence, the technology and process
design needs to be carefully considered before adoption. The section below will focus on the
present status of washing technology used in India & abroad and the supporting policies.
3.1 Coal Washing Technologies
The physical separation process is the most common method for washing coal particles due
to its efficiency and optimal yield attainable at a wide density cut-point range
5
. Within this,
dense media separation technologies are mostly deployed world-wide in wet beneficiation
methods. Gravity separation using air as media are commonly used in dry separation
methods. The dry-beneficiation methods are cost effective compared to dense media
separation methods. However, globally, these were considered to be much inferior to wet
5
https://www.iea-coal.org/report/coal-beneficiation-ccc-278/
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processing methods but are better than simple de-shaling of coal. In wet separation, particle
separation efficiency (Ep)
6
is normally in the range 0.01–0.05, while for dry methods the
reported range of 0.07–0.25
7
. Also, extensive gas and dust handling needs to be done for
operating in dry conditions. Over the years, due to growing concerns on water availability
and climate change, there is an emerging trend to adopt dry separation technologies in
certain regions supported by further & innovation and development. The particle separation
efficiency difference between wet and dry methods has also reduced substantially and so the
adoption.
3.1.1 Wet Beneficiation technologies
Under the wet beneficiation process, jigs and dense media bath technologies are commonly
in practice for washing coarse coal (exceeding 10mm) and medium coal (1-10mm).
i) Jigs (Pulsating water as media (Batac/ Baum)
ii) Dense –media separation
a. Dense/Heavy Media Vessel or Baths,
b. Dense/Heavy Media cyclone
c. Combination of above)
Jigs
Jigs are commonly used for washing coarse coal. Its operation depends on stratification in a
bed of coal based on specific gravity when the carrying water is pulsed. The shale tends to
sink and cleaner coal rises due to specific gravity difference to water. There are two types of
Jig commonly practiced; which are Baum and BATAC Jig. Even though, Baum jig can clean a
wide range of coal particle sizes, it is most effective at washing 10-35mm (CIL, 2020).
However, BATAC jig is suitable to wash medium coal (less than 10mm) as well. Hard dense
minerals like feldspar, etc. are also used for enhancing the stratification and prevent
rejigging, which is suitable for medium coal washing.
Dense media separation
Dense/Heavy Medium vessels also operate by specific gravity difference; however rather
than using water as the separating medium, a suspension of magnetite and water called
pulp is used. The dense-media washing process typically rejects about 20–40% of the ROM
coal feed
8
. Different types of vessels are used for dense-medium separators such as baths,
cyclones and cylindrical centrifugal separators. For coarse coal washing, various kinds of
baths are used, but substantial quantity of dense- medium, and therefore magnetite is
required for its operation. Hence the control and recovery of magnetite is at-most important
6
The effectiveness of a coal separation method may be assessed by examining the particle efficiency (Ep)
value; this provides a measure of the particle density difference at 25% and 75% coal partition. Lower Ep
values indicate a more efficient separation and low ash content.
7
https://www.iea-coal.org/report/coal-beneficiation-ccc-278/
8
https://www.iea-coal.org/report/coal-beneficiation-ccc-278/
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from operations perspective. For smaller sizes, cyclones are used where the settling time is
short and throughput is relatively high. The centrifugal effect created by vortex when pulp
is passed through inlet pipe of cyclone, separates the light carbon particles and high density
shale at wide range of density-cut points (1.3-1.9) and at high separation efficiency (0.02-
0.03). It can also process high near gravity material coal (NGMI -10 or more) at lowest Ep.
Cylindrical centrifugal separators are used for coarse and intermediate coal.
While dense media both provides better separation efficiency while washing coarse coal but
in case of fine and ultra-fine particles, dense media techniques are not suitable due to
requirement of long settling times and low coal recovery rate. Also for the ultra-fine coal
particles, dense media separation couldn’t be carried out based on density cut as difference
range is very small. Thus, for the separation of fine & ultra-fine particles, technologies such
as spirals, water only cyclones and flotation techniques (suitable for ultra-fine particles also)
are commonly practiced across the world.
Concentration table
In a concentrated air table separator, tables are tilted, ribbed and they move back and forth
in a horizontal direction. The feed and dense media is fed to the separator. The lighter coal
particles settle to the bottom of the table, while the heavier particles (rejects) are collected in
the ribs and are carried to the end of the table. Even though, the capacity is quite small; the
fine coal (upto density cut 1.5) can be clean cost effectively by this unit.
Hydro cyclones
Hydro-cyclones are water-based cyclones where the heavier particles accumulate near the
walls and are removed via the base cone. Lighter (cleaner) particles stay nearer the center
and are removed at the top via the vortex finder. Thus, the cyclone diameter has a significant
influence on the separation efficiency.
Flotation
The floatation technique is another method for cleaning fines and ultra-fine coal particles.
There are two types of floatation methods; Column and Froth flotation. Froth flotation cells,
the widely used technique within, utilize the hydrophobic property of coal particles to
separate and the method is suitable for washing ultrafine particles as well. The coal-water
mixture is conditioned with chemical reagents so that air bubbles will adhere only to the
coal and float it to the top, while the high dense particles sink. Air is bubbled up through the
slurry in the cell and clean coal is collected in the froth that forms at the top. This type of
cleaning is very complex and expensive and is principally for metallurgical coals.
Spirals
Spiral separation is internationally practiced method for fine coal washing in which coal-
water slurry is fed into a spiral conduit. As it flows downward, stratification occurs for the
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heavier particles which will concentrate in a band along the spiral. An equipped adjustable
splitter separates the stream into two product streams – a clean coal and the rejects.
3.1.2 Dry beneficiation technologies
Dry separation techniques are based on exploiting different aspects of coal particle
properties such as coal density, particle shape, friction, electrostatics, and magnetism. Major
dry beneficiation technologies deployed across countries are:
1. Air dense media fluidized bed separation (ADMFB)
2. Fluidized bed separation
3. Compound dry separation – Air Jigs, concentration air tables, FGX separator, TFX-8
AIR jigs, Pneumatic sorter etc.
These dry beneficiation technologies are used for beneficiation of coarse and medium coal
particle sizes. Out of these, compound dry separators are the dominant ones which mainly
use the particle friction, shape and density of coal particles.
Air dense media fluidized bed separation
This dry coal preparation technique uses a pseudo fluid system of the mix of dense medium
(fine magnetite powder) and screened coal (6-50mm) as separating medium, to process a
certain density cut and thus separate light and heavy particles according to density from
stable and uniform air-solid suspension in fluidized bed. The low-density material floats up
to the top and the high-density material sinks down to the bottom based on Archimedis
principle. The Indian scholars have tested this method with high ash coal and the separation
results show that the ash content is reduced from 40% to around 32%–35.5% and separate
clean coal product with a 60 %–72 % yield and high separation efficiency (Ep value is 0.12)
9
.
Air Jig
The Air jig operates using similar mechanism to that of a wet jig but here, the water is
replaced by compressed air. In the separating process the screened coal is fed into the
separator from a hopper and exposed to a combination of vibration and air pulses through a
perforated table. Light particles are lifted upward at a higher elevation than the dense
particles, loosened and stratified due to its relative density before it is separately collected
using scrapper.
FGX dry beneficiation
An FGX dry beneficiation is a density-based method which operates by integrating two
separation mechanisms i.e. air fluidized bed and a conventional air table separator. It is
more efficient and has better dust control. There are more than 2000 FGX separators
9
https://link.springer.com/article/10.1007/s40789-014-0014-5
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installed in China and other coal producing countries
10
. This is because; it separates at
typical relative density of 1.8 to 2 and shows relatively high particle efficiency Ep values of
0.2 to 0.3. However, the technology is restricted to process of coarse coal 6-80mm size range
mainly due to the operational difficulty when the particle size changes with high proportion
fines.
Other Key developments
The TFX-8 AIR jig is capable to process extended range of coal particles with an Ep value of
0.2, which is comparable to FGX unit. The experience of the technology with high ash Indian
coal shows that it can achieve ash reduction from 42% to 27% at 59% yield, middling having
ash content 55% at 22%yield and rejects having ash content 73% at 19%
11
yield. Several
developments are also there in with dry fine coal treatment technologies such as tribo-
electrostatic and magnetic separators but not commercialized yet due to its cost
12
.
Also, fine coal beneficiation with the application of a Pulsing ADMFB, pulsing air flow with
periodical velocity is introduced to air dense medium fluidized bed (ADMFB) to separate
fine coal by changing the velocity and pulsation frequency of air flow.
Recently, X-ray optical sorter is getting greater attention as it could separates the heavy
particles and light particles based on the color change occurred due to different radiation
absorption potential. This is under trial in different parts of world (CIL).
3.1.3 Global Washing technology
Globally, there is lack of uniformity in the coal characteristics especially the quality of input
coal and the washability characteristics due to the formation of coal. Hence, for the
determination of technology and process design of coal beneficiation, these are factored. A
summary of the key washing technologies deployed world-wide are shown in the table 2
below:
Table 2: Country-wise coal washing technologies in practice
Countries Coarse washing Medium washing Fine washing
Australia Mainly by DMC (diameter
1000 mm or more), Drums
or baths in some plants, Jigs
at few plants.
Spiral + Jameson or micro
cell technology Froth
flotation
China Mainly jigs (60%), Dense
medium separator
(Drewboy, vertical lifting
wheel separator)
2-product dense medium
cyclones (diameter 660–
1300 mm) 3-product dense
medium cyclones
(diameter 1000–1400 mm)
Mainly flotation Column
flotation (for very fine coal)
USA Dense medium vessel Dense medium cyclones Water-only cyclone Spirals
10
http://www.fgxseptechllc.com/dry-coal-processing/separators/
11
https://www.iea-coal.org/report/coal-beneficiation-ccc-278/
12
https://link.springer.com/article/10.1007/s40789-014-0014-5
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Countries Coarse washing Medium washing Fine washing
(diameter<1000 mm) Combination of both froth
flotation (very fine coal after
desliming: 35–40 µm)
Russia Heavy media baths & cyclones, Jigging, Flotation, High-angle separators (water-only
cyclones), Spiral separators, Pneumatics (for thermal brown coals)
Canada Dense medium vessel Dense medium cyclones
(diameter <1000 mm)
Water only cyclone, Spirals,
Combination of both Froth
flotation (very fine coal)
South
Africa
Mainly large diameter
pump fed dense media
cyclones, Dense medium
separator (Wemco Drum,
Drewboy), Jigs at few plants
Smaller diameter cyclones Limited use of froth flotation
Mainly spirals
India ROM jigs (moving screen
jig), Coarse coal jigs, Dense
medium separator, Barrel
washer
Small coal jig, Dense
medium cyclones
(diameter 600–1000 mm)
Flotation, Spirals, Water
only cyclones
Source: (IEA Clean coal centre, 2017)
3.2 Global benchmarks and coal washing
Number of coal producing countries have been involved in coal-washing practices to meet
the benchmarks standards for exporting thermal coal and to obtain desired quality (GCV)
and characteristics (Ash %). Table 3 below compares the thermal coal quality standards of
some countries.
Table 3: Country-wise ash content and energy Content of thermal coal
13
Coal benchmarks Energy content
(kcal)
Ash Content
(%)
Australian thermal export coal benchmark 6000 12-14%
Australian thermal export coal secondary benchmark 5500 20%
Indonesian thermal export coal 4500-5000 2-10%
South African thermal export coal 6000 15%
Russian thermal export coal 6500 10-25%
China domestic thermal coal 4000-5500 20-40%
Indian domestic thermal coal 4400 25-45%
It can be inferred that Australian coal has high energy content and thus require lesser
quantity to produce similar unit of electricity, which is the reason Australia stands second in
exporting thermal coal after Indonesia, which provide better environmental outcome as a
result of lesser ash content in coal. Since, countries seeking to limit the externalities from coal
fired power plants, aggressively banned imports of high ash and sulphur containing coal
which necessitates the washing of coal for the export dependent countries. Interestingly,
13
https://ieefa.org/wp-content/uploads/2015/10/IEEFA-Australian-coal-briefing-note.pdf
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South African thermal coal reserves contain high ash content, but still majority of coal is
processed to obtain the export grade coal at much lower yield and the intermediate product
so-called middlings are utilized for domestic thermal power generation. While the countries
like China and USA having 1380 MT/y and 636 MT/y of coal washing capacity (2015), has
not much to do with the exports but the pricing, environmental targets and efficiency which
drives the coal washing chain.
The scale of coal washing deployment in some countries is steered by the energy and
environmental policy regulations for the operations of thermal coal, while some countries
engaged in coal washing practices to maintain the competitive share in international export
markets.
An overview of the global coal washing practices has been presented above. However, for
proper assessment with regard to benchmarking and related policies for promoting use of
washed coal needs interaction and consultation with International/national experts.
3.3 Coal washing in India
Indian coal has general properties of Gondwana coal, having high ash content (35-55%),
high moisture content (4-20%), low Sulphur content (0.2-0.7%) and low calorific value
(between 2500- 5000Kcal/kg), which is much less than the normal range of 5000 to 8000
kcal/kg observed in other countries. Also, more than 75% of the Indian coal has ash content
more than 30%, even as high as 50%. It also has poor washability characteristics (i.e. low
Near Gravity Material Index (NGMI) and Govindarajan Washability Index (GWI)) and high
level of rejection >30% due to distribution of ash also challenge the washing economics
1415
(IEA Clean coal centre, 2017) (DOI, 2018). The Indian washery owners/developers
underlined that with each percentage decrease in ash content in washed coal, there is
considerable decrease in yield of clean coal.
Currently, technologies such as barrel washer, coarse coal jig for de-shaling; Jigs
(Baum/BATAC/ROM/AIR), Dense media bath, cyc lone for coarse and medium coal
treatments, water only cyclones, classifying cyclones, spiral concentrator, froth floatation
cells, Hydraulic hindered bed or Teeter bed separators, vibrating tables for fine coal
treatment are adopted and preferred by Indian coal washeries (Global mining, ACB, CIL
2020) but due to costlier and complicated technology, fine coal treatment is not carried out at
scale in India. Heavy media cyclone is the most favorable process as it is able to wash high
NGMI coal at high separation efficiency (low Ep).
14
https://www.iea-coal.org/report/coal-beneficiation-ccc-278/
15
https://doi.org/10.1016/B978-0-12-812632-5.00009-4
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Ultrafine technologies are not adopted in India yet due to the requirement of complex
technology and unviable economics due to washability characteristics.
Table 4: Applicable technology as per NGMI rating (Mahavir Coal washery, 2015)
NGMI Type of coal Process
0-7 Simple coal Jig
7-10 Moderately difficult Bath, tables, spirals
10-15 Difficult to wash
HM Cylone
15-20 Very difficult
20-25 Exceedingly difficult
>25 Formidable
3.3.1 Reject utilization: Technology and Practices in India
The washery rejects are discarded in considerable quantities during the process of
beneficiation. Typically, it contains combustible matter with heat content below 2200 Kcal/kg
with corresponding ash content of more than 60% as ideal separation of organic and in-
organic matter doesn’t takes place in physical separation(ACB,2020) (ORF, 2017). However,
the quantity generated and GCV of washery rejects are based on the input coal washability
characteristics, ash content in ROM coal, ash content requirement in output coal, selection of
technology, washing process design etc. The rejects thus generated can potentially be used
in FBC boilers (BP Singh, 2007) such as the following technology alternatives for captive
power generation for ash content upto 65%.
i. Atmospheric FBC,
ii. Bubbling Fluidized Bed Combustor (BFBC)
iii. Circulating Fluidized Bed Combustor (CFBC)
iv. Pressurized Fluidized Bed Combustor (PFBC)
Use of coal rejects in highly efficient FBC plants reduces the CO2 emission and use of the
lime stone or dolomite feed reduces SO2 emissions significantly. According to Bureau of
Energy Efficiency (BEE), advantages of FBC plants are listed below
16
:
The boiler can firecoals with ash content as high as 62% (also fines < 6mm) and
having calorific value as low as 2,500 KCal/kg.Even carbon content of only 1% by
weight can sustain the fluidized bed combustion.
Combustion efficiency of over 95% irrespective of ash content and operate at overall
efficiency of 84% (plus or minus 2%). Resulting in fuel savings of 4% at elevated
pressure operation which also reduces CO2 emissions.
High turbulence of the bed facilitates quick start up and shut down. Inherent high
thermal storage characteristics can easily absorb fluctuation in fuel feed rates.
Response to changing load is comparable to that of oil-fired boilers.
16
https://beeindia.gov.in/sites/default/files/2Ch6.pdf
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The absence of moving parts in the combustion zone results in a high degree of
reliability and low maintenance costs
Since the temperature of the furnace is in the range of 750 – 900 °C in FBC boilers,
even coal of low ash fusion temperature can be burnt without clinker formation thus
making ash removal easier, may automated and reduce associated costs.
SO2formation can be significantly reduced by addition of limestone or dolomite for
high sulphur coals. Low combustion temperature eliminates NOx formation.
The CO2 in the flue gases will be in the order of 14 – 15% at full load. Hence, the FBC
boiler can operate at low excess air (only 20 - 25%).
The remaining rejects having low GCV (typically less than 1500 kCal/kg) are presently used
for backfilling purpose at mines as it is less prone to self-combustion and other safety issues.
A technical committee constituted in 2018 provided the relevant recommendation to MoC
with respect to utilization of Coal washery rejects which is reproduced below:
‚A threshold for GCV of washery rejects as 1500 kcal/kg may be considered presently and rejects
having GCV 1500 kcal/kg and above may be used in FBC/CFBC based power plants whereas rejects of
GCV less than 1500 kcal/kg (i.e. low GCV rejects) may be used as replacement of construction
material for highways, railways, dams, embankments, reclamation of land, brick making etc. Globally
also, coal washery reject is being used as a replacement of construction material in many countries.
Coal washery rejects along with biomass may also be used as briquettes for generation of cooking gas.‛
Based on inputs from stakeholders, it can be inferred that FBC based power plants,
construction/infrastructure sectors and domestic fuel producers are the potential consumers
of the coal washery rejects. Some current reject utilization practices in India are:
Rejects from existing Piparwarwashery are being sold to consumers through e-
auction. Presently, the GCV of the rejects falls under Grade G-14 to G-16.
Rejects from existing Gidiwashery were handled by Gidi Reject based FBC CPP
which was designed to handle coal washery rejects with GCV varying from 1500 to
4000 kcal/kg. The minimum GCV of rejects fed in the past in Gidi CPP was about
1629 kcal/kg. However, the same is not operational since 3.01.15. Presently,
Gidiwashery rejects are collected on surface dumps prior to disposal/sale.
Rejects from existing Global Coal Mining Washery in Talcher are being sold to
Indian Metal &Ferrous Alloys (IMFA) to be used in CFBC boiler in their captive
power plant. The GCV of rejects is around 1800kcal/kg with 65% of ash which is
blended with high quality coal for operating at designed configurations.
3.4 Pricing of thermal coal and regulations– Global vs India
Encouraging the use of better quality coal is considered as one of the easiest ways to reduce
the negative externalities associated and to reap operational and economic gains through-
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out value chain. Therefore, better pricing and stringent regulations on coal and its usage
have due importance in mitigating the impact on environment. For this, it is important to
draw learning from international experiences for addressing environmental concerns in the
Indian context through pricing of non-coking coal and regulations for its usage. In many of
the coal producing countries, the pricing of non-coking coal is based on an elaborate manner
taking into consideration the sustainability issue which is discussed in the table 5below.
Table 5: Global experience in coal pricing to reduce the negative externalities
Country Key pricing interventions to accommodate environment aspect
Poland Coal price is a function of four quality parameters: heat value, ash+ sulphur and
moisture (heat/freight loss). Also, three ash content ranges were applied to
encourage coal cleaning. There is a 2 percent improvement in price for marginal
decrease in ash content. This increase in price was designed to compensate the cost
of beneficiation.
Indonesia Benchmark coal pricing, price imposes penalty for high sulphur (emission),
moisture (heat/freight loss) and ash to account for the particulate emissions and
for disposal cum storage of ash.
United Kingdom Ash penalty on utilities for disposal (landfill tax) in addition to actual ash disposal
cost.
United states Determined in the free market, based among others on environmental issues and
on the quality of coal: calorific value, sulphur and ash content.
Thermal power plant is heavily penalized, for emission of every additional tonne
of CO2 beyond the prescribed limit under pacific coast action plan
China Besides production cost and labour cost, price component consists of resource cost,
environment cost, sustainable development cost and safety cost. Sustainable cost
component is levied based on type of coal and tonnages consumed. Utilized for
solving regional ecological/environmental problems.
Source: (Rachit Tiwari, 2015)
In India, the pricing of non-coking coal is based on its heating value (GCV), discounting the
ash and moisture. Prices are notified for various GCV bands/grades, uniformly spaced at an
interval of 300kCal/kg ranging from 2200 kCal/Kg to 7000kCal/kg. The price increases
according to the heat content of the coal and vice versa which encourages consumption of
low priced coal in general.
For an Indian coal, having approximately same ash content, GCV is found to be varying up
to 900 Kcal/Kg which creates an incentive to disregard the negative externalities in handling
and use of coal caused through-out value chain. The cost of beneficiation is also fixed by
individual washeries, irrespective of the heat content of washed coal. This leads to utilities
paying cost which is not commensurate with the heat value of washed coal. The prevailing
generation scheduling based on merit order dispatch (based on variable cost) also
discourages the use of washed coal. On the other side, the emissions are per se regulated by
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government through coal ash content and emission norms for coal based power plants.
However, as of now there are no-penalties for non-compliance of emission norms. The
government has mandated the coal based power plants beyond 500 km from sources to use
raw coal or blended coal or beneficiated coal with ash content not exceeding 34% on
quarterly average basis
17
(MoEFCC, 2015). Hence, there is a need to look at a proper pricing
structure of washed coal, penalty for non-compliance of emission norms, and uniform reject
utilization policy.
17
http://www.indiaenvironmentportal.org.in/files/file/supply%20and%20use%20of%20coal%20with%20ash%2
0content%20MOEF.pdf
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21
Chapter 4: Economic Impact
Assessment of use of washed coal for
Power Generation
4.1 Introduction
Coal beneficiation is one of the ways to improve heat value of coal used in power plant. As
discussed in preceding chapters, coal washing removes dust/overburden and rock
sediments from the coal which leads to improvement in the heating value of coal resulting in
environmental as well as economic benefits at various stages of value chain. The economic
impacts have been analyzed historically. At Satpura Thermal Power Station, in one 210 MW
unit, trial of beneficiated non-coking coal from Nandan washery, WCL was carried out for
one month under a science & technology project by the expert team represented by
CMPDI, WCL, CEA, MPEB and NPC where benefits have been observed in all the areas
of environment, economics, quality power generation, etc. A study conducted by CMPDI in
1998 for a group of coal based thermal power plants located at a distance beyond 1000 km
from the source coal pit-head also suggested similar improvements. The detailed findings
are given in Annexure 2. The Ronghe Committee report (1998) on economic benefits of using
beneficiated non-coking coal in thermal power stations appraised the techno economic
benefits for two power plants namely Kayamkulam & Yamunanagar.
Coal washing results in improved GCV, lesser ash content. It also shows improvement in
heat rate and specific coal consumption at generating station end. This chapter analyses
economic impacts of coal washing up to 34 percent and 32 percent and highlights the cost of
coal beneficiation and its implications on transportation, cost build-up of landed coal,
impact on variable cost of electricity generation for three representative unit capacity sizes,
impact on fixed cost of power plants which are in pipeline as per under National Electricity
Plan (NEP), 2018. Other economic impacts like less ash disposal area requirement and
enhanced service life with improved efficiency of plant and machineries have not been
considered in the present study due to limitation in collection of primary data
18
.
While taking the learning from previous studies and empirical analysis, interaction was
done with key stakeholders such as CIL, CMPDI, NTPC, BHEL, and MOEFCC and sector
experts. Latest available data has been used to conduct analysis considering that the Indian
thermal power generation and coal sectors have witnessed changes which have a bearing on
power generation and emissions. The factors involving economics of power generation such
as quality and cost of raw coal, cost build-up of coal supplied, railway freight, tax structure,
18
https://www.researchgate.net/publication/279848475_Economic_Assessment_of_Utilization_of_Beneficiate
d_Indian_Power_Coal_for_Thermal_Power_Generation
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have, over the years been periodically revised/increased. Deployment of higher sized and
more efficient generating units, cost of complying to prevailing environment pollution
control norms have also impacted economics of power generation
Improvement in GCV and ash content in the washed coal vis-a-vis RoM coal are extremely
important factors in the context of use of beneficiated coal for power generation. GCV being
a function fixed carbon, volatile matter, inherent moisture and ash, estimation of ash% in
any grade of coal is a challenge, more so because of the GCV spread of 300 kCal/kg in each
grade. In absence of primary data of proximate analysis, we have relied upon secondary
data for drawing relationship between Ash% and GCV of coal.
To analyze economic impact of washed coal for various ash% improvements, distance from
mine/washery to power plant, and type of generating unit, a framework for integrated
assessment across the value chain has been developed. The framework has been developed
to study the results for three variants of unit size of power plants i.e. 660MW (super-critical),
500MW and 300 MW (sub-critical). Based on this framework, the cost build-up of landed
ROM coal and washed coal, and their impact on variable cost of power generation have been
presented in this chapter.
4.2 Grade wise coal GCV, its ROM cost and ash content
The quality of coal plays an important role in the regard to environmental impact of a
thermal power plant. Due to drift origin of Indian coal, inorganic impurities are intimately
mixed in the coal, resulting in difficult coal characteristics. In India, coal quality varies in a
wide GCV range of 7000-3000 kCal/kg. Indian coal has been classified by CIL in various
Grades starting from G1 to G17 as per the GCV range of coal. In Indian power sector, mostly
G11, G12, and G13 grades of coal (GCV range of 3400-4300 kCal/kg) are used for power
generation. CIL issues the Grade wise pithead Run of Mine (ROM) coal price applicable for
various coal fields. In our modeling framework, we have considered pithead ROM coal price
from CIL notification on dated 8 Jan’2018
19
.
4.2.1 Relation between ash content and GCV of coal
GCV of coal depends on the percentage / composition of four components, fixed carbon
(FC), volatile matter, inherent moisture and ash. Proximate analysis of coal gives the value
of this composition of coal in terms of these components. In the absence of proximate
analysis for various grades and GCV of coal, Ash% vs GCV correlation developed by using
CMPDI data and the correlation presented in the NIT, Rourkela study
20
has been used in the
study (figure 3).
19
https://www.coalindia.in/DesktopModules/DocumentList/documents/Price_Notification_dated_08.01.2018
_effective_from_0000_Hrs_of_09.01.2018_09012018.pdf
20
http://ethesis.nitrkl.ac.in/6858/1/PREDICTION_Seervi_2015.pdf
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y = -8271.8x + 7341.8
R² = 0.7806
0
1000
2000
3000
4000
5000
30%35%40%45%50%55%60%
GCV (kCal/kg)
Ash %
Figure 3: Relation between Ash% and GCV of coal developed using CMPDI data - TERI analysis
(left), Relation used by NIT Rourkela study (right)
Of the two, relationship reported in NIT Rourkela study has been considered for analysis
view of higher number of sample points, greater variability in ash% versus GCV as well as
better fit (R
2
= 0.872).
4.2.2 Cost of coal washing
In India, non- coking coal washeries are designed and set up to beneficiate high ash content
coal (38%-55%) to ash not exceeding 34% in order to comply with the norms for coal usage
in power plants located beyond 500 km from the pit-head. The process design and
equipment selection for the coal beneficiation plant depends on a number of factors, mainly
the washability characteristics of input coal, ash content requirement and moisture of output
coal, capital and operational costs, projected value of output coal, etc.
Generally, the cost of washing consists of capital costs and operational costs, and total cost
of washing depends on the project model. This also includes the additional capital and
operational costs incurred for water treatment process and costs for pollution control. In
India, washeries have been set up under different models such as Build, Operate, and
Maintain (BOM), Build, Own, Operate (BOO), turnkey basis. Historically, washeries were set
up by CIL majorly under Build, Operate, and Maintain (BOM) concept where the selected
bidders needed to install the washery, and operate and maintain the same for initial period
of 10 years with a provision for further extension of 5 years
21
. Under this model
Finance for projects developed through BOM model was required to be provided by
CIL or its subsidiaries.
The power plants needs to sign contract with CIL or its subsidiaries, if they require to
beneficiate the input coal from CIL owned washeries.
21
https://books.google.co.in/books?id=M-
hODQAAQBAJ&pg=PA165&lpg=PA165&dq=boo+model+washery+india&source=bl&ots=fo3CJE2wSz&sig=ACfU
3U3dtp7LbbpiCjOcsXPTCKL3j8A09Q&hl=en&sa=X&ved=2ahUKEwinnuOymJrpAhXDxTgGHa-
GDBMQ6AEwBHoECAoQAQ#v=onepage&q=boo%20model%20washery%20india&f=false
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Since ownership of washery and coal production are with same entity, the cost of
washed coal from their washeries is used to be notified instead of charging cost of
beneficiation and cost of input ROM coal separately.
Since 2003, considering the funding constraints of CIL, GOI has been encouraging
adopting BOOM and turn-key model to speed up development of CIL’s nine planned
non-coking coal washeries. Many private players such as ACB (India) Ltd, Global
washeries etc. have already set up their washeries on Built, Own, Operate and Maintain
(BOOM) model which attracts financing from private sector.
Under such model the practice was that,
The power plants need to sign separate contracts with coal producing company
for procuring ROM coal and with washery to beneficiate the coal procured.
Since ownership of washery is with different entity, the cost of washing is
charged separately unlike in the BOM model.
The detailed break-down of cost of washing (capital and operational costs) of a typical
washery are discussed here in after.
4.2.1.1 Capital costs
The capital cost of washery typically includes costs of land and plant &machinery. In India,
jigs and dense media separation process are commonly followed. On the basis of
stakeholder consultations with private and public sector coal washeries and pre-feasibility
reports of various washeries, the capital cost of washeries is noted to be typically in the
range of Rs 18 - 35 Cr/ MTPA for commonly used De–shaling/Jigs based plants to dense
media separation-based plants. The cost of financing also has an impact on the capital costs.
However, typically it amounts to around 25 – 50 Rs/Tonne of throughput coal. The table
below provides the components in capital costs and its respective share for a typical dense
media separation based plant.
Table 6: Cost components in capital costs and its respective share in percentage
S n: Cost components Percentage Cost (%)
1 Design and engineering 1-2
2 Building and structural (incl. Furniture, fittings and
electrical)
40-45
3 Plant and machinery (including pollution control
equipment in washery)
54-58
Source: Authors estimate
22
22
Compiled data from washery stakeholders, prefeasibility reports prepared by CMPDI and private companies
for setting up washeries.
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4.2.1.2 Operating costs
The operating cost of the washing includes salary & wages, consumables (Incl. magnetite,
flocculants, lubricants, electricity, maintenance (incl. spares), washery overhauling charge,
administrative expenses and miscellaneous charges. Altogether, it ranges between Rs 80-
120/Tonne of raw coal for beneficiating coal having ash content of 42% to 34%. Composition
of operating costs for a typical dense media separation equipped washery is shown in figure
4. For de-shaling or Jig based plants, the operational cost reduces by Rs 20-30/Tonne of raw
coal as the magnetite is not required and so the magnetite recovery process. However, as
discussed in chapter 3, de-shaling or Jig based plants have certain limitations to efficiently
beneficiate coal with high ash, low washability characteristics.
Figure 4: Composition of operating costs for a typical dense media separation equipped washery
Source: (CMPDI) (MAHAVIR COAL WASHERIES PVT. LTD, 2015)
Overall, the most important parameters which affects the technology/process selection and
so, the cost of washing are washability characteristics& ash content of ROM coal, target ash
content of output coal The total cost of coal washing in the market typically ranges in Rs 90-
160/Tonne throughput of raw coal (incl. GST). Out of the total cost of washing, the
operational cost is the major component which comes around 70-80%
23
and the fixed cost is
comes around 20-30% for majority of the projects. GST on coal washing is currently being
charged at 18% slab.
24
4.2.1.3 Price added to ROM and comparison with data from secondary sources
As discussed in previous sections, washing of coal generally costs around Rs 90-160/Tonne.
The landed cost of washed coal at the power plant includes impact of clean coal yield which
is a function of input coal characteristics such as ash % and extent of washing. To take clean
23
Assumption includes loan repayment period@ 12 years, interest on loan @11%, depreciation upto 90%, debt: equity@ 70:30 and
100% equity (BOM), return on equity @12%, economic life of project 15 years.
24
For the process of washing ROM coal having ash content of 42% to beneficiate to 34%
14%
19%
44%
7%
14%
2%
Salary & wages
Maintenance (incl. spares)
Consumables (incl floculant, magnetite,
lubricants, electricity etc.)
Overhauling charges
Administrative expenses
Miscellenious
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y = -1.5976x
2
- 1.5122x + 1.5251
R² = 0.9408
0%
20%
40%
60%
80%
100%
30%35%40%45%50%55%60%
Yield %
Ash %
Clean Coal Yield at 28%
coal yield in to account, we have developed a correlation between input ash content and
clean coal yield for washing upto 34%, 32%, 28% and 25% ash using data of CMPDI.
4.3 Relation between Ash percentage and clean coal yield at different
level of washing
Due to high degree of ash content in Indian coal, there is comparatively low yield of washed
coal. Using coal data received from CMPDI such as - ash % in input coal, yields observed at
various degree of washed coal with 34%, 32%, 28% and 25% ash, correlations have been
established (figure 5).
Figure5: Clean coal yield w.r.t ash percentage of input ROM coal - TERI analysis
From figure 5 it can be seen that for 43% ash ROM coal, yield of clean coal varies as 75%,
70%, 58%, and 49% for washing of coal upto 34%, 32%, 28%, and 25% ash in output coal
respectively. Using these yield curve, yield % has been calculated for wide range of input
ash% and used in integrated value chain framework.
y = -0.6826x
2
- 2.1917x + 1.5626
R² = 0.8947
0%
20%
40%
60%
80%
100%
30%35%40%45%50%55%60%
Yield %
Ash %
Clean Coal Yield at 25%
y = -2.8854x
2
- 0.4913x + 1.5002
R² = 0.9661
0%
20%
40%
60%
80%
100%
30%35%40%45%50%55%60%
Yield %
Ash %
Clean Coal Yield at 34%
y = -1.1164x
2
- 2.2268x + 1.8607
R² = 0.9816
0%
20%
40%
60%
80%
100%
30%35%40%45%50%55%60%
Yield %
Ash %
Clean Coal Yield at 32%
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4.4 Rationale for selection of coal grade for baseline analysis
An analysis of the use of grades of coal for thermal power generation in India reveals that it
primarily ranges from G 7 to G14. However G 11 is found to have the highest consumption
as can be observed from figure 6. The estimated consumption of G11 is more than 160
million tonne followed by G10 (115 million tonne), G13 (95 million tonne) and G12 (60
million tonne). Coal of G-10 & G-11 grade has lesser ash content (30-36%) and bulk of it may
not be candidate for the washing with ash content not exceeding 34%. However coal of G12
and inferior grade will require washing that has the benefits of enhancing energy content
while having the potential to reduce emissions.
Figure 6: Grade-Wise Coal Production (2017-18)
Source: Coal Directory of India
Most of the coal mined in India is by the various subsidiaries of Coal India Limited. The
Largest coal production subsidiaries are MCL & SECL (combined production of around
46%), and the coal produced largely fall under G-13 & G-14 grades which may require
washing (figure 6). An analysis of the production figures of MCL reveal that the G14 has the
highest production (34.5 million tonne) followed by G12 (34 million tonne) and G13 (32.2
million tonne).
Figure 7: Subsidiary-wise coal production (2017-18)
0
50
100
150
200
1234567891011121314151617
MT
Coal Grade
Grade-Wise Coal Production (2017-18)
0
50
100
150
200
ECL BCCL CCL NCL WCL SECL MCL NEC SCCL
MT
Subsidiary-wise coal production (2017-18)
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Source: Coal Directory of India
Most of the private washeries are situated in MCL as well as SECL, which are washing coal
having ash ranging between 40-45% or even higher as reported by washeries in MCL
indicating the grade of coal washed in India is G-13 coal for beneficiation. Hence from the
consumption and washing perspective G13 grade has been considered for analysis under
the reference case. Sensitivity analysis with G12 and G11 grade of coal has also been carried
out.
4.5 Washing Cost including impact of yield of clean coal
Washing of coal cost usually varies in range of Rs 90-160 /Tonne but it is the yield of washed
coal that makes washing of coal expensive. After taking yield correlations, washing costs
including impact of clean coal yield for various grades of coal have been estimated. A
sample calculation used in model has been presented in table 7 for G13 coal (GCV of 3550
kCal/kg) for which yield of clean coal is 75% for 9% ash improvement.
Table 7: A sample calculation used in model has been presented for G13 coal
S.N Particulars UOM Variables
A Input coal quantity Ton 1
B Input coal ash% % 43%
C Washing up to ash % % 34%
D Yield (as per curves) % 75%
E Input coal cost( including taxes) Rs/Tonne 1508
F Washing cost Rs/Tonne 122
G Rebate on rejects Rs/Tonne 0
H Washed coal quantity (yield) Tonne 0.75
I Reject quantity (A-H) Tonne 0.25
J Total per ton cost for washed coal ((E+F)/H – G*I) Rs/Tonne 2174
K Washing cost (including yield impact) (J-E) Rs/Tonne 666
In above table, no rebate on rejects (GCV: 1347kCal/kg) has been considered because CIL
considers the rejects at zero value in their books. Also, it can be seen from above table that
due to the yield of coal, the overall washing cost is significantly high, Rs 666/Ton, as
compared to basic washing cost of Rs 122/Ton.
4.6 Transportation
In India, installed capacity of thermal power stations that are pit head stands around 34 GW
for which the main source of transportation is trucks, MGR or through over land conveyors,
remaining capacity around 163 GW (80%) gets coal hauled over much longer distances,
mostly through rail network. Due to the fact that Indian coal has high ash % and average ash
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content touched 42% in 1999-2000
25
, many attempts were made to address the issue of
hauling ash at such longer distances. There are implications of additional burden on
railways to deliver the higher ash quantity and higher freight charges as well as reduced
energy content. Average lead distance of coal shipments in India has fallen from 639 km in
2012 to 460 km in 2017,
26
while the tonnage carried has increased from 456 MT to 533 MT
during the same duration. Falling average lead distance can be attributed to the fact that the
plant load factor (PLF) of generating stations that are distant from coal mines (Arora, 2017)
have been falling after FY 2012 due to the one-time coal linkage rationalization.
Indian Railways had revised freight charges multiple times in the past few years and also
withdrawn the busy season surcharges and development charges levied on transportation of
‘coal and coke’. While estimating economic impact of washed coal transportation over
unwashed coal, freight charges on delivery of coal have been considered from rate circular
no 19 of 2019 released by Ministry of Railways
27
. Moreover the impact of increase in
moisture content by 5% and decrease in density by 10% is considered on payload of the rail
transport.
The benefit due to washed coal transportation will increase with increasing distance
between the generating station and loading point at washeries as could be seen from Table 8.
The freight charges and the benefits have been used to calculate landed cost of coal and the
overall impact on variable cost of electricity generation.
Table 8: Annual transportation benefits due to use of washed coal in a 500 MW unit.
Annual benefits
(INR crore)
Washed up to 34% Washed up to 32%
Distance travelled G-11 G-12 G-13 G-11 G-12 G-13
250 3 12 21 7 15 25
500 6 22 40 13 29 47
750 9 30 56 19 40 65
1000 11 38 70 23 50 82
Savings from transportation of coal is the major saving and after breakeven distance, counter
balances the impact of higher yield and washing of coal. This aspect has been discussed in
greater details in later sections of report.
25
https://www.orfonline.org/wp-
content/uploads/2017/07/ORF_Report_CoalBeneficiation_FinalForUpload.pdf
26
https://www.brookings.edu/wp-content/uploads/2018/07/Railways-and-coal.pdf
27
http://www.indianrailways.gov.in/railwayboard/uploads/directorate/traffic_comm/downloads/Freight_Rate
_2018/RC_19_2018.PDF
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4.7 Cost- Build Up (Landed Cost of coal- washed upto 34% and 32%
ash content)
The build-up of landed cost of coal consists of various components such as ROM cost,
central and state-level taxes, levies, duties, cess, washing cost and freight etc.. Economic
impact has been analysed for the grades of coal which are commonly used in power
generation. Built-up cost of coal using a sample G-13 Grade (for 500 km – the distance
beyond which coal washing was required as per Environmental protection rule dated 2
nd
January, 2014) is given in Table 9.
Table 9: Coal cost build up for raw and washed coal (in Rs/Ton)
S.N. UOM Raw
Coal
34% 32%
X GCV Kcal 3550 4286 4445
Y Ash% % 43% 34% 32%
Z Yield % 1.00 0.75 0.70
1 ROM Rs/Tonne 817 817 817
2 Sizing charges Rs/Tonne 87 87 87
3 Royalty Rs/Tonne 114 114 114
4 MMDR - central fund Rs/Tonne 2 2 2
5 MMDR - central fund Rs/Tonne 34 34 34
6 GST compensation cess Rs/Tonne 400 400 400
7 GST on coal Rs/Tonne 53 53 53
A Total cost of ROM coal (1+2+3+4+5+6+7) Rs/Tonne 1508 1508 1508
B Surface transportation to/from washery to
railway slidings
Rs/Tonne
60 60 60
8 coal washing charges Rs/Tonne 0 666 866
9 GST on coal washing @ 18% Rs/Tonne 0 22 24
C Coal washing charges (8+9) Rs/Tonne 0 688 890
10 Railway Freight charge (500km) Rs/Tonne 1107 1107 1107
11 GST on transportation (@ 12%) Rs/Tonne 133 133 133
D Transportation charges (10+11)) Rs/Tonne 1240 1240 1240
E Total delivered cost of coal (A+B+C+D) Rs/Tonne 2808 3496 3698
F Cost per GCV (E/X) Paise/kCal 79 82 83
G Variable cost for 500 MW Unit Rs/kWh 2.02 2.08 2.12
*The cost build up for landed coal is based on per ton of delivered coal
#Coal washing charges includes the impact of yield of G13 coal due to washing up to 34% and 32%
The landed costs of coal or delivered cost of coal for various grades, yields, ash% have been
considered to analyse the impact of washing on variable cost of power generation.
4.8 Economic impact of use of washed coal over unwashed coal at
power station
Coal based power plants, with 75% contribution in total electricity generation in 2019,
continue to play dominating role in electricity generation in India. The current Indian coal
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based fleet has capacity of 197 GW which consists of diverse unit sizes ranging from 210
MW to 800 MW, which can be grouped in to three categories as given in Table 10. To assess
the economic impact of coal beneficiation, impact on variable cost of electricity generation
due to use of coal washing has been analysed on three representative unit sizes of 300, 500 &
660 MW.
Table 10: Unit size wise classification of coal based capacity
Unit size (MW) Total capacity (MW)
600 MW and above 71,350
~500 MW 46,650
350 MW and below 79,391
Total Capacity 197,391
4.8.1 Technical efficiency improvement
Washing of coal results in improvement of GCV of coal which reduces the amount of coal
used to generate same amount of electricity. Apart from this benefit, improved quality coal
reduces auxiliary power consumption (APC) to support unit generation as the system
handles less volume of coal and ash. The major impact on APC reduction comes from boiler
auxiliary and balance of plant (BOP) equipment such as coal handling plant (CHP), ash
handling plant (AHP), etc.
Apart from APC improvement, coal beneficiation also impacts the heat rate, life of boiler
auxiliaries, O&M cost etc. of generating units. Various studies such as ADB
28
, ORF study on
‚Coal beneficiation in India‛
29
suggest significant improvement in these aspects. During the
course of this study, TERI consulted BHEL, largest manufacture of thermal power plant in
India, for the analysis of these technical efficiency improvements.
4.8.2 Simulation Study for typical 500 MW unit
BHEL carried out a simulation study on a 500 MW subcritical plant designed for 42% ash,
0.49% Sulphur & GCV of 3400 kcal/kg. During the simulation, the subcritical 500 MW plant
was fired with washed coal having 32% ash, 0.60% Sulphur & GCV of 4500 kcal/kg and the
impact on plant efficiency, auxiliary power consumption, chemical consumption in FGD, life
of equipment, etc., have been reported. A typical configuration for boiler, turbine, generator,
mills ducts, CHP, AHP, etc, have reportedly been considered for the simulated run. The final
results of the simulation are as follows:
Boiler efficiency will have a marginal gain of about 0.5%. But the Main steam
and Reheat temperature is expected to be lower by 15⁰C.
28
https://www.adb.org/sites/default/files/project-document/72146/26095-ind-tacr.pdf
29
https://www.orfonline.org/wp-
content/uploads/2017/07/ORF_Report_CoalBeneficiation_FinalForUpload.pdf
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Turbine efficiency is expected to be lower by 0.38% due to lower Main steam and
Reheat steam temperatures. Overall, plant heat rate will marginally deteriorate
resulting in drop in cycle efficiency expected to be about 0.12%.
Equipment for emission control such as ESP & FGD will also have relatively
better & efficient performance. ESP will be typically able to operate with one
lesser field for meeting the environmental norms. With respect to FGD, savings
in terms of operational cost will be observed. FGD chemical consumption will be
lower by 9%.
Coal mills grinding elements & burner nozzles will also have better operating
life and it is expected that an increase of about 50% – 100% may be observed
depending on actual washed coal compositions.
Improvement is expected in Auxiliary Power Consumption (APC) with firing of
washed coal in the equipment listed below:
For boiler & its auxiliaries (ESP, Fans, Mills): APC is expected to be
reduced by about 10%.
For turbine & its auxiliaries: Increase in APC is expected to be increased
by 0.87%.
For BOP packages (CHP & AHP): APC is expected to be reduced by
about 20% for each of the packages as coal being fired is reduced by
about 25%.
FGD power consumption will be lower by 12%.
Total savings in APC is approximately 2 MW i.e. 5.5% reduction.
These results from BHEL simulation cannot be generalised and the results will differ
depending on the unit size, actual unit configuration, age, coal characteristics, washed coal
composition, etc.
While the BHEL simulation study carried out for specific fuel condition and specific unit
configuration shows a loss in heat rate due to firing of high GCV coal in units designed for
lower GCV coal, pilot studies conducted (Satpura, Ronghe committee, ADB and ORF study)
suggest improvement in heat rate of units. In the present study we have considered an
improvement of 5.5% of APC and improvement of 0.02% boiler efficiency (for every 1%
reduction in Ash %)
30
.
30
https://www.eecpowerindia.com/codelibrary/ckeditor/ckfinder/userfiles/files/Session%202%20Module%20
2%20Coal%20Properties%20and%20Effect%20on%20Cobustion.pdf
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4.8.3 Economic impact on variable cost of power plant
Impact of higher GCV, improved heat rate, reduced APC and higher coal cost is estimated
on the variable cost of power generation. Unit size wise normative heat rate and APC have
been considered as per CERC Tariff Regulations 2019-24
31
. Also, energy charge rate (ECR)/
variable cost has also been calculated based on the methodology provided in the aforesaid
CERC tariff regulations.
Impact on variable cost of power generation can be seen mainly in two ways, first in terms
of quantity of coal reduction because of various reasons such as improvement in GCV, heat
rate, and APC of power plant due to improved heat value of fired coal, second due to
increased coal cost due to washing.
To assess the impact of coal washing on variable cost of power generation, difference
between variable cost of cost electricity generation using washed and raw coal has been
calculated.
31
http://www.cercind.gov.in/2019/regulation/Tariff%20Regulations-2019.pdf
Net Impact on variable cost = Quantity / volume difference + Rate difference
Positive impacts on variable cost
Savings in coal quantity due to
1.Improved GCV
2.Improved Heat Rate
3.Less APC consumption
Savings due to reduction of coal quantity can also be seen in
1.ROM coal
2.Transportation of coal
3.Saving in Taxes on coal
Negative impacts on variable
cost
Loss / Rate variance due to
Washing of coal, which
includes the impact of clean
coal yieldS3
Increase/decrease in Variable cost = Variable cost of washed coal (VCWC) - Variable cost of raw coal
(VCRC)
In this study, above equation is used to estimate the impact of washing on variable cost / ECR of power
generation. Negative change implies that the variable cost of power generation using raw coal is higher
than the variable cost using washed coal and a positive impact on variable cost implies that the variable
cost of power generation using washed coal is lower than the variable cost using raw coal.
Negative value i.e. decrease in variable cost = VCWC is lower than VCRC (i.e. gain/benefit if washed
coal is used for power generation)
Positive values i.e. increase in variable cost = VCWC is higher than VCRC (i.e. loss if washed coal is
used for power generation)
Higher the reduction in variable cost, higher will be savings in variable cost due to washing of coal.
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On the basis of above, results of one sample bringing out impact on variable cost due to
various reasons for G-13 grade coal (3550 kCal/kg, 43% Ash) washed to output coal (GCV
4286 kCal/kg, 34% Ash) use in power generation is presented in table 11 and 12. A
comparison is also made on the basis of distance i.e. for 500 km and 800 km.
Table 11: Change in variable cost due to APC, Heat Rate, GCV and Higher coal Cost
Particulars UOM
For 500 km For 800 km
660
MW
500
MW
300
MW
660
MW
500
MW
300
MW
Variable cost (Raw coal)VCRC Rs/kWh 1.90 2.02 2.07 2.32 2.48 2.53
Variable cost (washed coal)VCWC Rs/kWh 1.95 2.08 2.12 2.29 2.45 2.50
Increase / decrease in variable cost Rs/kWh 0.05 0.05 0.05 -0.03 -0.03 -0.03
Break up of Increase / decrease in variable cost
Impact of improved APC Rs/kWh -0.01 -0.01 -0.01 -0.01 -0.01 -0.01
Impact of improved Heat Rate Rs/kWh 0.00 0.00 0.00 -0.01 -0.01 -0.01
Impact of Higher GCV Rs/kWh -0.33 -0.35 -0.36 -0.40 -0.43 -0.43
Impact of higher coal cost Rs/kWh 0.39 0.41 0.42 0.39 0.41 0.42
In table 11, increase/decrease in variable cost due to washed coal usage has been worked out
for four parameters - APC, Heat rate, GCV, and coal cost. From table 11 following can be
inferred.
From above table, variable cost has increased by Paisa 5/kWh if washed coal is being
transported for a distance of 500 km, whereas if the same washed coal is transported
at 800km it shows decrease in variable cost.
For longer distances, 800km, impact of higher washed coal GCV on variable cost
offsets the impact of cost of washing on variable cost. In table above, for G13 coal, the
improvement in variable cost (Rs 0.43/kWh) due to improved GCV completely
offsets impact of higher coal cost (Rs 0.41/kWh) , and hence makes washing of coal
economically viable.
Improved heat rate and APC has not much of significant impact on variable cost i.e.
Paisa 1 -2 /kWh.
To estimate impact of distance on the same grade of coal, used for table 11, the impact on
variable cost due to washed coal usage can also be seen on freight charges, taxes, ROM cost,
etc., as lesser coal is required to generate same electricity.
Table 12: Change in variable cost due to Transportation, Taxes, ROM and cleaning cost
Particulars UOM
For 500 km For 800 km
660
MW
500
MW
300
MW
660
MW
500
MW
300
MW
Variable cost (Raw coal) VCRC Rs/kWh 1.90 2.02 2.07 2.32 2.48 2.53
Variable cost (washed coal) VCWC Rs/kWh 1.95 2.08 2.12 2.29 2.45 2.50
Increase / decrease in variable cost Rs/kWh 0.05 0.05 0.05 -0.03 -0.03 -0.03
Break up of Increase / decrease in variable cost
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Particulars UOM
For 500 km For 800 km
660
MW
500
MW
300
MW
660
MW
500
MW
300
MW
Transportation cost impact Rs/kWh -0.16 -0.17 -0.17 -0.23 -0.24 -0.25
Taxes and Duty Rs/kWh -0.07 -0.08 -0.08 -0.07 -0.08 -0.08
ROM Coal Rs/kWh -0.11 -0.11 -0.12 -0.11 -0.11 -0.12
Impact of cleaning Rs/kWh 0.38 0.41 0.42 0.38 0.41 0.42
In table 12, increase/decrease in variable cost due to washed coal usage has been
seggregated in four parameters- transportation cost, taxes, ROM coal cost, and washing cost.
From the model based analysis (refer figure 8, picture presented in table 11 and 12), it can be
inferred that a power plant getting beneficiated coal from a coal washery, which handles
G13 ROM coal situated 500 km from the power plant, there will be an increase in the
variable cost. On the other hand, if the same plant gets beneficiated coal from a washery
situated beyond 600-650 km, there will be a reduction in the variable cost.
4.9 Net economic impact per unit of variable cost (ECR) of electricity
generation w.r.t distance of coal transportation
The result of the net economic costs and benefits has been presented for different grades of
coal with respect to distance of transportation in figure 8. The results are presented for a 500
MW unit, however the results show almost same trend for different unit sizes as there is not
much of change in ECR due to heat rate and APC improvement in generating unit. The
variation among different unit size for grade G13 coal can be seen in Annexure 5 for better
understanding.
4.9.1 Results for net impact on variable cost with distance of washing for
various grade of coal
Increase/decrease in variable cost due to use of washed coal in a generating station has been
analysed using an integrated value chain framework/modeling. This analysis has been
carried out for G11, G12, G13 ROM grade of coal washed up to 34% and 32% ash. Also,
impact of distance between washery and power plant on variable cost has been analysed
using this model. The results from the analysis in presented in figure 8.
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Figure 8: Impact on variable cost of power plant for using washing coal upto 34% and 32% ash
From the graph shown in figure 8, it can be inferred that the benefits of coal washing, up to
34% ash in output coal, offsets the cost of washing at distance of 600 and 700 km for G13 and
G12 grade and around 1500 km for G-11. The difference observed in washing upto 34% and
32% is the distance for G11. Benefits of coal washing of grade G11 (35% ash) coal offset cost
of washing at a distance of about 850 km if washed up to 32% ash and 1500 km if washed up
to 34%.
Sensitivity by taking reject rebate of Rs 250/Ton was also carried out during this exercise.
This resulted in reduction in washing cost and therefore in variable cost of washed coal.
However the nature of above graph remains the same, but reduction in variable cost due to
the usage of washed coal occurred at lesser distances i.e. 500-600 km onwards for G-12 and
13 grade coal.
4.10 Sensitivity Analysis
Due to significant variability arising due to (i) quality of RoM coal & cost of transportation
from mine to washeries, (ii) yield of clean coal and (iii) transportation distance of washed
coal to power stations, it is essential to analyse the impacts of various sensitivities on
variable cost of generation with washed coal. A sensitivity analysis has been carried out to
assess impact of freight charges from mine to washery, impact of clean coal yield, and
transportation distance on variable cost of power generation with the following
values/boundary conditions:
G12 and G13 grade ROM coal for various yield percentages has been considered in
view of the following.
o Bulk of the thermal coal washed in India is G13.
-0.40
-0.20
0.00
0.20
0.40
0.60
50
250 450 650 850
1050 1250 1450 1650 1850
Increase / decrease in variable cost (Rs/kWh)
Distance
Washing upto 34% Ash in output coal,
500MW unit
G11 G12 G13
-0.40
-0.20
0.00
0.20
0.40
50
250 450 650 850
1050 1250 1450 1650 1850
Increase / decrease in variable
cost (Rs/kWh
)
Distance
Washing upto 32% Ash in output coal,
500MW unit
G11 G12 G13
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o Further, pilot test carried out at NTPC, Dadri as reported by CEA was also carried
out with G13 raw coal and an assessment will help in comparing the estimates, thus
arrived from sensitivity analysis, with the results provided by CEA.
Two cost scenarios with Rs 60/T and Rs 160/T have been considered for
transportation of G12 and G13 grade coal from mine to washery.
Under each coal grade and transport cost scenarios, yields of 85% and 65% (+/- 10%
of the mean yield of 75% as per data received from CMPDI for G13 coal when
washed up to 34%) have been considered.
The sensitivity analysis has been presented for distances ranging from 50 to 2000 km.
Figure 9: Change in Variable cost of power generation w.r.t surface transportation, yields, and
distance between washery and power plant
From figure 9 following can be inferred:
Higher the yield of beneficiated coal, higher will be the benefit from using washed
coal.
For G13 coal having (a) 85% yield and transportation cost of Rs 60/tonne, use of
washed coal is beneficial if it is transported beyond 250 km (approx.) (freight charges
: Rs 706/tonne) and (b) lower yield of 65%, use of washed coal will be beneficial if it is
transported beyond 1550 km (freight charges : Rs 2885/tonne).
Similarly, G12 coal with yield of 85% will be beneficial if it is transported beyond 850
km (freight charges: Rs 1773/tonne). A lower yield of G12 coal, 65%, will result in
increase in variable cost even when used for longer distances (more than 2000 km).
Increase in surface transportation cost by Rs 100/Tonne resulted in increase in
variable cost by Rs 0.06/kWh under both the above yield scenarios (dotted lines)
-0.60
-0.40
-0.20
0.00
0.20
0.40
0.60
50
150 250 350 450 550 650 750 850 950
1050 1150 1250 1350 1450 1550 1650 1750 1850 1950
Change in Variable cost (Rs/kWh)
Distance (km)-->
G12, 65% yield, ST: Rs160/T
G12 65% yield, ST: Rs 60/T
G13, 65% yield, ST: Rs160/T
G13, 65% yield, ST: Rs60/T
G12, 85% yield, ST: Rs160/T
G12, 85% yield, ST: Rs60/T
G13, 85%yield, ST: Rs160/T
G13, 85% yield, ST: Rs60/T
NTPC Dadri, Rs 930/T washing cost, interpreted as
65-70% clean coal yield, Distance 1000 km, 3505
kCal/kg ROM coal, 3849 kCal/kg washed coal GCV
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The pilot study conducted at NTPC Dadri reported a washing cost of around Rs
930/Ton for raw coal having GCV of 3507 kCal/kg and ash of 37.48% (which
corresponds to G13 ROM coal) giving ash of 31.82% and GCV of 3849 kCal/kg. This
indicates that the yield is around 65% - 70%, which apparently seems low as
compared to yield arrived at using CMPDI data. Due to lower yield of clean coal
and/or higher washing cost, variable cost from use of washed G13 coal increases
variable cost by approximately Rs 0.13/kWh (TERI analysis) for the electricity
generated at NTPC Dadri project.
4.11 Comparison of change in ECR of some of power plants with ECR
as per model
Increase in the washing cost due to type of washing technology, yield of clean coal, surface
transportation, etc., have a significant bearing on overall change in ECR/variable cost of
power generation using washed coal. In order to mimic the conditions close to the data
provided by NITI Aayog in respect of two power plants, namely Dadri and Kota, model has
been run with conditions close to the coal characteristics, yield using CMPDI correlation
analysis (as presented in figure 5) and washing and transport costs as presented in the
subsequent paragraph. Table 13 presents the analysis for NTPC Dadri and Table 14 for Kota
thermal power station.
The estimations have been provided for two scenarios, (i) using at derived yield for G12 coal
and (ii) at a yield corresponding to the washing cost provided in the literature provided by
NITI. G12 coal has been considered for the modeled calculations keeping raw coal cost
comparatively in same range as given in NITI Aayog data. Washing of G12 coal gives a
change in GCV of 436kCal/kg which is near to the NTPC Dadri and KTPS’s coal GCV
improvement. The reason behind not considering G11 and G13 grade for comparison is that
G11 grade coal has higher raw coal cost and G13 coal washing gives higher GCV impact
than that is given in the NTPC and KTPS data.
Table 13: Impact on ECR for NTPC, Dadri due to actual washing cost vis-a-vis theoretical calculations
Key Takeaways:
Use of washed coal is beneficial for power plants if power plants are receiving
coal over longer distances that are more than 600kms.
However, at a higher yield than theoretical, inferior grade (G12 and lower)
washing up to 34% can be beneficial even at shorter distances of the order of 300
km.
Lesser the cost of the transportation from mine to washery, viability of use of
washed coal emerges even at shorter distances.
Higher the yield of clean coal (more than 75%), higher will be the benefit from
using washed coal.
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SN Particulars UOM In NITI
Aayog
study
TERI Analysis based on
Modelled yield Lower yield
1 Unit Size MW 490 500 500
2 GCV Washed Coal kCal/kg 3793 4286 4286
3 GCV Raw coal kCal/kg 3472 3850 3850
4 Difference in GCV (2-3) kCal/kg 321 436 436
5 Ash Washed Coal % 34% 34% 34%
6 Ash Raw Coal % 40% 40% 40%
7 ECR Washed coal
#
Rs/kWh 3.20 2.44 2.70
8 ECR Raw Coal
#
Rs/kWh 2.85 2.46 2.46
9 Change in ECR Rs/kWh 0.35 -0.02 0.24
Coal Cost break up
10 Yield of clean coal % - 86% 70%
11 Raw coal cost Rs/MT 1617 1654 1654
12 Washing cost (incl. yield) Rs/MT 834 416 860
13 Freight Charges Rs/MT 2076 2043 2043
14 Landed cost of Raw coal Rs/MT 3693 3697 3697
15 Landed cost of Washed coal Rs/MT 4527 4113 4557
#in actual data, net heat rate taken for ECR calculation is 2678 kCal/kWh. NTPC Dadri has given gross heat rate
of 2384kCal/kWh in pilot study conducted and result submitted to CEA. Taking 6.25% APC, net heat rate is
calculated as 2543kCal/kWh which is significantly different from the 2678kCal/kWh submitted in NITI Aayog’s
data. For modeled calculations net heat rate has been considered as 2558 kCal/kWh for raw coal use and 2543 for
washed coal use.
Modeled calculations for NTPC Dadri show that, at model yield of 86% for washing of G12
grade coal decrease the ECR by Rs 0.02/kWh, whereas at lower clean coal yield of 70% (to
represent same washing coat as in actual) there will be increase in ECR of about Rs
0.24/kWh. The difference between change in ECR in actual (35 Paise/kWh) and modeled (24
Paise/kWh, at lower yield) is primarily due to higher GCV improvement in modeled
calculations.
The same analysis has been carried out for Kota thermal power station (KTPS), Rajasthan. At
a lower yield than the modeled yield and higher surface transportation cost, calculations
show increase in variable cost by Rs 0.17/kWh as compared to Rs 0.29/kWh presented in the
earlier NITI Aayog assessment.
Table 14: Impact on ECR for KTPS, Rajasthan due to actual washing cost vis-a-vis modeled
calculations
SN Particulars UOM In NITI
Aayog
study
TERI Analysis based on
Modelled
yield
Lower yield
1 GCV Washed Coal kCal/kg 4200 4286 4286
2 GCV Raw coal kCal/kg 3950 3850 3850
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3 Difference in GCV (1-2) kCal/kg 250 436 436
4 Ash Washed Coal % 34% 34% 34%
5 Ash Raw Coal % 42% 40% 40%
6 ECR Washed coal Rs/kWh 2.50 2.34 2.51
7 ECR Raw Coal Rs/kWh 2.21 2.34 2.34
8 Change in ECR (6-7) Rs/kWh 0.29 0.00 0.17
Coal Cost break up
9 Yield of clean coal % 80% 86% 80%
10 Raw coal cost Rs/MT 1558 1654 1654
11 Washing cost (incl. yield impact) Rs/MT 693 416 711*
12 Freight Charges (800km) Rs/MT 1844 1866 1866
13 Landed cost of Raw coal Rs/MT 3402 3520 3520
14 Landed cost of Washed coal Rs/MT 4095 3936 4231
*including additional surface transportation of Rs 100/MT, washing cost Rs 50/MT, rebate on
reject of Rs30/MT to mimic the KTPC coal washing cost.
ECR is a function of specific coal consumption and landed price of coal at the power station.
Further specific coal consumption is a function of GCV and unit heat rate. Lower the yield
from washing of coal, higher will be landed price of coal. Hence any change in yield will
hence affect the cost of washing and finally the price of washed coal thereby affecting the
ECR. Figure 9 has captured the extent of variability of the yield on the variable cost/ECR. In
line with the above relationship, the difference in reported ECR (in NITI assessment) and
estimated ECR (TERI analysis) arises primarily because of the gap of the yield and washing
cost. In case of NTPC, the washing cost reported was INR 834/tonne while modeled nearest
cost were INR 416/tonne and INR 860/tonne. Similarly in case of Kota Thermal Power
Stations, the reported washing cost was INR 693/tonne while the nearest estimates of G12
coal are INR 416/tonne and INR711/tonne.
The improvement in the GCV from washing also varies from the reported data and that
estimated from the TERI model. The improvement reported for NTPC Dadri station was 321
Kcal/tonne while that of Kota was 250Kcal/tonne. However the improvement in GCV from
washing from TERI model has been found to be 436Kcal/kg. The relative less improvement
in GCV has a far greater impact on ECR than that modeled by TERI.
The GCV-ash% relationship for raw and washed coal, yield of washed coal and cost of
washery (or landed price of washed coal at power station) hold the key towards arriving
at a judicious and more meaningful conclusion so far impact on ECR is concerned. The
sample data point from only three power stations is too scanty to make any effective and
compelling conclusion. From a strict statistical analysis viewpoint these data points are
highly insignificant to arrive at any statistically robust estimates of ECR impacts.
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4.12 Economic Impact on Fixed cost of Power plant
The impact on fixed cost due to reduction in capital cost for a power plant operating on
washed coal will only be there in the new power plants. On the basis of consultation with
BHEL, 2% improvement in capital cost of power plant, designed for usage of washed coal, is
considered for overall impacts in fixed cost. This improvement is equivalent to 5-6
paisa/kWh (at normative PLF of 85%) reduction in fixed cost of power plant
Also, there will be additional benefits by use of washed coal such as 30% reduction in land
requirement for ash disposal in power plant using 34% ash coal instead of 41%
32
.
Furthermore, an ash reduction of 7% results in a reduction of about 2900 Ha of land for fly
ash disposal, and in reduction of water consumption for ash disposal of 131 MSCM
(DrManoj Kumar, 2016).
4.12.1 Coal Washing and emission standard
The coal beneficiation process which is generally used to remove the contaminants also
comes with environmental benefits. The process aims at reducing the ash content & remove
smaller amounts of other substances such as sulphur and other air pollutants. In order to
counter the growing emissions from power sector & their impact, Ministry of Environment
Forest & Climate Change (MoEF&CC) amended emission norms for SPM & introduced new
norms of SO2, NOx& Mercury in December, 2015. As per the specified limits, pre-installed
Electrostatic Precipitator (ESP) will require additional fields to achieve specified PM level
and Flue Gas Desulfurization (FGD) & Selective Catalytic Reduction (SCR) will be needed to
control SO2&NOx emissions respectively.
4.12.1.1 Impact on ESP
These pollution control equipment involve high capital investment upfront. For compliance
of new PM norms, ESP retrofitting is required for 66 GW out of 197 GW
33
. ESP retrofitting
costs around Rs 5-10 lakh/MW, which translates to ~2-3 paise/kWh increase in fixed charges
component of tariff.
For a typical 210 MW unit, complying with old PM norm of 100 mg/Nm
3
, washing of coal (5-
6% ash reduction) reduces PM concentration by 20% but is not sufficient to comply with
new norm of 50 mg/Nm
3
. Hence retrofitting/replacement of ESP fields is needed to comply
with the new norms. This compliance can be achieved in two ways, either by coal washing
and smaller ESP retrofit / new control equipment, or by large ESP retrofit/ new control
equipment. However, this analysis requires details of cost of retrofitting, under various
kinds of coal, distance of plant from washery, etc.
32
https://www.orfonline.org/wp-
content/uploads/2017/07/ORF_Report_CoalBeneficiation_FinalForUpload.pdf
33
https://www.indian-utility-week.com/__media/Report/Gov-of-India---Quarterly-Review-Report.pdf
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Consultation with BHEL brought out that the ESP designed for 100 mg/Nm
3
with
conventional Indian coal (unwashed), when fired with washed coal is able to meet both 100
mg/Nm
3
and 50 mg/Nm
3
criteria without any change in existing ESP. However, to meet 30
mg/Nm
3
criteria, existing ESP will require installation of one extra field.
The outcome from the study of one plant can be different for other generating stations and
cannot be generalized due to existing ESP design, collection efficiency of ESP, type of coal
used, etc. It is, therefore, recommended that a plant specific study is needed to analyse
impact of coal washing along with emissions abatement cost required for pollution control
equipment to comply with new emission norms.
4.12.1.2 Impact on FGD
For SO2 control, FGD is being considered as the primary option for which FGD planning has
already been done for 166 GW, feasibility study has been completed for 136 GW, NIT having
been issued for 95 GW, bids awarded for 13 GW and FGD already commissioned at around
2 GW capacity (CEA, 2019)
34
. Technology will come at the cost of Rs. 45 lakh/MW for
capacities ranging from 210-800 MW and will require 1-1.3% of increased APC and
additional operating cost depending upon reagent, additional water requirement, and man
power for O&M and by-product handling (CEA guidelines, 2015). Only reagent can cost up
to 0.15 INR/kWh and other elements will be additive to this.
Washing may also lead to reduction in SOx emission. ROM coal may contain pyrites. The
amount of pyrite present is likely to be reduced in a washed coal. A study by Cropper et al
(2012)
35
reported that washed coal can reduce emissions of SOx by 25% while other study
reported that Indian coal constitutes around 50-70% of pyritic Sulphur which can be
removed to the extent of 50% relative to total Sulphur content of raw coal
36
. The 25%
reduction of sulphur in raw coal reduces SO2 emission by 30%. Hence the capital cost
required for FGD reduces significantly.
Though literature suggests that washing of coal results in reduction in dust concentration
and SO2 emission. However, in view of large variation of sulphur in Indian coal, adequacy
of washing for meeting new environmental norms is required to be assessed on case to case
basis, and calls for much detailed assessment with sampling of data from different mines to
analyze the impacts on Sulphur content of coal post washing.
4.13 Coal blending versus washing of coal
Blending of high grade coal with low grade raw coal is one of the propositions other than
washing of coal that can reduce the ash in the delivered coal to power plant. Indian coal
34
http://www.cea.nic.in/reports/others/thermal/umpp/fgd_newnorms.pdf
35
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2093610
36
https://www.sciencedirect.com/science/article/pii/B9780128126325000094
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being higher in Ash% requires higher proportion of high grade coal to achieve ash% less
than 34%. In India, mostly G10, G11, G12 and G13 coal is used for power generation. For
blending purpose a higher grade, which is having less ash content, is required to be mixed
with lower grade of coal in such a way that resultant coal will have ash not exceeding 34%.
To analyse the cost benefit / loss of blending of coal over washing of coal, an analysis has
been carried out (refer Table 15). In the analysis, cost comparison has been made between
blending of G9 (Avg. GCV: 4750 kCal/kg) and G13 (Avg. GCV: 3550 kCal/kg) Raw Coal and
Washing of G13 coal. In the simulation study, blending of coal has been done is such a
manner that the delivered coal will have 34% ash. Quantities of G9 and G13 coal required for
1 tonne of delivered coal (34% ash coal) have been calculated using energy and mass balance
method.
Table 15: Cost comparison between blending of G9 and G13 Raw Coal and Washing of G13 coal
S.No. Particulars UOM Value
Cost of Blending
1 Quantity of ash in 1 tonne of G9 coal tonne 0.28
2 Quantity of ash in 1 tonne of G13 coal tonne 0.43
3 For 34% ash coal (target), G9 coal required for blending with G13 coal % 61%
A ROM Cost of 0.61 tonne of G9 coal Rs/MT 695
B ROM cost of 0.39 tonne of G13 coal Rs/MT 319
C Royalty Rs/MT 142
D Sizing charges Rs/MT 87
E MMDR - central fund (2% of Royalty) Rs/MT 3
F MMDR - central fund (30% of Royalty) Rs/MT 43
G Subtotal assessable value (A+B+C+D+E+F) Rs/MT 1288
H GST compensation cess Rs/MT 400
I GST (5%) Rs/MT 64
J Surface transportation Rs/MT 60
K Total cost of Blended coal (G+H+I+J) Rs/MT 1813
Cost of G13 washed coal (washing up to 34% Ash)
L ROM cost of G13 coal Rs/MT 817
M Royalty Rs/MT 114
N Sizing charges Rs/MT 87
O MMDR - central fund (2% of Royalty) Rs/MT 2
P MMDR - central fund (30% of Royalty) Rs/MT 34
Q Subtotal assessable value (L+M+N+O+P) Rs/MT 1055
R GST compensation cess Rs/MT 400
S GST (5%) Rs/MT 53
T Subtotal (Q+R+S) Rs/MT 1508
U Washing cost for 75% yield Rs/MT 688
V Surface transportation charges Rs/MT 60
W Total cost of washed G13 coal (T+U+V) Rs/MT 2256
X Difference between blend coal and washed coal (K-W) Rs/MT -443
Y % increase (X/K) % 24%
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The analysis for this particular case shows that blending of coal at power station is 24%
cheaper than the washed coal. However, blending of coal has many limitations as well. For
many cases, blending of coal to achieve 34% ash content in coal may be costlier (such as in
case of blending of low grade coal with very high grade of coal or imported coal) than the
washing of coal. So, viability of blending of coal shall be assessed taking the following
aspects into consideration:
• Availability of superior quality of coal – as Indian coal is higher in ash content, a
higher proportion of high-grade coal will be required to maintain 34% ash. So
availability of the same higher grade coal is also very important. Also, Power plants,
which are designed for higher grade of coal, may not be in a position to surrender
the same and production of high grade coal will have to suitably increase.
• Use of blended coal, in case where higher grade coal may be required to be supplied
from a longer distance / different source, will result in higher variable cost, which
will in turn put the power station at a disadvantage in merit order scheduling &
dispatch.
• Current FSA structure – Power plant that are using lower grade ROM coal will be
required to have another FSA for higher grade of coal for blending, in case the
generating company does not have any FSA for required grade (higher) of coal
taking limitation of annual contracted quantity (ACQ) in to consideration.
• Position of intermixing of different grades of coal – intermixing of coal whether at
power plant end or mine end is also one of the factors required to be taken in to
consideration.
4.14 Case study: Market potential of reject based electricity
generation from FBC plants
As discussed in the previous chapters, the co-produced rejects during the washing
process could potentially be utilized in FBC based plants either completely or with
appropriate blending with raw coal considering the technical specifications of FBC
boilers. Currently, the FBC plants are installed for captive purposes, which can generate
electricity from rejects having ash content up to 65% and GCV in the range of 1500 – 2200
kCal/kg. However, most of the FBC plants blend rejects with raw coal to achieve design
coal characteristics.
From the stakeholder interaction and literature survey, it was found that the price of
rejects based power generation from FBC falls in the range of 2.5 and 4.5 Rs/kWh
37
. Also,
the electricity tariff for industrial consumers (for washeries as well as other industrial
plants) is in the range 5.5 to 6.0 Rs/kWh in major coal bearing states such as Bihar,
Jharkhand & Orissa. It shows that FBC plants can produce less costly electricity from
37
https://fossil.energy.gov/international/Publications/Coal_Beneficiation_Workshop/DT_OP_CCL_presentatio
n.pdf
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rejects (complete usage or blending with raw coal), and is a viable option for captive
purposes than procuring from grid.
The cost of rejects based electricity generation from FBC can reduce further with lower
capital cost of FBC plant, better quality of rejects and when operating at high PLF in
parallel with grid connected plants.
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46
Chapter 5: Environmental Impact
Assessment of Coal Washing, use of
Washed Coal for Power Generation and
Rejects
The environmental impacts associated with three different stages of coal washing have been
presented in the following sections. Impacts associated with coal washery operations, usage
of washed coal for power generation and utilization of rejects have been detailed and
assessed.
5.1 Environmental Impact associated with coal washery operations
Coal washing processes, unless properly handled, has the potential to cause pollution of air,
water and soil. Environmental impacts of coal washing, therefore, is an area of concern from
the environment point of view and it is required to assess whether the benefits arising from
use of washed coal are outweighing the impacts generated from operating coal washeries.
5.1.1 Effluent Water and its environmental impact
Coal washery effluents contain large amount of suspended solids and high COD values
which hold potential for severe water pollution and siltation of river bed. However, the coal
washeries as per the environmental guidelines
38
have to adhere to the following norms
1. Water consumption shall not exceed 1.5 NM
3
per tonne of raw coal.
2. The efficiency of setting ponds of the waste-water treatment system shall not be less than
90%.
3. The coal washeries shall maintain the close circuit operation with zero discharge. In case
of any problems such as monsoon, cleaning;
4. The effluent discharge at final outlet should comply with the prescribed norms.
5. Under no circumstance the industry shall discharge wastewater to outside.
In the study, we assume that the washeries are complying (as there are no reports on non-
compliance) with the effluent discharge norms and so, we have considered overall
environmental impact related to effluent discharge as nil. Also, cost of water effluent
treatment/ water pollution abatement cost such as effluent treatment plant (ETP), sewage
treatment plant (STP) etc. is internalized in the capital cost of washeries, while operating
cost for water treatment such as cost of flocculant as chemical for water treatment and
electricity consumption are also internalized.
38
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5.1.2 Model Analysis of Electricity consumption and CO2 impacts
An comparative analysis was undertaken to assess the impact of CO2 emission from power
generation using raw coal (for Grade G11, G12, G13, G14) vis-à-vis electricity generated
from rejects including CO2 emission associated with electricity consumption during coal
washing. To carry out the analysis, a power station having annual coal consumption of 1
million tonne has been considered. The electricity that can be generated from raw coal with
grades G11, G12, G13 and G14 have has been estimated at 1729 MU, 1604 MU, 1479 MU and
1354 MU respectively.
Table 18: Calculations for one million tonne of different grades of coal
SN Particulars UOM G11 G12 G13 G14
1 Raw Coal Quantity Tonne 1,000,000 1,000,000 1,000,000 1,000,000
2 Ash% in Raw Coal % 36% 39% 43% 47%
3 Ash % in Washed coal % 34% 34% 34% 34%
4 Yield of clean coal % 96% 86% 75% 63%
5 Washed coal Quantity Tonne 960,000 860,000 750,000 630,000
6 Quantity of Reject Tonne 40,000 140,000 250,000 370,000
7 Power consumption in washery MU 3.0 3.3 3.6 4.0
8 CO2 generated by washery's power
Consumption
MT 2.49 2.74 3.01 3.31
9 Water consumption in washery Mil m3 1.5 1.5 1.5 1.5
10 Specific coal consumption of Raw coal kg/kWh 0.58 0.62 0.68 0.74
11 Specific coal consumption of Washed coal kg/kWh 0.56 0.56 0.56 0.56
12 Specific coal consumption of Reject kg/kWh 2.5 2.22 2.08 1.91
13 Power generation using Raw coal (PRC) MU 1729 1604 1479 1354
14 Power generation using washed coal (PWC) MU 1718 1540 1343 1129
15 Power generation using Reject (PRJ) MU 11 63 120 194
16 Difference in power generation (PRC-(PWC+PRJ)) MU 0 2 16 31
17 CO2 generation by raw coal cons. MT 1.54 1.43 1.32 1.21
18 CO2 generation by washed coal cons. MT 1.53 1.37 1.19 1.00
19 CO2 generation by reject cons. MT 0.02 0.07 0.13 0.20
20 Cost of CO2 from Raw coal Mil INR 3.41 3.16 2.91 2.67
21 Cost of CO2 from Washed coal Mil INR 3.38 3.03 2.64 2.22
22 Cost of CO2 from Rejects Mil INR 0.04 0.14 0.28 0.45
23 Aux power savings at power plant end MU 5.9 5.5 5.0 4.6
24 Power consumption in washery MU 3.0 3.3 3.6 4.0
25 Net saving (23-24) MU 2.9 2.2 1.4 0.6
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The specific coal consumption of raw coal for power generation from G11, G12, G13 and G14
grade coal is 0.58 kg/kWh, 0.62 kg/kWh, 0.68 kg/kWh, and 0.74 kg/kWh respectively. The
increase is attributed to reduction in GCV and the consequent increase in the coal
requirement as we move from G11 to G14.
However, if the coal of these grades was washed to 34%, the total volume of clean coal that
would have been generated based on analyzed maximum yield would be 0.96 million tonne,
0.86 million tonne, 0.75 million tonne and 0.63 million tonne respectively in the order of the
grades mentioned above. Given the characteristics of the coal, particularly GCV and ash
content after washing have been assumed to be same, the specific coal consumption falls to
0.56 kg/kWh and remains same for each grade as presented in table 18. The electricity
generated from using washed coal is 1718 MU, 1540 MU, 1343 MU and 1129 MU.
The estimated volume of rejects generated for these grades are 0.04 million tonne, 0.14
million tonne, 0.25 million tonne and 0.37 million tonne. This is arrived at using the energy
mass balance for individual grades of coal. The volume of electricity generated using rejects
from washing of coal G11 to G14 has been estimated to be low because of poor calorific
value and high ash content. Practically, no electricity is possible to be generated using these
rejects without blending. However, for theoretical purpose, the same has been estimated at
11 MU, 63 MU, 120 MU and 194 MU. From the analysis as presented in the table, it can be
inferred that the total electricity from raw coal is higher than the electricity generated
from washed coal as well as electricity generated from reject. However, the gap is nil for
G11 and reaches to 31 MU for G14.
The APC saving was estimated from using washed coal of grade G11 to G14 to the tune of
5.9 MU, 5.5 MU, 5.0 MU, and 4.6. On the other hand electricity consumption from washing 1
million tonne of raw G11 to G14 coal grades is 3.0 MU, 3.3 MU, 3.6 MU, 4.0 MU respectively.
The net savings have been estimated at 2.9 MU, 2.2 MU, 1.4 MU and 0.6 MU. The
incremental benefit in CO2 emissions due to APC reduction at power plant end compared
to electricity consumption at washery end is 3.64 KT, 2.92 KT, 2.12 KT, & 1.46 KT per
million tonne of coal consumption for G-11 to G-14 grades of coal respectively.
5.2 Environmental benefits from the use of washed coal for power
generation
The use of raw coal with high ash content has major environmental impacts in the form air
pollution caused by CO2 , oxides of nitrogen (NOx), oxides of sulphur (SOx) and air-borne
inorganic particles such as fly ash, carbonaceous material (soot), suspended particulate
matter (SPM) and other trace gas species. When burning unwashed coal for power
generation, large amount of particulate matter, sulphur dioxide, nitrogen oxide and mercury
is released that adversely impacts health of many people in various ways. This impact can
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be reduced by the use of washed coal as it is high in calorific value compared to unwashed
coal, thereby reducing consumption and overall emission (ADB 1998).
The use of washed coal has the potential to reduce CO2 emissions arising from the power
plants. The study conducted at the NTPC’s Dadri Power Plant which used washed coal with
around 31-32% ash revealed that more than 600,000 tonnes per year of CO2 emissions can be
reduced both from coal combustion. Thus it can be stated that the use of washed coal in
thermal power plants can have significant environmental benefits like the reduction in
carbon emissions per unit energy generation through improved thermal efficiency. With the
use of washed coal which can be combusted efficiently with less air, the formation of NOx
could also be reduced. Further the use of low ash coal could also result in reduced
particulates in the flue gas leading to reduced load in Electrostatic Precipitator (ESP) and
possibly enhancing life of ESPs.
5.2.1 Environmental benefit from the reduction in carbon emissions
The environmental benefits from reduction in CO2 emissions have been assessed across
three scenarios. Under the BAU scenario (S1), emissions from all the thermal power plants
was estimated as per the actual coal consumption in 2018 (CEA database), however the
levels of coal consumption reduces in the other two washed coal scenarios (S2-34% ash
content, S3-30% ash content) to produce the same level of electricity. The specific coal
consumption improvement in washed coal scenario leads to a difference in the total CO2
emissions at the country level to produce the same amount of electricity.
In the context of this study, it is pertinent to identify the environmental benefits of use of
washed coal from the reduction in both local as well as global pollution but here the impact
of CO2 could only be assessed due to the lack of data on local environmental pollution
39
. For
the estimation of the impact of global pollution, the emission inventory estimates of CO2
were estimated for 2018 and under the three different scenarios.
Out of the total installed capacity of 344,002 MW in 2018, more than 50% has been coal
sourced (CEA 2019) and the total coal sourced electricity generation was 985 TWh. Thus to
meet this generation of 985 TWh, specific coal consumption under each scenario was
estimated based on plant wise assessments of coal consumption and ash content. The coal
consumption under each scenario in 2018 is shown in Figure 10.
39
Since the data of the power plants with ESP installation and without ESPs could not be procured, so the
impact on the local pollution could not be assessed. Additionally, the TPPs which have installed ESPs would not
require washed coal if they are complying with the existing air pollution norms.
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Figure 10: Coal consumption in 2018 under each scenario
Source: TERI analysis
The overall coal consumption under the policy scenario (S1) was the highest with total coal
consumption of 644 MT as it also involves the TPPs which continue to use the raw coal
according to prevailing practice. However, the coal consumption decreases to 601 MT in S2
due to the use of washed coal with 34% ash and further to 571 MT in S3 with the use of coal
with 30% ash content. Using these amounts of coal consumptions, the CO2 emissions in each
scenario were respectively estimated using emission factor 1.04 tCO2/ MWh (CEA 2018). The
total CO2 emissions at power plants end in each scenario for 2018 are given in Figure 11.
Figure 11: CO2 emissions in 2018 under each scenario
Source: TERI analysis
The emissions in S1 are the highest due to the maximum amount of coal consumption in this
scenario, followed by S2 and S3 wherein the coal consumption declines because of the use of
higher quantum of washed coal.
644
601
571
520
540
560
580
600
620
640
660
S1S2S3
Coal Consumption (in MT)
Coal
consumption (in MT)
1024
956
908
850
900
950
1000
1050
S1S2S3
CO2 emissions
Emissions (in MT)
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5.2.2 Social cost of carbon and the incremental environmental benefits
The cost of climate change due to emission of CO2 has been estimated in this study using
the social cost of carbon based on estimates presented in (Nordhaus, 2017)
40
. Social cost of
carbon (SCC) represents the economic cost caused due to an additional tonnage of CO2
emissions or its equivalent in the atmosphere. Various models are used to estimate the
monetary value associated with the cost of CO2 emissions, using multiple assumptions,
associated with economic growth, world economy, future emissions and its impacts. This
study uses the estimates from Nordhaus (2017), which uses the DICE (Dynamic Integrated
model of Climate and the Economy) framework. The cost of carbon used in this study for
2016-17 (at constant prices 2013-14) is USD 2.6/tCO2 or INR 153/tCO2 (using 2016 exchange
rate). We inflate using the GDP deflator to arrive the SCC for the year 2018. Using the above
estimated CO2 emissions and the cost of carbon mentioned, the emissions were monetized
and thus the difference under each scenario was used to estimate the incremental
environmental benefit.
The incremental benefit of use of washed from its current scenario is presented in Table 19.
Table 19: Estimated incremental environmental benefit (in Rsbn)
Incremental Environmental Benefit
Year S1-S2 S1-S3 S2-S3
2018 10.5 17.8 7.3
Source: TERI analysis
Estimated benefit from social cost of carbon from use of 34% washed coal for 2018 is INR
10.5 bn while the benefit from use of the 30% washed coal is INR 17.8 bn. These
environmental benefits were expressed per unit of electricity generated to estimate the net
incremental benefits (Table 20).
Table 13: Net incremental environmental benefit (in Rs/kWh)
Incremental Environmental Benefit
Year S1-S2 S1-S3 S2-S3
2018 0.01 0.02 0.01
Source: TERI analysis
5.3 Comparative environmental impact assessment of use of washery
rejects in CBFC vis-à-vis their use in TPS
Coal washing leads to generation of substantial quantity of rejects. The rejects have been
found to have an average ash content that ranges between 55%- 85% with GCVs of 500 –
40
https://www.pnas.org/content/114/7/1518#T2
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2200 kCal/kg. Based on literature review and discussion with selected stakeholders
regarding the current applications of rejects, it was learnt that they end up getting used in
1) FBC plants
2) Filling voids in mines, &
3) Other applications (e.g. brick kilns, road construction etc.)
A brief description of use of rejects in these applications is presented below,
1. FBC plants: Most of the captive power plant owners operating in proximity to washeries
opt for CFBC technology due to its capability to convert these rejects (having low energy
content ranging1200-2000 kCal/kg) into electricity, which otherwise would have been left
unutilized. These power stations, using rejects as fuels, too need to adhere to emission
norms for PM, SO2, NOxas notified by the MoEFCC. In practise, rejects are blended with
high grade coal to prepare for a better feed in CFBC boilers.
2. Landfill: There are significant amount of very low-grade reject generation after washing
process, which do not qualify for combustion (i.e rejects having GCV less than 1000
kcal/kg or ash above 80%). Such rejects are reportedly disposed off in an
environmentally sound manner for backfilling purposes with proper safety measures.
3. Other applications (e.g. brick kilns, road construction, etc.): There is a significant
amount of rejects (having GCV between 1000- 1500 kCal/kg) which does not qualify for
usage in FBC plants but have a market mainly in small industries like brick kilns, road
construction, etc. The washeries reportedly auction these rejects to such consumers
where it may be burnt in unregulated manner.
The utilization of these rejects in various applications can also cause additional
environmental impacts which can have the potential to neutralize or negate the
environmental benefit gained through the use of washed coal in place of the use of raw coal
in thermal stations. Therefore, to study this in detail in the presence of the potential
application of rejects, a comparative environmental assessment of the use of washery rejects
in CBFCs has been undertaken along with use of washed coal for power generation vis-à-vis
sole use of raw coal in conventional TPSs. If RoM (unwashed) coal is used for electricity
generation, these rejects are in effect transported along with raw coal which is consumed at
thermal power stations. Impact analysis due to use of coal rejects in combustion in other
unregulated sectors has not been undertaken as part of the study because of non-availability
of information on usage of rejects and emissions there from.
5.4 Study Methodology
Comparative assessment of emissions from utilization of rejects in CFBC and use of the
washed coal vis-à-vis raw coal in TPSs has been performed based on three scenarios as
presented in figure 12. Under scenario 1 (S1), TPSs using unwashed coal having ash content
greater than 34% have been considered and their PM and CO2 emission has been estimated.
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SOx and NOx have not been considered here. Under Scenario 2 (S2+F1), the power stations
are assumed to use washed coal having ash content of 34%. Rejects thus generated from
washing of the coal to bring ash content down to 34% have been assumed to be fully
consumed in FBC based power plants. Emission inventory of PM and CO2 under S2+F2 is
thus calculated. Finally in the third scenario, rejects have been considered in FBC technology
with no pollution control equipment and consequent inventory is estimated. Finally the total
emissions and emission per unit of electricity generated under the three scenarios have been
compared.
Scenario description
Figure 12: Scenario Description
5.3.1 Detailed approach for emission estimation for scenarios
Emission of carbon dioxide and particular matter for three scenarios (i.e. S1, S2+F1, S2+F2)
have been estimated based on the methodology given below.
1. Particulate emissions:
Epm = [Pc]a × Ac× (1–fbr)× M ×(1–REa) ……………….. (1)
Equation (1) is used to estimate the particulate emissions. Where, Epm is the emission of
particulates, [Pc]a is annual coal or reject consumption in TPS or an FBC plant, Ac is ash
content of Coal or rejects , fbr is the ratio of bottom to fly ash for thermal or FBC plants, M =
particulate mass fraction (0.4 for PM2.5 to PM10 and 0.75 for PM10 to total particulates
following Mahtta et al., 2016), REa is the efficiency (%) of installed emission control
equipment in thermal or FBC plants.
2. Carbon dioxide emissions: CO2 emissions of thermal power stations were calculated
using the formula given below:
CO2[Pc]a x GCV x EF x OF ………………. (2)
Scenario (S1)
•S1- Considered those
thermal power plants
consuming greater than
34% ash content
continue to consume
high ash coal (>34%)
Scenario (S2+F1)
•S2 - Considered those
thermal power plants
consuming greater than
34% ash coal starts
consuming washed coal
of 34% ash content, &
• F1 -100% utilization of
rejects in FBC plants
complying to emission
norms.
Scenario (S2+F2)
•S2 - Considered those
thermal power plants
consuming greater than
34% ash coal starts
consuming washed coal
of 34% ash content,&
•F2 - 100% utilization of
rejects in FBC plants in
uncontrolled manner
having no PCEs.
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Where: CO2 emission of the station in a given year, [Pc]a amount of fuel of type consumed
annually, GCV Gross calorific value of the fuel, EF is CO2 emission factor of the fuel based
on GCV, OF is Oxidation factor of the fuel.
5.3.2 Key assumptions
The broad assumptions considered for the study are listed below; analysis specific
assumptions are presented in detail in the subsequent sections.
Table 21: Assumptions taken for estimation of emissions
5.5 Comparative analysis of environmental impacts across scenarios
The quantity of rejects discarded from washing of raw coal has been estimated using ash%
to clean coal yield relationship (as derived from data provided by CMPDI). The raw coal
and washed coal consumption under S1 and S2 ( as described in section 5.2.1) has been
estimated using TPS specific coal consumption and reported electricity generation in these
units for the year 2018. The total raw coal, washed coal consumed in power plants and the
estimated generation of rejects from washing are given in table 22.
Table 14: Coal consumption & Electricity Generation for S1, S2 & F1 scenarios
Coal Consumption (MT) Electricity Generation (MU)
Raw Coal 357 524140
Washed Coal 311 500217
Rejects 46 29636 (100% uptake)
Using formulae (1) and (2), plant-wise emission inventory has been estimated for raw coal
and washed coal under scenario S1 and S2 and as well for reject utilization in FBC
technologies under F1 & F2. The results are presented in table 23.
Table 15: Scenario results for emissions
Components Data /Assumption
Quality of raw coal at power station Power station specific ash content in raw coal and
has been used from secondary data sources
GCV has been estimated from Ash -GCV
relationship published in NIT – Rourkela study
Bottom to fly ash ratio and ESP efficiency of
thermal or FBC plants
BFR for
thermal power plants is 0.25 and
reject consuming CFBC is 0.4 as per
secondary literature and consultation;
Removal efficiency of ESP is
99.8% for S1, S2, and F1,
0% i.e. no ESP in F2
Rejects quality and utilization in FBC plants Assumed reject quality having ash content of 65%
& GCV 1800 kcal/kg,
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5.5.1 Comparative assessment of CO2 emissions
It can be inferred from the above table that if the thermal power plants use washed coal
having ash 34% and all the associated rejects are utilized in CFBC plants (S2+F1), then the
CO2 emission per unit of electricity generated is slightly higher compared to S1 ( 0.987
kg/kWh vs 0.994 kg/kWh). The picture in regard to CO2 emission per unit of electricity
generated in S2+F2 scenario also remains same ( 0.994 kg/kWh).
5.5.2 Comparative assessment of PM emissions
While analysing PM emissions, it should also be noted that the share of electricity generated
(2018) from thermal plants having emission norms of 30 mg/Nm
3
, 50mg/Nm
3
, 100 mg/Nm
3
is
7%, 82% & 11% respectively (Author’s analysis
41
). Given that the amount of reject uptake of
46 MT (assuming 100% utilization), 4 GW of CFBC capacity has been estimated to be
required. There is no data available on existing capacity of CFBC using rejects also the
current practices consume rejects after blending, however from stakeholder consultation it is
learnt that nearly 15-20% of reject can go in existing CFBC and 80-85% of new capacity will
needed to be installed in order to consume overall rejects. Thus new CFBC installations have
to comply with 30mg/Nm
3
norm which will have lesser impacts.
The analysis shows the increase in PM emissions from use of rejects in (S2+ F1) where PM
emissions per unit of electricity generated is 0.108g/kWh compared to 0.099 g/kWh in S1
scenario. While if the rejects are used in FBC plant having no pollution abatement
technology, the PM emissions reach level of 17.04 g/ kWh (around 172 times more than S1
scenario). Thus, it will be detrimental for the environment to use rejects in an
uncontrolled/inefficient manner.
41
CEA database, analysed from date of commissioning of each unit of PP
Scenario 1 Scenario (S2 + F1) Scenario (S2 + F2)
Quantity (MT) 357 357 (311 + 46) 357 (311 + 46)
Electricity Generation (MU) 524140 529854 529854
PM_10 (kT) 52.26 57.72 9029
CO2 (MT) 517.40 527.20 527.20
PM_10 per unit of electricity generated (g/kWh) 0.099 0.108 17.04
CO2 per unit of electricity generated (kg/kWh) 0.987 0.994 0.994
Utilization of rejects in CFBC played an extremely important role while analyzing emissions,
and it is evident from the above analysis that even small share of rejects used without PCEs or
if used in unregulated sector has the potential to sink the overall agenda of environmental
improvement from washing of coal.
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5.5.3 Sensitivity tests and analysis
Based on the primary data received from CIL and private washery, sensitivity analysis case
study (given in Annex VI) has been developed for reject utilization in FBC boilers. Rejects
generated from Indian washeries vary in characteristics due to type of raw coal,washing
characteristics(NGMI), technology of washing, etc. Accordingly, the quality and quantity
will differ which will determine its preferred application or utilization. In the absence of the
washery wise data, a sensitivity analysis is undertaken by varying these parameters in line
with the primary data received from selected washeries.
The parameters which play determining role in generating emissions are:
Table 16: Sensitivity Parameters
Sensitivities 1 2 3 4 5
Bottom ash to fly ash ratio 0.4 0.5 0.6
Heat rate of FBC 2800 2900 3000 3100
Ash content in rejects 55% 60% 65% 70% 75%
GCV of rejects 2000 1900 1800 1700 1600
Total percentage of reject
consumption in FBC
100% 75% 50%
Out of these parameters, two variables that have major impact on overall emissions i.e. ash
content and bottom to fly ash ratio in different scenarios of reject utilization.
Results
Net impact on emissions per unit of electricity generated is shown in table 25.
Table 17: Sensitivity analysis
Sensitivity Test: Ash % of rejects Sensitivity Test: BFR
of CFBC
Red – Net negative impact compared
to S1
Green- negative impact is neutralized
to S1
When reduced to
55% from 65%
When increased
to 75% from 65%
When BFR increased
to 0.66 from 0.4
Impact on CO2 per
unit of electricity
generated
S2 + F1 0.62% -0.63% No change
S2 + F2 0.47% -0.48% No change
Impact on PM per unit
of electricity generated
S2 + F1 5.69% -5.44% -20.24%
S2 + F2 18.82% -16.03% -64.71%
1. Ash Content: Net impact shown here (please refer Annexure VII.1 for results) shows
rejects having ash content in the range of 55%-60% can be used in CFBC with PCEs (as in
scenario S2+F1) as it could generate more electricity at comparatively low emission level.
After reduction in ash content net negative impact compared to S1 is neutralized for CO2
but not for PM. However, rejects having higher ash content leads to more emissions and
should be disposed off for backfilling purpose in an environmentally sound manner in
order to minimize its impact on environment.
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2. Bottom to Fly ash ratio: For the sensitivity analysis, two extreme scenarios of bottom-ash
to fly-ash ratio (BFR) ratio - 0.4 & 0.66 - are considered for CFBC technology as per BEE
guidelines for CFBC boilers. From the above analysis (please refer Annexure VII.2 for
results), it is clear that BFR is critical factor while assessing the overall PM emissions. It
leads to 20% and 64% increase in PM emissions per unit of electricity generated in S2+F1
and S2+F2 scenario respectively when BFR changes from 0.4 to 0.66. The technology
having low BFR is preferable for the consumption of rejects. The difference in BFRs of
CFBC & boilers in thermal power plants (sub-critical, super & ultra-super critical)
requires much detailed assessment considering its criticality in generating emissions
load.
5.5.4 Environmental Impact of rejects used in unregulated sector
As per the current practices of utilization of rejects in unregulated sector, there is no clear
picture available regarding the technology of application in which combustion is taking
place. From the stake holder consultations, it is learnt that the uptake is mainly through the
auction procedure and distributed to the miniscule industries like road construction, civil
works, bricks, ceramics, etc. The functional unit of output generated is also changes across
different industries as unit for power is per unit of electricity generated which will be
different for other unknown sectors like amount of bricks produced, length of road laid, etc.
Thus, the comparative assessment cannot be done for the usage of rejects and due to lack of
evidence and clarity on the data provided by CIL for reject sales on quantity of consumption
& technology/application of its usage, it is difficult to quantify the environmental impacts
especially air pollution such as PM. Also, there is no proximate and ultimate analysis data of
rejects available with the concerned stakeholders for assessing other pollutants. Thus, this
calls for complete inventory of technologies and much detailed assessment of environmental
impact of rejects usage in each of the unregulated sector.
While CO2 generated will be same in both the cases of reject utilization as fuel i.e. when
rejects are used in totally unregulated manner or in FBC with full compliance with the
environmental norms, if it used for combustion purpose as fuel.
5.5.5 Conclusion
From the environmental analysis, it can be concluded that the utilization of rejects can have
significant environmental impact which has the potential to negate the positive
environmental benefit gained through the use of washed coal. However, certain measures
can be taken to control the impact of rejects. Globally, filling rejects in mine voids is the most
common practice for disposing washery rejects. The same can be followed for high ash/low
GCV rejects through proper engineering solution such as substantially upgrading high ash
rejects, through compacting, etc. From the sensitivity tests, it is found that use of high GCV
rejects is desirable in FBC plants as it returns positive environmental impact per unit of
electricity produced. However, if high GCV rejects are used in FBC boilers or in other
sectors, proper pricing (based on calorific value and ash content) and adopting/mandating
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stringent emission norms as per consuming sector/technology need to be done. Framing
uniform reject utilization policy helps in setting up compliance norms for the sale/disposal
by washeries. This compliance should be ensured through proper monitoring of sale, piling
stock & disposal wherein a penal mechanism could be introduced for non-compliance.
5.6 Other anticipated benefits
5.6.1 Reduced fugitive emissions during transportation
Emissions from the initial coal preparation phase of either wet or dry processes consist
primarily of fugitive particulate matter (PM) as coal dust from roadways, stock piles, refuse
areas, loaded railroad cars, conveyor belt pour offs, crushers, and classifiers. These
emissions of coal particulates and other air pollutants mainly occur during loading,
unloading and en route. It is estimated that about 50% of the coal dust losses occur during
journey time and 25% at loading and 25% at unloading
42
. There is some loss also due to
spillage.
These fugitive emissions tend to cause both health and environmental impacts in and
around the surroundings. However the use of washed coal can reduce these emissions
during the transportation process. The reduction in the fugitive emissions will further
benefit the environment and health.
5.6.2 Reduced fly ash
The fly ash generated in thermal power plants due to the combustion of coal can cause
hazardous impacts on the environment and even public health. Hence, the options are either
to reduce the fly ash generation at source or to utilize the generated fly ash in environmental
friendly applications such as cement industry, bricks and tiles, road development etc. To
encourage its utilization, Government is taking various policy steps however, the uptake
remains at low level till now. While using washed coal, as a result of the improved GCV
compared to raw coal, the specific coal consumption reduces and thereby the fly ash
generation. This also indirectly lowers the requirement of water to effectively handle the fly
ash in landfills. However, the utilization of co-produced rejects in FBC plants has the
potential to neutralize or negate the benefits gained through the use of washed coal.
42
Environmental Impacts of Coal Transportation. (1987). Environmental Impacts of Coal Mining & Utilization,
73–80. doi:10.1016/b978-0-08-031427-3.50013-x
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59
Chapter 6: Summary
The non-coking thermal coal available in India has high ash content, low calorific value and
low sulphur. Use of raw, blended or beneficiated coal with ash not exceeding thirty-four
percent on an annual average basis was mandated by MOEFCC from 1stJune, 2001 for (a)
any thermal power plant located beyond 1000 km from the pit- head and (b) any thermal
Power plant located in urban area or sensitive area or critically polluted area irrespective of
their distance from the pit head. Plants using specified types of clean coal technologies were,
however, exempted from complying with the afore-mentioned stipulations.
Earlier vide notification dated 2ndJanuary 2014
43
, plants located at distances less than 1000
km were also mandated to use coal with ash not exceeding 34%. Stand-alone thermal power
plants of any capacity or captive power plants above 100 MW located between 750-1000 km
and 500-749 km from pit-head were also required to comply with aforementioned ash
content limits in coal on quarterly average basis with effect from 1 January 2015 and 5 June,
2016 respectively.
44
Onus for supply of such coal was put on coal supplier as compared to
power plants, which were hitherto required to use such coal. Main reasoning behind
limiting the ash content in coal seemed to avoid transportation of inorganic mineral matter
in coal which does not serve any purpose in power generation but is rather detrimental to
power plant equipment. Better utilization of capacity of railway wagons and rail
transportation network, environmental benefits in transportation of beneficiated coal with
less ash content from the washery to power plant are other intended benefits.
On 7thDecember 2015
45
, new environment pollution norms notified by Government of India
for thermal power stations tightened the emission norms in respect of PM and norms for
SOx, NOx and mercury were introduced. Graded norms have been specified for power
plants commissioned (a) before 31st December 2003, (b) after 31
st
December 2003 up to
31stDecember 2016 and (c) from 1
st
January 2017.This called for retrofitting/replacement of
ESPs in the existing power stations and appropriate design of ESPs in the new plants for
control of PM as well as addition of Flue Gas Desulphurization (FGD) and Selective
Catalytic or Non-Catalytic Reduction (SCR/SNCR) systems for de-NOx operations. Various
power plants are at different stages of implementation, ordering or design.
While, beneficiation of coal through coal washeries brings down ash content in coal, it also
improves GCV of coal, and so reduces the amount of coal to be transported from the
43
MoEFCC 2014.Notification on Environmental Protection
Rule.https://ercindia.org/archive.ercindia.org/files/erc_desk/MoEF%20CC%20OM%20Reg%20coal%20in%20T
PP%2002012014_gsr02e.PDF
44
The latest MoEF&CC vide notification dated 21
st
May, 2020 has waived the stipulation of washed coal usage
without any condition of distance or ash content.
45
MoEFCC 2015.Notification for new environmental regulations – 7th December –2015.
http://www. indiaenvironmentportal.org.in/files/file/Moef%20 notification%20-%20gazette.pdf
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railhead to the power station, and results in increased moisture. However, during pilot
study in NTPC Dadri, increase in NOx level has been observed while firing washed coal in
the generating unit.
Cost of washing coal largely depends on ash content of raw coal, level up to which ash
content is required to be brought down through washing, yield of washed coal vis-à-vis
rejects, which eventually increases the price of washed coal. Distance for which washed coal
is to be transported is the other important parameter affecting the relative reduction in the
price of landed cost of washed coal at the power stations.
Pricing of Run of mine (ROM) coal in India is based on grade of coal (G1 to G17) notified by
CIL time to time. The GCV range in each grade of coal is 300 kCal/kg. Estimation of ash% for
a particular grade of coal is a challenge since GCV of coal depends on four components –
fixed carbon (FC), volatile matter (VM), inherent moisture (IM) and ash. It may happen that
coal with a lower ash% has lower GCV as compared to coal with higher ash%. Developing
correlation between GCV of coal and ash% has been a key challenge in the study. Due to
variety of coal used in power sector in India, it is essential to use complete proximate
analysis of coal for conducting a proper study. In the absence of the same, the present study
has been carried out using correlation between ash% and GCV as established by NIT,
Rourkela.
Coal washing yields operational benefits to power stations in terms of better flame stability,
reduced operation and maintenance cost, increase in PLF, improved life of boiler auxiliaries
such as burners and mills, etc. Since majority of power stations in India use washed coal
along with raw or blended domestic and imported coal, good set of studies in regard to
operational benefits of beneficiated Indian coal are required in addition to pilot studies or
simulation model results before making generic recommendations for various typesof plants
using variety of coal.
Pilot studies (ORF
46
, ADB studies
47
, and Ronghe Committee) using washed coal in power
stations carried out in the past show improvement in auxiliary power consumption (APC),
unit heat rate (HR), availability/PLF. For the present study, BHEL carried out a simulation
study for a 500 MW Unit which is designed for 42% ash, 0.49% Sulphur & GCV of 3400
kCal/kg. In the simulation study, coal fired with GCV of 4500 kCal/kg, 32% ash and 0.60%
Sulphur showed deterioration in unit heat rate. Though, boiler efficiency is noted to increase
by 0.5% for 10% ash improvement, but overall cycle efficiency is reported to have
deteriorated by 0.12% due to reduction in main steam and re-heat steam temperatures. This
leads to the conclusion that, studies for a good number of representative cases capturing
unit size, actual unit configuration, age, coal characteristics, etc., are essential for drawing
46
https://www.orfonline.org/wp-
content/uploads/2017/07/ORF_Report_CoalBeneficiation_FinalForUpload.pdf
47
https://www.adb.org/sites/default/files/project-document/72146/26095-ind-tacr.pdf
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appropriate inferences and generic conclusions are not possible. Moreover, the studies show
improvement in auxiliary power consumption (APC) of generating unit but there is variance
in degree of improvement in APC in different studies. This again highlights the importance
of plant specific assessment. The TERI analysis shows that the use of washed coal in power
plants is economically beneficial for units if they meet three specified criteria’s i.e.
power plants receiving coal over long distances (over 600 km)
RoM coal from mines with higher ash content (more than 39% i.e G-12 and lower
grade)
Washing yield more than (75%)
Washing of coal brings down burden of ash at ESP inlet which leads to reduction in
emission of PM from stack. However, it needs to be analysed whether stack emissions
comply with new environmental norms merely by washing of coal or retrofitting of ESP
fields is also required. TERI’s analysis showed that use of washed coal having 5-6% less ash
in coal, in power generating station could reduce 20% PM emission from stack. However,
this result is highly dependent on the assumptions in regard to bottom ash to fly ash ratio in
boiler, collection efficiency of ESP, operational methodology of ESP, coal properties, etc.
Analysis of cost applicable for reduction in stack emissions due to washing of coal to cost of
ESP retrofitting to comply with new environment norms cannot be generalised, it rather
needs to be unit specific.
The existing thermal power stations following old environment norms have following
options to meet new environmental norms:
I. By coal washing alone, if possible.
II. By coal washing and smaller retrofit/new pollution control equipment.
III. A large retrofit / new pollution control equipment, with no coal washing.
It is extremely important to acknowledge here that the matrix of installed capacity of power
plants, their unit configuration and vintage, operational health, coal quality , and location of
power stations from mining and washing sites, etc. is quite complex. Such complexities in
the Indian power sector call for the development of an integrated value chain framework
and plant specific data analysis using that framework which will help in improved
understanding of the impacts of use of washed coal over unwashed coal. Economic
comparison of the three aforementioned options needs to be undertaken for each station /
unit duly factoring in the relevant values as applicable along the value chain.
Another major emphasis associated with use of washed coal is its environment
improvement potential due to the reduction of overall coal consumption at power plant
owing to improvement in specific coal consumption for power generation. India in its
Intended Nationally Determined Contributions (INDC) submitted to UN Framework
Convention on Climate Change in October 2015, committed to undertake clean coal policy
measures to combat global warming. Earlier studies have shown that the use of beneficiated
coal leads to lower global warming impact due to its higher thermal efficiency. As per
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TERI’s analysis, a transition towards enhanced use of beneficiated coal having ash content of
34% leads to reduction of CO2 emission by 6% from the emission estimated current coal mix.
A reduction of CO2 emission of 11% has been estimated to be achieved if the ash content in
the washed coal is reduced to 30% from current coal mix. The monetised benefits for the
emission reduction under the two scenarios have been estimated at INR 10.5 bn and INR
17.8 bn respectively. This will translate to Rs. 0.01/kWh and Rs. 0.02/kWh respectively. A
comparative analysis of reduction in CO2 emission due to lesser APC vis-à-vis CO2 emission
from electricity consumption for washery operations shows the incremental benefit of 3.64
KT, 2.92 KT, 2.12 KT, & 1.46 KT per million tonne of coal consumption for G-11 to G-
14 grades of coal respectively. There will also be reduction in secondary CO2 emissions
from lesser energy consumption in transportation due to reduction in quantum of coal to be
hauled.
It is important to underline that the unregulated/uncontrolled use of washery rejects will
negate the environmental benefits accrued from use of washed coal in thermal power plants.
As per TERI’s analysis, for the power plants consuming higher ash coal (>34%), the
combined environmental impact per unit electricity from the use of washed coal and co-
produced rejects with 100% utilization in FBC plants are slightly greater than those plants
using raw coal when used in controlled manner. However, from the sensitivity tests, it is
found that the usage of high GCV or low ash rejects in FBC plants with retrofitted ESPs and
PCEs can be considered for usage as it can result in neutral environmental benefit per unit of
electricity produced. Hence, there is a need to ensure that the washery rejects are used in a
manner that has zero or minimal environmental impacts with the help of regulations,
uniform reject utilization/disposal policy and stringent emission norms in those potential
applications.
Reduction in coal quantity to be transported for giving same heating value in power
generation and the attendant reduction in ash leading to reduced land requirement for ash
disposal are positive spin-offs of the use of washed coal. Pending availability of
comprehensive and granular data, means to be adopted by each power station to comply
with new environmental norms for thermal power stations may be left to the power
station/power utility as an interim measure. In the absence of holistic operational
improvement cum economic analysis based on transparently measured and documented
data, use of washed coal based on economics or constraints such as land for ash dumping,
ash water requirement, etc., is required to be carried out. An integrated value chain
framework has been developed for assessment of associated costs and benefits. Plant specific
inputs to this framework would help each plant to decide best option for meeting new
environmental pollution norms. And, given the fact the new notification has waived off the
stipulation of washed coal usage in power plants based on the distance and ash content
criteria, the adopted methodology in the study will help analyze the individual plants to
meet the environmental norms in cost effective manner vis-à-vis plant can assess the
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economic effectiveness of washed coal usage across the value chain using plant specific
inputs to arrive at the judicial decision for opting washed coal usage for power generation.
Proper pricing of washed coal with specified GCV range and ash percentage holds the key
for making it a win-win situation for coal supplier as well as power producer.
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64
Annexure I (Economic Assessment): An Integrated value chain framework and economic impacts from use of washed coal
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65
Annexure II: case study by CMPDI & NPC at Satpura thermal power
plant
The study carried out by Central Mine Planning &Design Institute (CMPDI) and National
Productivity Council (NPC) in 1988-89 at Satpura TPS of MPEB using 34 percent washed
coal in one 210 MW unit brought out the following findings.
Parameter From (RoM
Coal)
To (with
washed
coal)
%
Improvement
i) Improvement in PlantUtilisation Factor (PUF) 73% 96% 31.51%
ii) Improvement inGeneration in MU/day 3.71 4.83 30.19%
iii) Reduction in Specific Coal Consumption in
Kg/Kwh
0.77 0.553 28.18%
iv) Elimination ofSpecific support fuel in ml/unit
generated
5 ml NIL No need for support
fuel
v) Reduction in Rejects 0.3-0.4% 0.03% 91.43%
vi) Increase in Boiler
Efficiency
86.57% 89.51% 3.40%
vii) Reduction in Smoke & Dust Emission in g/m3 ESP inlet:29.78 17.23 42.14%
ESP Outlet:1.57 0.299 80.96%
viii) Reduction in AlphaQuartz 14.5% 11% 24.14%
By CEA at NTPC Dadri power plant
The analysis of the NTPC’s Dadri Power Plant which used washed coal with around 34-35
percent ash from Central Coalfield Ltd.’s Piparwarwashery revealed the following results:
Increase in operating hours up to 10percent
Increase in PLF up to 4percent
Increase in PUF up to 12percent
Reduction in breakdown period up to 60percent
Increase in overall efficiency up to 1.2percent
Increase in generation per day 2.4 Million units (MU or million kWh)
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Annexure III: Latest Data from NTPC Dadri power plant (as received
from CEA)
Landed Cost of Coal
Type of coal
Coal cost
(Rs/Tonne)
Freight
(Rs/Tonne)
Landed cost
(Rs/Tonne)
Cost/1000
K.Cal
Washed Coal 2910 2160 5070 1.32
Raw coal 1980 2160 4140 1.18
Assessment of impact of washed coal carried out at NTPC Dadri power plant
To assess the actual performance of washed coal, a study was carried out at NTPC Dadri
Power plant in its Stage-2 Unit-5 (490 MW unit size). However, as coal at Dadri is received
from different sources, it is difficult to analyse the exact impact of only washed coal or raw
coal on plant parameters.
To study the impact of washed coal, 100% CCL washed coal and CCL raw coal was fired on
03.02.20 and 22.01.20 respectively for 4 to 5 hours. The following data has been compiled for
this period:
Parameter Unit
03.02.2020 22.01.2020
Washed Coal Raw Coal
Load MW 283 281
GCV Kcal/kg 3849 3507
Avg. Heat Rate Kcal/kWh 2380 2384
Sp. Coal kg/kWh 0.618 0.680
Total coal T/H 175 191
Total Air T/H 1090 1162
Draft Power kWh 4073 4357
Heat Rate Kcal/kWh No change
Water consumption KL/kWh No change
SO2 mg/Nm3 1143 1210
NOx mg/Nm3 470 380
Table: Comparison of operating parameters
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Annexure IV: Cost heads from mine to power plant for different
grades and levels of washing for plants situated at 1000km from
washeries
G 12 grade coal washed up to 34% ash
Coal
Mine
>>>
Transportation
>>>
Washery
>>>
Transportation
>>>
Power Station
Quantity (Ton) 1 1 0.86 0.86 0.86
GCV (kCal/kg) 3850 3850 4286 4286 4286
Ash(%) 39% 39% 34% 34% 34%
Price (Rs/Tonne) 1594 60 416 2225 4295
G 12 grade coal washed up to 32% ash
Coal
Mine
>>>
Transportation
>>>
Washery
>>>
Transportation
>>>
Power Station
Quantity (Ton) 1 1 0.81 0.81 0.81
GCV (kCal/kg) 3850 3850 4445 4445 4445
Ash(%) 39% 39% 32% 32% 32%
Price (Rs/Tonne) 1594 60 549 2225 4427
G 13 grade coal washed up to 34% ash
Coal
Mine
>>>
Transportation
>>>
Washery
>>>
Transportation
>>>
Power Station
Quantity (Ton) 1 1 0.75 0.75 0.75
GCV (kCal/kg) 3550 3550 4286 4286 4286
Ash(%) 43% 43% 34% 34% 34%
Price (Rs/Tonne) 1508 60 688 2225 4480
G 13 grade coal washed up to 32% ash
Coal
Mine
>>>
Transportation
>>>
Washery
>>>
Transportation
>>>
Power Station
Quantity (Ton) 1 1 0.69 0.69 0.69
GCV (kCal/kg) 3550 3550 4445 4445 4445
Ash(%) 43% 43% 32% 32% 32%
Price (Rs/Tonne) 1508 60 890 2225 4682
G 14 grade coal washed up to 34% ash
Coal
Mine
>>>
Transportation
>>>
Washery
>>>
Transportation
>>>
Power Station
Quantity (Ton) 1 1 0.63 0.63 0.63
GCV (kCal/kg) 3250 3250 4286 4286 4286
Ash(%) 47% 47% 34% 34% 34%
Price (Rs/Tonne) 1422 60 1076 2225 4782
G 14 grade coal washed up to 32% ash
Coal
Mine
>>>
Transportation
>>>
Washery
>>>
Transportation
>>>
Power Station
Quantity (Ton) 1 1 0.57 0.57 0.57
GCV (kCal/kg) 3250 3250 4445 4445 4445
Ash(%) 47% 47% 32% 32% 32%
Price (Rs/Tonne) 1422 60 1382 2225 5088
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Annexure V: Unit size wise illustration of impact on variable cost due
to coal washing of G13 coal washed upto 34%
-0.30
-0.25
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
0.25
50
150 250 350 450 550 650 750 850 950
1050 1150 1250 1350 1450 1550 1650 1750 1850 1950
Increase / decrease in Variable cost (Rs/kWh)
Distance
660 MW
500 MW
300 MW
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Annexure VI: Case study of reject generation from different washeries,
its utilization and contribution to emissions
Case Study for Existing, three washeries generating different quantity and quality of rejects
and assessed emissions based on their utilization in CFBC plants. Two washeries are
operated by CIL (piparwarwashery and bina washery) and another one is a private washery
from Talcher area.
Case 1 PiparwarWashery
(CIL) - 2018
actual data
Case 2 Bina Washery
(CIL) - 2018
actual data
Case 3 Private
Washery (Talcher
area)
Coal Washing capacity
(MTY)
6.5 4.5 4
Raw coal (MT) 6.442794471 3.808 3.8
(at 95% utilization)
Clean coal Yield % 99.84% 83.59% 73.5%
Washed Coal (Ton) 6432486 3183000 2793000
Reject (Tons) 10510 625000 1007000
Ash% of raw coal 38% NA 43.00%
Ash % of rejects 55% 70% 65%
GCV of rejects (kcal/kg) 2500 1400
shared by CIL very low
grade rejects
1800
Reject Utilization in
CFBC boilers
Generation (MU) 8.5 306.8 593
Capacity (MW) required at
normative generation
1.15 41.2 79
Currently sold to local
industry through e -
auction, 5886.13 is utilized
out of 10510 tons (56%)
1 unit of 40 MW, currently
being not utilised as very
low grade
3 units of 25MW each
PM emissions (kT) 0.003 0.206 0.359
CO2 emissions (kT) 9.96 355 686.99
*Yellow highlighted numbers are assumptions where actual data was not available
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Annexure VII: Sensitivity analysis of the reject quality parameters on
emissions in different utilization scenarios
Sensitivity Analysis
1. Ash Content: Three ash content of rejects i.e 55%, 65%, & 75% and respective GCVs
are considered for this case of sensitivity analysis
BFR = 0.4 Scenario 1 Scenario (S2 + F1) Scenario (S2 + F2)
55% ash
& 2000
GCV
65% ash
& 1800
GCV
75% ash
& 1600
GCV
55% ash
& 2000
GCV
65% ash
& 1800
GCV
75% ash
& 1600
GCV
Electricity Generation (MU) 524140 533147 529854 526561 533147 529854 526561
PM_10 (kT) 52.26 54.96 57.72 60.49 7646 9029 10412
CO2 (MT) 517.40 527.20 527.20 527.20 527.20 527.20 527.20
PM_10 per unit of electricity
generated (g/kWh)
0.099 0.103 0.108 0.114
14.34 17.04 19.77
CO2 per unit of electricity
generated (kg/kWh)
0.987 0.987 0.994 1.001
0.988 0.994 1.001
2. BFR ratio: Two scenario of extreme extent of bottom to ash ratio (BFR) ratio i.e. 0.4 & 0.66
are considered according to BEE guidelines for this case of sensitivity analysis.
Reject Ash Content = 65% ,
GCV = 1800
Scenario 1 Scenario (S2 + F1) Scenario (S2 + F2)
FBR = 0.25 FBR = 0.4 FBR = 0.66 FBR = 0.4 FBR = 0.66
Electricity Generation (MU) 524140 529854 529854 529854 529854
PM_10 (kT) 52.26 57.72 69.41 9029 14873
CO2 (MT) 517.4 527.20 527.20 527.20 527.20
PM_10 per unit of electricity
generated (g/kWh)
0.099 0.108 0.131
17.04 28.07
CO2 per unit of electricity
generated (kg/kWh)
0.987 0.994 0.994
0.994 0.994
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