Report on
Data Structure for Customized Information
Database for Different Categories of Industries
in Andhra Pradesh
Submitted to
Andhra Pradesh Pollution Control Board A-3 Industrial Estate, Sanathnagar, Hyderabad (AP)
Consulting services for
Business Strategy for Environmental Compliance Assistance Centre
Project: Capacity Building for Industrial Pollution Management Project (CBIPMP)
Environmental Management Centre LLP
C29, Royal Industrial Estate, 2nd Floor, Near Naigaon Cross Roads,
Wadala (West), Mumbai 400031
P: +91 22 4004 9210-13
F: +91 22 4004 9210
U: www.emcentre.com
March, 2013
Report on Data Structure for Customized Information Database in AP
Environmental Management Centre LLP i
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Contents
A. Background ................................................................................................................................... 1
B. Rationale behind Prioritization of Industries ........................................................................... 2
C. Development of Prioritization Index ......................................................................................... 4
i. Calculation of R1: ..................................................................................................................... 5
i. Type of Industry – Score A ................................................................................................. 7
ii. Scale of Industry – Score B .................................................................................................. 7
iii. Location of Industry – Score C ....................................................................................... 8
iv. Overall Calculation of R1 .............................................................................................. 10
ii. Calculation of R2 .................................................................................................................... 11
iii. Calculation of R3 ................................................................................................................ 15
iv. Calculation of R4 ................................................................................................................ 16
v. Calculation of PI ..................................................................................................................... 16
D. Application and Use of PI ......................................................................................................... 17
i. Target Setting .......................................................................................................................... 17
ii. Prioritization for Inspections ................................................................................................ 18
iii. Taking Appropriate Action .............................................................................................. 18
iv. Tracking Performance ....................................................................................................... 22
E. Source of Data for R1, R2, R3 and R4 ...................................................................................... 23
F. Conclusions ................................................................................................................................. 24
G. Recommendations ...................................................................................................................... 25
i. Development of MIS for PI ............................................................................................... 25
ii. Resource Consumption Index : Expanding PI ............................................................... 25
1 Output of Task D6 as per Contract
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List of Tables
Table 1 Inspection Frequency for Red, Orange and Green category Industries ......................................... 3
Table 2 Rule Base for Calculation of Score A under R1 .................................................................................. 7
Table 3 Rule Base for Calculation of Score B under R1 .................................................................................. 8
Table 4 Rating of AP Districts based on Population & Industrial Densities ................................................ 9
Table 5 Rule Base for Calculation of Score C1 ............................................................................................... 10
Table 6 Rule Base for Calculation of Score C2 ............................................................................................... 10
Table 7 Recommended Parameters for Checking Compliance for 17 Categories Highly Polluting
Industries- Water Pollutants ............................................................................................................................ 11
Table 8 Recommended Parameters or Checking Compliance for 17 Categories Highly Polluting
Industries – Air Pollutants ................................................................................................................................ 12
Table 9 Rule Base for Calculation of R3 .......................................................................................................... 15
Table 10 Rule Base for Calculation of R4 ........................................................................................................ 16
Table 11 Prioritization of Industries and Proposed Actions for APPCB .................................................... 18
Table 13 Linking between ECAC’s Services and R1 x R2 vs. R3 x R4 Scores ............................................ 21
Table 13 Data Sources for Constructing PI ..................................................................................................... 23
Table 14 Recommended Sources of Information for R4 ............................................................................... 24
Table A15 District-wise Classification of Industries in AP (2007) ............................................................... 28
Table A16 Standards for Checking Compliance for 17 Category Highly Polluting Industries – Effluent
Generation .......................................................................................................................................................... 30
Table A17 Standards for Checking Compliance for 17 Category Highly Polluting Industries – Air
Emissions ............................................................................................................................................................ 31
List of Figures
Figure 1 Inspection Load for Different Monitoring Frequencies .................................................................. 4
Figure 2 The Pressure-State-Response (PSR) Model ....................................................................................... 6
Figure 3 Application of PSR Framework in Industrial Pollution Management .......................................... 6
Figure 4 Scoring Scheme based on Exceedance over Standard ................................................................... 13
Figure 5 Relation between the Four Potential Uses of PI ............................................................................. 17
Figure 5 A Conceptual Framework of Actioning based on R1 x R2 vs. R3 x R4 Score ........................... 19
Figure 6 Distribution of 10 industries in Quadrants based on R1XR1 vs. R3xR4 Scores ....................... 20
Figure 7 Use of PI Score to track Industry’s Performance and Effectiveness of Interventions by APPCB
and ECAC ........................................................................................................................................................... 22
Figure 9 District-wise concentration on Red Category industries in Andhra Pradesh ............................ 29
List of Boxes
Box 1 ....................................................................................................................................................... 2
Box 2 ....................................................................................................................................................... 6
Box 3 ..................................................................................................................................................... 14
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A. Background Andhra Pradesh Pollution Control Board (APPCB), under the World Bank assisted project
on Capacity Building and Industrial Pollution Management (CBIPMP) is setting up
Environmental Compliance and Assistance Centre (ECAC). Environmental Management
Centre LLP has been engaged by APPCB for developing the Business Strategy for ECAC.
ECAC is visualised as a facilitation agency that would assist industries to establish, operate
and attain regulatory and voluntary environmental compliance in a cost effective manner.
To this end, the ECAC will collaborate with various strategic partners and would provide
information, technical assistance and training. The ECAC is envisaged to be a sustainable
organization that provides assistance to industry (in specific Micro, Small and Medium
Enterprises (SME) and Urban Local Bodies (ULBs) with a focus on increasing compliance
and competitiveness.
In general, environmental compliance implies conforming to a rule, laid down under policy,
regulations or standard. In the Indian context, environmental compliance for industry could
typically include:
― Obtaining licenses like Consent/Clearances from appropriate authority;
― Compliance with the conditions laid down in such license;
― Compliance with discharge /emission / waste related standards; and
― Timely submission of monitoring reports and cess returns.
Industries often do not take meeting with environmental compliance seriously. Cost of non-
compliance generally is however greater than the cost incurred towards compliance2.
State Pollution Control Boards (SPCBs) have authority under the Water (Prevention and
Control of Pollution) Act, 1974, Air (Prevention and Control of Pollution) Act, 1981 and
Environmental (Protection) Rules, 1986 to initiate action against non-compliant industries
― Disconnect non-compliant facility’s utility connection,
― Issue of closure order against the non-compliant facility and /or
― Prosecution of the occupier of such errant facility.
BOX 1 shows illustrations of actions taken by SPCBs and Courts on no-complying
Industries. Closure of industries not only leads to business interruption but in addition leads
to loss of reputation and reduced confidence of investors. Meeting compliance in a
consistent and proactive manner is therefore beneficial to the industry. ECAC is expected to
play a facilitator in this direction.
2 http://www.tripwire.com/ponemon-cost-of-compliance/
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BOX 1
ACTION TAKEN ON NON-COMPLIANT INDUSTRIES
― Between 1997 and 2002, Maharashtra Pollution Control Board has disconnected services
for 858 for violation of the Water Act, and 145 for violation of the Air Act.
― In 1995, the Gujarat High Court ordered the closure of 756 industrial units in Vatva,
Narol, Naroda, and Odhav, asking them to compensate the villages affected by
pollution through discharge of untreated effluents.
― Between January 2005 and September 2006, the West Bengal PCB disconnected the
electricity for 373 facilities. Out of this 257 facilities were connected once compliance
was achieved.
― The Madras high court directed all bleaching and dyeing units in the textile hub of
Tirupur in west-central Tamil Nadu to close with immediate effect in January 2011. This
direction came on a petition from non-government bodies and farmers against these
units for polluting the Noyyal River flowing through the city, 390 km southwest from
Chennai. The court said these units would not be permitted to resume work till they
achieved Zero Liquid Discharge (ZLD) status. The Tamil Nadu Pollution Control Board
was ordered to inspect each unit and its report will be the sole basis to grant permission
to recommence.
Ensuring compliance, especially with the MSMEs, could be a resource intensive activity for
SPCBs. A prioritized approach is therefore necessary.
B. Rationale behind Prioritization of Industries APPCB is the apex authority in the State of Andhra Pradesh (AP) for upholding
environmental protection. APPCB is mandated to enforce the following major regulations
― Water (Prevention & Control of Pollution) Act, 1974 and Rules, 1975
― Water (Prevention & Control of Pollution) Cess Act, 1977 and Cess Rules, 1978
― Air (Prevention & Control of Pollution) Act, 1981 and Rules, 1982
― Environmental (Protection) Act, 1986 and Rules, 1986
― Hazardous Waste (Management and Handling) Rules, 1989 [superseded by
Hazardous Waste (Management, Handling & Trans-boundary Movement) Rules,
2008, as amended to date]
Depending on relative pollution potential, industries are classified (and thus prioritized)
into Red, Orange and Green categories. A district wise distribution of industries into Green,
Orange and Red Categories in AP is presented in Annexure 1. It may be observed that Red
and Orange category industries dominate the industrial scenario in most districts of AP. On
average, roughly 35% of the industries are of Red category and 90% are in Red plus Orange
category in the districts. In Nellore, more than 72% of the industries are in Red category.
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Districts with higher concentration of Red/Orange category industries could be consider as
priority districts.
The frequency for inspection of Red, Orange and Green category industry as guided by the
Central Pollution Control Board (CPCB) is given in Table 1.
Table 1 Inspection Frequency for Red, Orange and Green category Industries
Type Large Medium Small
Red Once every 3 months Once every 3 months Once a year
Orange Once a year Once a year Once in 3 years
Green Once in 2 years Once in 2 years Once in 5 years
For AP, assuming roughly 50% of the Red and Orange category industries are large, and
100% of the green category industries are of small scale, then the total inspection
requirement as per CPCB guidelines comes to approx. 10,700/year. Additional inspections
could be those against complaints received by SPCB, inspection carried out under court
directives etc. Adding these inspections, the total number of inspections requirement as per
CPCB guidelines could be close to 12,000/year for APPCB. This effort amounts to roughly 60
inspections/day (assuming effectively 200 working days in a year)!
The number of inspections conducted by the APPCB between 2003 and 2006 is approx.
24,565, or roughly 8,200 per year3. As per Centre of Science and Environment’s report “Turn
Around: Reform Agenda for Indian Regulators”(2009)4, Gujarat Pollution Control Board
(GPCB) inspects Red category industries (irrespective of size or scale) on a monthly basis.
The Orange category industries are inspected every six months and Green category
industries are inspected annually. This inspection frequency is higher than the one
prescribed by CPCB. If APPCB follows GPCB’s inspection frequency, then roughly 46060
inspections will be needed to be carried out over the year (or roughly 230 inspection/day)!
See Figure 1.
3 “Environmental Compliance and Enforcement in India”, OECD Report (2006), 4 Please refer to www.old.cseindia.org/regulators_report.pdf (accessed on 16-10-2012)
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Figure 1 Inspection Load for Different Monitoring Frequencies
APPCB has 88 technical staff out of a total strength of 3552. For 60 inspections to be carried
out each day (per CPCB norms), at least 70% of the technical staff will need to be deployed
on a dedicated basis only for inspections! For heightened inspection frequency like the one
practiced by GPCB, approximately 230 inspections will have to be carried out each day. This
would mean that the staff strength has to be increased to 250! Since new staff positions are
not possible and outsourcing may not be an option given the sensitivity around inspection,
further prioritization of industries is necessary. This scheme for prioritization should be
developed such that:
― It uses presently collected / available data to the extent possible with least
additional data collection effort to SPCB
― It provides an insight and focus on the nature and potential reason for non-
compliance to take regulatory and/or policy planning related actions
― It helps in recommending Cleaner Production (CP) related measures so as to
improve competitiveness of the industry
C. Development of Prioritization Index This report proposes a Prioritization Index (PI) to help APPCB to prioritize industries for
taking action related to compliance. PI can help ECAC towards playing a facilitator role for
improving competitiveness such as implementation of CP measures. PI is ‘measured’ based
on
8200
12000
46060
41
60
230
0
50
100
150
200
250
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
Inspection by APPCB in 2006 Inspection by CPCB norms Inspections if carried out at
GPCB norms
No
s. o
f In
spect
ion
/d
ay
No
s. o
f In
spect
ion
s/Y
ear
Nos. of Inspection/ year
Nos. of Inspection/day
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― Industry’s intrinsic characteristics like type, scale and location;
― Industry’s compliance with emission/discharge standards
― Legal action taken by APPCB
― Proactive measure taken by the industry such as Environmental Management
Systems., CP measures etc.
PI essentially follows a Pressure –State-Response (PSR) Framework. An introduction to the
PSR framework is provided in Box 2 and Figure 2.
PI is essentially built on four components R1, R2, R3 and R4. R1 is the Pressure variable and
R2 is the State variable. R3 denotes the reactive response by the regulators and R4 denotes
the proactive response by the Industries. See Figure 3. It is imperative, however, to
understand the relationship between R1, R2, R3 and R4 before constructing the structure of
PI. This relationship is described as below:
― R1 for an industry is stable over a period of time; since size, location and type
of industry is already determined.
― Industry’s environmental performance (determined by R2) is however
dynamic and is subject to external pressures (R3 – corrective action imposed
by State Pollution Control Boards) and internal pressures (R4 – industry’s
own initiatives guiding towards compliance).
― Both R3 and R4 are antagonistically linked to R2, i.e. when either internal or
external pressure builds up they tend to improve industry’s environmental
compliance. Thus as R3 and R4 increases, R2 is expected to decreases.
Based on above, PI is proposed as follows:
The scheme to compute R1, R2, R3 and R4 is described below.
i. Calculation of R1: R1 is a composite of three factors as given below.
― Type of industry (see sec. i) leading to Score A
― Scale of industry (see sec. ii) leading to Score B
― Location of industry (see sec. iii) leading to Score C
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Box 2 Pressure-State-Response Framework
The PSR Framework is a trilobe model where a certain external stimulation may lead to development of “Pressure”, which disrupts the natural state equilibrium or the baseline condition. In response to change in State, a “Response” is elicited which attempts to restore the system back into equilibrium. Response could be Proactive or Reactive. (See Figure 2)
Figure 2 The Pressure-State-Response (PSR) Model
An application of the PSR framework to industrial pollution management is elaborated in Figure 3.
Figure 3 Application of PSR Framework in Industrial Pollution Management
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i. Type of Industry Score A Under the ambit of the Environmental Protection Act (EPA, 1986) the industries are
categorized into three types as Red, Orange and Green, based on their relative
polluting potential. Seventeen categories of industries have been identified by CPCB
as highly polluting (see http://www.cpcb.nic.in/faq2.php). They have been termed
as ‘Red 17’ or ‘R17’. However, the red category includes industries other than these
17 categories5. These industries are considered significantly polluting (but with lesser
intensity than the R17 industries) and are termed as Red 95 or ‘R95’ category. The
orange and green category industries are relatively less polluting, and in that specific
order.
Accordingly the industries could be scored on the scale of 1-10, where score 1 refer to
least (green) and score 10 refers to most environmentally harmful (R17) type of
industries. Table 2 provides the rule base for calculating Score A.
Table 2 Rule Base for Calculation of Score A under R1
Industry Type Pollution Potential Score A
Red – R176 Very High 10
Red – R957 High 8
Orange8 Medium 5
Green9 Low 1
Thus, based on data on industry type, Score A could be assigned.
ii. Scale of Industry Score B Industries can be categorized based on scale of operation depending on the following
aspects:
― Plant area
― Production capacity
― Electricity output (for power plants)
― Capital investment (in plant and machinery)
5 Please refer to http://www.appcb.ap.nic.in/cm/red%20category.htm for a list of 101 types of red category industries in AP. 6 R17: group of 17 categories of highly polluting industries categorized by CPCB (see above link) 7 R95: group of RED category industries other than R17 group (see above link) 8 See http://www.appcb.ap.nic.in/cm/orange%20category.htm for a list of 55 types of orange category industries in AP. 9 See http://www.appcb.ap.nic.in/cm/green%20category.htm for a list of 70 types of green category industries in AP.
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Among above, to reflect the scale of the industry, capital investment could serve as a
surrogate variable. Table 3 gives the rule base for calculating Score B based on
capital investment. This rule base follows the definition provided in Micro, Small &
Medium Enterprises Development (MSMED) Act, 200610.
Table 3 Rule Base for Calculation of Score B under R1
Industry Category Capital Investment (in INR) Score B
Small <50 million 10
Medium >50 but <100 million 7
Large >100 but <1000 million 3
Very Large > 1000 million 1
Thus, based on data on capital investment, Score B could be assigned.
iii. Location of Industry Score C Following aspects may be looked at while examining the location of the industry:
― Whether the industry is located in a cluster of similar Red category industries
― Whether located in Critically Polluted Area (CPA) as notified by CPCB11
― Proximity to Sensitive Regions like:
Protected Areas (PAs)12
Notified eco-sensitive areas13
Sensitive coastal areas14
Interstate boundaries
Other sensitive areas as declared by Govt. of AP15
Score C could be thus arrived at by combining the location aspects and proximity to
SR. Score C will therefore be as below:
10 http://dcmsme.gov.in/ssiindia/defination_msme.htm accessed on 03-10-2012 11 See http://www.cpcb.nic.in/faq1.php for a list of critically polluted areas 12 A list of Protected Areas (PA) is provided in http://www.wiienvis.nic.in/Database/Andhra_Pradesh_7817.aspx 13 A list of notified eco-sensitive areas is provided in
http://assets.wwfindia.org/downloads/indias_notified_ecologicallysensitive_areas.pdf. Also check out CPCB website (www.cpcb.nic.in) and MoEF website (www.envfor.nic.in). 14 Refer to
http://www.indiancoastguard.nic.in/Indiancoastguard/NOSDCP/Marine%20Environment%20Security/Ecosensitive%20areas.pdf 15 See http://www.appcb.ap.nic.in/faq/index_gos.htm for a list of banned area
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Where,
― Score C1 is based on whether the industry is located in a densely populated
district and /or a district with high relatively higher density of Red category
industries and
― Score C2 is based on proximity of industry to SR.
Table 4 provides statistics for AP’s Districts on population, area and number of Red
category industries. This data can be processed to calculate population and industrial
densities for every District in AP. A Low, Moderate and High rating can be applied to this
processed data using a quartile function. In the quartile function, any value lying beyond the
third quartile (Q3 or 75% percentile) may be classified as ‘High’, between the Q1 and Q3 as
‘Moderate’ and less than Q1 as ‘Low’. In this way, each District in AP could be rated as
High, Moderate or Low based on population and industrial densities. District of East
Godavari (see Table 4) for example, is rated as High on the basis of population density and
Moderate on the basis of industrial density. A Composite rating could be arrived at by
assigning higher of the two ratings. Thus for East Godavari District, the composite rating
will be High. Table 5 provides the rule base to assign Score C1 based on Composite ratings
arrived at in Table 4.
To reflect the proximity of industry to SR, Score C2 may be computed. Table 6 give the rule
base for same that is based on radial distance.
Table 4 Rating of AP Districts based on Population & Industrial Densities16
District Population (2001)
Area (km²)
Density (person per sq. km)
Nos. of Red Cat. Industries
Normalized Density of Red Cat. Ind. (ind./km2)
Pop. Density Rating
Ind. Density Rating
Compo-site Rating
Adilabad 2479347 16105 154 43 0.42 L L L
Anantapur 3639304 19130 190 54 0.42 L L L
Chittoor 3735202 15152 247 132 1.26 M M M
East Godavari 4872622 10807 451 137 1.82 H M H
Guntur 4405521 11391 387 175 2.10 H H H
Hyderabad 3686460 217 16988 90 58.12 EH EH EH
Kadapa district 2573481 15359 168 48 0.42 L L L
Karimnagar 3477079 11823 294 53 0.56 M M M
Khammam 2565412 16029 160 42 0.42 L L M
Krishna 4218416 8727 483 184 2.94 H H H
Kurnool 3512266 17658 199 108 0.84 M M M
Mahbubnagar 3506876 18432 190 86 0.70 L M M
Medak 2662296 9699 274 403 5.88 M H H
Nalgonda 3238449 14240 227 157 1.54 M M M
Nellore 2659661 13076 203 86 0.98 M M M
16 http://en.wikipedia.org/wiki/List_of_districts_of_India (accessed on 11-10-12).
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Nizamabad 2342803 7956 294 18 0.28 M L M
Prakasam 3054941 17626 173 32 0.28 L L L
Ranga Reddy 3506670 7493 468 780 14.57 H H H
Srikakulam 2528491 5837 433 35 0.84 H M H
Vishakhapatnam 3789823 11161 340 169 2.10 M H H
Vizianagaram 2245103 6539 343 55 1.12 M M M
Warangal 3231174 12846 252 44 0.42 M L M
West Godavari 3796144 7742 490 109 1.96 H H H
Note: L = Low, M = Moderate, H= High and EH = Extremely High
Table 5 Rule Base for Calculation of Score C1
Location of Industries Score C1
Located in Low (L) Composite rating Districts 1
Located in Moderate (M) Composite rating Districts 2
Located in High (H) Composite rating Districts 3
Located in Extremely High (EH) Composite rating Districts 5
Table 6 Rule Base for Calculation of Score C2
Radial distance of industry from nearest SR Score C2
< 1km 5
>1 but < 5 km 3
> 5 km but < 10 km 2
>10 km 1
Total score C under R1 is addition of C1 and C2 as:
Score C could thus vary between 1 and 10.
iv. Overall Calculation of R1 R1 can be calculated by multiplying Scores A, B, and C as:
A multiplicative function is chosen to reflect the impact factor, lend a heightened
focus and sensitivity towards compliance.
As maximum values of Scores A, B and C will be 10 each, R1 will vary between 0.01
and 10. Higher the value of R1, more focus should be given to inspection and
monitoring of the industry.
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ii. Calculation of R2 R2 corresponds to the State aspect of the PSR framework. R2 focuses on compliance
with applicable standards. For the present development of PI, compliance is limited
to effluent discharge and air emissions.
Upto four parameters have been identified as critical parameters for each category of
polluting industry. The parameters have been identified based on prescriptions by
CPCB and where not available, guidelines provided by International Finance
Corporation (IFC)17 have been used (see cells marked by Gray). Table 7 and Table 8
provide such a compilation of 17 Highly Polluting Industries.
APPCB may develop such a list of priority parameters for industries other than HPIs.
Till then parameters listed under “Other” category (see Table 7 and Table 8) may be
followed.
Table 7 Recommended Parameters for Checking Compliance for 17 Categories Highly Polluting Industries- Water Pollutants
Industry Parameter 1 (
) Parameter 2 (
) Parameter 3 (
) Parameter 4 (
)
Aluminium pH TSS COD Fluoride
Cement pH TSS Temperature
Chlor-Alkali pH Mercury COD AOX
Copper pH TSS Cu(II) Fe(III)
Distillery pH TSS BOD Odour
Dyes & DI TSS Cr(III+VI) Chloride Sulphate
Fertilizer TKN NH4-N Phosphate TSS
Iron & Steel TSS COD NH4-N Phenol
Oil Refineries TSS BOD Oil & Grease Phenol
Pesticides BOD Bioassay Cyanide Arsenic
Petrochemicals COD Sulphide Flouride Phenols
Pharmaceuticals TSS Bioassay BOD Mercury
Pulp & Paper ( > 30 TPD)
pH TSS COD AOX
Sugar TSS BOD COD
Tannery pH TSS Cr(VI) BOD
Thermal Power pH TSS Cr(III+VI) Phosphate
Zinc pH TSS Zn (II) Sulphate
Others pH TSS BOD
Note: AOX – Aromatic Organic Halide; BOD – Biochemical Oxygen Demand, COD – Chemical
Oxygen Demand; Cr – Chromium, tri (III) and hexa(VI) valent; Fe – Iron ion , bi(II) and tri (III)
valent; (VI); pH – potential hydrogen; TSS – Total Suspended Solids; Zn – zinc bi (II) valent.
17 Visit http://www1.ifc.org/wps/wcm/connect/Topics_Ext_Content/IFC_External_Corporate_Site/IFC+Sustainability/Sustainability+Framework/Environmental,+Health,+and+Safety+Guidelines/
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Table 8 Recommended Parameters or Checking Compliance for 17 Categories Highly Polluting Industries – Air Pollutants
Industry Type Parameter 1 (
) Parameter 2 (
) Parameter 3 (
) Parameter 4 (
)
Aluminium PM CO Fluoride PFC
Cement PM NOx Tot. Heavy Metals
HCl
Chlor-Alkali Chlorine Mercury HCl
Copper PM CO SO2 NOx
Distillery Odour
Dyes & DI VOC
Fertilizer PM Fluoride NOx NH3
Iron & Steel PM SO2 NOx CO
Oil Refineries SO2 NH3 VOCs Aldehyde
Pesticides HCl Chloride H2S P2O5
Petrochemicals SO2 NOx HCl
Pharmaceuticals VOC PM Odour Benzene
Pulp & Paper ( > 30 TPD)
PM H2S
Sugar PM Odour
Tannery VOC H2S Odour
Thermal Power PM SO2 NOx CO2
Zinc SO2 NOx PM VOC
Others PM SO2 NOx
Note: CO – Carbon Monoxide; CO2 – Carbon Dioxide; HCl – Hydrogen Chloride; H2S –
Hydrogen Sulphide; PM – Particulate Matter, P2O5 – phosphorous pentoxide, PFC –
Perflourocarbons, NOx – nitrogen oxides, NH3 – Ammonia;
Annexure B provides values for parameters recommended in Table 7 and Table 8.
The data on effluent/emission concentrations for an industry could be made
available from (a) monitoring and inspections by APPCB (b) from results submitted
by industry in Environmental Statement (Form V) and routine monitoring reports (c)
results of third party monitoring. This data along with Tables 7, 8 and Annexure B
will help assess exceedance over the standard. Exceedance is defined as:
X can thus take a value between 0 and ∞, however for all practical purpose it may
range between 0 and 3, i.e. concentration going up to 3 times of the standards.
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Score D could be calculated for each prescribed parameter based on exceedance, ‘x’.
A rule base to compute Score D is as below:
This rule base is based on the following assumptions:
― Score D is scaled between 1 and 10
― One third (33.33% of 10 or 3.33) of Score D is allocated for compliant
industries.
― A linear relationship is assumed to assign score D in the case compliance
zone, i.e. when exceedance factor (x) < 1.
― When exceedance is equal to 1 or crosses 1 (but less than 1.733) the scoring
function takes a quadratic form to emphasize higher impact due to non-
compliance.
― Beyond an exceedance value of approx. 1.733, the highest possible score of 10
is attained for D. Beyond exccedance factor of 1.733, score for D is kept
constant as 10 indicating irreversible damage to the environment.
The above scoring scheme is depicted in Figure 418.
Figure 4 Scoring Scheme based on Exceedance over Standard
Based on this Scheme, Score Di can be arrived at for any parameter Pi
Now if D1, D2, D3 and D4 are Scores for parameters P1, P2, P3 and P4 (as per Table 7
and Table 8), for water/air pollutants then Rwater and Rair can be calculated as: 18 This scoring system may not hold for two parameters, viz. pH and temperature as for both these parameters, standard are
provided as range. For these two parameters, score 0 is assigned if compliant and 5 is assigned if non-compliant.
0
2
4
6
8
10
12
0 1 2 3 4 5 6
sco
re D
Exceedance1.73
3.33 Zone of
Compliance
Zon
e of
Non
-
Com
pli
ance
Zone of Non-Compliance and
Irreversible Damage
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A maximum operator (MAX) function is used to combine Scores across parameters
(D1,D2,D3,D4). MAX function has advantage of being non-eclipsing and unambiguous
as against additive or multiplicative functions. US EPA Pollution Standards Index
(PSI) also uses MAX function to combine scores of air quality parameters19.
Finally, R2 can be calculated as:
BOX 3 explains calculations for R2 with examples:
BOX 3 EXAMPLES OF R2 CALCULATIONS
Example 1: Monitoring of a large (>500 Mt/day capacity) and old (constructed in 1995) cement plant in Rangareddy district in A.P. revealed the following Air & Effluent characteristics:
Parameter Results Parameter Parameter
PM 320 mg/Nm3 BOD 100 mg/L
COD 280 mg/L
TSS 400 mg/L
Rair calculation:
Parameter Results CPCB standards Exceedance value (x) D value*
PM 320 mg/L 250 mg/L 320/250 = 1.28 5.46
MAX (5.46) = 5.46
Note: * Since Exceedance (x) is >1 but <1.73; D = 3.33*(x)2 = 3.33*(1.28)2 = 5.46 Rwater calculation:
Since there are no effluent discharge limits for cement plants, General effluent Discharge Standard will be used for BOD, COD or TSS. The calculation is shown as below:
Parameter Results CPCB standards$ Exceedance value (x) D value*
BOD 100 mg/L 30 mg/L 100/30 = 3.33 10
COD 280 mg/L 250 mg/L 280/250 = 1.12 4.177
TSS 400 mg/L 100 mg/L 400/100 = 4 10
MAX (10,4.177,10) = 10
Note: $ Effluent was discharged into inland surface water body * Since Exceedance (x) is >1.73; D = 10 Rwater = 10 R2 for the Cement Plant= (Rair + Rwater)/2 = (5.46+10)/2 = 7.73
Example 2 A large thermal power plant in East Goadvari district (660 MW x 3) (established in 2004) has
19 Ott, Wayne R. Environmental Indices. Ann Arbour. 1977
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the following Air and Effluent results.
Parameter Results Parameter Results
PM 120 mg/Nm3 TSS 2000 mg/L
Cr(III+VI) 1.35 mg/L
PO43- 3.5 mg/L
Rair Calculation:
Parameter Results CPCB standards Exceedance value (x) D value*
PM 190 mg/L 150 mg/L 120/150 = 0.8 2.66
Max (2.66) = 2.66
Note: * Since Exceedance (x) is >1 but <1.73 hence D = 3.33*(x)= 3.33*(0.8) = 2.66 Rwater Calculation:
Parameter Results CPCB standards Exceedance value (x) D value*
TSS 2000 mg/L 100 mg/L 2000/100 = 20 10
Cr(III+VI) 1.35 mg/L 0.2 mg/L 1.35/0.2 = 6.75 10
PO43- 3.5 mg/L 5.0 mg/L 3.5/5 = 0.7 2.33
Max(10,10,2.33) =10
Note: * Since Exceedance (x) for TSS and Cr is >1.73; P = 10,F or PO43- however x is less than 1 and hence P = 3.33*x Rwater = 10 R2 for the Thermal Power Plant = (Rair+Rwater)/2 = (2.66+10)/2 = 6.33
iii. Calculation of R3 R3 is a response variable, representing the actions initiated by the SPCB on the
industry in question. These actions are essentially reactive and cover directions
issued, closure orders issued or litigations filed in a court of law. Higher is the
number of legal actions against the industry, higher will be its R3 score.
Please refer to Table 9 for calculation of R3. R3 will range between 1 and 10.
Table 9 Rule Base for Calculation of R3
Administrative Response within last three years
# Response Never Once only
Multiple Times
1 Nos. of Show Cause Notices issued in last 3 years 1 2 3
2 Nos. of Closure Orders issued in last 3 years 1 2 3
3 Nos. of Litigations on environmental ground against industry in last 3 years
1 3 4
Total Maximum 3 7 10
Information on actions taken against industry (like show-cause notices, directions
issues, closure order or litigations) can be sourced from APPCB Legal Cell.
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iv. Calculation of R4 R4 is linked to the Proactive Response of the industry.
Score R4 reflects the effort taken by the industry to go beyond compliance. Table 10
show the Rule Bases for calculating R4.
Table 10 Rule Base for Calculation of R4
# Questions Answers
Positive Points Negative Points
1 Implemented Major Cleaner Production Projects in last 3 years?
Y 2 N 0
2 Presence of certified EMS (ISO 14001)? Y 2 N 0
3 In house Environment Management Cell/ personnel present?
Y 2 N 1
4 3rd Party Environmental Audit conducted at least once in last 3 years?
Y 2 N 0
5 Part of any Supply Chain which imposes its own Environmental & Social Code of Conduct?
Y 1 N 0
6 Use of Renewable Energy of the order of 5% of total Energy Consumption?
Y 1 N 0
Total Maximum 10
R4 may range from 1 to 10, with Score 1 denoting no effort exhibited by the industry
towards ensuring proactive compliance, and Score of 10 denoting maximum efforts
taken.
The data required for calculating R4 (as shown in Table 10) may not be readily
available from routine data source available with APPCB. There may be a need to
amend the existing data format to solicit the above information. A proposal to this
effect is described in Table 14.
v. Calculation of PI As outlined in the earlier section, calculation of PI is proposed as follows:
As R1, R2, R3 and R4 vary between 1 and 10, the maximum value of PI is 100 and
minimum value is 0.01.
Higher the PI, more critical is the industry for interventions. Some use of PI in
compliance tracking and management is illustrated in Section D below.
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D. Application and Use of PI PI can be used as a management tool. It can help in
― Set targets
― Prioritize inspections
― Plan interventions for enforcement as well as facilitation
― Track effectiveness of interventions
The relationship between the four aspects, viz. Prioritization of Industries based on
PI Score, Actioning on non-compliant industries by APPCB and ECAC, Tracking PI
score of industries over time and Target Setting to improve PI score of industries is
illustrated in Figure 5 below. The cycle resembles the Plan-Do-Check-Act Cycle.
Figure 5 Relation between the Four Potential Uses of PI
In order to "test" applicability of PI for above, 40 reports on Environmental
Statements were obtained from APPCB. These reports were used to create 10
motivational examples of industries. Suitable assumptions were made where data
was not available. Annexure C shows calculations of R1, R2, R3 and R4 and the PI for
the 10 industries on this basis.
i. Target Setting APPCB may use PI as a target. As an example, it can set a target of say 30% reduction
in PI for all industries above 70 and 20% reduction in PI between 50 to 70 etc.
Targets may be set up for an industry sector as well. For example, APPCB may set up
a target of 30% PI reduction for cement industries.
Prioritization
Actioning
Tracking Performance
Target Setting
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Targets could be set up for a district. A district may have a target to reduce PI below
60 for all industries by 2014 and below 50 by 2016.
ii. Prioritization for Inspections Inspections may be prioritized based on PI. When number of industries is large and
resources (like person-power, finance or time) are limited, prioritization of inspection
can help in attaining compliance. Table 11 shows list of 10 industries on sorting over
PI. If out of 10 only 5 industries are to be inspected, then IND2, IND6, IND1, IND7
and IND8 may be taken up based on their high PI score.
Table 11 Prioritization of Industries and Proposed Actions for APPCB
Code Industry type/scale & location R3*R4 R1*R2 PI Proposed Actions for APPCB
IND2 Mid. Cement near Hyderabad 4.00 83.33 20.83
Physical inspection of industry, monitoring of air and effluent discharges, issue Show Cause Notices (SCN) as deemed necessary
IND6 Mid. Pharma in Srikakulam 3.00 40.89 13.63
Physical inspection of industry, monitoring of air and effluent discharges, issue SCN, as deemed necessary
IND1 Small Pharma in Nellore 20.00 77.00 3.85 Physical inspection of industry, monitoring of air and effluent discharges, issue SCN, as deemed necessary
IND7 Mid. Fertilizer in Anantpur 28.00 70.00 2.50 Physical inspection of industry, evaluation of effectiveness of pollution control infrastructure
IND8 Small Pulp & Paper plant in Kurnool
27.00 50.84 1.88 Physical inspection of industry, evaluation of effectiveness of pollution control infrastructure
IND3 Large Pharma in Vizag 24.00 43.37 1.81 Physical inspection of industry, evaluation of effectiveness of pollution control infrastructure
IND9 Mid. Brewery in East Godavari 18.00 20.06 1.11 Physical inspection of industry, evaluation of effectiveness of pollution control infrastructure
IND4 Large Iron & Steel in Karimnagar
45.00 37.99 0.84 No immediate action necessary
IND10 Large sugar in Srikakulam 81.00 63.33 0.78 No immediate action necessary
IND5 Large Ceramic Ind. in Ananthpur
63.00 7.90 0.13 No immediate action necessary
Inspections at remaining three industries may be differed until additional resources
are available. PI thus helps in a more focused enforcement within the constraint of
human resources.
iii. Taking Appropriate Action It may be interesting to plot PI, R1 x R2 (indicating compliance related risk) vs. R3 x
R4 (indicating actions taken - reactive as well as proactive - for mitigating the risk). This
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plot could be shown in the form of quadrants based on R1 x R2 and R3 x R4. Please
refer to Figure 6. Following observations could be made.
― Industries on the top left hand corner (red quadrant in Figure 6) have higher
R1 x R2 scores indicating higher risk towards compliance. For these
industries, monitoring and inspections should be increased to reduce risk of
non-compliance. Efforts on building capacities and understanding of
compliance requirements is also necessary.
― Industries in the top right hand corner (violet quadrant in Figure 6) have
higher risk of becoming non compliant, however these industries have higher
internal capacity and/or presence of regulatory actions for ensuring
compliance. Moderate but sustained efforts of inspections and promotion of
CP and EMS should be a good strategy.
― Industries in the bottom left hand corner (blue quadrant in Figure 6) have
relatively low risk of becoming non-compliant. However their internal
capacity to mitigate this risk could be low. At these industries, mre their
internal capacity should be increased.
― Industries in the bottom right hand corner (green quadrant in Figure 6) have
lower risk of becoming non-compliant; vis-a-vis they have higher internal
capacity and external supervision to manage this risk. Thus the chances of
these industries becoming non-compliant in near future are low. Hence, no
immediate actions may be warranted.
Figure 6 A Conceptual Framework of Actioning based on R1 x R2 vs. R3 x R4
Score
R1*R2 is HIGH and R3*R4 is LOW
• Indicates high tendency to become non compliant
• No or very low internal capacity (R4) and external (R3) action for becoming compliant
• Major action from APPCB, constant vigil required to enhance environmental compliance
R1&R2 is HIGH and R3*R4 is HIGH
• Indicates high tendency to become non-complaint
• High internal capacity (R4) and high level of enforcement (R3) . Problems could be on the side of management , technology
• ECAC should do Internal capacity building, assist in technology transfer etc.
R1 * R2 LOW and R3 * R4 LOW
• Indicates a relatively lower tendency to become non-compliant
• Internal capacity (R4) and external actions i.e. Level of enforcement (R3) low
• Low threat, but can become potentially non-compliant,
• ECAC should propose CP interventions
R1*R2 LOW and R3*R4 HIGH
• Indicates a relatively lower tendency to become non-compliant
• High internal capacity (R4)
• Low threat. Possibly becomes compliant due to heightened internal and/or external pressure. No immediate action required
R3 * R4
R1
* R
2H
IGH
LO
W
LOW HIGH
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Figure 7 shows an illustration of mapping of these 10 industries in four quadrants based on
their R1 x R2 vs. R3 x R4 scores.
Table 12 shows computations of R1*R2 and R3*R4 and PI for the 10 industries (for detailed
calculation please refer to Annexure C). Accordingly, recommended actions for APPCB and
proposed services of ECAC are shown in tandem in Table 12.
Figure 7 Distribution of 10 industries in Quadrants based on R1XR1 vs. R3xR4 Scores
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Table 12 Linking between ECAC’s Services and R1 x R2 vs. R3 x R4 Scores
Code Industry type, scale & location
R1*R2 R3*R4 Quadrant PI Actions to be taken by APPCB (see Table 11)
Proposed Services of ECAC’s
IND1 Small Pharma in Nellore
77.00 20.00 Red 3.85 Physical inspection of industry, monitoring of air and effluent discharges, issue SCN, as deemed necessary
Deciphering Environmental regulations, Conducting Awareness programs, Disseminating environmental information, Conducting Environmental Audits
IND2 Mid. Cement near Hyderabad
83.33 4.00 Red 20.83 Physical inspection of industry, monitoring of air and effluent discharges, issue Show Cause Notices (SCN) as deemed necessary
Deciphering Environmental regulations, Conducting Awareness programs, Disseminating environmental information, Conducting Environmental Audits
IND3 Large Pharma in Vizag
43.37 24.00 Blue 1.81 Physical inspection of industry, evaluation of effectiveness of pollution control infrastructure
Deciphering Environmental regulations, Conducting Awareness programs, Cleaner Production Opportunity Assessment, CP Demonstration Projects
IND4 Large Iron & Steel in Karimnagar
37.99 45.00 Blue 0.84 No immediate action necessary Deciphering Environmental regulations, Conducting Awareness programs, Cleaner Production Opportunity Assessment, CP Demonstration Projects
IND5 Large Ceramic Ind. in Ananthpur
7.90 63.00 Green 0.13 No immediate action necessary Conducting Awareness programs, ISO 14001 implementation support, Providing Foot printing Service on Water, Energy, Carbon etc.
IND6 Mid. Pharma in Srikakulam
40.89 3.00 Blue 13.63 Physical inspection of industry, monitoring of air and effluent discharges, issue SCN, as deemed necessary
Deciphering Environmental regulations, Conducting Awareness programs, Cleaner Production Opportunity Assessment, CP Demonstration Projects
IND7 Mid. Fertilizer in Anantpur
70.00 28.00 Red 2.50 Physical inspection of industry, evaluation of effectiveness of pollution control infrastructure
Deciphering Environmental regulations, Conducting Awareness programs, Disseminating environmental information, Conducting Environmental Audits
IND8 Small Pulp & Paper plant in Kurnool
50.84 27.00 Red 1.88 Physical inspection of industry, evaluation of effectiveness of pollution control infrastructure
Deciphering Environmental regulations, Conducting Awareness programs, Disseminating environmental information, Conducting Environmental Audits
IND9 Mid. Brewery in East Godavari
20.06 18.00 Blue 1.11 Physical inspection of industry, evaluation of effectiveness of pollution control infrastructure
Deciphering Environmental regulations, Conducting Awareness programs, Cleaner Production Opportunity Assessment, CP Demonstration Projects
IND10 Large sugar in Srikakulam
63.33 81.00 Violet 0.78 No immediate action necessary Disseminating environmental information, Capacity Development, Conducting Environmental Audits, ISO 14001 implementation support, Providing Foot printing Service on Water, Energy, Carbon etc.
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iv. Tracking Performance PI can serve as an indicator of Industry’s environmental compliance related
performance. It can help to assess effectiveness of interventions taken by APPCB
and/or ECAC.
Figure 8 shows an illustration of and industry named XYZ Ltd. Red arrows indicate
action taken by APPCB on XYZ Ltd. and green arrows indicate interventions made
by ECAC. It can be seen that PI score of XYZ Ltd. falls over time indicating
effectiveness of joint actions of APPCB and ECAC. This example demonstrates how a
dual approach of enforcement and facilitation can lead to compliance and improved
competiveness. A tracking diagram depicting XYZ Ltd.’s PI score over a period of six
years in reproduced as Figure 8. Such composite action is thus recommended for all
industries above PI of 70.
Figure 8 Use of PI Score to track Industry’s Performance and Effectiveness of
Interventions by APPCB and ECAC
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E. Source of Data for R1, R2, R3 and R4 The data sources for calculation of R1, R2, R3 and R4 are presented below in Table
13. When multiple sources of data are mentioned; the most easily accessible sources
should be considered. Alternatively data from multiple sources could also be used
for the purpose of cross-checking.
The sources of the data for calculation of PI have been identified in Table 13. It could
be seen that approx. 65-70% data for constructing PI could be pooled from existing
sources.
Table 13 Data Sources for Constructing PI
# Data Requirement Source
A R1
A1 Type of Industry - Category Consent to Establish / Consent to Operate
A2 Scale – Capital Investment Consent to Establish / Consent to Operate
A3 Location of Industry Consent to Establish / Consent to Operate
B R2
B1 Parameters related to Air Emission Environmental Statement (Form V)/ Monitoring records of APPCB
B2 Parameters related to Effluent Environmental Statement (Form V)/ Monitoring records of APPCB
B3 Industry specific Standards Environmental (Protection) Rules/ Standards developed by APPCB mentioned in CTE/CTO
C R3
C1 Show cause notices issued in last 3 years APPCB’s Legal Cell
C2 Closure Orders issued in last 3 years APPCB’s Legal Cell
C3 Nos. of Litigations issued in last 3 years APPCB’s Legal Cell
D R4
D1 Implemented Major Cleaner Production Projects in last 3 years?
No sources in present APPCB documentation
D2 Presence of certified EMS (ISO 14001)? No sources in present APPCB documentation
D3 In house Environment Management Cell/ personnel present?
No sources in present APPCB documentation
D4 3rd Party Environmental Audit conducted at least once in last 3 years?
No sources in present APPCB documentation
D5 Part of any Supply Chain which imposes its own Environmental & Social Code of Conduct?
No sources in present APPCB documentation
D6 Use of Renewable Energy of the order of 5% of total Energy Consumption?
No sources in present APPCB documentation
Note: CTE = Consent to Establish and CTO = Consent to Operate
Table 13 shows that for calculations of R4, additional data like existence of ISO 14001
certification or existence of separate internal environmental management cell is
required. These may not available readily with APPCB. There is a need to amend the
existing formats like CTO applications / Form V to capture this information. Please
refer to Table 14.
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Table 14 Recommended Sources of Information for R4
# Questions Possible Sources of Additional Data
D1 Implemented Major Cleaner Production Projects in last 3 years?
Consent to Operate form; Environmental Statement form
D2 Presence of certified EMS (ISO 14001)? Consent to Operate form; Environmental Statement form
D3 In house Environment Management Cell/ personnel present?
Environmental Statement form (Form V)
D4 3rd Party Environmental Audit conducted at least once in last 3 years?
Environmental Statement form (Form V)
D5 Part of any Supply Chain which imposes its own Environmental & Social Code of Conduct?
Environmental Statement form (Form V)
D6 Use of Renewable Energy of the order of 5% of total Energy Consumption?
Environmental Statement form (Form V)
F. Conclusions Prioritization Index (PI) is a useful concept to SPCBs for managing compliance
within their constraints of resources.
PI makes use of the Pressure-State-Response (PSR) structure based on 4 key
parameters R1, R2, R3 and R4. R1 denotes the Pressure, R2 the State, R3 the reactive
response from SPCB and R4 represents the proactive initiatives taken by the
industry.
PI is computed as (R1*R2)/(R3*R4). PI varies between 0.01 and 100.
Higher is the value of PI, more is the importance to be assigned to the industry for
the purposes of intervention. PI can be used as a basis to plan inspection strategy.
Interventions at the industries could be related to inspections and enforcement
and/or process improvement and capacity building. A "quadrant" analyses based on
(R1*R2) vs. (R3*R4) provides a framework for guidance towards such actions.
PI can be used for target setting. Targets for PI reduction could be set for specific
industries, districts and industrial sectors.
Actions taken for reduction of PI can be tracked for their effectiveness. Generally, a
combination of enforcement and facilitation (like CP and EMS) should be used for
the management of PI.
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G. Recommendations The recommendations are as below:
i. Development of MIS for PI Most of the data required for calculation of PI is available with APPCB. Data that is
not currently available will need to be pooled from other sources or by expanding
the existing data formats.
Presently there is no functional database and/or MIS system in APPCB. Information
like consents, directions and closure information are stored on hard copies (i.e. on
paper) and handled manually. This may make pooling data for calculation of PI
difficult.
In order to address this difficulty, APPCB may develop a MIS where consent
information, Environmental Statements (Form V) etc. will be structured in an
electronic database. A software system could be developed to automatically pool the
data to calculate PI. Tools/processes such as sorting, quadrant presentation and
tracking and reporting could be built in this system for effective use of PI.
ii. Resource Consumption Index : Expanding PI Meeting of environmental compliance alone should not be considered as the sole
parameter for evaluating environmental performance of the industries. Aspects like
specific resource consumption (e.g. water or energy consumption) should also be
factored.
Indian environmental regulations do not stress on the aspect of resource
consumption. Neither there are India-specific benchmarks for industries on resource
consumption.
It is important to consider resource consumption because (a) resources especially
fresh water and energy are limited and depleting rapidly; (b) the central theme for
ECAC is also to promote Competitiveness in Industries through Cleaner Production
(CP).
One way of ‘measuring’ Industry’s performance is to compare its resource and waste
generation related performance against established benchmarks20. In order to
measure the performance of selected types of industries the benchmarks developed
by various authorities across the globe. The sources of such benchmarks are
described below:
20 Benchmarking is the process of comparing performance against established performance parameters, so as to identify areas for improvement
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― Industry Specific Standards proposed by Central Pollution Control Boards
(CPCB) (1988 onwards)21
― CPCB’s Charter On Corporate Responsibility For Environmental Protection
(March, 2003)22
― International Financial Corporation(IFC) Environmental, HeaLh and Safety
Guidelines for various industrial sectors (2006-2008) 23
― Assessment of Sources of Air, Water & Land Pollution; Part I : Rapid
Inventory Techniques in Environmental pollution by Alexander P.
Economopoulos (WHO, 1993) 24
― Europa : Best Available Technology Different Research or Manufacturing
Associations for the specific sectors (2001-2011)25
― UNIDO Global Industrial Energy Efficiency Benchmarking (2010)26
ECAC may build on the above knowledge bases to establish resource consumption
benchmarks for some of the priority industrial sectors. Once these benchmarks are
established, steps to assist industries to move towards the benchmarks could be taken. R2
for instance could be expanded to include "compliance with applicable benchmarks" for
zeroing on to industries that are potentially non-compliant and at the same time are
resources intensive. Such an expanded definition of PI will not only help to achieve
environmental compliance but also to improve competitiveness of the industry.
21 http://cpcb.nic.in/Industry_Specific_Standards.php & http://cpcb.nic.in/GeneralStandards.pdf 22 http://cpcb.nic.in/crep.php 23http://www1.ifc.org/wps/wcm/connect/Topics_Ext_Content/IFC_External_Corporate_Site/IFC+Sustainability/Sustainability+Framework/Environmental,+Health,+and+Safety+Guidelines/ 24 http://whqlibdoc.who.int/hq/1993/WHO_PEP_GETNET_93.1-A.pdf 25 http://eippcb.jrc.es/reference/ 26http://www.unido.org/fileadmin/user_media/Services/Energy_and_Climate_Change/Energy_Efficiency/Benchmarking_%20Energy_%20Policy_Tool.pdf
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ANNEXURES
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ANNEXURE A
DISTRICT WISE DISTRIBUTION OF RED, ORANGE & GREEN CATEGORY
INDUSTRIES
Table A15 District-wise Classification of Industries in AP (2007)
DISTRICTS Green category
industries
Orange category
industries
Red category
industries
Total industries
Red as %
of Total
Red + Orange as % of Total
Adilabad 1 32 43 76 56.6% 98.7%
Nizamabad 3 95 18 116 24.2% 97.8%
Sangareddy-I, Medak 20 49 181 250 33.8% 94.4%
Sangareddy-II, Medak 24 116 222 362 25.3% 98.0%
Nalgonda 18 114 157 289 27.6% 95.4%
Mehboobnagar 152 78 86 316 23.4% 48.7%
Hyderabad 197 97 90 384 38.7% 97.6%
Ranga Reddy-I 151 147 341 639 20.8% 98.4%
Ranga-Reddy-II 92 235 439 766 27.1% 96.8%
Karimnagar 4 198 53 255 38.6% 86.4%
Warangal 22 147 44 213 38.3% 96.8%
Ananthapur 5 164 54 223 27.2% 51.9%
Kurnool 9 165 108 282 54.3% 93.8%
Chittoor 22 237 132 391 27.8% 95.5%
Kadapa 3 73 48 124 15.5% 97.4%
Krishna 65 228 184 477 17.2% 97.8%
Guntur 29 431 175 635 53.4% 76.4%
Khammam 5 108 42 155 57.3% 88.0%
Nellore 14 209 86 309 72.4% 92.0%
Prakasam 4 150 32 186 61.3% 93.4%
Visakhapatnam 48 210 169 427 10.7% 96.9%
Srikakulam 10 282 35 327 39.6% 88.8%
Vizianagaram 6 91 55 152 36.2% 96.1%
East Godavari 11 394 137 542 20.7% 89.7%
West Godavari 17 274 109 400 27.3% 95.8%
Source: APPCB Annual Report
A graphical representation based on distribution of Red Category Industries is presented
below in Figure 9.
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Figure 9 District-wise concentration on Red Category industries in Andhra Pradesh
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ANNEXURE B
VALUES OF PARAMETERS FOR DISCHARGE / EMISSION
Table A16 Standards for Checking Compliance for 17 Category Highly Polluting Industries – Effluent Generation
Parameter 1 Parameter 2 Parameter 3 Parameter 4
Aluminium pH - 6–9 TSS – 50 mg/L COD - 150 mg/L Fluoride - 20 mg/L
Cement pH - 6-0 TSS – 50 mg/L Temperature – less than 3oC
Chlor-Alkali pH - 5.5- 9.0 Hg – 10,000 L/tonne of caustic
COD - 150 mg/L AOX -0.5 mg/L
Copper pH - 6 -9 TSS - 50 mg/L Cu(II) - 0.5 mg/L Fe(III) - 3.5 mg/L
Distillery pH - 6 – 9 TSS - 50 mg/L BOD - 25 mg/L Odour - Acceptable to boundary residents
Dyes & DI TSS - 100 mg/L
Cr(III+VI) = 2 mg/L
Chloride - 1000 mg/L Sulphate - 1000 mg/L
Fertilizer TKN - 100 mg/L
NH4-N - 50 mg/L Phosphate - 5 mg/L TSS - 100 mg/L
Iron & Steel TSS - 100 mg/L
COD - 250 mg/L NH4-N - 50 mg/L Phenol - 1 mg/L
Oil Refineries TSS - 20 mg/L
BOD - 15 mg/L Oil & Grease - 5 mg/L
Phenol - 0.35 mg/L
Pesticides BOD - 30 mg/L
Bioassay - 90% survival of fish after 96 hours in 100% effluent
CN - 0.2 mg/L As - 0.2 mg/L
Petrochemicals COD - 250 mg/L
Sulphide - 2 mg/L Flouride - 15 mg/L Phenols - 5 mg/L
Pharmaceuticals TSS - 100 mg/L
Bioassay - 90% survival of fish after first 96 hours in 100% effluent
BOD - 100 mg/L Hg - 0.01 mg/L
Pulp & Paper ( > 30 TPD)
pH - 7.0 – 8.5
TSS - 100 mg/L COD - 350 mg/L AOX - 40 mg/l and 2 kg/t (aim for 8 mg/l and 0.4 kg/t for retrofits and for 4 mg/l and 0.2 kg/t for new mills) and 4 mg/l for paper mills
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Sugar TSS - 100 mg/L for disposal on land. 30mg/L for disposal in surface waters.
BOD - 100 mg/L for disposal on land. 30mg/L for disposal in surface waters.
Tannery pH - 6.0 – 9.0
TSS - Inland surface water - 100mg/L, Public sewers - 0, land for irrigation - 200 mg/L, marine waters - 100 mg/L
Cr(VI) - Inland surface water - 0.1 mg/L, Public sewers - 0.2 mg/L, land for irrigation - 0.1 mg/L, marine waters - 1 mg/L
BOD - Inland surface water - 30 mg/L, Public sewers - 350 mg/L, land for irrigation - 100 mg/L, marine waters - 100 mg/L
Thermal Power pH - 6.5 – 8.5
TSS - 100 mg/L in boiler blow downs and ash pond effluent
Cr(III+IV) - 0.2 mg/L for cooling tower blow down
Phosphate - 5 mg/L for cooling tower blow down
Zinc pH - 6–9 TSS - 20 mg/L Zn (II) - 2.0 mg/L
Table A17 Standards for Checking Compliance for 17 Category Highly Polluting Industries – Air Emissions
Industry Type Parameter 1 Parameter 2 Parameter 3 Parameter 4
Aluminum PM - 30 mg/m3 CO - 5 mg/Nm3 Fluoride – 2 mg/Nm3
PFC - 0.1 anode effects / cell / day)
Cement PM - 50 mg/cu. Nm
NOx - 600 mg/ Nm3
Total Heavy Metals27 – 5 mg/Nm3
HCl – 10 mg/Nm3
Chlor-Alkali Cl- 15 mg/Nm3 Hg - 0.2 mg/Nm3
HCl - 35 mg/Nm3
Copper PM - 150 mg/Nm3 CO - 5 mg/Nm3 SO2 - 1000 mg/Nm3
NOx - 100 – 300 mg/Nm3
Distillery Odour - Odours should be acceptable at the plant boundary
Dyes & DI VOC - 20 mg/Nm3
Fertilizer PM - 0.3 kg/ton of NPK fertilizer produced
Fluoride - 0.02 kg/ton of NPK fertilizer produced
NOX - 0.2 kg/ton of NPK fertilizer produced
NH3 - 0.3 kg/ton of NPK fertilizer produced
27 Total Heavy Metals = Arsenic (As), Lead (Pb), Cobalt (Co), Chromium (Cr), Copper (Cu), Manganese (Mn), Nickel (Ni), Vanadium (V), and Antimony (Sb)
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Iron & Steel PM - 150 mg/Nm3 SO2 - 500 mg/m3
NOx - For pelletizing plants: 500 g/t; 250– 750 mg/Nm3; for sintering plants: 750 mg/Nm3
CO – 100 mg/Nm3 (Electric Arc Furnace) 300 mg/Nm3 (coke oven)
Oil Refineries SO2 - 150 mg/Nm3 for sulfur recovery units; 500 mg/Nm3 for other units
NH3 – 15 mg/Nm3
VOCs – 20 mg/Nm3
Aldehyde – 0.5 mg/Nm3 as formaldehyde
Pesticides HCl - 30 mg/Nm3 Cl- 5 mg/Nm3 H2S - 3 mg/Nm3
P2O5 - 10 mg/Nm3
Petrochemicals SO2- 500 mg/Nm3 NOx - 300 mg/Nm3
HCl - 10 mg/Nm3
Pharmaceuticals VOC – 20-150 mg/Nm3
PM - 20 mg/Nm3
Odour - Odours should be acceptable at the plant boundary
Benzene, Vinyl Chloride, Dichloroethane – 1mg/Nm3 each
Pulp & Paper ( > 30 TPD)
PM - 250 mg/Nm3 H2S - 10 mg/Nm3
Sugar PM - 250 mg/Nm3 Odour - Odours should be acceptable at the plant boundary
Tannery VOC -0.6 mg/m3 for formaldehyde
H2S - 10 ppm for 8 hours or 15 ppm for 15 min
Odour - Odours should be acceptable at the plant boundary
Thermal Power PM - 150 mg/m3 (24 hr average), 50 mg/m3 (annual average)
SO2 - 150 mg/m3 (24 hr average), 80 mg/m3 (annual average)
NOx - 150 mg/m3 (24 hr average), 100 mg/m3 (annual average)
CO2 – 756-836 gCO2/kHhr. (Coal based Supercritical) 807-907 gCO2/kWhr (Coal based Sub-critical) 654 -719 gCO2/kWhr. (Integrated Coal gasifier based Combined Cycle) 355 gCO2/kWhr. (advance Gas based Combined Cycle)
Zinc SO2 - 400 mg/Nm3 NOx – 100-300 mg/Nm3
PM - 20 mg/Nm3
VOC – 5-15 mg/Nm3
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ANNEXURE C
CALCULATION OF PI OF 10 INDUSTRIES
APPCB provided EMC 40 Environmental Statements (Form V) across various industrial sectors. From this data, 10 motivational examples were
created for testing PI. Suitable assumptions were made where complete data was not available.
Calculation of R1
Code Industry type/scale & location A B C1 C2 R1
IND1 Small Pharma in Nellore 10 10 2 2 8.0
IND2 Mid. Cement near Hyderabad 10 7 5 3 8.3
IND3 Large Pharma in Vizag 10 3 3 3 6.3
IND4 Large Iron & Steel in Karimnagar 8 3 2 5 6.0
IND5 Large Ceramic Ind. in Ananthpur 5 3 1 1 3.3
IND6 Mid. Pharma in Srikakulam 8 7 3 5 7.7
IND7 Mid. Fertilizer in Ananthpur 10 7 1 3 7.0
IND8 Small Pulp & Paper plant in Kurnool 10 10 2 1 7.7
IND9 Mid. Brewery in East Godavari 10 7 3 1 7.0
IND10 Large sugar in Srikakulam 10 3 3 3 6.3
Calculation of R2 Water
Parameter 1 Parameter 2 Parameter 3
Code Industry type/scale & location Name Level Standard Score Name Level Standard Score Name Level Standard Score
IND1 Small Pharma in Nellore TSS 185 100 10.00 Bioassay 50% 90% 1.85 BOD 250 100 10.00
IND2 Mid. Cement near Hyderabad TSS 200 100 10.00 BOD 75 30 10.00 COD 300 250 4.80
IND3 Large Pharma in Vizag TSS 99 100 3.30 Bioassay 90% 90% 3.33 BOD 200 100 10.00
IND4 Large Iron & Steel in Karimnagar TSS 88 100 2.93 COD 620 250 10.00 NH4-N 100 50 10.00
IND5 Large Ceramic Ind. in Ananthpur COD 80 250 1.07 BOD 15.3 30 1.70 TSS 89 100 2.96
IND6 Mid. Pharma in Srikakulam TSS 229 100 10.00 Bioassay 91% 90% 3.40 BOD 223 100 10.00
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IND7 Mid. Fertilizer in Anantpur TKN 212 100 10.00 NH4-N 8 4 10.00 Cr(tot.) 0.6 2 1.00
IND8 Small Pulp & Paper plant in Kurnool
BOD 61 30 10.00 COD 250 350 2.38 TSS 2000 500 10.00
IND9 Mid. Brewery in East Godavari pH 6.2 5.5-9.5 0.00 TSS 112 100 4.18 BOD 12 30 1.33
IND10 Large sugar in Srikakulam BOD 321 100 10.00 TSS 225 100 10.00
Air Parameter 1 Parameter 2 Parameter 3
Code Industry type/scale & location Name Level Standard Score Name Level Standard Score Name Level Standard Score
IND1 Small Pharma in Nellore PM 250 150 9.25
IND2 Mid. Cement near Hyderabad PM 500 250 10.00
IND3 Large Pharma in Vizag PM 158 150 3.69
IND4 Large Iron & Steel in Karimnagar PM 120 150 2.66 SO2 327 500 2.50 NOx 200 750 0.88
IND5 Large Ceramic Ind. in Ananthpur PM 80 150 1.78 F 0.2 10 0.07
IND6 Mid. Pharma in Srikakulam PM 30 150 0.67
IND7 Mid. Fertilizer in Anantpur PM 300 150 10.00
IND8 Small Pulp & Paper plant in Kurnool PM 245 250 3.26 H2S 8.1 10 2.70
IND9 Mid. Brewery in East Godavari PM 70 150 1.55
IND10 Large sugar in Srikakulam PM 340 150 10.00
R2 Rating
Code Industry type/scale & location Max (Water) Max (Air) R2 Score
IND1 Small Pharma in Nellore 10.00 9.25 9.63
IND2 Mid. Cement near Hyderabad 10.00 10.00 10.00
IND3 Large Pharma in Vizag 10.00 3.69 6.85
IND4 Large Iron & Steel in Karimnagar 10.00 2.66 6.33
IND5 Large Ceramic Ind. in Ananthpur 2.96 1.78 2.37
IND6 Mid. Pharma in Srikakulam 10.00 0.67 5.33
IND7 Mid. Fertilizer in Anantpur 10.00 10.00 10.00
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IND8 Small Pulp & Paper plant in Kurnool 10.00 3.26 6.63
IND9 Mid. Brewery in East Godavari 4.18 1.55 2.87
IND10 Large sugar in Srikakulam 10.00 10.00 10.00
Calculation of R3
Code Industry type/scale & location Nos. of SCN
issued Score 1 Nos. of Closure Orders Score 2 Nos. of Litigations Score 3 R3 Score
IND1 Small Pharma in Nellore M 3 N 0 O 2 5
IND2 Mid. Cement near Hyderabad N 0 O 2 O 2 4
IND3 Large Pharma in Vizag O 1 N 0 O 2 3
IND4 Large Iron & Steel in Karimnagar O 1 O 2 O 2 5
IND5 Large Ceramic Ind. in Ananthpur M 3 N 0 M 4 7
IND6 Mid. Pharma in Srikakulam O 1 N 0 N 0 1
IND7 Mid. Fertilizer in Anantpur M 3 O 2 O 2 7
IND8 Small Pulp & Paper plant in Kurnool M 3 N 0 N 0 3
IND9 Mid. Brewery in East Godavari M 3 N 0 N 0 3
IND10 Large sugar in Srikakulam M 3 O 2 M 4 9
Note: SCN = Show Cause Notice, N = None; O = Once; M= Multiple
Calculation of R4
Code Implemented Major CP in last 3 years?
Score 1
Presence of ISO 14001: 2004
Score 1
In-House Env. Mgt. Cell
Score 2
3rd part environmental
audits
Score 3
Part of Supply Chain
Score 5
Uses Renewable
Energy
Score 6
R4 Score
IND1 No 0 No 0 No 1 Yes 2 Yes 1 No 0 4
IND2 No 0 No 0 No 1 No 0 No 0 No 0 1
IND3 Yes 2 Yes 2 Yes 2 Yes 2 No 0 No 0 8
IND4 Yes 2 Yes 2 Yes 2 Yes 2 No 0 Yes 1 9
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IND5 Yes 2 Yes 2 Yes 2 Yes 2 No 0 Yes 1 9
IND6 No 0 Yes 2 No 1 No 0 No 0 No 0 3
IND7 No 0 No 0 No 1 Yes 2 No 0 Yes 1 4
IND8 Yes 2 Yes 2 Yes 2 Yes 2 No 0 Yes 1 9
IND9 Yes 2 No 0 Yes 2 Yes 2 No 0 No 0 6
IND10 Yes 2 Yes 2 Yes 2 Yes 2 Yes 1 No 0 9
Calculation of PI
Code Industry type/scale & location R1 R2 R3 R4 PI IND1 Small Pharma in Nellore 8.00 9.63 5.00 4.00 3.9
IND2 Mid. Cement near Hyderabad 8.33 10.00 4.00 1.00 20.8
IND3 Large Pharma in Vizag 6.33 6.85 3.00 8.00 1.8
IND4 Large Iron & Steel in Karimnagar 6.00 6.33 5.00 9.00 0.8
IND5 Large Ceramic Ind. in Ananthpur 3.33 2.37 7.00 9.00 0.1
IND6 Mid. Pharma in Srikakulam 7.67 5.33 1.00 3.00 13.6
IND7 Mid. Fertilizer in Anantpur 7.00 10.00 7.00 4.00 2.5
IND8 Small Pulp & Paper plant in Kurnool 7.67 6.63 3.00 9.00 1.9
IND9 Mid. Brewery in East Godavari 7.00 2.87 3.00 6.00 1.1
IND10 Large sugar in Srikakulam 6.33 10.00 9.00 9.00 0.8
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ANNEXURE D
EXAMPLES OF SECTORAL BENCHMARKS FOR THERMAL POWER PLANT
CENTRAL POLLUTION CONTROL BOARD (CPCB)
Emission Guidelines (mg/m3) Effluent Guidelines(mg/L)
PM pH TSS Oil & grease Phosphate Cu Zn Cr (hex) Fe
150 6.5 - 8.5 100 20 5 1 1 0.2(total) 1
CREP GUIDELINES
Emission guidelines
PM (mg/m3)
100
IFC SECTORAL EHS GUIDELINES
Combustion Technology/ Fuel Emission Guidelines(mg/m3)
PM SO2 NOX Excess O2
DA DA DA (%)
Gaseous Fuels
Natural Gas
Reciprocating Engine N/A N/A 200(SI), 400(DF/CI) 15
Combustion Turbine (unit > 50 MWth) N/A N/A 15
Boiler N/A N/A 240 3
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Other Gaseous Fuels
Reciprocating Engine 30 N/A 200(SI, Natural Gas) 400(other)
15
Combustion Turbine 30 Use of 0.5% or less S fuel 15
Boiler 30 400 240 3
Liquid Fuels
Reciprocating Engine Plant > 50MWth to < 300 MWth) 30 0.5% S 400 15
Plant >/= 300 MWth 30 0.2% S 400 15
Combustion Turbine Unit > > 50 MWth 30 Use of 0.5% or less S fuel 15
Boiler Plant >50 MWth to <600 MWth 30 400 200 3
>/=600 MWth 30 200 200 3
Solid Fuels
Reciprocating Engine N/A N/A N/A N/A
Combustion Turbine Unit > > 50 MWth 30 Use of 0.5% or less S fuel 15
Boiler Plant >50 MWth to <600 MWth 30 400 200 6
>/=600 MWth 30 200 6
Effluent Guidelines (all values in mg/L except pH)
pH TSS Oil and Grease Total Residual Carbon Total Chromium Cu Fe Zn Pb Cd Hg As
6.0-9.0 50 10 0.2 0.5 0.5 1 1 0.5 0.1 0.005 0.5
Note:
MWth = Megawatt thermal input on HHV basis
N/A = not applicable;
NDA = Non-degraded airshed
DA = Degraded airshed
SI = Spark Ignition
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DF = Dual Fuel
CI = Compression Engine
ASSESSMENT OF SOURCES OF AIR, WATER & LAND POLLUTION; PART I : RAPID INVENTORY TECHNIQUES IN
ENVIRONMENTAL POLLUTION BY ALEXANDER P. ECONOMOPOULOS (WHO, 1993)
Emission Guidelines Solid Wastes
Unit(U) TSP SO2 NOX CO VOC SO3 Pb Low Hazard
Kg/U Kg/MWH
35101 Gaseous Fuels
Natural Gas1
Utility Boilers 1000 Nm3 0.048 15.6S 8.8f 2 (= 3.04)* 0.64 0.028 N/A N/A N/A
tn 0.061 20S 11.3f (= 3.91)* 0.82 0.036 N/A N/A N/A
Industrial Boilers 1000 Nm3 0.048 15.6S 2.24 0.56 0.092 N/A N/A N/A
tn 0.061 20S 2.87 0.72 0.118 N/A N/A N/A
Domestic Furnaces 1000 Nm3 0.048 15.6S 1.6 0.32 0.127 N/A N/A N/A
tn 0.061 20S 2.05 0.41 0.163 N/A N/A N/A
Stationary Gas Turbines 1000 Nm3 0.224 15.6S 6.62 1.84 0.673 N/A N/A N/A
tn 0.287 20S 8.91 2.36 0.863 N/A N/A N/A
Liquefied Petroleum Gas
Industrial Boilers m3 (Liq.) 0.031 0.004 1.51 0.37 0.06 N/A N/A N/A
tn 0.06 0.007 2.9 0.71 0.12 N/A N/A N/A
Domestic Furnaces m3 (Liq.) 0.031 0.004 1.07 0.22 0.09 N/A N/A N/A
tn 0.06 0.007 2.05 0.42 0.17 N/A N/A N/A
35102 Liquid Fuels
Distillate Fuel Oil
Industrial and Commercial Boilers tn 0.28 20S 2.84 0.71 0.035 0.28S N/A N/A
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Residential Furnaces tn 0.36 3 20S 2.6 0.71 0.354 0.28S N/A N/A
Stationary Gas Turbines tn 0.71 20S 9.62 2.19 0.791 N/A N/A N/A
Residual Fuel Oil4
Utility Boilers
Uncontrolled tn P 20S 8.5 0.64 0.127 0.25S N/A N/A
ESP - Low Efficiency tn 0.5P 20S 8.5 0.64 0.09 0.25S N/A N/A
ESP - High Efficiency tn 0.1P 20S 8.5 0.64 0.09 0.25S N/A N/A
Scrubber tn 0.45P 1.5S 8.5 0.64 0.09 N/A N/A N/A
Industrial and Commercial Boilers tn P 20S 7 5 0.64 0.163 0.25S N/A N/A
Waste Lub Oil6
Industrial and Commercial Boilers tn 8.1A 20S 2.7 0.67 0.13 N/A 5.6P N/A
Domestic Heaters tn 8.6A 20S 2.7 0.67 0.13 N/A 6.8P N/A
35103 Solid Fuels
Anthracite Coal7
Pulverised Coal Furnace
Uncontrolled tn 5A 19.5S 9 0.3 0.055 N/A N/A N/A
Cyclone tn 1.25A 19.5S 9 0.3 0.055 N/A N/A N/A
ESP - High Efficiency tn 0.36A 19.5S 9 0.3 0.055 N/A N/A N/A
Fabric FiLer tn 0.01A 19.5S 9 0.3 0.055 N/A N/A N/A
Travelling Grate stoker
Uncontrolled tn 4.6 19.5S 5 0.3 0.055 N/A N/A N/A
Cyclone tn >1.2 19.5S 5 0.3 0.055 N/A N/A N/A
Hand Fed Units tn 5 19.5S 1.5 45 9 N/A N/A 4.3*A
Bituminous & Subbituminous Coal8
Pulverised Coal / Dry Bottom Furnace
Uncontrolled tn 5A 19.5S 10.5 0.3 0.055 N/A N/A N/A
MuLiple Cyclones tn 1.25A 19.5S 10.5 0.3 0.055 N/A N/A N/A
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ESP - High Efficiency
Low S Coal + No Conditioning tn 0.33A 19.5S 10.5 0.3 0.055 N/A N/A N/A
Otherwise tn >0.01A 19.5S 10.5 0.3 0.055 N/A N/A N/A
Fabric FiLer tn 0.01A 19.5S 10.5 0.3 0.055 N/A N/A N/A
Flue Gas Desulphirization tn 0.05A 1.95S 10.5 0.3 0.055 N/A N/A N/A
Pulverised Coal / Wet Bottom Furnace
Uncontrolled tn 3.5A 19.5S 17 0.3 0.055 N/A N/A N/A
MuLiple Cyclones tn 0.88a 19.5S 17 0.3 0.055 N/A N/A N/A
ESP - High Efficiency
Low S Coal + No Conditioning tn 0.227A 19.5S 17 0.3 0.055 N/A N/A N/A
Otherwise tn 0.007A 19.5S 17 0.3 0.055 N/A N/A N/A
Fabric FiLer tn 0.007A 19.5S 17 0.3 0.055 N/A N/A N/A
Flue Gas Desulphirization tn 0.035A 1.95S 17 0.3 0.055 N/A N/A N/A
Cyclone Furnace
Uncontrolled tn A 19.5S 18.5 0.3 0.055 N/A N/A N/A
ESP - High Efficiency tn 0.65A 19.5S 18.5 0.3 0.055 N/A N/A N/A
Fabric FiLer tn 0.002A 19.5S 18.5 0.3 0.055 N/A N/A N/A
Spreader Stoker Furnace
Uncontrolled tn 30 19.5S 7 2.5 0.055 N/A N/A N/A
MuLiple Cyclones tn 8.5 19.5S 7 2.5 0.055 N/A N/A N/A
Overfeed Stoker Furnace
Uncontrolled tn 8 19.5S 3.25 3 0.055 N/A N/A N/A
MuLiple Cyclones tn 4.5 19.5S 3.25 3 0.055 N/A N/A N/A
Underfeed Stoker Furnace
Uncontrolled tn 7.5 15.5S 4.75 5.5 1.05 N/A N/A N/A
MuLiple Cyclones tn 5.5 15.5S 4.75 5.5 1.05 N/A N/A N/A
Hand Fired Furnace tn 7.5 15.5S 1.5 45 9 N/A N/A N/A
Lignite9 10*A
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Pulverised Coal Furnace
Uncontrolled tn 3.1A 15S10 6 0.3 0.055 N/A N/A N/A
Cyclone tn 0.93A 15S 6 0.3 0.055 N/A N/A N/A
ESP - Older Units tn 0.16A 15S 6 0.3 0.055 N/A N/A N/A
ESP - High Efficiency tn >0.16A 15S 6 0.3 0.055 N/A N/A N/A
Fabric FiLer tn 0.16A 15S 6 0.3 0.055 N/A N/A N/A
Flue Gas Desulphirization tn 0.31A 1.5S 6 0.3 0.055 N/A N/A N/A
Cyclone Furnace
Uncontrolled tn 3.3A 15S 8.5 0.3 0.055 N/A N/A N/A
Cyclones tn A 15S 8.5 0.3 0.055 N/A N/A N/A
ESP - Older Units tn >.165A 15S 8.5 0.3 0.055 N/A N/A N/A
ESP - High Efficiency tn 0.017A 15S 8.5 0.3 0.055 N/A N/A N/A
Fabric FiLer tn 0.017A 15S 8.5 0.3 0.055 N/A N/A N/A
Spreader Stoker Furnace
Uncontrolled tn 3.4A 15S 3 2.5 0.055 N/A N/A N/A
MuLiple Cyclones tn A 15S 3 2.5 0.055 N/A N/A N/A
Overfeed Stoker Furnace
Uncontrolled tn 1.5A 15S 3 3 0.055 N/A N/A N/A
MuLiple Cyclones tn 0.84A 15S 3 3 0.055 N/A N/A N/A
Underfeed Stoker Furnace
Uncontrolled tn 1.5A 15S 3 5.5 1.05 N/A N/A N/A
MuLiple Cyclones tn 1.1A 15S 3 5.5 1.05 N/A N/A N/A
Wood & Bark
Wood Boilers tn 4.4 0.015 0.34 13 0.85 N/A N/A N/A
Wood-Bark Mixture Boilers
Uncontrolled tn 3.6 0.7 0.34 13 0.85 N/A N/A N/A
MuLiple Cyclones tn 2.7 0.75S 0.34 13 0.85 N/A N/A N/A
Bark Boilers
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Uncontrolled tn 24 0.2 0.34 13 0.85 N/A N/A N/A
MuLiple Cyclones tn 4.5 0.2 0.34 13 0.85 N/A N/A N/A
Wood Stoves
Conventional Units tn 15 0.2 1.4 140 46 N/A N/A N/A
Low emitting non-catalytic tn 9.6 0.2 N/A 130 N/A N/A N/A N/A
Low emitting catalytic tn 6.6 0.2 1 39 21 N/A N/A N/A
Residential Fireplaces tn 14 0.2 1.7 85 43 N/A N/A N/A
Bagasse tn 8 0 0.6 N/A N/A N/A N/A N/A
Note:
(a)"S" is the weight percent of Sulphur in the fuel
(b)"A" is the weight percent of Ash in the solid fuel
(c)"N" is the weight percent of Nitrogen in the fuel
1. Typical S content of NG is 0.000615%
2. f(load reduction coefficient) = 0.3505-0.005235 L + 0.0001173 L2 , L is the mean boiler load , typically L=0.87, So f=0.346
3. In the absence of boiler I/M programs, smoke emission factors may be closer to 1.6 kg/tn
4. P = fn (sulfur content of fuel) = 0.4 + 1.32 S
5. If N content of fuel is known, NOX EF = 3.25+59.2 N2
6. (a) Typical values of "A" and "S" in lub oils are 0.65% and 0.5%
(b) "P" is the weight percent of Pb in fuel
7. For Meta Anthracite, A= 8.1 % S=0.9%, Anthracite A= 9.4% S=0.6%, Semi-anthracite A=12.4% S=2%
8. (a) Bituminous coals, Low Volatility coals, A=4.9% & S = 0.8%
Med Volatility coals, A=2.9% & S= 0.6%
High Volatility A coals, A= 6.5% & S= 1.3%
High Volatility B coals, A= 5.4% & S= 1.4%
High Volatility C coals, A= 9.1% & S= 2.6%
(b) Sub-bituminous coals, A type, A= 4.7% & S=1%
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B type, A= 2.8% & S= 0.5%
C type, A= 13.2% & S= 0.4%
9. (a)"A" is the weight percent of Ash in the fuel (wet basis as fired)
(b)"S" is the weight percent of Sulphur in the fuel (wet basis as fired)
(c) Typical Ash and Sulphur contents are 8.8-9.5% and 0.8-1.1%(dry basis)
10. For more accurate estimate SO2 EF = (20-1.44*Na2O)*S
* Values after putting f = 0.346