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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

http://www.emcentre.com/

Report on Data Structure for Customized Information Database in AP

Environmental Management Centre LLP i

1

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


Environmental Management Centre LLP ii

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


Environmental Management Centre LLP 1

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/

http://www.tripwire.com/ponemon-cost-of-compliance/



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.



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)

http://www.old.cseindia.org/regulators_report.pdf



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



― 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



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



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.

http://www.cpcb.nic.in/faq2.php

http://www.appcb.ap.nic.in/cm/red%20category.htm

http://www.appcb.ap.nic.in/cm/orange%20category.htm

http://www.appcb.ap.nic.in/cm/green%20category.htm



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

http://dcmsme.gov.in/ssiindia/defination_msme.htm

http://www.cpcb.nic.in/faq1.php

http://www.wiienvis.nic.in/Database/Andhra_Pradesh_7817.aspx

http://assets.wwfindia.org/downloads/indias_notified_ecologicallysensitive_areas.pdf

http://www.cpcb.nic.in/

http://www.envfor.nic.in/

http://www.indiancoastguard.nic.in/Indiancoastguard/NOSDCP/Marine%20Environment%20Security/Ecosensitive%20areas.pdf

http://www.indiancoastguard.nic.in/Indiancoastguard/NOSDCP/Marine%20Environment%20Security/Ecosensitive%20areas.pdf

http://www.appcb.ap.nic.in/faq/index_gos.htm



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).

http://en.wikipedia.org/wiki/Anantapur_district

http://en.wikipedia.org/wiki/Chittoor_district

http://en.wikipedia.org/wiki/East_Godavari_district

http://en.wikipedia.org/wiki/Guntur_district

http://en.wikipedia.org/wiki/Kadapa_district

http://en.wikipedia.org/wiki/Karimnagar_district

http://en.wikipedia.org/wiki/Khammam_district

http://en.wikipedia.org/wiki/Krishna_district

http://en.wikipedia.org/wiki/Kurnool_district

http://en.wikipedia.org/wiki/Mahbubnagar_district

http://en.wikipedia.org/wiki/Medak_district

http://en.wikipedia.org/wiki/Nalgonda_district

http://en.wikipedia.org/wiki/Sri_Potti_Sri_Ramulu_Nellore_district

http://en.wikipedia.org/wiki/List_of_districts_of_India



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.

http://en.wikipedia.org/wiki/Nizamabad_district

http://en.wikipedia.org/wiki/Prakasam_district

http://en.wikipedia.org/wiki/Ranga_Reddy_district

http://en.wikipedia.org/wiki/Srikakulam_district

http://en.wikipedia.org/wiki/Visakhapatnam_district

http://en.wikipedia.org/wiki/Vizianagaram_district

http://en.wikipedia.org/wiki/Warangal_district

http://en.wikipedia.org/wiki/West_Godavari_district



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/

http://www1.ifc.org/wps/wcm/connect/Topics_Ext_Content/IFC_External_Corporate_Site/IFC+Sustainability/Sustainability+Framework/Environmental,+Health,+and+Safety+Guidelines/




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


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.



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



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



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:


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:


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.



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.



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



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



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



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



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


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


IND7 Mid. Fertilizer in Anantpur

70.00 28.00 Red 2.50 Physical inspection of industry, evaluation of effectiveness of pollution control infrastructure



50.84 27.00 Red 1.88 Physical inspection of industry, evaluation of effectiveness of pollution control infrastructure


IND9 Mid. Brewery in East Godavari

20.06 18.00 Blue 1.11 Physical inspection of industry, evaluation of effectiveness of pollution control infrastructure


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.



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



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?


D4 3rd Party Environmental Audit conducted at least once in last 3 years?


D5 Part of any Supply Chain which imposes its own Environmental & Social Code of Conduct?


D6 Use of Renewable Energy of the order of 5% of total Energy Consumption?


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.



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?


D5 Part of any Supply Chain which imposes its own Environmental & Social Code of Conduct?


D6 Use of Renewable Energy of the order of 5% of total Energy Consumption?


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.



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



― 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

http://cpcb.nic.in/Industry_Specific_Standards.php

http://cpcb.nic.in/GeneralStandards.pdf

http://cpcb.nic.in/crep.php



http://whqlibdoc.who.int/hq/1993/WHO_PEP_GETNET_93.1-A.pdf

http://eippcb.jrc.es/reference/

http://www.unido.org/fileadmin/user_media/Services/Energy_and_Climate_Change/Energy_Efficiency/Benchmarking_%20Energy_%20Policy_Tool.pdf

http://www.unido.org/fileadmin/user_media/Services/Energy_and_Climate_Change/Energy_Efficiency/Benchmarking_%20Energy_%20Policy_Tool.pdf



ANNEXURES



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.



Figure 9 District-wise concentration on Red Category industries in Andhra Pradesh



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


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



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)



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


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



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



IND7 Mid. Fertilizer in Anantpur TKN 212 100 10.00 NH4-N 8 4 10.00 Cr(tot.) 0.6 2 1.00


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



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




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


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



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



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



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



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



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



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



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%



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

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