Chapter 3: Chemical Industry Emissions

CHAPTER 3

CHEMICAL INDUSTRY EMISSIONS

2006 IPCC Guidelines for National Greenhouse Gas Inventories

3.1

Volume 3: Industrial Processes and Product Use

AuthorsS e c tion 3 .1
Jochen Harnisch (Germany)S e c tions 3.2 – 3.8
Charles Jubb (Australia)
Alexander Nakhutin (Russia) and Virginia Carla Sena Cianci (Uruguay)
S e c tion 3 .9
Robert Lanza (USA)Thomas Martinsen (Norway), Abdul Karim W. Mohammad (Iraq), and Maruo M. O. Santos (Brazil)
S e c tion 3 .10
Archie McCulloch (UK) and Brian T. Mader (USA)Contributing Authors
S e c tions 3.2 – 3.8
Javier Pérez-Ramírez (Spain)S e c tion 3 .9
Maarten Neelis (Netherlands) and Martin Patel (Germany)

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2006 IPCC Guidelines for National Greenhouse Gas Inventories

Chapter 3: Chemical Industry Emissions

Contents
3

Chemical Industry Emissions ...................................................................................................................... 3.10
3.1

Introduction ......................................................................................................................................... 3.10

3.2

Ammonia production........................................................................................................................... 3.11

3.2.1

Introduction ................................................................................................................................. 3.11

3.2.2

Methodological issues ................................................................................................................. 3.11

3.2.2.1

Choice of method ................................................................................................................... 3.12

3.2.2.2

Choice of emission factors ..................................................................................................... 3.14

3.2.2.3

Choice of activity data ........................................................................................................... 3.15

3.2.2.4

Completeness ......................................................................................................................... 3.17

3.2.2.5

Developing a consistent time series ....................................................................................... 3.17

3.2.3

Uncertainty assessment ............................................................................................................... 3.17

3.2.3.1

Emission factor uncertainties ................................................................................................. 3.17

3.2.3.2

Activity data uncertainties .................................................................................................... .3.17

3.2.4

Quality Assurance/Quality Control (QA/QC), Reporting and Documentation ........................... 3.17

3.2.4.1

Quality Assurance/Quality Control........................................................................................ 3.17

3.2.4.2

Reporting and Documentation ............................................................................................... 3.18

3.3

Nitric acid production.......................................................................................................................... 3.19

3.3.1

Introduction ................................................................................................................................. 3.19

3.3.2

Methodological issues ................................................................................................................. 3.19

3.3.2.1

Choice of method ................................................................................................................... 3.20

3.3.2.2

Choice of emission factors ..................................................................................................... 3.22

3.3.2.3

Choice of activity data ........................................................................................................... 3.23

3.3.2.4

Completeness ......................................................................................................................... 3.24

3.3.2.5

Developing a consistent time series ....................................................................................... 3.24

3.3.3
3.3.3.1

Emission factor uncertainties ................................................................................................. 3.24

3.3.3.2

Activity data uncertainties ..................................................................................................... 3.25

3.3.4

3.4

Uncertainty assessment ............................................................................................................... 3.24

Quality Assurance/Quality Control (QA/QC), Reporting and Documentation ........................... 3.25

3.3.4.1

Quality Assurance/Quality Control........................................................................................ 3.25

3.3.4.2

Reporting and Documentation ............................................................................................... 3.25

Adipic acid production ........................................................................................................................ 3.27

3.4.1

Introduction ................................................................................................................................. 3.27

3.4.2

Methodological issues ................................................................................................................. 3.27

3.4.2.1

Choice of method ................................................................................................................... 3.27

3.4.2.2

Choice of emission factors ..................................................................................................... 3.28

3.4.2.3

Choice of activity data ........................................................................................................... 3.30

3.4.2.4

Completeness ......................................................................................................................... 3.31

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Volume 3: Industrial Processes and Product Use

3.4.2.5
3.4.3

Uncertainty assessment ............................................................................................................... 3.31

3.4.3.1

Emission factor uncertainties ................................................................................................. 3.31

3.4.3.2

Activity data uncertainties ..................................................................................................... 3.31

3.4.4

3.5

Quality Assurance/Quality Control (QA/QC), Reporting and Documentation ........................... 3.31

3.4.4.1

Quality Assurance/Quality Control........................................................................................ 3.31

3.4.4.2

Reporting and Documentation ............................................................................................... 3.32

Caprolactam, glyoxal and glyoxylic acid production .......................................................................... 3.33

3.5.1

Introduction ................................................................................................................................. 3.33

3.5.2

Caprolactam ................................................................................................................................ 3.33

3.5.2.1

Methodological issues............................................................................................................ 3.33

3.5.2.2

Uncertainty assessment .......................................................................................................... 3.37

3.5.2.3

Quality Assurance/Quality Control (QA/QC), Reporting and Documentation...................... 3.38

3.5.3
3.6

Glyoxal and glyoxylic acid production ....................................................................................... 3.39

Carbide production .............................................................................................................................. 3.40

3.6.1

Introduction ................................................................................................................................. 3.40

3.6.2

Methodological issues ................................................................................................................. 3.40

3.6.2.1

Choice of method ................................................................................................................... 3.41

3.6.2.2

Choice of emission factors ..................................................................................................... 3.43

3.6.2.3

Choice of activity data ........................................................................................................... 3.44

3.6.2.4

Completeness ......................................................................................................................... 3.45

3.6.2.5

Developing a consistent time series ....................................................................................... 3.45

3.6.3

3.7

Uncertainty assessment ............................................................................................................... 3.45

3.6.3.1

Emission factor uncertainties ................................................................................................. 3.45

3.6.3.2

Activity data uncertainties ..................................................................................................... 3.45

3.6.4

Quality Assurance/Quality Control (QA/QC), Reporting and Documentation ........................... 3.46

3.6.4.1

Quality Assurance/Quality Control........................................................................................ 3.46

3.6.4.2

Reporting and Documentation ............................................................................................... 3.46

Titanium dioxide production ............................................................................................................... 3.47

3.7.1

Introduction ................................................................................................................................. 3.47

3.7.2

Methodological issues ................................................................................................................. 3.47

3.7.2.1

Choice of method ................................................................................................................... 3.47

3.7.2.2

Choice of emission factors ..................................................................................................... 3.48

3.7.2.3

Choice of activity data ........................................................................................................... 3.50

3.7.2.4

Completeness ......................................................................................................................... 3.50

3.7.2.5

Developing a consistent time series ....................................................................................... 3.50

3.7.3

Uncertainty assessment ............................................................................................................... 3.50

3.7.3.1

Emission factor uncertainties ................................................................................................. 3.50

3.7.3.2

Activity data uncertainties ..................................................................................................... 3.50

3.7.4
3.7.4.1

3.4

Developing a consistent time series ....................................................................................... 3.31

Quality Assurance/Quality Control (QA/QC), Reporting and Documentation ........................... 3.51
Quality Assurance/Quality Control........................................................................................ 3.51

2006 IPCC Guidelines for National Greenhouse Gas Inventories

Chapter 3: Chemical Industry Emissions

3.7.4.2
3.8

Reporting and Documentation ............................................................................................... 3.51

Soda ash production ............................................................................................................................ 3.52

3.8.1

Introduction ................................................................................................................................. 3.52

3.8.2

Natural soda ash production ........................................................................................................ 3.52

3.8.2.1

Methodological issues............................................................................................................ 3.52

3.8.2.2

Uncertainty assessment .......................................................................................................... 3.54

3.8.2.3

Quality Assurance/Quality Control (QA/QC), Reporting and Documentation...................... 3.55

3.8.3

Solvay soda ash production ......................................................................................................... 3.55

3.8.3.1
3.9

Quality Assurance/Quality Control (QA/QC), Reporting and Documentation...................... 3.56

Petrochemical and carbon black production........................................................................................ 3.57

3.9.1

Introduction ................................................................................................................................. 3.57

3.9.2

Methodological issues ................................................................................................................. 3.63

3.9.2.1

Choice of method ................................................................................................................... 3.63

3.9.2.2

Choice of emission factors ..................................................................................................... 3.72

3.9.2.3

Choice of activity data ........................................................................................................... 3.81

3.9.2.4

Completeness ......................................................................................................................... 3.83

3.9.2.5

Developing consistent time series .......................................................................................... 3.84

3.9.3

Uncertainty assessment ............................................................................................................... 3.84

3.9.4

Quality Assessment/Quality Control (QA/QC), Reporting and Documentation ......................... 3.87

3.9.4.1

Quality Assessment/Quality Control ..................................................................................... 3.87

3.9.4.2

Reporting and Documentation ............................................................................................... 3.88

Annex 3.9A Feedstock-product flow diagrams ...................................................................................... 3.90
3.10

Fluorochemical Production ................................................................................................................. 3.92

3.10.1

HFC-23 emission from HCFC-22 production ............................................................................. 3.92

3.10.1.1

Introduction............................................................................................................................ 3.92

3.10.1.2

Methodological issues............................................................................................................ 3.92

3.10.1.3

Uncertainty assessment ........................................................................................................ 3.100

3.10.1.4

Quality Assurance/Quality Control (QA/QC), Reporting and Documentation.................... 3.101

3.10.2Emissions from production of other fluorinated compounds .................................................... 3.102

3.10.2.1

Introduction.......................................................................................................................... 3.102

3.10.2.2

Methodological issues.......................................................................................................... 3.103

3.10.2.3

Uncertainty assessment ........................................................................................................ 3.106

3.10.2.4

Quality Assurance/Quality Control (QA/QC), Reporting and Documentation.................... 3.106

References .....................................................................................................................................................3.107

2006 IPCC Guidelines for National Greenhouse Gas Inventories

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Volume 3: Industrial Processes and Product Use

Equations
Equation 3.1

CO2 emissions from ammonia production – Tier 1 ............................................................. 3.12

Equation 3.2

Total fuel requirement for ammonia production – Tier 2..................................................... 3.13

Equation 3.3

CO2 emissions from ammonia production – Tier 2 and 3 .................................................... 3.13

Equation 3.4

Total fuel requirement for ammonia production – Tier 3..................................................... 3.13

Equation 3.5

N2O emissions from nitric acid production – Tier 1 ............................................................ 3.21

Equation 3.6

N2O emissions from nitric acid production – Tier 2 ............................................................ 3.21

Equation 3.7

N2O emissions from adipic acid production – Tier 1 ........................................................... 3.27

Equation 3.8

N2O emissions from adipic acid production – Tier 2 ........................................................... 3.28

Equation 3.9

N2O emissions from caprolactam production – Tier 1......................................................... 3.34

Equation 3.10 N2O emissions from caprolactam production – Tier 2......................................................... 3.35
Equation 3.11 Emissions from carbide production ..................................................................................... 3.41
Equation 3.12 CO2 emissions from titanium slag, synthetic rutile and rutile TiO2 production – Tier 1 ..... 3.48
Equation 3.13 CO2 emissions from titanium slag, synthetic rutile and rutile TiO2 production – Tier 2 ..... 3.48
Equation 3.14 CO2 emissions from natural soda ash production – Tier 1................................................... 3.52
Equation 3.15 Tier 1 CO2 emission calculation .......................................................................................... 3.65
Equation 3.16 Primary product production estimate calculation ................................................................ 3.65
Equation 3.17 Overall Tier 2 mass balance equation .................................................................................. 3.67
Equation 3.18 Estimate secondary product production from primary product [ethylene] production ........ 3.67
Equation 3.19 Estimate secondary product production from primary product [acrylonitrile] production .. 3.67
Equation 3.20 Tier 3 CO2 emissions calculation equation .......................................................................... 3.68
Equation 3.21 Fuel combustion Tier 3 CO2 emissions calculation ............................................................. 3.68
Equation 3.22 Flare gas Tier 3 CO2 emissions calculation ......................................................................... 3.69
Equation 3.23 Tier 1 CH4 fugitive emission calculation ............................................................................. 3.70
Equation 3.24 Tier 1 CH4 process vent emission calculation ..................................................................... 3.70
Equation 3.25 Tier 1 CH4 total emissions calculation................................................................................. 3.70
Equation 3.26 Tier 3 CH4 emission calculation based on atmospheric measurement data ......................... 3.71
Equation 3.27 Tier 3 CH4 emissions calculation equation .......................................................................... 3.71
Equation 3.28 Fuel combustion Tier 3 CH4 emissions calculation ............................................................. 3.72
Equation 3.29 Flare gas Tier 3 CH4 emissions calculation ......................................................................... 3.72
Equation 3.30 Tier 1 calculation of HFC-23 from HCFC-22 (produced) using default factor ................... 3.93
Equation 3.31 Tier 2 calculation of HFC-23 from HCFC-22 (produced) using factor(s) calculated fromprocess efficiencies .............................................................................................................. 3.93
Equation 3.32 Calculation of HFC-23 emission factor from carbon balance efficiency............................. 3.93
Equation 3.33 Calculation of HFC-23 emission factor from fluorine balance efficiency ........................... 3.94
Equation 3.34 Tier 3a calculation of HFC-23 emissions from individual process streams (direct method) ...... 3.94
Equation 3.35 Tier 3b calculation of HFC-23 emissions from individual process streams (proxy method) ..... 3.94

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2006 IPCC Guidelines for National Greenhouse Gas Inventories

Chapter 3: Chemical Industry Emissions

Equation 3.36 Tier 3c calculation of HFC-23 emissions from individual process streams (by monitoring
reactor product) ................................................................................................................... 3.95
Equation 3.37 Tier 3a calculation of ‘instantaneous’ HFC-23 emissions in an individual process stream(direct method) .................................................................................................................... 3.95
Equation 3.38 Tier 3b calculation of HFC-23 emissions in an individual process stream (proxy method) ....... 3.96
Equation 3.39 Tier 3b calculation of standard emission for proxy method ................................................ 3.96
Equation 3.40 Tier 3c calculation of HFC-23 emissions from an individual facility by in-process
measurement ........................................................................................................................ 3.97
Equation 3.41 Tier 1 calculation of production-related emissions ............................................................ 3.103
Equation 3.42 Tier 3 direct calculation of production-related emissions .................................................. 3.104
Equation 3.43 Tier 3 proxy calculation of production-related emissions.................................................. 3.104

FiguresFigure 3.1

Decision tree for estimation of CO2 emissions from ammonia production ......................... 3.14

Figure 3.2

Decision tree for estimation of N2O emissions from nitric acid production ........................ 3.22

Figure 3.3

Decision tree for estimation of N2O emissions from adipic acid production....................... 3.29

Figure 3.4

Decision tree for estimation of N2O emissions from caprolactam, glyoxal or
glyoxylic acid production .................................................................................................... 3.36

Figure 3.5

Decision tree for estimation of CO2 and CH4 emissions from carbide production .............. 3.43

Figure 3.6

Decision tree for estimation of CO2 emissions from titanium dioxide production .............. 3.49

Figure 3.7

Decision tree for estimation of CO2 emissions from natural soda ash production .............. 3.53

Figure 3.8

Decision tree for estimation of CO2 emissions from petrochemical industry andcarbon black industry .......................................................................................................... 3.63

Figure 3.9

Decision tree for estimation of CH4 emissions from petrochemical industry andcarbon black industry .......................................................................................................... 3.64

Figure 3.10

Tier 2 carbon mass balance flow diagram ........................................................................... 3.66

Figure 3.11

Methanol production feedstock-product flow diagram........................................................ 3.90

Figure 3.12

Ethylene dichloride production feedstock-product flow diagram........................................ 3.90

Figure 3.13

Ethylene oxide production feedstock-product flow diagram ............................................... 3.91

Figure 3.14

Acrylonitrile production feedstock-product flow diagram .................................................. 3.91

Figure 3.15

Carbon black production feedstock-product flow diagram.................................................. 3.91

Figure 3.16

Decision tree for HFC-23 emissions from HCFC-22 production(or other similar by-product emissions from fluorochemical production) ........................... 3.98

Figure 3.17

Decision tree for emissions of fluorinated greenhouse gases from production processes,
applicable to both fugitive and by-product emissions ....................................................... 3.105

2006 IPCC Guidelines for National Greenhouse Gas Inventories

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Volume 3: Industrial Processes and Product Use

Tables

3.8

Table 3.1

Default total fuel requirements (fuel plus feedstock) and emission factors for ammonia
production (per tonne NH3) ................................................................................................. 3.15

Table 3.2

N2O abatement approaches and abatement measures .......................................................... 3.20

Table 3.3

Default factors for nitric acid production ............................................................................ 3.23

Table 3.4

Default factors for adipic acid production ........................................................................... 3.30

Table 3.5

Default factor for caprolactam production........................................................................... 3.36

Table 3.6

Default factors for glyoxal and glyoxylic acid production .................................................. 3.39

Table 3.7

Default factors for CO2 and CH4 emissions from silicon carbide production ..................... 3.44

Table 3.8

Emission factors for CO2 emission from calcium carbide production and use .................... 3.44

Table 3.9

Default factors for titanium dioxide production (tonnes CO2 per tonne product)................ 3.49

Table 3.10

Specific carbon content of petrochemical feedstocks and products..................................... 3.69

Table 3.11

Petrochemical production Tier 1 default feedstocks and processes ..................................... 3.72

Table 3.12

Methanol production CO2 emission factors ......................................................................... 3.73

Table 3.13

Methanol production feedstock consumption factors .......................................................... 3.74

Table 3.14

Steam cracking ethylene production Tier 1 CO2 emission factors ....................................... 3.75

Table 3.15

Default Geographic Adjustment Factors for Tier 1 CO2 emission factors
for steam cracking ethylene production ............................................................................... 3.75

Table 3.16

Default methane emission factors for ethylene production ................................................. 3.76

Table 3.17

Ethylene dichloride/vinyl chloride production process Tier 1 CO2 emission factors .......... 3.77

Table 3.18

Ethylene dichloride/vinyl chloride monomer process Tier 1 feedstock
consumption factors............................................................................................................. 3.77

Table 3.19

Ethylene dichloride/vinyl chloride process Tier 1 default CH4 emission factor .................. 3.78

Table 3.20

Ethylene oxide production feedstock consumption and CO2 emission factors .................... 3.78

Table 3.21

Ethylene oxide production Tier 1 CH4 emission factors ..................................................... 3.79

Table 3.22

Acrylonitrile production CO2 emission factors ................................................................... 3.79

Table 3.23

Carbon black production Tier 1 CO2 emission factors ........................................................ 3.80

Table 3.24

Carbon black production Tier 1 CH4 emission factors ........................................................ 3.80

Table 3.25

Ethylene steam cracking feedstock-product matrix ............................................................. 3.82

Table 3.26

Secondary product production factors for acrylonitrile production process ........................ 3.82

Table 3.27

Uncertainty ranges for emission factors and activity data ................................................... 3.86

Table 3.28

HFC-23 default emission factors ......................................................................................... 3.99

2006 IPCC Guidelines for National Greenhouse Gas Inventories

Chapter 3: Chemical Industry Emissions

Boxes
Box 3.1

CO2 recovered for industrial gas.......................................................................................... 3.14

Box 3.2

Double counting .................................................................................................................. 3.16

Box 3.3

Urea production ................................................................................................................... 3.16

Box 3.4

Double counting .................................................................................................................. 3.40

Box 3.5

Allocation of emissions from CaO production .................................................................... 3.41

Box 3.6

Double counting .................................................................................................................. 3.48

Box 3.7

Double counting .................................................................................................................. 3.56

Box 3.8

Methanol process descriptions............................................................................................. 3.58

Box 3.9

Ethylene process description ............................................................................................... 3.59

Box 3.10

Ethylene dichloride and vinyl chloride monomer process descriptions............................... 3.59

Box 3.11

Ethylene oxide process description ..................................................................................... 3.60

Box 3.12

Acrylonitrile process description ......................................................................................... 3.61

Box 3.13

Carbon black production process descriptions .................................................................... 3.62

Box 3.14

Plant measurement frequency ............................................................................................ 3.100

2006 IPCC Guidelines for National Greenhouse Gas Inventories

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Volume 3: Industrial Processes and Product Use

3 CHEMICAL INDUSTRY EMISSIONS
3.1

INTRODUCTION

The following Sections 3.2 through 3.10 give guidance for estimating greenhouse gas emissions that result fromthe production of various inorganic and organic chemicals for which experience by a number of countries has
confirmed significant contributions to global or individual national greenhouse gas emission levels.
•

Section 3.2 covers emissions from ammonia production;•

Section 3.3 covers emissions from nitric acid production;•

Section 3.4 covers emissions from adipic acid production;•

Section 3.5 covers emissions from the production of caprolactam, glyoxal, and glyoxylic acid;•

Section 3.6 covers emissions from the production of carbide;•

Section 3.7 deals with emissions from the production of titanium dioxide;•

Section 3.8 deals with emissions from the production of soda ash;•

Section 3.9 covers emissions from key processes in the petrochemical and carbon black production, i.e.,methanol, ethylene and propylene, ethylene dichloride, ethylene oxide, acrylonitrile, and carbon black;•

Section 3.10 deals with emissions from fluorochemical production i.e., HFC-23 from the production of
HCFC-22 and fugitive and by-product emissions from the production of other fluorinated compounds
including hydrofluorocarbons (HFCs), sulphur hexafluoride (SF6) and uranium hexafluoride (UF6).

Care should be exercised to avoid double counting of carbon dioxide (CO2) emissions in both this chapter and in
Volume 2 on Energy Sector, or, in omitting CO2 emissions since CO2 emissions resulting from carbon’s role asprocess reactant and as a heat source to drive the chemical reactions involved in the chemical processes can beclosely related. Should CO2 capture technology be installed at a chemical plant, the CO2 captured should be
deducted in a higher tier emissions calculation. Respective guidance on the capture and subsequent destruction
or use of HFC-23 or other fluorochemicals is given in section 3.10. Any methodology taking into account CO2
capture should consider that CO2 emissions captured in the process may be both combustion and process-related.
In cases where combustion and process emissions are to be reported separately, e.g., in the petrochemicalindustry, inventory compilers should ensure that the same quantities of CO2 are not double counted. In thesecases the total amount of CO2 captured should preferably be reported in the corresponding energy combustion
and IPPU categories in proportion to the amounts of CO2 generated in these source categories. The default
assumption is that there is no CO2 capture and storage (CCS) taking place. For additional information on CO2
capture and storage refer to Volume 3, Section 1.2.2 and for more details to Volume 2, Section 2.3.4.

3.10

2006 IPCC Guidelines for National Greenhouse Gas Inventories

Chapter 3: Chemical Industry Emissions

3.2

AMMONIA PRODUCTION

3.2.1

Introduction

Ammonia (NH3) is a major industrial chemical and the most important nitrogenous material produced. Ammonia
gas is used directly as a fertiliser, in heat treating, paper pulping, nitric acid and nitrates manufacture, nitric acid
ester and nitro compound manufacture, explosives of various types, and as a refrigerant. Amines, amides, andmiscellaneous other organic compounds, such as urea, are made from ammonia (Austin, 1984; p.303).
Ammonia production requires a source of nitrogen (N) and hydrogen (H). Nitrogen is obtained from air throughliquid air distillation or an oxidative process where air is burnt and the residual nitrogen is recovered. Most
ammonia is produced from natural gas (chiefly methane (CH4)), although H can be obtained from otherhydrocarbons (coal (indirectly), oil), and water (Hocking, 1998; p.317). A small number of plants continue to use
fuel oil as the fuel input and H source in the partial oxidation process. The carbon (C) content of the hydrocarbon
is eliminated from the process at the primary steam reforming stage and shift conversion stage throughconversion to carbon dioxide (CO2) which is the main potential direct greenhouse gas emission. Plants usinghydrogen rather than natural gas to produce ammonia do not release CO2 from the synthesis process.

3.2.2

Methodological issues

The chemistry to obtain ammonia feedstocks is similar irrespective of the hydrocarbon used – CH4 or other fossil
fuels (Hocking, 1998; p.319). Because the industry uses predominantly natural gas, the following outline of theprocess and sources of greenhouse emissions (CO2) is based on production using natural gas. Anhydrous
ammonia produced by catalytic steam reforming of natural gas (mostly CH4) involves the following reactions
with carbon dioxide produced as a by-product.
Primary steam reforming:
CH4 + H2O → CO + 3H2
CO + H2O → CO2 + H2
Secondary air reforming:
CH4 + air → CO + 2H2 + 2N2
Overall reaction:
0.88CH4 + 1.26Air + 1.24H2O → 0.88CO2 + N2 + 3H2
Ammonia synthesis:
N2 + 3H2 → 2NH3
Secondary reformer process gas shift conversion:
CO + H2O → CO2 + H2
(Hocking, 1998; EFMA, 2000a; EIPPCB, 2004a)
The processes that affect CO2 emissions associated with ammonia production are:•carbon monoxide shift at two temperatures using iron oxide, copper oxide and/or chromium oxide catalyst
for conversion to carbon dioxide;•

carbon dioxide absorption by a scrubber solution of hot potassium carbonate, monoethanolamine (MEA),
Sulfinol (alkanol amine and tetrahydrothiophene dioxide) or others;•

methanation of residual CO2 to methane with nickel catalysts to purify the synthesis gas.

The production of ammonia represents a significant non-energy industrial source of CO2 emissions. The primary
release of CO2 at plants using the natural gas catalytic steam reforming process occurs during regeneration of theCO2 scrubbing solution with lesser emissions resulting from condensate stripping.
Should CO2 capture technology be installed and used at a plant, it is good practice to deduct the CO2 captured ina higher tier emissions calculation. The default assumption is that there is no CO2 capture and storage (CCS). In
most cases, methodologies that account for CO2 capture should consider that CO2 emissions captured in theprocess may be both combustion and process-related. However, in the case of ammonia production no distinction
is made between fuel and feedstock emissions with all emissions accounted for in the IPPU Sector. Similarly, all
CO2 captured should be accounted for in the IPPU Sector. For additional information on CO2 capture and storagerefer to Volume 3, Section 1.2.2 and for more details on capture and storage to Volume 2, Section 2.3.4.

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Volume 3: Industrial Processes and Product Use

CARBON DIOXIDE REGENERATOR
After absorption of CO2 from the process gas, the saturated scrubbing solutions (e.g., potassium carbonate, MEA,etc.) are regenerated (i.e., for re-use) with steam stripping and/or boiling to release CO2 from the bicarbonatesaccording to the following reactions:

Heat

Heat
2KHCO3 → K2CO3 + H2O + CO2(C2H5ONH2)2 + H2CO3 → 2C2H5ONH2 + H2O + CO2

The stripping gas, containing CO2 and other impurities, may be directed to a urea plant (where operational), to aliquid carbonic acid plant, or vented to the atmosphere (Environment Canada, 1987).

CONDENSATE STRIPPER
Cooling the synthesis gas after low temperature shift conversion forms a condensate containing small quantities
of CO2 and other process impurities. The condensate is stripped by steam, whereby the components may bevented to the atmosphere, but normally recycled to the process together with the process stream (U.S. EPA,
1985).

3.2.2.1

C HOICE OF METHOD

The choice of method will depend on national circumstances as shown in the decision tree, Figure 3.1. Emissions
are estimated from the total fuel requirement, or values derived from estimates of the total fuel requirement, usedin the production of NH3. The fuel energy requirement is not accounted for separately. Note that values reported
in energy units (or volume units) need to be converted to mass units when estimating emissions.
Methods are classified according to the extent of plant-level data that are available. The Tier 1 method is basedon default values and national statistics; the Tier 2 method is based on complete plant-level output data
distinguished by fuel input type and process type, and default values; and the Tier 3 method is based entirely onplant-level input data.
The Tier 3 method uses plant-level output data and plant-level fuel input per unit of output to derive the total fuelrequirement. Similarly, Tier 3 can also use plant-level emission factors per unit of output provided that thesource of these factors is plant-level detailed data on the fuel inputs per unit of output.

TIER 1 METHODThe Tier 1 method uses ammonia production to derive emissions as follows:
EQUATION 3.1
CO2 EMISSIONS FROM AMMONIA PRODUCTION – TIER 1
ECO 2 = AP • FR • CCF • COF • 44 12 − RCO 2
Where:
ECO2 = emissions of CO2, kg
AP = ammonia production, tonnes
FR = fuel requirement per unit of output, GJ/tonne ammonia produced
CCF = carbon content factor of the fuel, kg C/GJ
COF = carbon oxidation factor of the fuel, fraction
RCO2 = CO2 recovered for downstream use (urea production), kg
Ammonia production and emission factors can be obtained from national statistics and the emission factor can be
determined from default values shown in Table 3.1. Where no information is available on the fuel type and/or
process type, it is good practice to use the highest emission factor shown in Table 3.1. CO2 recovered fordownstream use can be estimated from the quantity of urea produced where CO2 is estimated by multiplying
urea production by 44/60, the stoichiometric ratio of CO2 to urea. When a deduction is made for CO2 used inurea production it is good practice to ensure that emissions from urea use are included elsewhere in theinventory. If data are not available on urea production it is good practice to assume that CO2 recovered is zero.

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TIER 2 METHOD
The initial step is to determine the total fuel requirement. For the Tier 2 method the total fuel requirement foreach fuel type is estimated as follows:
EQUATION 3.2
TOTAL FUEL REQUIREMENT FOR AMMONIA PRODUCTION – TIER 2
TFRi = ∑ APij • FRijj()

Where:
TFRi = total fuel requirement for fuel type i, GJ
APij = ammonia production using fuel type i in process type j, tonnes
FRij = fuel requirement per unit of output for fuel type i in process type j, GJ/tonne ammonia produced
Ammonia production, the fuel type and process type can be obtained from producers, and the fuel requirement
per unit of output (FR) can be determined from the default values shown in Table 3.1. Emissions are derived
according to Equation 3.3:
EQUATION 3.3
CO2 EMISSIONS FROM AMMONIA PRODUCTION – TIER 2 AND 3
ECO 2 = ∑ (TFRi • CCFi • COFi • 44 12 ) − RCO 2i

Where:
ECO2 = emissions of CO2, kg
TFRi = total fuel requirement for fuel type i, GJ
CCFi = carbon content factor of the fuel type i, kg C/GJ
COFi = carbon oxidation factor of the fuel type i, fraction
RCO2 = CO2 recovered for downstream use (urea production, CO2 capture and storage (CCS)), kg
When using the Tier 2 method, the C content of the fuel (CCF) and C oxidation factor (COF) may be obtained
from the default values shown in Table 3.1 or country specific Energy Sector information. Data on CO2
recovered for urea production and CCS should be obtained from producers.

TIER 3 METHODThe Tier 3 method requires that the fuel requirement be obtained from producers. The total fuel requirement is
the sum of the total fuel requirements reported by each NH3 production plant. That is:
EQUATION 3.4
TOTAL FUEL REQUIREMENT FOR AMMONIA PRODUCTION – TIER 3
TFRi = ∑ TFRinn

Where:
TFRi = total fuel requirement for fuel type i, GJ
TFRin = total fuel requirement for fuel type i used by plant n, GJ
Once data on total fuel requirements are collected and collated, CO2 emissions can be estimated using Equation
3.3. When using the Tier 3 method, it is good practice to obtain information on the CCF and COF fromproducers or to use country specific energy sector information. As with the Tier 2 method, data on CO2
recovered for urea production (if any) and CCS (if undertaken) should be obtained from producers.
Although data on ammonia production is not used in the calculation under the Tier 3 method it also needs to becollected from producers for reporting purposes.

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BOX 3.1
CO2 RECOVERED FOR INDUSTRIAL GAS

CO2 recovered for industrial gas applications is not accounted for separately as this is a relatively
low volume short term use and it is assumed that all industrial gas carbon will be emitted to theatmosphere in the producing country. For example, industrial CO2 used in freezing applications is
assumed to be released in the producing country.
Figure 3.1

Decision tree for estimation of CO 2 emissions from ammonia production
Start

Are total
fuel input and CO2
recovered data available
directly fromplants?

Use the plant-specific total fuel data
as basis for the Tier 3 method andsubtract plant-specific CO2 recoveredfor urea production and CO2 captureand storage (CCS).

Yes

Box 3: Tier 3

No
Are ammonia
production data by fueltype and process typeavailable?

Calculate total fuel requirement byfuel type, calculate emissions, andsubtract CO2 recovered for urea
production and CO2 capture andstorage (CCS).

Yes

Box 2: Tier 2

No
Is this a key
category1?

No

Are national
aggregate ammonia
production data
available?

Yes

Collect data for the Tier 2
or Tier 3 method.

Yes

No

Gather production data or
use production capacity data.

Calculate emissions using
default emission factors and national
aggregate ammonia production.
Subtract CO2 recovered for urea
production if data are available fromnational statistics.
Box 1: Tier 1

Note:
1. See Volume 1 Chapter 4, Methodological Choice and Identification of Key Categories (noting Section 4.1.2 on limited resources), for
discussion of key categories and use of decision trees.

3.2.2.2

C HOICE OF EMISSION FACTORSTIER 1 METHOD
If plant-level information is not available, it is good practice to use default factors. These default values often
represent midpoint or mean values of data sets (as determined by expert analysis). The extent to which they
represent a specific plant’s emission rate is unknown. Default factors by production process are provided inTable 3.1, and should be used only in cases where plant-specific data are not available. The default factors are
estimates of total fuel requirements per unit of output expressed in energy units. They can be converted to massunits based on C content of the fuel and the C oxidation factor in Volume 2: Energy of these Guidelines. These
values are also included in Table 3.1 as are emission factors of tonnes of CO2 per tonne of NH3 derived using
these values.

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Chapter 3: Chemical Industry Emissions

For the Tier 1 method it is good practice to use the highest total fuel requirement per tonne of ammonia. If noinformation on fuel type is available, it is good practice to use the average value shown in Table 3.1 for partial
oxidation.
TABLE 3.1
DEFAULT TOTAL FUEL REQUIREMENTS (FUEL PLUS FEEDSTOCK) AND EMISSION FACTORS FOR AMMONIA PRODUCTION(PER TONNE NH3)
Production Process± Uncertainty (%)

Carbon content
factor [CCF]1(kg/GJ)

Carbon oxidation
factor [COF]1(fraction)

CO2 emission
factor(tonnes CO2/tonne NH3)

Modern plants – Europe
Conventional reforming –natural gas

30.2 (± 6%)

15.3

1

1.694

Excess air reforming –natural gas

29.7 (± 6%)

15.3

1

1.666

Autothermal reforming –natural gas

30.2 (± 6%)

15.3

1

1.694

36.0 (± 6%)

21.0

1

2.772

Derived from European
average values for specificenergy consumption (Mix ofmodern and older plants)
Average value – natural gas

37.5 (± 7%)

15.3

1

2.104

Average value –partial oxidation

42.5 (± 7%)

21.0

1

3.273

Partial oxidation

Total fuel requirement(GJ(NCV)/tonne NH3)

NCV – Net Calorific Value.
1.

Values from Energy, Vol. 2, Chapter.1, Tables 1.3 and 1.4..

Source: Adapted from EFMA (2000b; p.21); de Beer, Phylipsen and Bates (2001; p.21); for modern plants default factors can be derived
using C content based on natural gas (dry basis) and partial oxidation default factors can be derived using C content based on residual
fuel oil.

TIER 2 METHOD
The total fuel requirement values per unit of output in Table 3.1 can be used in conjunction with data on NH3
production by fuel type and process type, along with either default or country specific data on the C content
factor and carbon oxidation factor of the fuels.

TIER 3 METHOD
Plant-level data on total fuel requirement provide the most rigorous data for calculating CO2 emissions fromammonia production. It is good practice to obtain information on the CCF and COF from producers or use
country-specific Energy Sector data. The CCF is the key emission factor variable for deriving the quantity of
CO2 emissions. Derivation of emissions using plant-level ammonia production depends on an accurate estimateof the fuel requirement per unit of output, along with information on the other variables.

3.2.2.3

C HOICE OF ACTIVITY DATATIER 1 METHODThe Tier 1 method requires data on national production of NH3. If national-level activity data are not available,
information on production capacity can be used. It is good practice to multiply the total national production
capacity by a capacity utilisation factor of 80 percent ± 10 percent (i.e., a range of 70-90 percent) if the inventory
compiler can document that utilisation for a year was below capacity. The same capacity utilisation factor should
be applied to each year of the time-series.

TIER 2 METHODThe Tier 2 method requires plant level data on ammonia production classified by fuel type and production
process. In addition, plant level data on CO2 recovered for downstream use or other application are required.

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Volume 3: Industrial Processes and Product Use

TIER 3 METHOD
The plant-level activity data required for the Tier 3 approach are total fuel requirement classified by fuel type,
CO2 recovered for downstream use or other applications, ammonia production. Although ammonia production is
not used in the Tier 3 calculation, collection of all activity data that influence the estimation of emissions allows
changes over time and any misreporting of activity data to be identified. Where plant-level fuel requirement perunit of output is used, collection of plant-level production data is required.

BOX 3.2
DOUBLE COUNTING

In order to avoid double counting, the total quantities of oil or gas used (fuel plus feedstock) inammonia production must be subtracted from the quantity reported under energy use in the
Energy Sector.
In addition, the quantity of CO2 recovered for downstream use in urea production must be
subtracted from the total quantity of CO2 generated to derive CO2 emitted. Emissions of CO2 fromurea use should be accounted for in the corresponding sectors. In particular, emissions from urea
use as fertiliser should be included in the Agriculture Forestry and Other Land Use (AFOLU)
Sector (see Volume 4). Emissions from urea use in automobile catalytic converters should be
accounted for in the Energy Sector (Volume 2). Emissions from any other chemical products
manufactured using CO2 recovered from the process (e.g., emissions from carbonic acid use) arecovered by methodology suggested in this section and should not be accounted for in other IPPU
sections or in other sectors.

BOX 3.3
UREA PRODUCTION

Urea (CO(NH2)2) (carbonyl amide or carbamide) is an important nitrogenous fertiliser with thehighest nitrogen content available in a solid fertiliser. Urea is also used as a protein foodsupplement for ruminants, in melamine production, as an ingredient in the manufacture of resins,
plastics, adhesives, coatings, textile anti-shrink agents, and ion-exchange resins (Austin, 1984;
pp.311-312). A developing use is as a reducing agent in selective catalytic reduction of NOx in
exhaust gases originating from diesel or gasoline direct injection engines. Emissions from urea
applications should be accounted for in the appropriate application sectors.
Urea production is a downstream process associated with ammonia production plants. The processuses the by-product CO2 stream from an ammonia synthesis plant along with ammonia.
Urea is produced by the reaction of NH3 and CO2 to produce ammonium carbamate which is thendehydrated to urea according to the reactions:
Ammonium carbamate production:
2NH3 + CO2 → NH2COONH4
Dehydration of ammonium carbamate to urea:
NH2COONH4 → CO(NH2)2 + H2O
Assuming complete conversion of NH3 and CO2 to urea, 0.733 tonnes of CO2 are required per
tonne of urea produced. Greenhouse gas emissions from modern plants are likely to be small.
Excess NH3 and CO2 are contained in the process water which is formed during the reaction.
Water treatment is designed to recover these substances from the process water to enable recyclingof the gases to the synthesis (EIPPCB, 2004a; p.118). Based on typical inputs for modern plants(EIPPCB, 2004a; p.121), the input values imply that emissions of CO2 range from 2 to 7kg per
tonne of urea. For a plant of 1 000 tonnes of urea per day and assuming capacity utilisation ofaround 90 percent, this would imply annual emissions of CO2 of slightly in excess of 2Gg.
Although emissions from urea production are unlikely to be significant in well-managed modern
plants, it is good practice to obtain plant-level information on urea production and to account forany significant emissions.

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3.2.2.4

C OMPLETENESS

In countries where only a subset of plants report data for the Tier 3 method or where there is a transition fromTier 2 to Tier 3, it may not be possible to report emissions using Tier 3 for all facilities during the transition.
Where data for the Tier 3 method are not available for all plants, Tier 2 could be used for the remaining plants.
Also, where data for the Tier 2 method are reported by only a subset of plants or where there is a transition fromTier 1 to Tier 2, it may be possible to determine the share of production represented by non-reporting plants anduse this information to estimate the remaining emissions using Tier 1 in order to ensure completeness during thetransition period.
Complete coverage for ammonia production requires accounting for all emissions from all sources. CO2
emissions are straightforward. Completeness can be improved by ensuring that emissions of any fugitive CH4
either from the primary reformer stage or catalytic methanation of CO2 process are included. In order to include
emissions of NOx, CO and SO2 from the primary reformer stage, see guidance provided in Chapter 7 of Volume
1: General Guidance and Reporting.

3.2.2.5

D EVELOPING A CONSISTENT TIME SERIESCO2 emissions should be recalculated for all years whenever emission calculation methods are changed (e.g., if
the inventory compiler changes from the use of default values to actual values determined at the plant level). If
plant-specific data are not available, including plant-specific production data and data for downstream use, for all
years in the time series, it will be necessary to consider how current plant data can be used to recalculate
emissions for previous years. It may be possible to apply current plant-specific emission factors to production
data from previous years, provided that plant operations have not changed substantially. Recalculation isrequired to ensure that any changes in emissions trends are real and not an artefact of changes in procedure. It isgood practice to recalculate the time series according to the guidance provided in Volume 1, Chapter 5.

3.2.3
3.2.3.1

Uncertainty assessment
E MISSION FACTOR UNCERTAINTIES

Uncertainties for the default values shown in Table 3.1 are estimates based on data from EFMA (2000a; p.21)
and de Beer, Phylipsen and Bates (2001; p.21). In general, default emission factors for gaseous inputs andoutputs have higher uncertainties than for solid or liquid inputs and outputs. Mass values for gaseous substances
are influenced by temperature and pressure variations and gases are more easily lost through process leaks. It isgood practice to obtain uncertainty estimates at the plant level, which should be lower than uncertainty values
associated with default values. Default emission factor uncertainties reflect variations between plants acrossdifferent locations.

3.2.3.2

A CTIVITY DATA UNCERTAINTIES

Where activity data are obtained from plants, uncertainty estimates can be obtained from producers. These
activity data are likely to be highly accurate (i.e., with uncertainty as low as ±2 percent). This will include
uncertainty estimates for fuel use, uncertainty estimates for ammonia production and CO2 recovered. Data thatare obtained from national statistical agencies usually do not include uncertainty estimates. It is good practice toconsult with national statistical agencies to obtain information on any sampling errors. Where national statisticalagencies collect data from the population of ammonia production facilities, uncertainties in national statistics are
not expected to differ from uncertainties established from plant-level consultations. Where uncertainty values are
not available from other sources, a default value of ±5 percent can be used.

3.2.4
3.2.4.1

Quality Assurance/Quality Control (QA/QC),
Reporting and Documentation
Q UALITY A SSURANCE /Q UALITY C ONTROL

It is good practice to conduct quality control checks as outlined in Volume 1, Chapter 6. More extensive quality
control checks and quality assurance procedures are applicable, if higher tier methods are used to determine

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Volume 3: Industrial Processes and Product Useemissions. Inventory compilers are encouraged to use higher tier QA/QC for key categories as identified inVolume 1, Chapter 4.

Comparison of emission factors
Inventory compilers should check if the estimated emission factors are within the range of default emission
factors provided for the Tier 1 method, and also ensure that the emission factors are consistent with the values
derived from analysis of the process chemistry. For example, the CO2 generation rate based on natural gas
should not be less than 1.14 tonnes of CO2 per tonne of ammonia produced. If the emission factors are outside ofthe estimated ranges, it is good practice to assess and document the plant-specific conditions that account for thedifferences.

Plant-specific data check
The following plant-specific data are required for adequate auditing of emissions estimates:•

Activity data comprising input and output data (input data should be total fuel requirement – fuel energy
input plus feedstock input;•

Calculations and estimation method;•

List of assumptions;•

Documentation of any plant-specific measurement method, and measurement results.

If emission measurements from individual plants are collected, inventory compilers should ensure that themeasurements were made according to recognised national or international standards. QC procedures in use at
the site should be directly referenced and included in the QC plan. If the measurement practices were notconsistent with QC standards, the inventory compiler should reconsider the use of these data.

3.2.4.2

R EPORTING AND D OCUMENTATION

It is good practice to document and archive all information required to produce the national emissions inventory
estimates as outlined in Volume 1, Section 6.11. It is not practical to include all documentation in the national
inventory report. However, the inventory should include summaries of methods used and references to source
data such that the reported emissions estimates are transparent and steps in their calculation may be retraced.
Much of the production and process data are considered proprietary by operators, especially where there are onlya small number of plants within a country. It is good practice to apply appropriate techniques, including
aggregation of data, to ensure protection of confidential data. Guidance on managing confidential data isprovided in Section 2.2, Volume 1.

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3.3

NITRIC ACID PRODUCTION

3.3.1

Introduction

Nitric acid is used as a raw material mainly in the manufacture of nitrogenous-based fertiliser. Nitric acid may
also be used in the production of adipic acid and explosives (e.g., dynamite), for metal etching and in theprocessing of ferrous metals.
During the production of nitric acid (HNO3), nitrous oxide (N2O) is generated as an unintended by-product of thehigh temperature catalytic oxidation of ammonia (NH3). The amount of N2O formed depends, inter alia, on
combustion conditions (pressure, temperature), catalyst composition and age, and burner design (EFMA, 2000b;p.15). In addition, some NOx is produced. Formation of NOx is most pronounced at start-up and shut-down when
the process is least stable (EFMA, 2000b; p.15). N2O is also generated in other industrial processes that use
nitrogen oxides or nitric acid as feedstocks (e.g. the manufacture of caprolactam, glyoxal, and nuclear fuelreprocessing). Nitric acid is a significant source of atmospheric N2O if not abated and is the major source of N2Oemissions in the chemical industry. While, unlike other emissions from nitric acid production, there are nomature technologies specifically designed for the destruction of N2O (Perez-Ramirez et al., 2003) a number oftechnologies for N2O mitigation during nitric acid manufacture have been developed in recent years. Examples
include a tail-gas process where both N2O and NO emissions can be simultaneously reduced (requiring additionof ammonia to the tail-gas), a process-gas option involving direct catalytic decomposition right after theplatinum gauzes, and a full-scale catalyst decomposition option.
There are two types of nitric acid plants, single pressure plants and dual pressure plants. In single pressure plants
the oxidation and absorption take place at essentially the same pressure, and in dual pressure plants absorption
takes place at a higher pressure than the oxidation stage.

3.3.2

Methodological issues

Nitric acid production involves three distinct chemical reactions that can be summarised as follows:
4NH3 + 5O2 → 4NO + 6H2O
2NO + O2 → 2NO2
3NO2 + H2O → 2HNO3 + NO
Nitrous oxide generation during the production of nitric acid is not well documented. Nitrogen oxidation steps
under overall reducing conditions are considered to be potential sources of N2O. Nitric oxide (NO), anintermediate in the production of nitric acid, is also documented to readily decompose to N2O and nitrogendioxide (NO2) at high pressures for a temperature range of 30 to 50ºC (Cotton and Wilkinson, 1988).
Perez-Ramirez et al. (2003; p.123) specify three intermediate reactions during the oxidation of ammonia thatmight result in the formation of N2O:
NH3 + O2 → 0.5N2O + 1.5H2O
NH3 + 4NO → 2.5N2O + 1.5H2O
NH3 + NO + 0.75O2 → N2O + 1.5H2O
Reactions that lead to the formation of N2O or N2 are undesirable in that they decrease the conversion efficiencyof NH3 and reduce the yield of the desired product, NO (Perez-Ramirez et al., 2003; p.124). It is not possible todefine a precise relationship between NH3 input and N2O formation because in general, ‘the amount of N2O
formed depends on combustion conditions, catalyst composition and state (age), and burner design’ (PerezRamirez et al., 2003; p.123). Emissions of N2O depend on the amount generated in the production process andthe amount destroyed in any subsequent abatement process. Abatement of N2O can be intentional, throughinstallation of equipment designed to destroy N2O, or unintentional in systems designed to abate other emissions
such as nitrogen oxides (NOx).
Perez-Ramirez et al. (2003; p.126) classify abatement approaches as follows and abatement measures associatedwith each approach are outlined in Table 3.2:

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Volume 3: Industrial Processes and Product Use•

Primary abatement measures aim at preventing N2O being formed in the ammonia burner. This involves
modification of the ammonia oxidation process and/or catalyst.

•

Secondary abatement measures remove N2O from the valuable intermediate stream, i.e. from the NOx gases
between the ammonia converter and the absorption column. Usually this will mean intervening at thehighest temperature, immediately downstream of the ammonia oxidation catalyst.

•

Tertiary abatement measures involve treating the tail-gas leaving the absorption column to destroy N2O. The
most promising position for N2O abatement is upstream of the tail-gas expansion turbine.

•

Quaternary abatement measures are the pure end-of-pipe solution, where the tail-gas is treated downstreamof the expander on its way to the stack.
TABLE 3.2
N2O ABATEMENT APPROACHES AND ABATEMENT MEASURES
Abatement approaches

Abatement measures

Primary abatement•••

Optimal oxidation process
Modification of platinum-rhodium gauzes
Oxide-based combustion catalysts

Secondary abatement••

Homogeneous decomposition in the burner
Catalytic decomposition in the burner (process gas
catalytic decomposition)
Catalytic decomposition downstream of the burner(before the absorption column)•
Tertiary abatement

•
•
•
•

Thermal decomposition
Non-selective catalytic reduction (NSCR)
Tail-gas catalytic decomposition
Selective catalytic reduction (SCR)

Quaternary abatement•••

Non-selective catalytic reduction (NSCR)
Catalytic decomposition
Selective catalytic reduction (SCR)

Source: Adapted from Perez-Ramirez et al. (2003).

The abatement achieved will depend on the technology implemented with tertiary measures stated as, ‘enabling
the achievement of high levels of N2O removal (>99 percent)’ (Perez-Ramirez et al., 2003; p.136). Additionally,
it is noted that although NSCR is a proven technology for N2O reduction, the replacement of NSCR systems by
SCR systems for NOx reduction has a negative side-effect on its application for N2O reduction. Further, ‘NSCR
is most likely not a viable option anymore, due to the high fuel consumption levels and high secondary
emissions’ (Perez-Ramirez et al., 2003; p.137).
Future adoption of technologies will depend on cost-effectiveness and the stringency of any emissions regulation.
More cost-effective options are available for new plants than for existing plants. Tail-gas options are appealing
since they do not interfere with the process. Direct N2O decomposition is a very attractive and cost effective
option in plants with tail-gas temperatures greater than 723 K. However, two-thirds of the nitric acid plants in
Europe have low-temperature tail-gases. To this end, preheating or using reductants (light hydrocarbons orammonia) is required, making the after-treatment prohibitive. The most elegant and cost-effective option is the inprocess-gas catalytic decomposition, located in the heart of the plant (the ammonia burner). Concerns with thisabatement option are chemical and mechanical stability of the catalyst as well as the possible NO loss. Several
catalyst manufacturers and nitric acid producers have addressed this problem and catalysts are in the early stagesof commercialisation. Advantageously, and contrary to the tail-gas option, this technology can be retrospectively
applied to all existing plants. Further discussion of options is provided in Perez-Ramirez et al. (2003).

3.3.2.1

C HOICE OF METHOD

The choice of good practice method depends on national circumstances. The decision tree in Figure 3.2
describes good practice in adapting the methods to national circumstances. Emissions can be estimated from:•

3.20

continuous emissions monitoring (CEM) where emissions are directly measured at all times;

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Chapter 3: Chemical Industry Emissions•

periodic emissions monitoring that is undertaken over a period(s) that is reflective of the usual pattern ofoperation of the plant to derive an emission factor that is multiplied by output (100 percent HNO3) to derive
emissions;•

irregular sampling to derive an emission factor that is multiplied by output (100 percent HNO3) to derive
emissions;•by multiplying a default emission factor by output (100 percent HNO3).

Methods are classified according to the extent of plant-level data that are available. Both Tier 2 and Tier 3 arebased on plant-level activity data.

TIER 1 METHOD
Emissions are estimated as follows:
EQUATION 3.5
N2O EMISSIONS FROM NITRIC ACID PRODUCTION – TIER 1
E N 2O = EF • NAP
Where:
EN2O = N2O emissions, kg
EF = N2O emission factor (default), kg N2O/tonne nitric acid produced
NAP = nitric acid production, tonnes
When applying the Tier 1 method it is good practice to assume that there is no abatement of N2O emissions andto use the highest default emission factor based on technology type shown in Table 3.3.

TIER 2 METHOD
There are a large number of nitric acid plants (estimates range from 255 to 600 plants according to Choe et al.,
1993; Bockman and Granli, 1994) with substantial variations in the N2O generation factors among plant types.
Consequently, default factors may be needed more often for nitric acid N2O emissions estimates. Where default
values are used to estimate emissions from nitric acid production, it is good practice to categorise plants
according to type and to use an appropriate N2O generation factor.
The Tier 2 method uses plant-level production data disaggregated by technology type and default emission
factors classified by technology type. Emissions are calculated as follows:
EQUATION 3.6
N2O EMISSIONS FROM NITRIC ACID PRODUCTION – TIER 2[(

E N 2O = ∑ EFi • NAPi • 1 − DF j • ASUF j
i, j

)]

Where:
EN2O = emissions of N2O, kg
EFi = N2O emission factor for technology type i, kg N2O/tonne nitric acid produced
NAPi = nitric acid production from technology type i, tonnes
DFj = destruction factor for abatement technology type j, fraction
ASUFj = abatement system utilisation factor for abatement technology type j, fraction
Note that the default emission factors shown in Table 3.3 include the impact on emissions of abatement
technology where relevant. To use these factors, inventory compilers should verify that the abatement
technology is installed at individual plants and operated throughout the year.
The basic equation for estimating N2O emissions includes additional terms that recognise the potential future useof N2O abatement technologies. The N2O destruction factor has to be multiplied by an abatement systemutilisation factor in order to account for any down-time of the emission abatement equipment (i.e., time theequipment is not operating).

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Volume 3: Industrial Processes and Product Use

TIER 3 METHOD – DIRECT MEASUREMENT
While the tier 2 approach applies technology specific emission factors reflecting the national technology mix.
Tier 3 is based on real measurement data (e.g., CEMS). Plant-level production data disaggregated by technology
type and plant level emission factors obtained from direct measurement of emissions. These may be derived
from irregular sampling of emissions of N2O or periodic emissions monitoring of N2O undertaken over a
period(s) that reflects the usual pattern of operation of the plant. Emissions can be derived using Equation 3.6.
Alternatively, the Tier 3 method uses the results of continuous emissions monitoring (CEM), although it is notedthat most plants are unlikely to employ CEM due to the resource costs. Where CEM is employed, emissions canbe estimated based on the sum of measured N2O emissions derived from the concentration of N2O in monitored
emissions for each recorded monitoring interval.
Figure 3.2

Decision tree for estimation of N 2 O emissions from nitric acid production
Start

Are direct
measurement data
available?

Yes

Use plant specific-emissions data
and activity data (irregular sampling
data, periodic monitoring data orcontinuous emissions monitoring) as
basis for Tier 3 method.
Box 3: Tier 3NoAre
plant-specificactivity data on nitric acidproduction
available?

Yes

Use plant-specific data on quantityof nitric acid by technology typeproduced as basis for Tier 2 method.
Box 2: Tier 2

No

Is this a key
category1?

No

Use national data on nitric acidproduction or national data on
capacity, and default emission factors.
Box 1: Tier 1

Yes
Collect data for the Tier 3
or Tier 2 method.
Note:
1. See Volume 1 Chapter 4, Methodological Choice and Identification of Key Categories (noting Section 4.1.2 on limited resources), for
discussion of key categories and use of decision trees.

3.3.2.2

C HOICE OF EMISSION FACTORSTIER 1 METHOD
It is good practice to use the highest emission factor based on the technology type shown in Table 3.3 and toassume that there is no abatement of N2O emissions.

TIER 2 METHOD
If plant-level factors are not available, it is good practice to use default factors. These default values often
represent midpoint or mean values of data sets (as determined by expert analysis). The extent to which they

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Chapter 3: Chemical Industry Emissions

represent a specific plant’s emission rate is unknown. Default factors in Table 3.3 should be used only in cases
where plant-specific measurements are not available.
Table 3.3 includes emission factors for N2O, and associated uncertainties. The factors listed in Table 3.3 forplants using non-selective catalytic reduction (NSCR), (a NOx abatement technology that can also be managed toabate N2O), already incorporate the effect of N2O abatement measures. To use these factors, inventory compilers
should verify that the abatement technology is installed at individual plants and operated throughout the year.

TIER 3 METHOD
Plant measurements provide the most rigorous data for calculating net emissions (i.e., N2O generation anddestruction factors). Monitoring N2O emissions from nitric acid production is practical because these are point
sources and there are a finite number of production plants. Given currently available technology, instrumentation
for sampling and monitoring emission rates do not limit precision or accuracy of the overall measurement.
Usually sampling frequency and timing is sufficient to avoid systematic errors and to achieve the desired level ofaccuracy.
As a general rule, it is good practice to conduct sampling and analysis whenever a plant makes any significant
process changes that would affect the generation rate of N2O, and sufficiently often otherwise to ensure that
operating conditions are constant. In addition, plant operators should be consulted annually to determine thespecific destruction technologies employed and confirm their use, since technologies may change over time.
Precise measurement of the emissions rate and abatement efficiencies requires measurement of both the exit
stream and the uncontrolled stream. Where measurement data are available only on the exit stream, goodpractice is to base emissions on these data. In this case, any available estimates of abatement efficiency should
be provided only for information purposes and are not used to calculate emissions.
TABLE 3.3
DEFAULT FACTORS FOR NITRIC ACID PRODUCTIONa

Production Process

N2O Emission Factor(relating to 100 percent pure acid)

Plants with NSCRa (all processes)

2 kg N2O/tonne nitric acid ±10%

Plants with process-integrated or tailgas N2O destruction

2.5 kg N2O/tonne nitric acid ±10%

Atmospheric pressure plants (low pressure)

5 kg N2O/tonne nitric acid ±10%

Medium pressure combustion plants

7 kg N2O/tonne nitric acid ±20%High pressure plants

9 kg N2O/tonne nitric acid ±40%

Non-Selective Catalytic Reduction (NSCR).

Source: van Balken (2005).

3.3.2.3

C HOICE OF ACTIVITY DATA

It is good practice to compile production data at a level of detail that allows the use of a Tier 2 or Tier 3 method,where possible. Activity data should be based on 100 percent HNO3, - it is good practice to ensure that all
production data reported are for 100 percent HNO3.

TIER 1 METHODThe Tier 1 method requires data on national production of nitric acid. National nitric acid statistics may omit a
substantial proportion of the national total (see details in Section 3.3.2.4 Completeness). If national-level activity
data are not available, information on production capacity can be used. It is good practice to multiply the total
national production capacity by a capacity utilisation factor of 80 percent ± 10 percent (i.e., a range of 70-90
percent).

TIER 2 METHODThe Tier 2 method requires plant-level production data disaggregated by technology type and abatement system
type. It is good practice to gather activity (production) data at a level of detail consistent with that of any
generation and destruction data. Typical plant-level production data is assumed to have an uncertainty of ±2
percent due to the economic value of having accurate information.

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TIER 3 METHOD
As with the Tier 2 method, plant-level production data disaggregated by technology and abatement system typeare required. It is good practice to gather activity (production) data at a level of detail consistent with that of any
generation and destruction data. Although production data are not used in the estimation of emissions where theestimate is based on CEM, these data should be collected and reported to ensure that changes in variables that
influence emissions can be monitored over time. Typical plant-level production data is assumed to have an
uncertainty of ±2 percent due to the economic value of having accurate information.

3.3.2.4

C OMPLETENESS

Nationally compiled nitric acid production statistics could underestimate production. Studies that compare global
statistics compiled from national data on nitric acid production with industry estimates of global production
suggest that the national statistics account for only 50 to 70 percent of the total (Bouwman et al., 1995; Olivier,1999). This is probably due to nitric acid production that is integrated as part of larger production processes,
where the nitric acid never enters into commerce and is not counted in the national statistics. It is good practiceto account for these sources by methods such as identifying them through national registries of NOx emissions,another unintended by-product of nitric acid production.
NSCR and SCR systems designed to abate N2O can give rise to additional emissions of CO, CO2 andhydrocarbons (CH4 and NMVOCs). These emissions will depend on the hydrocarbon reducing agent that is used(methane (CH4), propane (C3H8), propene (C3H6), LPG). Emissions can be estimated based on the quantity of
reducing agent used and the completeness of combustion. Plant-level information will be required to enableemissions estimation. Over time default values could be developed as more information becomes available,
however, at present there are no default values. Methods for estimating these emissions are not included in these
Guidelines, however, inventory compilers are encouraged to investigate these emission sources and to develop
appropriate methodologies.
There will usually be few nitric acid plants in a country, and it is suggested that emissions are calculated fromplant specific data. In countries where only a subset of plants report data for the Tier 3 method or where there isa transition from Tier 2 to Tier 3, it may not be possible to report emissions using Tier 3 for all facilities during
the transition. Where data for the Tier 3 method are not available for all plants, Tier 2 could be used for theremaining plants. Also, where data for the Tier 2 method are reported by only a subset of plants or where there isa transition from Tier 1 to Tier 2, it may be possible to determine the share of production represented by nonreporting plants and use this information to estimate the remaining emissions using Tier 1 in order to ensurecompleteness during the transition period.

3.3.2.5

D EVELOPING A CONSISTENT TIME SERIESN2O emissions should be recalculated for all years whenever emission calculation methods are changed (e.g., if
the inventory compiler changes from the use of default values to actual values determined at the plant level). If
plant-specific data are not available for all years in the time series, it will be necessary to consider how current
plant measurements can be used to recalculate emissions for previous years. It may be possible to apply current
plant-specific emission factors to production data from previous years, provided that plant operations have notchanged substantially. Such a recalculation is required to ensure that any changes in emissions trends are realand not an artefact of changes in procedure. It is good practice to recalculate the time series according to theguidance provided in Volume 1, Chapter 5.

3.3.3
3.3.3.1

Uncertainty assessment
E MISSION FACTOR UNCERTAINTIES

Uncertainties for the default values shown in Table 3.3 are estimates based on expert judgment. In general,
default emission factors for gaseous substances have higher uncertainties because mass values for gaseous
substances are influenced by temperature and pressure variations and gases are more easily lost through process
leaks. The default values for nitric acid production have a relatively high level of uncertainty for two reasons.
First, N2O may be generated in the gauze reactor section of nitric acid production as an unintended reaction byproduct (Cook, 1999). Second, the exhaust gas may or may not be treated for NOx control, and the NOx

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Chapter 3: Chemical Industry Emissions

abatement system may or may not reduce (or may even increase) the N2O concentration of the treated gas 1. It isgood practice to obtain uncertainty estimates at the plant-level which should be lower than uncertainty values
associated with default values.

3.3.3.2

A CTIVITY DATA UNCERTAINTIES

Where activity data are obtained from plants, uncertainty estimates can be obtained from producers. Data that are
obtained from national statistical agencies usually do not include uncertainty estimates. It is good practice toconsult with national statistical agencies to obtain information on any sampling errors. Where national statisticalagencies collect data from the population of nitric acid production facilities, uncertainties in national statistics
are not expected to differ from uncertainties established from plant-level consultations. Where uncertainty values
are not available from other sources, a default value of ±2 percent can be used. To reduce uncertainty it is goodpractice to ensure that all activity data are for 100 percent HNO3.

3.3.4
3.3.4.1

Quality Assurance/Quality Control (QA/QC),
Reporting and Documentation
Q UALITY A SSURANCE /Q UALITY C ONTROL

It is good practice to conduct quality control checks as outlined in Volume 1, Chapter 6. More extensive quality
control checks and quality assurance procedures are applicable if higher tier methods are used to determine
emissions. Inventory compilers are encouraged to use higher tier QA/QC for key categories as identified inVolume 1, Chapter 4.

Comparison of emissions estimates using different approaches
If emissions are calculated using data from individual nitric acid plants (bottom-up approach), inventory
compilers should compare the estimate to emissions calculated using national production data (top-down
approach). They should record the results and investigate any unexplained discrepancies.
Since industrial N2O source categories are relatively small compared to other anthropogenic and natural sources,
it is not feasible to compare emissions with measured trends in atmospheric N2O concentrations.

Plant-level data
Inventory compilers should archive sufficient information to allow an independent review of the time series ofemissions beginning in the base year, and to explain trends in emissions when making historical comparisons.
This is particularly important in cases where recalculations are necessary, for example, when an inventory
compiler changes from using default values to actual values determined at the plant level.

Revision of direct emission measurements
If plant-level N2O measurements are available, inventory compilers should confirm that internationallyrecognised, standard methods were used. If the measurement practices fail this criterion, then they should
evaluate the use of these emissions data. In addition, they should reconsider the uncertainty estimates in light of
the QA/QC results.
Inventory compilers should compare plant-based factors to the IPCC defaults to ensure that the plant-specificfactors are reasonable. They should explain and document any differences between plant-specific factors anddefault factors, particularly any differences in plant characteristics that might lead to these differences.

3.3.4.2

R EPORTING AND D OCUMENTATION

It is good practice to document and archive all information required to produce the national emissions inventory
estimates as outlined in Volume 1, Section 6.11.
Some examples of specific documentation and reporting relevant to this source category are provided below:

1

In some cases, processes designed to reduce NOx emissions may result in additional N2O generation. Increased N2O
concentrations due to NOx abatement technology have been measured at various power plants that employ non-catalytic
reduction for NOx (Cook, 1999). From at least one nitric acid plant, it is known that NOx control resulted in increased N2Oemissions (Burtscher, 1999).

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Description of the method used;•

Number of nitric acid plants;•

Emission factors;•

Production data;•

Production capacity;•

Number of plants using abatement technology;•

Type of abatement technology, destruction efficiency, and utilisation;•

Any other assumptions.

Plant operators should supply this information to the inventory compiler for compilation, and also archive theinformation at the site. Plant operators should also log and archive the measurement frequencies andinstrumental calibration records where actual plant measurements are made.
Where there are only one or two producers in a country, activity data may be considered confidential. In this case,
operators and the inventory compiler should determine the level of aggregation at which information can bereported while still protecting confidentiality. Detailed information including instrumentation records should still
be archived at the plant level.
It is not practical to include all documentation in the national inventory report. However, the inventory should
include summaries of methods used and references to source data such that the reported emissions estimates aretransparent and steps in their calculation may be retraced.

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3.4

ADIPIC ACID PRODUCTION

3.4.1

Introduction

Adipic acid is used in the manufacture of a large number of products including synthetic fibres, coatings, plastics,
urethane foams, elastomers and synthetic lubricants. The production of Nylon 6.6 accounts for the bulk of adipic
acid use. As noted by Hocking (1998; p.657), ‘A large fraction of this consumption is direct, as adipic acid in the
production of nylon 6.6, but a substantial fraction of the adipic acid is further processed to give hexamethylene
diamine, the other monomer required. A further small fraction of the adipic acid is converted into di-octyl (di-2ethylhexyl) or di-hexyl esters for use as plasticizers in flexible grades of PVC, etc., or as a high boiling point
component of synthetic motor oils’.

3.4.2

Methodological issues

Adipic acid is a dicarboxylic acid manufactured from a cyclohexanone/cyclohexanol mixture which is oxidisedby nitric acid in the presence of a catalyst to form adipic acid. Nitrous oxide (N2O) is generated as an unintended
by-product of the nitric acid oxidation stage:(CH2)5CO (Cyclohexanone) + (CH2)5CHOH (Cyclohexanol) + wHNO3 →HOOC(CH2)4COOH (Adipic Acid) + xN2O + yH2O
Adipic acid is a significant source of atmospheric N2O if not abated. Emissions of N2O depend on the amount
generated in the production process and the amount destroyed in any subsequent abatement process. Abatementof N2O can be intentional through installation of equipment specifically designed to destroy N2O in adipic acidplants. Adipic acid production also results in the emissions of NMVOC, CO and NOx. Process emissions fromthe production of adipic acid vary substantially with the level of emission control employed.

3.4.2.1

C HOICE OF METHOD

The decision tree in Figure 3.3 describes good practice in adapting the methods to national circumstances.
Emissions can be estimated from continuous emissions monitoring (CEM) where emissions are directly
measured at all times, periodic emissions monitoring that is undertaken over a period(s) that is reflective of theusual pattern of operation of the plant to derive an emission factor that is multiplied by output to derive
emissions, irregular sampling to derive an emission factor that is multiplied by output to derive emissions, or bymultiplying a default emission factor by output.
Methods are classified according to the extent of plant-level data that are available. Both Tier 2 and Tier 3
require plant-level activity data.

TIER 1 METHOD
Emissions are estimated as follows:
EQUATION 3.7
N2O EMISSIONS FROM ADIPIC ACID PRODUCTION – TIER 1
E N 2O = EF • AAP
Where:
EN2O = N2O emissions, kg
EF = N2O emission factor (default), kg N2O/tonne adipic acid produced
AAP = adipic acid production, tonnes
When applying the Tier 1 method it is good practice to assume that there is no abatement of N2O emissions andto use the highest default emission factor shown in Table 3.4.

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TIER 2 METHODThe Tier 2 method uses plant-level production data and default emission factors. Where default values are used
to estimate emissions, it is good practice to categorise plants according to the abatement technology type
employed and the utilisation factor of the abatement technology. Emissions are calculated as follows:
EQUATION 3.8
N2O EMISSIONS FROM ADIPIC ACID PRODUCTION – TIER 2[(

EN 2O = ∑ EFi • AAPi • 1 − DF j • ASUF j
i, j

)]

Where:
EN2O = emissions of N2O, kg
EFi = N2O emission factor for technology type i, kg N2O/tonne adipic acid produced
AAPi = adipic acid production from technology type i, tonnes
DFj = destruction factor for abatement technology type j, fraction
ASUFj = abatement system utilisation factor for abatement technology type j, fraction
The basic equation for estimating N2O emissions includes additional terms that recognise the use of N2O
abatement technologies. The N2O destruction factor has to be multiplied by an abatement system utilisation
factor in order to account for any down-time of the emission abatement equipment (i.e., time the equipment is
not operating).
To achieve the highest accuracy, good practice is to apply this equation at the plant-level using N2O generationand destruction factors developed from plant-specific measurement data. In this case, the national total is equal
to the sum of plant totals. Where plant-level information is not available, good practice provides default N2O
generation factors and destruction factors as shown in Table 3.4, Default Factors for Adipic Acid Production,
based on abatement technologies implemented. To use these factors, inventory compilers should verify that theabatement technology is installed at individual plants and operated throughout the year.

TIER 3 METHOD – DIRECT MEASUREMENTThe Tier 3 method uses plant level production data and plant-level emission factors obtained from direct
measurement of emissions. These may be derived from irregular sampling of emissions of N2O or periodic
emissions monitoring of N2O undertaken over a period(s) that reflects the usual pattern of operation of the plant.
Emissions can be derived using Equation 3.8. To achieve the highest accuracy, good practice is to apply thisequation at the plant-level using N2O generation and destruction factors developed from plant-specificmeasurement data where relevant. Given the relatively small number of adipic acid plants (about 23 globally,
Choe et al., 1993), obtaining plant-specific information requires few additional resources.
Alternatively, the Tier 3 method uses the results of continuous emissions monitoring (CEM), although it is notedthat most plants are unlikely to employ CEM due to the resource costs. Where CEM is employed, emissions canbe estimated based on the sum of measured N2O emissions derived from the concentration of N2O in monitored
emissions for each recorded monitoring interval.

3.4.2.2

C HOICE OF EMISSION FACTORSTIER 1 METHOD
It is good practice to use the default emission factor shown in Table 3.4 and to assume that there is no abatementof N2O emissions.

TIER 2 METHOD
If plant-level factors are not available, it is good practice to use default factors. The Tier 2 method is based on
default emission factors. These default values often represent midpoint or mean values of data sets (asdetermined by expert analysis). The extent to which they represent a specific plant’s emission rate is unknown.
Default factors in Table 3.4 should be used only in cases where plant-specific measurements are not available.
Also included in Table 3.4 are default N2O destruction factors for commonly used abatement technologies, andassociated uncertainties. To use these factors, inventory compilers should verify that the abatement technology is
installed at individual plants and operated throughout the year. Failure to determine if abatement technologies

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Chapter 3: Chemical Industry Emissions

are being used can result in overestimation of emissions. Determination of the appropriate values requires thatplants be classified according to the abatement technology implemented..

TIER 3 METHODThe Tier 3 method requires plant measurements. If the N2O abatement system is in use, plant measurements
provide the most rigorous data for calculating net emissions (i.e., N2O generation and destruction factors).
Monitoring N2O emissions from adipic acid production is practical because these are point sources and there area finite number of production plants. Given currently available technology, instrumentation for sampling andmonitoring emission rates do not limit precision or accuracy of the overall measurement. Usually sampling
frequency and timing is sufficient to avoid systematic errors and to achieve the desired level of accuracy.
Where the N2O abatement system is not in use, a plant-specific emission factor can be obtained from periodic
monitoring of emissions which is multiplied by the production level to estimate plant-level emissions.
As a general rule, it is good practice to conduct sampling and analysis whenever a plant makes any significant
process changes that would affect the generation rate of N2O, and sufficiently often otherwise to ensure that
operating conditions are constant. In addition, plant operators should be consulted annually to determine thespecific destruction technologies employed and confirm their use, since technologies may change over time.
Precise measurement of the emissions rate and abatement efficiencies requires measurement of both the exit
stream and the uncontrolled stream. Where measurement data are available only on the exit stream, goodpractice is to base emissions on these data. In this case, any available estimates of abatement efficiency should
be provided only for information purposes and not used to calculate emissions.

Figure 3.3

Decision tree for estimation of N 2 O emissions from adipic acid production
Start

Are direct
measurement data
available?

Yes

Use plant specific-emissions data
and activity data (irregular sampling
data, periodic monitoring data orcontinuous emissions monitoring) as
basis for Tier 3 method.
Box 3: Tier 3NoAre
plant- specificactivity data available on adipic
acid production?

Yes

Use plant-specific data on quantityof adipic acid produced as basis forTier 2 method.
Box 2: Tier 2

No

Is this a key
category1?

No

Use national data on adipic acidproduction or national data on
capacity, and default emission factors.
Box 1: Tier 1

Yes
Collect data for the Tier 3
or Tier 2 method.
Note:
1. See Volume 1 Chapter 4, Methodological Choice and Identification of Key Categories (noting Section 4.1.2 on limited resources), for
discussion of key categories and use of decision trees.

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TABLE 3.4
DEFAULT FACTORS FOR ADIPIC ACID PRODUCTION
Production
ProcessN2O Generation
Factora,dNitric Acid
Oxidation

300 kg/tonne
adipic acid
(uncontrolled)

Abatement
Technology

N2O Destruction
Factorb

Catalytic
Destruction

92.5%

90-95% (based on expert judgement). Manufacturers known to employ thistechnology include: BASF (Scott, 1998), and DuPont (Reimer, 1999b).

ThermalDestruction

98.5%

98-99% (based on expert judgement). Manufacturers known to employ thistechnology include: Asahi, DuPont, Bayer, and Solutia (Scott, 1998).

Recycle to
Nitric Acid

98.5%

98-99% (based on expert judgement). Manufacturers known to employ thistechnology include: Alsachemie (Scott, 1998).

Recycle tofeedstock for
Adipic Acid94%

90-98% (based on expert judgement). Solutia implemented this technology
around 2002.

Abatement
SystemUtilisation Factord

Catalytic
Destruction89%

80-98% (based on expert judgement)c.

ThermalDestruction97%

95-99% (based on expert judgement)c.

Recycle to
Nitric Acid94%

90-98% (based on expert judgement)c.

Recycle to
Adipic Acid89%

80-98% (based on expert judgement)c.

Uncertainty Estimate± 10% (based on expert judgement). The range of 300 kg ± 10%
encompasses the variability from pure ketone to pure alcohol feedstocks,
with most manufacturers somewhere in the middle.a
Uncertainty Estimate

Uncertainty EstimateaWith regard to a value from the Japan Environment Agency (1995) (282 kg N2O/tonne adipic acid), it is believed that thismanufacturer uses oxidation of pure cyclohexanol (alcohol), instead of a ketone-alcohol mixture (Reimer et al., 1999). This is the only
plant known to use this method.

b

The destruction factor (that represents the technology abatement efficiency) should be multiplied by an abatement system utility
factor.

c

Note that these default values are based on expert judgement and not industry-supplied data or plant-specific measurements. In the first
1-5 years of the abatement technology implementation, the utilisation factor tends to be at the lower end of the range. Lower utility ofthe equipment typically results because of the need to learn how to operate the abatement system and because more maintenanceproblems occur during the initial phase. After 1-5 years, the operating experience improves and the utilisation factor would tend to beat the high end of the range.

Source:Thiemans and Trogler (1991).
eReimer (1999b).
d3.4.2.3

C HOICE OF ACTIVITY DATA

It is good practice to compile production data at a level of detail that allows the use of a Tier 2 or Tier 3 method.

TIER 1 METHODThe Tier 1 method requires data on national production of adipic acid. If national-level activity data are notavailable, information on production capacity can be used. It is good practice to multiply the total national
production capacity by a capacity utilisation factor of 80 percent ± 10 percent (i.e., a range of 70-90 percent).

TIER 2 METHODThe Tier 2 method requires plant-level production data disaggregated by abatement technology type. It is goodpractice to gather activity (production) data at a level of detail consistent with that of any generation anddestruction data. Typical plant-level production data is accurate to ±2 percent due to the economic value of
having accurate information.

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TIER 3 METHOD
As with the Tier 2 method, plant-level production data disaggregated by abatement technology type are required
when emissions estimates are derived using data from irregular or periodic sampling of emissions. It is goodpractice to gather activity (production) data at a level of detail consistent with that of any generation anddestruction data. Although production is not used in the estimation of emissions where the estimate is based on
CEM, these data should be collected and reported to ensure that changes in variables that influence emissions
can be monitored over time. Typical plant-level production data is accurate to ±2 percent due to the economic
value of having accurate information.

3.4.2.4

C OMPLETENESS

Complete coverage for the adipic acid source category is straightforward because of the small number of readily
identifiable plants.

3.4.2.5

D EVELOPING A CONSISTENT TIME SERIESN2O emissions should be recalculated for all years whenever emission calculation methods are changed (e.g., if
the inventory compiler changes from the use of default values to actual values determined at the plant level). If
plant-specific data are not available for all years in the time series, it will be necessary to consider how current
plant measurements can be used to recalculate emissions for previous years. It may be possible to apply current
plant-specific emission factors to production data from previous years, provided that plant operations have notchanged substantially. Such a recalculation is required to ensure that any changes in emissions trends are realand not an artefact of changes in procedure. It is good practice to recalculate the time series according to theguidance provided in Volume 1, Chapter 5.

3.4.3
3.4.3.1

Uncertainty assessment
E MISSION FACTOR UNCERTAINTIES

Uncertainties for the default values shown in Table 3.4 are estimates based on expert judgement. In general,
adipic acid default emission factors are relatively certain because they are derived from the stoichiometry of an
intended chemical reaction (nitric acid oxidation) and N2O-specific abatement systems. The uncertainty in theemission factor for adipic acid represents a variability in N2O generation due to differences in the composition of
the cyclohexanone and cyclohexanol feedstock (i.e. ketone and alcohol) that are used by different manufacturers.
Higher ketone content results in increased N2O generation, whereas higher alcohol content results in less N2O
generation (Reimer, 1999a). Dependent on the process, based on nitric acid (HNO3) consumption an individual
plant should be able to determine the production of N2O within 1 percent. Uncertainties for the default values areshown in Table 3.4.

3.4.3.2

A CTIVITY DATA UNCERTAINTIES

Potential N2O emissions per metric tonne produced are far greater for adipic acid production than for otherindustrial sources of N2O. Measurements obtained from a properly maintained and calibrated monitoring system
can determine emissions using Equation 3.8 to within ±5 percent at the 95 percent confidence level. Given thesmall number of adipic acid plants, the uncertainty in national production data (Tier 1) is the same as for plantlevel data, namely, ±2 percent.

3.4.4
3.4.4.1

Quality Assurance/Quality Control (QA/QC),
Reporting and Documentation
Q UALITY A SSURANCE /Q UALITY C ONTROL

It is good practice to conduct quality control checks as outlined in Volume 1, Chapter 6, and an expert review ofthe emissions estimates. Additional quality control checks as outlined in Volume 1 and quality assurance
procedures may also be applicable, particularly if higher tier methods are used to determine emissions from this2006 IPCC Guidelines for National Greenhouse Gas Inventories

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Volume 3: Industrial Processes and Product Usesource category. Inventory compilers are encouraged to use higher tier QA/QC for key categories as identified inVolume 1, Chapter 4.
In addition to the guidance in Volume 1, specific procedures of relevance to this source category are outlined
below.

Comparison of emissions estimates using different approaches
If emissions are calculated using data from individual adipic acid plants (bottom-up approach), inventory
compilers should compare the estimate to emissions calculated using national production data (top-down
approach). They should record the results and investigate any unexplained discrepancies.
Since industrial N2O source categories are relatively small compared to other anthropogenic and natural sources,
it is not feasible to compare emissions with measured trends in atmospheric N2O concentrations.

Plant-level data
Inventory compilers should archive sufficient information to allow an independent review of the time series ofemissions beginning in the base year, and to explain trends in emissions when making historical comparisons.
This is particularly important in cases where recalculations are necessary, for example, when an inventory
compiler changes from using default values to actual values determined at the plant level.

Revision of direct emission measurements
If plant-level N2O measurements are available, it is suggested that inventory compilers confirm thatinternationally recognised, standard methods were used. If the measurement practices fail this criterion, then theyshould evaluate the use of these emissions data. In addition, they should reconsider the uncertainty estimates inlight of the QA/QC results.
Inventory compilers are encouraged to compare plant-based factors to the IPCC defaults to ensure that the plantspecific factors are reasonable. They should explain and document any differences between plant-specific factors
and default factors, particularly any differences in plant characteristics that might lead to these differences.

3.4.4.2

R EPORTING AND D OCUMENTATION

It is good practice to document and archive all information required to produce the national emissions inventory
estimates as outlined in Volume 1, Section 6.11.
Some examples of specific documentation and reporting relevant to this source category are provided below:•

Description of the method used;•

Number of adipic acid plants;•

Emission factors;•

Production data;•

Production capacity;•

Number of plants using abatement technology;•

Type of abatement technology, destruction efficiency, and utilisation;•

Any other assumptions.

Plant operators should supply this information to the inventory compiler for compilation, and also archive theinformation at the site. Plant operators should also log and archive the measurement frequencies andinstrumental calibration records where actual plant measurements are made.
Where there are only one or two producers in a country, as could often be the case for adipic acid production,
activity data may be considered confidential. In this case, operators and the inventory compiler should determine
the level of aggregation at which information can be reported while still protecting confidentiality. Detailed
information including instrumentation records should still be archived at the plant level.
It is not practical to include all documentation in the national inventory report. However, the inventory should
include summaries of methods used and references to source data such that the reported emissions estimates aretransparent and steps in their calculation may be retraced.

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3.5

CAPROLACTAM, GLYOXAL AND GLYOXYLICACID PRODUCTION

3.5.1

Introduction

This section addresses the production of three chemicals - caprolactam, glyoxal, and glyoxylic acid - that arepotentially important sources of nitrous oxide (N2O) emissions in the countries in which the chemicals areproduced. The methodology for caprolactam is discussed in detail and is suitable for application to estimation ofemissions from glyoxal and glyoxylic acid. In Section 3.5.3, the production processes for glyoxal and glyoxylic
acid that give rise to emissions of N2O are outlined. Default generation factors, destruction factors, and emission
factors are provided based on information from Clariant (France) (Babusiaux, 2005).

3.5.2

Caprolactam

Almost all of the annual production of caprolactam (C6H11NO) is consumed as the monomer for nylon-6 fibres
and plastics (Kirk-Othmer, 1999; p.310), with a substantial proportion of the fibre used in carpet manufacturing.
All commercial processes for the manufacture of caprolactam are based on either toluene or benzene.

3.5.2.1

M ETHODOLOGICAL ISSUES

Where caprolactam is produced from benzene, the main process, the benzene is hydrogenated to cyclohexane
which is then oxidised to produce cyclohexanone (C6H10O). The classical route (Raschig process) and basic
reaction equations for production from cyclohexanone are (Reimschuessel, 1977; p.83: Lowenheim and Moran,
1975; p. 201):
Oxidation of NH3 to NO/NO2↓
NH3 reacted with CO2/H2O to yield ammonium carbonate (NH4)2CO3↓(NH4)2CO3 reacted with NO/NO2 (from NH3 oxidation) to yield ammonium nitrite (NH4NO2)↓
NH3 reacted with SO2/H2O to yield ammonium bisulphite (NH4HSO3)↓
NH4NO2 and NH4HSO3 reacted to yield hydroxylamine disulphonate (NOH(SO3NH4)2)↓
NOH(SO3NH4)2 hydrolised to yield hydroxylamine sulphate (NH2OH)2.H2SO4) and ammonium
sulphate ((NH4)2SO4)↓
Cyclohexanone reaction:
C6H10O + ½(NH2OH)2.H2SO4 (+NH3 and H2SO4) → C6H10NOH + (NH4)2SO4 + H2O
Beckmann rearrangement:
C6H10NOH (+H2SO4 and SO2) → C6H11NO.H2SO4 (+4NH3 and H2O) → C6H11NO + 2(NH4)2SO4
Lowenheim and Moran (1975; p. 202) summarise the Raschig production process as follows. Caprolactam is
produced via Beckmann rearrangement (conversion of a ketone oxime into an amide, usually using sulphuricacid as a catalyst) by the addition of hydroxylamine sulphate to cyclohexanone. Hydroxylamine sulphate is
produced from ammonium nitrate and sulphur dioxide. Ammonia gas and air are fed to a converter whereammonia is converted to hydroxylamine disulphonate by contacting it with ammonium carbonate and sulphur
dioxide in series. Ammonium carbonate is produced by dissolving ammonia and carbon dioxide in water, andsulphur dioxide by burning sulphur. The disulphonate is hydrolysed to hydroxylamine sulphate and ammonium
sulphate. The addition of hydroxylamine sulphate to cyclohexanone produces cyclohexanone oxime which isconverted to caprolactam by the Beckmann rearrangement.

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Production of caprolactam can give rise to emissions of nitrous oxide (N2O) from the ammonia oxidation step,
emissions of CO2 from the ammonium carbonate step, emissions of sulphur dioxide (SO2) from the ammonium
bisulphite step, and emissions of NMVOCs. Emissions of CO2, SO2 and NMVOCs from the conventional
process are unlikely to be significant in well-managed plants. The main greenhouse gas to be accounted for from
caprolactam production is N2O. Modified caprolactam production processes are primarily concerned withelimination of the high volumes of ammonium sulphate that are produced as a by-product of the conventional
process (Reimschuessel, 1977; p.84). NH3 oxidation remains an integral part of all processes to obtain the
NO/NO2 required.

CHOICE OF METHOD
Estimation of emissions of N2O from caprolactam production can be treated as analogous to estimation ofemissions of N2O from nitric acid production. Both production processes involve an initial step of NH3 oxidation
which is the source of N2O formation and emissions.
The choice of good practice method depends on national circumstances. The decision tree in Figure 3.4
describes good practice in adapting the methods to national circumstances. Emissions can be estimated fromcontinuous emissions monitoring (CEM) where emissions are directly measured at all times, periodic emissions
monitoring that is undertaken over a period(s) that is reflective of the usual pattern of operation of the plant toderive an emission factor that is multiplied by output to derive emissions, irregular sampling to derive anemission factor that is multiplied by output to derive emissions, or by multiplying a default emission factor by
output.
Methods are classified according to the extent of plant-level data that are available. Both Tier 2 and Tier 3 arerequire plant-level activity data.

Tier 1 method
Emissions are estimated as follows:
EQUATION 3.9
N2O EMISSIONS FROM CAPROLACTAM PRODUCTION – TIER 1
E N 2O = EF • CP
Where:
EN2O = N2O emissions, kg
EF = N2O emission factor (default), kg N2O/tonne caprolactam produced
CP = caprolactam production, tonnes
When applying the Tier 1 method it is good practice to assume that there is no abatement of N2O emissions andto use the highest default emission factor shown in Table 3.5.

Tier 2 method
Information on emissions arising from caprolactam production and control technologies is limited. Where plantlevel information is not available, good practice provides default N2O generation factors as shown in Table 3.5.
The default factors are based on N2O emissions from nitric acid plants because there is no information on
caprolactam plants and the initial reaction step of oxidation of ammonia is similar for both processes. Good
practice encourages the development of factors specific to caprolactam plants.
The number of caprolactam plants is relatively small (approximately 42 plants with around 19 plants using DSM(Stamicarbon) technology). It is unlikely that there are substantial variations in the N2O generation factors
between plants. Where default values are used to estimate emissions from caprolactam production, it is goodpractice to ascertain the extent to which plant emissions vary according to type and to use an appropriate N2O
generation factor.
The Tier 2 method uses plant-level production data disaggregated by technology type and default emission
factors classified by technology type. Emissions are calculated as follows:

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EQUATION 3.10
N2O EMISSIONS FROM CAPROLACTAM PRODUCTION – TIER 2[(

E N 2O = ∑ EFi • CPi • 1 − DF j • ASUF j
i, j

)]

Where:
EN2O = emissions of N2O, kg
EFi = N2O emission factor for technology type i, kg N2O/tonne caprolactam produced
CPi = caprolactam production from technology type i, tonnes
DFj = destruction factor for abatement technology type j, fraction
ASUFj = abatement system utilisation factor for abatement technology type j, fraction
The basic equation for estimating N2O emissions includes additional terms that recognise current and thepotential future use of N2O abatement technologies. The N2O destruction factor has to be multiplied by anabatement system utilisation factor in order to account for any down-time of the emission abatement equipment(i.e. time the equipment is not operating).
Where plant-level information is not available, good practice provides default N2O generation factors as shownin Table 3.5, Default Factors for Caprolactam Production, based on plant types classified by age. To achieve thehighest accuracy, good practice is to apply Equation 3.10 at the plant-level taking into account N2O generationand destruction factors developed from plant-specific measurement data. In this case, the national total is equal
to the sum of plant totals.

Tier 3 method – direct measurement
The Tier 3 method uses plant level production data and plant-level emission factors obtained from direct
measurement of emissions. These may be derived from irregular sampling of emissions of N2O or periodic
emissions monitoring of N2O undertaken over a period(s) that reflects the usual pattern of operation of the plant.
Emissions can be derived using Equation 3.10.
Alternatively, the Tier 3 method uses the results of continuous emissions monitoring (CEM), although it is notedthat most plants are unlikely to employ CEM due to the resource costs. Where CEM is employed, emissions canbe estimated based on the sum of measured N2O emissions derived from the concentration of N2O in monitored
emissions for each recorded monitoring interval.

CHOICE OF EMISSION FACTORS
Tier 1 method
It is good practice to use the emission factor shown in Table 3.5 and to assume that there is no abatement of N2Oemissions.

Tier 2 method
If plant-level factors are not available, it is good practice to use default factors. The Tier 2 method uses a default
factor. Default values often represent midpoint or mean values of data sets (as determined by expert analysis).
The extent to which they represent a specific plant’s emission rate is unknown. This is especially true forcaprolactam production where the value is based on high pressure nitric acid plants. Default factor in Table 3.5
should be used only in cases where plant-specific measurements are not available.

Tier 3 method
Plant measurements provide the most rigorous data for calculating net emissions (i.e., N2O generation anddestruction factors). Monitoring N2O emissions from caprolactam production is practical because these are point
sources and there are a finite number of production plants. Given currently available technology, instrumentation
for sampling and monitoring emission rates do not limit precision or accuracy of the overall measurement.
Usually sampling frequency and timing is sufficient to avoid systematic errors and to achieve the desired level ofaccuracy.
As a general rule, it is good practice to conduct sampling and analysis whenever a plant makes any significant
process changes that would affect the generation rate of N2O, and sufficiently often otherwise to ensure that
operating conditions are constant. In addition, plant operators should be consulted annually to determine thespecific destruction technologies employed and confirm their use, since technologies may change over time.
Precise measurement of the emissions rate and abatement efficiencies requires measurement of both the exit

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stream and the uncontrolled stream. Where measurement data are available only on the exit stream, goodpractice is to base emissions on these data. In this case, any available estimates of abatement efficiency should
be provided only for information purposes and not used to calculate emissions.
TABLE 3.5
DEFAULT FACTOR FOR CAPROLACTAM PRODUCTION
Production Process

N2O Emission Factor(kg N2O/tonne caprolactam)

Raschiga

Uncertainty

9.0a

± 40%

Based on high pressure plants for nitric acid production.

Source: Default Factors for Nitric Acid Production. (See Table 3.3 in this chapter.)Figure 3.4

Decision tree for estimation of N 2 O emissions from caprolactam, glyoxal or
glyoxylic acid production
Start

Are direct
measurement data
available?

Use plant specific-emissions data
and activity data (irregular sampling
data, periodic monitoring data orcontinuous emissions monitoring) as
basis for Tier 3 method.

Yes

Box 3: Tier 3NoAre
plant-specific activity
data available on caprolactam,
glyoxal or glyoxylic acidproduction?

Yes

Use plant-specific data on quantity ofcaprolactam, glyoxal or glyoxylic acidproduced as basis for Tier 2 method.
Box 2: Tier 2

No

Is Caprolactam,
Glyoxal and Glyoxylic
Acid Production a key category1,
and is this a significant
subcategory?

No

Use national data on caprolactam,
glyoxal or glyoxylic acid production
or national data on capacity, anddefault emission factors.
Box 1: Tier 1

Yes
Collect data for the Tier 3
or Tier 2 method.
Note:
1. See Volume 1 Chapter 4, Methodological Choice and Identification of Key Categories (noting Section 4.1.2 on limited resources), for
discussion of key categories and use of decision trees.

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Chapter 3: Chemical Industry Emissions

CHOICE OF ACTIVITY DATA
It is good practice to compile production data at a level of detail that allows the use of Tier 2 or Tier 3 method.

Tier 1 method
The Tier 1 method requires data on national production of caprolactam. If national-level activity data are notavailable, information on production capacity can be used. It is good practice to multiply the total national
production capacity by a capacity utilisation factor of 80 percent ± 20 percent (i.e., a range of 60-100 percent).

Tier 2 method
The Tier 2 method requires plant-level production data disaggregated by the age the plant. If additional
information on technology type and abatement technology is available, it is good practice to collect thisinformation and disaggregate production data according to the information obtained. That is, it is good practiceto gather activity (production) data at a level of detail consistent with that of generation and destruction data.
Where plant-level emission factors are used, good practice is to collect plant-level production data. Typicalplant-level production data are accurate to ±2 percent due to the economic value of having accurate information.

Tier 3 method
The Tier 3 method require plant-level production data disaggregated by technology type when emissions
estimates are derived using data from irregular or periodic sampling of emissions. It is good practice to collectactivity (production) data at a level of detail consistent with that of any generation and destruction data.
Although production is not used in the estimation of emissions where the estimate is based on CEM, these data
should be collected and reported to ensure that changes in variables that influence emissions can be monitored
over time. Typical plant-level production data are accurate to ±2 percent due to the economic value of having
accurate information.

COMPLETENESS
Complete coverage requires accounting for all plants and emissions of all direct greenhouse gases. In addition to
N2O, there may be non-combustion emissions of CO2, NOx, NMVOCs and SO2. In order to include emissions of
the indirect greenhouse gases (NOx, NMVOCs and SO2), see guidance provided in Chapter 7 of Volume 1:
General Guidance and Reporting. Plant-level information will be required to enable emissions estimation. Over
time default values could be developed as more information becomes available.
There will be few caprolactam plants in a country, and it is suggested that emissions are calculated from plant
specific data.

DEVELOPING A CONSISTENT TIME SERIESN2O emissions should be recalculated for all years whenever emission calculation methods are changed (e.g., if
the inventory compiler changes from the use of default values to actual values determined at the plant level). If
plant-specific data are not available for all years in the time series, it will be necessary to consider how current
plant measurements can be used to recalculate emissions for previous years. It may be possible to apply current
plant-specific emission factors to production data from previous years, provided that plant operations have notchanged substantially. Such a recalculation is required to ensure that any changes in emissions trends are realand not an artefact of changes in procedure. It is good practice to recalculate the time series according to theguidance provided in Volume 1, Chapter 5.

3.5.2.2

U NCERTAINTY ASSESSMENTEMISSION FACTOR UNCERTAINTIES
Uncertainties for the default value shown in Table 3.5 is an estimate based on default values for nitric acid plants.
In general, default emission factors for gaseous substances have higher uncertainties because mass values forgaseous substances are influenced by temperature and pressure variations and gases are more easily lost throughprocess leaks. The default values for caprolactam production have a relatively high level of uncertainty due tothe limited information available. It is good practice to obtain uncertainty estimates at the plant-level whichshould be lower than uncertainty values associated with default values.

ACTIVITY DATA UNCERTAINTIES
Where activity data are obtained from plants, uncertainty estimates can be obtained from producers. Data that are
obtained from national statistical agencies usually do not include uncertainty estimates. It is good practice toconsult with national statistical agencies to obtain information on any sampling errors. Where national statistical2006 IPCC Guidelines for National Greenhouse Gas Inventories

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Volume 3: Industrial Processes and Product Useagencies collect data from the population of nitric acid production facilities, uncertainties in national statistics
are not expected to differ from uncertainties established from plant-level consultations. Where uncertainty values
are not available from other sources, a default value of ±2 percent can be used.

3.5.2.3

Q UALITY A SSURANCE /Q UALITY C ONTROL (QA/QC),R EPORTING AND D OCUMENTATIONQUALITY ASSURANCE/QUALITY CONTROL
It is good practice to conduct quality control checks as outlined in Volume 1, Chapter 6. More extensive quality
control checks and quality assurance procedures are applicable if higher tier methods are used to determine
emissions. Inventory compilers are encouraged to use higher tier QA/QC for key categories as identified inVolume 1, Chapter 4.

Comparison of emissions estimates using different approaches
If emissions are calculated using data from individual caprolactam plants (bottom-up approach), inventory
compilers should compare the estimate to emissions calculated using national production data (top-down
approach). They should record the results and investigate any unexplained discrepancies.
Since industrial N2O source categories are relatively small compared to other anthropogenic and natural sources,
it is not feasible to compare emissions with measured trends in atmospheric N2O concentrations.

Plant-level data
Inventory compilers should archive sufficient information to allow an independent review of the time series ofemissions beginning in the base year, and to explain trends in emissions when making historical comparisons.
This is particularly important in cases where recalculations are necessary, for example, when an inventory
compiler changes from using default values to actual values determined at the plant level.

Revision of direct emission measurements
If plant-level N2O measurements are available, inventory compilers should confirm that internationallyrecognised, standard methods were used. If the measurement practices fail this criterion, then they should
evaluate the use of these emissions data. In addition, they should reconsider the uncertainty estimates in light of
the QA/QC results.
Inventory compilers should compare plant-based factors to the IPCC defaults to ensure that the plant-specificfactors are reasonable. They should explain and document any differences between plant-specific factors anddefault factors, particularly any differences in plant characteristics that might lead to these differences.

REPORTING AND DOCUMENTATION
It is good practice to document and archive all information required to produce the national emissions inventory
estimates as outlined in Volume 1, Section 6.11.
Some examples of specific documentation and reporting relevant to this source category are provided below:•

Description of the method used;•

Number of caprolactam plants;•

Emission factors;•

Production data;•

Production capacity;•

Number of plants using abatement technology;•

Type of abatement technology, destruction efficiency, and utilisation;•

Any other assumptions.

Plant operators should supply this information to the inventory compiler for compilation, and also archive theinformation at the site. Plant operators should also log and archive the measurement frequencies andinstrumental calibration records where actual plant measurements are made.
Where there are only one or two producers in a country as will be the case for caprolactam producers, activity
data may be considered confidential. In this case, operators and the inventory compiler should determine the

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level of aggregation at which information can be reported while still protecting confidentiality. Detailed
information including instrumentation records should still be archived at the plant level.
It is not practical to include all documentation in the national inventory report. However, the inventory should
include summaries of methods used and references to source data such that the reported emissions estimates aretransparent and steps in their calculation may be retraced.

3.5.3

Glyoxal and glyoxylic acid production

Glyoxal (ethanedial) (C2H2O2) is produced from oxidation of acetaldehyde (ethanal) (C2H4O) with concentrated
nitric acid (HNO3). Glyoxal can also be produced from catalytic oxidation of ethylene glycol (ethanediol)(CH2OHCH2OH). Glyoxal is used as a crosslinking agent for vinyl acetate/acrylic resins, disinfectant, gelatine
hardening agent, textile finishing agent (permanent-press cotton, rayon fabrics), wet-resistance additive (paper
coatings) (Ashford, 1994; p.454).
Glyoxylic acid is produced by nitric acid oxidation of glyoxal. Glyoxylic acid is used for the production ofsynthetic aromas, agrochemicals and pharmaceutical intermediates (Babusiaux, 2005; p.1).
The basic reaction equation for the production of glyoxal from acetaldehyde is:
2C2H4O (Acetaldehyde) + 2HNO3 → 2C2H2O2 (Glyoxal) + N2O + 3 H2O
The stoichiometric relationship indicates that complete reaction will result in 0.379 tonnes of N2O per tonne ofglyoxal. Under commercial conditions, the yield of N2O per tonne of glyoxal is approximately 0.52 tonnes(Babusiaux, 2005; p.1).
Glyoxylic acid production is a batch process where nitric acid is reduced to NO and N2O with NO recovered as
HNO3 in the process. N2O arises in the production process through a secondary reaction where glyoxal isconverted to oxalic acid (COOH)2.
Default factors for glyoxal and glyoxylic acid production are shown in Table 3.6. Emissions can be estimatedusing the same approach as described in the foregoing for caprolactam. To use default destruction factors,
inventory compilers should verify that the abatement technology is installed at individual plants and operated
throughout the year.
TABLE 3.6
DEFAULT FACTORS FOR GLYOXAL AND GLYOXYLIC ACID PRODUCTION
Product

N2O Generation Factor(tonnes N2O/tonne)

N2O Destruction Rate(%)

N2O Emission Factor(tonnes N2O/tonne)

Uncertainty(%)

Glyoxal

0.52

80

0.10

±10

Glyoxylic acid

0.10

80

0.02

±10

Source: Babusiaux (2005)

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3.6

CARBIDE PRODUCTION

3.6.1

Introduction

Greenhouse gas emissions are associated with production of silicon carbide (SiC) and calcium carbide (CaC2).
The production of carbide can result in emissions of carbon dioxide (CO2), methane (CH4), carbon monoxide(CO) and sulphur dioxide (SO2). Silicon carbide is a significant artificial abrasive. It is produced from silica sandor quartz and petroleum coke. Calcium carbide is used in the production of acetylene, in the manufacture of
cyanamide (a minor historical use), and as a reductant in electric arc steel furnaces. It is made from two carboncontaining raw materials: calcium carbonate (limestone) and petroleum coke.
Use of carbon-containing raw materials in the production processes result in emissions of CO2 and CO. The
presence of hydrogen-containing volatile compounds and sulphur (S) in the petroleum coke may cause formationand emission to the atmosphere of CH4 and SO2.

3.6.2

Methodological issues

CO 2 AND CH 4 FROM SILICON CARBIDE PRODUCTION
Silicon carbide is produced from silica sand or quartz and petroleum coke, which is used as a carbon source,
according to the reactions (Austin, 1984; p. 262):
SiO2 + 2C → Si + 2CO
Si + C → SiC
The formula describing the overall reaction is given below but in practice it does not proceed in the
stoichiometric proportions indicated:
SiO2 + 3C → SiC + 2CO (+ O2 → 2CO2)
In the production process, silica sand and carbon are mixed in an approximate molar ratio of 1:3. Some carbon,
about 35 percent, is contained in the product and the rest is converted to CO2 in excess oxygen and released tothe atmosphere as a process by-product.
The petroleum coke used in this process may contain volatile compounds, which will form methane. Somemethane will escape to the atmosphere, particularly during start-up.

CO 2 FROM CALCIUM CARBIDE PRODUCTION
Calcium carbide (CaC2) is made by heating calcium carbonate (limestone) and subsequently reducing CaO withcarbon e.g., petroleum coke. Both steps lead to emissions of CO2. Around 67 percent of the carbon frompetroleum coke will be contained in the product.
The basic reactions are:
CaCO3 → CaO + CO2
CaO + 3C → CaC2 + CO (+ ½ O2 → CO2)
The CO gas will be used as an energy source in most plants.

BOX 3.4
DOUBLE COUNTING

To avoid double counting, CO2 emission from combusting CO gas generated in the process of
CaC2 production should be accounted in the IPPU Sector, and should not be included in the
Energy Sector. Petroleum coke used in the production process should be deducted from theEnergy Sector as a non-energy use of petroleum coke.

The most important application of calcium carbide is producing acetylene (C2H2) by reacting CaC2 with water. A
substantial use of acetylene is welding applications. Acetylene is also used in chemical synthesis for the

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production of acetaldehyde, acetic acid, acetic anhydride, and as a feedstock to manufacture ‘acetylene black’, aform of carbon black. Frequently, acetylene is not produced within the same plant that produces CaC2 and thisneeds to be taken into account when applying higher tier methods to estimating CO2 emissions from CaC2 use.
Use of acetylene in chemical synthesis and production of acetylene black results in carbon contained in the
products reducing the total emissions of CO2 that are related to CaC2 use. Acetylene may be produced frompartial oxidation of natural gas as well as from CaC2. The approach to accounting for acetylene in these uses isoutlined in Section 3.9 of this volume.
Production and use of acetylene for welding applications is summarised by reaction:
CaC2 + 2H2O → Ca(OH)2 + C2H2 (+ 2.5O2 → 2CO2 + H2O)
Where acetylene is used in welding applications, emissions can be derived from the quantity of CaC2 used in the
production of this acetylene on the assumption that the acetylene will be used in a relatively short period of timeafter production.

BOX 3.5
ALLOCATION OF EMISSIONS FROM CaO PRODUCTION

CaO (lime) might be produced in-house or at a plant other than the carbide plant. In either case, theemissions from the CaO step should be reported as emissions from lime production (Section 2.3 ofthis volume) and only the emissions from reaction of CaO with petroleum coke and use of the
product to produce acetylene for welding applications should be reported as emissions from
calcium carbide.

3.6.2.1

C HOICE OF METHOD

Methods are classified according the extent of plant-level data that are available. The Tier 1 method is based on
default values and national statistics. Tier 2 is based on plant-level data on production and use of CaC2 inacetylene production for welding applications. The Tier 3 method is based on plant-level data on petroleum coke
input (including the carbon content factor (CCF) and carbon oxidation factor (COF) if available; alternatively,
country specific Energy Sector values may be used), use of CaC2 in acetylene production for welding
applications, and plant-level emission factors where relevant.
Both Tier 2 and Tier 3 are based on plant-level activity data. The choice of method to estimate emissions of CO2
and CH4 depends on national circumstances as shown in Figure 3.5.

CO 2 AND CH 4 FROM CARBIDE PRODUCTION
Tier 1 method
Emissions from carbide production can be estimated from activity data (AD) on petroleum coke consumption or
carbide production, calcium carbide used in the production of acetylene used in welding applications, and default
emission factors. Where AD on petroleum coke consumption are used the CCF and COF of the petroleum cokecan be obtained from Volume 2, Chapter 1 and the result must be multiplied by 44/12 to convert C to CO2. The
basic equation for estimating emissions is:
EQUATION 3.11
EMISSIONS FROM CARBIDE PRODUCTION
ECO 2 = AD • EF
Where:
ECO2 = emissions of CO2, tonnes
AD = activity data on petroleum coke consumption or carbide production, tonnes raw material used or
tonnes carbide produced
EF = CO2 emission factor. There are two options as follows:
When carbide production is used as activity data, EF should be average CO2 emissions per unit ofoutput for carbide production, tonnes CO2/tonne carbide production.
When petroleum coke consumption is used as activity data, EF should be CCF (carbon content

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factor) multiplied by COF (carbon oxidation factor) multiplied by 44/12 and adjusted to account for
the C contained in the product, tonnes CO2/tonne material used
Adjustment factor for SiC = 0.35 ⇒ Emission factor = 0.65 • CCF • COF • 44/12;
Adjustment factor for CaC2 = 0.67 ⇒ Emission factor = 0.33 • CCF • COF • 44/12.
Equation 3.11 can also be used to estimate CH4 emissions, where EF is the appropriate emission factor for CH4.
Estimation of emissions from CaC2 needs to include emissions of CO2 indirectly attributable to CaC2 that is usedin acetylene production. Equation 3.11 can be applied where AD is the amount of CaC2 used and EF is theemission factor associated with this use. Under the Tier 1 method it is good practice to assume that all CaC2 usedin acetylene production gives rise to CO2 emissions.

Tier 2 method
The Tier 2 method uses plant-level data on production of carbide and the amount of C contained in the product.
For CaC2, data on the use of CaC2 for the production of acetylene used in welding applications is also required.
Emissions from production and use can be estimated with Equation 3.11 using default emission factors. Where
acetylene is produced from CaC2 at another location and the quantity of CaC2 used for this purpose is not known,
it is good practice to document this fact.

Tier 3 method
The Tier 3 method requires plant-level data on the petroleum coke input along with the CCF and COF if
available; alternatively, country specific Energy Sector values for CCF and COF may be used. Plant-level dataon the amount of C contained in the product are also required.
In the case of CaC2, data on the use of CaC2 for the production of acetylene used in welding applications are
required, as are plant-level emission factors. Where acetylene is produced from CaC2 at another location and thequantity of CaC2 used for this purpose is not known, it is good practice to document this fact. In addition, plantlevel emission factors for CH4 need to be collected. Equation 3.11 can be applied to estimate emissions for eachplant and total national emissions are the sum of these estimates.
Production data are not used in the calculation but should be collected for reporting purposes. Where acetylene
production data cannot be disaggregated by use, national inventory compilers using the Tier 3 method areencouraged to account for any emissions at the point where they arise; for example, emissions from acetylene
use in welding applications should be accounted for at the point of use of acetylene using a country specificemission factor. A similar approach should be followed for other uses of acetylene.

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Figure 3.5

Decision tree for estimation of CO 2 and CH 4 emissions from carbide
production
Start

Are
plant-level
data available on the
petroleum coke
input1?

Yes

Use the plant-specific coke consumption
data including C content and percent
oxidised, along with plant-specificCH4 emission factor as basis for the
Tier 3 method.
Box 3: Tier 3NoAre
plant-level carbide
production data
available?

Yes

Calculate emissions using plant-level
data on production of carbide and plantspecific emission factors. For the plants
where plant-specific emission factors are
not available, use default emission factors.
Box 2: Tier 2

No

Is this a key
category2?

No

Use national aggregate input data, national
production data or production capacity data
and default emission factors to calculate
emissions.
Box 1: Tier 1

Yes
Collect data for the Tier 3
or Tier 2 method.
Note:
1. "Input data" means raw material consumption data.
2. See Volume 1 Chapter 4, Methodological Choice and Identification of Key Categories (noting Section 4.1.2 on limited resources), for
discussion of key categories and use of decision trees.

3.6.2.2

C HOICE OF EMISSION FACTORS

Tier 1 method
The Tier 1 method uses default values for CCF, COF and C contained in the product where petroleum coke isused in the estimation. Alternatively, where carbide production is used, the method uses default emission factors
shown in Tables 3.7 and 3.8 where relevant. In both cases, the default factor for CaC2 use is applied.

Tier 2 method
As for the Tier 1 method, the Tier 2 method uses default emission factor values except for the amount of C
contained in the product, where plant-level data are required.

Tier 3 method
The Tier 3 method requires plant-level data for all variables except for CCF and COF of the petroleum coke
where country specific Energy Sector values may be used. This includes plant-level emission factors for lime if
it is produced in-house and plant-level emission factors for CaC2 used to produce acetylene for welding
applications.

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CO 2 from silicon carbide productionMore carbon is needed in the silicon carbide production process than calculated from a stoichiometric reaction.
The excess carbon is oxidised during the process, little is left as ash (Raaness, 1991). Typical default values for
Norwegian plants for carbon content in coke are 97 percent and for carbon contained in product, 35 percent. Thisimplies a typical emission factor of 2.3 tonnes CO2/tonne petroleum coke used (IPCC, 1997), or 2.62 tonnes
CO2/tonne carbide produced.

CH 4 f rom silicon carbide production
Measurements at Norwegian plants suggest emission factors of 10.2 kg CH4/tonne petroleum coke or 11.6 kg
CH4/tonne carbide produced (IPCC, 1997).
TABLE 3.7
DEFAULT FACTORS FOR CO2 AND CH4 EMISSIONS FROM SILICON CARBIDE PRODUCTION
Process

Silicon carbide
production

Emission Factor(tonnes CO2/tonne
raw material used)

Emission Factor(kg CH4/tonne raw
material used)

Emission Factor(tonnes CO2/tonne
carbide produced)

Emission Factor(kg CH4/tonne
carbide produced)

2.30

10.2

2.62

11.6

Source: Revised 1996 IPCC National Greenhouse Gas Inventories, Vol.3, p.2.21 (IPCC, 1997)

CO 2 from calcium carbide production
Emission factors may be derived from the use of raw materials (petroleum coke) and from carbide production
using a mass-balance approach. Limestone used in carbide manufacture contains about 98 percent CaCO3 and isaccounted for elsewhere. 1 750 kg limestone (or 950 kg CaO), 640 kg of petroleum coke and 20 kg carbon
electrodes are required to produce 1 tonne of carbide.
The default emission factors for estimating emissions are included in Table 3.8.
TABLE 3.8
EMISSION FACTORS FOR CO2 EMISSION FROM CALCIUM CARBIDE PRODUCTION AND USE
Process
Petroleum coke use
Use of product

Default Emission Factor(tonnes CO2/tonne raw material used)

Default Emission Factor(tonnes CO2/tonne carbide produced)

1.70

1.090

not relevant

1.100

Source: Revised 1996 IPCC National Greenhouse Gas Inventories, Vol.3, p.2.22 (IPCC, 1997)

The theoretical emission factor calculated from a stoichiometric reaction is lower for the petroleum coke stepthan that shown in the table. Excess carbon is oxidised in the process and the suggested emission factors were
calculated from the actual use of raw materials in a Norwegian plant. The emission factor for acetylene use iscalculated from the actual (not stoichiometric) carbon content of carbide.
The CO2 emissions may be lowered by utilising the gas when producing dicyanodiamide from carbide (Olsen,
1991).

3.6.2.3

C HOICE OF ACTIVITY DATA

Tier 1 method
The Tier 1 method requires data on petroleum coke used in carbide production or national production of carbide.
These data may be obtained from national statistics or from industrial and trade organizations representing
carbide and petroleum coke producers.

Tier 2 method
Activity data required for the Tier 2 method comprise plant-level data on carbide produced and the amount of
CaC2 used in the production of acetylene for welding applications.

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Tier 3 method
The Tier 3 method requires plant-level activity data for all variables including the petroleum coke input and
CaC2 used to produce acetylene for welding applications.
The Tier 2 methods require the collection of activity data from individual plants or companies. In Tier 1 theactivity data provided by national statistics or by industrial and trade organizations associated with carbide andpetroleum coke production should be used. However, if sufficient plant-specific or company-specific data are
available, they may be used to estimate emissions.

3.6.2.4

C OMPLETENESS

Carbide production plants are generally known in each country. As a result, carbide production data may beavailable in national statistical databases, or could be collected, even if these data have not been published innational statistics. The petroleum coke consumption data may be obtained directly from carbide production
plants, or from coke producers and traders. Activity data and emissions estimation is complicated by the fact thatacetylene produced from CaC2 is not necessarily produced at the same plant that produces the CaC2. This needs
to be accounted for when using the higher tier methods, with emissions originating from the use of CaC2
accounted at the point where the emissions occur; for example, in the case of acetylene used in welding
applications, where the acetylene is produced at a different location to the CaC2 emissions should be accounted
for at the point of production of the acetylene on the assumption that it will be used in a short time after
production.
Application of the Tier 2 and 3 methods assumes the bottom-up (plant by plant) estimation of emissions andplant-level data collection. In countries where only a subset of plants report data for the Tier 3 method or where
there is a transition from Tier 2 to Tier 3, it may not be possible to report emissions using Tier 3 for all facilities
during the transition. Where data for the Tier 3 method are not available for all plants, Tier 2 could be used forthe remaining plants. Also, where data for the Tier 2 method are reported by only a subset of plants or where
there is a transition from Tier 1 to Tier 2, it may be possible to determine the share of production represented by
non-reporting plants and use this information to estimate the remaining emissions using Tier 1 in order to ensurecompleteness during the transition period.

3.6.2.5

D EVELOPING A CONSISTENT TIME SERIESIt is good practice to estimate emissions from carbide production using the same method for every year in thetime series. Where data are unavailable to support a more rigorous method for all years in the time series, it isgood practice is to recalculate these gaps according to the guidance provided in Volume 1, Chapter 5.

3.6.3
3.6.3.1

Uncertainty assessment
E MISSION FACTOR U NCERTAINTIESIn general, the default CO2 emission factors are relatively uncertain because industrial-scale carbide production
processes differ from the stoichiometry of theoretical chemical reactions. The uncertainty in the emission factors
for CH4 is due to the possible variations in the hydrogen-containing volatile compounds in the raw material(petroleum coke) that are used by different manufacturers and due to the possible variations in production
process parameters. Where uncertainty values are not available from other sources, a default value of ±10
percent can be used.
It is good practice to obtain uncertainty estimates at the plant level which should be lower than uncertainties
associated with default values.

3.6.3.2

A CTIVITY DATA UNCERTAINTIES

Where activity data are obtained directly from plants, uncertainty estimates can be obtained from producers. This
will include uncertainty estimates for petroleum coke and limestone used and for carbide production data. Data
that are obtained from national statistical agencies or from industrial and trade organizations usually do notinclude uncertainty estimates. It is good practice to consult with national statistical agencies to obtain
information on any sampling errors. Where national statistic agencies collect carbide production data fromproduction facilities, uncertainties in national statistics are not expected to differ from uncertainties estimated2006 IPCC Guidelines for National Greenhouse Gas Inventories

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Volume 3: Industrial Processes and Product Usefrom plant-level consultations. Where uncertainty values are not available from other sources, a default value of±5 percent can be used.

3.6.4
3.6.4.1

Quality Assurance/Quality Control (QA/QC),
Reporting and Documentation
Q UALITY A SSURANCE /Q UALITY C ONTROL

It is good practice to conduct quality control checks as outlined in Volume 1, Chapter 6, and an expert review ofthe emission estimates. More extensive quality control checks and quality assurance procedures may be
applicable, particularly if higher tier methods are used to determine emissions from this source category.
Inventory compilers are encouraged to use higher tier QA/QC for key categories as identified in Volume 1,
Chapter 4.
In addition to the guidance given in Volume 1, specific procedures of relevance to this source category are
outlined below.

Comparison of emission estimates using different approaches
If the Tier 2 (plant-specific) method is used, then inventory compilers should compare the emission estimates tothe estimates calculated using national level activity data (Tier 1). The inventory compilers are also encouraged
to compare the emission estimates calculated using different modifications of the same methods.
The results of such comparison should be recorded for internal documentation, including explanation for any
discrepancies.

Review of emission factors
Inventory compilers should compare aggregated national emission factors with the IPCC default emission factors
in order to determine if the national factor is reasonable relative to the IPCC default. The same procedure (i.e.,comparison with the IPCC default) should be applied to plant specific emission factors. Differences between
national or plant specific factors and default factors should be explained and documented, particularly if they are
representative of different circumstances.

Plant-specific data check
For plant-specific data, inventory compilers should review inconsistencies between plants to establish whether
they reflect errors, different measurement techniques, or result from real differences in raw materials, operational
conditions or technology.
Inventory compilers should ensure that activity data and emission factors are developed in accordance withinternationally recognized and proven measurement methods. If any emission measurements from individual
plants are collected inventory compilers should ensure that the measurements were made according to therecognised national or international standards. If the measurement practices fall this criterion, then the use of thisemission factors and activity data should be carefully evaluated, uncertainty estimations reconsidered andqualifications documented.

Expert review
Inventory compilers are encouraged to include key industrial and trade organizations associated with carbide andpetroleum coke production in a review process. This process should begin on the early stage of the inventory
development to provide input to the development and review of methods and data acquisition.
Third party reviews may be also useful for this source category, particularly in relation of initial data collection,transcription, calculation and documentation.

3.6.4.2

R EPORTING AND D OCUMENTATION

It is good practice to document and archive all information required to produce the national emissions inventory
estimates as outlined in Volume 1, Section 6.11. Recalculation of previous years emissions also should be
documented and archived.

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3.7

TITANIUM DIOXIDE PRODUCTION

3.7.1

Introduction

Titanium dioxide (TiO2) is one of the most commonly used white pigments. The main use is in paintmanufacture followed by paper, plastics, rubber, ceramics, fabrics, floor covering, printing ink, and othermiscellaneous uses (Austin, 1984; Lowenheim and Moran, 1975). Given production of around 4 million tonnesof TiO2, and the substantial use of the chloride route, carbon dioxide (CO2) emissions are likely to be significant
and need to be accounted for in greenhouse gas inventories. Global production by the chloride route has increase
approximately eight fold since 1970 whilst sulphate route production has been relatively stable (Kirk-Othmer,
1999; p. 2017). Note that in the discussion, titanium dioxide products are referred to generically as titanium
dioxide unless there is a need to make a distinction between the products. The discussion applies to titanium slag,
synthetic rutile (>90 percent TiO2) and rutile TiO2.

3.7.2

Methodological issues

TiO2 is produced as anatase TiO2 and rutile TiO2. The forms of TiO2 differ in terms of the crystalline structure
and purity of the final product. Anatase TiO2 may be produced by digesting ilmenite (essentially ferrous titanate(FeO.TiO2)) with sulphuric acid, the sulphate process, or from titanium slag. Basic reaction equations for theacid digestion route are (Lowenheim and Moran, 1975; p. 814):
FeTiO3 + 2H2SO4 → FeSO4 + TiO.SO4 + 2H2O
TiO.SO4 + 2H2O → TiO2.H2O + H2SO4
TiO2.H2O + heat → TiO2 + H2O
The sulphate route process does not give rise to process greenhouse gas emissions that are of significance.
There are three processes that are used in the production of TiO2 that lead to process greenhouse gas emissions:titanium slag production in electric furnaces, synthetic rutile production using the Becher process, and rutile
TiO2 production via the chloride route.
Titanium slag used for production of anatase TiO2 is produced from electric furnace smelting of ilmenite. Wheretitanium slag is used the acid reduction step is not required as the electric furnace smelting reduces the ferric ironcontained as an impurity in ilmenite. Rutile TiO2 may be produced by further processing of the anatase TiO2.
Process emissions arise from the reductant used in the process.
Production of synthetic rutile can give rise to CO2 emissions where the Becher process is used. This process
reduces the iron oxide in ilmenite to metallic iron and then reoxidises it to iron oxide, and in the process
separates out the titanium dioxide as synthetic rutile of about 91 to 93 percent purity (Chemlink, 1997). Black
coal is used as the reductant and the CO2 emissions arising should be treated as industrial process emissions.
The main route for the production of rutile TiO2 is the chloride route. Rutile TiO2 is produced through thecarbothermal chlorination of rutile ore or synthetic rutile to produce titanium tetrachloride (TiCl4) and oxidationof the TiCl4 vapours to TiO2 according to the following reactions (Kirk-Othmer, 1999; p.2017):
2TiO2 + 4Cl2 + 3C → 2TiCl4 + 2CO + CO2
TiCl4 + O2 → TiO2 + 2Cl2
Based on stoichiometry and assuming complete conversion of the input C to CO2 through further conversion of
CO in excess air, the CO2 emission factor cannot be less than 0.826 tonnes of CO2 per tonne of TiO2 (based on
1.5 moles of CO2 per mole of TiO2).

3.7.2.1

C HOICE OF METHOD

The general approach for calculating CO2 emissions from titanium dioxide production is the same irrespective of
the product because the emissions are based on the quantity of reducing agent or carbothermal input. The choiceof a good practice method depends on national circumstances as shown in the decision tree in Figure 3.6.
Process emissions of carbon dioxide in TiO2 production take place primarily as a result of anode carbon
oxidisation in the production of titanium slag, coal oxidisation in the process of producing synthetic rutile using
the Becher process, and petroleum coke oxidisation in the process of producing rutile TiO2 via the chloride route.
Methods are classified according to the extent of plant-level data that are available.

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TIER 1 METHODThe Tier 1 method uses a default emission factor per unit of output multiplied by activity data obtained fromnational statistics. The basic equation for estimating CO2 emissions is:
EQUATION 3.12
CO2 EMISSIONS FROM TITANIUM SLAG, SYNTHETIC RUTILE AND RUTILE TIO2 PRODUCTION –TIER 1
ECO 2 = ∑ ( ADi • EFi )i

Where:
ECO2 = emissions of CO2, tonnes
ADi = production of titanium slag, synthetic rutile or rutile TiO2 (product i), tonnes
EFi = CO2 emissions per unit of production of titanium slag, synthetic rutile or rutile TiO2 (product i),tonnes CO2/tonne product

TIER 2 METHOD
Emissions can be calculated from the consumption of the reducing agent for electrode carbon (titanium slag),and coal (synthetic rutile) in the Becher process, and the carbothermal input (petroleum coke) for rutile TiO2
from the chloride rout process. The Tier 2 method uses plant-level data on the quantities of reducing agent andcarbothermal input to derive emissions as follows:
EQUATION 3.13
CO2 EMISSIONS FROM TITANIUM SLAG, SYNTHETIC RUTILE AND RUTILE TIO2 PRODUCTION –TIER 2
ECO 2 = ∑ ( ADi • CCFi • COFi • 44 12 )i

Where:
ECO2 = emissions of CO2, kg
ADi = amount of reducing agent or carbothermal input i, GJ
CCFi = carbon content factor of reducing agent or carbothermal input i, kg C/GJ
COFi = carbon oxidation factor for reducing agent or carbothermal input i, fraction
To achieve the highest accuracy, good practice is to apply Equation 3.13 at the plant-level with all data inputs
obtained from plant operators.
Where plant-level information is not available, good practice provides default CO2 emission factors for synthetic
rutile and rutile TiO2 as shown in Table 3.9. A default factor for titanium slag is not available because of thesmall number of plants.

BOX 3.6
DOUBLE COUNTING

In order to avoid double counting, the quantities of electrode carbon, coal used as a reductant, andpetroleum coke used in the chloride route process, must be subtracted from the quantity reported
under energy and non-energy use in the Energy Sector.

3.7.2.2

C HOICE OF EMISSION FACTORSTIER 1 METHOD
If plant-level information is not available, it is good practice to use default factors. These default values often
represent midpoint or mean values of data sets (as determined by expert analysis). The extent to which they
represent a specific plant’s emission rate is unknown. Default factors by product are provided in Table 3.9, andshould be used only in cases where plant-specific data are not available. The default factors are based on

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estimates of reductant or carbothermal input per unit of output assuming complete conversion of the C content to
CO2.

TIER 2 METHOD
Plant-level data provides the most rigorous data for calculating CO2 emissions from titanium dioxide production.
For the Tier 3 method, C content of the reductant and carbothermal inputs along with the proportion of C
oxidised are the key emission factor variables for deriving the quantity of CO2 emitted.
TABLE 3.9
DEFAULT FACTORS FOR TITANIUM DIOXIDE PRODUCTION (TONNES CO2 PER TONNE PRODUCT)
Product

Emission factor and respective uncertainty(tonnes CO2/tonne product)

Titanium slag1

Not available

Synthetic rutile2

1.43 (± 10%)

Rutile titanium dioxide (chloride route)31.34 (± 15%)

Source:1

A default emission factor is not available because there are two plants only, Richards Bay in South Africa, and Allard
Lake in Canada, and data are confidential. It is good practice for the respective countries to include plant specificestimates of emissions in their national greenhouse gas inventories.

2

Derived from data provided by Iluka Resources.

3

Adapted from EIPPCB (2004a; p.99).

Figure 3.6

Decision tree for estimation of CO 2 emissions from titanium dioxide
production
Start

Are
plant-level data on
the quantities of reducing agent
and carbothermal
input available?

Use the plant-level data on thequantities of reducing agent
and carbothermal input, andcarbon content and carbon
oxidation factors.

Yes

Box 2: Tier 2
No

Is this a key
category1?

NoAre
national
aggregate data on
production of titanium slag,
synthetic rutile or rutile
TiO2 available?

Yes
Yes
Collect data for
the Tier 2 method.

No
Gather production data or
use production capacity data.

Calculate emissions using
national aggregate data on
production of titanium slag,
synthetic rutile or rutile TiO2
and default emission factors.
Box 1: Tier 1

Note:
1. See Volume 1 Chapter 4, Methodological Choice and Identification of Key Categories (noting Section 4.1.2 on limited resources), for
discussion of key categories and use of decision trees.

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3.7.2.3

C HOICE OF ACTIVITY DATA

It is good practice to compile activity data at a level of detail that allows the use of the Tier 2 method. When
applying the methods it is essential that a clear distinction is made between the products to avoid multiplying theincorrect emission factor by activity data.

TIER 1 METHODThe Tier 1 method requires data on national production of titanium slag, synthetic rutile and rutile TiO2. Ifnational-level activity data are not available, information on production capacity can be used with emissions
estimated using a default emission factor. It is good practice to multiply the total national production capacity bya capacity utilisation factor of 80 percent ± 10 percent (i.e., a range of 70-90 percent).

TIER 2 METHOD
The plant-level activity data required for the Tier 2 method are total reductant use, total carbon electrodeconsumption, and total carbothermal input. It is good practice to also collect data on total titanium slag
production, total synthetic rutile production, and total rutile TiO2 production. Collection of production data
enables comparisons of inputs per unit of outputs over time and provides a sound basis for ensuring time seriesconsistency. Where plant-level emission factors are used, good practice is to collect plant-level production data.
Typical plant-level activity data is assumed to be accurate to ±2 percent due to the economic value of having
accurate information. If plant-level data are not available, nationally compiled production data may be used.

3.7.2.4

C OMPLETENESS

Complete coverage for titanium dioxide production requires accounting for all emissions from all sources
including titanium slag, synthetic rutile and rutile TiO2. CO2 emissions are the main process emissions. In order
to include emissions of NOx, CO and SO2 from this source category, see guidance provided in Chapter 7 ofVolume 1: General Guidance and Reporting.

3.7.2.5

D EVELOPING A CONSISTENT TIME SERIESCO2 emissions should be recalculated for all years whenever emission calculation methods are changed (e.g., if
the inventory compiler changes from the use of default values to actual values determined at the plant level). If
plant-specific data are not available, including plant-specific production data, for all years in the time series, itwill be necessary to consider how current plant data can be used to recalculate emissions for previous years. It
may be possible to apply current plant-specific emission factors to production data from previous years, provided
that plant operations have not changed substantially. Recalculation is required to ensure that any changes inemissions trends are real and not an artefact of changes in procedure. It is good practice to recalculate the timeseries according to the guidance provided in Volume 1, Chapter 5.

3.7.3
3.7.3.1

Uncertainty assessment
E MISSION FACTOR UNCERTAINTIES

Uncertainties for the default values are estimates based on expert judgement. It is good practice to obtain
uncertainty estimates at the plant level which should be lower than uncertainty values associated with default
values.

3.7.3.2

A CTIVITY DATA UNCERTAINTIES

Where activity data are obtained from plants, uncertainty estimates can be obtained from producers. This will
include uncertainty estimates for reductant use, carbothermal inputs, and production data. Data that are obtained
from national statistical agencies usually do not include uncertainty estimates. It is good practice to consult withnational statistical agencies to obtain information on any sampling errors. Where national statistical agencies
collect data from the population of titanium dioxide production facilities, uncertainties in national statistics are
not expected to differ from uncertainties established from plant-level consultations. Where uncertainty values are
not available from other sources, a default value of ±5 percent can be used.

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3.7.4
3.7.4.1

Quality Assurance/Quality Control (QA/QC),
Reporting and Documentation
Q UALITY A SSURANCE /Q UALITY C ONTROL

It is good practice to conduct quality control checks as outlined in Volume 1, Chapter 6. More extensive quality
control checks and quality assurance procedures are applicable, if higher tier methods are used to determine
emissions. Inventory compilers are encouraged to use higher tier QA/QC for key categories as identified inVolume 1, Chapter 4.

Comparison of emission factors
Inventory compilers should check if the estimated emission factors are within the range of default emission
factors provided for the Tier 1 method, and also ensure that the emission factors are consistent with the values
derived from analysis of the process chemistry. For example, the CO2 generation rate for rutile TiO2 from thechloride route process should not be less than 0.826 tonnes of CO2 per tonne of rutile TiO2 produced. If theemission factors are outside of the estimated ranges, it is good practice to assess and document the plant-specificconditions that account for the differences.
If emission measurements from individual plants are collected, inventory compilers should ensure that themeasurements were made according to recognised national or international standards. QC procedures in use at
the site should be directly referenced and included in the QC plan. If the measurement practices were notconsistent with QC standards, the inventory compiler should reconsider the use of these data.

3.7.4.2

R EPORTING AND D OCUMENTATION

It is good practice to document and archive all information required to produce the national emissions inventory
estimates as outlined in Volume 1, Section 6.11. It is not practical to include all documentation in the national
inventory report. However, the inventory should include summaries of methods used and references to source
data such that the reported emissions estimates are transparent and steps in their calculation may be retraced.

Plant-specific data check
The following plant-specific data is required for adequate auditing of emissions estimates:•

Activity data comprising electrode carbon consumption (titanium slag), coal reductant use (synthetic rutile),
carbothermal input (rutile TiO2), titanium slag production, synthetic rutile production, and rutile TiO2
production;•

Emission factor data including the carbon content of the reductant (carbon electrode and coal) andcarbothermal input (petroleum coke), and the proportion oxidised in the process;•Calculations and estimation method;•

List of assumptions;•

Documentation of any plant-specific measurement method, and measurement results.

In general production and process data are considered proprietary by operators, especially where there are only asmall number of plants within a country. It is good practice to apply appropriate techniques, including
aggregation of data, to ensure protection of confidential data.

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3.8

SODA ASH PRODUCTION

3.8.1

Introduction

Soda ash (sodium carbonate, Na2CO3) is a white crystalline solid that is used as a raw material in a large numberof industries including glass manufacture, soap and detergents, pulp and paper production and water treatment.
Carbon dioxide (CO2) is emitted from the use of soda ash and these emissions are accounted for as a source
under the relevant using industry as discussed in Volume 3, Chapter 2. CO2 is also emitted during production
with the quantity emitted dependent on the industrial process used to manufacture soda ash.
Emissions of CO2 from the production of soda ash vary substantially with the manufacturing process. Fourdifferent processes may be used commercially to produce soda ash. Three of these processes, monohydrate,sodium sesquicarbonate (trona) and direct carbonation, are referred to as natural processes. The fourth, theSolvay process, is classified as a synthetic process. Calcium carbonate (limestone) is used as a source of CO2 in
the Solvay process. Other uses of limestone and other carbonates are discussed in Volume 3, Chapter 2.

3.8.2

Natural soda ash production

About 25 percent of the world production is produced from natural sodium carbonate-bearing deposits referred
to as natural processes. During the production process, Trona (the principal ore from which natural soda ash ismade) is calcined in a rotary kiln and chemically transformed into a crude soda ash. Carbon dioxide and water
are generated as by-products of this process. Carbon dioxide emissions can be estimated based on the following
chemical reaction:
2Na2CO3.NaHCO3.2H2O (Trona) → 3Na2CO3 (Soda Ash) + 5H2O + CO2

3.8.2.1

M ETHODOLOGICAL ISSUESCHOICE OF METHOD
The choice of method will depend on national circumstances. Emissions can be estimated using an output-based
approach (emissions per unit of output), or an input-based approach (emissions per unit of input). However, it isgood practice to use the input-based method where data are available.
Methods are classified according to the extent of plant-level data that are available. The Tier 1 method is basedon default values and national statistics, and the Tier 2 method is based on complete plant-level input or output
data and plant specific emission factors. If there is monitoring and direct measurement of CO2 emissions thiswould be equivalent to a Tier 3 method.

Tier 1 method
Natural soda ash production emits CO2 through the thermal decomposition (calcination) of the Trona(Na2CO3.NaHCO3.2H2O) to produce soda ash. According to the chemical reaction presented above, it takes
10.27 tonnes of Trona to produce 1 tonne of carbon dioxide. Hence, for natural soda ash production using Trona,emissions of carbon dioxide can be calculated from the Trona input or natural soda ash output by the following
formula:EQUATION 3.14
CO2 EMISSIONS FROM NATURAL SODA ASH PRODUCTION – TIER 1
ECO 2 = AD • EF
Where:
ECO2 = emissions of CO2, tonnes
AD = quantity of Trona used or soda ash produced, tonnes of Trona used or tonnes natural soda ash
produced
EF = emission factor per unit of Trona input or natural soda ash output, tonnes CO2/tonne of Trona or
tonnes CO2/tonne natural soda ash produced: EFTrona = 0.097 tonnes CO2/tonne of Trona, EFSoda Ash =0.138 tonnes CO2/tonnes natural soda ash produced.

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It is good practice to assess the available national statistics for completeness. The choice of good practicemethods depends on national circumstances, as shown in Figure 3.7: Decision Tree for Estimation of CO2
Emissions from Natural Soda Ash Production. If no data are available for the purity of the Trona input, it is goodpractice to assume it is 90 percent and adjust the emission factor shown in Equation 3.14.

Tier 2 method
To use the Tier 2 method, it is necessary to gather complete data on Trona consumption or natural soda ash
production for each of the plants within the country along with plant-specific emission factors for the Trona
input or soda ash output. The CO2 emissions for each plant can be calculated using either variation of Equation
3.14. For plants where plant-specific emission factors are not available, the default emission factors provided in
Equation 3.14 can be used. Total CO2 emissions are the sum of the emissions from all plants.

Tier 3 method
The Tier 3 method uses plant-level CO2 emissions data obtained from direct measurement. Total emissions are
the sum of emissions from all plants.

Figure 3.7

Decision tree for estimation of CO 2 emissions from natural soda ash
production
Start

Are
plant-level CO2
emissions data obtainable fromdirect measurement?

Yes

Use plant-level CO2
emissions data obtained
from direct measurement.
Box 4: Tier 3

Collect data for the
Tier 3 or 2 method.

No
Are
plant-level data on
Trona consumption
available?

Yes

Box 3: Tier 2

No

Yes

Are
plant-level
data on natural soda ash
production
available?

Yes

Calculate emissions using
plant-level natural soda
ash production data andplant-specific emission
factors, if available.
Box 2: Tier 2

No
Is this a key
category1?

Calculate emissions
using plant-level Tronaconsumption data, using
plant-specific emission
factor if available.

No

Calculate emissions using national aggregate dataof Trona consumption or natural soda ash
production and default emission factor. In casethe national aggregate data are not available,
estimate it by using production capacity data.
Box 1: Tier 1

Note:
1. See Volume 1 Chapter 4, Methodological Choice and Identification of Key Categories (noting Section 4.1.2 on limited resources), for
discussion of key categories and use of decision trees.

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CHOICE OF EMISSION FACTORS
Tier 1 method
The Tier method uses the default emission factors presented in Equation 3.14. The default emission factors arederived from the stoichiometric ratio between soda ash produced and purified sodium sesquicarbonate obtained
from Trona. They are based on the main natural production process that is used at present, where soda ash is
produced by calcination of purified sodium sesquicarbonate.

Tier 2 method
The Tier 2 method requires plant-level emission factors per unit of Trona input or per unit of natural soda ash
output. Plant-level emission factors should reflect the fractional purities of the Trona input and natural soda ash
output and it is good practice to ensure that these are taken into account in the derivation of plant-level emission
factors.

CHOICE OF ACTIVITY DATA
It is good practice to compile activity data at a level of detail that allows the use of the Tier 2 method. When
applying the methods it is essential that a clear distinction is made between the products to avoid multiplying theincorrect emission factor by activity data.

Tier 1 method
The Tier 1 method requires data on national consumption of Trona or national production of natural soda ash. Ifnational-level activity data are not available, information on production capacity can be used with emissions
estimated using a default emission factor. It is good practice to multiply the total national production capacity bya capacity utilisation factor of 80 percent ± 10 percent (i.e., a range of 70-90 percent).

Tier 2 method
Activity data should be collected at the plant-level to use the Tier 2 method. The most important data are theamount of Trona used for soda ash production and the amount of natural soda ash produced at each plant.
Although soda ash production is not used in the calculation if emissions are derived from Trona input, it is goodpractice to collect and report these data to enable comparisons of inputs per unit of outputs over time andprovide a sound basis for ensuring time series consistency.

COMPLETENESS
Completeness of the activity data (e.g., Trona utilisation) is a crucial attribute of good practice. Therefore, it isgood practice to assess the available national statistics for completeness. If data are available at the plant-level,
it is good practice to aggregate these data and check the result with the data available at a national level. This
practice enables assessment of whether any significant soda ash producer is omitted, and ensures that all
production processes within the country have been considered. If data at the plant-level are not available, it isgood practice to use production capacity data along with national statistics to estimate the emissions forcompleteness purposes.

DEVELOPING A CONSISTENT TIME SERIESIt is good practice to calculate emissions from soda ash using the same method for every year in the time series.
Where data are unavailable to support a more rigorous method for all years in the time series, good practice is torecalculate these gaps according to the guidance provided in Volume 1, Chapter 5.

3.8.2.2

U NCERTAINTY A SSESSMENTEMISSION FACTOR UNCERTAINTIESThe stoichiometric ratio is an exact number and assuming 100 percent purity of the input or output, theuncertainty of the default emission factor is negligible. However, the default factors do not take into account thefractional purities of either the Trona input or soda ash output and, in both cases, are expected to result in
consistent over-estimation of emissions. As noted earlier, if no data are available for the purity of the Trona input,
it is good practice to assume it is 90 percent and adjust the emission factor shown in Equation 3.14. It is goodpractice to develop uncertainty estimates based on plant-level data.

ACTIVITY DATA UNCERTAINTIES
Where activity data are obtained from plants, uncertainty estimates can be obtained from producers. This will
include uncertainty estimates for Trona used and natural soda ash used. Data that are obtained from national
statistical agencies usually do not include uncertainty estimates. It is good practice to consult with national
statistical agencies to obtain information on any sampling errors. Where national statistical agencies collect data

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from the population of soda ash production facilities, uncertainties in national statistics are not expected to differ
from uncertainties established from plant-level consultations. Where uncertainty values are not available fromother sources, a default value of ±5 percent can be used.

3.8.2.3

Q UALITY A SSURANCE /Q UALITY C ONTROL (QA/QC),R EPORTING AND D OCUMENTATIONQUALITY ASSURANCE/QUALITY CONTROL
It is good practice to conduct quality control checks as outlined in Volume 1, Chapter 6, and an expert review ofthe emissions estimates. Additional quality control checks as outlined in Volume 1, and quality assurance
procedures may also be applicable, particularly if higher tier methods are used to determine emissions from thissource category. Inventory compilers are encouraged to use higher tier QA/QC for key categories as identified inVolume 1, Chapter 4.

Comparison of the emissions estimates using different approaches
If the bottom-up approach is used, then inventory compilers should compare the emissions estimates to theestimate calculated using the top-down approach. The results of such comparisons should be recorded forinternal documentation, including explanations for any discrepancies.

REPORTING AND DOCUMENTATION
It is good practice to document and archive all information required to produce the national emissions inventory
estimates as outlined in Volume1, Section 6.11. It is not practical to include all documentation in the national
inventory report. However, the inventory should include summaries of methods used and references to data
sources, and all the information needed to reproduce the estimate.
Besides the emissions, good practice is to report the activity data used in the calculation (Trona utilisation) andthe corresponding emission factors along with all assumptions used in the derivation.
To preserve an internally consistent emission time series, whenever national methods change, good practice is torecalculate the entire time series. If confidentiality is an issue for any type of production, estimates may be
aggregated to the minimum extent possible to maintain confidentiality.
In addition, inventory compilers should document the QA/QC procedures.

3.8.3

Solvay soda ash production

About 75 percent of the world production of soda ash is synthetic ash made from sodium chloride. In the Solvay
process, sodium chloride brine, limestone, metallurgical coke and ammonia are the raw materials used in a seriesof reactions leading to the production of soda ash. Ammonia, however, is recycled and only a small amount islost. The series of reactions involved in the Solvay process may be described as follows:
CaCO3 + heat → CaO + CO2
CaO + H2O → Ca(OH)22NaCl + 2H2O + 2NH3 + 2CO2 → 2NaHCO3 + 2NH4Cl
2NaHCO3 + heat → Na2CO3 + CO2 + H2O
Ca(OH)2 + 2NH4Cl → CaCl2 + 2NH3 + 2H2O
The net overall reaction may be summarised as:
CaCO3 + 2NaCl → Na2CO3 + CaCl2
From the series of reactions presented above, CO2 is generated in two pyrolysis processes. The CO2 generated is
captured, compressed and directed to Solvay precipitating towers for consumption in a mixture of brine (aqueous
NaCl) and ammonia. Although CO2 is generated as a by-product, the CO2 is recovered and recycled for use in
the carbonation stage and in theory the process is neutral, i.e., CO2 generation equals uptake.
In practice, some CO2 is emitted to the atmosphere during production by the Solvay process because more CO2 is
produced than is stoichiometrically required. The excess CO2 arises from calcining the limestone withmetallurgical grade coke. The limestone is combined with the coke at approximately 7 percent of limestone byweight.

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The estimation of the CO2 emissions from a stand alone soda ash plant should be based on an overall balance of
CO2 around the whole chemical process. For inventory purposes, a simplified version of the balance may be usedassuming that the CO2 emissions result from the stoichiometric oxidation of the coke carbon. The Solvay
ammonia soda ash production process is a chemical industry activity and emissions should be reported under the
Industrial Processes and Product Use (IPPU) Sector.

BOX 3.7
DOUBLE COUNTING

In order to avoid double counting, CO2 emissions generated in the process of soda ash production
should be accounted in the IPPU Sector, and should not be included in the Energy Sector. Coke
used in the production process should be deducted from the Energy Sector as a non-energy use ofcoke.

3.8.3.1

Q UALITY A SSURANCE /Q UALITY C ONTROL (QA/QC),R EPORTING AND D OCUMENTATION

The allocation of emissions from the use of metallurgical grade coke in the Solvay process to the Energy Sectormeans that a methodology for estimating these emissions is not provided in the Industrial Processes andProduct Use Sector. However, data on soda ash production from the Solvay process should be collected andcollated to ensure that all data on soda ash production by process are available for recording, reporting, archiving
and reconciliation with national statistics on soda ash use.

QUALITY ASSURANCE/ QUALITY CONTROL
It is good practice to conduct quality control checks as outlined in Volume 1, Chapter 6. Additional quality
control checks as outlined in Volume 1, and quality assurance procedures may also be applicable. Inventory
compilers are encouraged to use higher tier QA/QC for key categories as identified in Volume 1, Chapter 4.

REPORTING AND DOCUMENTATION
It is good practice to document and archive all information required to produce the national emissions inventory
estimates as outlined in Volume1, Section 6.11. It is not practical to include all documentation in the national
inventory report. However, the inventory should include summaries of methods used and references to data
sources, and all the information needed to reproduce the estimate.

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3.9

PETROCHEMICAL AND CARBON BLACKPRODUCTION

3.9.1

Introduction

The petrochemical industry uses fossil fuels (e.g., natural gas) or petroleum refinery products (e.g., naphtha) as
feedstocks. This section provides guidance for estimating emissions from the production of methanol, ethylene
and propylene 2, ethylene dichloride, ethylene oxide, and acrylonitrile. These petrochemicals are addressed indetail because their global production volume and associated greenhouse gas emissions are relatively large.
However, the chemicals included are not intended to represent the entire petrochemical process industry. There
are a number of other petrochemical processes that emit small amounts of greenhouse gases for which specificguidance is not provided (e.g., styrene production).
This section also provides guidance for production of carbon black. Carbon black is not considered to be apetrochemical; however, the carbon black production process uses petrochemical feedstocks. Emissions fromcarbon black production are smaller than for petrochemical processes but may be significant for certain countries.
Examples of feedstock to product production chains for methanol, ethylene and propylene, ethylene dichloride,
ethylene oxide, acrylonitrile, and carbon black are included in the Annex to Section 3.9.

Allocation and Reporting
Within the petrochemical industry and carbon black industry, primary fossil fuels (natural gas, petroleum, coal)
are used for non-fuel purposes in the production of petrochemicals and carbon black. The use of these primary
fossil fuels may involve combustion of part of the hydrocarbon content for heat raising and the production of
secondary fuels (e.g., off gases).
Combustion emissions from fuels obtained from the feedstocks should be allocated to the source category in the
IPPU Sector. However, where the fuels are not used within the source category but are transferred out of theprocess for combustion elsewhere (e.g., for district heating purposes) the emissions should be reported in theappropriate Energy Sector source category. The industries are included in the source category Chemical
Industry (2B1 – 2B10), see Figure 1.1, Industrial Process and Product Use Source Categories in Chapter 1 of thisvolume. Further discussion of the non-energy use of fuels is included in Chapters 1 and 5 of this volume.
Note that national energy statistics may include total combustion of fossil fuels (including natural gas, oil, andcoal,) and also secondary fuels (such as industrial process off gases) for energy production. It is important toinvestigate if fuels used in petrochemical industries are included in national energy statistics. If this is the case,emissions from petrochemical processes should be subtracted from the calculated energy sector emissions to
avoid double counting. This is particularly relevant for ethylene and methanol, where primary fuel (e.g., naturalgas, ethane, propane) feedstock consumption may be reported in national energy statistics.
Should carbon dioxide (CO2) capture technology be installed and used at a plant, it is good practice to deduct theCO2 captured in a higher tier emissions calculation. The default assumption is that there is no CO2 capture andstorage (CCS) taking place. Any methodology taking into account CO2 capture should consider that CO2
emissions captured in the process may be both combustion and process-related. In cases where combustion andprocess emissions are to be reported separately, inventory compilers should ensure that the same quantities of
CO2 are not double counted. In these cases the total amount of CO2 captured should preferably be reported in thecorresponding energy combustion and IPPU source categories in proportion to the amounts of CO2 generated inthese source categories. For additional information on CO2 capture and storage refer to Volume 3, Section 1.2.2
and for more details on capture and storage to Volume 2, Section 2.3.4.
Petrochemical processes may utilise CO2 captured elsewhere as a feedstock, and CO2 may also be captured frompetrochemical processes. This may create potential double counting issues. For example, some methanol plants
may utilise by-product CO2 captured from other industrial processes as a feedstock for methanol production. To
avoid double counting the CO2 captured should not be reported as CO2 emissions from the process from which
the CO2 is captured.

2

Note that there is no separate inventory methodology for propylene. Propylene is assumed to be a co-product of ethylene
production.

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METHANOLWorldwide almost all methanol is made by way of steam reforming of natural gas. The steam reforming and shift
reaction produce ‘synthesis gas’ comprised of CO2, carbon monoxide (CO), and hydrogen (H2). The natural gas
to methanol production process produces methanol and by-product CO2, CO, and H2 from the synthesis gas.
There are several alternative processes for producing methanol from natural gas or other feedstocks. These
include conventional reforming process, combined reforming and partial oxidation process. An example of afeedstock to product process flow diagram for methanol production is provided in an Annex to Section 3.9(Annex 3.9A). Process descriptions for methanol production are included in Box 3.8 below.
BOX 3.8
METHANOL PROCESS DESCRIPTIONSConventional Reforming Process
The Conventional Reforming Process for methanol production involves steam reforming (which
may include either a single reformer unit or both a primary reformer unit and a secondary reformerunit) and methanol synthesis. The overall equations for the Conventional Reforming Process are:
Steam Reforming

Shift Reaction

Methanol Production

CH4 + H2O → CO + 3 H2

CO + H2O → CO2 + H2

CO + 2 H2 → CH3OH

CnHm + nH2O → nCO + (m/2 + n) H2

CO2 + 3 H2 → CH3OH + H2O

Reforming/Shift Reaction

Methanol Production

2 CH4 + 3 H2O → CO + CO2 + 7 H2

CO + CO2 + 7 H2 → 2 CH3OH + 2 H2 + H2O

The surplus hydrogen from this process and methanol process purge gas containing methane (CH4)and non-methane volatile organic compounds (NMVOC) are recovered and burned for energy
recovery, generally within the methanol production process, to produce process steam and/or
electricity for the process. The Conventional Reforming Process may utilise CO2 captured fromother industrial processes as a supplemental feedstock to the methanol production process.
Combined Reforming Process
The Combined Reforming Process combines the Conventional Steam Reforming process with a
Catalytic Partial Oxidation process. The Partial Oxidation chemical equations are:Methanol Steam Reforming Reaction

Feedstock Oxidation Reaction

CH4 + ½ O2 → CO + 2 H2 → CH3OH

CH4 + O2 → CO2 + 2 H2The Combined Reforming Process produces a synthesis gas that contains a more balanced ratio ofhydrogen to carbon monoxide (CO) and CO2 than does the Conventional Reforming Process, anddoes not produce a hydrogen gas stream for energy recovery. The Combined Reforming Process
produces a purge gas containing CH4 that is burned for energy recovery within the methanol
process.
Other Production Processes
Methanol may also be produced from the partial oxidation of oil, coal, or petrochemical
feedstocks, or by gasification of coal to synthesis gas, however; these feedstocks and processes
currently represent only a small amount of worldwide methanol production.

ETHYLENE
Worldwide almost all ethylene is made by way of steam cracking of petrochemical feedstocks. Ethylene may be
produced from steam cracking of petrochemical feedstocks in a petrochemical plant, and may also be produced
from cracking and other processes operated at petroleum refineries. Steam cracking for ethylene production also
produces secondary products including propylene and butadiene. A process description for steam cracking
process for ethylene production is provided in Box 3.9 below.

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BOX 3.9
ETHYLENE PROCESS DESCRIPTION

Steam Cracking
The fundamental chemical equation for ethylene production is as follows:
Ethane Dehydrogenation to Ethylene
C2H6 → C2H4 + H2

The types and mix of feedstock used in steam cracking for ethylene production varies by region,and include ethane, propane, butane, naphtha, gas oil, and other petrochemical feedstocks. In the
United States, most ethylene is produced from steam cracking of ethane, while in Europe, Korea,
and Japan most ethylene is produced from steam cracking of naphtha.
Steam cracking of petrochemical feedstocks to produce ethylene also produces other high value(saleable) petrochemical products, including propylene, butadiene, and aromatic compounds. Most
propylene worldwide is produced as a by-product of ethylene production, recovered either fromsteam crackers or from fluid catalytic cracking units at petroleum refineries. Steam crackers using
naphtha feedstock are the largest source of propylene. There are other process technologies that areused to produce propylene including catalytic dehydrogenation of propane. Note that the emissions
estimation methods in this section apply only to production of ethylene and propylene in steam
crackers and do not apply to other process technologies used to produce ethylene or propylene.
The steam cracking process also produces by-product hydrogen and methane and C4+hydrocarbons that are generally burned for energy recovery within the process.
(Houdek, 2005: Figure 1 on Page 3, Page 4)

ETHYLENE DICHLORIDE AND VINYL CHLORIDE M ONOMERWorldwide almost all ethylene dichloride (1, 2 dichloroethane) is made by way of direct chlorination or
oxychlorination of ethylene, or by a combination of the two processes (referred to as the ‘balanced process.’) An
example of a feedstock to product process flow diagram for ethylene dichloride production is provided in an
Annex to Section 3.9 (Annex 3.9A). Process descriptions for ethylene dichloride and vinyl chloride monomer
production are provided in Box 3.10 below. Note that the chemical compound ‘ethylene dichloride’ is also
referred to as 1,2-dichloroethane. The chemical compound ‘dichloroethylene,’ also referred to as 1, 2dichloroethene, is a different compound.
BOX 3.10
ETHYLENE DICHLORIDE AND VINYL CHLORIDE MONOMER PROCESS DESCRIPTIONS

Direct Chlorination and Oxychlorination Processes
The direct chlorination process involves gas-phase reaction of ethylene with chlorine to produce
ethylene dichloride. The oxychlorination process involves gas-phase reaction of ethylene withhydrochloric acid and oxygen to produce ethylene dichloride and water. The ethylene dichloride isthen cracked to produce vinyl chloride monomer and hydrochloric acid. The oxychlorination
process produces a process off gas containing by-product CO2 produced from the direct oxidationof the ethylene feedstock.
The fundamental chemical equations for the direct chlorination and oxychlorination processes are
as follows:
Direct chlorination
C2H4 + Cl2 → C2H4Cl2

Oxychlorination reaction
C2H4 + ½ O2 + 2 HCl→ C2H4Cl2 + H2O

Ethylene dichloride>vinyl chloride
2 C2H4Cl2 → 2 CH2CHCl + 2 HCl[C2H4 + 3 O2 → 2 CO2 + 2 H2O]

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BOX 3.10 (CONTINUATION)ETHYLENE DICHLORIDE AND VINYL CHLORIDE MONOMER PROCESS DESCRIPTIONS

Balanced Process
The combination of the direct chlorination process to produce ethylene dichloride and the ethylene
dichloride cracking process to produce vinyl chloride monomer produces a surplus of hydrogenchloride. The oxychlorination process provides a sink for the hydrogen chloride. Therefore,
ethylene dichloride/vinyl chloride monomer production facilities may operate a ‘balanced process’
in which both the direct chlorination process and the oxychlorination process are combined. The‘balanced process’ also produces process vent gas containing by-product CO2 from the directoxidation of the ethylene feedstock.
The fundamental chemical equations for the ‘balanced process’ for producing vinyl chloride
monomer from ethylene are as follows:
Ethylene Dichloride-Vinyl Chloride Monomer Reaction

Feedstock Oxidation Reaction

2 C2H4 + Cl2 + ½ O2 → 2 CH2CHCl + H2O[C2H4 + 3 O2 → 2 CO2 + 2 H2O]

The direct chlorination process and the oxychlorination process for ethylene dichloride production
are not 100 percent efficient in the utilisation of the ethylene feedstock. On the order of three
percent of the ethylene feedstock is not converted to ethylene dichloride but is converted either to
CO2 (by direct oxidation in the oxychlorination process) or to other chlorinated hydrocarbons (ineither the oxychlorination process or the direct chlorination process.) Process off gas containing
other chlorinated hydrocarbons is generally treated prior to discharge to the atmosphere. The
chlorinated hydrocarbons are converted to CO2 in a thermal incineration process or a catalytic
incineration process. Most ethylene dichloride/vinyl chloride monomer plants recover energy fromthe incinerator off gases and process off gases.

ETHYLENE OXIDE
Ethylene oxide (C2H4O) is manufactured by reacting ethylene with oxygen over a catalyst. The by-product CO2
from the direct oxidation of the ethylene feedstock is removed from the process vent stream using a recycled
carbonate solution, and the recovered CO2 may be vented to the atmosphere or recovered for further utilisation(e.g., food production.) The oxygen may be supplied to the process through either air or through pure oxygen
separated from air. An example of a feedstock to product process flow diagram for ethylene oxide production isprovided in an Annex to Section 3.9 (Annex 3.9A). A process description for ethylene oxide production isprovided in Box 3.11 below.
BOX 3.11
ETHYLENE OXIDE PROCESS DESCRIPTION

The fundamental chemical equations for the production of ethylene oxide from ethylene and the
production of monoethylene glycol are as follows:
Ethylene Oxide Reaction

Feedstock Oxidation Reaction

Monoethylene Glycol Production

C2H4 + ½ O2 → C2H4O

C2H4 + 3 O2 → 2 CO2 + 2 H2O

C2H4O + H2O → HO- C2H4 - OH

The ratio of the ethylene oxide reaction and the by-product reaction defines the selectivity of theethylene oxide process, in terms of tonnes of ethylene consumed per tonne of ethylene oxide
produced. The combined ethylene oxide reaction and by-product CO2 reaction is exothermic andgenerates heat, which is recovered to produce steam for the process. The ethylene oxide process
also produces other liquid and off-gas by-products (e.g., ethane) that may be burned for energy
recovery within the process. The amount of CO2 and other by-products produced from the process
and the amount of steam produced from the process is dependent upon the selectivity of theprocess.
Ethylene oxide is used as a feedstock in the manufacture of glycols, glycol ethers, alcohols, andamines. Worldwide approximately 70 percent of ethylene oxide produced is used in the
manufacture of glycols, including monoethylene glycol.

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ACRYLONTRILEWorldwide more than 90 percent of acrylonitrile (vinyl cyanide) is made by way of direct ammoxidation of
propylene with ammonia (NH3) and oxygen over a catalyst. This process is referred to as the SOHIO process,after the Standard Oil Company of Ohio (SOHIO). Acrylonitrile can also be manufactured by ammoxidation of
propane or directly from reaction of propane with hydrogen peroxide. The propane-peroxide direct process has
recently been commercialised by British Petroleum (BP) and other manufacturers. (DOE, 2000) However,process data were not readily available for production of acrylonitrile from propane feedstocks. Therefore noemission estimation methodology is provided for this process. An example of a feedstock to product process
flow diagram for acrylonitrile production from propylene is provided in an Annex to Section 3.9 (Annex 3.9A).
Process descriptions for acrylonitrile production are provided in Box 3.12 below.
BOX 3.12
ACRYLONITRILE PROCESS DESCRIPTIONSOHIO Process
The SOHIO process involves a fluidized bed reaction of chemical-grade propylene, ammonia, andoxygen over a catalyst. The catalyst is a mixture of heavy metal oxides (including bismuth andmolybdenum). The process produces acrylonitrile as its primary product and acetonitrile (methyl
cyanide) and hydrogen cyanide (HCN) as secondary products. The process yield of the primary
product acrylonitrile depends in part on the type of catalyst used and the process configuration.
The ammoxidation process also produces by-product CO2, CO, and water from the direct oxidationof the propylene feedstock, and produces other hydrocarbons from side reactions in theammoxidation process.
The acetonitrile and hydrogen cyanide are separated from the acrylonitrile by absorption, and thehydrogen cyanide may be used in manufacturing other products on site or sold as product.
Hydrogen cyanide that is not used or sold may be burned for energy recovery or flared. The
acetonitrile may be also recovered for sale as a product, but more often the acetonitrile is burnedfor energy recovery or flared. The off gas from the main absorber vent containing CO2, CO,nitrogen, water, unreacted propylene, and other hydrocarbons, may be flared or treated in a thermal
or catalytic oxidation unit, with or without energy recovery.
Heavy bottoms liquids from the acetonitrile – hydrogen cyanide - acrylonitrile absorption
separations process may also be burned for energy recovery or recycled. Acrylonitrile and othernon-methane hydrocarbons are also released from miscellaneous process vents, including storage
tanks. These miscellaneous process vents may be flared or captured and burned for energy
recovery.
The fundamental chemical equations for the production of acrylonitrile by ammoxidation are as
follows:
Acrylonitrile Reaction
CH2=CHCH3 + 1.5 O2 + NH3→ CH2=CHCN + 3 H2OHydrogen Cyanide Reaction

Acetonitrile Reaction
CH2=CHCH3 + 1.5 O2 + 1.5 NH3→ 1.5 CH3CN + 3 H2OFeedstock Oxidation

CH2=CHCH3 + 3 O2 + 3 NH3 → 3 HCN + 6 H2O

C3H6 + 4.5 O2 → 3 CO2 + 3 H2O
C3H6 + 3 O2 → 3 CO + 3 H2O

The ammoxidation of propylene to acrylonitrile is not 100 percent efficient in utilisation of the
propylene feedstock. On the order of 70 percent of the propylene feedstock is converted toacrylonitrile. On the order of 85 percent of the propylene feedstock is converted to either the
primary product acrylonitrile or secondary products acetonitrile or hydrogen cyanide. The
remainder of the propylene feedstock is either converted directly to CO2 by direct oxidation of thefeedstock in the ammoxidation process or converted to other hydrocarbons through side reactionsin the ammoxidation process.

CARBON BLACK
Worldwide almost all carbon black is produced from petroleum-based or coal-based feedstocks using the‘furnace black’ process. Process descriptions for carbon black production are provided in Box 3.13 below.

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The furnace black process is a partial combustion process where a portion of the carbon black feedstock is
combusted to provide energy to the process. Carbon black may also be produced using other petroleumfeedstock or coal-based feedstock partial oxidation processes, including the ‘channel black’ process and ‘lamp
black’ process, or may be produced directly by the partial oxidation of natural gas or aromatic oils (‘channel
black process’). Carbon black may also be produced by the thermal cracking of acetylene-containing feedstocks(‘acetylene black process’) or by the thermal cracking of other hydrocarbons (‘thermal black process’.)
Approximately 95 percent of worldwide carbon black production is by way of the furnace black process; theremaining 5 percent being produced by way of other processes.
Approximately 90 percent of carbon black produced worldwide is used in the tire and rubber industry (referred
to as ‘rubber black.’) and the remainder is used in pigment applications (e.g., inks) and other applications (e.g.,
carbon dry cell batteries.) Carbon black may be produced using a furnace black process, thermal black process,acetylene carbon black process, channel black process and lamp black process. These processes are further
described in Box 3.13 below. An example of a feedstock to product process flow diagram for carbon black
production using the furnace black process is provided in an Annex to Section 3.9 (Annex 3.9A).
BOX 3.13
CARBON BLACK PRODUCTION PROCESS DESCRIPTIONS

Furnace Black Process
The furnace black process produces carbon black from ‘carbon black feedstock’ (also referred toas ‘carbon black oil’) which is a heavy aromatic oil that may be derived either as a by-product ofthe petroleum refining process or the metallurgical (coal) coke production process. For either
petroleum-derived or coal-derived feedstock, the carbon black feedstock, the ‘primary feedstock,’is injected into a furnace heated by a ‘secondary feedstock’ (generally natural gas or oil). Both thenatural gas secondary feedstock and a portion of the carbon black feedstock are oxidized toprovide heat to the production process that pyrolyzes the remaining carbon black feedstock to
carbon black. The vent gas from the furnace black process contains CO2, CO, sulphur compounds,
CH4, and NMVOCs. A portion of the tail gas is generally burned for energy recovery to heat thedownstream carbon black product dryers. The remaining tail gas may also be burned for energy
recovery, flared, or vented uncontrolled to the atmosphere.
Thermal Black Process
Carbon black is produced in the thermal black process by thermal decomposition of gaseoushydrocarbons or atomized petroleum oils in the absence of air in a pair of production furnaces.
The carbon black feedstock is introduced into a preheated furnace that is heated by a secondary
feedstock, usually natural gas, and by the off gas from the carbon black production process. One ofthe pair of furnaces is being preheated by the secondary feedstock while the other furnace isreceiving carbon black feedstock. Yield from this process is approximately 45 percent of total
carbon input to the process (or 40 percent with respect to the total carbon black feedstock used)and energy utilisation is approximately 280 MJ/kg carbon black produced.
Acetylene Black Process
Carbon black produced from acetylene or acetylene-containing light hydrocarbons by feeding thefeedstock to a preheated reactor where the acetylene decomposes to carbon black in an exothermic
process. Total worldwide production of acetylene black is only approximately 40 000 metric tons
per year. The carbon black yield from this process is approximately 95-99 percent of theoreticalyield. Acetylene black is approximately 99.7 percent carbon.
Other Production Processes
The channel black process involves partial oxidation of vaporised carbon black feedstock that isburned in a furnace with a carrier gas (which may be coke oven gas, hydrogen, or methane). The
carbon black yield for this process may be 60 percent of total carbon input for production ofrubber-grade carbon black or 10-30 percent of total carbon input for pigment-grade carbon black.
The lamp black process involves open burning of carbon black feedstock in shallow pans. Data are
not readily available concerning feedstock yield and energy consumption for the lamp black
process. This process represents an insignificant percentage of worldwide carbon black production.
(Kirk Othmer, 1992)

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3.9.2

Methodological issues

3.9.2.1

C HOICE OF METHOD

The emissions from petrochemical and carbon black production vary both with the process used and thefeedstock used. The choice of method should thus be repeated for each product, process and feedstock used.
Three methodological tiers are provided depending on the availability of data. The choice of method depends onnational circumstances and is given by the decision trees in Figure 3.8 and Figure 3.9.
Figure 3.8

Decision tree for estimation of CO 2 emissions from petrochemical industry
and carbon black industry
StartCollect
feedstockand theprocess
data1.

Are
both the typeof feedstock used andprocess
known?

Repeat for eachfeedstock andpetrochemical.
Are
plant-specificemission factors
available?

Yes

Estimate emissions
using Tier 3
plant-specificemission factors.

No
Are theactivity data for
all carbon flows
available?

No
No

Yes

Yes

Is
Petrochemicaland Carbon Black
Production a key category andis this subcategory
significant?

YesAre
by-products
transferred out of theprocess?

No

No

Is it theprocess that is
unknown?

Issupplementary
fossil fuel transferred
into the process?

Yes
Assume default
process.

No
Is it thefeedstock that is
unknown?

Box 4: Tier 3

Yes

Yes

No

No

Estimate emissions using Tier 1 default
emission factors using Equation 3.15. If
the annual primary product production
data are not available, use Equation 3.16.

Yes

Box 2: Tier 1

Assume default feedstock.

Estimate emissions using Tier 1 default
emission factors using Equation 3.15.

Subtract
carbonfrom carbon
balance.

Add carbon emitted tocarbon balance.
Estimate emissions
using Tier 2 carbon
balance.
Box 3: Tier 2

Box 1: Tier 1

Note:
1. See Volume 1 Chapter 4,"Methodological Choice and Identification of Key Categories" (noting Section 4.1.2 on limited resources), for
discussion of key categories and use of decision trees.

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Figure 3.9

Decision tree for estimation of CH 4 emissions from petrochemical industry
and carbon black industry
StartCollect
feedstockand theprocess
data1.

Yes

Are
both the typeof feedstock used andprocess
known?

Repeat for eachfeedstock andpetrochemical.
Are
plant-specificemission factors
available?

Yes

No

Yes
Estimate emissions
using Tier 3
plant-specificemission factors.
Box 3: Tier 3NoIsPetrochemicaland Carbon Black
Production a key category andis this subcategory
significant?

No
Is it theprocess that is
unknown?

Yes
Assume default
process.

No

Is it thefeedstock that is
unknown?
Yes
Assume default feedstock.

No

Estimate emissions using Tier 1 default
emission factors. If the annual primary
product production data are notavailable, use Equation 3.16.
Box 2: Tier 1

Estimate emissions using Tier 1 default
emission factors.
Box 1: Tier 1

Note:
1. See Volume 1 Chapter 4,"Methodological Choice and Identification of Key Categories" (noting Section 4.1.2 on limited resources), for
discussion of key categories and use of decision trees.
2. Note that there is no Tier 2 method for estimating CH4 emissions. The Tier 2 method is a total feedstock carbon mass balance methodthat is applicable to estimating total carbon (CO2) emissions but not applicable to estimating CH4 emissions.

The Tier 3 methodology can be used to estimate plant-level CO2 emissions and CH4 emissions. The Tier 3
method depends upon the availability of plant-specific data for the petrochemical process. The Tier 2
methodology is a mass balance approach that is applicable to estimating CO2 emissions but is not applicable toestimating CH4 emissions. When using the Tier 2 methodology, both carbon flows of primary and secondary
feedstocks to the process are included in the mass balance calculation. Carbon flows of primary fuels to the

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process may involve combustion of part of the hydrocarbon content for heat raising and the production of
secondary fuels (e.g., off gases). In order to apply the Tier 2 methodology the flows of primary and secondary
feedstocks to the process and the flows of primary and secondary products must be characterised, and the flows
of by-products burned for energy recovery within the process and flows of by-products transferred out of theprocess must be characterised.

CARBON DIOXIDEThe decision tree for choice of method for CO2 emissions is shown in Figure 3.8. The Tier 1, Tier 2, and Tier 3
methods are described in this section.

Tier 1 product-based emission factor method
The Tier 1 emission factor methodology is applied to estimate CO2 emissions from the petrochemical process incases where neither plant specific data nor activity data for carbon flows are available for the petrochemical
process. The Tier 1 emission factor method does not require activity data for the consumption of each carboncontaining feedstock to the petrochemical production process. It requires only activity data for the amount of
product produced. The Tier 1 methodology does not consider the carbon content of emissions of carbon
monoxide or NMVOC that may be generated by the petrochemical processes. The equations in this section for
petrochemical production processes also apply to carbon black production.
The Tier 1 method calculates emissions from petrochemical processes on the basis of activity data for productionof each petrochemical and the process-specific emission factor for each petrochemical, as shown in the Equation
3.15 for production of each primary petrochemical product (e.g., methanol, ethylene, ethylene dichloride,
ethylene oxide, acrylonitrile) and carbon black.
EQUATION 3.15
TIER 1 CO2 EMISSION CALCULATIONECO 2 i = PPi • EFi • GAF / 100
Where:
ECO2i = CO2 emissions from production of petrochemical i, tonnes
PPi = annual production of petrochemical i, tonnes
EFi = CO2 emission factor for petrochemical i, tonnes CO2/tonne product produced
GAF = Geographic Adjustment Factor (for Tier 1 CO2 emission factors for ethylene production, See
Table 3.15), percent
Tier 1 CO2 emission factors for ethylene production (discussed in Section 3.9.2.2) have been developed based ondata for ethylene steam crackers operating in Western Europe. Geographic Adjustment Factors are applied to theTier 1 emission factor to account for regional variability in steam cracker operating efficiency. Geographic
Adjustment Factors are only applicable to ethylene production.
If activity data for annual primary product production are not available, primary product production may be
estimated from feedstock consumption, as shown in the Equation 3.16:
EQUATION 3.16
PRIMARY PRODUCT PRODUCTION ESTIMATE CALCULATION
PPi = ∑ (FAi , k • SPPi , k )kWhere:
PPi = annual production of petrochemical i, tonnes
FAi,k = annual consumption of feedstock k consumed for production of petrochemical (i), tonnes
SPPi,k = specific primary product production factor for petrochemical i and feedstock k ,tonnes primary
product/tonne feedstock consumed
Either Equation 3.15 or both Equation 3.15 and Equation 3.16 would be applied separately to each of the known
feedstocks for each petrochemical process. The Tier 1 emissions estimate shown in Box 1 of Figure 3.8 would
utilise Equation 3.15, while the Tier 1 emissions estimate shown in Box 2 of Figure 3.8 would use either

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Equation 3.15 or both Equation 3.16 and Equation 3.15. Equation 3.15 would be utilised alone in cases whereannual primary product production data are available for the petrochemical process. In cases where annual
primary product production data are not available but feedstock consumption data are available for the
petrochemical process, Equation 3.16 would be utilised to estimate the annual production of primary products,
and the annual primary product production estimated using Equation 3.16 would then be applied in Equation
3.15 to estimate the emissions.

Tier 2 total feedstock carbon balance method
The Tier 2 method is a feedstock-specific and process-specific carbon balance approach. This approach isapplicable in cases where activity data are available for both feedstock consumption and primary and secondary
product production and disposition. Activity data for all carbon flows are required to implement the Tier 2
methodology. Examples of process flow diagrams that illustrate feedstock and product flows for the methanol,
ethylene dichloride, ethylene oxide, acrylonitrile, and carbon black production processes are included in an
Annex to Section 3.9. The number of potential feedstocks and products for ethylene production from the steam
cracking process is such that the process is better illustrated by a feedstock-product matrix rather than by aprocess flow diagram. The feedstock-product matrix for ethylene production is included in Table 3.25 in Section
3.9.2.3. A flow diagram of the Tier 2 method is shown in Figure 3.10.
Figure 3.10

Tier 2 carbon mass balance flow diagram
Identify Petrochemical Production Process.

Identify PrimaryFeedstock toProcess.

Identify Secondary
Feedstock(s) to
Process.

Identify Primary
Product ofProcess.

Identify Secondary
Product(s) of
Process.

Determine PrimaryFeedstock
Consumption using
activity data.

Determine Secondary
Feedstock
Consumption using
activity data.

Determine Primary
Product Production
using activity data.

Determine Secondary
Product Production
using activity data or
Table 3.25 andEquation 3.18
(ethylene) or Table
3.26 and Equation
3.19 (acrylonitrile).

Determine PrimaryFeedstock Carbon
Content using Table
3.10 or activity data.

Determine Secondary
Feedstock Carbon
Content using Table
3.10 or activity data.

Determine Primary
Product Carbon
Content using Table
3.10 or activity data.

Determine Secondary
Product Carbon Content
using Table 3.10 oractivity data.

Calculate carbon input{∑k(FAi,k・FCk) in Equation 3.17}

Calculate carbon output{[PPi・PCi + ∑j(SPi,j・SCj)] in
Equation 3.17}

Calculate carbon emissions from process using Equation 3.17.

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The Tier 2 method calculates the difference between the total amount of carbon entering into the production
process as primary and secondary feedstock and the amount of carbon leaving the production process as
petrochemical products. The difference in carbon content of the primary and secondary feedstocks and thecarbon content of the primary and secondary products produced by and recovered from the process is calculated
as CO2. The Tier 2 mass balance methodology is based on the assumption that all of the carbon input to theprocess is converted either into primary and secondary products or into CO2. This means that any of the carbon
input to the process that is converted into CO, CH4, or NMVOC are assumed to be CO2 emissions for the
purposes of the mass balance calculation.
The overall mass balance equation for the Tier 2 methodology is Equation 3.17.

EQUATION 3.17
OVERALL TIER 2 MASS BALANCE EQUATION


 
ECO 2i = ∑ (FAi , k • FCk ) −  PPi • PCi + ∑ SPi , j • SC j   • 44 12
 k
j

 

(

)

Where:
ECO2i = CO2 emissions from production of petrochemical i, tonnes
FAi,k = annual consumption of feedstock k for production of petrochemical i, tonnes
FCk = carbon content of feedstock k, tonnes C/tonne feedstock
PPi = annual production of primary petrochemical product i, tonnes
PCi = carbon content of primary petrochemical product i, tonnes C/tonne product
SPi,j = annual amount of secondary product j produced from production process for petrochemical i,tonnes[The value of SPi,j is zero for the methanol, ethylene dichloride, ethylene oxide, and carbon black
processes because there are no secondary products produced from these processes. For ethylene
production and acrylonitrile production, see secondary product production Equations 3.18 and 3.19
below to calculate values for SPi,j.]
SCj = carbon content of secondary product j, tonnes C/tonne productFor ethylene production and acrylonitrile production there are both primary and secondary products produced by
the process. If activity data are not available for the amount of secondary products produced by these processes,
the amount of secondary products produced may be estimated by applying default values to the primaryfeedstock consumption, as shown in Equations 3.18 and 3.19:

EQUATION 3.18
ESTIMATE SECONDARY PRODUCT PRODUCTION FROM PRIMARY PRODUCT [ETHYLENE]
PRODUCTION(

SPEthylene, j = ∑ FAEthylene, k • SSPj , kk)Where:
SPEthylene ,j = annual production of secondary product j from ethylene production, tonnes
FAEthylene k = annual consumption of feedstock k consumed for ethylene production, tonnes
SSPj,k = specific secondary product production factor for secondary product j and feedstock k, tonnes
secondary product/tonne feedstock consumed
EQUATION 3.19
ESTIMATE SECONDARY PRODUCT PRODUCTION FROM PRIMARY PRODUCT [ACRYLONITRILE]PRODUCTION(

SPAcrylonitrile, j = ∑ FPAcrylonitrile, k • SSPj , kk)Where:

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SP Acrylonitrile,j = annual production of secondary product j from acrylonitrile production, tonnes
FP Acrylonitrile,k = annual production of acrylonitrile from feedstock k, tonnes
SSPj,k = specific secondary product production factor for secondary product j and feedstock k, tonnes
secondary product/tonne acrylonitrile produced
Note: It is anticipated that in most cases only a single feedstock (propylene) would be used foracrylonitrile production.

Feedstock and product carbon contents

Carbon contents of feedstocks and products of petrochemical production processes are listed in Table 3.10, inunits of tonnes of carbon per tonne of feedstock or product. Carbon contents of pure substances (e.g., methanol)
are calculated from the chemical formula. Carbon contents of other feedstocks and products (e.g., carbon blackfeedstock, carbon black) are estimated from literature sources. Representative carbon contents of fossil fuels(e.g., natural gas, naphtha) can be found in Table 1.3 in Chapter 1 of Volume 2: Energy; however, carbon
contents for fossil fuels will vary by country and region and are best obtained from national energy statistics or
fossil fuel product specifications or national standards.

Tier 3 direct estimate of plant-specific emissions
The most rigorous good practice method is to use plant specific data to calculate CO2 emissions from thepetrochemical production process. In order to apply the Tier 3 method, plant-specific data and/or plant-specificmeasurements are required. The emissions from the petrochemical production process include CO2 emitted fromfuel or process by-products combusted to provide heat or thermal energy to the production process, CO2 emitted
from process vents, and CO2 emitted from flared waste gases. These emissions are calculated using Equations
3.20 through 3.22.
Overall CO2 emissions from the petrochemical production process are calculated using Equation 3.20
EQUATION 3.20
TIER 3 CO2 EMISSIONS CALCULATION EQUATIONECO 2i = ECombustion , i + E Process Vent , i + E Flare, i
Where:
ECO2i = CO2 emissions from production of petrochemical i, tonnes
E Combustion,i = CO2 emitted from fuel or process by-products combusted to provide heat or thermal energy
to the production process for petrochemical i, tonnes
E Process Vent,i = CO2 emitted from process vents during production of petrochemical i, tonnes
E Flare,i = CO2 emitted from flared waste gases during production of petrochemical i, tonnes
E combustion and E flare are given by Equations 3.21 and 3.22 where plant specific or national net calorific value data
should be used. The emission factor is given by the carbon content of the fuel, the combustion oxidation factor
and a constant (44/12) converting the result from carbon to CO2. If the emission factor is not known a default
value may be found in Table 1.4 in Chapter 1 of Volume 2: Energy. Net calorific values are included in Table
1.2 in Chapter 1 of Volume 2: Energy. Carbon contents are included in Table 1.3 in Chapter 1 of Volume 2:
Energy. For the process vents, inventory compilers should measure/estimate emissions of CO2 directly and thus
no further equation is provided.
EQUATION 3.21
FUEL COMBUSTION TIER 3 CO2 EMISSIONS CALCULATION
ECombustion, i = ∑ (FAi , k • NCVk • EFk )k

Where:
FAi,k = amount of fuel k consumed for production of petrochemical i, tonnes
NCVk = net calorific value of fuel k, TJ/tonne(Note: In Table 1.2 in Chapter 1 of Volume 2, net calorific values are expressed in TJ/kg)

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EFk = CO2 emission factor of fuel k, tonnes CO2/TJ(Note: In Table 1.4 in Chapter 1 of Volume 2, CO2 emission factors are expressed in kg/TJ)

EQUATION 3.22
FLARE GAS TIER 3 CO2 EMISSIONS CALCULATION
E Flare, i = ∑ (FGi , k • NCVk • EFk )k

Where:
FGi,k = amount of gas k flared during production of petrochemical i, tonnes
NCVk = net calorific value of flared gas k, TJ/tonne(Note: In Table 1.2 in Chapter 1 of Volume 2, net calorific values are expressed in TJ/kg)
EFk = CO2 emission factor of flared gas k, tonnes CO2/TJ(Note: In Table 1.4 in Chapter 1 of Volume 2, CO2 emission factors are expressed in kg/TJ)

TABLE 3.10
SPECIFIC CARBON CONTENT OF PETROCHEMICAL FEEDSTOCKS AND PRODUCTS
Substance

Carbon (tonne carbon per tonne feedstock or
product)

Acetonitrile

0.5852

Acrylonitrile

0.6664

Butadiene

0.888

Carbon black

0.970

Carbon Black Feedstock

0.900

Ethane0.856

Ethylene

0.856

Ethylene dichloride

0.245

Ethylene glycol

0.387

Ethylene oxide

0.545

Hydrogen Cyanide

0.4444

Methanol

0.375

Methane0.749

Propane0.817

Propylene

0.8563

Vinyl Chloride Monomer

0.384

Note: Carbon content values for natural gas and naphtha vary by country and region. Net
calorific values (NCV) for natural gas, naphtha, and other primary fuels that may be used as
petrochemical feedstocks are included in Table 1.2 in Chapter 1 of Volume 2: Energy.
Feedstock carbon contents are included in Table 1.3 in Chapter 1 of Volume 2: Energy.

METHANE
The decision tree for choice of method for CH4 emissions is shown in Figure 3.9. The Tier 1 and Tier 3 methods
for CH4 are described in this section. There is no Tier 2 method applicable to CH4 emissions.

Tier 1 product-based emission factor method
CH4 emissions from petrochemical processes may be fugitive emissions and/or process vent emissions. Fugitive
emissions are emitted from flanges, valves, and other process equipment. Emissions from process vent sources
include incomplete combustion of waste gas in flare and energy recovery systems. CH4 emissions using the Tier
1 method may be calculated using Equation 3.23 for fugitive CH4 emissions and Equation 3.24 for process vent2006 IPCC Guidelines for National Greenhouse Gas Inventories

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Volume 3: Industrial Processes and Product Useemissions and Equation 3.25 for total CH4 emissions. If annual primary product production data are not available
but feedstock consumption data are available for the petrochemical process, Equation 3.16 would be utilised toestimate the annual production of primary products, and the annual primary product production estimated using
Equation 3.16 would then be applied in Equations 3.23 and 3.24 to estimate the emissions.
EQUATION 3.23
TIER 1 CH4 FUGITIVE EMISSION CALCULATIONECH 4 Fugitive, i = PPi • EFf i

EQUATION 3.24
TIER 1 CH4 PROCESS VENT EMISSION CALCULATIONECH 4 Process Vent , i = PPi • EFpi

EQUATION 3.25
TIER 1 CH4 TOTAL EMISSIONS CALCULATIONECH 4Total , i = ECH 4 Fugitive, i + ECH 4 Process Vent , i
Where:
ECH4 Total,i = total emissions of CH4 from production of petrochemical i, kg
ECH4 Fugitive,i = fugitive emissions of CH4 from production of petrochemical i, kg
ECH4 Process Vent,i = process vent emissions of CH4 from production of petrochemical i, kg
PPi = annual production of petrochemical i, tonnes
EFfi = CH4 fugitive emission factor for petrochemical i, kg CH4/tonne productEFpi = CH4 process vent emission factor for petrochemical i, kg CH4/tonne productTier 2 total feedstock carbon balance method
The total feedstock carbon mass balance method is not applicable to estimation of CH4 emissions. The total
carbon mass balance method estimates the total carbon emissions from the process but does not directly provide
an estimate of the amount of the total carbon emissions that is emitted as CO2, CH4, CO, or NMVOC.

Tier 3 direct estimate of plant-specific emissions
The Tier 3 method is based on continuous or periodic plant-specific measurements. The emissions from thepetrochemical production process include CH4 emitted from fuel or process by-products combusted to provide
heat or thermal energy to the production process, CH4 emitted from process vents, and CH4 emitted from flared
waste gases. If methane is vented directly to the atmosphere this will dominate the emissions. CH4 emissions
from process vents may also be combusted in a flare or energy recovery device. Measurement of atmosphericconcentration of VOCs directly above the plants or in the plume is the preferred activity data for estimating
fugitive CH4 emissions; however, such data may not be available. The atmospheric measurements are generally
expensive and will most often not be continuous measurements but rather a discrete and periodic measurement
program to obtain data to be used as basis for the development of plant specific emission factors. The results ofsuch measurement programs would then be related to other plant process parameters to enable estimation ofemissions between measurement periods.
Direct measurement of VOC and CH4 concentrations in plant exhaust gas streams and direct measurement offugitive VOC and CH4 emissions from plant valves, fittings, and related equipment using a comprehensive leakdetection programme can also be used to obtain plant-specific activity data for developing Tier 3 estimates ofCH4 emissions. However the plant-specific leak detection programme should provide fugitive CH4 emissions
data for all of the relevant CH4-emitting plant equipment. Similarly, the plant-specific measurement data forstacks and vents would need to cover the major portion of stack and vent CH4 emissions sources at the plant inorder to provide a basis for a Tier 3 emission calculation.

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Emissions of CH4 from process stacks and vents may be estimated by direct measurement of the CH4
concentration of the exhaust gas or estimated as a component of the total VOC concentration measured in theexhaust gas. Fugitive emissions of CH4 from plant equipment (e.g., valves, fittings) may be estimated throughapplication of plant-specific leak detection data and plant equipment inventories, provided that the plant-specificleak detection program and equipment inventory are comprehensive, such that the program provides fugitive
CH4 emissions data for all of the relevant CH4-emitting plant equipment. Similarly, the plant-specificmeasurement data for stacks and vents would need to cover the major portion of stack and vent CH4 emissions
sources at the plant in order to provide a basis for a Tier 3 emission calculation.
Measurement of fugitive emissions may also be based on the CH4 concentration in the atmosphere immediately
above the plant or in a plume downwind. Such atmospheric measurement data would generally measureemissions from the entire plant, and does not separate between the different sources. In addition to CH4
concentration the area of the plume and the wind speed must be measured. The emissions are given by Equation
3.26.
EQUATION 3.26
TIER 3 CH4 EMISSION CALCULATION BASED ON ATMOSPHERIC MEASUREMENT DATA

[(

)

]

CH 4 Emissions = ∫t C total VOCs • CH 4 fraction − CH 4 background level • WS • PA

Where:
CH4 Emissions = total plant CH4 emissions, µg/s
C total VOCs = VOC concentration at the plant, µg/m3
CH4 fraction = fraction of total VOC concentration that is CH4, fraction
CH4 background level = ambient CH4 concentration at background location, µg/m3
WS = wind speed at the plant, m/s
PA = plume area, m2
Note: ∫t means the quantity should be summed over time.
Note that the Tier 3 methodology does not direct inventory compilers to conduct atmospheric measurements orother specific types of direct measurements to estimate site-specific CH4 emissions. It is anticipated that plantspecific leak detection data and plant-specific stack and vent emission data will be more readily available thanatmospheric measurement data. However, if atmospheric measurement data are available the data may be used
to develop Tier 3 estimates of CH4 emissions, or to verify other estimates. Atmospheric measurement data may
provide a more accurate estimate of process CH4 emissions than leak detection data and stack and vent emission
data. A plant would use either i) Equation 3.26 or ii) Equations 3.27, 3.28, and 3.29 to estimate CH4 emissions.
Process vent emissions are assumed to be monitored either discretely or continuously. The method of calculation
will vary depending upon the type of data, and therefore no separate equation is provided for process ventemissions calculation.
Overall emissions of CH4 from the petrochemical production process based on plant-specific leak detection dataand plant-specific stack and vent emissions data are calculated using Equation 3.27
EQUATION 3.27
TIER 3 CH4 EMISSIONS CALCULATION EQUATIONECH 4i = ECombustion, i + E Process Vent , i + E Flare, i
Where:
ECH4i = total emissions of CH4 from production of petrochemical i, kg
E Combustion,i = emissions of CH4 from fuel or process by-products combusted to provide heat or thermalenergy to the production process for petrochemical i, kg
E Process Vent,i = emissions of CH4 from process vents during production of petrochemical i, kg
E Flare,i = emissions of CH4 from flared waste gases during production of petrochemical i, kg
E combustion and E flare are given by Equations 3.28 and 3.29 where plant specific or national net calorific value data
should be used.

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EQUATION 3.28
FUEL COMBUSTION TIER 3 CH4 EMISSIONS CALCULATION
ECombustion, i = ∑ (FAi , k • NCVk • EFk )k

Where:
FAi,k = amount of fuel k consumed for production of petrochemical i, tonnes
NCVk = net calorific value of fuel k, TJ/tonne(Note: In Table 1.2 in Chapter 1 of Volume 2, net calorific values are expressed in TJ/kg)
EFk = CH4 emission factor of fuel k, kg/TJ

EQUATION 3.29
FLARE GAS TIER 3 CH4 EMISSIONS CALCULATION
E Flare, i = ∑ (FGi , k • NCVk • EFk )k

Where:
FGi,k = amount of gas k flared during production of petrochemical i, tonnes
NCVk = net calorific value of flared gas k, TJ/tonne(Note: In Table 1.2 in Chapter 1 of Volume2, net calorific values are expressed in TJ/kg)
EFk = CH4 emission factor of flared gas k, kg/TJ

3.9.2.2

C HOICE OF EMISSION FACTORSThis section includes a discussion of the choice of emission factors for the Tier 1 method. The Tier 2 method isbased on mass balance principles and the Tier 3 method is based on plant-specific data; therefore there are nodefault emission factors applicable to the Tier 2 and Tier 3 methods.
TABLE 3.11
PETROCHEMICAL PRODUCTION TIER 1 DEFAULT FEEDSTOCKS AND PROCESSESPetrochemical Process

Default Feedstock

Default Process

MethanolNatural Gas

Conventional steam reforming without primaryreformer

Ethylene

North America, South America,
Australia - Ethane
Other Continents - Naphtha

Steam cracking

Ethylene Dichloride /Vinyl Chloride Monomer

Ethylene

Balanced Process for EDC production withintegrated VCM production plant

Ethylene Oxide

Ethylene

Catalytic Oxidation, Air Process, with thermal
treatment

Acrylonitrile

Propylene

Direct Ammoxidation with secondary products
burned for energy recovery or flared

Carbon Black

Carbon black feedstock and natural gas

Furnace black process with thermal treatment

Steam cracking

TIER 1
Tier 1 emission factors for CO2 emissions and CH4 emissions for petrochemical products are provided below.
Tier 1 emission factors for CO2 emissions do not include carbon emitted as CO, CH4, or NMVOC. Separate Tier
1 emission factors are provided for CH4 emissions from petrochemical processes. Tier 1 emission factors are notprovided for carbon monoxide and NMVOC emissions.
The Tier 1 method allows for the selection of a ‘default’ feedstock and ‘default’ process in instances where
activity data are not available to identify the feedstock or the process utilised to produce the petrochemical.
Table 3.11 provides the default feedstocks and default processes for each petrochemical production process. In

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the event that no activity data are available concerning the specific processes and feedstocks used within acountry to produce the petrochemical, the default process and default feedstock identified in Table 3.11 and theassociated Tier 1 emission factors identified in the subsequent tables in this section are used to estimate the CO2
emissions from the petrochemical production process. Country-specific emission factors may be used instead ofthe default emission factors if country-specific factors are available.

Methanol
Carbon dioxide emissions

Emissions of CO2 from methanol production from the steam reforming and partial oxidation processes may be
estimated by applying the default process feedstock emission factors, or the feedstock-specific and processspecific emission factors in Table 3.12, to activity data for methanol production, process configuration andprocess feedstock. The default emission factors are based on the average of plant-specific CO2 emissions datareported for four methanol plants using the conventional steam reforming process without primary reformer andusing natural gas feedstock. Emissions data used in developing the default CO2 emission factor were reported
for conventional process methanol plants in New Zealand, Chile, and Canada and in the Netherlands. Emission
factors in the table include both the CO2 emissions arising from the process feedstock and the CO2 emissions
arising from feedstock combusted within the steam reforming process. Table 3.13 summarises the total feedstock
consumption, in units of GJ/tonne methanol produced, for the various methanol production process
configurations and feedstocks shown in Table 3.12.
The conventional reforming process can include a single reformer unit or both a primary reformer unit and asecondary reformer. The emission factors differ depending upon the number of reformer units. Lurgi is aprovider of methanol process technology and has published emission factors for several conventional reforming
process technologies, see Table 3.12. The production capacity of Mega Methanol plants is generally greater than
5 000 tonnes per day of methanol. The emission factors for the Lurgi Conventional process technologies should
be applied only if the specific process technology is known. Otherwise the emission factor for conventional
steam reforming without primary reformer, or the emission factor for conventional steam reforming with primaryreformer, should be applied.
The conventional steam reforming process for methanol production can be integrated with an ammonia
production process. The emission factor for integrated methanol and ammonia production should be used only if
the specific process technology is known.
TABLE 3.12
METHANOL PRODUCTION CO2 EMISSION FACTORS
tonne CO2/tonne methanol produced
Process Configuration

Feedstock

Nat. gas Nat. gas +CO2

Conventional Steam Reforming, without primary reformer (a)(Default Process and Natural Gas Default Feedstock)

0.67

Conventional Steam Reforming, with primary reformer (b)0.497

Conventional Steam Reforming, Lurgi Conventional process (c1)0.385

Conventional Steam Reforming, Lurgi Low Pressure Process (c2)0.267

Combined Steam Reforming, Lurgi Combined Process (c3)0.396

Conventional Steam Reforming, Lurgi Mega Methanol Process (c4)0.310Partial oxidation process (d)Conventional Steam Reforming with integrated ammonia production

Oil

Coal

Lignite

1.376

5.285

5.020

0.267

1.02

Nat. gas + CO2 feedstock process based on 0.2-0.3 tonne CO2 feedstock per tonne methanol
Emission factors in this table are calculated from the feedstock consumption values in Table 3.13 based on the following feedstock
carbon contents and heating values:
Natural Gas:

56 kg CO2/GJ

48.0 GJ/tonne

Oil:

74 kg CO2/GJ

42.7 GJ/tonne

Coal:

93 kg CO2/GJ

27.3 GJ/tonne

Lignite:111 kg CO2/GJ

Uncertainty values for this table are included in Table 3.27
Sources: (a) Struker, A, and Blok, K, 1995; Methanex, 2003: (b) Hinderink, 1996: (c1 – c4) Lurgi, 2004a; Lurgi, 2004b; Lurgi, 2004c:(d) FgH-ISI, 1999

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TABLE 3.13
METHANOL PRODUCTION FEEDSTOCK CONSUMPTION FACTORSGJ feedstock input /tonne methanol produced
Process Configuration

Feedstock

Nat. gas Nat. gas +CO2

Conventional Steam Reforming, without primary reforme (a)(Default Process and Natural Gas Default Feedstock)

36.5

Conventional Steam Reforming, with primary reformer (b)33.4

Conventional Steam Reforming, Lurgi Conventional process (c1)31.4

Conventional Steam Reforming, Lurgi Low Pressure Process (c2)29.3

Combined Steam Reforming, Lurgi Combined Process (c3)31.6

Conventional Steam Reforming, Lurgi Mega Methanol Process (c4)30.1Partial oxidation process (d)

Oil

Coal

Lignite

37.15

71.6

57.6

29.3

Nat. gas + CO2 feedstock process based on 0.2-0.3 tonne CO2 feedstock per tonne methanol
Sources: (a) Struker, A, and Blok, K, 1995; Methanex, 2003: (b) Hinderink, 1996: (c1 – c4) Lurgi, 2004a; Lurgi, 2004b; Lurgi, 2004c :(d) FgH-ISI, 1999
Uncertainty values for this table are included in Table 3.27

Methane emissions

Methanex reported CH4 emissions from two Canadian methanol production plants in their 1996 Climate Change
Action Plan (Methanex, 1996). Methanex reported that CH4 emissions from methanol production may arise fromreformers, package boilers, methanol distillation units, and crude methanol storage tanks. CH4 emissions fromthe plants accounted for approximately 0.5 percent to 1.0 percent of the total greenhouse gas emissions from theplants, but were reported to vary depending upon the level of maintenance and operational control of the plant
equipment. The average emission factor reported for two reporting years is 2.3 kg CH4 emissions per tonne ofmethanol produced. CH4 emissions from a second Methanex methanol production plant were reported to be 0.15
kg CH4 per tonne of methanol produced. The higher of the two reported values, 2.3 kg CH4 per tonne ofmethanol produced, should be applied as the default CH4 emission factor for methanol production. CH4emissions as low as 0.1 kg/tonne have been estimated for the methanol plant Tjeldbergodden, Norway (SFT,
2003a).

Ethylene
Carbon dioxide emissions

Emissions of CO2 from steam cracking for ethylene production may be estimated using the feedstock-specificemission factors in Table 3.14 and activity data for the amount of ethylene produced from the steam cracking
processes. Separate emission factors are provided in Table 3.14 for the CO2 emissions from feedstock
consumption and from supplemental energy consumption in the steam cracking process. However, the CO2
emissions from both feedstock consumption and supplemental energy consumption are to be reported as
Industrial Process emissions under the reporting convention discussed above. The default emission factors arederived from plant-specific data for steam crackers operating in Western Europe. The emission factors may be
adjusted by applying the default geographic adjustment factors in Table 3.15 to account for differences in theenergy efficiency of steam cracking units among various countries and regions. Note that as indicated in Table
3.11, the default feedstock for steam crackers operating in North and South America and Australia is ethane, andthe default feedstock for steam crackers operating on other continents is naphtha.
These default emission factors do not include CO2 emissions from flaring. Emissions from flaring amount toabout 7 percent of total emissions in a well-maintained plant in Norway. Steam cracking processes that utilise
naphtha, propane, and butane feedstocks are assumed to be energy neutral, requiring no use of supplemental fuel,therefore there are assumed to be no CO2 emissions associated with supplemental fuel consumption for thesefeedstocks.

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TABLE 3.14
STEAM CRACKING ETHYLENE PRODUCTION TIER 1 CO2 EMISSION FACTORS
tonnes CO2/tonne ethylene produced
Feedstock

NaphthaGas Oil

EthanePropaneButaneOther

Ethylene (Total Process and Energy Feedstock Use)

1.73

2.29

0.95

1.04

1.07

1.73

- Process Feedstock Use

1.73

2.17

0.76

1.04

1.07

1.73

- Supplemental Fuel (Energy Feedstock) Use

0

0.12

0.19

0

0

0

Source: Neelis, M., Patel, M., and de Feber, M., 2003, Table 2.3, Page 26.
Default feedstocks for ethylene production are identified in Table 3.11. The emission factors do not include supplemental fuel use in flares.
Other feedstocks are assumed to have the same product yields as naphtha feedstock.
Uncertainty values for this table are included in Table 3.27.

The emission factors in Table 3.14 may be used in the event that activity data are available only for the amountof ethylene produced by the steam cracking process. Steam cracking is a multi-product process that leads toethylene, propylene, butadiene, aromatics, and several other high-value chemicals. There is an inherent
assumption of a specific product mix in the default emission factors in Table 3.14. The default product mix foreach emission factor in Table 3.14 is identified in the ethylene steam cracking feedstock-product matrix in
Section 3.9.2.3. The feedstock/product matrix identifies the default values for production of ethylene, propylene,
and other hydrocarbon products from the steam cracking process in units of kilograms of each product produced
per tonne of feedstock. In order to develop the emission factors for steam cracking shown in Table 3.14 the total
CO2 process emissions of a steam cracker have been divided by the output of ethylene only. In other words
ethylene has been chosen as the reference for estimating the total CO2 emissions from the steam cracking process
as a whole. Multiplication of the emission factors in Table 3.14 by the ethylene production therefore leads to thetotal CO2 emissions resulting not only from the production of ethylene but also from the production of propylene,
butadiene, aromatics, and all other chemicals produced by the steam cracking process. The default emission
factors in Table 3.14 provide the total CO2 emissions from the steam cracking process, not only the CO2
emissions associated with the production of the ethylene from the steam cracking process.
TABLE 3.15
DEFAULT GEOGRAPHIC ADJUSTMENT FACTORS FOR TIER 1 CO2 EMISSION FACTORS FOR STEAM CRACKING ETHYLENE
PRODUCTION

Geographic Region

Adjustment Factor

Notes

Western Europe

100%

Values in Table 3.14 are based on data from Western
European steam crackers

Eastern Europe

110%

Not including Russia

Japan and Korea

90%

Asia, Africa, Russia

130%

North America and SouthAmerica and Australia

110%

Including Asia other than Japan and Korea

Source: Adjustment factors are based on data provided by Mr. Roger Matthews in personal communication to Mr. Martin Patel, May 2002.
Uncertainty values for this table are included in Table 3.27.

Methane emissions

Default fugitive CH4 emission factors for steam cracking of ethane and naphtha for ethylene production are
estimated from total VOC emissions factors and VOC species profile data from EMEP/CORINAIR Emission
Inventory Guidebook (EEA, 2005). Overall volatile organic compound emissions from steam cracking are
estimated to be 5 kg/tonne ethylene produced based on a European publication, for which the feedstock is
assumed to be naphtha, and estimated to be 10 kg VOC/tonne ethylene produced based on a U.S. publication, forwhich the feedstock is assumed to be ethane. From the total VOC emission factors the overall CH4 emissions
from steam cracking of naphtha are estimated from the VOC species profile to be 3 kg/tonne ethylene produced,
primarily from leakage losses, and the overall CH4 emissions from cracking of ethane are estimated from thespecies profile to be twice those from cracking of naphtha (6 kg/tonne ethylene produced); however these factors
are subject to uncertainty as the overall VOC emission factors of 5 kg VOC/tonne ethylene for naphtha feedstockand 10 kg VOC/tonne ethylene for ethane feedstock are each based on a single publication. Emissions of CH4

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estimated from the EMEP/CORINAIR data for steam cracking of naphtha.
Published data show a large variability in reported CH4 emission factors for ethylene production. The European
Association of Plastics Manufacturers (APME) Eco-Profiles of the European Plastics Industry reports a CH4
emission factor for ethylene production of 2.9 kg CH4/tonne ethylene produced, as referenced in the APME EcoProfiles for Olefins Production (Boustead, 2003a). The CH4 emission factor for ethylene steam cracker process
operations is based on life-cycle analysis data for 15 European steam crackers. Emissions as low as 0.14 kg
CH4/tonne ethylene are estimated on the basis of direct measurement at a Norwegian ethylene plant (SFT 2003b)
and as low as 0.03 kg CH4/tonne ethylene based on company data reported in the Australian Methodology for the
Estimation of Greenhouse Gas Emissions and Sinks, 2003 (AGO, 2005). Other European and Australian steam
cracker operators reported plant-specific CH4 emissions on the order of 10 percent of the values reported inTable 3.16 (DSM, 2002; Qenos, 2003; Qenos, 2005). Therefore, the emission factors in Table 3.16 should not be
used to estimate CH4 emissions from steam cracker ethylene plants for which plant-specific data are available.
In this case the plant-specific data and the Tier 3 method should be used. Default CH4 emission factors forvarious process feedstocks are shown in Table 3.16. Note that the default feedstocks for ethylene production are
identified in Table 3.11.
TABLE 3.16
DEFAULT METHANE EMISSION FACTORS FOR ETHYLENE PRODUCTION
Feedstock

kg CH4/ tonne ethylene produced

Ethane6Naphtha3

All Other Feedstocks

3

Source: EEA, 2005 (EMEP/CORINAIR Emission Inventory Guidebook)
Uncertainty values for this table are included in Table 3.27.

Ethylene dichloride and vinyl chloride monomer
Carbon dioxide emissions

Emission factors are provided in Table 3.17 for the ethylene dichloride and vinyl chloride monomer production
processes, including the direct chlorination process, oxychlorination process, and balanced process. The CO2
emission factors are derived by averaging plant-specific CO2 emissions data for European plants reported in the
Integrated Pollution Prevention and Control (IPPC) Reference Document on Best Available Techniques in the
Large Volume Organic Chemical Industry (European IPPC Bureau, February 2003; referred to in this section as
the IPPC LVOC BAT Document). Note that as indicated in Table 3.11, the default process is the balanced
process for EDC production with an integrated VCM production plant. The total CO2 emission factor for eachprocess includes noncombustion CO2 emissions from the ethylene dichloride process vent and combustion CO2emissions from ethylene dichloride plant combustion sources. Plant combustion source emission factors include
combustion of both process waste gas and auxiliary fuel in the process waste gas thermal incinerator. The
combustion-related emission factor does not include emissions from flares. Combustion-related emission factors
in Table 3.17 are based on data from oxychlorination process plants but the emission factors are assumed also toapply to direct chlorination and balanced process plants. Feedstock consumption factors for ethylene dichloride
and vinyl chloride monomer production processes are provided in Table 3.18. The PlasticsEurope EcoProfiles(Boustead, 2005) for EDC production indicates ethylene utilisation of 0.306 tonnes ethylene per tonne EDC
produced, based on eight European plants.

It should be noted that the CO2 emission factors in Table 3.17 in units of tonnes CO2 per tonne EDC produced
and in units of tonnes CO2 per tonne VCM produced are not additive. The two CO2 emission factors both apply
to the integrated EDC/VCM production process, however the tonnes CO2 per tonne EDC factor is based on EDC
production activity data while the tonnes CO2 per tonne VCM factor is based on VCM production activity data.
The CO2 emission factor that will be applied will depend upon whether activity data for EDC production or
activity data for VCM production are available. Similarly, the feedstock consumption factors in Table 3.18 inunits of tonnes ethylene consumed per tonne EDC produced and in units of tonnes ethylene consumed per tonne
VCM produced are not additive. The feedstock consumption factor that will be applied will depend upon
whether activity data are available for EDC production or for VCM production.

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TABLE 3.17
ETHYLENE DICHLORIDE/VINYL CHLORIDE PRODUCTION PROCESS TIER 1 CO2 EMISSION FACTORS
Process Configuration

tonne CO2/tonne EDC produced

tonne CO2/tonne VCM produced

negligible emissions

negligible emissions

Combustion Emissions

0.191

0.286

Total CO2 Emission Factor

0.191

0286

Noncombustion Process Vent

0.01130.0166

Combustion Emissions

0.191

0.286

Total CO2 Emission Factor

0.202

0.302

Noncombustion Process Vent

0.00570.0083

Combustion Emissions

0.191

0.286

Total CO2 Emission Factor

0.196

0.294

Direct Chlorination Process
Noncombustion Process Vent

Oxychlorination Process

Balanced Process [default process]Values for CO2 emissions from EDC and VCM production for several European production plants were provided in Tables 12.6 and12.7 of the IPPC LVOC BAT Document (European IPPC Bureau, 2003). These values were averaged to calculate CO2 emission factors
for EDC and VCM production. One EDC plant that is equipped with a CO2 control device and that reported zero CO2 emissions fromthe process is not included in the average emission factor.
Source: European IPPC Bureau, 2003 (IPPC LVOC BAT Document, Tables 12.6 and 12.7 data).
Uncertainty values for this table are included in Table 3.27.

TABLE 3.18
ETHYLENE DICHLORIDE/VINYL CHLORIDE MONOMER PROCESS TIER 1 FEEDSTOCK CONSUMPTION FACTORS
Process Configuration

tonne ethylene/tonne EDC
produced

tonne ethylene/tonne VCM
produced

Direct Chlorination Process

0.290

--

Oxychlorination Process

0.302

--

Balanced Process

0.296

0.47

Source: European IPPC Bureau, 2003 (IPPC LVOC BAT Document, Section 12.3.1, Page 299-300, Section 12.1 Table 12.3, Page 293).
Uncertainty values for this table are included in Table 3.27.

Methane emissions

The EMEP/CORINAIR ‘species profile’ for the ethylene dichloride/vinyl chloride monomer balanced process
indicates that there are no CH4 emissions from the process other than CH4 emissions from combustion sources.
The EMEP/CORINAIR species profile reports that VOC emissions from leakage losses and storage andhandling do not contain CH4. The EMEP/CORINAIR also reports that 2 percent of the total VOC emissions
from the balanced process are from combustion sources and that CH4 constitutes 1.2 percent of overall VOC
emissions. Therefore it may be assumed that non-combustion CH4 emissions from ethylene dichloride/vinyl
chloride monomer production are negligible.
CH4 emissions from combustion of natural gas supplemental fuel in the ethylene dichloride/vinyl chloride
monomer production process may be estimated from activity data for natural gas supplemental fuel consumption
and CH4 emission factor for natural gas combustion. Natural gas consumption for integrated ethylene
dichloride/vinyl chloride monomer production is estimated to be 110.1 Nm3 natural gas/tonne VCM produced for
an integrated ethylene dichloride/vinyl chloride monomer production plant in the Netherlands and 126.4 Nm3
natural gas/tonne VCM produced for an integrated ethylene dichloride/vinyl chloride monomer production plantin Germany. The average of these two values is 118.3 Nm3 natural gas/tonne VCM. The CH4 emission factor for
the integrated EDC/VCM production process is based on a CH4 emission factor of 5 g CH4/GJ natural gas
combusted and the average natural gas consumption of the two European plants. The default CH4 emission factor
for the integrated ethylene dichloride/vinyl chloride monomer production process is provided in Table 3.19. The

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default emission factor is not applicable to stand-alone EDC production plants. If natural gas consumption
activity data are available, the CH4 emission factor of 5 g CH4/GJ may be applied directly to the activity data,rather than using the default emission factor.
TABLE 3.19
ETHYLENE DICHLORIDE/VINYL CHLORIDE PROCESS TIER 1 DEFAULT CH4 EMISSION FACTOR
Process Configuration

kg CH4/tonne VCM product produced

Integrated EDC/VCM Production Plant

0.0226

Sources: European IPPC Bureau, 2003 (IPPC LVOC BAT Document, Section 12.3.1, Table 12.4, Page 300); EEA, 2005
(EMEP/CORINAIR Emission Inventory Guidebook, Processes in Organic Chemical Industries (Bulk Production) 1, 2-Dichloroethane
and Vinyl Chloride (Balanced Process), Activity 040505, February 15, 1996, Section 3.4, Page B455-3, and Table 9.2, B455-5).

Ethylene oxide
Carbon dioxide emissions

Emissions of CO2 from ethylene oxide production may be estimated using emission factors based on activity
data for ethylene oxide production, and activity data for process configuration and catalyst selectivity. Separate
CO2 emission factors are provided in Table 3.20 for the CO2 emissions from the air process and for the CO2
emissions from the oxygen process for a range of catalyst selectivity. The default emission factors for the airprocess and for the oxygen process are estimated from process-specific catalyst selectivity data provided in the
IPPC LVOC BAT document. Specific data concerning the type of process and the selectivity of the processcatalyst are needed in order to select emission factors from Table 3.20. The emission factors are derived from thecatalyst selectivity using stoichiometric principles and are based on the assumption that emissions of CH4 and
NMVOC from the process are negligible and that all of the carbon contained in the ethylene feedstock isconverted either into ethylene oxide product or to CO2 emissions. The emission factors in Table 3.20 do notinclude emissions from flares.
As shown in Table 3.20, the default emission factor for the air process is based on a default process catalyst
selectivity of 70 percent and the default emission factor for the oxygen process is based on a default catalyst
selectivity of 75 percent. If activity data are not available for the process configuration or the catalyst selectivity,
the default process configuration is the air process and the default catalyst selectivity is 70 percent. If activity
data are available that identify the process used as the oxygen process, but activity data are not for the catalyst
selectivity for the oxygen process, the emission factor for the default catalyst selectivity of 75 percent for theoxygen process in Table 3.20 should be used.
TABLE 3.20
ETHYLENE OXIDE PRODUCTION FEEDSTOCK CONSUMPTION AND CO2 EMISSION FACTORS
Process Configuration

Air Process [default process]Oxygen Process

Catalyst
Selectivity

Feedstock Consumption(tonne ethylene/
tonne ethylene oxide)

Emission Factor(tonne CO2/
tonne ethylene oxide)

Default (70)7580Default (75)
80
85

0.90
0.85
0.80
0.85
0.80
0.75

0.863
0.663
0.5
0.663
0.5
0.35

Source: European IPPC Bureau, 2003 (IPPC LVOC BAT Document, Section 9.2.1, Page 224, Section 9.3.1.1, Page 231, Figure 9.6)

Methane emissions

The IPPC LVOC BAT document for ethylene oxide production reported CH4 emissions factors (in units ofkilograms methane per tonne ethylene oxide produced) for the ethylene oxide process vent, ethylene oxide
purification process exhaust gas steam, and fugitive emissions sources. CH4 emission factors were reported in
the IPPC LVOC BAT document for European ethylene oxide plant carbon dioxide removal vents before andafter treatment. CH4 emissions were also reported for two ethylene oxide plants in the Netherlands. CH4emission factors for ethylene oxide production were developed by averaging these data. Emissions of CH4 may
be estimated by applying the emissions factors included in Table 3.21 to activity data for ethylene oxide
production. The default CH4 emission factor for ethylene oxide production assumes no thermal treatment process.

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TABLE 3.21
ETHYLENE OXIDE PRODUCTION TIER 1 CH4 EMISSION FACTORS
Process Configuration

kg CH4/tonne ethylene oxide produced

No Thermal Treatment [default factor]

1.79

Thermal Treatment

0.79

Source: European IPPC Bureau, 2003 (IPPC LVOC BAT Document, Table 9.6, Page 233; Table 9.8, Page 236; Table 9.9, Page 236).

Acrylonitrile
Carbon dioxide emissions

Process vent CO2 emissions from the acrylonitrile production process by the direct ammoxidation of propylene
may be calculated from acrylonitrile production activity data using the emission factors provided in Table 3.22:
TABLE 3.22
ACRYLONITRILE PRODUCTION CO2 EMISSION FACTORS
Process Configuration
Direct Ammoxidation of Propylene

tonnes CO2/tonne acrylonitrile produced

Secondary Products Burned for Energy Recovery/Flared (default)

1.00

Acetonitrile Burned for Energy Recovery/Flared

0.83

Acetonitrile and Hydrogen Cyanide Recovered as Product0.79

Source: European IPPC Bureau, 2003 (IPPC LVOC BAT Document, Section 11.3.1.1, Table 11.2, Page 274 and Section 11.3.1.2, Page
275)

The emission factors in Table 3.22 are based on an average (default) propylene feedstock consumption factor of
1.09 tonnes propylene feedstock per tonne acrylonitrile produced, corresponding to a primary product yieldfactor of approximately 70 percent. The default CO2 emission factor is based on conversion of propylene
feedstock to secondary product acetonitrile at 18.5 kilograms per tonne acrylonitrile produced, and conversion of
propylene to secondary product hydrogen cyanide at 105 kilograms per tonne acrylonitrile produced, and isbased on process-specific acrylonitrile yield data and process-specific feedstock consumption data reported in
the IPPC LVOC BAT document (European IPPC Bureau, 2003). Note however that the acrylonitrile production
process may be configured and operated to produce a greater or lesser amount of secondary products. The
default CO2 emission factor is based on the assumption that the secondary products (acetonitrile and hydrogencyanide) of the acrylonitrile production process and hydrocarbon by products in the main absorber vent gas areeither burned for energy recovery or flared to CO2 and are not recovered as products or emitted to theatmosphere without combustion treatment. The CO2 emission factors do not include CO2 emissions from any
combustion of auxiliary fuel (e.g., natural gas) for the process waste gas energy recovery or flare systems.
If activity data are not available concerning whether secondary products are recovered for sale, the default
assumption is that the secondary products are either burned for energy recovery or flared to CO2 and the default
primary product process yield factor is 70 percent.
For the process configuration where secondary products (acetonitrile and hydrogen cyanide) are recovered forsale and are not either flared to CO2 or burned for energy recovery, the overall process yield factor of primaryand secondary products is 85 percent.
If activity data for propylene feedstock consumption are not available, the propylene feedstock consumption may
be estimated from the acrylonitrile production activity data by applying a default feedstock consumption factorof 1.09 tonnes propylene feedstock consumed per tonne acrylonitrile produced.

Methane emissions

The Life-Cycle Analysis Data Summary for Acrylonitrile reports a CH4 emission factor for acrylonitrile
production of 0.18 kg CH4/tonne acrylonitrile produced, as referenced in the European Association of Plastics
Manufacturers (APME) Life-Cycle Analysis Report (Boustead, 1999). The CH4 emission factor for acrylonitrile
process operations is based on life-cycle analysis data for European acrylonitrile plants in Germany, Italy, andthe United Kingdom collected between 1990 and 1996. CH4 emissions from acrylonitrile production may be
estimated by applying this default emission factor to the acrylonitrile production data.

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Carbon black
Carbon dioxide emissions

Emissions of CO2 from carbon black production may be estimated by applying the process and feedstockspecific emission factors to the carbon black production activity data. Separate emission factors are provided inTable 3.23 for the furnace black process, thermal black process, and acetylene black process and their associatedfeedstocks, and separate emission factors are provided for primary feedstock and secondary feedstock. The
emission factors are based on the assumption that process emissions are subjected to a thermal treatment process.
A range of values for primary and secondary carbon black feedstock is included in Table 4.11 of the draft
Integrated Pollution Prevention and Control (IPPC) Reference Document for Best Available Techniques in the
Large Volume Inorganic Chemicals (LVIC) Solid and Others Industry (European IPPC Bureau, June 2005;
referred to in this chapter as the Draft IPPC LVIC BAT Document.) The CO2 emission factors in Table 3.23 arebased on the average of the range of values. Primary and secondary feedstock consumption is converted tocarbon consumption using average values for carbon black feedstock carbon content. The CO2 emission factors
are calculated from the carbon input to the process (primary and secondary feedstocks) and carbon output(carbon black) from the process, using an average value for carbon black carbon content.
TABLE 3.23
CARBON BLACK PRODUCTION TIER 1 CO2 EMISSION FACTORS
tonnes CO2/tonne carbon black produced
Process Configuration

Primary Feedstock

Secondary Feedstock

Total Feedstock

Furnace Black Process (default process)

1.96

0.66

2.62

Thermal Black Process

4.59

0.66

5.25

Acetylene Black Process

0.12

0.66

0.78

Source: European IPPC Bureau, 2005 (Draft IPPC LVIC BAT Document, Table 4.11 data)

Methane emissions

CH4 emissions for the carbon black production process are provided in Table 3.24. The draft IPPC LVIC BAT
document for carbon black reported the CH4 content of uncombusted tail gas from the carbon black production
process and the estimated rate of generation of tail gas from the carbon black production process. Based on
10,000 Nm3 tail gas per tonne carbon black produced and an average reported CH4 concentration of 0.425
percent by volume, the uncontrolled CH4 emission factors is 28.7 kg CH4/tonne carbon black produced.
Combustion flare efficiency for carbon black process flare systems was reported in the Draft IPPC LVIC BATDocument as 99.8 percent for carbon monoxide, and the same efficiency is assumed to apply to CH4. The CH4
emission factor for carbon black production after application of combustion control is 0.06 kg CH4/tonne carbon
black produced. An overall CH4 emission factor of 0.11 kg CH4/tonne carbon black, based on company data, wasreported in the Australian Methodology for the Estimation of Greenhouse Gas Emissions and Sinks, 2003 (AGO,
2005.) Three carbon black production plants in Germany reported a common CH4 emission factor of 0.03 kg
CH4/tonne carbon black produced, based on measurement data after waste gas combustion using BAT(Thermische Nachverbrennung als Stand der Technik.)
TABLE 3.24
CARBON BLACK PRODUCTION TIER 1 CH4 EMISSION FACTORS
Process Configuration

kilogram CH4/tonne carbon black produced(Carbon Black Process Tail Gas )No Thermal Treatment

28.7

Thermal Treatment (default process)

0.06

Source: European IPPC Bureau, 2005 (Draft IPPC LVIC BAT Document, Table 4.8, Page 209; Table 4.10,
Page 213, Section 4.3.2.3, Page 210).

TIER 2The Tier 2 methodology is based on mass balance calculations and therefore there are no emission factors
associated with the methodology.

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TIER 3For the Tier 3 method plant specific emissions may be estimated using Equations 3.20 through 3.22 for CO2, andusing either Equation 3.26 or Equations 3.27 through 3.29 for CH4. The emission factors may be related toannual production for estimation of emissions between measurements when these are not continuous.

3.9.2.3

C HOICE OF ACTIVITY DATA

General aspects of data collection for obtaining activity data are discussed in Chapter 2 of Volume 1. Whenusing the Tier 3 method plant-specific activity data should be obtained from the production plants. Direct
measurements of the total flow to the steam cracker and flare system together with an analysis of the gas carbon
content will provide the most accurate basis for an emissions estimate.
Plant specific energy balance and/or carbon balance may also be used to derive plant specific emission factors.
The variety of energy and carbon flows across the plant boundary makes this a data intensive but still much lessresource intensive approach. While feedstock consumption data may be hard to obtain sales data and national
statistics may provide approximate production volumes of the chemicals.

METHANOL
Emissions of CO2 from methanol production may be calculated from specific feedstock (e.g., natural gas)
consumption and product (methanol) production activity data and carbon mass balance calculations.

ETHYLENE
Emissions of CO2 from ethylene production may be calculated from specific feedstock consumption and productproduction activity data and carbon mass balance calculations. In order to create a complete mass balance for theethylene production process and implement the Tier 2 methodology for ethylene production, all feedstocks andthe production and disposition of all primary and secondary products of the process should be identified using
activity data. In cases where activity data are available for ethylene production but not available for productionof secondary products from the steam cracking process, the production of secondary products may be estimatedusing the default factors in Table 3.25 and Equation 3.18. However, use of these default factors is a less accurate
method than use of specific activity data for all primary and secondary products, and will increase theuncertainty of the estimate, as performance of steam crackers may vary depending on site-specific conditions.
For example, site-specific data reported for steam crackers operating in Germany indicate that hydrocarbon
losses under normal operating conditions are on the order of 8.5 kg per tonne of hydrocarbon feedstock (BASF,
2006) whereas the default value for hydrocarbon losses shown in Table 3.25 is 5 kg per tonne of hydrocarbon
feedstock. In the event that activity data are not available for all secondary products, the Tier 1 method can beapplied instead of the Tier 2 method.
Secondary products produced by the steam cracking process may recovered and transferred to a petrochemicalplant or petroleum refinery for material reuse, recycled within the steam cracking process as feedstock, or burnedfor energy recovery. Typically C4+ secondary products are recycled as feedstock or recovered for material reuse(BASF, 2006). Allocation of CO2 emissions from combustion of secondary products for energy recovery is
described in Box 1.1 in Chapter 1 of this volume. If activity data are not available for the disposition of C4+
secondary products the default assumption is that the C4+ secondary products are recovered and transferred toanother process for material reuse. If data are not available for the disposition of CH4 produced by the steam
cracking process, the default assumption is that the CH4 is burned for energy recovery within the steam cracking
process and results in CO2 emissions from the process.
Steam crackers operated within the petrochemical industry may obtain the petrochemical feedstock for theethylene production process directly from an adjacent petroleum refinery. Depending upon the feedstock andprocess operating conditions, steam crackers may also generate ‘backflows’ of hydrocarbon by-products that are
returned to the adjacent refinery for further processing. Any CO2 emissions from processing backflows at
petroleum refineries are not included in the process CO2 emission factors for the steam cracker ethylene
production process, but are considered in the feedstock and carbon flow analysis for the process.

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TABLE 3.25
ETHYLENE STEAM CRACKING FEEDSTOCK-PRODUCT MATRIX
kg product/tonne feedstock
Product

Feedstock

Naphtha645

Gas oil
569

Ethane842

Propane638

Butane635

Others645

Ethylene

324

250

803

465

441

324

Propylene

168

144

16

125

151

168

Butadiene

50

50

23

48

44

50

Aromatics

104

124

0

0

0

104

Fuel grade products and backflows

355

431

157

362

365

355

High Value Chemicals

Hydrogen

11

8

60

15

14

11

Methane

139

114

61

267

204

139

Ethane and propane after recycle

0

0

0

0

0

0

Other C4

62

40

6

12

33

62

C5/C6

40

21

26

63

108

40

C7+ non-aromatics

12

21

0

0

0

12

<430C

52

26

0

0

0

52

>430C

34

196

0

0

0

34

Losses

5

5

5

5

5

5

Total

1 000

1 000

1 000

1 000

1 000

1 000

Source: Neelis, M; Patel, M; de Feber, M; Copernicus Institute, April 2003, Table 2.2, Page 24

ETHYLENE DICHLORIDE AND VINYL CHLORIDE M ONOMEREmissions of CO2 from ethylene dichloride and vinyl chloride monomer production may be calculated from
specific feedstock (ethylene) consumption and product (ethylene dichloride) production activity data and carbon
mass balance calculations.

ETHYLENE OXIDEEmissions of CO2 from ethylene oxide production may be calculated from specific feedstock (ethylene)
consumption and product (ethylene oxide) production activity data and carbon mass balance calculations.

ACRYLONITRILE
In the event that activity data are not available for production of secondary products (acetonitrile and hydrogencyanide), the default values in Table 3.26 and Equation 3.19 may be applied to the activity data for primary
product production to estimate secondary product production.
TABLE 3.26
SECONDARY PRODUCT PRODUCTION FACTORS FOR ACRYLONITRILE PRODUCTION PROCESS
Secondary Productkg secondary product/tonne acrylonitrile produced

Acetonitrile

18.5

Hydrogen Cyanide

105

Note: The secondary product production factors in this table are based on acrylonitrile production from propylene feedstock. In theevent that feedstocks other than propylene are used, the factors in this table would not apply. Process-specific factors would need to be
developed in order to apply the Tier 2 mass balance approach to acrylonitrile production from feedstocks other than propylene.
Source: European IPPC Bureau, 2005 (IPPC LVOC BAT Document, Section 11.3.4, Page 27)

If no activity data are available concerning acetonitrile product recovery it may be assumed that it is notrecovered as product and is burned for energy recovery to CO2. If no activity data are available concerningthermal treatment of the acetonitrile main absorber vent gas it may be assumed that the vent gas is thermallytreated and combusted to CO2 and is not vented to the atmosphere uncontrolled.

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CARBON BLACK
Emissions of CO2 from carbon black production may be calculated from specific primary feedstock (e.g., carbon
black feedstock) and secondary feedstock (e.g., natural gas) consumption and product (carbon black) production
activity data and carbon mass balance calculations.

3.9.2.4

C OMPLETENESS

In estimating CO2 emissions from petrochemical and carbon black processes, there is a risk of double-counting
or omission in either the IPPU or the Energy Sector. Petrochemical and carbon black plants produce methaneand non-methane hydrocarbon by-products that may be burned for energy recovery and such energy recovery
may be reported in national energy statistics under ‘other’ fuels or some similar categorisation. If CO2 emissions
from ‘other’ fuel combustion include industrial process off gases that are burned for energy recovery someadjustment to the energy statistics or to the CO2 emissions calculation for petrochemical production would beneeded to avoid double counting of the CO2 emissions.

METHANOL
There may be production of methanol from biogenic (renewable) sources. Such biogenic methanol may beincorporated into methanol national production statistics, which would result in overestimation of CO2 emissions
from fossil fuel (e.g., natural gas) derived methanol unless adjustments are made to the methanol production
activity data.

ETHYLENE
There may be production of ethylene from petroleum refining processes or from petrochemical processes otherthan steam crackers. Such ethylene may be incorporated into ethylene national production statistics, which
would result in overestimation of CO2 emissions from steam cracker derived ethylene unless adjustments are
made to the ethylene production activity data.

ETHYLENE DICHLORIDE AND VINYL CHLORIDE MONOMER
Ethylene dichloride is an intermediate petrochemical product used to manufacture vinyl chloride monomer andother products. Activity data for production of ethylene dichloride may not be complete because the ethylene
dichloride may be converted directly to vinyl chloride monomer in an integrated EDC/VCM plant. Therefore it
may be the case that the vinyl chloride monomer production activity data are more complete with respect toindustry coverage than the ethylene dichloride production activity data. However, utilisation of vinyl chloride
monomer activity data as a surrogate for ethylene dichloride data also has issues related to completeness because
not all of the ethylene dichloride is used to manufacture vinyl chloride monomer. Therefore adjustments to theactivity data for vinyl chloride monomer may be needed to account for utilisation of ethylene dichloride in the
production of other products. Based on data for North America and Europe utilisation of ethylene dichloride for
products other than vinyl chloride monomer would amount to the order of 5 percent of total ethylene dichloride
production.

ETHYLENE OXIDE
Ethylene oxide is an intermediate petrochemical product used to manufacture ethylene glycols and otherproducts. Activity data for production of ethylene oxide may not be complete because the ethylene oxide may be
converted directly to ethylene glycol in an integrated EO/EG plant. Ethylene oxide may also be converted into
other products (e.g., amines, ethers, etc.) in integrated plants. Since only on the order of 70 percent of ethyleneoxide production worldwide is used in the manufacture of ethylene glycols, production activity data for chemical
products of ethylene oxide may not be more complete with respect to industry coverage than the ethylene oxide
production activity data.

CARBON BLACK
There may be small amounts of production of carbon black from biogenic (renewable) sources such as animal
black and bone black. Such biogenic carbon black may be incorporated into carbon black national production
statistics, which would result in overestimation of CO2 emissions from fossil fuel derived carbon black. Therealso may be carbon black production within the physical boundaries of petroleum refineries rather than within
the chemical industry. Carbon black produced within petroleum refineries is anticipated to be incorporated into
national carbon black production statistics, therefore CO2 emissions from carbon black production within
petroleum refineries should be reported along with other emissions from carbon black production within thechemical industry as industrial process emissions.
There may be gaps in completeness with respect to carbon black feedstock consumption activity data. Activity
data for carbon black feedstock derived from coal tar products, waste gases, or acetylene may not be available,

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which would result in underestimating of CO2 emissions from carbon black production if a higher-tier carbon
balance approach was used.

3.9.2.5

D EVELOPING CONSISTENT TIME SERIESThe emissions from petrochemical and carbon black production should be estimated using the same Tier andtype of activity data for all years. Constructing a time series for emissions from petrochemical and carbon black
production using plant specific measurement activity data will give the most accurate current emissions.
However activity data on flaring and fugitive emissions will most likely not be available for previous years. If notechnology upgrades have taken place calculating a plant specific emission factor based on recent measurement
data related to production of petrochemicals may provide a reasonable result. Petrochemical production is often
integrated in an industrial complex producing more than one chemical, or exchanges energy or chemical flows
with adjacent industrial plants, and carbon black may be produced within petroleum refineries. When
constructing a time series based on feedstock consumption great care should be taken to assure that the activity
data includes the same flows every year in the time series. Again a Tier 1 type calculation using emission factors
developed from recent plant specific emission estimates based on Tier 2 carbon balance calculation may be used.
Investigations to uncover a change in choice of feedstock as well as variations in primary and secondary
chemicals produced both within a single year and between years. Reconstruction of gaps in emission estimatesand recalculations should follow the guidance in Volume 1, Chapter 5.

3.9.3

Uncertainty assessment

Uncertainty assessments for each emissions factor and activity data applicable to each process are discussed inthis section. Uncertainty ranges for the emission factors and activity data included in the Tables in the previous
sections are summarised in Table 3.27.

METHANOL
Much of the uncertainty in emission estimates for methanol production is related to the difficulty in determining
activity data including the quantity of methanol produced and, for higher tier methodologies, the amount of
natural gas and other feedstocks consumed on an annual basis. Natural gas and other feedstock consumption may
only be reported on an annual basis in national energy statistics, without any breakout of consumption formethanol production. If natural gas consumption activity data are not available then only an emission factor
approach rather than a higher tier carbon balance approach is applicable. If activity data are not available for
consumption of other feedstocks for methanol production, it may be assumed that all of the national methanol
production is from natural gas feedstock. However, this assumption would introduce some uncertainty. Further,
activity data may not be available for annual CO2 feedstock consumption in methanol production plants thatutilise CO2 as a supplemental feedstock in the production process.

ETHYLENE
Uncertainty in activity data for ethylene production is related to the difficulty in determining the types, quantities,
and characteristics of feedstocks to the steam cracking process (e.g., ethane, naphtha) and the types, quantities,
and characteristics of products from the process (e.g., ethylene, propylene). Feedstock consumption and productproduction may only be reported on an annual basis in national energy statistics and commodity statistics,
without any breakout of feedstock consumption for ethylene production or product production from the steam
cracking ethylene production process. The ability to conduct a carbon balance calculation for ethylene
production depends upon the availability of both activity data for consumption of specific feedstocks andproduction of specific products of the steam cracking process. If only activity data for national annual ethylene
production are available, the default feedstock for the country/region may be assumed and the default emission
factor applied. In this case the feedstocks analysis would be conducted by utilising the default yield table for thedefault feedstock. However, considering the wide variability in emission factors and yield factors among thefeedstocks, the unavailability of specific feedstock consumption data would introduce significant uncertainty into
the emissions calculations and feedstocks analysis. If specific feedstock consumption activity data are available
then a separate emissions estimate and feedstocks analysis may be conducted for each feedstock, which would
reduce the uncertainty. Ideally, however, activity data would be available for both specific feedstock
consumption and specific product production, allowing a higher tier carbon balance calculation to be conducted.
Another source of uncertainty is related to the difficulty in determining other details of the steam cracking
ethylene process configuration, including backflows of products of the steam cracking process from thepetrochemical plant to the [potentially adjacent] petroleum refinery and flows of by products to energy recovery
or flaring. The unavailability of activity for refinery backflows would introduce uncertainty into the feedstocks
analysis.

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ETHYLENE DICHLORIDE AND VINYL CHLORIDE MONOMER
Sources of uncertainty for ethylene dichloride include the difficulty in determining the specific process utilised
for the ethylene dichloride production and in determining activity data for the consumption of ethylene feedstockin the production process. If only activity data for ethylene dichloride production are available, the emission
calculation may be conducted using the default [balanced] process product yield factor and default emission
factor for the process. However, considering the variability in emission factors and yield factors for theoxychlorination process, direct oxidation process, and balanced process, the unavailability of specific ethylene
feedstock consumption data by process would introduce significant uncertainty into the emissions calculations

ETHYLENE OXIDEA main source of uncertainty for ethylene oxide production is the difficulty in determining activity data for the
consumption of ethylene feedstock for ethylene oxide production. If ethylene consumption activity data are notavailable then only an emission factor approach rather than a higher tier carbon balance approach is applicable.
If only activity data for national annual ethylene oxide production are available, the default product yield may be
assumed and the default emission factor applied. In this case the feedstocks analysis would be conducted byutilising the default product yield factor. However, considering the range of reported product yield factors andemission factors for the ethylene oxide process, the unavailability of specific ethylene feedstock consumption
data would introduce significant uncertainty into the emissions calculations.

ACRYLONITRILE
Sources of uncertainty for acrylonitrile production include the difficulty in determining the specific process
configuration for acrylonitrile production, in determining activity data for the consumption of propylene
feedstock in the production process, and in determining activity data for the production of acrylonitrile andacetonitrile from the process. If only activity data for acrylonitrile production are available, the emission
calculation may be conducted using the default process configuration (assuming no acetonitrile recovery) anddefault emission factor for the process. However, the assumption that acetonitrile is not recovered from theprocess introduces significant uncertainty in the emission and feedstocks calculations and may result inoverestimation of emissions and underestimation of feedstocks flows from the acrylonitrile process. Activity
data for national production of both acrylonitrile and acetonitrile from the acrylonitrile production process would
allow application of the process-specific emission factor for the percentage of national acrylonitrile production
from which acetonitrile is recovered. Ideally, however, activity data for propylene consumption and activity data
for acrylonitrile, acetonitrile, and hydrogen cyanide production from the acrylonitrile production process would
allow utilisation of a higher-tier method, which would reduce the uncertainty.

CARBON BLACK
Uncertainty in activity data for carbon black production is related to the difficulty in determining the types,
quantities, and characteristics of primary and secondary feedstocks to the carbon black process, and in
determining the type of process used for the carbon black production and the characteristics of the carbon black
product from the process. Primary and secondary feedstock consumption and carbon black production may only
be reported on an annual basis in national energy statistics and commodity statistics, without any breakout offeedstock consumption for carbon black production for each carbon black production process. Most worldwide
production of carbon black is by the furnace black process, therefore if feedstock consumption activity data are
not available by process, all of the carbon black production may be assumed to be from the furnace black process
without introducing a large amount of uncertainty.
Also, if activity data are available for primary carbon black feedstock consumption, the data may be reported ingeneric terms as ‘carbon black feedstock’ without any indication of whether the feedstock is a petroleum-based
feedstock produced at petroleum refineries or a coal tar-based feedstock produced from metallurgical cokeproduction. Activity data may also not be available for other primary carbon black feedstocks (e.g., acetylene).
Also, specific activity data may be available for natural gas consumption as secondary carbon black feedstock,
however, activity data may not be available for other secondary feedstocks that may be used in carbon black
production (e.g., coke oven gas). Unavailability of specific primary and secondary feedstock consumption data
would add uncertainty to the feedstocks analysis.
The ability to conduct a carbon balance calculation for carbon black production depends upon the availability ofactivity data for the consumption and the characteristics of primary and secondary feedstocks. If only activity
data for national annual carbon black production are available, the default feedstock characteristics and productyield may be assumed and the default emission factor may be applied. However, considering the variability infeedstock characteristics and origin, the unavailability of specific feedstock consumption and composition
activity data would introduce significant uncertainty into the emissions and feedstocks calculations. If specificfeedstock consumption and characteristics activity data and associated carbon black production activity data are2006 IPCC Guidelines for National Greenhouse Gas Inventories

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UNCERTAINTY RANGES
Uncertainty ranges for Tier 1 emission factors and Tier 2 activity data and Tier 3 activity data for each process
are provided in Table 3.27. The source of the data or expert judgement used in preparing the uncertainty estimate
is identified in the table for each factor or activity data. Expert judgement elicitation was conducted byevaluating the range of available data. In many cases process-specific data were available only for several plants;
the relatively large uncertainty ranges are the result of the relatively few data available and the expectedvariability of process configurations and feedstock utilisation efficiency among petrochemical and carbon black
plants.
TABLE 3.27
UNCERTAINTY RANGES FOR EMISSION FACTORS AND ACTIVITY DATA
MethodReference

Tier 3

Factor

Uncertainty Range

SourceDirect measurement of fuelconsumption together with gas
composition samples for all
substances- 5 to + 5 %Expert judgement by Lead
Authors of Section 3.9, on thebasis of discussions withnational industry January 2005.

Tier 1

Table 3.12

Methanol production CO2emission factors-30% to +30%

Expert judgement by Lead
Authors of Section 3.9.

Tier 1

Table 3.13

Methanol Production Feedstock
Consumption Factors-30% to +30%

Expert judgement by Lead
Authors of Section 3.9.

Methane Emission Factor for
Methanol Production-80% to +30%

Expert judgement by Lead
Authors of Section 3.9 on thebasis of Methanex plant data.

Tier 1

Tier 1

Table 3.14

Ethylene Production CO2Emission Factors-30% to +30%

IPPC LVOC BAT Document,
Figure 7.10,

Tier 1

Table 3.15

Geographic Adjustment Factors
For CO2 Emissions Factors For
Ethylene Production-10% to +10%

Expert judgement by Lead
Authors of Section 3.9.

Tier 1

Table 3.16

Methane Emission Factors for
Ethylene Production-10% to +10%

Expert judgement by Lead
Authors of Section 3.9.

Tier 1

Table 3.17

Ethylene Dichloride/Vinyl
Chloride Production Process
Vent CO2 Emission Factors-20% to +10%

IPPC LVOC BAT Document,
Tables 12.6 and 12.7

Tier 1

Table 3.17

Ethylene Dichloride/Vinyl
Chloride Production CO2Emission Factors-50% to +20%

IPPC LVOC BAT Document,
Tables 12.6 and 12.7

Tier 1

Table 3.18

Ethylene Dichloride/Vinyl
Chloride Monomer Process
Feedstock Consumption
Factors-2% to +2%

IPPC LVOC BAT Document,
Section 12.3.1, Page 300

Tier 1

Table 3.19

Ethylene Dichloride/Vinyl
Chloride Monomer Process
CH4 Emission Factors-10% to +10%

IPPC LVOC BAT Document,
Section 12.3.1, Table 12.4, Page
300

Tier 1

Table 3.20

Ethylene Oxide Production
Feedstock Consumption and
CO2 Emission Factors-10% to +10%

Expert judgement by
Lead Authors of Section 3.9.

Tier 1

Table 3.21

Ethylene Oxide Production
CH4 Emission Factors-60% to +60%

IPPC LVOC BAT Document,
Table 9.6, Page 233; Table 9.8,
Page 236; Table 9.9, Page 236

Tier 1

Table 3.22

Acrylonitrile Production CO2Emission Factors-60% to +60%

IPPC LVOC BAT Document,
Section 11.3.1.1, Table 11.2,
Page 274.

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TABLE 3.27 (CONTINUATION)UNCERTAINTY RANGES FOR EMISSION FACTORS AND ACTIVITY DATA
MethodReference

Tier 1

Factor

Uncertainty Range

SourceAcrylonitrile Production CH4Emission Factors-10% to +10%

Boustead, 2003b (Eco-Profilesof the European Plastics
Industry Methodology I.
Boustead, Report prepared for
APME, July 2003, Page 40)

Tier 1

Table 3.23

Carbon Black Production CO2Emission Factors-15% to +15%

Draft IPPC LVIC BATDocument, Table 4.11, Page 214

Tier 1

Table 3.24

Carbon Black Production CH4Emission Factors-85% to +85%

Draft IPPC LVIC BATDocument, Table 4.8, Page 209

Tier 2

Table 3.25

Ethylene Steam Cracking
Feedstock-Product Matrix-10% to + 10%

Expert judgement by Contributing
Authors of Section 3.9

Tier 2

Table 3.26

Secondary Product Production
Factors for Acrylonitrile
Production Process-20% to +20%

Expert judgement by Lead
Authors of Section 3.9.

3.9.4
3.9.4.1

Quality Assessment/Quality Control (QA/QC),
Reporting and Documentation
Q UALITY A SSESSMENT /Q UALITY C ONTROL

Quality Assurance/Quality Control for emissions factors and activity data involves methods to improve thequality or better understand the uncertainty of the emissions estimates. It is good practice to conduct quality
control checks for the Tier 1 method as outlined in Volume 1, Chapter 6. More extensive quality control checks
and quality assurance procedures are applicable, if Tier 2 or Tier 3 methods are used to determine emissions.
Inventory compilers are encouraged to use higher tier QA/QC for key categories as identified in Volume 1,
Chapter 4.

Evaluation of Tier 1 and Tier 2 method activity data
The Tier 1 and Tier 2 methods both depend upon the application of activity data for petrochemical and carbon
black production and/or activity data for feedstock consumption. These activity data should not be expected tovary by more than about +/- 10 percent year to year, barring significant changes in the overall economic outputof the country, the construction of new petrochemical production capacity, or other similar factors. If theactivity data vary by more than about +/-10 percent year to year, it is good practice to assess and document thecountry-specific conditions that account for the differences.

Evaluation of Tier 1 method emission factors
Inventory compilers that develop country-specific emission factors for petrochemical and carbon black
production and apply the Tier 1 method should assess whether the estimated emission factors are within therange of the default emission factors and process-specific emission factors provided for the Tier 1 method in thisguidance. If the emission factors are outside of the range of factors reported in this Guidance, then the reasons
why this is the case should be investigated (e.g., the process configuration differs from that for the emission
factors reported in this guidance; the feedstock is a unique material not considered in this Guidance.) Inventory
compilers should also ensure that the country-specific emission factors are consistent with the values derived
from analysis of the process chemistry. For example, for methanol production from natural gas the carbon
content of the CO2 generated, as estimated using the emission factor, should equal approximately the difference
between the carbon content of the natural gas feedstock and the carbon content of the methanol product. If theemission factors are outside of the estimated ranges, it is good practice to assess and document the plant-specificconditions that account for the differences. It is also good practice or inventory compilers using Tier 1 method
emission factors included in this Guidance to conduct quality control checks to assess whether the datacharacteristics of the emission factor conform to the characteristics of the petrochemical and carbon black
production processes in the country in which the emission factor is applied.

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Evaluation of Tier 2 method mass balance calculations
Application of the Tier 2 mass balance method depends upon the identification and characterisation of process
flows. For the Tier 2 method, failure to identify all carbon-containing process flows or mischaracterisation of theflow rates or carbon contents of such process flows could result in significant deviation of the estimated CO2
emissions from the actual CO2 emissions. The quality of Tier 2 mass balance calculation results are generally
more dependent upon the quality of the activity data than are Tier 1 calculation results because in general agreater number of activity data need to be applied to the Tier 2 method than to the Tier 1 method. Therefore, it isgood practice to assess and document the quality of each activity data applied to the Tier 2 method and thecompleteness of the activity data prior to applying the Tier 2 method. If the data quality or completeness are
deemed not adequate for application of the Tier 2 method then the Tier 1 method should be applied.

Evaluation of Tier 3 method plant-specific data
The Tier 3 method is based on the application of plant-specific emissions data. It is good practice for inventory
compilers that conduct audits of plant-specific emissions estimates used in the inventory. This involves
evaluating whether the plant-specific data are representative of plant emissions and, if plant-specific data for a
specific plant are applied to the national inventory, evaluating whether the plant-specific data representative of
petrochemical and carbon black production processes in the country as a whole. Audits of plant-specific data
would involve the evaluation of:•Documentation of plant-specific measurement methodology;•

Documentation of plant-specific measurement results;•

Emissions estimation method and calculations;•

Process feedstock(s) and product(s)•Activity data employed in emissions calculations;•

Documentation of process technology and configuration;•

List of assumptions;

If the specific process for which plant-specific data are obtained is deemed not to be representative of otherplants in the country producing the same petrochemical (e.g., if the feedstock differs or the process configurationdiffers) then the plant-specific data should not be applied to the overall inventory but only to the activity data forthe specific plant. If emission measurements from individual plants are collected, inventory compilers should
ensure that the measurements were made according to recognised national or international standards and thequality control methods were applied to the emissions measurement. Quality control procedures in use at theplant should be directly referenced and included in the quality control plan. If the measurement practices were
not consistent with quality control standards or if the measurement procedures and results cannot be adequately
documented, the inventory compiler should reconsider the use of the plant-specific data.

3.9.4.2

R EPORTING AND D OCUMENTATION

Combustion emissions from combustion of off gases generated by petrochemical production processes are
attributed to the IPPU Sector source category which produces them, and are reported as industrial process
emissions. However, if any portion of the off gases generated by an IPPU Sector source category is combusted
within a different IPPU Sector source category, or combusted within an Energy Sector source category, thecorresponding emissions are reported as fuel combustion emissions rather than as industrial process emissions.
This means that if the combustion emissions occur within the IPPU Sector source category which produced theoff gases, then the emissions are reported as industrial process emissions attributed to that IPPU Sector source
category. However, if the off gases are transferred out of the process to another source category in the IPPU
Sector or a source category in the Energy Sector, then the emissions from the combustion of the off gases arereported as fuel combustion emissions within that source category. When the total emissions from the
combustion of the off gases are calculated, the quantity transferred to and reported in the Energy Sector and thequantity transferred to and reported in a different IPPU Sector source category should be clearly quantified in the
IPPU Sector source category calculations and in the Energy Sector source category calculations. If a countryspecific emission factor was developed, the corresponding data should be provided as how the emission factor
was developed and applied in the emission factor calculation, including reporting of the production process
configuration upon which the emission factor and calculation are based.

METHANOL
The amount of methanol produced, the amount of natural gas feedstock consumed in methanol production, andthe amount of supplemental CO2 feedstock consumed in methanol production are to be reported when available.

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If a default emission factor is used, this should be noted in the reporting documentation, and the methanol
production process configuration should be reported in the event that the default process configuration is not
used.

ETHYLENE
The amount of each feedstock consumed in ethylene production and the amounts of ethylene and each otherprimary product produced and recovered as product are to be reported when available. If a default emission
factor is used, this should be noted in the reporting documentation, and the ethylene production process
configuration and feedstock(s) should be reported in the event that the default process configuration and default
feedstock for the country/region are not used.

ETHYLENE DICHLORIDE
The amount of ethylene dichloride produced and ethylene feedstock consumed in ethylene dichloride production
are to be reported when available. If a default emission factor is used, this should be noted in the reporting
documentation, and the ethylene dichloride production process configuration should be reported in the event thatthe default process configuration is not used.

ETHYLENE OXIDEThe amount of ethylene oxide produced and ethylene feedstock consumed in ethylene oxide production are to bereported when available. If a default emission factor is used, this should be noted in the reporting documentation,and the ethylene oxide production process configuration should be reported in the event that the default process
configuration is not used.

ACRYLONITRILE
The amount of propylene feedstock consumed in acrylonitrile production and the amounts of acrylonitrile,
acetonitrile, and hydrogen cyanide produced and recovered as product are to be reported when available. If a
default emission factor is used, this should be noted in the reporting documentation, and the acrylonitrile
production process configuration should be reported in the event that the default process configuration is not
used.

CARBON BLACK
The amount of carbon black produced and the amounts and characteristics (carbon content) of each primary andsecondary feedstock consumed in carbon black production are to be reported when available. If a default
emission factor is used, this should be noted in the reporting documentation, and the carbon black production
process configuration should be reported in the event that the default process configuration is not used.

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Annex 3.9A
Figure 3.11

Feedstock-product flow diagrams
Methanol production feedstock-product flow diagram
Vent Gas CO2

Flare CO2

Energy Recovery
Process Steam
Secondary Feedstock
Carbon Dioxide

Primary Feedstock
Natural Gas

Figure 3.12

Process
Purge Gas

Steam Reforming
Process

Methanol
Production Process

Methanol Product

Methanol ProductPurification

Process
Vent Gas

Ethylene dichloride production feedstock-product flow diagram
Vent Gas CO2

Flare CO2

Vent Gas Incinerator
Process
Vent Gas
Primary Feedstock
Ethylene

ChlorinatedHydrocarbons

Oxychlorination
Process Reactor
Ethylene Dichloride
Purification Process

Primary Feedstock
Ethylene

Direct Chlorination
Process Reactor
Ethylene Dichloride Product3.90

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Figure 3.13

Ethylene oxide production feedstock-product flow diagram
Vent Gas CO2

Flare CO2

Energy Recovery
Process
Vent Gas
Primary Feedstock
Ethylene

Figure 3.14

Ethylene Oxide
Reactor Process

Ethylene Oxide
Product

Ethylene Oxide
Recovery Process

Acrylonitrile production feedstock-product flow diagram
Flare CO2

Vent Gas CO2

Energy Recovery
No

Absorber
Vent Gas
Primary Feedstock
Propylene

Ammoxidation
Reactor Process

Acrylonitrile ProductPurification

Acrylonitrile Product

Acetonitrile By-productHydrogen Cyanide
By-productFigure 3.15

Acetonitrile
By-product
Recovery?

Product
Recovery Process

Yes

Yes

No

Hydrogen
CyanideRecovery?

Carbon black production feedstock-product flow diagram
Flare CO2

Vent Gas CO2

Energy Recovery
Process
Vent Gas
Primary Feedstock
Carbon Black Feedstock
Secondary Feedstock
Natural Gas

Furnace Black
Process Reactor

2006 IPCC Guidelines for National Greenhouse Gas Inventories

Carbon Black
Product Dryers

Carbon Black
Product

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3.10

FLUOROCHEMICAL PRODUCTION

3.10.1

HFC-23 emission from HCFC-22 production

3.10.1.1

I NTRODUCTION

Trifluoromethane (HFC-23 or CHF3), is generated as a by-product during the manufacture ofchlorodifluoromethane (HCFC-22 or CHClF2). 3 Materials such as HFC-23 (and other HFCs, PFCs and SF6) arenot significantly removed by aqueous (acidic, neutral or alkaline) scrubbing processes and will be released into
the atmosphere. It is estimated that in 1990 the HFC-23 released from HCFC-22 plants was at most 4 percent of
the production of HCFC-22 (U.S. EPA, 2001), in the absence of abatement measures. There are a small numberof HCFC-22 production plants globally and thus a discrete number of point sources of HFC-23 emissions. While
the methodology described here is applicable to by-product emissions of any fluorinated greenhouse gas, it has
been written specifically for HFC-23. The methodology for emissions of fluorinated by-products in general and‘fugitive emissions’ is covered by Section 3.10.2.

3.10.1.2

M ETHODOLOGICAL ISSUESCHOICE OF METHOD
There are two broad measurement approaches to estimating HFC-23 emissions from HCFC-22 plants. These aredescribed in IPCC (2000), DEFRA (2002a and 2002b), EFCTC (2003) and UN (2004) and have been translated
into Tier 2 and 3 methodologies described below. National emissions using either of these methodologies are thesum of those from the individual facilities. Tier 1 (default) methodology can be applied to individual plants or, if
there is no abatement by destruction, to the total national output of HCFC-22. Accounting for HFC-23 emissions
is not simply mechanistic but requires information on the process operations responsible for producing andemitting HFC-23, so that the most appropriate methodology and factors can be adopted. Therefore, it is goodpractice, to the extent possible, to establish contacts with plant managers in order to obtain the necessary data.
The Tier 1 method is relatively simple, involving the application of a default emission factor to the quantity of
HCFC-22 produced. This method can be applied at the plant level or the national level. Tier 2 and Tier 3
methodologies are suitable only for plant level calculations because they rely on data that are only available fromplants. In cases where there are Tier 3 data available for some plants, the Tier 1 or Tier 2 methods can be applied
to the remainder to ensure complete coverage.
It is good practice to estimate national emissions by summing measured parameters from all HCFC-22 plants ina country. Tier 3 plant emission measurements are the most accurate, followed by Tier 2 measurements based onplant efficiencies. Direct measurement is significantly more accurate than Tier 1 because it reflects theconditions specific to each manufacturing facility. In most cases, the data necessary to prepare Tier 3 estimatesshould be available because facilities operating to good business practice perform regular or periodic sampling of
the final process vent or within the process itself as part of routine operations. The Tier 1 (default) methodshould be used only in cases where plant-specific data are unavailable and this subcategory is not identified as
significant subcategory under key category. (See Section 4.2 of Volume 1.) Modern plant using processoptimization will need to keep accurate HFC-23 generation data as part of this optimization, so plant-specificdata should be available to most countries in most cases.
The choice of good practice method will depend on national circumstances. The decision tree in Figure 3.16
describes good practice in adapting the methods in these Guidelines to country-specific circumstances.
Procedures to abate emissions include destruction of HFC-23 in a discrete facility and, in this case, emissions
occur only when the destruction facility is not in operation. The tiers of methodology provide estimates for thequantity of HFC-23 that is produced and the share of production that is ultimately emitted depends on the lengthof time that the destruction facility is not operated. For facilities using abatement techniques such as HFC-23
destruction, verification of the abatement efficiency is also done routinely. It is good practice to subtract abated
HFC-23 emissions from national estimates where the abatement has been verified by process records on every
plant.

3

HCFC-22 is used as a refrigerant in several different applications, as a blend component in foam blowing, and as achemical feedstock for manufacturing synthetic polymers.

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Tier 1In the Tier 1 methodology, a default factor is used to estimate production (and potential emissions) of HFC-23
from the total HCFC-22 production from each facility (for both potentially dispersive uses, as reported under theMontreal Protocol, and feedstock uses, which are reported separately to the Ozone Secretariat). See Equation
3.30.
EQUATION 3.30
TIER 1 CALCULATION OF HFC-23 FROM HCFC-22 (PRODUCED) USING DEFAULT FACTOR
E HFC − 23 = EFdefault • PHCFC − 22
Where:
EHFC-23 = by-product HFC-23 emissions from HCFC-22 production, kg
EFdefault = HFC-23 default emission factor, kg HFC-23/kg HCFC-22
PHCFC-22 = total HCFC-22 production, kg
This methodology is suitable where plant-specific measurements are not available and, in that case, the default
condition is that all of the estimated HFC-23 production is released into the atmosphere.

Tier 2In the Tier 2 methodology, the HFC-23 emission factor is derived from records of process efficiencies and usedin the calculation shown as Equation 3.31. This is a material balance approach and relies on calculating thedifference between the expected production of HCFC-22 and the actual production and then assigning thatdifference to loss of raw materials, loss of product (HCFC-22) and conversion to by-products, including HFC-23.
These parameters will be different for each plant and so should be assessed separately for each facility reporting
into the national data.
EQUATION 3.31
TIER 2 CALCULATION OF HFC-23 FROM HCFC-22 (PRODUCED) USING FACTOR(S) CALCULATEDFROM PROCESS EFFICIENCIESE HFC − 23 = EFcalculated • PHCFC − 22 • Freleased

Where:
EHFC-23 = by-product HFC-23 emissions from HCFC-22 production, kg
EFcalculated = HFC-23 calculated emission factor, kg HFC-23/kg HCFC-22
PHCFC-22 = total HCFC-22 production, kg
Freleased = Fraction of the year that this stream was released to atmosphere untreated, fraction
The emission factor can be calculated from both the carbon efficiency (Equation 3.32) and the fluorine efficiency(Equation 3.33) and the value used in Equation 3.31 should normally be the average of these two values unlessthere are overriding considerations (such as a much lower uncertainty of one of the efficiency measures) that canbe adequately documented. Annual average carbon and fluorine balance efficiencies are features of a wellmanaged HCFC-22 plant and are either normally available to the plant operator or may be obtained byexamination of process accounting records. Similarly, if there is a vent treatment system, the length of time that
this was in operation, and treating the vent stream from the HCFC-22 plant, should be available from records.
Total HCFC-22 production includes material that is used as a chemical feedstock as well as that which is sold forpotentially dispersive uses.
EQUATION 3.32
CALCULATION OF HFC-23 EMISSION FACTOR FROM CARBON BALANCE EFFICIENCY(100 − CBE ) • F
EFcarbon _ balance =efficiency loss • FCC
100
Where:
EFcarbon_balance = HFC-23 emission factor calculated from carbon balance efficiency, kg HFC-23/kg HCFC-22
CBE = carbon balance efficiency, percent

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Fefficiency loss = factor to assign efficiency loss to HFC-23, fraction
FCC = factor for the carbon content of this component (= 0.81), kg HFC-23/kg HCFC-22
and
EQUATION 3.33
CALCULATION OF HFC-23 EMISSION FACTOR FROM FLUORINE BALANCE EFFICIENCY(100 − FBE ) • F
EF fluorine _ balance =efficiency loss • FFC
100
Where:
EFfluorine_balance = HFC-23 emission factor calculated from fluorine balance efficiency, kg HFC-23/kg
HCFC-22
FBE = fluorine balance efficiency, percent
Fefficiency loss = factor to assign efficiency loss to HFC-23, fraction
FFC = factor for the fluorine content of this component (= 0.54), kg HFC-23/kg HCFC-22
The factor to assign the efficiency loss to HFC-23 is specific to each plant and, if this method of calculation isused, the factor should have been established by the process operator. By default, the value is 1; that is all of theloss in efficiency is due to co-production of HFC-23. In practice, this is commonly the most significant
efficiency loss, being much larger than losses of raw materials or products.
The factors for carbon and fluorine contents are calculated from the molecular compositions of HFC-23 andHCFC-22 and are common to all HCFC-22 plants at 0.81 for carbon and 0.54 for fluorine.

Tier 3Tier 3 methodologies are potentially the most accurate. The Tier 3 methodologies provided here give equivalent
results and the choice between them will be dictated by the information available in individual facilities. In eachcase, the national emission is the sum of factory specific emissions, each of which may be determined using a
Tier 3 method to estimate the composition and flowrate of gas streams vented to atmosphere (either directly andcontinuously – as in Tier 3a - or by continuous monitoring of a process parameter related to the emission - Tier
3b - or by monitoring the HFC-23 concentration continuously within the reactor product stream - Tier 3c):
EQUATION 3.34
TIER 3a CALCULATION OF HFC-23 EMISSIONS FROM INDIVIDUAL PROCESS STREAMS(DIRECT METHOD)E HFC − 23 = ∑ ∑ ∫t C ij • f ijij

[ ∫t means the quantity should be summed over time.]

Where:
EHFC-23 = total HFC-23 emissions: the sum over all i plants, over all j streams in each plant of the emitted
mass flows f and concentrations C is integrated over time t. (See Equation 3.37 for calculation of‘instantaneous’ HFC-23 emissions in an individual process stream.)or, where proxy methodology is used:
EQUATION 3.35
TIER 3b CALCULATION OF HFC-23 EMISSIONS FROM INDIVIDUAL PROCESS STREAMS(PROXY METHOD)E HFC − 23 = ∑ ∑ ∫t E ijij

[ ∫t means the quantity should be summed over time.]

Where:
EHFC-23 = total HFC-23 emissions: Ei,j are the emissions from each plant and stream determined by theproxy methods. (See Equation 3.38 for calculation of HFC-23 emissions in an individual process
stream.)or, where the HFC-23 concentration within the reactor product stream is used:

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EQUATION 3.36
TIER 3c CALCULATION OF HFC-23 EMISSIONS FROM INDIVIDUAL PROCESS STREAMS(BY MONITORING REACTOR PRODUCT)E HFC − 23 = ∑ ∫t C i • Pii

[ ∫t means the quantity should be summed over time.]

Where:
EHFC-23 = total HFC-23 emissions: Pi is the mass flow of HCFC-22 product from the plant reactor at theplant i, and Ci is the concentration of HFC-23 relative to the HCFC-22 product at the plant i. (See
Equation 3.40 for calculation of HFC-23 emissions at an individual facility by in-process
measurement.)

Tier 3a

The Tier 3a method is based on frequent or continuous measurement of the concentration and flow-rate from thevent at an individual plant. So that the quantity emitted to atmosphere is the mathematical product of the massconcentration of the component in the stream, the flowrate of the total stream (in units compatible with the massconcentration) and the length of time that this flow occurred:
EQUATION 3.37
TIER 3a CALCULATION OF ‘INSTANTANEOUS’ HFC-23 EMISSIONS IN AN INDIVIDUAL PROCESSSTREAM (DIRECT METHOD)
E ij = C ij • f ij • t
Where:
Eij = ‘instantaneous’ HFC-23 emissions from process stream j at plant i, kg
Cij = the concentration of HFC-23 in the gas stream actually vented from process stream j at plant i,
kg HFC-23/kg gas
fij = the mass flow of the gas stream from process stream j at plant i (generally measured volumetricallyand converted into mass flow using standard process engineering methods), kg gas/hourt = the length of time over which these parameters are measured and remain constant, hours
If any HFC-23 is recovered from the vent stream for use as chemical feedstock, and hence destroyed, it should
be discounted from this emission; material recovered for uses where it may be emitted may be discounted here, if
the emissions are included in the quantity calculated by the methods in Chapter 7. Because emissions aremeasured directly in this tier, it is not necessary to have a separate term for material recovered, unlike Tiers 3band 3c.
The total quantity of HFC-23 released is then the annual sum of these measured instantaneous releases. Periods
when the vent stream is processed in a destruction unit to remove HFC-23 should not be counted in thiscalculation. If it is necessary to estimate the quantity destroyed at each facility, the operator should calculate thisbased on the difference between the operating time of the plant and the duration of release (t above).

Tier 3b

In many cases, measurements are not continuous but were gained during an intensive process survey or plant
trial, and the results of the trial may be used to provide a proxy for calculating emissions during normal plant
operation. In this case, the emission rate of the by-product is related to a more easily (or accurately) measurable
parameter, such as feedstock flow rate. The trial(s) must meet the following conditions:•

There should have been no major process design, construction or operating changes that affect the plant
upstream of the measurement point and so could render relationships between emissions and production
invalid. (See also Box 3.14)•

The relationship between emissions and plant operating rate must be established during the trial(s), together
with its uncertainty.

For almost all cases the rate of plant operation is a suitable proxy and the quantity of HFC-23 emitted depends
on the current plant operating rate and the length of time that the vent flow was released.

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EQUATION 3.38
TIER 3b CALCULATION OF HFC-23 EMISSIONS IN AN INDIVIDUAL PROCESS STREAM(PROXY METHOD)
Eij = Sij • Fij • PORij • t − Rij
Where:
Eij = the mass emission of HFC-23 in vent stream j at plant i, kg
Sij = the standard mass emission of HFC-23 in vent stream j at plant i per ‘unit’ of proxy quantity, such asprocess operating rate (described in Equation 3.39, below), kg/‘unit’Fij = a dimensionless factor relating the measured standard mass emission rate to the emission rate at theactual plant operating rate. In many cases, the fraction produced is not sensitive to operating rate and
Fi is unity (i.e., the emission rate is proportional to operating rate). In other cases the emission rate isa more complex function of the operating rate. In all cases Fi should be derived during the plant trial
by measuring HFC-23 production at different operating rates. For situations where a simple function
relating the emissions to the operating rate cannot be determined from testing, the proxy method is
not considered appropriate and continuous measurement is desirable.
PORij = the current process operating rate applicable to vent stream j at plant i averaged over t in‘unit/hour’. The units of this parameter must be consistent between the plant trial establishing thestandard emission rate and the estimate of ongoing, operational emissions (described in Equation
3.39, below).
t = the actual total duration of venting for the year, or the period if the process is not operated
continuously in hours. Annual emissions become the sum of all the periods during the year. The
periods during which the vent stream is processed in a destruction system should not be counted here.
Rij = the quantity of HFC-23 recovered for vent stream j at plant i for use as chemical feedstock, andhence destroyed, kg. Material recovered for uses where it may be emitted potentially may be counted
here if the emissions are included in the quantity calculated by the methods for ODS substitutes in
Chapter 7 of this volume.

EQUATION 3.39
TIER 3b CALCULATION OF STANDARD EMISSION FOR PROXY METHOD

S T ,ij = CT ,ij • f T ,ij PORT ,ij
Where (for each test T):
Sij = the standard mass emission of HFC-23 in vent stream j at plant i, kg/‘unit’ (in units compatible withthe factors in Equation 3.38, see PORT,ij below)
CT,ij = the average mass fractional concentration of HFC-23 in vent stream j at plant i during the trial,
kg/kg
f T,ij= the average mass flowrate of vent stream j at plant i during the trial, kg/hour
PORT,ij = the proxy quantity (such as process operating rate) at plant i during the trial, ‘unit’/hour. The‘unit’ depends on the proxy quantity adopted for plant i vent stream j (for example, kg/hour or
m3/hour of feedstock)

Tier 3c

It is a relatively simple procedure to monitor the concentration of HFC-23 in the product of a reaction system
relative to the amount of HCFC-22. This provides a basis for estimation of the quantity of HFC-23 released as
the mathematical product of the monitored concentration and the mass flow of HCFC-22 made. If there is novent treatment to abate emissions, this is a simple procedure. However, where there is abatement then it must be
shown that this actually treats all streams that may be released into the atmosphere, including direct gas ventsand the outgassing of aqueous streams. The latter, especially, may not be passed to the destruction facility. If all
potential vent streams are not treated, the method cannot be used.

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EQUATION 3.40
TIER 3c CALCULATION OF HFC-23 EMISSIONS FROM AN INDIVIDUAL FACILITY BY IN-PROCESSMEASUREMENT

Ei = Ci • Pj • t F − Ri
Where:
Ei = HFC-23 emissions from an individual facility i, kg
Ci = the concentration of HFC-23 in the reactor product at facility i, kg HFC-23/kg HCFC-22
Pi = the mass of HCFC-22 produced at facility i while this concentration applied, kg
tF = the fractional duration during which this HFC-23 is actually vented to the atmosphere, rather thandestroyed, fraction
Ri = the quantity of HFC-23 recovered from facility i for use as chemical feedstock, and hence destroyed,kg
Material recovered for uses where it may be emitted potentially may be counted here if the emissions
are included in the quantity calculated by the methods in Chapter 7 of this volume.
The total quantity of HFC-23 released into the atmosphere is the sum of the quantities from the individual
release periods and individual reaction systems.
HFC-23 that is recovered for use as chemical feedstock should be subtracted from the total quantity estimatedhere.
In summary, the Tier 1 method is relatively simple, involving the application of a default emission factor to thequantity of HCFC-22 produced. This method can be applied at the plant level or the national level. Tier 2 andTier 3 methodologies are suitable only for plant level calculations. In cases where there are Tier 3 data available
for some plants, the Tier 1 or Tier 2 methods can be applied to the remainder to ensure complete coverage.
Uncertainty in the national emission is then calculated using production weighted uncertainties of the individual
sources and standard statistical techniques. Regardless of the method, emissions abated should be subtracted
from the gross estimate from each plant to determine net emissions before these are added together in thenational estimate.

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Figure 3.16

Decision tree for HFC-23 emissions from HCFC-22 production (or othersimilar by-product emissions from fluorochemical production)
Start

Are
plant-level
HFC-23 measurement
data available?

Yes

Calculate plant-levelemissions using
plant-level data andTier 3a, 3b or 3c
methodology.

Does any
HFC-23 destruction
take place?

No
Obtain plant-level HFC23 measurement data.
Is theFluorochemical
Production a key category1,
and is this subcategory
significant?

No

Yes

No

Yes

Are
plant-level
HCFC-22 production
data
available?

Are
plant-level
efficiencies
available?

Yes

Estimate emissions byaggregating plant-levelmeasurements, andestimates for plants
without measurements2,
adjusting for HFC-23
destruction.
Box 5: Tier 3
Estimate emissions byaggregating plant-levelmeasurements2, andestimates for plants
without measurements.

Calculate plantlevel emissions
using the Tier 2emission factor.
Is itpossible todocument any
HFC-23destruction?

No

Estimate emissions using the default
emission factor. If the emissions are
estimated at the plant level, aggregate
plant-level emissions.
Box 1: Tier 1

Box 4: Tier 3
Yes

Aggregate plant-levelemissions, adjusting for
HFC-23 destruction.

No
Collect national
HCFC-22
production data.

Yes

Box 3: Tier 2No

Aggregate plant-levelemissions.
Box 2: Tier 2

Note:
1. See Volume 1 Chapter 4, Methodological Choice and Identification of Key Categories (noting Section 4.1.2 on limited resources), for
discussion of key categories and use of decision trees.
2. If there are Tier 3 data available for some plants, the Tier 1 or Tier 2 methods can be applied to the remainder to ensure complete
coverage.

It is good practice to use the Tier 3 method if possible. Direct measurement is significantly more accurate thanTier 1 because it reflects the conditions specific to each manufacturing facility. In most cases, the data necessary
to prepare Tier 3 estimates should be available because facilities operating to good business practice perform
regular or periodic sampling of the final process vent or within the process itself as part of routine operations.
For facilities using abatement techniques such as HFC-23 destruction, verification of the abatement efficiency isalso done routinely. The Tier 1 (default) method should be used only in rare cases where plant-specific data areunavailable and this subcategory is not identified as significant subcategory under key category. (See Section 4.2
of Volume 1.)

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CHOICE OF EMISSION FACTORS
There are several measurement options within the Tier 3 method relating to the location and frequency of thesampling. In general, direct measurement of the emissions of HFC-23 may provide the highest accuracy but
continuous or frequent measurement of parameters within the production process area itself may be more
pragmatic and can be equally accurate. In both cases, the frequency of measurement must be high enough torepresent the variability in the process (e.g., across the life of the catalyst). Issues related to measurement
frequency are summarised in Box 3.14, Plant Measurement Frequency. General advice on sampling andrepresentativeness is provided in Volume 1, Chapter 2.
In cases where plant-specific measurements or sampling are not available and Tier 1 methods are used, thedefault emission factor should be used, assuming no abatement methods. For plants in operation prior to 1995
the default emission factor is 0.04 kg HFC-23/kg HCFC-22 (4 percent) (IPCC, 1996; USEPA, 2001). This is a
default to be used when there are no measurements and describes the output of HFC-23 from a typical HCFC-22
plant in the absence of recovery or destruction of HFC-23. The value is consistent with atmospheric observationsof HFC-23 concentrations in the 1978-1995 time period (Oram et al.,1998). These showed globally averaged
emissions to be equivalent to 2 percent of the total quantity of HCFC-22 produced at a time when significant
HFC-23 was being recovered and converted into Halon 1301 (McCulloch, 1992) and abatement was required
practice in several countries where there was significant production.
It is possible, by process optimisation, to reduce the production to between 0.014 and 0.03 kg HFC-23/kg
HCFC-22 (1.4 to 3 percent) but it is not possible to completely eliminate HFC-23 formation this way (IPCC,
2000). Furthermore, the extent of the reduction is highly dependent on the process design and the economic
environment (measures to reduce HFC-23 can often reduce the process output). In an optimised process HFC-23
production and emissions will, invariably, have been measured; it is not possible to optimise process operation
without such measurements and so default values have no meaning in this context for an individual plant.
However, the state of the technological art has been advanced by optimisation of individual plants and that art
should have been built into the design of recent plants, suggesting a default emission factor of 0.03 kg HFC23/kg HCFC-22 (3 percent). These default values have a large uncertainty (in the region of 50 percent). For moreaccurate assessments, the actual emissions should be determined by Tier 2 or Tier 3 methodology and, if
necessary, assigned to previous years using the guidance provided in Chapter 7 of this volume.
TABLE 3.28
HFC-23 DEFAULT EMISSION FACTORSTechnology
Old, unoptimised plants (e.g., 1940s to 1990/1995)

0.04

Plants of recent design, not specifically optimised

0.03

Global average emissions (1978 - 1995) 4

0.02

For comparison:
Optimised large plant- requiring measurement of HFC-23 (Tier 3)
Plant with effective capture and destruction of HFC-23 (Tier 3)

4

Emission Factor(kg HFC-23/kg HCFC-22 produced)

Down to 0.014
Down to zeroThe global average is calculated from the change in atmospheric concentration of HFC-23. It does not discriminate
between plant emissions, which range from nothing to greater than 4 percent of the HCFC-22 production.

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BOX 3.14
PLANT MEASUREMENT FREQUENCY

The accuracy and precision of the estimates of annual HFC-23 emissions depend on the number ofsamples (the frequency of sample collection) together with the accuracy of measurement offlowrates and the extent to which discrete flow measurements can represent the total quantity
vented. Since production processes are not completely static, the greater the process variability, themore frequently plants need to measure. As a general rule, sampling and analysis should be
repeated whenever a plant makes any significant process changes. Before choosing a sampling
frequency, the plant should set a goal for accuracy and use statistical tools to determine the sample
size necessary to achieve the goal. For example, a study of HCFC-22 producers indicates thatsampling once per day is sufficient to achieve an extremely accurate annual estimate. Thisaccuracy goal should then be revised, if necessary, to take into account the available resources.
(RTI, Cadmus, 1998)

CHOICE OF ACTIVITY DATA
When using the Tier 1 method, production data should be obtained directly from producers. There are several
ways producers may determine their production levels, including shipment weights and measuring volumetimes-density, using flow meters. These data should account for all HCFC-22 production for the year, whether
for sale or for use internally as feedstock, and the plant should describe how the HCFC-22 production rate isdetermined. In some circumstances, producers may consider plant production data to be confidential. For
national-level activity data, submission of HCFC-22 production data is already required under the Montreal
Protocol.

COMPLETENESSIt should be possible to obtain complete sampling data because there are only a small number of HCFC-22 plants
in each country, and it is standard practice for each plant operator to monitor process efficiencies and hence
HFC-23 losses, leading to the adoption of Tier 2 methodology. The destruction efficiencies of thermal oxidisers
used to abate HFC-23 are generally high (>99 percent) but it is important to establish the composition of the exit
gas in order to ensure that account is taken of emissions of fluorinated greenhouse gases from this point.

DEVELOPING A CONSISTENT TIME SERIESEmission of HFC-23 from HCFC-22 production should be estimated using the same method for the entire timeseries and appropriate emission factors. If data for any years in the time series are unavailable for the Tier 3
method, these gaps should be filled according to the guidance provided in Volume 1, Chapter 5.

3.10.1.3

U NCERTAINTY ASSESSMENT

TIER 1
Unlike the other Tiers, where uncertainties are based on measurements and statistics, Tier 1 uncertainties areassessed through expert judgement and an error of approximately 50 percent could be considered for Tier 1
based upon knowledge of the variability in emissions from different manufacturing facilities. An error of thismagnitude will completely outweigh the uncertainty in the activity.

TIER 2
Uncertainty of the Tier 2 result is calculated by the root-squared sum of the individual uncertainties in
production mass quantity and efficiencies, assuming the carbon and fluorine uncertainties are the same. Where
the uncertainties in carbon and fluorine efficiency differ significantly (enough to cause a material difference tothe calculated emission), the value with the lower uncertainty should be used throughout the calculation.
Uncertainty in the value derived by Tier 2 methods is much larger than that expected from Tier 3 but is,nevertheless, quantifiable. Typically, for a plant producing about 4 percent HFC-23, the carbon efficiency is in
the region of 95 percent and the fluorine efficiency 92 percent. If these efficiencies can be measured to within 1
percent, then the error in the Tier 2 HFC-23 estimate would be less than 20 percent. Estimating efficiencies tothis degree of accuracy will require rigorous accounting procedures and that all raw materials and product forsale should be weighed in or out of the facility. Such a regime sets the expected accuracy of the overall activity(for both Tiers 1 and 2); with good accounting and measurement of production by weight, it should be possible
to reduce the error in the activity to below 1 percent.

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TIER 3
For HFC-23, the Tier 3 method is significantly more accurate than either the Tier 2 measured or Tier 1 default
methods. Regular Tier 3 sampling of the vent stream can achieve an accuracy of 1-2 percent at a 95 percent
confidence level in HFC-23 emissions and the uncertainty of the Tier 3 (proxy) result may be similar. In bothcases, the uncertainty may be calculated statistically from the uncertainties of the input parameters and, because
these methods do not rely on emission factors or activities, the concept of subdividing uncertainty has no validity.
Uncertainty of the estimate is expressed as a coefficient of variance (percent) and, for each of these streams,
there will be an uncertainty as a consequence of uncertainties in measured concentration and flowrate anduncertainty in the duration of the flow. The combined uncertainty can be determined analytically and should be
calculated using the standard methodology described in Chapter 3 of Volume 1.

3.10.1.4

Q UALITY A SSURANCE /Q UALITY C ONTROL (QA/QC),R EPORTING AND D OCUMENTATIONQUALITY ASSURANCE/QUALITY CONTROL
It is good practice to conduct quality control checks as outlined in Volume 1, Chapter 6, and an expert review ofthe emissions estimates. Additional quality control checks as outlined in Volume 1, Chapter 6, and quality
assurance procedures may also be applicable, particularly if higher tier methods are used to determine emissions
from this source category. Inventory compilers are encouraged to use higher tier QA/QC for key categories as
identified in Volume 1, Chapter 4.
In addition to the guidance in Volume 1, specific procedures of relevance to this sub-source category are
outlined below:

Comparison of emissions estimates using different approaches
Inventory compilers should compare reported plant emissions estimates against those determined using the Tier
1 default factor and production data. If only national production data are available, they should compare
aggregated plant emissions to a national default estimate. If significant differences are found in the comparison,
they should answer the following questions:1.

Are there inaccuracies associated with any of the individual plant estimates (e.g., an extreme outlier may be
accounting for an unreasonable quantity of emissions)?

2.

Are the plant-specific emission factors significantly different from one another?

3.

Are the plant-specific production rates consistent with published national level production rates?

4.

Is there any other explanation for a significant difference, such as the effect of controls, the manner in which
production is reported or possibly undocumented assumptions?

Direct emission measurement check•

Inventory compilers should confirm that internationally recognised, standard methods were used for plantmeasurements. If the measurement practices fail this criterion, then the use of these emissions data should be
carefully evaluated. It is also possible that, where a high standard of measurement and QA/QC is in place atsites, the uncertainty of the emissions estimates may be revised downwards.

•

Each plant’s QA/QC process should be evaluated to assess if the number of samples and the frequency ofsample collection is appropriate given the variability in the process itself.

•

Where possible, inventory compilers should verify all measured and calculated data through comparison
with other systems of measurement or calculation. For example, emissions measurement within the processitself can be verified periodically with measurement of the vent stream. Inventory compilers should verify
abatement system utilisation and efficiency.

•

With a periodic external audit of the plant measurement techniques and results, it is also possible to compare
implied emission factors across plants and account for major differences.

REPORTING AND DOCUMENTATION
It is good practice to document and archive all information required to produce the national emissions inventory
estimates as outlined in Volume 1, Section 6.11.
Some examples of specific documentation and reporting relevant to this source category are provided below:

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To provide for completely transparent reporting, emissions of HFC-23 from HCFC-22 production should bereported as a separate item, rather than included with other HFC emissions.

•

Documentation should also include:(i) Methodological description;(ii) Number of HCFC-22 plants;(iii) HCFC-22 production (if multiple producers);(iv) Presence of abatement technology;(v) Process descriptions, operating parameters; and(vi) Related emission factors.

Confidentiality•

Th e us e of th e T ier s 2 and 3 methods would mean that the plant emissions of HFC-23 are reported
separately from the production of HCFC-22. By de-coupling the HFC-23 emissions and HCFC-22
production, the emission data on HFC-23 cannot be considered to be of commercial confidence as it does
not reveal the levels of production of HCFC-22 without detailed and confidential knowledge of theindividual manufacturing facility.

•

Th e app lication of the T ier 1 method to total national production of HCFC-22 would enable this to be
calculated from published emissions of HFC-23 and, if there were less than three producers, such production
data could be considered confidential business information. In such cases, steps should be taken to protect
confidentiality through, for example, the aggregation of all HFC emissions. For transparency reasons,whenever there is aggregation, a qualitative discussion of HCFC-22 production should be included.

•

When national emissions are calculated as the sum from individual facilities and these have been calculatedusing different methodologies, it is not possible to recalculate the HCFC-22 production from these dataalone and there should be no problems concerning confidentiality.

3.10.2
3.10.2.1

Emissions from production of other fluorinatedcompounds
I NTRODUCTION

A large number of fluorine containing greenhouse gases can be produced as by-products of fluorochemical
manufacture and emitted into the atmosphere. For example, in a recent national inventory, significant by-productemissions of SF6, CF4, C2F6, C3F8, C4F10, C5F12 and C6F14 were reported for a fluorochemical plant (UNFCCC,2005). Other examples include the release of by-product CF4 from the production of CFC-11 and 12 or of SF6
from the production of uranium hexafluoride in the nuclear fuel cycle.
Emissions of a chemical occur during its production and distribution or as a by-product during the production ofa related chemical (HFC-23 from HCFC-22 production is covered specifically in Section 3.10.1 above). There
may also be emissions of the material that is being produced; the so-called ‘fugitive emissions’. Both by-productand fugitive emissions are calculated in the same way. In this section, emissions associated with use are notaddressed specifically, being counted in the emissions related to consumption (see Chapters 4.5, 6, 7 and 8 inthis volume). Typically, fluorochemicals may be released from chemical processes involving a broad range oftechnologies and processes 5:•

Telomerization Process used in the production of fluorochemicals fluids and polymers•

Photooxidation of tetrafluoroethylene to make fluorochemical fluids•

Direct Fluorination often used in SF6 production•

Halogen Exchange Processes to make low boiling PFCs like C2F6 and CF4, HFC 134a and 245fa•

NF3 manufacturing by direct fluorination•

Production of uranium hexafluoride

5

This list is illustrative.

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Chapter 3: Chemical Industry Emissions•

Production of fluorinated monomers like tetrafluoroethylene and hexafluoropropylene•

Production of fluorochemical agrochemcials•

Production of fluorochemical anesthetics

Halogen exchange processes are extensively used for HFC manufacture, while most PFCs and SF6 requireelemental fluorine, generated electrochemically. In ‘electrochemical fluorination’ processes, the fluorine is notseparated but makes the desired product in the electrochemical cell. In other processes it is separated andsubsequently used, either as the elemental gas or as a component of a carrier system, such as CoF3. Each process
will have a different spectrum of emissions, in terms of both chemical nature and quantities, and so a common
default emission function is of relatively little value. It is essential that the existence of potentially emissiveplants is identified within each country, hence this step is first in the decision tree (Figure 3.17). The common
factor for these plants is the use of anhydrous hydrogen fluoride, which is the source of fluorine in halogen
exchange processes and in processes that use elemental fluorine. The production and importation of anhydroushydrogen fluoride can therefore be used as a means of tracing significant producers of fluorochemicals. Further
enquiries (see Figure 3.17) can then elucidate whether or not there are significant fluorochemical greenhouse gas
emissions.

3.10.2.2

M ETHODOLOGICAL ISSUESCHOICE OF METHOD
It is good practice to choose the method using the decision tree shown in Figure 3.17. If the Category 2B9Fluorochemical Production is identified as key and this subcategory is judged to be significant, inventory
compilers should consider whether or not emissions are dominated by the production of a sub-set of chemicals,
and focus more sophisticated data collection efforts on production of these chemicals. The number of major
producers of these fluorinated greenhouse gases is quite small: in the case of SF6, there are globally about 6
companies with about 10 production facilities world-wide (Preisegger, 1999). The number of smaller producers
may grow in the near future, particularly in developing economies. However, a survey of national producers
should not be difficult to compile.

Tier 1In the Tier 1 methodology, a default emission factor, or a similar number derived for the particular country's
circumstances, can be used to estimate national production-related emissions of individual HFCs, PFCs, SF6 andother fluorinated greenhouse gases.
EQUATION 3.41
TIER 1 CALCULATION OF PRODUCTION-RELATED EMISSIONS
E k = EFdefault , k • Pk
Where:
Ek = production-related emissions of fluorinated greenhouse gas k, kg
EFdefault, k = default emission factor, kg/kg
Pk = total production of fluorinated greenhouse gas k, kg
Problems of confidentiality arising from reporting specific component data can be circumvented by providing asingle number for total national emissions of each HFC, PFC and SF6. This may be facilitated if data arecollected by a third party and reported only as this total.

Tier 2The method based on process efficiencies, which works for HFC-23 emissions from HCFC-22 plants, is of lessvalue for other types of plants. This is due in part to the lower inefficiency expected from these other by-productemissions; the uncertainty in measurement of efficiencies is likely to be much greater than the by-productemission factor. Furthermore, a range of by-products may be responsible for process inefficiency (unlike the casefor HCFC-22 where one by-product predominates). However, production efficiency data should exist for eachprocess and, in the absence of a more rigorous estimate, the quantity of emissions estimated from process
inefficiencies may be used in a qualitative decision as to whether or not these emissions are a significant
subcategory under a key category (in which case, Tier 3 methodology is specified).

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Tier 3
The Tier 3 methodology is potentially the most accurate estimate and is the sum of factory specific emissions ofeach by-product fluorinated greenhouse gas determined using standard methods to estimate the composition andflowrate of gas streams actually vented to atmosphere after any abatement technology. In this case:
EQUATION 3.42
TIER 3 DIRECT CALCULATION OF PRODUCTION-RELATED EMISSIONS
E k = ∑ ∑ ∫t C ijk • f ijkij[ ∫t means the quantity should be summed over time.]

Where:
Ek = total production-related emissions of fluorinated greenhouse gas k: the sum over all i plants, over all
j streams in each plant of the emitted mass flows f and concentrations C integrated over time t.
or, where proxy methodology is used, for example where the emission rate of the by-product is normalised to amore easily (or accurately) measurable parameter, such as feedstock flow rate, as described in Equation 3.35 in
Section 3.10.1:
EQUATION 3.43
TIER 3 PROXY CALCULATION OF PRODUCTION-RELATED EMISSIONS
Ek = ∑ ∑ ∫t Eijkij[ ∫t means the quantity should be summed over time.]

Where:
Ek = total production-related emissions of fluorinated greenhouse gas k: Eijk = the emissions offluorinated greenhouse gas k from each plant and stream determined by the proxy methods, describedin Equations 3.38 and 3.39 in Section 3.10.1
Note that, generally, flows are measured volumetrically and should be converted into mass flow (kg/hour) basedon the ideal gas law, temperature, pressure and composition, similarly concentration should be converted into
compatible units (e.g., kg/kg).
In this case, the flowrates, concentrations and duration should be calculated separately for the periods when theabatement technology is or is not operating and only those that lead to actual emissions should be summed andreported.

CHOICE OF EMISSION FACTORS
Tier 3 relies on measurements of the quantities of individual materials that are released into the atmosphere andneither Tier 2 nor Tier 3 relies on emission factors. For Tier 1, in the absence of abatement measures, a default
emission factor of 0.5 percent of production, not counting losses in transport and transfer of materials, issuggested for HFCs and PFCs, based on data supplied to AFEAS (2004). There is a wide range of substancesthat may potentially be released. However, the AFEAS data showed that the components that were lost during
production of a particular fluorochemical had, in general, radiative forcing properties similar to those of thedesired fluorochemical. Consequently, for sources that are not significant subcategories under key category,fugitive and by-product emissions are the same and are included in the 0.5 percent emission factor.
In the case of SF6, based on German experience, a default emission factor of 0.2 percent of the total quantity ofSF6 produced is suggested for those countries in which the predominant end use does not require highly purified
SF6 gas (e.g., electrical equipment, insulated windows) (Preisegger, 1999). Based on experience in Japan, in
countries where the major uses require highly purified SF6 gas (e.g., semiconductor manufacturing), the default
value should be 8 percent because of handling losses during disposal of residual gas (i.e., the ‘heel’ that is not
used or recycled) in returned cylinders (Suizu, 1999). If national data are available, these should be used,particularly for other materials not specifically listed here.
The default emission factors are based on situations where no abatement measures are employed. If the quantityof gas emitted to the atmosphere is reduced by, for example, thermal oxidation of the vent stream, the quantity
emitted should be adjusted to account for the destruction efficiency of the oxidiser and the length of time that it
is in service. Based on the experience in the destruction of HFC-23, a default destruction efficiency of 100
percent is suggested but the on-line time of the destruction process will have a greater effect on emissions andshould be recorded.

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Chapter 3: Chemical Industry Emissions

Figure 3.17

Decision tree for emissions of fluorinated greenhouse gases from production
processes, applicable to both fugitive and by-product emissions
Start

Compile a list of all
fluorochemical
manufacturers.
Box 5: Tier 3
Aredetailed data available
on plant-specificestimates?

Yes

Sum data for eachgreenhouse gas fromplants, taking account ofabatement (Tier 3).

NoAre
national activity data
available?

No

Collect national
activity data.

YesIs
Fluorochemical
Production a key category, and is
this production process/gas
significant1,2?

Yes

Collect emissions
data from plants.3

No
Is there
abatement ofemissions?

Yes

No

Estimate emissions fromfluorochemical plants(Tier 1).

Estimate emissions fromfluorochemical plants
adjusting for abatement(Tier 1).
Box 2: Tier 1

Box 1: Tier 1

Note:
1. See Volume 1 Chapter 4, Methodological Choice and Identification of Key Categories (noting Section 4.1.2 on limited resources), for
discussion of key categories and use of decision trees.
2. Tier 2 methodology may be used at this point to establish whether or not this is a key category but, as explained in Section 3.10.2.2, thisis the only use for Tier 2.
3. Data may be collected as a country study by a third party in order to preserve confidentiality.

CHOICE OF ACTIVITY DATA
Again, activity data has no role in the Tiers 3 and 2 estimates, which are based on measurements. For Tier 1, theactivity is the annual mass of the desired fluorochemical that is produced.

Recycling
Recycling of used gas may be done by the producers of new gas or by other recycling firms. Emissions may
occur during handling and purification of old gas and handling of recycled gas. Specific emission factors are notavailable. Thus, good practice is to use the same default factor as for new production.

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COMPLETENESS
For some inventory compilers, identifying smaller producers and, in particular, recycling firms may be a difficult
task. However, initial estimates based on the national mass balance of these fluorinated greenhouse gases should
identify if production related emissions from such entities provide a sizeable contribution to total nationalemissions.

DEVELOPING A CONSISTENT TIME SERIESBoth by-product and fugitive emissions of fluorocompounds from production processes should be estimatedusing the same method for the entire time series and appropriate emission factors. If data for any years in thetime series are unavailable for the Tier 3 method, these gaps should be filled according to the guidance provided
in Volume 1, Chapter 5.

3.10.2.3

U NCERTAINTY ASSESSMENT

For Tier 1, the uncertainty in activity data needs to be determined for the reporting country and statisticallycombined with the uncertainty in the default emission factor. Typically, in a well operated facility, the default
uncertainty in activity data should be in the region of 1 percent, assuming that rigorous accounting records aremaintained and that production is monitored by weight. The actual emission factor may range from well inexcess of the default value to zero. The default uncertainty of the default emission factors is therefore set at 100
percent, for example 0.5±0.5 (%).
For Tier 3 emissions, the uncertainty of the measurements should be determined individually and combined(using standard statistical methods) to provide a total uncertainty for the estimate. The methodology is identicalto that described for HFC-23 from HCFC-22. In the Tier 2 methodology, the uncertainty both of themeasurements of efficiencies and the assignment of losses to individual compounds should be assessed. Because
these are liable to produce a much larger uncertainty than that from Tier 3, the utility of Tier 2 is likely to belimited to assessing whether or not by-product fluorochemical emissions are a significant subcategory under key
category.

3.10.2.4

Q UALITY A SSURANCE /Q UALITY C ONTROL (QA/QC),R EPORTING AND D OCUMENTATIONQUALITY ASSURANCE/QUALITY CONTROL
It is good practice to conduct quality control checks as outlined in Volume 1, Chapter 6, and an expert review ofthe emissions estimates. Additional quality control checks as outlined in Volume 1, Chapter 6, quality assurance
procedures may also be applicable, particularly if higher tier methods are used to determine emissions from thissource category. Inventory compilers are encouraged to use higher tier QA/QC for key categories as identified inVolume 1, Chapter 4.

Comparison of emissions estimates using different approaches
Inventory compilers should compare the estimate based on aggregated producer-level data to an estimate basedon national production data and the suggested default emission factors. They should investigate significant
discrepancies in cooperation with the producers to determine if there are unexplained differences.

REPORTING AND DOCUMENTATION
Confidentiality issues may arise where there are limited numbers of manufacturers. In these cases moreaggregate reporting of total national emissions may be necessary. If survey responses cannot be released as
public information, third-party review of survey data may be necessary to support data verification efforts.
It is good practice to document and archive all information required to produce the national emissions inventory
estimates as outlined in Volume 1, Section 6.11. It is not practical to include all documentation in the national
inventory report. However, the inventory should include summaries of methods used and references to source
data such that the reported emissions estimates are transparent and steps in their calculation may be retraced.

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Chapter 3: Chemical Industry Emissions

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Department of Science, Technology, and Society, Utrecht, The Netherlands, April 2003.
Qenos (2003). Annual Report on Manufacturing Operations at Qenos Olefins, Plastics, Resins, and Elastomers
Sites to Altona Complex Neighborhood Consultative Group, April 2003, Qenos Pty. Ltd.
Qenos (2005). 2004 Annual Report on Manufacturing Operations at Qenos Olefins, Plastics, Resins, andElastomers Sites to Altona Complex Neighborhood Consultative Group, April 2005, Qenos Pty. Ltd.
SFT (2003a). Self-reporting of emissions to the Norwegian Pollution Control Authority based on direct
measurements at Statoil Tjeldbergodden Methanol Plant. (In Norwegian).
SFT (2003b). Self-reporting of emissions to the Norwegian Pollution Control Authority based on direct
measurements at Nordetyl ethylene Plant. (In Norwegian).
Struker, A. and Blok, K. (1995). Sectorstudie organische chemie, National Energy Efficiency Data Informatie
Systeem (NEEDIS), Patten, December 1995. Cited in Neelis, M; Patel, M; de Feber, M; 2003.
Improvement of CO2 Emissions Estimates from the Non-energy Use of Fossil Fuels in the Netherlands,
Report Number NW&S-E-2003-10, Copernicus Institute, Department of Science, Technology, andSociety, Utrecht, The Netherlands, April 2003

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SECTION 3.10.1
Defra (2002a). Protocol C1: Measurement of HFCs and PFCs from the Manufacture of HF, CTF, HCFC-22,
HFC-125 and HFC-134a, in Guidelines for the Measurement and Reporting of Emissions by Direct
Participants in the UK Emissions Trading Scheme, UK Department for Environment, Food and Rural
Affairs, Report No. UKETS(01)05rev1, Defra, London, 2002.
Defra (2002b). Protocol C9: Measurement of HFCs and PFCs from Chemical Process Operations, UK
Department for Environment, Food and Rural Affairs, as above, London, 2002.
EFCTC (2003). Protocol for the Measurement of HFC and PFC Greenhouse Gas Emissions from Chemical
Process Operations, Standard Methodology, European Fluorocarbon Technical Committee, Cefic,
Brussels, 2003.
IPCC (1997). Revised 1996 IPCC Guidelines for National Greenhouse Inventories. Houghton J.T., Meira Filho
L.G., Lim B., Tréanton K., Mamaty I., Bonduki Y., Griggs D.J. Callander B.A. (Eds). Intergovernmental
Panel on Climate Change (IPCC), IPCC/OECD/IEA, Paris, France.
IPCC (2000). Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories.
Penman J., Kruger D., Galbally I., Hiraishi T., Nyenzi B., Emmanuel S., Buendia L., Hoppaus R.,
Martinsen T., Meijer J., Miwa K., Tanabe K. (Eds). Intergovernmental Panel on Climate Change (IPCC),
IPCC/OECD/IEA/IGES, Hayama, Japan.
McCulloch A. (1992). Global Production and Emissions of Bromochlorodifluoromethane
Bromotrifluoromethane (Halons 1211 and 1301), Atmos. Environ., 26A(7), 1325-1329.

andOram D.E., Sturges, W.T., Penkett, S.A., McCulloch, A. and Fraser, P.J. (1998). Growth of fluoroform (CHF3,
HFC-23) in the background atmosphere, Geophys. Res. Lett., 25(1), 35-38.
RTI, Cadmus, (1998). ‘Performance Standards for Determining Emissions of HFC-23 from the Production of
HCFC-22’, draft final report prepared for USEPA, February 1998.
UN (2004). Approved baseline methodology, ‘Incineration of HFC 23 waste streams’, AM0001/Version 02,
CDM – Executive Board, United Nations Framework Convention on Climate Change, 7 April 2004
U.S. EPA (2001). Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-1999. United States
Environmental Protection Agency, Report No. EPA 236-R-01-001, Washington, U.S.A., 2001.

SECTION 3.10.2
AFEAS (2004). Production, Sales and Estimated Atmospheric Emissions of CFCs, HCFCs and HFCs,
Alternative Fluorocarbons Environmental Acceptability Study, Arlington, U.S.A., 2004. Available atwww.afeas.org.
Preisegger, E. (1999). Statement on experiences of Solvay Fluor und Derivate GmbH, Hannover, Germany
regarding an emission factor at the IPCC expert group meeting on Good practice in Inventory Preparation,
Washington D.C. Jan, 1999.
Suizu, T. (1999). Partnership activities for SF6 gas emission reduction from gas insulated electrical equipment inJapan. Proc. Joint IPCC/TEAP Expert Meeting on Options for the Limitation of Emissions of HFCs andPFCs, Petten, Netherlands, 26-28 May 1999. ECN, Petten.
UNFCCC (2005). Belgium’s Greenhouse Gas Inventory (1990-2003), National Inventory Report 2005,
submitted under the United Nations Framework Convention on Climate Change, April 2005.
http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/2761.
php.

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