Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.1 

# CHAPTER 3

CHEMICAL INDUSTRY EMISSIONSVolume 3: Industrial Processes and Product Use

3.2 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### Authors

Section 3.1 Jochen Harnisch (Germany)

Sections 3.2 – 3.8 Charles Jubb (Australia) Alexander Nakhutin (Russia) and Virg inia Carla Sena Cianci (Uruguay)

Section 3.9 Robert Lanza (USA) Thomas Martinsen (Norway), Abdul Karim W. Mohammad (Iraq), and Maruo M. O. Santos (Brazil)

Section 3.10 Archie McCulloch (UK) and Brian T. Mader (USA)


### Contributing Authors

Sections 3.2 – 3.8 Javier Pérez-Ramírez (Spain)

Section 3.9 Maarten Neelis (Netherlands) and Martin Patel (Germany)Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.3 

# Contents

3 Chemical Indu stry Emissions.................................................................................................. ....................3.10

3.1 Intro duction............................................................................................................... ..........................3.10 3.2 Ammonia production......................................................................................................... ..................3.11

3.2.1 Intr oduction ............................................................................................................. ....................3.11 3.2.2 Methodol ogical issues .................................................................................................... .............3.11

3.2.2.1 Choice of method....................................................................................................... ............3.12 3.2.2.2 Choice of em ission 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 c onsistent tim e series.................................................................................... ...3.17 3.2.3 Uncertainty assessment ................................................................................................... ............3.17

3.2.3.1 Emission fact or uncertainties.......................................................................................... .......3.17 3.2.3.2 Activity da ta uncerta inties ............................................................................................ .........3.17 3.2.4 Quality Assurance/Quality Control ( QA/QC), Reporting and Documentation ...........................3.17

3.2.4.1 Quality Assura nce/Quality Control...................................................................................... ..3.17 3.2.4.2 Reporting an d Documentation ............................................................................................ ...3.18 3.3 Nitric aci d production..................................................................................................... .....................3.19

3.3.1 Intr oduction ............................................................................................................. ....................3.19 3.3.2 Methodol ogical issues .................................................................................................... .............3.19

3.3.2.1 Choice of method....................................................................................................... ............3.20 3.3.2.2 Choice of em ission 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 c onsistent tim e series.................................................................................... ...3.24 3.3.3 Uncertainty assessment ................................................................................................... ............3.24

3.3.3.1 Emission fact or uncertainties.......................................................................................... .......3.24 3.3.3.2 Activity da ta uncerta inties ............................................................................................ .........3.25 3.3.4 Quality Assurance/Quality Control ( QA/QC), Reporting and Documentation ...........................3.25

3.3.4.1 Quality Assura nce/Quality Control...................................................................................... ..3.25 3.3.4.2 Reporting an d Documentation ............................................................................................ ...3.25 3.4 Adipic aci d produc tion ..................................................................................................... ...................3.27

3.4.1 Intr oduction ............................................................................................................. ....................3.27 3.4.2 Methodol ogical issues .................................................................................................... .............3.27

3.4.2.1 Choice of method....................................................................................................... ............3.27 3.4.2.2 Choice of em ission factors............................................................................................. ........3.28 3.4.2.3 Choice of activity data ................................................................................................ ...........3.30 3.4.2.4 Completeness........................................................................................................... ..............3.31Volume 3: Industrial Processes and Product Use

3.4 2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.4.2.5 Developing a c onsistent tim e series.................................................................................... ...3.31 3.4.3 Uncertainty assessment ................................................................................................... ............3.31

3.4.3.1 Emission fact or uncertainties.......................................................................................... .......3.31 3.4.3.2 Activity da ta uncerta inties ............................................................................................ .........3.31 3.4.4 Quality Assurance/Quality Control ( QA/QC), Reporting and Documentation ...........................3.31

3.4.4.1 Quality Assura nce/Quality Control...................................................................................... ..3.31 3.4.4.2 Reporting an d Documentation ............................................................................................ ...3.32 3.5 Caprolactam, glyoxal and glyoxylic acid production......................................................................... .3.33

3.5.1 Intr oduction ............................................................................................................. ....................3.33 3.5.2 Capr olactam .............................................................................................................. ..................3.33

3.5.2.1 Methodological issues.................................................................................................. ..........3.33 3.5.2.2 Uncertai nty assessment................................................................................................. .........3.37 3.5.2.3 Quality Assurance/Qua lity Control (QA/QC), Repor ting and Documentation......................3.38 3.5.3 Glyoxal and gly oxylic acid pr oduction .................................................................................... ...3.39 3.6 Carbide produc tion......................................................................................................... .....................3.40

3.6.1 Intr oduction ............................................................................................................. ....................3.40 3.6.2 Methodol ogical issues .................................................................................................... .............3.40

3.6.2.1 Choice of method....................................................................................................... ............3.41 3.6.2.2 Choice of em ission 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 c onsistent tim e series.................................................................................... ...3.45 3.6.3 Uncertainty assessment ................................................................................................... ............3.45

3.6.3.1 Emission fact or uncertainties.......................................................................................... .......3.45 3.6.3.2 Activity da ta uncerta inties ............................................................................................ .........3.45 3.6.4 Quality Assurance/Quality Control ( QA/QC), Reporting and Documentation ...........................3.46

3.6.4.1 Quality Assura nce/Quality Control...................................................................................... ..3.46 3.6.4.2 Reporting an d Documentation ............................................................................................ ...3.46 3.7 Titanium dioxi de production................................................................................................ ...............3.47

3.7.1 Intr oduction ............................................................................................................. ....................3.47 3.7.2 Methodol ogical issues .................................................................................................... .............3.47

3.7.2.1 Choice of method....................................................................................................... ............3.47 3.7.2.2 Choice of em ission 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 c onsistent tim e series.................................................................................... ...3.50 3.7.3 Uncertainty assessment ................................................................................................... ............3.50

3.7.3.1 Emission fact or uncertainties.......................................................................................... .......3.50 3.7.3.2 Activity da ta uncerta inties ............................................................................................ .........3.50 3.7.4 Quality Assurance/Quality Control ( QA/QC), Reporting and Documentation ...........................3.51

3.7.4.1 Quality Assura nce/Quality Control...................................................................................... ..3.51Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.5 3.7.4.2 Reporting an d Documentation ............................................................................................ ...3.51 3.8 Soda ash production ........................................................................................................ ....................3.52

3.8.1 Intr oduction ............................................................................................................. ....................3.52 3.8.2 Natural soda ash production .............................................................................................. ..........3.52 3.8.2.1 Methodological issues.................................................................................................. ..........3.52 3.8.2.2 Uncertai nty assessment................................................................................................. .........3.54 3.8.2.3 Quality Assurance/Qua lity Control (QA/QC), Repor ting and Documentation......................3.55 3.8.3 Solvay soda ash production............................................................................................... ..........3.55 3.8.3.1 Quality Assurance/Qua lity Control (QA/QC), Repor ting and Documentation......................3.56 3.9 Petrochemical and car bon black production.................................................................................. ......3.57 3.9.1 Intr oduction ............................................................................................................. ....................3.57 3.9.2 Methodol ogical issues .................................................................................................... .............3.63

3.9.2.1 Choice of method....................................................................................................... ............3.63 3.9.2.2 Choice of em ission 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 co nsistent tim e series...................................................................................... ....3.84 3.9.3 Uncertainty assessment ................................................................................................... ............3.84 3.9.4 Quality Assessment/Quality Control (Q A/QC), Reporting and Documentation.........................3.87

3.9.4.1 Quality Assess ment/Quality Control ..................................................................................... 3.87 3.9.4.2 Reporting an d Documentation ............................................................................................ ...3.88 Annex 3.9A Feedstock-product flow diagrams .................................................................................... ..3.90 3.10 Fluorochemic al Production ................................................................................................. ................3.92

3.10.1 HFC-23 emission fr om HCFC-22 production .............................................................................3.92

3.10.1.1 In troduc tion

.......................................................................................................... ..................3.92 3.10.1.2 Metho dological issues................................................................................................. ...........3.92 3.10.1.3 Uncertai nty assessment................................................................................................ ........3.100 3.10.1.4 Quality Assurance/Qu ality Control (QA/QC), Repor ting and Document ation....................3.101 3.10.2 Emissions from production of other fluorinated compounds ....................................................3.102

3.10.2.1 In troduc tion

.......................................................................................................... ................3.102 3.10.2.2 Metho dological issues................................................................................................. .........3.103 3.10.2.3 Uncertai nty assessment................................................................................................ ........3.106 3.10.2.4 Quality Assurance/Qu ality Control (QA/QC), Repor ting and Document ation....................3.106 References..................................................................................................................... ............................... 3.107Volume 3: Industrial Processes and Product Use

3.6 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

# Equations

Equation 3.1 CO 2 emissions from ammonia production – Ti er 1 .............................................................3.12 Equation 3.2 Total fuel requirement fo r ammonia production – Tier 2.....................................................3.13 Equation 3.3 CO 2 emissions from ammonia produ ction – Tier 2 and 3....................................................3.13 Equation 3.4 Total fuel requirement fo r ammonia production – Tier 3.....................................................3.13 Equation 3.5 N 2 O emissions from nitric aci d production – Tier 1............................................................3.21 Equation 3.6 N 2 O emissions from nitric aci d production – Tier 2............................................................3.21 Equation 3.7 N 2 O emissions from adipic acid production – Tier 1...........................................................3.27 Equation 3.8 N 2 O emissions from adipic acid production – Tier 2...........................................................3.28 Equation 3.9 N 2 O emissions from caprolactam production – Tier 1.........................................................3.34 Equation 3.10 N 2 O emissions from caprolactam production – Tier 2.........................................................3.35 Equation 3.11 Emissions fr om carbide production................................................................................ .....3.41 Equation 3.12 CO 2 emissions from titanium slag, synthetic rutile and rutile TiO 2 production – Tier 1 .....3.48 Equation 3.13 CO 2 emissions from titanium slag, synthetic rutile and rutile TiO 2 production – Tier 2 .....3.48 Equation 3.14 CO 2 emissions from natural soda ash production – Tier 1...................................................3.52 Equation 3.15 Tier 1 CO 2 emission calculation ..........................................................................................3.65 Equation 3.16 Primary product pro duction estimate calculation ................................................................3. 65 Equation 3.17 Overall Tier 2 mass balan ce equation............................................................................. .....3.67 Equation 3.18 Estimate seco ndary product production fr om 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 CO 2 emissions calcula tion equatio n..........................................................................3.68 Equation 3.21 Fuel combustion Tier 3 CO 2 emissions calculation .............................................................3.68 Equation 3.22 Flare gas Tier 3 CO 2 emissions cal culation .........................................................................3.69 Equation 3.23 Tier 1 CH 4 fugitive emission calculation.............................................................................3.70 Equation 3.24 Tier 1 CH 4 process vent emissi on calcula tion .....................................................................3.70 Equation 3.25 Tier 1 CH 4 total emissions calculation.................................................................................3.70 Equation 3.26 Tier 3 CH 4 emission calculation based on at mospheric measurement data.........................3.71 Equation 3.27 Tier 3 CH 4 emissions calcula tion equatio n..........................................................................3.71 Equation 3.28 Fuel combustion Tier 3 CH 4 emissions calculation .............................................................3.72 Equation 3.29 Flare gas Tier 3 CH 4 emissions cal culation .........................................................................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 from process effi cienci es........................................................................................................... ...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 f actor 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) .....3.94Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.7 Equation 3.36 Tier 3c calculation of HFC-23 emissions from individual process streams (by monitoring reactor pr oduct) ............................................................................................................... ....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 st andard 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 cal culation of production -related emissions............................................................3.1 03 Equation 3.42 Tier 3 direct calculation of production-relate d emissions..................................................3.104 Equation 3.43 Tier 3 proxy calculation of production-relate d emissions..................................................3.104



# Figures

Figure 3.1 Decision tree for estimation of CO 2 emissions from ammonia production .........................3.14 Figure 3.2 Decision tree for estimation of N 2 O emissions from nitric acid production........................3.22 Figure 3.3 Decision tree for estimation of N 2 O emissions from adipic acid production.......................3.29 Figure 3.4 Decision tr ee for estimation of N 2 O emissions from caprolactam, glyoxal or glyoxylic acid production ....................................................................................................3. 36 Figure 3.5 Decision tree for estimation of CO 2 and CH 4 emissions from carbide production..............3.43 Figure 3.6 Decision tr ee for estimation of CO 2 emissions from titanium dioxide production..............3.49 Figure 3.7 Decision tr ee for estimation of CO 2 emissions from natural soda ash production ..............3.53 Figure 3.8 Decision tr ee for estimation of CO 2 emissions from petrochemical industry and carbon black industry .......................................................................................................... 3.63 Figure 3.9 Decision tr ee for estimation of CH 4 emissions from petrochemical industry and carbon black industry .......................................................................................................... 3.64 Figure 3.10 Tier 2 carbon ma ss balance flow diagram ...........................................................................3 .66 Figure 3.11 Methanol production fe edstock-product flow diagram........................................................3.90 Figure 3.12 Ethylene dichlo ride production feedstock-pr oduct flow diagram........................................3.90 Figure 3.13 Ethylene oxide production feedstock-product fl ow diagram...............................................3.91 Figure 3.14 Acrylonitrile production fe edstock-product fl ow diagram ..................................................3.91 Figure 3.15 Carbon black production fe edstock-product fl ow diagram..................................................3.91 Figure 3.16 Decision tree for HFC-23 emissions from HCFC-22 production (or other similar by-produ ct emissions from fluoroch emical production)...........................3.98 Figure 3.17 Decision tree for emissions of fluorinated greenhouse gases from production processes, applicable to both fugitive and by-produ ct emissi ons .......................................................3.105Volume 3: Industrial Processes and Product Use

3.8 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

# Tables

Table 3.1 Default total fuel requirements (fuel plus feedstock) and emission factors for ammonia production (per tonne NH 3 ) .................................................................................................3.15 Table 3.2 N 2 O abatement approaches an d abatement measures..........................................................3.20 Table 3.3 Default factors fo r nitric acid production ........................................................................... .3.23 Table 3.4 Default factors fo r adipic acid production ........................................................................... 3.30 Table 3.5 Default factor fo r caprolactam production...........................................................................3 .36 Table 3.6 Default factors for glyoxal and glyoxylic aci d production ..................................................3.39 Table 3.7 Default factors for CO 2 and CH 4 emissions from silicon carbide produ ction .....................3.44 Table 3.8 Emission factors for CO 2 emission from calcium carbi de production and use....................3.44 Table 3.9 Default factors for titanium dioxide production (tonnes CO 2 per tonne product)................3.49 Table 3.10 Specific carbon content of petr ochemical feedstocks and products.....................................3.69 Table 3.11 Petrochemical production Tier 1 default feedstocks and processes.....................................3.72 Table 3.12 Methanol production CO 2 emission factors.........................................................................3.73 Table 3.13 Methanol production feed stock consumption factors..........................................................3.74 Table 3.14 Steam cracking ethylene production Tier 1 CO 2 emission factors.......................................3.75 Table 3.15 Default Geographic Adjustment Factors for Tier 1 CO 2 emission factors for steam cracking ethy lene production...............................................................................3.75 Table 3.16 Default methane emission fa ctors for ethylene production .................................................3.76 Table 3.17 Ethylene dichloride/vinyl chloride production process Tier 1 CO 2 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 CH 4 emission factor..................3.78 Table 3.20 Ethylene oxide production feedstock consumption and CO 2 emission factors....................3.78 Table 3.21 Ethylene oxide production Tier 1 CH 4 emission factors.....................................................3.79 Table 3.22 Acrylonitrile production CO 2 emission factors ...................................................................3.79 Table 3.23 Carbon black production Tier 1 CO 2 emission factors ........................................................3.80 Table 3.24 Carbon black production Tier 1 CH 4 emission factors ........................................................3.80 Table 3.25 Ethylene steam cracking feedstock-product matrix.............................................................3.82 Table 3.26 Secondary product production factor s for acrylonitrile production process........................3.82 Table 3.27 Uncertainty ranges for emi ssion factors and activity data ...................................................3.86 Table 3.28 HFC-23 defa ult emission factors..................................................................................... ....3.99Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.9 

# Boxes

Box 3.1 CO 2 recovered for industrial gas..........................................................................................3.14 Box 3.2 Double counting ........................................................................................................ ..........3.16 Box 3.3 Urea produc tion........................................................................................................ ...........3.16 Box 3.4 Double counting ........................................................................................................ ..........3.40 Box 3.5 Allocation of emissi ons from CaO production....................................................................3.41 Box 3.6 Double counting ........................................................................................................ ..........3.48 Box 3.7 Double counting ........................................................................................................ ..........3.56 Box 3.8 Methanol pr ocess desc riptions.......................................................................................... ...3.58 Box 3.9 Ethylene pr ocess description ........................................................................................... ....3.59 Box 3.10 Ethylene dichloride and vinyl ch loride monomer proces s 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 productio n process desc riptions ....................................................................3.62 Box 3.14 Plant meas urement frequency........................................................................................... .3.100Volume 3: Industrial Processes and Product Use

3.10 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

# 3 CHEMICAL INDUSTRY EMISSIONS
3.1 INTRODUCTION
The following Sections 3.2 through 3.10 give guidance for estimating greenhouse gas emissions that result from the 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 dichlori de, ethylene oxide, acryl onitrile, 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 (SF 6 ) and uranium hexafluoride (UF 6 )

. Care should be exercised to avoid double counting of carbon dioxide (CO 2 ) emissions in both this chapter and in Volume 2 on Energy Sector, or, in omitting CO 2 emissions since CO 2 emissions resulting from carbon’s role as process reactant and as a heat source to drive the chemic al reactions involved in the chemical processes can be closely related. Should CO 2 capture technology be installe d at a chemical plant, the CO 2 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 CO 2 capture should consider that CO 2 emissions captured in the process may be both combustion and process-related. In cases where combustion and proce ss emissions are to be reported separately, e.g., in the petrochemical industry, inventory compilers should ensure that the same quantities of CO 2 are not double counted. In these cases the total amount of CO 2 captured should preferably be reported in the corresponding energy combustion and IPPU categories in proportion to the amounts of CO 2 generated in these source categories. The default assumption is that there is no CO 2 capture and storage (CCS) taking place. For additional information on CO 2 capture and storage refer to Volume 3, Section 1.2.2 and for more details to Volume 2, Section 2.3.4.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.11 

# 3.2 AMMONIA PRODUCTION

3.2.1 Introduction
Ammonia (NH 3 ) is a major industrial chemical and the most important nitrogenous material produced. Ammonia gas is used directly as a fertiliser, in heat treating, pa per pulping, nitric acid and nitrates manufacture, nitric acid ester and nitro compound manufacture, explosives of various types, and as a refrigerant. Amines, amides, and miscellaneous 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 through liquid 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 (CH 4 )), although H can be obtained from other hydrocarbons (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 through conversion to carbon dioxide (CO 2 ) which is the main potential direct greenhouse gas emission. Plants using hydrogen rather than natural gas to produce ammonia do not release CO 2 from the synthesis process.


# 3.2.2 Methodological issues The chemistry to obtain ammonia feedstocks is similar irrespective of the hydrocarbon used – CH 4 or other fossil fuels (Hocking, 1998; p.319). Because the industry uses predominantly natural gas, the follo wing outline of the process and sources of greenhouse emissions (CO 2 ) is based on production using natural gas. Anhydrous ammonia produced by catalytic steam reforming of natural gas (mostly CH 4 ) involves the following reactions with carbon dioxide produced as a by-product.
Primary steam reforming: CH 4 + H 2 O → CO + 3H 2

CO + H 2 O → CO 2 + H 2 Secondary air reforming: CH 4 + air → CO + 2H 2 + 2N 2 Overall reaction: 0.88CH 4 + 1.26Air + 1.24H 2 O → 0.88CO 2 + N 2 + 3H 2 Ammonia synthesis: N 2 + 3H 2 → 2NH 3 Secondary reformer proce ss gas shift conversion: CO + H 2 O → CO 2 + H 2 (Hocking, 1998; EFMA, 2000a; EIPPCB, 2004a) The processes that affect CO 2 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 CO 2 to methane with nickel catalysts to purify the synthesis gas. The production of ammonia represents a significant non-energy industrial source of CO 2 emissions. The primary release of CO 2 at plants using the natural gas catalytic steam reforming process occurs during regeneration of the CO 2 scrubbing solution with lesser emissi ons resulting from condensate stripping. Should CO 2 capture technology be installed and used at a plant, it is good practice to deduct the CO 2 captured in a higher tier emissions calculation. The default assumption is that there is no CO 2 capture and storage (CCS). In most cases, methodologies that account for CO 2 capture should consider that CO 2 emissions captured in the process 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 CO 2 captured should be accounted for in the IP PU Sector. For additional information on CO 2 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.Volume 3: Industrial Processes and Product Use

3.12 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### CARBON DIOXIDE REGENERATOR After absorption of CO 2 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 CO 2 from the bicarbonates according to the following reactions:

Heat 2KHCO 3 → K 2 CO 3 + H 2 O + CO 2 Heat (C 2 H 5 ONH 2 ) 2 + H 2 CO 3 → 2C 2 H 5 ONH 2 + H 2 O + CO 2 The stripping gas, containing CO 2 and other impurities, may be directed to a urea plant (where operational), to a liquid carbonic acid plant, or vented to the atmosphere (Environment Canada, 1987). 

### CONDENSATE STRIPPER Cooling the synthesis gas after low temperature shift co nversion forms a condensate containing small quantities of CO 2 and other process impurities. The condensate is stripped by steam, whereby the components may be vented to the atmosphere, but normally recycled to th e 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, used in the production of NH 3 . 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-le vel data that are available. The Tier 1 method is based on default values and national statistics; the Tier 2 me thod is based on complete plant-level output data distinguished by fuel input type and process type, and de fault values; and the Tier 3 method is based entirely on plant-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 fuel requirement. Similarly, Tier 3 can also use plant-level emission factors per unit of output provided that the source of these factors is plant-level detailed data on the fuel inputs per unit of output. 

### TIER 1 METHOD The Tier 1 method uses ammonia production to derive emissions as follows:

E QUATION 3.1 CO 2 EMISSIONS FROM AMMONIA PRODUCTION

– T IER 1

2 2 12 44 CO CO R COF CCF FR AP E

− • • • • =
Where:
E CO2 = emissions of CO 2 , 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
R CO2 = CO 2 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. CO 2 recovered for downstream use can be estimated from the quantity of urea produced where CO 2 is estimated by multiplying urea production by 44/60, the stoichiometric ratio of CO 2 to urea. When a deduction is made for CO 2 used in urea production it is good practice to ensure that emissions from ur ea use are included elsewhere in the inventory. If data are not available on urea production it is good practice to assume that CO 2 recovered is zero.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.13 

### TIER 2 METHOD The initial step is to determine the total fuel requirement. For the Tier 2 method the total fuel requirement for each fuel type is estimated as follows:

E QUATION 3.2 T OTAL FUEL REQUIREMENT FOR AMMONIA PRODUCTION

– T IER 2 

# ( ) ∑ • = j ij ij i FR AP TFR

Where:
TFR i = total fuel requirement for fuel type i , GJ
AP ij = ammonia production using fuel type i in process type j , tonnes FR ij = 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:

E QUATION 3.3 CO 2 EMISSIONS FROM AMMONIA PRODUCTION

– T IER 2 AND 3 

## ( ) 2 2 12 44 CO i i i i CO R COF CCF TFR E

− • • • = 

### ∑

Where:
E CO2 = emissions of CO 2 , kg
TFR i = total fuel requirement for fuel type i , GJ CCF i = carbon content factor of the fuel type i , kg C/GJ COF i = carbon oxidation fact or of the fuel type i , fraction
R CO2 = CO 2 recovered for downstream use (urea production, CO 2 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 coun try specific Energy Sector information. Data on CO 2 recovered for urea production and CCS should be obtained from producers. 

### TIER 3 METHOD The Tier 3 method requires that the fuel requirement be obtained from producers. Th e total fuel requirement is the sum of the total fuel requirements reported by each NH 3 production plant. That is:

E QUATION 3.4 T OTAL FUEL REQUIREMENT FOR AMMONIA PRODUCTION

– T IER 3 

### ∑ =

n in i TFR TFR

Where:
TFR i = total fuel requirement for fuel type i , GJ
TFR in = total fuel requir ement for fuel type i used by plant n , GJ Once data on total fuel requirem ents are collected and collated, CO 2 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 from producers or to use country specific energy sector in formation. As with the Tier 2 method, data on CO 2 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 ca lculation under the Tier 3 method it also needs to be collected from producers for reporting purposes.Volume 3: Industrial Processes and Product Use

3.14 2006 IPCC Guidelines for National Greenhouse Gas Inventories B OX 3.1 CO 2 RECOVERED FOR INDUSTRIAL GAS CO 2 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 a ll industrial gas carbon will be emitted to the atmosphere in the producing country. For example, industrial CO 2 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 CO 2 recovered data available directly from plants?

Are national aggregate ammonia

production data available? Are ammonia production data by fuel type and process type available?

Yes No No

Collect data for the Tier 2 or Tier 3 method. Use the plant-specific total fuel data as basis for the Tier 3 method and subtract plant-specific CO 2 recovered for urea production and CO 2 capture and storage (CCS).

Calculate total fuel requirement by fuel type, calcul ate emissions, and

subtract CO 2 recovered for urea production and CO 2 capture and storage (CCS).

Calculate emi ssions using default emission fa ctors and national

aggregate ammonia production. Subtract CO 2 recovered for urea production if data are available from national statistics.

Box 1: Tier 1 Box 2: Tier 2 Box 3: Tier 3

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

No Is this a key category 1 ? Gather production data or use production capacity data. Yes

No

Yes



## 3.2.2.2 C HOICE OF EMISSION FACTORS

TIER 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 dete rmined by expert analysis). The extent to which they represent a specific plant’s emission rate is unknown. Default factors by production process are provided in Table 3.1, and should be used only in cases where plan t-specific data are not available. The default factors are estimates of total fuel requi rements per unit of output expressed in energy units. They can be converted to mass units 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 CO 2 per tonne of NH 3 derived using these values.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.15 For the Tier 1 method it is good practice to use the highest total fuel requirement per tonne of ammonia. If no information on fuel type is available, it is good practice to use the average value s hown in Table 3.1 for partial oxidation.

T ABLE 3.1 D EFAULT TOTAL FUEL REQUIREMENTS ( FUEL PLUS FEEDSTOCK ) AND EMISSION FACTORS FOR AMMONIA PRODUCTION ( PER TONNE NH 3 ) Production Process Total fuel requirement (GJ(NCV)/tonne NH 3 )

± Uncertainty (%) Carbon content factor [CCF] 1 (kg/GJ) Carbon oxidation factor [COF] 1

(fraction) CO 2 emission factor (tonnes CO 2 /tonne NH 3 ) 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

Partial oxidation 36.0 ( ± 6%) 21.0 1 2.772 Derived from European average values for specific energy consumption (Mix of modern 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

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 de rived 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 pe r unit of output in Table 3.1 can be used in conjunction with data on NH 3 production by fuel type and process type, along with e ither default or co untry specific data on the C content factor and carbon oxidation factor of the fuels. 

### TIER 3 METHOD Plant-level data on total fuel requirement pr ovide the most rigorous data for calculating CO 2 emissions from ammonia 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 va riable for deriving the quantity of CO 2 emissions. Derivation of emissions using plant-level ammonia productio n depends on an accurate estimate of the fuel requirement per unit of output, along with information on the other variables.


## 3.2.2.3 C HOICE OF ACTIVITY DATA

TIER 1 METHOD The Tier 1 method requires data on national production of NH 3 . If national-level activity data are not available, information on production cap acity can be used. It is good practice to multiply the to tal national production capacity by a capacity utilisation factor of 80 percent ± 10 percen t (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 METHOD The Tier 2 method requires plant level data on ammoni a production classified by fuel type and production process. In addition, plant level data on CO 2 recovered for downstream use or other application are required.Volume 3: Industrial Processes and Product Use

3.16 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### TIER 3 METHOD The plant-level activity data re quired for the Tier 3 appro ach are total fuel requiremen t classified by fuel type, CO 2 recovered for downstream use or other applications, ammonia production. Although ammonia production is not used in the Tier 3 calculation, coll ection of all activity data that influen ce the estimation of emissions allows changes over time and any misreporting of activity data to be id entified. Where pl ant-level fuel requirement per unit of output is used, co llection of plant-level pro duction data is required.

B OX 3.2 D OUBLE COUNTING In order to avoid double counting, the total quantities of o il or gas used (fuel plus feedstock) in ammonia production must be subtracted from the quantity reported under energy use in the Energy Sector

. In addition, th e quantity of CO 2 recovered for downstream use in urea production must be subtracted from the total quantity of CO 2 generated to derive CO 2 emitted. Emissions of CO 2 from urea 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 au tomobile catalytic co nverters should be accounted for in the Energy Sector (Volume 2). Emissions from any other chemical products manufactured using CO 2 recovered from the process (e.g., emissions from carbonic acid use) are covered by methodology suggested in this section and should not be accounted for in other IPPU sections or in other sectors.

B OX 3.3 U REA PRODUCTION Urea (CO(NH 2 ) 2 ) (carbonyl amide or carbam ide) is an important nitr ogenous fertilis er with the highest nitrogen content available in a solid fertiliser. Urea is also used as a protein food supplement 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 NO x in exhaust gases originating from diesel or gasolin e direct injection engines. Emissions from urea applications should be accounted for in the appropriate application sectors. Urea production is a downstream process associ ated with ammonia production plants. The process uses the by-product CO 2 stream from an ammonia synthesis plant along with ammonia. Urea is produced by the reaction of NH 3 and CO 2 to produce ammonium carbamate which is then dehydrated to urea according to the reactions: Ammonium carbamate production:

2NH 3 + CO 2 → NH 2 COONH 4 Dehydration of ammonium carbamate to urea:
NH 2 COONH 4 → CO(NH 2 ) 2 + H 2 O Assuming complete conversion of NH 3 and CO 2 to urea, 0.733 tonnes of CO 2 are required per tonne of urea produced. Greenhouse gas emissions from modern plants are likely to be small. Excess NH 3 and CO 2 are contained in the process water wh ich is formed during the reaction. Water treatment is designed to re cover these substances from the pr ocess water to enable recycling of 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 CO 2 range from 2 to 7kg per tonne of urea. For a plant of 1 000 tonnes of urea per day and assuming capacity utilisation of around 90 percent, this would imply annual emissions of CO 2 of slightly in excess of 2Gg. Although emissions from urea production are unlik ely to be significant in well-managed modern plants, it is good practice to obtain plant-level information on urea production and to account for any significant emissions.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.17 

## 3.2.2.4 C OMPLETENESS
In countries where only a subs et 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 emissi ons using Tier 3 for all fac ilities during the transition. Where data for the Tier 3 method are not available for all plants, Tier 2 c ould 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 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 re maining emissions using Tier 1 in orde r to ensure completeness during the transition period. Complete coverage for ammonia production requires accounting for all emissions from all sources. CO 2 emissions are straightforward. Completeness can be im proved by ensuring that emissions of any fugitive CH 4 either from the primary reformer stage or catalytic methanation of CO 2 process are included. In order to include emissions of NO x , CO and SO 2 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 SERIES

CO 2 emissions should be recalculated for all years whenev er emission calculation methods are changed (e.g., if the inventory compiler changes from the use of default valu es 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 ap ply current plant-specific em ission factors to production data from previous years, provided that plant operations have not ch anged substantially. Recalculation is required to ensure that any changes in emissions trends are real and not an artefact of changes in procedure. It is good practice to recalculate the time series according to the guidance provided in Volume 1, Chapter 5.


# 3.2.3 Uncertainty assessment

3.2.3.1 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 and outputs 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 is good practice to obtain uncertainty estimates at the plant leve l, which should be lower than uncertainty values associated with default va lues. Default emission factor uncertainties reflect variations between plants across different 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 uncer tainty as low as ± 2 percent). This will include uncertainty estimates for fuel use, uncertainty estimates for ammonia production and CO 2 recovered. Data that are obtained from national statistical agencies usua lly do not include uncert ainty estimates. It is good practice to consult with national statisti cal agencies to obtain information on any sampling errors. Where national statistical agencies collect data from the population of ammonia pr oduction facilities, uncertaintie s in national statistics are not expected to differ from uncertainties established from plant-level consultations. Wh ere uncertainty values are not available from other sources, a default value of ± 5 percent can be used.


# 3.2.4 Quality Assurance/Quality Control (QA/QC), Reporting and Documentation

3.2.4.1 Q UALITY 

## A SSURANCE 

## /Q UALITY 

## C ONTROL

It is good practice to conduct quality control checks as outlined in Volume 1, Ch apter 6. More ex tensive quality control checks and quality assurance procedures are applicable, if higher tier methods are used to determineVolume 3: Industrial Processes and Product Use

3.18 2006 IPCC Guidelines for National Greenhouse Gas Inventories emissions. Inventory compilers are encouraged to use higher tier QA/QC for key categories as identified in Volume 1, Chapter 4. 

### Comparison of emission factors Inventory compilers should check if the estimated emission factors ar e 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 pro cess chemistry. For example, the CO 2 generation rate based on natural gas should not be less than 1.14 tonnes of CO 2 per tonne of ammonia produced. If th e emission factors are outside of the estimated ranges, it is good practice to assess and document the plant-spec ific conditions that account for the differences. 

### Plant-specific data check The following plant-specific data are required for adequate au diting of emissions estimates:

• Activity data comprising input and out put data (input data should be to tal fuel requiremen t – fuel energy input plus feedstock input;

• Calculations and estimation method;

• List of assumptions;

• Documentation of any plant-specific measur ement method, and measurement results. If emission measurements from individual plants are co llected, inventory compilers should ensure that the measurements were made according to recognised national or international standards. QC procedures in use at the site should be directly referenc ed and included in the QC plan. If the measurement practices were not consistent with QC sta ndards, 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 in formation required to produce the national emissions inventory estimates as outlined in Volume 1, Se ction 6.11. It is not practical to in clude 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 tr ansparent and steps in their calculation may be retraced. Much of the production and process data are considered pr oprietary by operators, esp ecially where there are only a small number of plants within a country. It is good practice to apply appropriate techniques, including aggregation of data, to ensure protection of confiden tial data. Guidance on managing confidential data is provided in Section 2.2, Volume 1.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.19 

# 3.3 NITRIC ACID PRODUCTION

3.3.1 Introduction

Nitric acid is used as a raw material mainly in the manufactu re of nitrogenous-based fertiliser. Nitric acid may also be used in the production of ad ipic acid and explosives (e.g., dyna mite), for metal etching and in the processing of ferrous metals. During the production of nitric acid (HNO 3 ), nitrous oxide (N 2 O) is generated as an unintended by-product of the high temperature catalytic oxidation of ammonia (NH 3 ). The amount of N 2 O formed depends, inter alia, on combustion conditions (pressure, temp erature), catalyst composition and age, and burner design (EFMA, 2000b; p.15). In addition, some NO x is produced. Formation of NO x is most pronounced at start-up and shut-down when the process is least stable (EFMA, 2000b; p.15). N 2 O 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 fuel reprocessing). Nitric acid is a significant source of atmospheric N 2 O if not abated and is the major source of N 2 O emissions in the chemical industry. While, unlike othe r emissions from nitric acid production, there are no mature technologies specifically de signed for the destruction of N 2 O (Perez-Ramirez et al ., 2003) a number of technologies for N 2 O mitigation during nitric acid manufacture have been developed in recent years. Examples include a tail-gas process where both N 2 O and NO emissions can be simultane ously reduced (req uiring addition of ammonia to the tail-gas), a pro cess-gas option involving direct catalytic decomposition right after the platinum 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 thre e distinct chemical reactions that can be summarised as follows:

4NH 3 + 5O 2 → 4NO + 6H 2 O 2NO + O 2 → 2NO 2 3NO 2 + H 2 O → 2HNO 3 + 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 N 2 O. Nitric ox ide (NO), an intermediate in the production of nitric acid, is also documented to readily decompose to N 2 O and nitrogen dioxide (NO 2 ) 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 r eactions during the oxidation of ammonia that might result in the formation of N 2 O:

NH 3 + O 2 → 0.5N 2 O + 1.5H 2 O NH 3 + 4NO → 2.5N 2 O + 1.5H 2 O NH 3 + NO + 0.75O 2 → N 2 O + 1.5H 2 O

Reactions that lead to the formation of N 2 O or N 2 are undesirable in that they de crease the conversion efficiency of NH 3 and reduce the yield of the desired product, NO (Perez-Ramirez et al ., 2003; p.124). It is not possible to define a precise relationship between NH 3 input and N 2 O formation because in general, ‘the amount of N 2 O formed depends on combustion conditions, catalyst composition and state (age), and burner design’ (PerezRamirez et al ., 2003; p.123). Emissions of N 2 O depend on the amount generated in the production process and the amount destroyed in any subsequent abatement process. Abatement of N 2 O can be inten tional, through installation of equipment designed to destroy N 2 O, or unintentional in systems de signed to abate other emissions such as nitrogen oxides (NO x ). Perez-Ramirez et al . (2003; p.126) classify abatement approaches as follows and abatement measures associated with each approach are outlined in Table 3.2:Volume 3: Industrial Processes and Product Use

3.20 2006 IPCC Guidelines for National Greenhouse Gas Inventories • Primary abatement measur es aim at preventing N 2 O being formed in the ammonia burner. This involves modification of the ammonia oxidation process and/or catalyst.

• Secondary abatement measures remove N 2 O from the valuable intermedia te stream, i.e. from the NO x gases between the ammonia conver ter and the absorptio n column. Usually this will mean interven ing at the highest temperature, immediately downstr eam of the ammonia oxidation catalyst.

• Tertiary abatement measures invo lve treating the tail-gas leaving th e absorption column to destroy N 2 O. The most promising position for N 2 O abatement is upstream of th e tail-gas expansion turbine.

• Quaternary abatement measures are the pure end-of-pipe so lution, where the tail-ga s is treated downstream of the expander on its way to the stack.

T ABLE 3.2 N 2 O ABATEMENT APPROACHES AND ABATEMENT MEASURES Abatement approaches Abatement measures Primary abatement • Optimal oxidation process

• Modification of platinum-rhodium gauzes

• Oxide-based com bustion 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 de pend on the technology impl emented with tertiary meas ures stated as, ‘enabling the achievement of high levels of N 2 O removal (>99 percent)’ (Perez-Ramirez et al ., 2003; p.136). Additionally, it is noted that although NSCR is a proven technology for N 2 O reduction, the replacement of NSCR systems by SCR systems for NO x reduction has a negative side -effect on its application for N 2 O 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-effectivene ss 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 N 2 O decomposition is a very a ttractive and co st effective option in plants with tail-gas temperatur es 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 or ammonia) is required, making the afte r-treatment prohibitive. Th e most elegant and cost-e ffective option is the in process-gas catalytic decompos ition, located in the heart of the plant (the ammoni a burner). Concerns with this abatement option are chemical and mech anical stability of the catalyst as well as the possible NO loss. Several catalyst manufacturers and nitric acid pr oducers have addressed this problem and catalysts are in the early stages of commercialisation. Advantageously, and contrary to th e tail-gas option, this technol ogy 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 meth ods to national circumstances. Emi ssions can be estimated from:

• continuous emissions monitoring (CEM) where emissions are directly measured at all times;Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.21 • periodic emissions monitoring that is undertaken over a period(s) that is reflectiv e of the usual pattern of operation of the plant to derive an emission factor that is multiplied by output (100 percent HNO 3 ) to derive emissions;

• irregular sampling to derive an emission factor that is multiplied by output (100 percent HNO 3 ) to derive emissions;

• by multiplying a default emission factor by out put (100 percent HNO 3 ). Methods are classified according to the ex tent of plant-level data that are available. Both Tier 2 and Tier 3 are based on plant-level activity data. 

### TIER 1 METHOD
Emissions are estimated as follows:

E QUATION 3.5 N 2 O EMISSIONS FROM NITRIC ACID PRODUCTION

– T IER 1 NAP EF E O

N • = 2
Where:
E N2O = N 2 O emissions, kg
EF = N 2 O emission factor(default), kg N 2 O/tonne nitric acid produced NAP = nitric acid production, tonnes When applying the Ti er 1 method it is good practice to assume that there is no abatement of N 2 O emissions and to 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 (estimat es range from 255 to 600 plants according to Choe et al ., 1993; Bockman and Granli, 1994) with substantial variations in the N 2 O generation factors among plant types. Consequently, default factors may be needed more often for nitric acid N 2 O 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 N 2 O generation factor. The Tier 2 method uses plant-level production data di saggregated by technology type and default emission factors classified by technology type . Emissions are calculated as follows:

E QUATION 3.6 N 2 O EMISSIONS FROM NITRIC ACID PRODUCTION

– T IER 2 

# ( ) 

# [ ] ∑ •

− • • = j

i j j i i O N ASUF DF NAP EF E

, 2 1

Where:
E N2O = emissions of N 2 O, kg
EF i = N 2 O emission factor fo r technology type i , kg N 2 O/tonne nitric acid produced
NAP i = nitric acid production from technology type i , tonnes DF j = destruction factor for abatement technology type j , fraction ASUF j = abatement system utilisation fact or for abatement technology type j , fraction Note that the default emission factors shown in Tabl e 3.3 include the impact on emissions of abatement technology where relevant. To use these factors, inventor y compilers should veri fy that the abatement technology is installed at individual pl ants and operated throughout the year. The basic equation for estimating N 2 O emissions includes additional terms that recognise the potential future use of N 2 O abatement technologies. The N 2 O destruction factor has to be multiplied by an abatement system utilisation factor in order to account for any down-time of the emission ab atement equipment (i.e., time the equipment is not operating).Volume 3: Industrial Processes and Product Use

3.22 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### 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 di rect measurement of emissions. These may be derived from irregular sampli ng of emissions of N 2 O or periodic emissions monitoring of N 2 O 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 noted that most plants are unlikely to em ploy CEM due to the resource costs. Where CEM is employed, emissions can be estimated based on the sum of measured N 2 O emissions derived from the concentration of N 2 O 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?

Is this a key category 1 ? Are plant-specific activity data on nitric acid production available?

Yes No No

Collect data for the Tier 3 or Tier 2 method. Use plant specific-emissions data and activity data (irregular sampling

data, periodic monitoring data or continuous emissions monitoring) as basis for Tier 3 method.

Use plant-specific data on quantity

of nitric acid by technology type produced as basis for Tier 2 method.

Use national data on nitric acid production or national data on capacity, and defaul t emission factors.
Box 1: Tier 1 Box 2: Tier 2 Box 3: Tier 3

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

No Yes



## 3.3.2.2 C HOICE OF EMISSION FACTORS

TIER 1 METHOD
It is good practice to use the highest emission factor based on the technology type shown in Table 3.3 and to assume that there is no abatement of N 2 O 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 dete rmined by expert analysis). The extent to which theyChapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.23 represent a specific plant’s emission ra te 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 N 2 O, and associated uncertainties. The factors listed in Table 3.3 for plants using non-selective catal ytic reduction (NSCR), (a NO x abatement technology that can also be managed to abate N 2 O), already incorporat e the effect of N 2 O abatement measures. To use these factors, inventory compilers should verify that the abatement tech nology is installed at individual plan ts and operated th roughout the year. 

### TIER 3 METHOD Plant measurements provide the most rigorous data for calculating net emissions (i.e., N 2 O generation and destruction factors). Monitoring N 2 O emissions from nitric acid productionis 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 system atic errors and to achieve the desired level of accuracy. 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 N 2 O, and sufficiently often otherwise to ensure that operating conditions are consta nt. In addition, plant opera tors should be consulted annually to determine the specific destruction technologies employ ed and confirm their use, since t echnologies may change over time. Precise measurement of the emissions rate and abatemen t efficiencies requires measurement of both the exit stream and the uncontrolled stream. Where measurem ent data are available only on the exit stream, good practice is to base emissions on these data. In this case, an y available estimates of ab atement efficiency should be provided only for information purposes and are not used to calculate emissions.

T ABLE 3.3 D EFAULT FACTORS FOR NITRIC ACID PRODUCTION
Production Process N 2 O Emission Factor (relating to 100 percent pure acid)
Plants with NSCR a (all processes) 2 kg N 2 O/tonne nitric acid ± 10% Plants with process-integrated or tailgas N 2 O destruction 2.5 kg N 2 O/tonne nitric acid ± 10% Atmospheric pressure plants (low pressure) 5 kg N 2 O/tonne nitric acid ± 10% Medium pressure combustion plants 7 kg N 2 O/tonne nitric acid ± 20% High pressure plants 9 kg N 2 O/tonne nitric acid ± 40%

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

### TIER 1 METHOD The 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 METHOD The Tier 2 method requires plant-level production data di saggregated 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 produc tion data is assumed to ha ve an uncertainty of ±2 percent due to the economic value of having accurate information.Volume 3: Industrial Processes and Product Use

3.24 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### TIER 3 METHOD As with the Tier 2 method, plant-level production data disaggregated by technology and abatement system type are required. It is good practice to gather activity (p roduction) data at a level of de tail consistent with that of any generation and destruction data. Althou gh production data are 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 assumed to have an uncertainty of ±2 percent du e to the economic va lue of having accurate information.


## 3.3.2.4 C OMPLETENESS
Nationally compiled nitric acid production statistics c ould 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 percen t 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 neve r enters into commerce and is not counted in the national statistics. It is good practice to account for these sources by methods such as identifying them through national registries of NO x emissions, another unintended by-product of nitric acid production. NSCR and SCR systems designed to abate N 2 O can give rise to additional emissions of CO, CO 2 and hydrocarbons (CH 4 and NMVOCs). These emissions will depend on the hyd rocarbon reducing ag ent that is used (methane (CH 4 ), propane (C 3 H 8 ), propene (C 3 H 6 ), LPG). Emissions can be estim ated based on the quantity of reducing agent used and the completeness of combustion. Plant-level information wi ll be required to enable emissions 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 pl ants in a country, and it is suggested that emissions ar e calculated from plant specific data. 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 emi ssions 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 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 th e remaining emissions using Tier 1 in order to ensure completeness during the transition period.


## 3.3.2.5 D EVELOPING A CONSISTENT TIME SERIES

N 2 O emissions should be recalculated for all years whenev er emission calculation methods are changed (e.g., if the inventory compiler changes from the use of default valu es to actual values determined at the plant level). If plant-specific data are not available fo r 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 prev ious years, provided that plant operations have not changed substantially. Such a recalculation is required to ensure that any changes in emissions trends are real and not an artefact of changes in procedure. It is good practice to recalculate the time series according to the guidance provided in Volume 1, Chapter 5.


# 3.3.3 Uncertainty assessment

3.3.3.1 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 va riations and gases are more easily lost through process leaks. The default values for nitric acid production have a relatively high level of unc ertainty for two reasons. First, N 2 O 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 NO x control, and the NO xChapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.25 abatement system may or may not re duce (or may even increase) the N 2 O concentration of the treated gas 1 . It is good practice to obtain uncertainty estimates at the plant-leve l which should be lower than uncertainty values associated with default values.


## 3.3.3.2 A CTIVITY DATA UNCERTAINTIES
Where activity data are obtain ed from plants, uncertainty estimates can be obtained from producers. Data that are obtained from national statistical agencies usually do not include uncertain ty estimates. It is good practice to consult with national statisti cal agencies to obtain information on any sampling errors. Where national statistical agencies collect data from the population of nitric aci d production facilities, uncertainties in national statistics are not expected to differ from uncer tainties established from plant-level co nsultations. Where unc ertainty values are not available from other sources, a default value of ± 2 percent can be used. To reduce uncertainty it is good practice to ensure that all activity data are for 100 percent HNO 3 . 

# 3.3.4 Quality Assurance/Quality Control (QA/QC), Reporting and Documentation

3.3.4.1 Q UALITY 

## A SSURANCE 

## /Q UALITY 

## C ONTROL

It is good practice to conduct quality control checks as outlined in Volume 1, Ch apter 6. More ex tensive quality control checks and quality a ssurance 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 in Volume 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 th e estimate to emissions calculated using national production data (top-down approach). They should record the results and investigate any unexplained discrepancies. Since industrial N 2 O source categories are relatively small compar ed to other anthropogenic and natural sources, it is not feasible to compare emissions with measured trends in atmospheric N 2 O concentrations. 

### Plant-level data Inventory compilers should archive sufficient information to allow an independent revi ew of the time series of emissions beginning in the base year, and to explain tr ends in emissions when making historical comparisons. This is particularly important in cases where recalcu lations are necessary, for ex ample, when an inventory compiler changes from using default values to actual values de termined at the plant level. 

### Revision of direct emission measurements If plant-level N 2 O measurements are available, inventory co mpilers should confirm that internationally recognised, standard methods were us ed. If the measurement practices fail this criterion, then they should evaluate the use of these emissions data . In addition, they should reconsider the uncerta inty estimates in light of the QA/QC results. Inventory compilers should compare plant-based factors to the IPCC defaults to ensu re that the plant-specific factors are reasonable. They should explain and docum ent any differences between plant-specific factors and default factors, particularly any differences in plan t 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 in formation 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 NO x emissions may result in additional N 2 O generation. Increased N 2 O

concentrations due to NO x abatement technology have been measured at various power pl ants that employ non-catalytic reduction for NO x (Cook, 1999). From at least one nitr ic acid plant, it is known that NO x control resulted in increased N 2 O emissions (Burtscher, 1999).Volume 3: Industrial Processes and Product Use

3.26 2006 IPCC Guidelines for National Greenhouse Gas Inventories • 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, destru ction efficiency, and utilisation;

• Any other assumptions. Plant operators should supply this information to the in ventory compiler for compilati on, and also archive the information at the site. Plant op erators should also log and arch ive the measurement frequencies and instrumental calibration re cords where actual plant measurements are made. Where there are only one or two producers in a country, activ ity data may be considered confidential. In this case, operators and the inventory compiler should determine th e level of aggregation at which information can be reported while still protectin g confidentiality. Detailed information incl uding instrumentation records should still be archived at the plant level. It is not practical to include all doc umentation in the national inventory report. However, the inventory should include summaries of methods used and references to sour ce data such that the repor ted emissions estimates are transparent and steps in their calculation may be retraced.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.27 

# 3.4 ADIPIC ACID PRODUCTION

3.4.1 Introduction Adipic acid is used in the manufactur e of a large number of products includ ing 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 fracti on 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 fractio n of the adipic acid is converted into di-octyl (di-2- ethylhexyl) 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 oxidised by nitric acid in the presence of a cataly st to form adipic acid. Nitrous oxide (N 2 O) is generated as an unintended by-product of the nitric acid oxidation stage:
(CH 2 ) 5 CO (Cyclohexanone) + (CH 2 ) 5 CHOH (Cyclohexanol) + wHNO 3 → HOOC(CH 2 ) 4 COOH (Adipic Acid) + xN 2 O + yH 2 O

Adipic acid is a significan t source of atmospheric N 2 O if not abated. Emissions of N 2 O depend on the amount generated in the production process and the amount destr oyed in any subsequent abatement process. Abatement of N 2 O can be intentional th rough installation of equipment sp ecifically designed to destroy N 2 O in adipic acid plants. Adipic acid productio n also results in the emissions of NMVOC, CO and NO x . Process emissions from the production of adipic acid vary substantially with the level of em ission 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 emissi ons monitoring (CEM) where emissions are directly measured at all times, periodic emissions monitoring that is unde rtaken over a period(s) that is reflective of the usual pattern of operation of the plant to derive an em ission factor that is multiplied by output to derive emissions, irregular sampling to derive an emission factor that is multiplied by output to deri ve emissions, or by multiplying a default emission factor by output. Methods are classified according to th e extent of plant-level data that ar e available. Both Tier 2 and Tier 3 require plant-level activity data. 

### TIER 1 METHOD
Emissions are estimated as follows:

E QUATION 3.7 N 2 O EMISSIONS FROM ADIPIC ACID PRODUCTION

– T IER 1 AAP EF E O

N • = 2
Where:
E N2O = N 2 O emissions, kg
EF = N 2 O emission factor(default), kg N 2 O/tonne adipic acid produced AAP = adipic acid production, tonnes When applying the Ti er 1 method it is good practice to assume that there is no abatement of N 2 O emissions and to use the highest default emission factor shown in Table 3.4.Volume 3: Industrial Processes and Product Use

3.28 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### TIER 2 METHOD The 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. Emi ssions are calculated as follows:

E QUATION 3.8 N 2 O EMISSIONS FROM ADIPIC ACID PRODUCTION

– T IER 2 

# ( ) 

# [ ] ∑ •

− • • = j

i j j i i O N ASUF DF AAP EF E

, 2 1

Where:
E N2O = emissions of N 2 O, kg
EF i = N 2 O emission factor fo r technology type i , kg N 2 O/tonne adipic acid produced
AAP i = adipic acid production from technology type i , tonnes DF j = destruction factor for abatement technology type j , fraction ASUF j = abatement system utilisation fact or for abatement technology type j , fraction The basic equation for estimating N 2 O emissions includes additional te rms that recognise the use of N 2 O abatement technologies. The N 2 O destruction factor has to be multipli ed by an abatement system utilisation factor in order to account for any do wn-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 N 2 O generation and destruction factors developed from plant-specific measurement data. In this case, the national total is equal to the sum of plant totals . Where plant-leve l information is not available, good practice provides default N 2 O generation factors and destruction factors as shown in Ta ble 3.4, Default Factors for Adipic Acid Production, based on abatement technologies implemented. To use thes e factors, inventory compilers should verify that the abatement technology is installe d at individual plants and op erated throughou t the year. 

### TIER 3 METHOD – DIRECT MEASUREMENT The Tier 3 method uses plant leve l production data and pl ant-level emission factors obtained from direct measurement of emissions. These may be derive d from irregular sampling of emissions of N 2 O or periodic emissions monitoring of N 2 O undertaken over a period(s) that reflects th e 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 this equation at the plant-level using N 2 O generation and destruction factor s developed from plant-specific measurement data where relevant. Given the relatively sm all number of adipic acid plants (about 23 globally, Choe et al ., 1993), obtaining plant- specific information requir es few additional resources. Alternatively, the Tier 3 method uses the results of continuous emissions monitoring (CEM), although it is noted that most plants are unlikely to em ploy CEM due to the resource costs. Where CEM is employed, emissions can be estimated based on the sum of measured N 2 O emissions derived from the concentration of N 2 O in monitored emissions for each recorded monitoring interval.


## 3.4.2.2 C HOICE OF EMISSION FACTORS

TIER 1 METHOD
It is good practice to use the default emission fact or shown in Table 3.4 and to assume that there is no abatement of N 2 O 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 re present midpoint or mean values of data sets (as determined by expert analysis). The ex tent to which they repres ent a specific pl ant’s emission rate is unknown. Default factors in Table 3.4 should be used only in cases where plant-specific measur ements are not available. Also included in Table 3.4 are default N 2 O destruction factors for commonly used abatement technologies, and associated uncertainties. To use these factors, inventory compilers should veri fy that the abatement technology is installed at individual plants and operated throughout th e year. Failure to determine if abatement technologiesChapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.29 are being used can result in overestimation of emissions. Determination of the appropri ate values requires that plants be classified according to the abatement technology implemented.. 

### TIER 3 METHOD The Tier 3 method requires plant measurements. If the N 2 O abatement system is in use, plant measurements provide the most rigorous data for calculating net emissions (i.e., N 2 O generation and destruction factors). Monitoring N 2 O emissions from adipic acid production is practic al 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 accu racy of the overall measur ement. Usually sampling frequency and timing is sufficient to avoid systematic errors and to achieve the desired level of accuracy. Where the N 2 O abatement system is not in use, a plant-specif ic 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 N 2 O, and sufficiently often otherwise to ensure that operating conditions are consta nt. In addition, plant opera tors should be consulted annually to determine the specific destruction technologies employ ed and confirm their use, since t echnologies may change over time. Precise measurement of the emissions rate and abatemen t efficiencies requires measurement of both the exit stream and the uncontrolled stream. Where measurem ent data are available only on the exit stream, good practice is to base emissions on these data. In this case, an y available estimates of ab atement efficiency should be provided only for information purpos es 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?

Is this a key category 1 ? Are plant- specific activity data available on adipic acid production?

Yes No No

Collect data for the Tier 3 or Tier 2 method. Use plant specific-emissions data and activity data (irregular sampling

data, periodic monitoring data or continuous emissions monitoring) as basis for Tier 3 method.

Use plant-specific data on quantity of adipic acid produced as basis for Tier 2 method.

Use national data on adipic acid production or national data on capacity, and defaul t emission factors.
Box 1: Tier 1 Box 2: Tier 2 Box 3: Tier 3

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

No YesVolume 3: Industrial Processes and Product Use

3.30 2006 IPCC Guidelines for National Greenhouse Gas Inventories T ABLE 3.4 D EFAULT FACTORS FOR ADIPIC ACID PRODUCTION
Production Process N 2 O Generation Factor a,d Uncertainty Estimate

Nitric Acid Oxidation 300 kg/tonne adipic acid (uncontrolled) ± 10% (based on expert judgement). The range of 300 kg ± 10% encompasses the variability from pure ke tone to pure alcohol feedstocks, with most manufacturers somewhere in the middle. a
Abatement Technology N 2 O Destruction Factor b Uncertainty Estimate

Catalytic Destruction 92.5% 90-95% (based on expert judgement ). Manufacturers known to employ this technology include: BASF (Scott, 1998), and DuPont (Reimer, 1999b).
Thermal Destruction 98.5% 98-99% (based on expert judgement ). Manufacturers known to employ this technology include: Asahi, DuPont, Bayer, and Solutia (Scott, 1998). Recycle to Nitric Acid 98.5% 98-99% (based on expert judgement ). Manufacturers known to employ this technology include: Al sachemie (Scott, 1998). Recycle to feedstock for Adipic Acid 94% 90-98% (based on expert judgement). Solutia implemente d this technology around 2002.

Abatement System Utilisation Factor d Uncertainty Estimate

Catalytic Destruction 89% 80-98% (based on expert judgement) c

.

Thermal Destruction 97% 95-99% (based on expert judgement) c

.
Recycle to Nitric Acid 94% 90-98% (based on expert judgement) c

.
Recycle to Adipic Acid 89% 80-98% (based on expert judgement) c

.

aWith regard to a value from the Japan Environment Agency (1995) (282 kg N 2 O/tonne adipic acid), it is believed that this

manufacturer uses oxidation of pure cyclohexanol (alc ohol), 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 abatemen t efficiency) should be multiplied by an abatement system utili ty

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 implem entation, the utilisation factor tends to be at the lower end of the range. Lower u tility of the equipment typically results because of the need to learn how to ope rate the abatement system a nd because more maintenance problems occur during the initial phase. After 1-5 years, the ope rating experience improves and th e utilisation factor would te nd to be at the high end of the range. Source: d Thiemans and Trogler (1991).

e Reimer (1999b).



## 3.4.2.3 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 METHOD The Tier 1 method requires data on national production of adipic acid. 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 utilisat ion factor of 80 percen t ± 10 percent (i .e., a range of 70-90 pe rcent). 

### TIER 2 METHOD The Tier 2 method requires plant-level production data disaggregated by abatement technology 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 accurate to ±2 percent due to the economic value of having accurate information.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.31 

### 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 samp ling of emissions. 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 is not used in the estimation of emissi ons where the estimate is based on CEM, these data should be collected and reported to ensure that chan ges in variables that influence emissions can be monitored over time. Typical plant-level productio n 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 stra ightforward because of the small number of readily identifiable plants.


## 3.4.2.5 D EVELOPING A CONSISTENT TIME SERIES

N 2 O emissions should be recalculated for all years whenev er emission calculation methods are changed (e.g., if the inventory compiler changes from the use of default valu es to actual values determined at the plant level). If plant-specific data are not available fo r 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 prev ious years, provided that plant operations have not changed substantially. Such a recalculation is required to ensure that any changes in emissions trends are real and not an artefact of changes in procedure. It is good practice to recalculate the time series according to the guidance provided in Volume 1, Chapter 5.


# 3.4.3 Uncertainty assessment

3.4.3.1 E MISSION FACTOR UNCERTAINTIES

Uncertainties for the defau lt 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 (n itric acid oxidation) and N 2 O-specific abatement systems. The uncertainty in the emission factor for adipic acid represents a variability in N 2 O generation due to differences in the composition of the cyclohexanone and cyclohex anol feedstock (i.e. ketone and alcohol) that are used by different manufacturers. Higher ketone content results in increased N 2 O generation, whereas higher alcohol content results in less N 2 O generation (Reimer, 1999a). Dependent on the process, based on nitric acid (HNO 3 ) consumption an individual plant should be able to determine the production of N 2 O within 1 percent. Uncertain ties for the default values are shown in Table 3.4.


## 3.4.3.2 A CTIVITY DATA UNCERTAINTIES

Potential N 2 O emissions per metric tonne produced are far gr eater for adipic acid production than for other industrial sources of N 2 O. Measurements obtained fro m 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 the small number of adipic acid plants, the uncertainty in national pr oduction data (Tier 1) is the same as for plantlevel data, namely, ±2 percent.


# 3.4.4 Quality Assurance/Quality Control (QA/QC), Reporting and Documentation

3.4.4.1 Q UALITY 

## A SSURANCE 

## /Q UALITY 

## C ONTROL

It is good practice to conduct quality control checks as outlined in Volume 1, Chapte r 6, and an expert review of the 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 thisVolume 3: Industrial Processes and Product Use

3.32 2006 IPCC Guidelines for National Greenhouse Gas Inventories 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 s ource 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 th e estimate to emissions calculated using national production data (top-down approach). They should record the results and investigate any unexplained discrepancies. Since industrial N 2 O source categories are relatively small compar ed to other anthropogenic and natural sources, it is not feasible to compare emissions with measured trends in atmospheric N 2 O concentrations. 

### Plant-level data Inventory compilers should archive sufficient information to allow an independent revi ew of the time series of emissions beginning in the base year, and to explain tr ends in emissions when making historical comparisons. This is particularly important in cases where recalcu lations are necessary, for ex ample, when an inventory compiler changes from using default values to actual values de termined at the plant level. 

### Revision of direct emission measurements If plant-level N 2 O measurements are available, it is sugges ted that inventory compilers confirm that internationally recognised, standard methods were used. If the measurement practices fail this criterion, then they should evaluate the use of these emissi ons data. In addition, they should r econsider the uncerta inty estimates in light of the QA/QC results. Inventory compilers are encouraged to compare plant-based factors to the IPCC defaults to ensure th at the plantspecific factors are reasonable. They should explain and document any differences between plant-specific factors and default factors, particularly any differences in plan t 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 in formation 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, destru ction efficiency, and utilisation;

• Any other assumptions. Plant operators should supply this information to the in ventory compiler for compilati on, and also archive the information at the site. Plant op erators should also log and arch ive the measurement frequencies and instrumental calibration re cords 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 confid ential. In this case, operators and th e inventory compiler should determine the level of aggrega tion at which information can be reported while still protecting conf identiality. Detailed information including instrumentation records s hould still be archived at the plant level. It is not practical to include all doc umentation in the national inventory report. However, the inventory should include summaries of methods used and references to sour ce data such that the repor ted emissions estimates are transparent and steps in their calculation may be retraced.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.33 

# 3.5 CAPROLACTAM, GLYOXAL AND GLYOXYLIC ACID PRODUCTION

3.5.1 Introduction This section addresses the production of three chemical s - caprolactam, glyoxal, and glyoxylic acid - that are potentially important sour ces of nitrous oxide (N 2 O) emissions in the countrie s in which the chemicals are produced. The methodology for caprolactam is discussed in detail and is suitable for application to estimation of emissions from glyoxal and glyoxylic acid. In Section 3. 5.3, the production processes for glyoxal and glyoxylic acid that give rise to emissions of N 2 O are outlined. Default gene ration factors, destructio n 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 (C 6 H 11 NO) 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 base d 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 (C 6 H 10 O). The classical route (Raschig process) and basic reaction equations for production from cyclohexanone ar e (Reimschuessel, 1977; p.83: Lowenheim and Moran, 1975; p. 201):

Oxidation of NH 3 to NO/NO 2 ↓ NH 3 reacted with CO 2 /H 2 O to yield ammonium carbonate (NH 4 ) 2 CO 3 ↓ (NH 4 ) 2 CO 3 reacted with NO/NO 2 (from NH 3 oxidation) to yield ammonium nitrite (NH 4 NO 2 ) ↓ NH 3 reacted with SO 2 /H 2 O to yield ammonium bisulphite (NH 4 HSO 3 ) ↓ NH 4 NO 2 and NH 4 HSO 3 reacted to yield hydroxylamine disulphonate (NOH(SO 3 NH 4 ) 2 ) ↓ NOH(SO 3 NH 4 ) 2 hydrolised to yield hydroxylamine sulphate (NH 2 OH) 2 .H 2 SO 4 ) and ammonium sulphate ((NH 4 ) 2 SO 4 ) ↓ Cyclohexanone reaction: C 6 H 10 O + 1⁄2(NH 2 OH) 2 .H 2 SO 4 (+NH 3 and H 2 SO 4 ) → C 6 H 10 NOH + (NH 4 ) 2 SO 4 + H 2 O Beckmann rearrangement: C 6 H 10 NOH (+H 2 SO 4 and SO 2 ) → C 6 H 11 NO.H 2 SO 4 (+4NH 3 and H 2 O) → C 6 H 11 NO + 2(NH 4 ) 2 SO 4

Lowenheim and Moran (1975; p. 202) summarise the Ra schig production process as follows. Caprolactam is produced via Beckmann rearrangement (conversion of a ke tone oxime into an amide, usually using sulphuric acid as a catalyst) by the addition of hydroxylamine su lphate to cyclohexanone. Hy droxylamine sulphate is produced from ammonium nitrate and sulphur dioxide . Ammonia gas and air are fed to a converter where ammonia 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, and sulphur dioxide by burning sulphur. The disulphonate is hydrolysed to hydroxylamine sulphate and ammonium sulphate. The addition of hydroxylam ine sulphate to cyclohe xanone produces cyclohex anone oxime which is converted to caprolactam by the Beckmann rearrangement.Volume 3: Industrial Processes and Product Use

3.34 2006 IPCC Guidelines for National Greenhouse Gas Inventories Production of caprolactam can give rise to emissions of nitrous oxide (N 2 O) from the ammonia oxidation step, emissions of CO 2 from the ammonium carbonate step, emissions of sulphur dioxide (SO 2 ) from the ammonium bisulphite step, and emissions of NMVOCs. Emissions of CO 2 , SO 2 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 N 2 O. Modified caprolactam production processes are primarily concerned with elimination of the high volumes of ammonium sulphate that are produced as a by-product of the conventional process (Reimschuessel, 1977; p.84). NH 3 oxidation remains an in tegral part of all pr ocesses to obtain the NO/NO 2 required.



### CHOICE OF METHOD
Estimation of emissions of N 2 O from caprolactam production can be tr eated as analogous to estimation of emissions of N 2 O from nitric acid production. Both produc tion processes involve an initial step of NH 3 oxidation which is the source of N 2 O 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 meth ods to national circumstances. Emissions can be estimated from continuous emissions monitoring (CEM) where emissions ar e directly measured at all times, periodic emissions monitoring that is undertaken over a period(s) that is refl ective of the usual 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 ou tput to derive emissi ons, or by multiplying a de fault emission factor by output. Methods are classified according to the ex tent of plant-level data that are available. Both Tier 2 and Tier 3 are require plant-level activity data. 

### Tier 1 method Emissions are estimated as follows:

E QUATION 3.9 N 2 O EMISSIONS FROM CAPROLACTAM PRODUCTION

– T IER 1 CP EF E O

N • = 2
Where:
E N2O = N 2 O emissions, kg
EF = N 2 O emission factor(default), kg N 2 O/tonne caprolactam produced CP = caprolactam production, tonnes When applying the Ti er 1 method it is good practice to assume that there is no abatement of N 2 O emissions and to use the highest default emission factor shown in Table 3.5. 

### Tier 2 method Information on emissions arising from caprolactam production and control tech nologies is limited. Where plantlevel information is not available, good practice provides default N 2 O generation factors as shown in Table 3.5. The default factors are based on N 2 O emissions from nitric acid plants because there is no information on caprolactam plants and the initial r eaction step of oxidation of ammoni a is similar for both processes. Good practice encourages the development of factor s specific to caprolactam plants. The number of caprolactam plants is relatively small (approximately 42 plan ts with around 19 plants using DSM (Stamicarbon) technology). It is unlikely that ther e are substantial va riations in the N 2 O generation factors between plants. Where default values are used to es timate emissions from caprolactam production, it is good practice to ascertain the extent to which plant emissions vary according to type and to use an appropriate N 2 O generation factor. The Tier 2 method uses plant-level production data di saggregated by technology type and default emission factors classified by technology type . Emissions are calculated as follows:Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.35 E QUATION 3.10 N 2 O EMISSIONS FROM CAPROLACTAM PRODUCTION

– T IER 2 

# ( ) 

# [ ] ∑ •

− • • = j

i j j i i O N ASUF DF CP EF E

, 2 1

Where:
E N2O = emissions of N 2 O, kg
EF i = N 2 O emission factor fo r technology type i , kg N 2 O/tonne caprolactam produced CP i = caprolactam production from technology type i , tonnes DF j = destruction factor for abatement technology type j , fraction ASUF j = abatement system utilisation fact or for abatement technology type j , fraction The basic equation for estimating N 2 O emissions includes additional term s that recognise current and the potential future use of N 2 O abatement technologies. The N 2 O destruction factor has to be multiplied by an abatement system utilisation factor in order to accoun t for any down-time of the em ission abatement equipment (i.e. time the equipment is not operating). Where plant-level informa tion is not available, good practice provides default N 2 O generation factors as shown in Table 3.5, Default Factors for Caprolactam Production, based on plant types classified by age. To achieve the highest accuracy, good practice is to apply Equation 3.10 at th e plant-level taking into account N 2 O generation and 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 leve l production data and pl ant-level emission factors obtained from direct measurement of emissions. These may be derive d from irregular sampling of emissions of N 2 O or periodic emissions monitoring of N 2 O undertaken over a period(s) that reflects th e 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 noted that most plants are unlikely to em ploy CEM due to the resource costs. Where CEM is employed, emissions can be estimated based on the sum of measured N 2 O emissions derived from the concentration of N 2 O 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 an d to assume that there is no abatement of N 2 O emissions. 

### Tier 2 method If plant-level factors ar e 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 valu es of data sets (as determined by expert analysis). The extent to which they re present a specific plant’s emission rate is unknown. This is es pecially true for caprolactam production where the value is based on high pr essure nitric acid plants. De fault factor in Table 3.5 should be used only in cases where plan t-specific measurements are not available. 

### Tier 3 method Plant measurements provide the most rigorous data for calculating net emissions (i.e., N 2 O generation and destruction factors). Monitoring N 2 O 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 system atic errors and to achieve the desired level of accuracy. 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 N 2 O, and sufficiently often otherwise to ensure that operating conditions are consta nt. In addition, plant opera tors should be consulted annually to determine the specific destruction technologies employ ed and confirm their use, since t echnologies may change over time. Precise measurement of the emissions rate and abatemen t efficiencies requires measurement of both the exitVolume 3: Industrial Processes and Product Use

3.36 2006 IPCC Guidelines for National Greenhouse Gas Inventories stream and the uncontrolled stream. Where measurem ent data are available only on the exit stream, good practice is to base emissions on these data. In this case, an y available estimates of ab atement efficiency should be provided only for information purpos es and not used to calculate emissions.

T ABLE 3.5 D EFAULT FACTOR FOR CAPROLACTAM PRODUCTION
Production Process N 2 O Emission Factor (kg N 2 O/tonne caprolactam) Uncertainty

Raschig 9.0 a ± 40%

aBased on high pressure plants for nitric acid production. Source: Default Factors for Nitric Acid Pr oduction. (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?

Is Caprolactam, Glyoxal and Glyoxylic Acid Production a key category 1

, and is this a significant subcategory? Are plant-specific activity data available on caprolactam,

glyoxal or glyoxylic acid production?

Yes No No

Collect data for the Tier 3 or Tier 2 method. Use plant specific-emissions data and activity data (irregular sampling

data, periodic monitoring data or continuous emissions monitoring) as basis for Tier 3 method.

Use plant-specific data on quantity of caprolactam, glyoxal or glyoxylic acid produced as basis for Tier 2 method.

Use national data on caprolactam, glyoxal or glyoxylic acid production

or national data on capacity, and default emission factors.
Box 1: Tier 1 Box 2: Tier 2 Box 3: Tier 3

Note: 1. See Volume 1 Chapter 4, Methodological Choice and Identification of Key Categori es (noting Section 4.1.2 on limited resource s), for discussion of key categories and use of decision trees. No Yes

YesChapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.37 

### CHOICE OF ACTIVITY DATA
It is good practice to compile production data at a level of detail th at 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 not available, information on production capacity can be used. It is good practice to multiply the total national production capacity by a capacity utilisat ion factor of 80 percen t ± 20 percent (i .e., a range of 60-100 percent). 

### Tier 2 method The Tier 2 method requires plant-le vel production data disaggregated by the age the plant. If additional information on technology type and abat ement technology is available, it is good practice to collect this information and disaggregate production data accord ing to the information obtained. That is, it is good practice to gather activity (produ ction) 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-leve l production data. Typical plant-level production data are accurate to ±2 percent due to the economic value of havi ng accurate information. 

### Tier 3 method The Tier 3 method require plant-le vel 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 collect activity (production) data at a leve l of detail consistent with that of any generation and destruction data. Although production is not used in th e estimation of emissions where the estimate is based on CEM, these data should be collected and reported to en sure 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 ac counting for all plants and emissions of all direct greenhouse gases. In addition to N 2 O, there may be non-combustion emissions of CO 2 , NO x , NMVOCs and SO 2 . In order to include emissions of the indirect greenhouse gases (NO x , NMVOCs and SO 2 ), see guidance provided in Chapter 7 of Volume 1: General Guidance and Reporti ng. Plant-level information w ill 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 SERIES
N 2 O emissions should be recalculated for all years whenev er emission calculation methods are changed (e.g., if the inventory compiler changes from the use of default valu es to actual values determined at the plant level). If plant-specific data are not available fo r 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 prev ious years, provided that plant operations have not changed substantially. Such a recalculation is required to ensure that any changes in emissions trends are real and not an artefact of changes in procedure. It is good practice to recalculate the time series according to the guidance provided in Volume 1, Chapter 5.


## 3.5.2.2 U NCERTAINTY ASSESSMENT

EMISSION 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 substa nces 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 caprolactam production have a relatively high level of uncertainty due to the limited information available. It is good practice to obtain uncertainty estima tes at the plant-level which should be lower than uncertainty valu es associated with default values. 

### ACTIVITY DATA UNCERTAINTIES Where activity data are obtain ed from plants, uncertainty estimates can be obtained from producers. Data that are obtained from national statistical agencies usually do not include uncertain ty estimates. It is good practice to consult with national statisti cal agencies to obtain information on any sampling errors. Where national statisticalVolume 3: Industrial Processes and Product Use

3.38 2006 IPCC Guidelines for National Greenhouse Gas Inventories agencies collect data from the population of nitric aci d production facilities, uncertainties in national statistics are not expected to differ from uncer tainties established from plant-level co nsultations. Where unc ertainty 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 OCUMENTATION QUALITY ASSURANCE/QUALITY CONTROL
It is good practice to conduct quality control checks as outlined in Volume 1, Ch apter 6. More ex tensive quality control checks and quality a ssurance 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 in Volume 1, Chapter 4. 

### Comparison of emissions estimates using different approaches If emissions are calculated using da ta from individual caprolactam plants (bottom-up approach), inventory compilers should compare th e estimate to emissions calculated using national production data (top-down approach). They should record the results and investigate any unexplained discrepancies. Since industrial N 2 O source categories are relatively small compar ed to other anthropogenic and natural sources, it is not feasible to compare emissions with measured trends in atmospheric N 2 O concentrations. 

### Plant-level data Inventory compilers should archive sufficient information to allow an independent revi ew of the time series of emissions beginning in the base year, and to explain tr ends in emissions when making historical comparisons. This is particularly important in cases where recalcu lations are necessary, for ex ample, when an inventory compiler changes from using default values to actual values de termined at the plant level. 

### Revision of direct emission measurements If plant-level N 2 O measurements are available, inventory co mpilers should confirm that internationally recognised, standard methods were us ed. If the measurement practices fail this criterion, then they should evaluate the use of these emissions data . In addition, they should reconsider the uncerta inty estimates in light of the QA/QC results. Inventory compilers should compare plant-based factors to the IPCC defaults to ensu re that the plant-specific factors are reasonable. They should explain and docum ent any differences between plant-specific factors and default factors, particularly any differences in plan t characteristics that might lead to these differences.



### REPORTING AND DOCUMENTATION
It is good practice to document and archive all in formation 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, destru ction efficiency, and utilisation;

• Any other assumptions. Plant operators should supply this information to the in ventory compiler for compilati on, and also archive the information at the site. Plant op erators should also log and arch ive the measurement frequencies and instrumental calibration re cords 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 theChapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.39 level of aggregation at which information can be reported while still protec ting confidentiality. Detailed information including instrumentation records s hould still be archived at the plant level. It is not practical to include all doc umentation in the national inventory report. However, the inventory should include summaries of methods used and references to sour ce data such that the repor ted emissions estimates are transparent and steps in their calculation may be retraced.


# 3.5.3 Glyoxal and glyoxylic acid production Glyoxal (ethanedial) (C 2 H 2 O 2 ) is produced from oxidation of acetaldehyde (ethanal) (C 2 H 4 O) with concentrated nitric acid (HNO 3 ). Glyoxal can also be produced from cataly tic oxidation of ethylene glycol (ethanediol) (CH 2 OHCH 2 OH). Glyoxal is used as a crosslinking agent fo r vinyl acetate/acrylic resi ns, disinfectant, gelatine hardening agent, textile fi nishing agent (permanent-pre ss cotton, rayon fabrics), we t-resistance additive (paper coatings) (Ashford, 1994; p.454). Glyoxylic acid is produced by nitric aci d oxidation of glyoxal. Glyoxylic acid is used for the production of synthetic aromas, agrochemicals and pharmaceu tical intermediates (B abusiaux, 2005; p.1). The basic reaction equation for the produ ction of glyoxal from acetaldehyde is:

2C 2 H 4 O (Acetaldehyde) + 2HNO 3 → 2C 2 H 2 O 2 (Glyoxal) + N 2 O + H 2 O The stoichiometric relationship in dicates that complete reaction will result in 0. 543 tonnes of N 2 O per tonne of glyoxal. Under commercial conditions, the yield of N 2 O 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 N 2 O with NO recovered as HNO 3 in the process. N 2 O arises in the production process through a secondary reaction where glyoxal is converted to oxalic acid (COOH) 2 . Default factors for glyoxal and glyoxylic acid producti on are shown in Table 3.6. Emissions can be estimated using the same approach as described in the foregoing for caprolactam. To use defa ult destruction factors, inventory compilers should verify that the abatement tech nology is installed at individual plants and operated throughout the year.

T ABLE 3.6 D EFAULT FACTORS FOR GLYOXAL AND GLYOXYLIC ACID PRODUCTION
Product N 2 O Generation Factor (tonnes N 2 O/tonne) N 2 O Destruction Rate (%) N 2 O Emission Factor (tonnes N 2 O/tonne) Uncertainty (%) Glyoxal 0.52 80 0.10 ± 10 Glyoxylic acid 0.10 80 0.02 ± 10 Source: Babusiaux (2005)Volume 3: Industrial Processes and Product Use

3.40 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

# 3.6 CARBIDE PRODUCTION

3.6.1 Introduction Greenhouse gas emissions are associ ated with production of silicon carb ide (SiC) and calcium carbide (CaC 2 ). The production of carbide can result in emissions of carbon dioxide (CO 2 ), methane (CH 4 ), carbon monoxide (CO) and sulphur dioxide (SO 2 ). Silicon carbide is a significant artificial abrasive. It is produc ed from silica sand or quartz and petroleum coke. Calcium carbide is used in the production of acetylen e, 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 carbo nate (limestone) and petroleum coke. Use of carbon-containing raw materials in the production processes result in emissions of CO 2 and CO. The presence of hydrogen-containing volatile compounds and su lphur (S) in the petroleum coke may cause formation and emission to the atmosphere of CH 4 and SO 2 . 

# 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):

SiO 2 + 2C → Si + 2CO Si + C → SiC The formula describing the overall reaction is give n below but in practice it does not proceed in the stoichiometric prop ortions indicated:

SiO 2 + 3C → SiC + 2CO (+ O 2 → 2CO 2 ) 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 CO 2 in excess oxygen and released to the atmosphere as a process by-product. The petroleum coke used in this process may contain volatile compound s, which will form methane. Some methane will escape to the atmosphere , particularly du ring start-up. 

### CO 2 

### FROM CALCIUM CARBIDE PRODUCTION Calcium carbide (CaC 2 ) is made by heating calcium carbonate (lim estone) and subsequently reducing CaO with carbon e.g., petroleum coke. Both steps lead to emissions of CO 2 . Around 67 percent of the carbon from petroleum coke will be contained in the product. The basic reactions are:

CaCO 3 → CaO + CO 2 CaO + 3C → CaC 2 + CO (+ 1⁄2 O 2 → CO 2 ) The CO gas will be used as an energy source in most plants.

B OX 3.4 D OUBLE COUNTING To avoid double counting, CO 2 emission from combusting CO gas generated in the process of CaC 2 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 the Energy Sectoras a non-energy use of petroleum coke.

The most important application of cal cium carbide is producing acetylene (C 2 H 2 ) by reacting CaC 2 with water. A substantial use of acetylene is weld ing applications. Acetylene is also used in chemical synthesis for theChapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.41 production of acetaldehyde, acetic acid, acetic anhydride, and as a feedstock to manufacture ‘acetylene black’, a form of carbon black. Frequently, acetylene is not produced within the same plant that produces CaC 2 and this needs to be taken into account when appl ying higher tier methods to estimating CO 2 emissions from CaC 2 use. Use of acetylene in chemical synthe sis and production of acetylene black results in carbon contained in the products reducing the total emissions of CO 2 that are related to CaC 2 use. Acetylene may be produced from partial oxidation of natural gas as well as from CaC 2 . The approach to accounting fo r acetylene in these uses is outlined in Section 3. 9 of this volume. Production and use of acetylene for welding applications is summarised by reaction:

CaC 2 + 2H 2 O → Ca(OH) 2 + C 2 H 2 (+ 2.5O 2 → 2CO 2 + H 2 O) Where acetylene is used in weldin g applications, emissions can be derived from the quantity of CaC 2 used in the production of this acetylene on the assu mption that the acetylene will be used in a relatively short period of time after production.

B OX 3.5 A LLOCATION OF EMISSIONS FROM CaO PRODUCTION CaO (lime) might be produced in-house or at a plant other than the carbide plant. In either case, the emissions from the CaO step should be reported as emissions from lime production (Section 2.3 of this 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 accordin g the extent of plant-level da ta 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 CaC 2 in acetylene production for weldi ng applications. The Tier 3 method is base d on plant-level data on petroleum coke input (including the carbon content f actor (CCF) and carbon oxid ation factor (COF) if av ailable; alternatively, country specific Energy Sector values may be used), use of CaC 2 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 CO 2 and CH 4 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 ca rbide used in the production of acetylene us ed in welding applications, and default emission factors. Where AD on petroleum coke consumption are used the CCF and COF of the petroleum coke can be obtained from Volume 2, Chapter 1 and the result must be mu ltiplied by 44/12 to convert C to CO 2 . The basic equation for estimating emissions is:

E QUATION 3.11 E MISSIONS FROM CARBIDE PRODUCTION EF AD E CO • = 2
Where:
E CO2 = emissions of CO 2 , tonnes AD = activity data on petroleum coke consumption or carbide production, tonnes raw material used or tonnes carbide produced EF = CO 2 emission factor. There are two options as follows: When carbide production is used as ac tivity data, EF shou ld be average CO 2 emissions per unit of output for carbide production, tonnes CO 2 /tonne carbide production. When petroleum coke consumption is used as activity data, EF should be CCF (carbon contentVolume 3: Industrial Processes and Product Use

3.42 2006 IPCC Guidelines for National Greenhouse Gas Inventories factor) multiplied by COF (carbon oxidation factor) multiplied by 44/1 2 and adjusted to account for the C contained in th e product, tonnes CO 2 /tonne material used Adjustment factor for SiC = 0.35 ⇒ Emission factor = 0.65 • CCF • COF • 44/12; Adjustment factor for CaC 2 = 0.67 ⇒ Emission factor = 0.33 • CCF • COF • 44/12. Equation 3.11 can also be used to estimate CH 4 emissions, where EF is the ap propriate emission factor for CH 4 . Estimation of emissions from CaC 2 needs to include emissions of CO 2 indirectly attributable to CaC 2 that is used in acetylene production. Equation 3.11 can be applied where AD is the amount of CaC 2 used and EF is the emission factor associated with this use. Under the Tier 1 method it is good practice to assume that all CaC 2 used in acetylene production gives rise to CO 2 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 CaC 2 , data on the use of CaC 2 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 CaC 2 at another location a nd the quantity of CaC 2 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 speci fic Energy Sector values for CCF and COF may be used. Plant-level data on the amount of C contained in the product are also required. In the case of CaC 2 , data on the use of CaC 2 for the production of acetylene us ed in welding applications are required, as are plant-level emission factor s. Where acetylene is produced from CaC 2 at another location and the quantity of CaC 2 used for this purpose is not known, it is good practice to document this fact . In addition, plantlevel emission factors for CH 4 need to be collected. Equation 3.11 can be applied to estimate emissions for each plant and total national emissions are the sum of these estimates. Production data are not used in the calculation but should be collected fo r reporting purposes. Where acetylene production data cannot be disaggregated by use, nati onal inventory compilers using the Tier 3 method are encouraged to account fo r any emissions at the point where they ar ise; for example, emissions from acetylene use in welding applications should be accounted for at the point of use of acetylene using a country specific emission factor. A similar approach should be followed for other uses of acetylene.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.43 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 input 1 ?

Is this a key category 2 ? Are plant-level carbide

production data available?

Yes No No

Collect data for the Tier 3 or Tier 2 method. Use the plant-specific coke consumption data including C content and percent oxidised, along with plant-specific CH 4 emission factor as basis for the Tier 3 method.

Calculate emissions using plant-leveldata on production of carbide and plantspecific emission factors. For the plants where plant-specific emission factors are not available, use default emission factors.

Use national aggregate input data, national production data or production capacity data

and default emission factors to calculate emissions.
Box 1: Tier 1 Box 2: Tier 2 Box 3: Tier 3

Note: 1. "Input data" means raw ma terial consumption data. 2. See Volume 1 Chapter 4, Me thodological Choice and Identifica tion of Key Categories (noting Section 4.1.2 on limited resource s), for discussion of key categories and use of decision trees. No Yes

Yes



## 3.6.2.2 C HOICE OF EMISSION FACTORS

Tier 1 method The Tier 1 method uses default values for CCF, COF an d C contained in the product where petroleum coke is used in the estimation. Alternatively, where carbide prod uction 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 CaC 2 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 excep t 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 CaC 2 used to produce acetylene for welding applications.Volume 3: Industrial Processes and Product Use

3.44 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### CO 2 

### from silicon carbide production More carbon is needed in the silicon carbide production pr ocess than calculated from a stoichiometric reaction. The excess carbon is oxidised du ring the process, little is left as ash (Raa ness, 1991). Typical default values for Norwegian plants for carbon content in coke are 97 percent and for carbon contained in product, 35 percent. This implies a typical emission factor of 2.3 tonnes CO 2 /tonne petroleum coke used (IPCC, 1997), or 2.62 tonnes CO 2 /tonne carbid e produced. 

### CH 4 f 

### rom silicon carbide production Measurements at Norwegian plants s uggest emission factors of 10.2 kg CH 4 /tonne petroleum coke or 11.6 kg CH 4 /tonne carbide produced (IPCC, 1997).

T ABLE 3.7 D EFAULT FACTORS FOR CO 2 AND CH 4 EMISSIONS FROM SILICON CARBIDE PRODUCTION
Process Emission Factor (tonnes CO 2 /tonne raw material used) Emission Factor (kg CH 4 /tonne raw

material used) Emission Factor (tonnes CO 2 /tonne carbide produced) Emission Factor (kg CH 4 /tonne carbide produced)
Silicon carbide production 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 CaCO 3 and is accounted for elsewhere. 1 750 kg lim estone (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 estimati ng emissions are included in Table 3.8.

T ABLE 3.8 E MISSION FACTORS FOR CO 2 EMISSION FROM CALCIUM CARBIDE PRODUCTION AND USE
Process Default Emission Factor (tonnes CO 2 /tonne raw material used) Default Emission Factor (tonnes CO 2 /tonne carbide produced)
Petroleum coke use 1.70 1.090 Use of product not relevant 1.100
Source: Revised 1996 IPCC National Greenhouse Gas Inventories, Vol.3, p.2.22 (IPCC, 1997)

The theoretical emission factor calculat ed from a stoichiometric reaction is lower for the petroleum coke step than 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 Norw egian plant. The emission factor for acetylene use is calculated from the actual (not stoichio metric) carbon content of carbide. The CO 2 emissions may be lowere d 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 na tional 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 pl ant-level data on carbide produced and the amount of CaC 2 used in the production of acet ylene for welding applications.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.45 

### Tier 3 method The Tier 3 method requires plant-leve l activity data for all variables in cluding the petroleum coke input and CaC 2 used to produce acetylene for welding applications. The Tier 2 methods require the collecti on of activity data from individual plants or companies. In Tier 1 the activity data provided by national statistics or by industri al and trade organizations a ssociated with carbide and petroleum 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 plan ts are generally known in eac h country. As a result, carbide production data may be available in national statistical databases, or could be collected, even if these data have not been published in national 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 that acetylene produced from CaC 2 is not necessarily produced at th e same plant that produces the CaC 2 . This needs to be accounted for when using the higher tier methods, with emissions originating from the use of CaC 2 accounted at the point where the emissions occur; for example, in the case of acetylene used in welding applications, where the acetylene is produ ced at a different location to the CaC 2 emissions should be accounted for at the point of production of th e acetylene on the assumption that it w ill be used in a short time after production. Application of the Tier 2 and 3 methods assumes the bo ttom-up (plant by plant) estimation of emissions and plant-level data collection. In countries where only a subs et of plants report data for the Tier 3 method or where there is a transition from Tier 2 to Ti er 3, it may not be possible to report emissions using Tier 3 for all facilities during the transition. Where data for th e Tier 3 method are not available for all plants, Tier 2 could be used for the remaining plants. Also, wh ere data for the Tier 2 method are reported by only a subset of plants or where there is a transition from Tier 1 to Ti er 2, it may be possible to determine the share of production represented by non-reporting plants and use this info rmation to estimate the remaining emissi ons using Tier 1 in order to ensure completeness during the transition period.


## 3.6.2.5 D EVELOPING A CONSISTENT TIME SERIES

It is good practice to estimate emissions from carbide production 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, it is good practice is to recalculate these gaps according to th e guidance provided in Volume 1, Chapter 5.


# 3.6.3 Uncertainty assessment

3.6.3.1 E MISSION FACTOR 

## U NCERTAINTIES
In general, the default CO 2 emission factors are relatively uncertain because industrial-scale carbide production processes differ from the stoichiometr y of theoretical chemical reactions. Th e uncertainty in the emission factors for CH 4 is due to the possible va riations in the hydrogen -containing volatile compou nds in the raw material (petroleum coke) that are used by different manufactur ers 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 plan t 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 an d limestone used and for ca rbide production data. Data that are obtained from national statistical agencies or from industrial and trade organizations usually do not include uncertainty estimates. It is good practice to consult with national sta tistical agencies to obtain information on any sampling errors. Where national statistic agencies co llect carbide production data from production facilities, uncertainties in national statistics are not expected to differ from uncertainties estimatedVolume 3: Industrial Processes and Product Use

3.46 2006 IPCC Guidelines for National Greenhouse Gas Inventories from plant-level consultations. Where un certainty values are not available fr om other sources, a default value of ± 5 percent can be used.


# 3.6.4 Quality Assurance/Quality Control (QA/QC), Reporting and Documentation

3.6.4.1 Q UALITY 

## A SSURANCE 

## /Q UALITY 

## C ONTROL

It is good practice to conduct quality control checks as outlined in Volume 1, Chapte r 6, and an expert review of the emission estimates. More extensive quality cont rol 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, sp ecific procedures of relevan ce to this source category are outlined below. 

### Comparison of emission estim ates using different approaches If the Tier 2 (plant-specific) method is used, then i nventory compilers should compare the emission estimates to the estimates calculated using national level activity data(Tier 1). The inventory compilers are also encouraged to compare the emission estimates calculated usin g different modifications of the same methods. The results of such compar ison 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) sh ould 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 pl ants to establish whether they reflect errors, different measurement techniques, or re sult from real differences in raw materials, operational conditions or technology. Inventory compilers should ensure that activity data and emission factors are developed in accordance with internationally recognized and proven measurement me thods. If any emission measurements from individual plants are collected inventory compilers should ensure that the measurements were made according to the recognised national or international standards. If the measur ement practices fall this crite rion, then the use of this emission factors and activity data should be carefully evaluated, uncertainty estimations reconsidered and qualifications documented. 

### Expert review Inventory compilers are encouraged to include key industri al and trade organizations as sociated with carbide and petroleum 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 in formation required to produce the national emissions inventory estimates as outlined in Volume 1, Section 6.11. Recal culation of previous years emissions also should be documented and archived.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.47 

# 3.7 TITANIUM DIOXIDE PRODUCTION

3.7.1 Introduction
Titanium dioxide (TiO 2 ) is one of the most commonly used white pigments. The main use is in paint manufacture followed by paper, plastics, rubber, cerami cs, fabrics, floor covering, printing ink, and other miscellaneous uses (Austin, 1984; Lowenheim and Moran, 1975). Given production of around 4 million tonnes of TiO 2 , and the substantial use of the ch loride route, carbon dioxide (CO 2 ) emissions are likely to be significant and need to be accounted for in greenho use gas inventories. Global production by the chloride route has increase approximately eight fold since 1970 whilst sulphate route production has b een relatively stable (Kirk-Othmer, 1999; p. 2017). Note th at in the discussion, titanium dioxide products ar e referred to gene rically as titanium dioxide unless there is a need to make a distinction between the prod ucts. The discussion applies to titanium slag, synthetic rutile (>90 percent TiO 2 ) and rutile TiO 2 . 

# 3.7.2 Methodological issues

TiO 2 is produced as anatase TiO 2 and rutile TiO 2 . The forms of TiO 2 differ in terms of the crystalline structure and purity of the final product. Anatase TiO 2 may be produced by digesting ilmenite (essentially ferrous titanate (FeO.TiO 2 )) with sulphuric acid, th e sulphate process, or from titanium slag. Basic reaction equations for the acid digestion route are (Lowenheim and Moran, 1975; p. 814):

FeTiO 3 + 2H 2 SO 4 → FeSO 4 + TiO.SO 4 + 2H 2 O TiO.SO 4 + 2H 2 O → TiO 2 .H 2 O + H 2 SO 4 TiO 2 .H 2 O + heat → TiO 2 + H 2 O The sulphate route process does not give rise to pro cess greenhouse gas emissions that are of significance. There are three processes that are used in the production of TiO 2 that lead to process greenhouse gas emissions: titanium slag production in electric fu rnaces, synthetic rutile production us ing the Becher process, and rutile TiO 2 production via the chloride route. Titanium slag used for production of anatase TiO 2 is produced from electric fu rnace smelting of ilmenite. Where titanium slag is used the acid reduction step is not requ ired as the electric furnace smelting reduces the ferric iron contained as an impurity in ilmenite. Rutile TiO 2 may be produced by further processing of the anatase TiO 2 . Process emissions arise from the reductant used in the process. Production of synthetic rutile can give rise to CO 2 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, an d in the process separates out the titanium dioxide as synthetic rutile of about 91 to 93 percent pur ity (Chemlink, 1997). Black coal is used as the reductant and the CO 2 emissions arising should be treat ed as industrial process emissions. The main route for the production of rutile TiO 2 is the chloride route. Rutile TiO 2 is produced through the carbothermal chlorination of rutile ore or synthetic rutile to produ ce titanium tetrachloride (TiCl 4 ) and oxidation of the TiCl 4 vapours to TiO 2 according to the following reactions (Kirk-Othmer, 1999; p.2017):

2TiO 2 + 4Cl 2 + 3C → 2TiCl 4 + 2CO + CO 2 TiCl 4 + O 2 → TiO 2 + 2Cl 2 Based on stoichiometry and assuming comp lete conversion of the input C to CO 2 through further conversion of CO in excess air, the CO 2 emission factor cannot be less than 0.826 tonnes of CO 2 per tonne of TiO 2 (based on 1.5 moles of CO 2 per mole of TiO 2 ).


## 3.7.2.1 C HOICE OF METHOD
The general approach for calculating CO 2 emissions from titanium dioxide pro duction is the same irrespective of the product because the emissions are based on the quantity of reducing ag ent or carbothermal input. The choice of a good practice method depends on national circumstances as s hown in the decision tree in Figure 3.6. Process emissions of carbon dioxide in TiO 2 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 petrol eum coke oxidisation in the pr ocess of producing rutile TiO 2 via the chloride route. Methods are classified according to the extent of plant-level data that are available.Volume 3: Industrial Processes and Product Use

3.48 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### TIER 1 METHOD
The Tier 1 method uses a default em ission factor per unit of output multip lied by activity data obtained from national statistics. The basi c equation for estimating CO 2 emissions is:

E QUATION 3.12 CO 2 EMISSIONS FROM TITANIUM SLAG , SYNTHETIC RUTILE AND RUTILE T I O 2 PRODUCTION

– T IER 1 

## ( ) ∑ • = i i i CO EF AD E 2

Where:
E CO2 = emissions of CO 2 , tonnes AD i = production of titanium slag, synthetic rutile or rutile TiO 2 (product i ), tonnes
EF i = CO 2 emissions per un it of production of titanium slag , synthetic rutile or rutile TiO 2 (product i ), tonnes CO 2 /tonne product 

### TIER 2 METHOD
Emissions can be calculated from the consumption of the reducing agent fo r electrode carbon (titanium slag), and coal (synthetic rutile) in the Be cher process, and the car bothermal input (petroleum coke) for rutile TiO 2 from the chloride rout process. Th e Tier 2 method uses plant-level data on the quantities of reducing agent and carbothermal input to deri ve emissions as follows:

E QUATION 3.13 CO 2 EMISSIONS FROM TITANIUM SLAG , SYNTHETIC RUTILE AND RUTILE T I O 2 PRODUCTION

– T IER 2 

## ( ) ∑ • • • = i i i i CO COF CCF AD E 12 44 2

Where:
E CO2 = emissions of CO 2 , kg
AD i = amount of reducing agent or carbothermal input i , GJ CCF i = carbon content factor of reducing agent or carbothermal input i , kg C/GJ COF i = 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 informa tion is not available, good practice provides default CO 2 emission factors for synthetic rutile and rutile TiO 2 as shown in Table 3.9. A default factor for titanium slag is not available because of the small number of plants.

B OX 3.6 D OUBLE COUNTING In order to avoid double counting, the quantities of electrode carbon, coal used as a reductant, and petroleum coke used in the chlori de route process, must be subtr acted from the quantity reported under energy and non-energy use in the Energy Sector

.


## 3.7.2.2 C HOICE OF EMISSION FACTORS

TIER 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 dete rmined 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, and should be used only in cases where plant-specific data are not available. The default factors are based onChapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.49 estimates of reductant or carbothermal input per unit of output assuming complete conversion of the C content to CO 2 . 

### TIER 2 METHOD Plant-level data provides the most rigorous data for calculating CO 2 emissions from titanium dioxide production. For the Tier 3 method, C content of the reductant an d carbothermal inputs along with the proportion of C oxidised are the key emission factor vari ables for deriving the quantity of CO 2 emitted.

T ABLE 3.9 D EFAULT FACTORS FOR TITANIUM DIOXIDE PRODUCTION ( TONNES CO 2 PER TONNE PRODUCT ) Product Emission factor and respective uncertainty (tonnes CO 2 /tonne product) Titanium slag 1 Not available Synthetic rutile 2 1.43 ( ± 10%) Rutile titanium dioxide (chloride route) 3 1.34 ( ± 15%)
Source:

1 A default emission factor is not available because there ar e 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 specific estimates of emissions in their na tional greenhouse gas inventories.

2 Derived from data provi ded 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?

Are national aggregate data on production of titanium slag,

synthetic rutile or rutile TiO 2 available? Is this a key category 1 ?

Yes Yes No

Collect data for the Tier 2 method. Use the plant-level data on the quantities of reducing agent and carbothermal input, and carbon content and carbon oxidation factors.

Calculate emis sions using national aggregate data on production of titanium slag, synthetic rutile or rutile TiO 2 and default emission factors.
Box 1: Tier 1 Box 2: Tier 2

Note: 1. See Volume 1 Chapter 4, Methodological Choice and Identification of Key Categori es (noting Section 4.1.2 on limited resource s), for discussion of key categories and use of decision trees. No Yes

No

Gather production data or use production capacity data.Volume 3: Industrial Processes and Product Use

3.50 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

## 3.7.2.3 C HOICE OF ACTIVITY DATA

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

### TIER 1 METHOD The Tier 1 method requires data on national production of titanium sl ag, synthetic rutile and rutile TiO 2 . If national-level activity data are not available, informa tion 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 by a 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 to tal reductant use, total carbon electrode consumption, and total carbothermal input. It is good practice to also collect data on total titanium slag production, total synthetic rutile production, and total rutile TiO 2 production. Collection of production data enables comparisons of inputs per unit of outputs over time and provides a sound basis for ensuring time series consistency. 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 accurat e to ±2 percent due to the economic value of having accurate information. If plant-level data are not available, nationally co mpiled production data may be used.


## 3.7.2.4 C OMPLETENESS
Complete coverage for titanium dioxide production re quires accounting for all em issions from all sources including titanium slag, synthetic rutile and rutile TiO 2 . CO 2 emissions are the main process emissions. In order to include emissions of NO x , CO and SO 2 from this source category, see guidance provided in Chapter 7 of Volume 1: General Guidance and Reporting.


## 3.7.2.5 D EVELOPING A CONSISTENT TIME SERIES

CO 2 emissions should be recalculated for all years whenev er emission calculation methods are changed (e.g., if the inventory compiler changes from the use of default valu es 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, it will be necessary to consider how curren t 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. R ecalculation is required to ensure that any changes in emissions trends are real and not an arte fact of changes in procedure. It is good practice to recalculate the time series according to the guidance pr ovided in Volume 1, Chapter 5.


# 3.7.3 Uncertainty assessment

3.7.3.1 E MISSION FACTOR UNCERTAINTIES

Uncertainties for the default values are es timates based on expert judgement. It is good practice to obtain uncertainty estimates at the plant leve l which should be lower than uncertain ty 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 prod ucers. This will include uncertainty estimates for reduct ant 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 with national statistical agencies to obtain information on any sampling errors. Where national statistical agencies collect data from the popul ation of titanium dioxi de production facilities, uncertainties in national statistics are not expected to differ from uncertainties established from plant-level consultations. Wh ere uncertainty values are not available from other sources, a default value of ± 5 percent can be used.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.51 

# 3.7.4 Quality Assurance/Quality Control (QA/QC), Reporting and Documentation

3.7.4.1 Q UALITY 

## A SSURANCE 

## /Q UALITY 

## C ONTROL

It is good practice to conduct quality control checks as outlined in Volume 1, Ch apter 6. More ex tensive 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 in Volume 1, Chapter 4. 

### Comparison of emission factors Inventory compilers should check if the estimated emission factors ar e 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 pro cess chemistry. For example, the CO 2 generation rate for rutile TiO 2 from the chloride route process should not be less than 0.826 tonnes of CO 2 per tonne of rutile TiO 2 produced. If the emission factors are outside of the estimated ranges, it is good practice to assess and document the plant-specific conditions that account for the differences. If emission measurements from individual plants are co llected, inventory compilers should ensure that the measurements were made according to recognised national or international standards. QC procedures in use at the site should be directly referenc ed and included in the QC plan. If the measurement practices were not consistent with QC sta ndards, 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 in formation required to produce the national emissions inventory estimates as outlined in Volume 1, Se ction 6.11. It is not practical to in clude 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 tr ansparent and steps in their calculation may be retraced. 

### Plant-specific data check The following plant-specific data is required for adequate a uditing of emissions estimates:

• Activity data comprising electrode ca rbon consumption (titanium slag), coal reductant use (synthetic rutile), carbothermal in put (rutile TiO 2 ), titanium slag produc tion, synthetic rutile production, and rutile TiO 2 production;

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

• Calculations and estimation method;

• List of assumptions;

• Documentation of any plant-specific measur ement method, and measurement results. In general production and process data are considered prop rietary by operators, especi ally where there are only a small number of plants w ithin a country. It is good practice to apply appropriate techniques, including aggregation of data, to ensure protection of co nfidential data.Volume 3: Industrial Processes and Product Use

3.52 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

# 3.8 SODA ASH PRODUCTION

3.8.1 Introduction
Soda ash (sodium carbonate, Na 2 CO 3 ) is a white crystallin e solid that is used as a ra w material in a large number of industries including glass manufacture, soap and de tergents, pulp and paper production and water treatment. Carbon dioxide (CO 2 ) is emitted from the use of soda ash and thes e emissions are accoun ted for as a source under the relevant using industry as discussed in Volume 3, Chapter 2. CO 2 is also emitted during production with the quantity emitted depende nt on the industrial process used to manufacture soda ash. Emissions of CO 2 from the production of soda ash vary substantially with the manufacturing process. Four different processes may be used commercially to produce soda ash. Three of these processes, monohydrate, sodium sesquicarbonate (trona) and direct carbonation, ar e referred to as natural processes. The fourth, the Solvay process, is classified as a synthetic process. Calcium carbonate (limestone) is used as a source of CO 2 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 is made) is calcined in a rotary kiln and chemically transf ormed into a crude soda ash. Carbon dioxide and water are generated as by-products of this process. Carbon di oxide emissions can be estimated based on the following chemical reaction:

2Na 2 CO 3 .NaHCO 3 .2H 2 O (Trona) → 3Na 2 CO 3 (Soda Ash) + 5H 2 O + CO 2



## 3.8.2.1 M ETHODOLOGICAL ISSUES

CHOICE OF METHOD The choice of method will depend on national circumstance s. 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 is good practice to use the input-based method where data are available. Methods are classified according to the extent of plant-level data that are av ailable. The Tier 1 method is based on default values and national statistics, and the Tier 2 me thod is based on complete plant-level input or output data and plant specific emission factors. If th ere is monitoring and direct measurement of CO 2 emissions this would be equivalent to a Tier 3 method. 

### Tier 1 method Natural soda ash production emits CO 2 through the thermal decomposition (calcination) of the Trona (Na 2 CO 3 .NaHCO 3 .2H 2 O) 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:

E QUATION 3.14 CO 2 EMISSIONS FROM NATURAL SODA ASH PRODUCTION

– T IER 1 EF AD E CO • = 2
Where:
E CO2 = emissions of CO 2 , tonnes AD = quantity of Trona used or soda ash produced, t onnes of Trona used or tonnes natural soda ash produced EF = emission factor per unit of Trona input or natural soda ash output, tonnes CO 2 /tonne of Trona or tonnes CO 2 /tonne natural soda ash produced: EF Trona= 0.097 tonnes CO 2 /tonne of Trona, EF Soda Ash = 0.138 tonnes CO 2 /tonnes natural soda ash produced.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.53 It is good practice to assess the available national sta tistics for completeness. The choice of good practice methods depends on national circumstances, as shown in Figure 3.7: Decision Tree for Estimation of CO 2 Emissions from Natural Soda Ash Production. 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. 

### 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 CO 2 emissions for each plant can be calculated using either variation of Equation 3.14. For plants where plant-specific em ission factors are not available, the default emission factors provided in Equation 3.14 can be used. Total CO 2 emissions are the sum of the emissions from all plants. 

### Tier 3 method The Tier 3 method uses plant-level CO 2 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 CO 2 emissions data obtainable from direct measurement?

Are plant-level data on Trona consumption available?

Are plant-level data on natural soda ash production available? No

No No Collect data for the Tier 3 or 2 method. Use plant-level CO 2 emissions data obtained from direct measurement.

Calculate emissions using

plant-level natural soda ash production data and plant-specific emission

factors, if available.
Box 2: Tier 2 Box 4: Tier 3

Note: 1. See Volume 1 Chapter 4, Me thodological Choice and Identifica tion of Key Categories (noting Section 4.1.2 on limited resource s), for discussion of key categories and use of decision trees. Yes

Yes

No Is this a key category 1 ? Calculate emissions using plant-level Trona consumption data, using plant-specific emission

factor if available.

Calculate emissions using national aggregate data of Trona consumption or natural soda ash production and default emission factor. In case

the national aggregate data are not available, estimate it by using production capacity data. Box 3: Tier 2

Box 1: Tier 1 Yes

YesVolume 3: Industrial Processes and Product Use

3.54 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### CHOICE OF EMISSION FACTORS Tier 1 method The Tier method uses the default emission factors presen ted in Equation 3.14. The default emission factors are derived from the stoichiometric ratio between soda as h produced and purified sodium sesquicarbonate obtained from Trona. They are based on the main natural productio n 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 shou ld 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 accoun t 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 th at allows the use of th e Tier 2 method. When applying the methods it is essential th at a clear distinction is made betwee n the products to avoid multiplying the incorrect 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. If national-level activity data are not available, informa tion 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 by a capacity utilisation factor of 80 percent ± 10 percent (i.e ., a range of 70-90 percent). 

### Tier 2 method Activity data should be coll ected at the plant-level to use the Tier 2 method. The most important data are the amount 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 good practice to collect and report these data to enable compar isons of inputs per unit of outputs over time and provide a sound basis for ensuring time series consistency. 

### COMPLETENESS Completeness of the activity data (e.g., Tr ona utilisation) is a crucial attribute of good practice . Therefore, it is good practice to assess the available national st atistics 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 consider ed. If data at the plant-le vel are not available, it is good practice to use production capacity data along with national statistics to estimate the emissions for completeness purposes. 

### DEVELOPING A CONSISTENT TIME SERIES
It is good practice to calculate emissions from soda ash using the sa me method for every year in the time series. Where data are unavailable to support a more rigo rous method for all years in the time series, good practice is to recalculate these gaps according to the gui dance provided in Volume 1, Chapter 5.


## 3.8.2.2 U NCERTAINTY 

## A SSESSMENT

EMISSION FACTOR UNCERTAINTIES
The stoichiometric ratio is an ex act number and assuming 100 percent purity of the input or output, the uncertainty of the default emi ssion factor is negligible. However, the de fault factors do not ta ke into account the fractional 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 good practice 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 prod ucers. This will include uncertainty estimates for Trona used and natural soda ash used. Data that are obtained from national statistical agencies usually do not in clude uncertainty estimates. It is good practice to consult with national statistical agencies to obta in information on any sampli ng errors. Where national statistical agencies collect dataChapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.55 from the population of soda ash production facilities, uncertainties in natio nal statistics are not expected to differ from uncertainties established from plant-level consulta tions. Where uncertainty values are not available from other 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 OCUMENTATION QUALITY ASSURANCE/QUALITY CONTROL
It is good practice to conduct quality control checks as outlined in Volume 1, Chapte r 6, and an expert review of the emissions estimates. Additional qu ality 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 this source category. Inventory compilers are encouraged to use higher tier QA/QC for key categories as identified in Volume 1, Chapter 4. 

### Comparison of the emissions esti mates using different approaches If the bottom-up approach is used, then inventory comp ilers should compare the em issions estimates to the estimate calculated using the top-do wn approach. The results of such comparisons should be recorded for internal documentation, including e xplanations for any discrepancies. 

### REPORTING AND DOCUMENTATION
It is good practice to document and archive all in formation required to produce the national emissions inventory estimates as outlined in Volume1, Sec tion 6.11. It is not practical to in clude all documentati on in the national inventory report. However, the inventory should include summaries of methods used and references to data sources, and all the information need ed to reproduce the estimate. Besides the emissions, good practice is to report the activity data used in the calculation (Trona utilisation) and the 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 to recalculate the entire time series. If confidentiality is an issue for any ty pe of production, estimates may be aggregated to the minimum extent po ssible to maintain confidentiality. In addition, inventory compilers sh ould 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, lime stone, metallurgical coke and ammonia are the raw materials used in a series of reactions leading to the production of soda ash. Ammonia, however, is recycled and only a small amount is lost. The series of reactions involved in the Solvay process may be described as follows:

CaCO 3 + heat → CaO + CO 2

CaO + H 2 O → Ca(OH) 2 2NaCl + 2H 2 O + 2NH 3 + 2CO 2 → 2NaHCO 3 + 2NH 4 Cl 2NaHCO 3 + heat → Na 2 CO 3 + CO 2 + H 2 O Ca(OH) 2 + 2NH 4 Cl → CaCl 2 + 2NH 3 + 2H 2 O The net overall reaction may be summarised as:

CaCO 3 + 2NaCl → Na 2 CO 3 + CaCl 2 From the series of reactions presented above, CO 2 is generated in two pyrolysis processes. The CO 2 generated is captured, compressed and directed to Solvay precipitati ng towers for consumption in a mixture of brine (aqueous NaCl) and ammonia. Although CO 2 is generated as a by-product, the CO 2 is recovered and recycled for use in the carbonation stage and in theory the process is neutral, i.e., CO 2 generation equals uptake. In practice, some CO 2 is emitted to the atmosphere during production by the Solvay process because more CO 2 is produced than is stoichiometr ically required. The excess CO 2 arises from calcining the limestone with metallurgical grade coke . The limestone is combined w ith the coke at approximately 7 percent of limestone by weight.Volume 3: Industrial Processes and Product Use

3.56 2006 IPCC Guidelines for National Greenhouse Gas Inventories The estimation of the CO 2 emissions from a stand alone soda ash plant should be based on an overall balance of CO 2 around the whole chemical process. For inventory purposes, a simplified version of the balance may be used assuming that the CO 2 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.

B OX 3.7 D OUBLE COUNTING In order to avoid double counting, CO 2 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 of coke.



## 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 metallu rgical grade coke in th e Solvay process to the Energy Sector means that a methodology for estimating these emissions is not provided in the Industrial Processes and Product Use Sector . However, data on soda ash production from the Solvay process should be collected and collated to ensure that all data on so da 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 chec ks 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 in formation required to produce the national emissions inventory estimates as outlined in Volume1, Sec tion 6.11. It is not practical to in clude all documentati on in the national inventory report. However, the inventory should include summaries of methods used and references to data sources, and all the information need ed to reproduce the estimate.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.57 

# 3.9 PETROCHEMICAL AND CARBON BLACK PRODUCTION

3.9.1 Introduction The petrochemical industry uses fossil fuels (e.g., natura l 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 in detail because their global productio n 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 specific guidance is not provided (e.g., styrene production). This section also provides guidance for production of carbon black. Carbon black is not considered to be a petrochemical; however, the carbon black production process uses petrochemical feedstocks. Emissions from carbon 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 indust ry, primary fossil fuels (natur al 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 feedstoc ks should be allocated to the source category in the IPPU Sector. However, where the fuel s are not used within the source cat egory but are transferred out of the process for combustion elsewhere (e.g., for district heating purposes) the emissions should be reported in the appropriate Energy Sector source cat egory. 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 this volume. 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, and coal,) and also secondary fuels (such as industrial process off gases) for energy production. It is important to investigate 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., natural gas, ethane, propane) feedstock consumption may be reported in national energy statistics. Should carbon dioxide (CO 2 ) capture technology be installed and used at a plant, it is good practice to deduct the CO 2 captured in a higher tier emissions calculation. The default assumption is that there is no CO 2 capture and storage (CCS) taking place. Any me thodology taking into account CO 2 capture should consider that CO 2 emissions captured in the process may be both combustion and process-related. In cases where combustion and process emissions are to be reported separately, inventory compilers should ensure that the same quantities of CO 2 are not double counted. In thes e cases the total amount of CO 2 captured should preferably be reported in the corresponding energy combustion and IPPU source categories in proportion to the amounts of CO 2 generated in these source categories. Fo r additional information on CO 2 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 CO 2 captured elsewhere as a feedstock, and CO 2 may also be captured from petrochemical processes. This may create potential double counting issues. For example, some methanol plants may utilise by-product CO 2 captured from other industrial processes as a feedstock for methanol production. To avoid double counting the CO 2 captured should not be reported as CO 2 emissions from the process from which the CO 2 is captured.

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

production.Volume 3: Industrial Processes and Product Use

3. 58 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### METHANOL Worldwide almost all methanol is made by way of steam reforming of natural gas. The steam reforming and shift reaction produce ‘synthesis gas’ comprised of CO 2 , carbon monoxide (CO), and hydrogen (H 2 ). The natural gas to methanol production process produces methanol and by-product CO 2 , CO, and H 2 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 a feedstock 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.

B OX 3.8 M ETHANOL PROCESS DESCRIPTIONS Conventional 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 an d a secondary reformer unit) and methanol synthesis. The overall equations for the Conventional Reforming Process are:

The surplus hydrogen from this process and methanol process purge gas containing methane (CH 4 ) 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 CO 2 captured from other 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:

The Combined Reforming Process produces a synthesis gas that contains a more balanced ratio of hydrogen to carbon monoxide (CO) and CO 2 than does the Conventional Reforming Process, and does not produce a hydrogen gas stream for energy recovery. The Combined Reforming Process produces a purge gas containing CH 4 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. Methanol Steam Reforming Reaction CH 4 + 1⁄2 O 2 → CO + 2 H 2 → CH 3 OH Feedstock Oxidation Reaction CH 4 + O 2 → CO 2 + 2 H 2 Reforming/Shift Reaction 2 CH 4 + 3 H 2 O → CO + CO 2 + 7 H 2 Methanol Production CO + CO 2 + 7 H 2 → 2 CH 3 OH + 2 H 2 + H 2 O Steam Reforming CH 4 + H 2 O → CO + 3 H 2 C n H m + nH 2 O → nCO + (m/2 + n) H 2 Shift Reaction CO + H 2 O → CO 2 + H 2 Methanol Production CO + 2 H 2 → CH 3 OH CO 2 + 3 H 2 → CH 3 OH + H 2 OChapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.59 B OX 3.9 E THYLENE PROCESS DESCRIPTION Steam Cracking The fundamental chemical equation for ethylene production is as follows:

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 from steam crackers or from fluid catalytic cracking un its at petroleum refineries. Steam crackers using naphtha feedstock are the largest source of propyl ene. There are other process technologies that are used 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 MONOMER Worldwide 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 com pound ‘dichloroethylene,’ also referred to as 1, 2- dichloroethene, is a different compound.

B OX 3.10 E THYLENE DICHLORIDE AND VINYL CHLORI DE 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 with hydrochloric acid and oxygen to produce ethylene dichloride and water. The ethylene dichloride is then cracked to produce vinyl chloride monomer and hydrochloric acid. The oxychlorination process produces a process off gas containing by-product CO 2 produced from the direct oxidation of the ethylene feedstock. The fundamental chemical equatio ns for the direct chlorination and oxychlorination processes are as follows:

Direct chlorination C 2 H 4 + Cl 2 → C 2 H 4 Cl 2 Oxychlorination reaction C 2 H 4 + 1⁄2 O 2 + 2 HCl
→ C 2 H 4 Cl 2 + H 2 O [C 2 H 4 + 3 O 2 → 2 CO 2 + 2 H 2 O] Ethylene dichloride>vinyl chloride 2 C 2 H 4 Cl 2 → 2 CH 2 CHCl + 2 HCl Ethane Dehydrogenation to Ethylene C 2 H 6 → C 2 H 4 + H 2Volume 3: Industrial Processes and Product Use

3. 60 2006 IPCC Guidelines for National Greenhouse Gas Inventories B OX 3.10 ( CONTINUATION ) E THYLENE DICHLORIDE AND VINYL CHLORI DE 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 hydrogen chloride. The oxychlorination process provides a sink for the hydrogen chloride. Therefore, ethylene dichloride/vinyl chloride monomer produ ction 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 CO 2 from the direct oxidation of the ethylene feedstock. The fundamental chemical equatio ns for the ‘balanced process’ for producing vinyl chloride monomer from ethylene are as follows:

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 CO 2 (by direct oxidation in the oxychlorination process) or to other chlorinated hydrocarbons (in either 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 CO 2 in a thermal incineration process or a catalytic incineration process. Most ethylene dichloride/vinyl chloride monomer plants recover energy from the incinerator off gases and process off gases.



### ETHYLENE OXIDE Ethylene oxide (C 2 H 4 O) is manufactured by reacting ethylene w ith oxygen over a catalyst. The by-product CO 2 from the direct oxidation of the ethylene feedstock is removed from the process vent stream using a recycled carbonate solution, and the recovered CO 2 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 is provided in an Annex to Section 3.9 (Annex 3.9A). A process description for ethylene oxide production is provided in Box 3.11 below.

B OX 3.11 E THYLENE OXIDE PROCESS DESCRIPTION The fundamental chemical equations for the production of ethylene oxide from ethylene and the production of monoethylene glycol are as follows:

The ratio of the ethylene oxide reaction and the by-product reaction defines the selectivity of the ethylene oxide process, in terms of tonnes of ethylene consumed per tonne of ethylene oxide produced. The combined ethylene oxide reaction and by-product CO 2 reaction is exothermic and generates heat, which is recovered to produce st eam 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 CO 2 and other by-products produced from the process and the amount of steam produced from the process is dependent upon the selectivity of the process. Ethylene oxide is used as a feedstock in the manufacture of glycols, glycol ethers, alcohols, and amines. Worldwide approximately 70 percent of ethylene oxide produced is used in the manufacture of glycols, including monoethylene glycol. Ethylene Oxide Reaction C 2 H 4 + 1⁄2 O 2 → C 2 H 4 O Feedstock Oxidation Reaction C 2 H 4 + 3 O 2 → 2 CO 2 + 2 H 2 O Monoethylene Glycol Production C 2 H 4 O + H 2 O → HO- C 2 H 4 - OH Ethylene Dichloride-Vinyl Chloride Monomer Reaction 2 C 2 H 4 + Cl 2 + 1⁄2 O 2 → 2 CH 2 CHCl + H 2 O Feedstock Oxidation Reaction [C 2 H 4 + 3 O 2 → 2 CO 2 + 2 H 2 O]Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.61 

### ACRYLONTRILE Worldwide more than 90 percent of acrylonitrile (vinyl cyanide) is made by way of direct ammoxidation of propylene with ammonia (NH 3 ) 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 (B P) and other manufacturers. (DOE, 2000) However, process data were not readily available for production of acrylonitrile from propane feedstocks. Therefore no emission 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.

B OX 3.12 A CRYLONITRILE PROCESS DESCRIPTION SOHIO Process The SOHIO process involves a fluidized bed reactio n of chemical-grade pr opylene, ammonia, and oxygen over a catalyst. The catalyst is a mixture of heavy metal oxides (including bismuth and molybdenum). The process produces acrylonitrile as its primary product and acetonitrile (methyl cyanide) and hydrogen cyanide (H CN) 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 CO 2 , CO, and water from the direct oxidation of the propylene feedstock, and produces other hydrocarbons from side reactions in the ammoxidation process. The acetonitrile and hydrogen cyanid e are separated from the acrylo nitrile by absorption, and the hydrogen 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 th e acetonitrile is burned for energy recovery or flared. The off gas from the main absorber vent containing CO 2 , 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 - acr ylonitrile absorption separations process may also be burned for energy recovery or recycled. Acrylonitrile and other non-methane hydrocarbons ar e also released from miscellaneou s 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:

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 to acrylonitrile. On the order of 85 percent of the propylene feedstock is converted to either the primary product acrylonitrile or secondary prod ucts acetonitrile or hydrogen cyanide. The remainder of the propylene feedstock is either converted directly to CO 2 by direct oxidation of the feedstock in the ammoxidation process or converted to other hydrocarbons through side reactions in 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 desc riptions for carbon black production are provided in Box 3.13 below. Acrylonitrile Reaction CH 2 =CHCH 3 + 1.5 O 2 + NH 3 → CH 2 =CHCN + 3 H 2 O Hydrogen Cyanide Reaction CH 2 =CHCH 3 + 3 O 2 + 3 NH 3 → 3 HCN + 6 H 2 O

Acetonitrile Reaction CH 2 =CHCH 3 + 1.5 O 2 + 1.5 NH 3 → 1.5 CH 3 CN + 3 H 2 O Feedstock Oxidation C 3 H 6 + 4.5 O 2 → 3 CO 2 + 3 H 2 O C 3 H 6 + 3 O 2 → 3 CO + 3 H 2 OVolume 3: Industrial Processes and Product Use

3. 62 2006 IPCC Guidelines for National Greenhouse Gas Inventories The furnace black process is a partial combustion proce ss where a portion of the ca rbon black feedstock iscombusted 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 par tial oxidation of natural gas or aromatic oils (‘channel black process’). Carbon black may also be produced by the thermal cracking of acet ylene-containing feedstocks (‘acetylene black process’) or by th e thermal cracking of other hydrocar bons (‘thermal black process’.) Approximately 95 percent of worldwid e carbon black production is by wa y of the furnace black process; the remaining 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 an d 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).

B OX 3.13 C ARBON BLACK PRODUCTION PROCESS DESCRIPTIONS Furnace Black Process The furnace black process produces carbon black from ‘carbon black feedstock’ (also referred to as ‘carbon black oil’) which is a heavy aromatic oil that may be derived either as a by-product of the petroleum refining process or the metallurgi cal (coal) coke productio n 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 the natural gas secondary feedstock and a portion of the carbon black feedstock are oxidized to provide heat to the production process that pyrolyzes the remaining carbon black feedstock to carbon black. The vent gas from the furnace black process contains CO 2 , CO, sulphur compounds, CH 4 , and NMVOCs. A portion of the tail gas is genera lly burned for energy recovery to heat the downstream 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 gaseous hydrocarbons or atomized petroleu m oils in the absence of air in a pair of production furnaces. The carbon black feedstock is in troduced into a preheated furnace that is heated by a secondary feedstock, usually natural gas, and by the off ga s from the carbon black production process. One of the pair of furnaces is being preheated by the secondary feedstock while the other furnace is receiving carbon black feedstock. Yield from this process is ap proximately 45 percent of total carbon input to the process (or 40 percent with re spect to the total carbon black feedstock used) and energy utilisation is approximately 280 MJ/kg carbon black produced. Acetylene Black Process Carbon black produced fr om acetylene or acetylene-containing light hydrocarbons by feeding the feedstock to a preheated reactor where the acetylen e decomposes to carbon black in an exothermic process. Total worldwide produc tion of acetylene black is only a pproximately 40 000 metric tons per year. The carbon black yield from this proces s is approximately 95-99 percent of theoretical yield. Acetylene black is appr oximately 99.7 percent carbon. Other Production Processes The channel black process involves partial oxidation of vaporised carbon black feedstock that is burned 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 of rubber-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)Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.63 

# 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 the feedstock used. The choice of method should thus be re peated for each product, pr ocess and feedstock used. Three methodological tiers ar e provided depending on the availability of data. The choice of method depends on national 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

Start

Are both the type of feedstock used and process known?

Is Petrochemical and Carbon Black Production a key category and is this subcategory significant?

Is it the process that is

unknown? No

No No Collect feedstock

and the process data 1

. Estimate emissions using Tier 3 plant-specific emission factors.

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

Box 1: Tier 1 Box 4: Tier 3

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

No Is it the feedstock that is

unknown? Estimate emissions using Tier 2 carbon balance. 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. Box 3: Tier 2

Box 2: Tier 1 Yes

Yes

Is supplementary fossil fuel transferred

into the process? Are by-products transferred out of the process? Are the activity data for all carbon flows available? Are plant-specific emission factors available?

Assume default process. Subtract carbon from carbon

balance.

Add carbon emitted to carbon balance.

Assume default feedstock. Repeat for each feedstock and petrochemical.

Yes

No

No

Yes

No

Yes Yes

No YesVolume 3: Industrial Processes and Product Use

3. 64 2006 IPCC Guidelines for National Greenhouse Gas Inventories Figure 3.9 Decision tree for estimation of CH 4 emissions from petrochemical industry and carbon black industry

Start

Are both the type of feedstock used and process known?

Is Petrochemical and Carbon Black Production a key category and is this subcategory significant?

Is it the process that is

unknown? No

No No Collect feedstock

and the process data 1

. Estimate emissions using Tier 3 plant-specific emission factors.

Estimate emissions using Tier 1 default emission factors.

Box 1: Tier 1 Box 3: Tier 3

Note: 1. See Volume 1 Chapter 4,"Methodological Choice and Identificat ion of Key Categories" (noting Section 4.1.2 on limited resourc es), for discussion of key categories and use of decision trees. 2. Note that there is no Tier 2 method for estimating CH 4 emissions. The Tier 2 method is a tota l feedstock carbon mass balance method that is applicable to estimating total carbon (CO 2 ) emissions but not applicable to estimating CH 4 emissions. Yes

No Is it the feedstock that is

unknown? Estimate emissions using Tier 1 default emission factors. If the annual primary product production data are not

available, use Equation 3.16.
Box 2: Tier 1 Yes

Yes Are plant-specific emission factors available?

Assume default process.

Assume default feedstock. Repeat for each feedstock and petrochemical.

Yes

No

Yes

The Tier 3 methodology can be used to estimate plant-level CO 2 emissions and CH 4 emissions. The Tier 3 method depends upon the availability of plant-specific data for the pe trochemical process. The Tier 2 methodology is a mass balance approach that is applicable to estimating CO 2 emissions but is not applicable to estimating CH 4 emissions. When using the Tier 2 methodology, both carbon flows of primary and secondary feedstocks to the process are included in the mass ba lance calculation. Carbon flow s of primary fuels to theChapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.65 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 the process must be characterised.



### CARBON DIOXIDE
The decision tree for choice of method for CO 2 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 emi ssion factor method The Tier 1 emission factor methodology is applied to estimate CO 2 emissions from the petrochemical process in cases where neither plant specific data nor activity data for carbon flows are available for the petrochemicalprocess. The Tier 1 emission factor method does not require activity data for the consumption of each carboncontaining feedstock to the petrochemical production pro cess. 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 production of 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, acrylon itrile) and carbon black.

E QUATION 3.15 T IER 1 CO 2 EMISSION CALCULATION 100 / 2 GAF EF PP ECO i i i • • =
Where: ECO2 i = CO 2 emissions from production of petrochemical i , tonnes PP i = annual production of petrochemical i , tonnes EF i = CO 2 emission factor for petrochemical i , tonnes CO 2 /tonne product produced GAF = Geographic Adjustment Factor (for Tier 1 CO 2 emission factors for ethylene production, See Table 3.15), percent Tier 1 CO 2 emission factors for ethylene production (discussed in Section 3.9.2.2) have been developed based on data for ethylene steam crackers opera ting in Western Europe. Geographic Adjustment Factors are applied to the Tier 1 emission factor to account for regional variabilit y 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:

E QUATION 3.16 P RIMARY PRODUCT PRODUCTION ESTIMATE CALCULATION 

# ( ) ∑ • = k k i k i i SPP FA PP

, ,
Where:
PP i = annual production of petrochemical i , tonnes FA i,k = annual consumption of feedstock k consumed for production of petrochemical (i), tonnes SPP i , 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 app lied separately to each of the known feedstocks for each petrochemical process. The Tier 1 em issions 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 eitherVolume 3: Industrial Processes and Product Use

3. 66 2006 IPCC Guidelines for National Greenhouse Gas Inventories Equation 3.15 or both Equation 3.16 and Equation 3.15. Equation 3.15 would be utilised alone in cases where annual primary product production data are available fo r 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 is applicable in cases where activity data are available fo r both feedstock consumption and primary and secondary product production and disposition. Activity data for a ll 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 illust rated by a feedstock-product matrix rather than by a process 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 Primary

Feedstock to

Process.

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

Calculate carbon emis sions from process using Equation 3.17. Identify Petrochemical Production Process.

Calculate carbon output {[PP i ・ PC i + ∑ j (SP i,j ・ SC j )] in Equation 3.17} Calculate carbon input {∑ k (FA i,k ・ FC k ) in Equation 3.17} Determine Secondary Product Carbon Content

using Table 3.10 or activity data. Determine Secondary

Feedstock Carbon Content using Table 3.10 or activity data. Determine Primary Feedstock Carbon Content using Table 3.10 or activity data. Determine Secondary Product Production using activity data or Table 3.25 and Equation 3.18 (ethylene) or Table 3.26 and Equation 3.19 (acrylonitrile). Determine Primary Product Production using activity data. Determine Secondary Feedstock Consumption using activity data. Determine Primary Feedstock Consumption using activity data. Identify Secondary Product(s) of

Process. Identify Primary Product of

Process. Identify Secondary

Feedstock(s) to Process.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.67 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 cont ent of the primary and secondary feedstocks and the carbon content of the primary and secondary products produced by and recovered from the process is calculated as CO 2. The Tier 2 mass balance methodology is based on the assumption that all of the carbon input to the process is converted either into primary and secondary products or into CO 2 . This means that any of the carbon input to the process that is converted into CO, CH 4 , or NMVOC are assumed to be CO 2 emissions for the purposes of the mass balance calculation. The overall mass balance equation for the Tier 2 methodology is Equation 3.17.

E QUATION 3.17 O VERALL T IER 2 MASS BALANCE EQUATION 

# ( ) 

# ( ) 12 44 2

, , • ⎪ ⎭ ⎪ ⎬ ⎫ ⎪ ⎩ ⎪ ⎨ ⎧ ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎣ ⎡

• + •

− • = 

### ∑ ∑ j j j i i i k k k i i SC SP PC PP FC FA ECO

Where: ECO2 i = CO 2 emissions from production of petrochemical i , tonnes FA i,k = annual consumption of feedstock k for production of petrochemical i , tonnes FC k = carbon content of feedstock k , tonnes C/tonne feedstock
PP i = annual production of primary petrochemical product i , tonnes PC i = carbon content of primary petrochemical product i , tonnes C/tonne product SP i,j = annual amount of secondary product j produced from production process for petrochemical i , tonnes [The value of SP i,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 SP i,j .] SC j = carbon content of secondary product j , tonnes C/tonne product For 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 primary feedstock consumption, as shown in Equations 3.18 and 3.19:

E QUATION 3.18 E STIMATE SECONDARY PRODUCT PRO DUCTION FROM PRIMARY PRODUCT [ ETHYLENE ] PRODUCTION 

# ( ) ∑ • = k k j k Ethylene j Ethylene SSP FA SP

, , ,
Where: SP Ethylene ,j = annual production of secondary product j from ethylene production, tonnes
FA Ethylene k = annual consumption of feedstock k consumed for ethylene production, tonnes SSP j , k

= specific secondary product production factor for secondary product j and feedstock k , tonnes secondary product/tonne feedstock consumed

E QUATION 3.19 E STIMATE SECONDARY PRODUCT PRO DUCTION FROM PRIMARY PRODUCT [ ACRYLONITRILE ] PRODUCTION 

# ( ) ∑ • = k k j k ile Acrylonitr j ile Acrylonitr SSP FP SP

, , ,
Where:Volume 3: Industrial Processes and Product Use

3. 68 2006 IPCC Guidelines for National Greenhouse Gas Inventories SP Acrylonitrile,j = annual production of secondary product j from acrylonitrile production, tonnes
FP Acrylonitrile,k = annual production of acrylonitrile from feedstock k , tonnes SSP j , 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 for acrylonitrile production. 

### Feedstock and product carbon contents Carbon contents of feedstocks and products of petroc hemical production processes are listed in Table 3.10, in units 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 black feedstock, 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 CO 2 emissions from the petrochemical production process. In order to apply the Tier 3 method, plant-specific data and/or plant-specific measurements are required. The emissions from the petrochemical production process include CO 2 emitted from fuel or process by-products combusted to provide heat or thermal energy to the production process, CO 2 emitted from process vents, and CO 2 emitted from flared waste gases. These emissions are calculated using Equations 3.20 through 3.22. Overall CO 2 emissions from the petrochemical production process are calculated using Equation 3.20

E QUATION 3.20 T IER 3 CO 2 EMISSIONS CALCULATION EQUATION

i Flare i Vent cess Pro i Combustion i E E E ECO

, , , 2 + + =

Where: ECO2 i = CO 2 emissions from production of petrochemical i , tonnes E Combustion,i = CO 2 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 = CO 2 emitted from process vents during production of petrochemical i , tonnes E Flare,i = CO 2 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 CO 2 . 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 CO 2 directly and thus no further equation is provided.

E QUATION 3.21 F UEL COMBUSTION T IER 3 CO 2 EMISSIONS CALCULATION 

# ( ) ∑ • • = k k k k i i Combustion EF NCV FA E

, ,
Where:
FA i,k = amount of fuel k consumed for production of petrochemical i , tonnes NCV k = 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)Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.69 EF k = CO 2 emission factor of fuel k , tonnes CO 2 /TJ (Note: In Table 1.4 in Chapter 1 of Volume 2, CO 2 emission factors are expressed in kg/TJ)

E QUATION 3.22 F LARE GAS T IER 3 CO 2 EMISSIONS CALCULATION 

# ( ) ∑ • • = k k k k i i Flare EF NCV FG E

, ,
Where: FG i,k = amount of gas k flared during production of petrochemical i , tonnes NCV k = 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)
EF k = CO 2 emission factor of flared gas k , tonnes CO 2 /TJ (Note: In Table 1.4 in Chapter 1 of Volume 2, CO 2 emission factors are expressed in kg/TJ)

T ABLE 3.10 S PECIFIC 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
Ethane 0.856 Ethylene 0.856 Ethylene dichloride 0.245 Ethylene glycol 0.387 Ethylene oxide 0.545 Hydrogen Cyanide 0.4444
Methanol 0.375
Methane 0.749 Propane 0.817 Propylene 0.8563 Vinyl Chloride Monomer 0.384 Note: Carbon content values for natural gas a nd naphtha vary by count ry and region. Net calorific values (NCV) for natural gas, naphtha, and other primary fuels that may be used as petrochemical feedstocks are included in Tabl e 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 CH 4 emissions is shown in Figure 3.9. The Tier 1 and Tier 3 methods for CH 4 are described in this section. There is no Tier 2 method applicable to CH 4 emissions. 

### Tier 1 product-based emi ssion factor method CH 4 emissions from petrochemical processes may be fug itive 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. CH 4 emissions using the Tier 1 method may be calculated usi ng Equation 3.23 for fugitive CH 4 emissions and Equation 3.24 for process ventVolume 3: Industrial Processes and Product Use

3. 70 2006 IPCC Guidelines for National Greenhouse Gas Inventories emissions and Equation 3.25 for total CH 4 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 to estimate 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.

E QUATION 3.23 T IER 1 CH 4 FUGITIVE EMISSION CALCULATION

i i i Fugitive EFf PP ECH • =

, 4

E QUATION 3.24 T IER 1 CH 4 PROCESS VENT EMISSION CALCULATION

i i i Vent ocess Pr EFp PP ECH • =

, 4

E QUATION 3.25 T IER 1 CH 4 TOTAL EMISSIONS CALCULATION

i Vent ocess Pr i Fugitive i Total ECH ECH ECH

, , , 4 4 4 + =

Where: ECH4 Total,i = total emissions of CH 4 from production of petrochemical i , kg ECH4 Fugitive,i = fugitive emissions of CH 4 from production of petrochemical i , kg ECH4 Process Vent,i = process vent emissions of CH 4 from production of petrochemical i , kg
PP i = annual production of petrochemical i , tonnes EFf i = CH 4 fugitive emission factor for petrochemical i , kg CH 4 /tonne product EFp i = CH 4 process vent emission factor for petrochemical i , kg CH 4 /tonne product



### Tier 2 total feedstock carbon balance method The total feedstock carbon mass balance method is not applicable to estimation of CH 4 emissions. The total carbon mass balance method estimates the total carbon emi ssions from the process but does not directly provide an estimate of the amount of the total carbon emissions that is emitted as CO 2 , CH 4 , 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 the petrochemical production process include CH 4 emitted from fuel or process by-products combusted to provide heat or thermal energy to the production process, CH 4 emitted from process vents, and CH 4 emitted from flared waste gases. If methane is vented directly to the atmosphere this will dominate the emissions. CH 4 emissions from process vents may also be combusted in a flare or energy recovery device. Measurement of atmospheric concentration of VOCs directly above the plants or in the plume is the preferred activity data for estimating fugitive CH 4 emissions; however, such data may not be available. The atmospheric measurements are generally expensive and will most often not be continuous measurem ents 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 of such measurement programs would then be related to other plant process parameters to enable estimation of emissions between measurement periods. Direct measurement of VOC and CH 4 concentrations in plant exhaust ga s streams and direct measurement of fugitive VOC and CH 4 emissions from plant valves, fittings, and related equipment using a comprehensive leak detection programme can also be used to obtain plant-sp ecific activity data for developing Tier 3 estimates of CH 4 emissions. However the plant-specific leak detection programme should provide fugitive CH 4 emissions data for all of the relevant CH 4 -emitting plant equipment. Similarly, the plant-specific measurement data for stacks and vents would need to cover the major portion of stack and vent CH 4 emissions sources at the plant in order to provide a basis for a Tier 3 emission calculation.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.71 Emissions of CH 4 from process stacks and vents may be es timated by direct measurement of the CH 4 concentration of the exhaust gas or estimated as a comp onent of the total VOC concentration measured in the exhaust gas. Fugitive emissions of CH 4 from plant equipment (e.g., valves, fittings) may be estimated through application of plant-specific leak det ection data and plant equipment inventories, provided that the plant-specific leak detection program and equipment inventory are comprehensive, such that the program provides fugitive CH 4 emissions data for all of the relevant CH 4 -emitting plant equipment. Similarly, the plant-specific measurement data for stacks and vents would need to cover the major portion of stack and vent CH 4 emissions sources at the plant in orde r to provide a basis for a Tier 3 emission calculation. Measurement of fugitive emissions may also be based on the CH 4 concentration in the atmosphere immediately above the plant or in a plume downwind. Such atmo spheric measurement data would generally measure emissions from the entire plant, and does not separa te between the different sources. In addition to CH 4 concentration the area of the plume and the wind speed must be measured. The emissions are given by Equation 3.26.

E QUATION 3.26 T IER 3 CH 4 EMISSION CALCULATION BASED ON ATMOSPHERIC MEASUREMENT DATA 

# ( ) 

# [ ] ∫ • •

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

Where: CH4 Emissions = total plant CH 4 emissions, μg/s C total VOCs = VOC concentration at the plant, μg/m 3
CH 4 fraction = fraction of total VOC concentration that is CH 4 , fraction CH 4 background level = ambient CH 4 concentration at background location, μg/m 3 WS = wind speed at the plant, m/s PA = plume area, m 2

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 or other specific types of di rect measurements to es timate site-specific CH 4 emissions. It is anticipated that plantspecific leak detection data and plant-specific stack and vent emission data will be more readily available than atmospheric measurement data. However, if atmospheric measurement data are available the data may be used to develop Tier 3 estimates of CH 4 emissions, or to verify other estimates. Atmospheric measurement data may provide a more accurate estimate of process CH 4 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 CH 4 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 vent emissions calculation. Overall emissions of CH 4 from the petrochemical production process based on plant-specific leak detection data and plant-specific stack and vent emissions data are calculated using Equation 3.27

E QUATION 3.27 T IER 3 CH 4 EMISSIONS CALCULATION EQUATION

i Flare i Vent cess Pro i Combustion i E E E ECH

, , , 4 + + =

Where: ECH4 i = total emissions of CH 4 from production of petrochemical i , kg
E Combustion,i = emissions of CH 4 from fuel or process by-products combusted to provide heat or thermal energy to the production process for petrochemical i , kg
E Process Vent,i = emissions of CH 4 from process vents during production of petrochemical i , kg
E Flare,i = emissions of CH 4 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.Volume 3: Industrial Processes and Product Use

3. 72 2006 IPCC Guidelines for National Greenhouse Gas Inventories E QUATION 3.28 F UEL COMBUSTION T IER 3 CH 4 EMISSIONS CALCULATION 

# ( ) ∑ • • = k k k k i i Combustion EF NCV FA E

, ,
Where:
FA i,k = amount of fuel k consumed for production of petrochemical i , tonnes NCV k = 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)
EF k = CH 4 emission factor of fuel k , kg/TJ

E QUATION 3.29 F LARE GAS T IER 3 CH 4 EMISSIONS CALCULATION 

# ( ) ∑ • • = k k k k i i Flare EF NCV FG E

, ,
Where: FG i,k = amount of gas k flared during production of petrochemical i , tonnes NCV k = 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)
EF k = CH 4 emission factor of flared gas k , kg/TJ


## 3.9.2.2 C HOICE OF EMISSION FACTORS

This section includes a discussion of the choice of emission factors for the Tier 1 method. The Tier 2 method is based on mass balance principles and the Tier 3 method is based on plant-specific data; therefore there are no default emission factors applicable to the Tier 2 and Tier 3 methods.

T ABLE 3.11 P ETROCHEMICAL PRODUCTION T IER 1 DEFAULT FEEDSTOCKS AND PROCESSES
Petrochemical Process Defaul t Feedstock Default Process
Methanol Natural Gas Conventional steam reforming without primary reformer Ethylene North Americ a, South America, Australia - Ethane Other Continents - Naphtha Steam cracking
Steam cracking Ethylene Dichloride / Vinyl Chloride Monomer Ethylene Balanced Process for EDC production with integrated VCM production plant Ethylene Oxide Ethylene Catalytic Oxidation, Air Process, with thermal treatment Acrylonitrile Propylene Direct A mmoxidation with secondary products burned for energy recovery or flared Carbon Black Carbon black feedstock and natural gas Furnace black process with thermal treatment



### TIER 1
Tier 1 emission factors for CO 2 emissions and CH 4 emissions for petrochemical products are provided below. Tier 1 emission factors for CO 2 emissions do not include carbon emitted as CO, CH 4 , or NMVOC. Separate Tier 1 emission factors are provided for CH 4 emissions from petrochemical processes. Tier 1 emission factors are not provided for carbon monoxide and NMVOC emissions. The Tier 1 method allows for the se lection of a ‘default’ feedstock and ‘default’ process in instances where activity data are not available to identify the feedstoc k or the process utilised to produce the petrochemical. Table 3.11 provides the default feedstocks and default processes for each petrochemical production process. InChapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.73 the event that no activity data are available concerning the specific pro cesses and feedstocks used within a country to produce the petrochemical, the default process and default feedstock identified in Table 3.11 and the associated Tier 1 emission factors iden tified in the subsequent tables in th is section are used to estimate the CO 2 emissions from the petrochemical production process. Country-specific emission factors may be used instead of the default emission factors if coun try-specific factors are available. 

### Methanol Carbon dioxide emissions Emissions of CO 2 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 and process feedstock. The default emission factors are based on the average of plant-specific CO 2 emissions data reported for four methanol plants using the conventional steam reforming process without primary reformer and using natural gas feedstock. Emissions data used in developing the default CO 2 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 CO 2 emissions arising from the process feedstock and the CO 2 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 a secondary reformer. The emission factors differ depending upon the number of reformer units. Lurgi is a provider 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 primary reformer, 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 te chnology is known.

T ABLE 3.12 M ETHANOL PRODUCTION CO 2 EMISSION FACTORS
tonne CO 2 /tonne methanol produced Process Configuration Feed stock Nat. gas Nat. gas + CO 2 Oil Coal Lignite

Conventional Steam Re forming, without pr imary reformer (a) (Default Process and Natural Gas Default Feedstock) 0.67

Conventional Steam Reform ing, with primary reformer (b) 0.497
Conventional Steam Reformi ng, Lurgi Conventional process (c1) 0.385 0.267
Conventional Steam Reformi ng, Lurgi Low Pressure Process (c2) 0.267 Combined Steam Reforming, Lurgi Combined Process (c3) 0.396
Conventional Steam Reformi ng, Lurgi Mega Methanol Process (c4) 0.310 Partial oxidation process (d) 1.376 5.285 5.020 Conventional Steam Reforming with inte grated ammonia production 1.02 Nat. gas + CO 2 feedstock process based on 0.2-0.3 tonne CO 2 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 CO 2 /GJ 48.0 GJ/tonne Oil: 74 kg CO 2 /GJ 42.7 GJ/tonne Coal: 93 kg CO 2 /GJ 27.3 GJ/tonne Lignite: 111 kg CO 2 /GJ Uncertainty values for this ta ble 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, 1999Volume 3: Industrial Processes and Product Use

3. 74 2006 IPCC Guidelines for National Greenhouse Gas Inventories T ABLE 3.13 M ETHANOL PRODUCTION FEEDSTOCK CONSUMPTION FACTORS GJ feedstock input /tonne methanol produced Process Configuration Feed stock Nat. gas Nat. gas + CO 2 Oil Coal Lignite

Conventional Steam Re forming, without pr imary reforme (a) (Default Process and Natural Gas Default Feedstock) 36.5

Conventional Steam Reform ing, with primary reformer (b) 33.4 29.3
Conventional Steam Reformi ng, Lurgi Conventional process (c1) 31.4
Conventional Steam Reformi ng, Lurgi Low Pressure Process (c2) 29.3 Combined Steam Reforming, Lurgi Combined Process (c3) 31.6
Conventional Steam Reformi ng, Lurgi Mega Methanol Process (c4) 30.1 Partial oxidation process (d) 37.15 71.6 57.6 Nat. gas + CO 2 feedstock process based on 0.2-0.3 tonne CO 2 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 ta ble are included in Table 3.27



### Methane emissions Methanex reported CH 4 emissions from two Canadian methanol production plants in their 1996 Climate Change Action Plan (Methanex, 1996). Methanex reported that CH 4 emissions from methanol production may arise from reformers, package boilers, methanol distillati on units, and crude methanol storage tanks. CH 4 emissions from the plants accounted for approximately 0.5 percent to 1.0 percent of the total greenhouse gas emissions from the plants, but were reported to vary depending upon the level of maintenance and operational control of the plant equipment. The average emission factor re ported for two reporting years is 2.3 kg CH 4 emissions per tonne of methanol produced. CH 4 emissions from a second Methanex methanol production plant were reported to be 0.15 kg CH 4 per tonne of methanol produced. The higher of the two reported values, 2.3 kg CH 4 per tonne of methanol produced, should be applied as the default CH 4 emission factor for methanol production. CH 4 emissions as low as 0.1 kg/tonne have been estimated for the methanol plant Tjeldbergodden, Norway (SFT, 2003a).



### Ethylene Carbon dioxide emissions Emissions of CO 2 from steam cracking for ethylene production may be estimated using the feedstock-specific emission 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 CO 2 emissions from feedstock consumption and from supplemental energy consumption in the steam cracking process. However, the CO 2 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 are derived from plant-specific data for steam crackers operating in Western Europe. The emission factors may be adjusted by applying the default geogr aphic adjustment factors in Table 3. 15 to account for differences in the energy 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, and the default feedstock for steam crackers operating on other continents is naphtha. These default emission factors do not include CO 2 emissions from flaring. Emissions from flaring amount to about 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 CO 2 emissions associated with supple mental fuel consumption for these feedstocks.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.75 T ABLE 3.14 S TEAM CRACKING ETHYLENE PRODUCTION T IER 1 CO 2 EMISSION FACTORS
tonnes CO 2 /tonne ethylene produced Feedstock Naphtha Gas Oil Ethane Propane Butane Other Ethylene (Total Process and Energy F eedstock 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 ta ble 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 amount of ethylene produced by the steam cracking process. Steam cracking is a multi-product process that leads to ethylene, 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 for each emission factor in Table 3.14 is identified in the ethylene steam cracking feedstock- product matrix in Section 3.9.2.3. The fe edstock/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 CO 2 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 CO 2 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 the total CO 2 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 CO 2 emissions from the steam crack ing process, not only the CO 2 emissions associated with the production of the ethylene from the steam cracking process.

T ABLE 3.15 D EFAULT G EOGRAPHIC A DJUSTMENT F ACTORS FOR T IER 1 CO 2 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% Including Asia other than Japan and Korea
North America and South America and Australia 110%
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 ta ble are included in Table 3.27.



### Methane emissions Default fugitive CH 4 emission factors for steam cracking of ethane and naphtha for ethylene production are estimated from total VOC emissions factors and VOC sp ecies profile data from EMEP/CORINAIR Emission Inventory Guidebook (EEA, 2005). Overall volatile or ganic 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, for which the feedstock is assumed to be ethane. From the total VOC emission factors the overall CH 4 emissions from steam cracking of naphtha are estimated from the VOC species profile to be 3 kg/tonne ethylene produced, primarily from leakage lo sses, and the overall CH 4 emissions from cracking of et hane are estimated from the species profile to be twice those fro m cracking of naphtha (6 kg/tonne ethyl ene produced); however these factors are subject to uncertainty as the overall VOC emission factors of 5 kg VOC/tonne ethylene for naphtha feedstock and 10 kg VOC/tonne ethylene for ethane feedstock are each based on a single publication. Emissions of CH 4Volume 3: Industrial Processes and Product Use

3. 76 2006 IPCC Guidelines for National Greenhouse Gas Inventories from steam cracking of feedstocks other than ethane and naphtha have been assumed to be the same as that estimated from the EMEP/CORINAIR da ta for steam cracking of naphtha. Published data show a large variability in reported CH 4 emission factors for ethylene production. The European Association of Plastics Manufacturers (APME) Eco-Prof iles of the European Plastics Industry reports a CH 4 emission factor for ethylene production of 2.9 kg CH 4 /tonne ethylene produced, as referenced in the APME EcoProfiles for Olefins Production (Boustead, 2003a). The CH 4 emission factor for ethyle ne steam cracker process operations is based on life-cycle analysis data for 15 European steam crackers. Emissions as low as 0.14 kg CH 4 /tonne ethylene are estimated on the ba sis of direct measurement at a No rwegian ethylene plant (SFT 2003b) and as low as 0.03 kg CH 4 /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 CH 4 emissions on the order of 10 percent of the values reported in Table 3.16 (DSM, 2002; Qenos, 2003; Qenos, 2005). Therefore, the emission factors in Table 3.16 should not be used to estimate CH 4 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 CH 4 emission factors for various process feedstocks are shown in Table 3.16. Note that the default feedstocks for ethylene production are identified in Table 3.11.

T ABLE 3.16 D EFAULT METHANE EMISSION FACT ORS FOR ETHYLENE PRODUCTION Feedstock kg CH 4 / tonne ethylene produced
Ethane 6 Naphtha 3
All Other Feedstocks 3

Source: EEA, 2005 (EMEP/CORINAIR Emission Inventory Guidebook) Uncertainty values for this ta ble 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 CO 2 emission factors are derived by averaging plant-specific CO 2 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 CO 2 emission factor for each process includes noncombustion CO 2 emissions from the ethylene dichloride process vent and combustion CO 2 emissions 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 to apply 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 CO 2 emission factors in Table 3.17 in units of tonnes CO 2 per tonne EDC produced and in units of tonnes CO 2 per tonne VCM produced are not additive. The two CO 2 emission factors both apply to the integrated EDC/VCM production process, however the tonnes CO 2 per tonne EDC factor is based on EDC production activity data while the tonnes CO 2 per tonne VCM factor is based on VCM production activity data. The CO 2 emission factor that will be applied will depend upon whether activity data for EDC production or activity data for VCM production are available. Similarl y, the feedstock consumption factors in Table 3.18 in units of tonnes ethylene consumed per tonne EDC produced and in units of tonnes ethylene consumed per tonne VCM produced are not additive. The feedstock consumpt ion factor that will be applied will depend upon whether activity data are available for EDC production or for VCM production.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.77 T ABLE 3.17 E THYLENE DICHLORIDE / VINYL CHLORIDE PRODUCTION PROCESS T IER 1 CO 2 EMISSION FACTORS Process Configuration tonne CO 2 /tonne EDC produced tonne CO 2 /tonne VCM produced
Direct Chlorination Process Noncombustion Process Vent negligib le emissions negligible emissions
Combustion Emissions 0.191 0.286
Total CO 2 Emission Factor 0.191 0286 Oxychlorination Process
Noncombustion Process Vent 0.0113 0.0166
Combustion Emissions 0.191 0.286
Total CO 2 Emission Factor 0.202 0.302 Balanced Process [default process]
Noncombustion Process Vent 0.0057 0.0083
Combustion Emissions 0.191 0.286
Total CO 2 Emission Factor 0.196 0.294
Values for CO 2 emissions from EDC and VCM production for several European production plants were provided in Tables 12.6 and 12.7 of the IPPC LVOC BAT Document (European IPPC Bu reau, 2003). These values were averaged to calculate CO 2 emission factors for EDC and VCM production. One EDC plant that is equipped with a CO 2 control device and that reported zero CO 2 emissions from the 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 ta ble are included in Table 3.27.

T ABLE 3.18 E THYLENE DICHLORIDE / VINYL CHLORIDE MONOMER PROCESS T IER 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, Se ction 12.3.1, Page 299-300, Sec tion 12.1 Table 12.3, Page 293). Uncertainty values for this tabl e 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 CH 4 emissions from the process other than CH 4 emissions from combustion sources. The EMEP/CORINAIR species profile reports that VO C emissions from leakage losses and storage and handling do not contain CH 4 . The EMEP/CORINAIR also reports that 2 percent of the total VOC emissions from the balanced process are fr om combustion sources and that CH 4 constitutes 1.2 percent of overall VOC emissions. Therefore it may be assumed that non-combustion CH 4 emissions from ethylene dichloride/vinyl chloride monomer production are negligible. CH 4 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 CH 4 emission factor for natural gas combustion. Natural gas consumption for integrated ethylene dichloride/vinyl chloride monomer production is estimated to be 110.1 Nm 3 natural gas/tonne VCM produced for an integrated ethylene dichloride/vinyl chloride monomer production plant in the Netherlands and 126.4 Nm 3 natural gas/tonne VCM produced for an integrated ethylene dichloride/vinyl chloride monomer production plant in Germany. The average of these two values is 118.3 Nm 3 natural gas/tonne VCM. The CH 4 emission factor for the integrated EDC/VCM production process is based on a CH 4 emission factor of 5 g CH 4 /GJ natural gas combusted and the average natural gas consumption of the two European plants. The default CH 4 emission factor for the integrated ethylene dichloride/vinyl chloride monomer production process is provided in Table 3.19. TheVolume 3: Industrial Processes and Product Use

3. 78 2006 IPCC Guidelines for National Greenhouse Gas Inventories default emission factor is not applicable to stand-alone EDC production plants. If natural gas consumption activity data are available, the CH 4 emission factor of 5 g CH 4 /GJ may be applied directly to the activity data, rather than using the default emission factor.

T ABLE 3.19 E THYLENE DICHLORIDE / VINYL CHLORIDE PROCESS T IER 1 DEFAULT CH 4 EMISSION FACTOR Process Configuration kg CH 4 /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 Industrie s (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 CO 2 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 CO 2 emission factors are provided in Table 3.20 for the CO 2 emissions from the air process and for the CO 2 emissions from the oxygen process for a range of catalyst selectivity. The default emission factors for the air process and for the oxygen process are estimated from pro cess-specific catalyst selectiv ity data provided in the IPPC LVOC BAT document. Specific data concerning the type of process and the selectivity of the process catalyst are needed in order to select emission factors from Table 3.20. The emission factors are derived from the catalyst selectivity using stoichiometric principles and are based on the assumption that emissions of CH 4 and NMVOC from the process are negligible and that all of the carbon contained in the ethylene feedstock is converted either into ethylene oxide product or to CO 2 emissions. The emission factors in Table 3.20 do not include 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 availa ble for the process configuration or the catalyst selectivity, the default process configuration is the air process and th e 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 the oxygen process in Table 3.20 should be used.

T ABLE 3.20 E THYLENE OXIDE PRODUCTION FEEDSTOCK CONSUMPTION AND CO 2 EMISSION FACTORS

Process Configuration Catalyst Selectivity Feedstock Consumption (tonne ethylene/ tonne ethylene oxide) Emission Factor (tonne CO 2 / tonne ethylene oxide) Default (70) 0.90 0.863 75 0.85 0.663 Air Process [default process] 80 0.80 0.5 Default (75) 0.85 0.663 80 0.80 0.5 Oxygen Process 85 0.75 0.35 Source: European IPPC Bureau, 2003 (IPPC LVOC BAT Document, Sec tion 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 CH 4 emissions factors (in units of kilograms methane per tonne ethylene oxide produced) for the ethylene oxide process vent, ethylene oxide purification process exhaust gas steam, and fugitive emissions sources. CH 4 emission factors were reported in the IPPC LVOC BAT document for European ethylene oxide plant carbon dioxide removal vents before and after treatment. CH 4 emissions were also reported for two ethylene oxide plants in the Netherlands. CH 4 emission factors for ethylene oxide production were developed by averaging these data. Emissions of CH 4 may be estimated by applying the emissions factors included in Table 3.21 to activity data for ethylene oxide production. The default CH 4 emission factor for ethylene oxide production assumes no thermal treatment process.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.79 T ABLE 3.21 E THYLENE OXIDE PRODUCTION T IER 1 CH 4 EMISSION FACTORS Process Configuration kg CH 4 /tonne ethylene oxide produced No Thermal Treatment [default factor] 1.79
Thermal Treatment 0.79 Source: European IPPC Bureau, 2003 (IPPC LVOC BAT Document, Tabl e 9.6, Page 233; Table 9.8, Pa ge 236; Table 9.9, Page 236).



### Acrylonitrile Carbon dioxide emissions Process vent CO 2 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:

T ABLE 3.22 A CRYLONITRILE PRODUCTION CO 2 EMISSION FACTORS Process Configuration Direct Ammoxidation of Propylene tonnes CO 2 /tonne acrylonitrile produced

Secondary Products Burned for Ener gy Recovery/Flared (default) 1.00 Acetonitrile Burned for Energy Recovery/Flared 0.83 Acetonitrile and Hydrogen Cyan ide Recovered as Product 0.79 Source: European IPPC Bureau, 2003 (IPPC LVOC BAT Document, Sec tion 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 yield factor of approximately 70 percent. The default CO 2 emission factor is based on conversion of propylene feedstock to secondary produc t 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 is based 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 CO 2 emission factor is based on the assumption that the secondary products ( acetonitrile and hydrogen cyanide) of the acrylonitrile production process and hydrocarbon by products in the main absorber vent gas are either burned for energy recovery or flared to CO 2 and are not recovered as products or emitted to the atmosphere without combustion treatment. The CO 2 emission factors do not include CO 2 emissions from any combustion of auxiliary fuel (e.g., natural gas) for th e 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 CO 2 and the default primary product process yield factor is 70 percent. For the process configuratio n where secondary products (acetonitrile an d hydrogen cyanide) are recovered for sale and are not either flared to CO 2 or burned for energy recovery, the overall process yield factor of primary and 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 factor of 1.09 tonnes propylene feedstock consumed per tonne acrylonitrile produced. 

### Methane emissions The Life-Cycle Analysis Data Summary for Acrylonitrile reports a CH 4 emission factor for acrylonitrile production of 0.18 kg CH 4 /tonne acrylonitrile produced, as referenced in the European Association of Plastics Manufacturers (APME) Life-Cycle Analysis Report (Boustead, 1999). The CH 4 emission factor for acrylonitrile process operations is based on life-cycle analysis data fo r European acrylonitrile plants in Germany, Italy, and the United Kingdom collected between 1990 and 1996. CH 4 emissions from acrylonitrile production may be estimated by applying this default emission factor to the acrylonitrile production data.Volume 3: Industrial Processes and Product Use

3. 80 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### Carbon black Carbon dioxide emissions Emissions of CO 2 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 in Table 3.23 for the furnace black proces s, thermal black process, and acetylen e black process and their associated feedstocks, and separate emission f actors 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 CO 2 emission factors in Table 3.23 are based on the average of the range of values. Primary and secondary feedstock consumption is converted to carbon consumption using average values for ca rbon black feedstock carbon content. The CO 2 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.

T ABLE 3.23 C ARBON BLACK PRODUCTION T IER 1 CO 2 EMISSION FACTORS
tonnes CO 2 /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 CH 4 emissions for the carbon black production process are provided in Table 3.24. The draft IPPC LVIC BAT document for carbon black reported the CH 4 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 Nm 3 tail gas per tonne carbon black produced and an average reported CH 4 concentration of 0.425 percent by volume, the uncontrolled CH 4 emission factors is 28.7 kg CH 4 /tonne carbon black produced. Combustion flare efficiency for carbon black process flare systems was repo rted in the Draft IPPC LVIC BAT Document as 99.8 percent for carbon monoxide, and the same efficiency is assumed to apply to CH 4 . The CH 4 emission factor for carbon black production after application of combustion control is 0.06 kg CH 4 /tonne carbon black produced. An overall CH 4 emission factor of 0.11 kg CH 4 /tonne carbon black, based on company data, was reported 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 CH 4 emission factor of 0.03 kg CH 4 /tonne carbon black produced, based on measurement data after waste gas combustion using BAT (Thermische Nachverbrennung als Stand der Technik.)

T ABLE 3.24 C ARBON BLACK PRODUCTION T IER 1 CH 4 EMISSION FACTORS Process Configuration kilogram CH 4 /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 2 The Tier 2 methodology is based on mass balance calculations and therefore there are no emission factors associated with the methodology.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.81 

### TIER 3 For the Tier 3 method plant specific emissions may be estimated using Equations 3.20 through 3.22 for CO 2 , and using either Equation 3.26 or Equations 3.27 through 3.29 for CH 4 . The emission factors may be related to annual production for estimation of emissions betw een measurements when th ese 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. When using the Tier 3 method plant-specifi c 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 al so 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 less resource intensive approach. While feedstock consumption data may be hard to obtain sales data and national statistics may provide approximate pro duction volumes of the chemicals. 

### METHANOL
Emissions of CO 2 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 CO 2 from ethylene production may be calculated from specific feedstock consumption and product production activity data and carbon mass balance calculations. In order to create a complete mass balance for the ethylene production process and implement the Tier 2 methodology for ethylene production, all feedstocks and the 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 production of secondary products from the steam cracking process, the production of secondary products may be estimated using 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 produ cts, and will increase the uncertainty of the estimate, as performance of steam crackers may vary depending on site-specific conditions. For example, site-specific data reported for steam cr ackers 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 availa ble for all secondary products, the Tier 1 method can be applied instead of the Tier 2 method. Secondary products produced by the steam cracking process may recovered and transferred to a petrochemical plant or petroleum refinery for material reuse, recycled within the steam crack ing process as feedstock, or burned for energy recovery. Typically C4+ secondary products are recycled as feedstock or recovered for material reuse (BASF, 2006). Allocation of CO 2 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 to another process for material reuse. If data are not available for the disposition of CH 4 produced by the steam cracking process, the default assumption is that the CH 4 is burned for energy recovery within the steam cracking process and results in CO 2 emissions from the process. Steam crackers operated within the petrochemical industry may obtain the petrochemical feedstock for the ethylene production process directly from an adjacent petroleum refinery. Depending upon the feedstock and process operating conditions, steam crackers may also gene rate ‘backflows’ of hydrocarbon by-products that are returned to the adjacent refinery for further processing. Any CO 2 emissions from processing backflows at petroleum refineries are not included in the process CO 2 emission factors for the steam cracker ethylene production process, but are considered in the feed stock and carbon flow anal ysis for the process.Volume 3: Industrial Processes and Product Use

3. 82 2006 IPCC Guidelines for National Greenhouse Gas Inventories T ABLE 3.25 E THYLENE STEAM CRACKING FEEDSTOCK - PRODUCT MATRIX kg product/tonne feedstock Product Feedstock Naphtha Gas oil Ethane Propane Butane Others Hi g h Value Chemicals 645 569 842 638 635 645 Eth y lene 324 250 803 465 441 324
Pro py lene 168 144 16 125 151 168 Butadiene 50 50 23 48 44 50 Aromatics 104 124 0 0 0 104 Fuel g rade p roducts and backflows 355 431 157 362 365 355
H y dro g en 11 8 60 15 14 11 Methane 139 114 61 267 204 139 Ethane and p ro p ane after rec y cle 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; Cope rnicus Institute, April 2003, Table 2.2, Page 24



### ETHYLENE DICHLORIDE AND VINYL CHLORIDE MONOMER
Emissions of CO 2 from ethylene dichloride and vinyl chloride monomer production may be calculated from specific feedstock (ethylene) consump tion and product (ethylene dichloride) production activity data and carbon mass balance calculations. 

### ETHYLENE OXIDE
Emissions of CO 2 from ethylene oxide production may be cal culated 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 pro duction of secondary products (acetonitrile and hydrogen cyanide), 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.

T ABLE 3.26 S ECONDARY PRODUCT PRODUCTION FACTOR S FOR ACRYLONITRILE PRODUCTION PROCESS Secondary Product kg secondary pro duct/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 the event 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 ma ss balance approach to acrylonitrile producti on 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 not recovered as product and is burn ed for energy recovery to CO 2 . If no activity data are available concerning thermal treatment of the acetonitrile main absorber vent gas it may be assumed that the vent gas is thermally treated and combusted to CO 2 and is not vented to the atmosphere uncontrolled.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.83 

### CARBON BLACK
Emissions of CO 2 from carbon black production may be calculated from specific primary f eedstock (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 CO 2 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 methane and 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 CO 2 emissions from ‘other’ fuel combustion include industrial process off gases that are burned for energy recovery some adjustment to the energy statistics or to the CO 2 emissions calculation for petrochemical production would be needed to avoid double counting of the CO 2 emissions. 

### METHANOL There may be production of methanol from biogenic (renewable) sources. Such biogenic methanol may be incorporated into methanol national production sta tistics, which would result in overestimation of CO 2 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 refi ning processes or from petrochemical processes other than steam crackers. Such ethylene may be incorporated into ethylene national production statistics, which would result in overestimation of CO 2 emissions from steam cracker derive d 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 and other 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 to industry 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 the activity 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 Am erica 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 other products. 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 ethylene oxide 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 CO 2 emissions from fossil fuel derived carbon black. There also 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 CO 2 emissions from carbon black production within petroleum refineries should be reported along with other emissions from carbon black production within the chemical 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 pr oducts, waste gases, or acetyl ene may not be available,Volume 3: Industrial Processes and Product Use

3. 84 2006 IPCC Guidelines for National Greenhouse Gas Inventories which would result in underestimating of CO 2 emissions from carbon black pr oduction if a higher-tier carbon balance approach was used.


## 3.9.2.5 D EVELOPING CONSISTENT TIME SERIES
The emissions from petrochemical and carbon black production should be estimated using the same Tier and type of activity data for all years. Constructing a time series for emissions from petrochemical and carbon black production using plant specific meas urement activity data will give th e most accurate current emissions. However activity data on flaring and fu gitive emissions will most likely not be available for previous years. If no technology upgrades have taken place calculating a plant sp ecific 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 y ear 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 estimates and recalculations should follow the guidan ce in Volume 1, Chapter 5.


# 3.9.3 Uncertainty assessment Uncertainty assessments for each emissions factor and activ ity data applicable to each process are discussed in this section. Uncertainty ranges for the emission factors an d 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 produc ed and, for higher tier me thodologies, 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 for methanol production. If natural gas consumption activity data are not available then only an emission factor approach rather than a higher tier car bon 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 CO 2 feedstock consumption in methanol production plants that utilise CO 2 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 pr ocess (e.g., ethane, naphtha) and the types, quantities, and characteristics of products from the process (e.g., ethylene, propylene). Feedstock consumption and product production 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 and production 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 woul d be conducted by utilising the default yield table for the default feedstock. However, considering the wide vari ability in emission factors and yield factors among the feedstocks, the unavailability of specific feedstock consumption data would introduce significant uncertainty into the emissions calculations and feedstocks analysis. If spec ific 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 hi gher 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 the petrochemical plant to the [potentially adjacent] petroleum refinery and flows of by products to energy recovery or flaring. The unavailability of activity for refinery b ackflows would introduce uncertainty into the feedstocks analysis.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.85 

### 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 feedstock in the production process. If only activity data for ethy lene dichloride production are available, the emission calculation may be conducted using th e default [balanced] process product yield factor and default emission factor for the process. However, considering the vari ability in emission factors and yield factors for the oxychlorination process, direct oxidation process, and bala nced process, the unavailability of specific ethylene feedstock consumption data by process would introduce significant uncertainty into the emissions calculations 

### ETHYLENE OXIDE A main source of uncertainty for ethylene oxide productio n is the difficulty in determining activity data for the consumption of ethylene feedstock for ethylene oxide pr oduction. If ethylene consumption activity data are not available 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 th is case the feedstocks analysis would be conducted by utilising the default product yield factor. However, cons idering the range of reported product yield factors and emission factors for the ethylene oxide process, the un availability of specific ethylene feedstock consumption data would introduce significant uncertainty into the emissions calculations. 

### ACRYLONITRILE Sources of uncertainty for acrylonitrile production includ e 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 and acetonitrile from the process. If on ly activity data for acrylonitrile pr oduction are available, the emission calculation may be conducted using the default process configuration (assuming no acetonitrile recovery) and default emission factor for the proce ss. However, the assumption that acet onitrile is not recovered from the process introduces significant uncertainty in the emission and feedstocks calculations and may result in overestimation of emissions and underestimation of feedstocks flows from the acrylonitrile process. Activity data for national production of both acrylonitrile and acet onitrile from the acrylonitrile production process would allow application of the process-speci fic 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 cyanid e production from the acrylonitrile production process would allow utilisation of a higher-tier met hod, 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 secondar y 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 sta tistics and commodity statistic s, without any breakout of feedstock 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 in generic 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 coke production. Activity data may also not be available for other primary carbon black feedstocks (e.g., acetylene). Also, specific activity data may be available for natura l gas consumption as second ary 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 sp ecific 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 of activity 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 product yield may be assumed and the default emission factor ma y be applied. However, considering the variability in feedstock characteristics and origin, the unavailability of specific feedstock consumption and composition activity data would introduce significant uncertainty into the emissions and feedstocks calculations. If specific feedstock consumption and characteristics activity data an d associated carbon black production activity data areVolume 3: Industrial Processes and Product Use

3. 86 2006 IPCC Guidelines for National Greenhouse Gas Inventories available then a separate carbon balance and feedstoc ks analysis may be conducted for each feedstock and process using a higher tier method, which would reduce the uncertainty.



### UNCERTAINTY RANGES Uncertainty ranges for Tier 1 emission f actors and Tier 2 activity data and Ti er 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 by evaluating the range of available data. In many cases proc ess-specific data were available only for several plants; the relatively large uncertainty ranges are the result of the relatively few data available and the expected variability of process configurations and feedstock u tilisation efficiency among petr ochemical and carbon black plants.

T ABLE 3.27 U NCERTAINTY RANGES FOR EMISSION FACTORS AND ACTIVITY DATA Method Reference Factor Uncertainty Range Source
Tier 3 Direct measurement of fuel consumption together with gas composition samples for all substances - 5 to + 5 % Expert judgement by Lead Authors of Section 3.9, on the basis of discussions with national industry January 2005. Tier 1 Table 3.12 Methanol production CO 2 emission 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.
Tier 1 Methane Emission Factor for Methanol Production -80% to +30% Expert judgement by Lead Authors of Section 3.9 on the basis of Methanex plant data.
Tier 1 Table 3.14 Ethylene Production CO 2 Emission Factors -30% to +30% IPPC LVOC BAT Document, Figure 7.10, Tier 1 Table 3.15 Geographic Adjustment Factors For CO 2 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 CO 2 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 CO 2 Emission 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 CH 4 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 CO 2 Emission Factors -10% to +10% Expert judgement by Lead Authors of Section 3.9.
Tier 1 Table 3.21 Ethylene Oxide Production CH 4 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 CO 2 Emission Factors -60% to +60% IPPC LVOC BAT Document, Section 11.3.1.1, Table 11.2, Page 274.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.87 T ABLE 3.27 ( CONTINUATION ) U NCERTAINTY RANGES FOR EMISSION FACTORS AND ACTIVITY DATA Method Reference Factor Uncertainty Range Source Tier 1 Acrylonitrile Production CH 4 Emission Factors -10% to +10% Boustead, 2003b (Eco-Profiles of the European Plastics Industry Methodology I. Boustead, Report prepared for APME, July 2003, Page 40)
Tier 1 Table 3.23 Carbon Black Production CO 2 Emission Factors -15% to +15% Draft IPPC LVIC BAT Document, Table 4.11, Page 214
Tier 1 Table 3.24 Carbon Black Production CH 4 Emission Factors -85% to +85% Draft IPPC LVIC BAT Document, 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 Quality Assessment/Quality Control (QA/QC), Reporting and Documentation

3.9.4.1 Q UALITY 

## A SSESSMENT 

## /Q UALITY 

## C ONTROL
Quality Assurance/Quality Control fo r emissions factors and activity data involves methods to improve the quality 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 ap plicable, if Tier 2 or Tier 3 met hods 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 Ti er 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 to vary by more than about +/- 10 percent year to year, barring significant changes in the overall economic output of the country, the construction of new petrochemical production capacity, or other similar factors. If the activity data vary by more than about +/-10 percent year to year, it is good practice to assess and document the country-specific conditions that account for the differences. 

### Evaluation of Tier 1 me thod emission factors Inventory compilers that develop country-specific emission factors for petroc hemical and carbon black production and apply the Tier 1 method should assess whether the estimated emission factors are within the range of the default emission factors an d process-specific emission factors provid ed for the Tier 1 method in this guidance. 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 pr ocess configuration differs from that for the emission factors reported in this guidance; the feedstock is a uni que material not considered in this Guidance.) Inventory compilers should also ensure that th e country-specific emission factors are consistent with the values derived from analysis of the process chemis try. For example, for methanol production from natural gas the carbon content of the CO 2 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 the emission factors are outside of the estimated ranges, it is good practice to assess and document the plant-specific conditions that accoun t 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 data characteristics 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.Volume 3: Industrial Processes and Product Use

3. 88 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### 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 the flow rates or carbon contents of such process flows could result in significant deviation of the estimated CO 2 emissions from the actual CO 2 emissions. The quality of Tier 2 mass balance calculation results are generally more dependent upon the quality of the activity data th an are Tier 1 calculation results because in general a greater number of activity data need to be applied to the Tier 2 method than to the Tier 1 method. Therefore, it is good practice to assess and document the quality of each activity data applied to the Tier 2 method and the completeness 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 me thod plant-specific data The Tier 3 method is based on the applicatio n of plant-specific emissions data. It is good practice for inventory compilers that conduct audits of pl ant-specific emissions estimates used in the inventory. This involves evaluating whether the plant-specific data are representativ e of plant emissions and, if plant-specific data for a specific plant are applied to the national inventory, eval uating whether the plant-speci fic 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 other plants in the country producing the same petrochemical (e.g., if the feedstock differs or the process configuration differs) then the plant-specific data should not be applied to the overall inventory but only to the activity data for the specific plant. If emission measurements from indi vidual plants are collected, inventory compilers should ensure that the measurements were made according to recognised national or international standards and the quality control methods were applied to the emissions measurement. Quality control procedures in use at the plant 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 ge nerated by petrochemical production processes are attributed to the IPPU Sector sour ce category which produces them, and ar e 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 co mbusted within an Energy Sector source category, the corresponding emissions are reported as fuel combustion emissions rather than as industrial process emissions. This means that if the combustion emissions occur with in the IPPU Sector source category which produced the off gases, then the emissions are reported as industrial pr ocess emissions attributed to that IPPU Sector source category. However, if the o ff gases are transferred out of the process to another source category in the IPPU Sector or a source category in the En ergy Sector, then the emissions from the combustion of the off gases are reported as fuel combustion emissions within that source category. When the total emissions from the combustion of the off gases are calculated, the quantity tran sferred to and reported in the Energy Sector and the quantity transferred to and reported in a different IPPU Sector source categor y should be clearly quantified in the IPPU Sector source category calculatio ns and in the Energy Sector sour ce 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 emissi on factor and calculation are based. 

### METHANOL The amount of methanol produced, the amount of natural gas feedstock consumed in methanol production, and the amount of supplemental CO 2 feedstock consumed in methanol production are to be reported when available.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.89 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 productio n and the amounts of ethy lene and each other primary 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 that the default process configuration is not used. 

### ETHYLENE OXIDE The amount of ethylene oxide produced and ethylene feedstock consumed in ethylene oxide 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 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 (c arbon content) of each primary and secondary 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.Volume 3: Industrial Processes and Product Use

3. 90 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

# Annex 3.9A Feedstock-product flow diagrams

Figure 3.11 Methanol production feedstock-product flow diagram

Secondary Feedstock

Carbon Dioxide

Primary Feedstock Natural Gas Steam Reforming Process

Methanol Product Methanol Production Process

Methanol Product Purification Flare CO 2

Vent Gas CO 2

Energy Recovery

Process Vent Gas Process Purge Gas Process Steam

Figure 3.12 Ethylene dichloride produc tion feedstock-product flow diagram

Primary Feedstock Ethylene

Primary Feedstock Ethylene Vent Gas Incinerator

Oxychlorination Process Reactor

Direct Chlorination

Process Reactor Ethylene Dichloride Purification Process

Ethylene Dichloride Product Flare CO 2 Vent Gas CO 2

Chlorinated Hydrocarbons Process Vent GasChapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.91 Figure 3.13 Ethylene oxide production feedstock-product flow diagram

Primary Feedstock Ethylene Energy Recovery

Ethylene Oxide Reactor Process Ethylene Oxide Product Ethylene Oxide Recovery Process Flare CO 2 Vent Gas CO 2

Process Vent Gas

Figure 3.14 Acrylonitrile production feedstock-product flow diagram

Primary Feedstock Propylene Energy Recovery

Ammoxidation Reactor Process Absorber Vent Gas

Acrylonitrile Product Purification

Product Recovery Process Flare CO 2 Vent Gas CO 2

No

Hydrogen Cyanide By-product Acetonitrile By-product

Acrylonitrile Product

Hydrogen Cyanide Recovery? Acetonitrile By-product Recovery?

No

Yes Yes

Figure 3.15 Carbon black production feedstock-product flow diagram

Primary Feedstock Carbon Black Feedstock Energy Recovery

Furnace Black Process Reactor Carbon Black Product Dryers Flare CO 2 Vent Gas CO 2

Carbon Black Product Secondary Feedstock Natural Gas Process Vent GasVolume 3: Industrial Processes and Product Use

3.92 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

# 3.10 FLUOROCHEMICAL PRODUCTION

3.10.1 HFC-23 emission from HCFC-22 production

3.10.1.1 I NTRODUCTION
Trifluoromethane (HFC-23 or CHF 3 ), is generated as a by-product during the manufacture of chlorodifluoromethane (HCFC-22 or CHClF 2 ). 3 Materials such as HFC-23 (and other HFCs, PFCs and SF 6 ) are not 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 re leased from HCFC-22 plants was at most 4 percent of the production of HCFC-22 (U.S. EPA, 2001), in the ab sence of abatement measures. There are a small number of 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 ISSUES

CHOICE OF METHOD There are two broad measurement approaches to estimating HFC-23 emissions from HCFC-22 plants. These are described 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 the sum 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 nati onal output of HCFC-22. Accounting for HFC-23 emissions is not simply mechanistic but requires information on the process operations responsible for producing and emitting HFC-23, so that the most appropriate methodology and factors can be adopted. Therefore, it is good practice , 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 b ecause they rely on data that are only available from plants. 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 in a country. Tier 3 plant emission measur ements are the most accurate, followed by Tier 2 measurements based on plant efficiencies. Direct measurement is significan tly more accurate than Tier 1 because it reflects the conditions specific to each manufacturing facility. In most cases, th e 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. The Tier 1 (default) method should 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 process optimization will need to keep accurate HFC-23 generation data as part of this optimization, so plant-specific data 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 opera tion. The tiers of methodology provide estimates for the quantity of HFC-23 that is produced and the share of production that is ultimately emitted depends on the length of time that the destruction facility is not operated. For facilities using abatement techniques such as HFC-23 destruction, verification of the abatement e fficiency is also done routinely. It is good practice to subtract abated HFC-23 emissions from national estimates where the abatem ent has been verified by process records on every plant.

3 HCFC-22 is used as a refrigerant in several different a pplications, as a blend component in foam blowing, and as a chemical feedstock for manufacturing synthetic polymers.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.93 

### Tier 1 In 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 disper sive uses, as re ported under the Montreal Protocol, and feedstock uses, which are reported separately to the Ozone Secretariat). See Equation 3.30.

E QUATION 3.30 T IER 1 CALCULATION OF HFC-23 FROM HCFC-22 ( PRODUCED ) USING DEFAULT FACTOR

22 23

− − • = HCFC default HFC P EF E

Where:
E HFC-23 = by-product HFC-23 emissions from HCFC-22 production, kg
EF default = HFC-23 default emission factor, kg HFC-23/kg HCFC-22
P HCFC-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 2 In the Tier 2 methodology, the HFC-23 emission factor is derived from reco rds of process effi ciencies and used in the calculation shown as Equation 3.31. This is a material balance approach and relies on calculating the difference between the expected production of HCFC-22 and the actual production and then assigning that difference 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

.
E QUATION 3.31 T IER 2 CALCULATION OF HFC-23 FROM HCFC-22 ( PRODUCED ) USING FACTOR ( S ) CALCULATED FROM PROCESS EFFICIENCIES

released HCFC calculated HFC F P EF E • • =

− − 22

23
Where:
E HFC-23 = by-product HFC-23 emissions from HCFC-22 production, kg
EF default = HFC-23 calculated emission factor, kg HFC-23/kg HCFC-22
P HCFC-22 = total HCFC-22 production, kg
F released = Fraction of the year that this stream wa s released to atmosphere untreated, fraction The emission factor can be calculated from both the carbon efficiency (Equation 3.32) and th e fluorine efficiency (Equation 3.33) and the value used in Equation 3.31 should normally be the average of these two values unless there are overriding considerations (suc h as a much lower uncertainty of one of the efficiency measures) that can be adequately documented. Annual av erage carbon and fluorine balance e fficiencies are features of a wellmanaged HCFC-22 plant and are either normally available to the plant operator or may be obtained by examination of process accounting records. Similarly, if th ere is a vent treatment syst em, the length of time that this was in operation, and treating the vent stream fro m 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 for potentially dispersive uses.

E QUATION 3.32 C ALCULATION OF HFC-23 EMISSION FACTOR FROM CARBON BALANCE EFFICIENCY 

## ( ) FCC F CBE EF loss efficiency balance carbon • • − = 100 100

_
Where:
EF carbon_balance = HFC-23 emission factor calculated from car bon balance efficiency, kg HFC-23/kg HCFC-22 CBE = carbon balance efficiency, percentVolume 3: Industrial Processes and Product Use

3.94 2006 IPCC Guidelines for National Greenhouse Gas Inventories F efficiency loss = factor to assign effici ency loss to HFC-23, fraction FCC = factor for the carbon content of this component (= 0.81), kg HFC-23/kg HCFC-22 and

E QUATION 3.33 C ALCULATION OF HFC-23 EMISSION FACTOR FROM FLUORINE BALANCE EFFICIENCY 

## ( ) FFC F FBE EF loss efficiency balance fluorine • • − = 100 100

_
Where:
EF fluorine_balance = HFC-23 emission factor calculated from fluorine balance efficiency, kg HFC-23/kg HCFC-22 FBE = fluorine balanc e efficiency, percent
F efficiency loss = factor to assign effici ency 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 is used, the factor should have been established by the process operator. By default, the value is 1; that is all of the loss in efficiency is due to co-pr oduction 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 mol ecular compositions of HFC-23 and HCFC-22 and are common to all HCFC-22 plants at 0.81 for carbon and 0.54 for fluorine.



### Tier 3 Tier 3 methodologies are potentially the most accurate. The Tier 3 methodologies provid ed here give equivalent results and the choice between them will be dictated by the information available in individual facilities. In each case, 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 and continuously – 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):

E QUATION 3.34 T IER 3a CALCULATION OF HFC-23 EMISSIONS FROM INDI VIDUAL PROCESS STREAMS ( DIRECT METHOD ) 

### ∑ ∑ ∫ • =

− i j t ij ij HFC f C E 23 [ 

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

Where:
E HFC-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:

E QUATION 3.35 T IER 3b CALCULATION OF HFC-23 EMISSIONS FROM INDI VIDUAL PROCESS STREAMS ( PROXY METHOD ) 

### ∑ ∑ ∫ =

− i j t ij HFC E E 23 [ 

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

Where:
E HFC-23 = total HFC-23 emissions: E i,j are the emissions from each plan t and stream determined by the proxy 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:Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.95 E QUATION 3.36 T IER 3c CALCULATION OF HFC-23 EMISSIONS FROM INDI VIDUAL PROCESS STREAMS ( BY MONITORING REACTOR PRODUCT ) 

### ∑ ∫ • =

− i t i i HFC P C E 23 [ 

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

Where:
E HFC-23 = total HFC-23 emissions: P i is the mass flow of HCFC-22 produ ct from the plant reactor at the plant i , and C i is the concentration of HFC-23 relativ e 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 the vent at an individual plant. So that the quantity emitted to atmosphere is the mathematical product of the mass concentration of the component in the stream, the flowrate of the total stream (in units compatible with the mass concentration) and the length of time that this flow occurred:

E QUATION 3.37 T IER 3a CALCULATION OF ‘ INSTANTANEOUS ’ HFC-23 EMISSIONS IN AN INDIVIDUAL PROCESS STREAM ( DIRECT METHOD )


### t f C E ij ij ij 

### • • =

Where:
E ij = ‘instantaneous’ HFC-23 emissions from process stream j at plant i , kg C ij = the concentration of HFC-23 in the gas stream actually vented from process stream j at plant i , kg HFC-23/kg gas
f ij = the mass flow of the gas stream from process stream j at plant i (generally measur ed volumetrically and converted into mass flow using standard process engineering methods), kg gas/hour t = 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 are measured directly in this tier, it is not necessary to have a separate term for material recovered, unlike Tiers 3b and 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 this calculation. If it is necessary to estimate the quantity dest royed at each facility, the operator should calculate this based 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.Volume 3: Industrial Processes and Product Use

3.96 2006 IPCC Guidelines for National Greenhouse Gas Inventories E QUATION 3.38 T IER 3b CALCULATION OF HFC-23 EMISSIONS IN AN INDIVIDUAL PROCESS STREAM ( PROXY METHOD )

ij ij ij ij ij 

### R t POR F S E

− • • • =

Where:
E ij = the mass emission of HFC-23 in vent stream j at plant i , kg S ij = the standard mass emission of HFC-23 in vent stream j at plant i per ‘unit’ of proxy quantity, such as process operating rate (described in Equation 3.39, below), kg/‘unit’
F ij = a dimensionless factor relating the measured standard mass emission rate to the emission rate at the actual plant operating rate. In many cases, the frac tion produced is not sensitive to operating rate and F i is unity (i.e., the emission rate is proportional to operating rate). In other cases the emission rate is a more complex function of the operating rate. In all cases F i 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 conti nuous measurement is desirable. POR ij = 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 co nsistent between the plant trial establishing the standard 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.
R ij = the quantity of HFC-23 recovered for vent stream j at plant 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 for ODS substitutes in Chapter 7 of this volume.

E QUATION 3.39 T IER 3b CALCULATION OF STANDARD EMISSION FOR PROXY METHOD

ij T ij T ij T ij T 

### POR f C S

, , , , 

### •

= Where (for each test T): S ij = the standard mass emission of HFC-23 in vent stream j at plant i, kg/‘unit’ (in units compatible with the factors in Equation 3.38, see POR T,ij below) C T,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 POR T,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
m 3 /hour of feedstock) 

### Tier 3c It is a relatively simple procedure to monitor the concen tration of HFC-23 in the product of a reaction system relative to the amount of HCFC-22. Th is 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 no vent treatment to abate emissions, this is a simple proced ure. 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 vents and the outgassing of aqueous streams. The latter, especia lly, may not be passed to the destruction facility. If all potential vent streams are not treated, the method cannot be used.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.97 E QUATION 3.40 T IER 3c CALCULATION OF HFC-23 EMISSIONS FROM AN INDIVIDUAL FACILITY BY IN - PROCESS MEASUREMENT

i F j i i 

### R t P C E

− • • =

Where:
E i = HFC-23 emissions from an individual facility i , kg C i = the concentration of HFC-23 in the reactor product at facility i , kg HFC-23/kg HCFC-22
P i = the mass of HCFC-22 produced at facility i while this concentration applied, kg

t F = the fractional duration during which this HFC-23 is actually vented to the atmosphere, rather than destroyed, fraction
R i = 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 th e 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 indivi dual reaction systems. HFC-23 that is recovered for use as chemical feedstock should be subtracted from the total quantity estimated here. In summary, 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 calcu lations. 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 ne t emissions before these are added together in the national estimate.Volume 3: Industrial Processes and Product Use

3.98 2006 IPCC Guidelines for National Greenhouse Gas Inventories Figure 3.16 Decision tree for HFC-23 emissions from HCFC-22 production (or other similar by-product emissions from fluorochemical production)

Start

Are plant-level HFC-23 measurement data available?

Is the Fluorochemical Production a key category 1

,

and is this subcategory significant?

No No Obtain plant-level HFC23 measurement data. Estimate emissions by aggregating plant-level

measurements, and estimates for plants without m easurements 2

,

adjusting for HFC-23 destruction.

Aggregate plant-level emissions. Box 2: Tier 2 Box 5: Tier 3

Note: 1. See Volume 1 Chapter 4, Methodological Choice and Identifi cation of Key Categories (noting Section 4.1.2 on limited resource s), 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 applie d to the remainder to ensure c omplete coverage. Yes

Yes Are plant-level HCFC-22 production data available?

Aggregate plant-level emissions, adjusting for

HFC-23 destruction. Box 3: Tier 2 Yes

Yes Does any HFC-23 destruction take place?

Calculate plantlevel emissions using the Tier 2 emission factor.

Collect national HCFC-22 production data. Calculate plant-level emissions using plant-level data and

Tier 3a, 3b or 3c

methodology. Yes

No

No Estimate emissions using the default emission factor. If the emissions are estimated at the plan t level, aggregate plant-level emissions. Estimate emissions by aggregating plant-level

measurements 2 , and estimates for plants without measurements.

Are plant-level efficiencies available? Is it possible to document any HFC-23 destruction?

No Yes

Box 1: Tier 1 Box 4: Tier 3 No

It is good practice to use the Tier 3 method if possible. Direct measurement is significantly more accurate than Tier 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 de struction, verification of the abatement efficiency is also done routinely. The Tier 1 (default) method should be used only in rare 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.)Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.99 

### CHOICE OF EMISSION FACTORS There are several measurement options within the Tier 3 method relating to the location and frequency of the sampling. In general, direct measur ement of the emissions of HFC-23 ma y provide the high est 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, th e frequency of measurement must be high enough to represent the variability in the process (e.g., across th e life of the catalyst). Issues related to measurement frequency are summarised in Box 3.14, Plant Measur ement Frequency. General advice on sampling and representativeness is provided in Volume 1, Chapter 2. In cases where plant-specific measurements or sampling are not available and Tier 1 methods are used, the default 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 observations of 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 co mpletely 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 desi gn of recent plants, suggesting a defa ult 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 more accurate assessments, the actual emi ssions should be determin ed by Tier 2 or Tier 3 methodology and, if necessary, assigned to previous years using the guidance provided in Chapter 7 of this volume.

T ABLE 3.28 HFC-23 DEFAULT EMISSION FACTORS Technology Emission Factor (kg HFC-23/kg HCFC-22 produced) Old, unoptimised pl ants (e.g., 1940s to 1990/1995) 0.04 Plants of recent design, no t 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) Down to 0.014 Down to zero

4 The global average is calculated from the change in atmos pheric concentration of HFC-23. It does not discriminate

between plant emissions, which range from nothing to greater than 4 pe rcent of the HCFC-22 production.Volume 3: Industrial Processes and Product Use

3.100 2006 IPCC Guidelines for National Greenhouse Gas Inventories B OX 3.14 P LANT MEASUREMENT FREQUENCY The accuracy and precision of the estimates of annual HFC-23 emissions depend on the number of samples (the frequency of sample collection) t ogether with the accuracy of measurement of flowrates 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, the more frequently plants need to measure. As a general rule, sampling and analysis should be repeated whenever a plant make s any significant process changes. Before choosing a sampling frequency, the plant should set a goal for accuracy an d use statistical tools to determine the sample size necessary to achieve the goal. For example, a study of HCFC-22 producers indicates that sampling once per day is sufficient to achiev e an extremely accurate annual estimate. This accuracy 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 severalways 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 pl ant should describe how the HCFC-22 production rate is determined. In some circumstances, producers may cons ider plant production data to be confidential. For national-level activity data, submission of HCFC-22 production data is already required under the Montreal Protocol. 

### COMPLETENESS It 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 plan t 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 SERIES Emission of HFC-23 from HCFC-22 production should be estimated using the same method for the entire time series and appropriate emission factors. If data for any years in the time series are unavailable for the Tier 3 method, these gaps should be f illed according to the guidance prov ided in Volume 1, Chapter 5.


## 3.10.1.3 U NCERTAINTY ASSESSMENT

TIER 1 Unlike the other Tiers, where uncertain ties are based on measurements and statistics, Tier 1 uncertainties are assessed 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 this magnitude 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 ca rbon and fluorine uncertain ties are the same. Where the uncertainties in carbon and fluorine efficiency differ significantly (enou gh to cause a material difference to the 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 produci ng about 4 percent HFC-23, the carbon efficiency is in the region of 95 percent and the fluorine efficiency 92 pe rcent. If these efficiencies can be measured to within 1 percent, then the error in the Tier 2 HFC-23 estimate wo uld be less than 20 percent. Estimating efficiencies to this degree of accuracy will require rigorous accounting procedures and th at all raw materials and product for sale 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.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.101 

### TIER 3 For HFC-23, the Tier 3 method is significantly more accur ate 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 both cases, 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 subd ividing uncertainty has no validity. Uncertainty of the estimate is expressed as a coefficien t of variance (percent) and, for each of these streams, there will be an uncertainty as a consequence of uncer tainties in measured concentration and flowrate and uncertainty 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 OCUMENTATION QUALITY ASSURANCE/QUALITY CONTROL
It is good practice to conduct quality control checks as outlined in Volume 1, Chapter 6, and an expert review of the 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 emissi ons 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 indi vidual plant estimates (e.g., an extreme outlier may be accounting for an unreasonabl e 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 si gnificant 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 plant measurements. If the measurement practi ces fail this criterion, then the use of these emissions data should be carefully evaluated. It is also possi ble that, where a high standard of measurement and QA/QC is in place at sites, 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 of sample 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. Fo r example, emissions measurement within the process itself 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 measuremen t 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:Volume 3: Industrial Processes and Product Use

3.102 2006 IPCC Guidelines for National Greenhouse Gas Inventories • To provide for completely transparent reporting, emissions of HFC-23 from HCFC-22 production should be reported 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

• The use of the Tiers 2 and 3 methods would mean th at 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 cons idered to be of commerci al confidence as it does not reveal the levels of production of HCFC-22 without detailed and confid ential knowledge of the individual manufacturing facility

.

• The application of the Tier 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 informatio n. In such cases, steps should be taken to protect confidentiality through, for example, the aggregation of all HFC emi ssions. 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 calculated using different methodologies, it is not possible to recalculate the HC FC-22 production fr om these data alone and there should be no problems concerning confidentiality.


# 3.10.2 Emissions from production of other fluorinated compounds

3.10.2.1 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-product emissions of SF 6 , CF 4 , C 2 F 6 , C 3 F 8 , C 4 F 10 , C 5 F 12 and C 6 F 14 were reported for a fluo rochemical plant (UNFCCC, 2005). Other examples include the release of by-product CF 4 from the production of CFC-11 and 12 or of SF 6 from the production of uranium hexafluo ride in the nuclear fuel cycle. Emissions of a chemical occur during its production and distribution or as a by-product during the production of a 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-product and fugitive emissions are calculated in the same way. In this section, emissions associated with use are not addressed specifically, being counted in the emissions related to consumption (see Chapters 4.5, 6, 7 and 8 in this volume). Typically, fluorochemicals may be released from chemical processes involving a broad range of technologies 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 SF 6 production

• Halogen Exchange Processes to make low boiling PFCs like C 2 F 6 and CF 4 , HFC 134a and 245fa

• NF 3 manufacturing by direct fluorination

• Production of uranium hexafluoride

5 This list is illustrative.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.103 • 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 SF 6 require elemental fluorine, generated electrochemically. In ‘electro chemical fluorination’ processes, the fluorine is not separated but makes the desired product in the electrochemical cell. In other processes it is separated and subsequently used, either as the elemental gas or as a component of a carrier system, such as CoF 3 . 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 emissive plants 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 anhydrous hydrogen fluoride can therefore be us ed as a means of tracing significant producers of fluorochemicals. Further enquiries (see Figure 3.17) can then el ucidate whether or not there are sign ificant fluorochemical greenhouse gas emissions.


## 3.10.2.2 M ETHODOLOGICAL ISSUES

CHOICE OF METHOD
It is good practice to choose the method using the decision tree shown in Figure 3.17. If the Category 2B9 Fluorochemical 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 chemi cals. The number of major producers of these fluorinated greenhouse gases is quite small: in the case of SF 6 , there are globally about 6 companies with about 10 production facilities world-wi de (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 1 In 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, SF 6 and other fluorinated greenhouse gases.

E QUATION 3.41 T IER 1 CALCULATION OF PRODUCTION - RELATED EMISSIONS

k k default k P EF E • =

, Where:
E k

= production-related emissions of fluorinated greenhouse gas k , kg
EF default, k = default emission factor, kg/kg
P k

= total production of fluorinated greenhouse gas k , kg Problems of confidentiality arising from reporting specific component data can be circumvented by providing a single number for total national emissions of each HFC, PFC and SF 6 . This may be facilitated if data are collected by a third party and reported only as this total.



### Tier 2 The method based on process efficiencies, which works for HFC-23 emissions from HCFC-22 plants, is of less value for other types of plants. This is due in part to the lower inefficiency expected from these other by-product emissions; the uncertainty in measurem ent of efficiencies is likely to be much greater than the by-product emission factor. Furthermore, a range of by-products may be responsible for process in efficiency (unlike the case for HCFC-22 where one by-product predominates). Howeve r, production efficiency data should exist for each process 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).Volume 3: Industrial Processes and Product Use

3.104 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### Tier 3 The Tier 3 methodology is potentially the most accurate es timate and is the sum of factory specific emissions of each by-product fluorinated greenhouse gas determined us ing standard methods to estimate the composition and flowrate of gas streams actually vented to atmosphe re after any abatement technology. In this case:

E QUATION 3.42 T IER 3 DIRECT CALCULATION OF PRODUCTION - RELATED EMISSIONS 

### ∑ ∑ ∫ • = i j t ijk ijk k f C E [ 

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

Where:
E k

= 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 a more easily (or accurately) measurable parameter, such as feedstock flow rate, as described in Equation 3.35 in Section 3.10.1:

E QUATION 3.43 T IER 3 PROXY CALCULATION OF PRODUCTION - RELATED EMISSIONS 

### ∑ ∑ ∫ = i j t ijk k E E [ 

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

Where:
E k

= total production-related emissions of fluorinated greenhouse gas k : E ijk = the emissions of

fluorinated greenhouse gas k from each plant and stream determin ed by the proxy methods, described in 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) based on the ideal gas law, temperature, pressure and compos ition, 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 the abatement technology is or is not operating and only those that lead to actual emissions should be summed and reported.



### CHOICE OF EMISSION FACTORS Tier 3 relies on measurements of the quantities of individual materials that are released into the atmosphere and neither 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, is suggested for HFCs and PFCs, based on data supplied to AFEAS (2004). There is a wide range of substances that may potentially be released. However, the AFEAS data showed that the components that were lost during production of a particular fluorochemical had, in genera l, radiative forcing propertie s similar to those of the desired 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 SF 6 , based on German experience, a default emission factor of 0.2 percent of the total quantity of SF 6 produced is suggested for those countries in which the predominant end use does not require highly purified SF 6 gas (e.g., electrical equipment, insulated windows) (Preisegger, 1999). Based on experience in Japan, in countries where the major uses require highly purified SF 6 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 wher e no abatement measures are employed. If the quantity of gas emitted to the atmosphere is reduced by, for example, thermal oxidation of the vent stream, the quantity emitted should be adjusted to account fo r the destruction efficiency of the oxi diser 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 destruct ion process will have a greater effect on emissions and should be recorded.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.105 Figure 3.17 Decision tree for emissions of fl uorinated greenhouse gases from production processes, applicable to both fugitive and by-product emissions

Start

Are detailed data available on plant-specific estimates?

Are national activity data available? No

Collect national activity data. Sum data for each greenhouse gas from plants, taking account of

abatement (Tier 3).

Estimate emissions from

fluorochemical plants adjusting for abatement (Tier 1).
Box 2: Tier 1 Box 5: Tier 3

Note: 1. See Volume 1 Chapter 4, Methodological Choice and Identification of Key Categorie s (noting Section 4.1.2 on limited resource s), 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, this is the only use for Tier 2. 3. Data may be collected as a country study by a third party in order to preserve confidentiality. Yes Is Fluorochemical Production a key category , and is this production process/gas significant 1,2 ? Yes

Collect emissions data from plants. 3 Compile a list of all

fluorochemical manufacturers.

No

Yes

Estimate emissions from

fluorochemical plants (Tier 1). Is there abatement of emissions?

Box 1: Tier 1 No

Yes

No



### CHOICE OF ACTIVITY DATA Again, activity data has no role in the Tiers 3 and 2 estim ates, which are based on measurements. For Tier 1, the activity 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 not available. Thus, good practice is to use the same default factor as for new production.Volume 3: Industrial Processes and Product Use

3.106 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### 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 emissi ons from such entities provide a sizeab le contribution to total national emissions. 

### DEVELOPING A CONSISTENT TIME SERIES Both by-product and fugitive emissions of fluorocompounds from production processes should be estimated using the same method for the entire time series and appropriate emission factors. If data for any years in the time series are unavailable for the Tier 3 method, these ga ps 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 statistically combined with the uncertainty in the default emission f actor. 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 are maintained and that production is monitored by weight. The actual emission factor may range from well in excess of the default value to zero. Th e default uncertainty of the default em ission 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 identical to that described for HFC-23 from HCFC-22. In the Tier 2 methodology, the uncertainty both of the measurements of efficiencies and the assignment of losses to individual compounds should be assessed. Because these are liable to produce a much larger uncertainty than th at from Tier 3, the utility of Tier 2 is likely to be limited to assessing whether or not by-product fluoro chemical emissions are a si gnificant subcategory under key category

. 

## 3.10.2.4 Q UALITY 

## A SSURANCE 

## /Q UALITY 

## C ONTROL 

## (QA/QC), R EPORTING AND 

## D OCUMENTATION QUALITY ASSURANCE/QUALITY CONTROL
It is good practice to conduct quality control checks as outlined in Volume 1, Chapter 6, and an expert review of the 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 this source category. Inventory compilers are encouraged to use higher tier QA/QC for key categories as identified in Volume 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 based on 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 wher e there are limited numbers of ma nufacturers. In these cases more aggregate reporting of total national emissions may be necessary. If survey response s 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 tr ansparent and steps in their calculation may be retraced.Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.107 

## References
SECTIONS 3.2 - 3.8 Ashford, R.D. (1994). Ashford’s Dictionary of Industrial Chemicals, Wavelength Publications Ltd, London England. Austin, G.T. (1984). Shreve’s Chemical Process Industries, Fifth Edition, McGraw-Hill, Inc., USA. Babusiaux, P. (2005). Note on production of Glyoxa l and Glyoxylic acid, Clariant, Lamotte, France. Bockman, O. and Granli, T. (1994). ‘Nitrous oxide from agriculture’. Norwegian Journal of Agricultural Sciences , Supplement No. 12. Norsk Hydro Research Centre, Porsgrunn, Norway. Bouwman, A.F., van der Hoek, K.W. and Olivier, J.G.J. (1995). ‘Uncertainties in the global source distribution of nitrous oxide’. Journal of Geophysical Research , 100:D2, pp. 2785-2800, February 20, 1995. Burtscher, K. (1999). Personal communication between Kurt Burtscher of Federal Environment Agency of Austria and plant operator of chemical industry in Linz, Austria, 1999. Chemlink (1997). Website http://www.chemlink.com.au/titanium.htm . Chemlink Pty Ltd ACN 007 034 022. Publications 1997. Choe J.S., Gook, P.J. and Petro celli, F.P. (1993). Developing N 2 O abatement technology for the nitric acid industry. Paper presented at the 1993 ANPSG Conf erence, Destin, Florida, USA, 6 October, 1993. Cook, P. (1999). Personal communication between Phillip Cook of Air Products and Chemicals, Inc., USA, and Heike Mainhardt of ICF, Inc., USA. March 5, 1999. Cotton, F.A. and Wilkinson, G. (1988). Advanced In organic Chemistry, 5th Editio n, ISBN 0-471-84997-9. Wiley, New York, USA. de Beer, J., Phylipsen, D. and Bates, J. (2001). Economic Evaluation of Sectoral Emission Reduction Objectives for Climate Change: Economic Evaluation of Carbon Dioxide and Nitrous Oxide Emission Reductions in Industry in the EU – Bottom-up Analysis, Contribution to a Study for DG Environment, European Commission by Ecofys Energy and Environment, AEA Technology Environment and National Technical University of Athens. Environment Canada (1987). Review of the Canadian Fer tiliser Industry and Evaluation of Control Technology, Conservation and Protection Report EPS 2/AG/1. EFMA (2000a). European Fertilizer Manufacturers’ Association, Best Available Techniques for Pollution Prevention and Control in the European Fertilizer Indu stry: Production of Ammonia, Booklet No. 1 of 8, European Fertilizer Manufactur ers’ Association, Brussels. EFMA (2000b). European Fertilizer Manufacturers’ Association, Best Available Techniques for Pollution Prevention and Control in the European Fertilizer Indu stry: Production of Nitric Acid, Booklet No. 2 of 8, European Fertilizer Manufactur ers’ Association, Brussels. EFMA (2000c). European Fertilizer Manufacturers’ Association, Best Available Techniques for Pollution Prevention and Control in the European Fertilizer Industry: Production of Ur ea and Urea Ammonium Nitrate, Booklet No. 5 of 8, European Fer tilizer Manufacturers’ Association, Brussels. EIPPCB (2004a). European Integrated Pollution Prevention and Control Bureau, Draft Reference Document on Best Available Techniques in the Large Volume I norganic Chemicals, Ammonia, Acids and Fertilisers Industries, Draft March 2004, European Commission Directorate General JRC, Joint Research Centre, Institute for Prospective Technological Studies, Spain. EIPPCB (2004b). European Integrated Pollution Prevention and Control Bureau, Draft Reference Document on Best Available Techniques in the Large Volume I norganic Chemicals-Solid and Others Industry, Draft August 2004, European Commission Directorate Gene ral JRC, Joint Research Centre, Institute for Prospective Technological Studies, Spain. Hocking, M. B. (1998). Handbook of Chemical Technology and Pollution Control, Academic Press USA. 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., Grig gs D.J. Callander B.A. (Eds). Intergovernmental Panel on Climate Change (IPCC), IPCC/OECD/IEA, Paris, France. Japan Environment Agency (1995). Study of Emission Factors for N 2 O from Stationary Sources.Volume 3: Industrial Processes and Product Use

3.108 2006 IPCC Guidelines for National Greenhouse Gas Inventories Kirk-Othmer (1999). Concise Encyclopedia of Chemical Technology, Fourth Edition, John Wiley & Sons, Inc. USA. Lowenheim, F.A. and Moran, M.K. (1975). Faith, Keyes, and Clark’s Industrial Chemicals, Fourth Edition, John Wiley & Sons, Inc. USA. Olivier, J. (1999). Personal communica tion between Jos Olivier of National In stitute of Public Health and the Environment (RIVM), The Netherlands and Heike Mainhardt of ICF, Inc., USA. February 2, 1999. Olsen, S.E. (1991). Kalsiumkarbid og CO2, STF34 A91142. SINTEF. Perez-Ramirez, J., Kapteijn, F., Shoffel, K. and Moulijn, J. A. (2003). ‘Formation and control of N 2 O in nitric acid production: Where do we stand today?’, Applied Catalysis B: Environmental 44 , pp.117-131, Elsevier Science B.V. Raaness, O. (1991). Silisiumkarbid og CO 2 , STF34 A91134. SINTEF 1991. Reimer, R.A., Slaten, C.S., Seapan, M. , Koch, T.A. and Triner, V.G. (1999). ‘Implementation of Technologies for Abatement of N 2 O Emissions Associated with Adipic Ac id Manufacture. Proceedings of the 2nd Symposium on Non-CO 2 Greenhouse Gases (NCGG-2), Noordwijkerhout, The Netherlands, 8-10 Sept. 1999, Ed. J. van Ham et al., Kluwer Academic Publishers, Dordrecht, pp. 347-358. Reimer, R., (1999a). Personal communication between Ron Reimer of DuPont, USA and Heike Mainhardt of ICF, Inc., USA. February 8, 1999. Reimer, R., (1999b). Personal communication between Ron Reimer of DuPont, USA and Heike Mainhardt of ICF, Inc., USA. May 19, 1999. Reimschuessel, H. K. (1977). ‘Nylon 6 Chemistry and Mechanisms’, Journal of Polymer Science: Macromolecular Reviews , Vol. 12, 65-139, John Wiley & Sons, Inc. Scott, A. (1998). ‘The winners and losers of N 2 O emission control’. Chemical Week , February 18, 1998. Thiemens, M.H. and Trogler, W.C. (1991). ‘Nylon production; an unknown source of atmospheric nitrous oxide’. Science, 251, pp. 932-934. U.S. EPA (1985). Criteria Pollutant Emissions Factors. Volume 1, Stationary Point and Area Sources. AP-42 4th Edition (and Supplements A and B). U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA. van Balken, J.A.M. (2005). Personal communication from J.A.M. van Balken (European Fertilizer Manufacturers Association).



### SECTION 3.9 AGO (2005). Australian Methodology for the Estimation of Greenhouse Gas Emissions and Sinks 2003: Industrial Processes, Australian Government, Department of the Environment and Heritage, Australian Greenhouse Gas Office, 200 5, Table 4, Page 18. BASF (2006). Personal Communication from Silke Schmidt, BASF Aktiengesellschaft, Ludwidshafen, Germany to Robert Lanza, ICF Consulting, Inc., Washington, DC, USA, January 9, 2006. Boustead, I. (1999). Eco-Profiles of Plastics and Relate d Intermediates, published by APME, Brussels, 1999. Boustead, I. (2003a). Eco-Profiles of the European Pl astics Industry: Olefins. A Report for the European Association of Plastics Manufacturers (APME), Brussels, July 2003, Table 7, Page 9. http://www.apme.org/dashboard/bus iness_layer/template.asp?url=h ttp://www.apme.org/media/public_do cuments/20030820_114355/olefinsreport_july2003. pdf&title=Microsoft+Word+%2D+olefins%2Edoc&k euze1=&keuze2=&keuze3=&invulstrook=olefin+AND+eco%2Dprofile Boustead, I. (2003b). Eco-Profiles of the European Plastics Industry, Methodology: A Report for APME, Brussels, July 2003. http://www.apme.org/media/public_ documents/20010817_1 41031/method.pdf Boustead, I. (2005). ETHYLENE DICHLORIDE: A report by I Boustead for The European Council of Vinyl Manufacturers (ECVM) & PlasticsEurope, March 2005. DOE (2000). Energy and Environmental Profile of the U.S. Chemical Industry, U.S. Department of Energy Office of Industrial Technologies, Ma y 2000, Section 3.1.4, Page 92. DSM (2002). DSM Responsible Care Progress Report 2001; Safety, Health and Environmental Management at DSM, 2002Chapter 3: Chemical Industry Emissions

2006 IPCC Guidelines for National Greenhouse Gas Inventories 3.109 EEA (2005). EMEP/CORINAIR. Emission Inventory Guidebook – 2005, European Environment Agency, Technical report No 30. Copenhagen, Denmark, (December 2005). Available from web site see: http://reports.eea.eu.int/EMEPCORINAIR4/en European IPPC Bureau (2005). Integrated Pollution Pr evention and Control (IPPC) Draft Reference Document on Best Available Techniques in the Large Volume Inorganic Chemicals (LVIC) – Solid and Others Industry, EK/EIPPCB/LVIC -S_Draft_2, Draft, June 2005. http ://eippcb.jrc.es/pages/FActivities.htm European IPPC Bureau (2003). Integr ated Pollution Prevention and Control (IPPC) Reference Document on Best Available Techniques in the Large Volume Organic Chemical (LVOC) Industry, February 2003. http://eippcb.jrc.es/pages/FActivities.htm FgH-ISI (1999). Fraunhofer-Institut für Systemtechnik u nd Innovationsforschung. C-Ströme Abschätzung der Material –Energie und CO2 Ströme für Modellsysteme in Zuzammenhang mit dem nichenergetishen Verbrauch, orientiert am Lebensweg – Stand und Szenarienbetractthung, Karlsrue, 1999. Cited in Neelis, M; Patel, M; de Feber, M; 2003. Improvement of CO 2 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, and Society, Utr echt, The Netherlands, April 2003 Hinderink, et al . (1996). Exergy Analysis with Flowsheetin g Simulator – II Application Synthesis Gas Production from Natural Gas, Chemical Engineering Science, Volume 51, No. 20, Page 4701-4715, 1996. 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, an d Society, Utrecht, The Netherlands, April 2003 Houdek, J.M., Andersen, J. (2005). “On Purpose“ Propylene – Technology Developments, UOP LLC. Presented at the ARTC 8th Annual Meeting, Kuala Lumpur, April 29, 2005, Figure 1, Page 3 and Page 4. Kirk Othmer (1992). Encyclopedia of Chemical Technology, 4th Edition, Vo lume 4, 1992. Carbon Black. Page 1054. Lurgi (2004a). Lurgi Mega Methanol. Lurgi Oel-Gas-Chemie Lurgi (2004b). Integrated Low Pressure Methanol Process: Synthesis Gas Production by Combined Reforming of Natural Gas or Oil Associated Gas. Lurgi Oel-Gas-Chemie. http://www.lurgi-oel.de/lurgi_oel/english/nbsp/main/info/methanol_combined_reforming.pdf Lurgi (2004c). Integrated Low Pressure Methanol Process: Synthesis Gas Production by Conventional Steam Reforming of Natural Gas or Oil Associated Gas. Lurgi Oel-Gas-Chemie. http://www.lurgi-oel.de/lurgi_oel/english/nbsp/main/info/methanol_conventional_reforming.pdf Methanex (1996). Methanex Corporation Climate Change Voluntary Challenge and Registry Program Action Plan, September 1996. http://www.vcr-mvr.ca/registry/out/C969-METHANEX-W52.PDF Methanex (2003). Global Environmental Excelle nce Report 2002, Methanex Corporation, 2003 Neelis, M., Patel, M. and de Feber, M. (2003). Improvement of CO 2 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, and Societ y, Utrecht, The Nether lands, April 2003. Qenos (2003). Annual Report on Manufacturing Operations at Qenos Olefins, Plastics, Resins, and Elastomers Sites to Altona Complex Neighborhood Consu ltative Group, April 2003, Qenos Pty. Ltd. Qenos (2005). 2004 Annual Report on Manufacturing Operations at Qenos Olefins, Plastics, Resins, and Elastomers Sites to Altona Complex Neighborhood Consultative Group, April 2005, Qenos Pty. Ltd. SFT (2003a). Self-reporting of emissions to the Norw egian Pollution Control Authority based on direct measurements at Statoil Tjeldbergodden Methanol Plant. (In Norwegian). SFT (2003b). Self-reporting of emissions to the Norw egian Pollution Control Authority based on direct measurements at Nordetyl ethy lene Plant. (In Norwegian). Struker, A. and Blok, K. (1995). Sectorstudie organisc he 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 Ins titute, Department of Science, Technology, and Society, Utrecht, The Netherlands, April 2003Volume 3: Industrial Processes and Product Use

3.110 2006 IPCC Guidelines for National Greenhouse Gas Inventories 

### 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., Grig gs 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 and Bromotrifluoromethane (Halons 1211 and 1301), Atmos. Environ., 26A(7) , 1325-1329. Oram D.E., Sturges, W.T., Penkett, S.A., McCulloch, A. and Fraser, P.J. (1998). Growth of fluoroform (CHF 3 , 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, Ar lington, U.S.A., 2004. Available at www.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 emi ssion reduction from gas insulated electrical equipment in Japan. Proc. Joint IPCC/TEAP Expert Meeting on Options for the Limitation of Emissions of HFCs and PFCs, Petten, Netherlands , 26-28 May 1999. ECN, Petten. UNFCCC (2005). Belgium’s Greenhouse Gas Inventor y (1990-2003), National Inventory Report 2005, submitted under the United Nations Framework Convention on Climate Change, April 2005. http://unfccc.int/national_re ports/annex_i_ghg_inventories/national_ inventories_submissions/items/2761. php.