### .



# Italian Greenhouse Gas Inventory

1990

- 2007

National Inventory Report 200 9

Daniela Romano, Chiara Arcarese, Antonella Bernetti, Antonio Caputo, Rocío D. Cóndor , Mario
Contaldi, Riccardo De Lauretis, Eleonora Di Cristofaro, Sand ro Federici, Andrea Gagna, Barbara
Gonella, Riccardo Liburdi, Ernesto Taurino, Marina Vitullo

ISPRA

- Institute for Environmental Protection and Research

Annual Report for submission under the UN Framework Convention on Climate Change and the European Union’s Greenhouse Gas Monitoring Mechanism

© ISPRA 

# ISPRA

Institute for Environmental

Protection and Research

### Legal Disclaimer

The Institute for Environmental Protection and Research, or person acting on its behalf, are not responsible for the use that may be made of the information contained in this report.

ISPRA

–Istituto Superiore per la Protezione e la Ricerca Ambientale
(Institute for Environmental Protection and Research)
Via Vitaliano Brancati, 48

–00144 Rome www.apat.gov.it

ISPRA is the Institute for Environ mental Protection and Research established by Italian Law 133/2008, as published in the Official Journal n. 195, August 21 2008. The Institute performs the functions of three former institutions: APAT (Agency for Environmental Protection and Technical

Serv ices), ICRAM (Central Institute for Applied Marine Research), INFS (National Institute for Wildlife). This publication refers to activities carried out prior to the unification of the three institutions and,
therefore, individual reference is still made t o them.

Extracts from this document may be reproduced on the condition that the source is acknowledged

© ISPRA

### Authors

Chiara Arcarese (national registry), Antonella Bernetti ( energy

- road transport ), Antonio Caputo (energy

- fugitive), Rocío D . Cóndor ( agriculture), Mario Contaldi (energy), Riccardo De Lauretis (energy, industrial processes), Eleonora Di Cristofaro ( energy

- navigation, solvent and other product use), Sandro Federici (national registry for forest carbon sinks), Andrea Gagna (indu strial processes), Barbara Gonella (industrial processes, waste), Riccardo Liburdi (national registry), Daniela Romano (general coordination and editing, cross cutting issues), Ernesto Taurino (industrial processes), Marina Vitullo (land use, land use chan ge and forestry)

Contact : Riccardo De Lauretis

Telephone +39 0650072543

Fax +39 0650072657

E

- mail delauretis@apat.it

ISPRA

- Institute for Environmental Protection and Research

Enviro nment Department Monitoring and Prevention of Atmospheric Impacts Air Emission Inventory Unit
Via V. Brancati, 48

00144 Rome

I TALY

# Premessa

Nell’ambito degli strumenti e delle politiche per fronteggiare i cambiamenti climatici, un ruolo

fondamentale è svolto dal monitoraggio delle emissioni dei gas climalteranti.

A garantire questa funzione, in Italia, è l’ ISPRA (ex APAT) su incarico del Ministero dell’Ambiente attraverso il Decreto Legislativo n. 51 del 7 marzo 2008 che istituisce il Sistema

Naziona le, National System , relativo all’inventario delle emissioni dei gas serra.

L’ ISPRA , infatti, realizza ogni anno l’inventario nazionale delle emissioni in atmosfera, che è strumento indispensabile di verifica degli impegni assunti a livello internaziona le sulla protezione dell’ambiente atmosferico, come la Convenzione Quadro sui Cambiamenti Climatici (UNFCCC), il Protocollo di Kyoto, la Convenzione di Ginevra sull’inquinamento atmosferico transfrontaliero
(UNECE

- CLRTAP), le Direttive europee sulla limita zione delle emissioni. In particolare, o gni Paese che partecipa alla Convenzione sui Cambiamenti Climatici, oltre a fornire annualmente l’inventario nazionale delle emissioni dei gas serra secondo i formati richiesti, deve

documentare in un

o specifico docu

mento , il National Inventory Report , le metodologie di stima unitamente ad una spiegazione degli andamenti osservati.

Il National Inventory Report facilita i processi internazionali di verifica cui le stime ufficiali di emissione dei gas serra sono sottop oste. In particolare, viene esaminata la rispondenza alle proprietà di trasparenza, consistenza, comparabilità, completezza e accuratezza nella realizzazione, qualità richieste esplicitamente dalla Convenzione suddetta. L’inventario delle emissioni è, in r ealtà, sottoposto ogni anno ad un esame da parte di un organismo nominato dal Segretariato della Convenzione che analizza tutto il materiale presentato dal Paese e ne verifica in dettaglio le qualità su enunciate. Senza tali requisiti l’Italia sarebbe escl usa dalla partecipazione ai meccanismi flessibili previsti dallo stesso Protocollo come il mercato delle quote di emissioni, il trasferimento delle tecnologie (TT), l’implementazione di progetti con i paesi in via di sviluppo (CDM) e l’implementazione di p rogetti congiunti con i paesi delle economie in transizione (JI).

In particolare, il rapporto “Italian Greenhouse Gas Inventory 1990

- 2007 . National Inventory Report

2009 ” descrive la comunicazione annuale italiana dell’inventario delle emissioni dei gas s erra dal

1990 al 200 7.

Il documento è uno strumento fondamentale per la pianificazione e l’attuazione di efficaci politiche ambientali e fornisce alle istituzioni centrali e periferiche un adeguato contributo conoscitivo sulle problematiche inerenti ai ca mbiamenti climatici a livello settoriale.

Nuove politiche ed interventi a livello nazionale ed internazionale saranno, infatti, indispensabili per garantire nel futuro il rispetto degli obiettivi del Protocollo di Kyoto, dal momento che, come emerge dal r

apporto, le emissioni totali dei gas serra (espressi in termini di CO 2 

### equivalente) sono
aumentate, dal 1990 al 200 7 , del 7.1 % a fronte di un impegno nazionale di riduzione pari al 6,5% entro il periodo 2008

- 2012.

### Contents

E XECUTIVE SUMMARY



### 11

ES.1 Background information on greenhouse gas inventories and climate change 11

ES.2 Summary of national emission and removal related trends 12

ES.3 Overview of source and sink category emission estimates and trends 14

ES.4 Other information 17

S OMMARIO 

### (I TALIAN 

### ) 18

1. I NTRODUCTION 

### 19

1.1 Background information on greenhouse gas inventories and climate change 19

1.2 Description of the institutional arrangement for inventory prepa ration 20

1.2.1 National Inventory System

1.2.2 Institutional arrangement for reporting under Article 3, paragraphs 3 and 4 of Kyoto Protocol

1.2.3 National Registry System

1.3 Brief description of the process of inventory preparation 24

1.4 Brief general description of methodologies and data sources used 26

1.5 Brief description of key categories 28

1.6 Information on the QA/QC plan including verification and treatment of confidentiality issues where relevant 31

1.7 General uncertainty evalu ation, including data on the overall uncertainty for the inventory totals 35

1.8 General assessment of the completeness 36

2. T RENDS IN GREENHOUSE GAS EMISSIONS 

### 39

2.1 Description and interpretation of emission trends for aggregate gre enhouse gas emissions 39

2.2 Description and interpretation of emission trends by gas 40

2.2.1 Carbon dioxide emissions

2.2.2 Methane emissions

2.2.3 Nitrous oxide emissions

2.2.4 Fluorinated gas emissions

2.3 Description and interpretation of emission trends by source 44

2.3.1 Energy

2.3.2 Industrial processes

2.3.3 Solvent and other product use

2.3.4 Agriculture

2.3.5 LULUCF

2.3.6 Waste

2.4 Description and interpretation of emission trends for indirect gases and SO 2 

### 51

3. E NERGY 

### [CRF

SECTOR 

### 1] 52

3.1 Introduction

52

3.2 Key categories 52

3.3 Methodology for estimation of emissions from combustion 53

3.4 Energy industries 57

3.4.1 Electricity production

3.4.2 Refineries

3.4.3 Manufacture of Solid Fuels and Other Energy Industries

3.5 Manufacturing industries and constru ction 61

3.5.1 Estimation of carbon content of coals used in industry

### 3.5.2 Time series

3.6 Transport 63

3.6.1 Aviation

3.6.1.1 Source category description

3.6.1.2 Methodological issues

3.6.1.3 Uncertainty and time

- series consisten cy 3.6.1.4 Source

- specific QA/QC and verification

3.6.1.5 Source

- specific recalculations

3.6.1.6 Source

- specific planned improvements

3.6.2 Railways

3.6.3 Road transport

3.6.3.1 Source category description

3.6.3.1.1 Fuel

- based emissions

3.6.3.1.2 Traffic

- based emissions

3.6.3.2 Methodological issues

3.6.3.3 Uncertainty and time

- series consistency

3.6.3.4 Source

- specific QA/QC and verification

3.6.3.5 Source

- specific recalculations

3.6.1.6

Source

- specific planned improvements

3.6.4 Navigation

3.6.4.1 Source category description

3.6.4.2 Methodological issues

3.6.4.3 Uncertainty and time

- series consistency

3.6.4.4 Source

- specific QA/QC and verification

3.6.1.5 Source

- specific recalculations

3.6.1.6 Source

- specifi c planned improvements

3.7 Other sectors 77

3.7.1 Other combustion

3.7.2 Other off

- road sources

3.8 International bunkers 79

3.9 Feedstock and non

- energy use of fuels 79

3.10 Country specific issues 81

3.10.1 National energ y balance

3.10.2 National emission factors

3.11 F ugitive emissions from solid fuels, oil and natural gas 81

4. I NDUSTRIAL 

### P

ROCESSES 

### [CRF

SECTOR 

### 2] 85

4.1 Overview of sector 85

4.2 Mineral products (2A) 86

4.2.1 Source category description

4.2.2 Methodological issues

4.2.3 Uncertainty and time

- series consistency

4.2.4 Source

- specific QA/QC and verification

4.2.5 Source

- specific recalculations

4.2.6 Source

- specific planned improvements

4.3 Chemical industry (2B) 90

4.3.1 Source category description

4.3.2 Methodo logical issues

4.3.3 Uncertainty and time

- series consistency

4.3.4 Source

- specific QA/QC and verification

4.3.5 Source

- specific recalculations

4.3.6 Source

- specific planned improvements

4.4 Metal production (2C) 94

### 4.4.1 Source category descripti on 4.4.2 Methodological issues

4.4.3 Uncertainty and time

- series consistency

4.4.4 Source

- specific QA/QC and verification

4.4.5 Source

- specific recalculations

4.4.6 Source

- specific planned improvements

4.5 Other production (2D) 100

4.5.1 Source ca tegory description

4.6 Production of halocarbons and SF 6 

### (2E) 101

4.6.1 Source category description

4.6.2 Methodological issues

4.6.3 Uncertainty and time

- series consistency

4.6.4 Source

- specific QA/QC and verification

4.6.5 Source

- specific recalculations

4.6.6 Source

- specific planned improvements

4.7 Consumption of halocarbons and SF 6 

### (2F) 102

4.7.1 Source category description

4.7.2 Methodological issues

4.7.3 Uncertainty and time

- series consistency

4.7.4 Source

- specific QA/QC and verification

4.7.5 Source

- specific recalculations

4.7.6 Source

- specific planned improvements

5. S OLVEN T AND OTHER PRODUCT USE 

### [CRF SECTOR 

### 3] 107

5.1 Overview of sector 107

5.2 Source category description 108

5.3 Methodological issues 108

5.4 Uncertainty and time

- series consistency 109

5.5 Source

- specific QA/QC and verification 109

5.6 Source

- sp ecific recalculations 110

6. A GRICULTURE 

### [CRF SECTOR 

### 4] 111

6.1 Overview of sector 111

6.1.1 Emission trends

6.1.2 Key categories

6.1.3 Activities

6.1.4 Agricultural statistics

6.2 Enteric fermentation (4A) 114

6.2.1 Source category description

6.2.2 Methodological issues

6.2.3 Uncertainty and time

- series consistency

6.2.4 Source

- specific QA/QC and verification

6.2.5 Source

- specific recalculations

6.2.6 Source

- specific planned improvements

6.3 Manure management (4B) 121

6.3.1 Source category description

6.3.2 Methodological issues

6.3.3 Uncertainty and time

- series consistency

6.3.4 Source

- specific QA/QC and verification

6.3.5 Source

- specific recalculations

6.3.6 Source

- specific planned improvements

6.4 Rice cultivation (4C) 133

6.4.1 Source category description

### 6.4.2 Methodological issues

6.4.3 Uncertainty and time

- series consistency

6.4.4 Source

- specific QA/QC and verification

6.4.5 Source

- specific recalculations

6.4.6 Source

- specific planned improvements

6.5 Agriculture soils (4D) 137

6.5.1 Source category description

6.5.2 Methodological issues

6.5.3 Uncertainty and time

- series consistency

6.5.4 Source

- specific QA/QC and verification

6.5.5 Source

- specific recalculations

6.5.6 Source

- specific planned improvements

6.6 Field burning of agriculture residues (4F) 145

6.6.1 Source category description

6.6.2 Methodological issues

6.6.3 Uncertainty and time

- series consistency

6.6.4 Source

- specific QA/QC and verification

6.6.5 Source

- specific recalculations

6.6.6 Source

- specific plann ed improvements

7. L AND USE 

### , L AND USE CHANGE AND F ORESTRY 

### [CRF

SECTOR 

### 5] 149

7.1 Overview of sector 149

7.2 Forest Land (5A) 156

7.2.1 Source category description

7.2.2 Methodological issues

7.2.3 Uncertainty and time

- series consistency

7.2.4 Source

- speci

fic QA/QC and verification

7.2.5 Source

- specific recalculations

7.2.6 Source

- specific planned improvements

7.3 Cropland (5B) 172

7.3.1 Source category description

7.3.2 Methodological issues

7.3.3 Source

- specific recalculations

7.3.4 Source

- specific planned improvements

7.4 Gra ssland (5C) 176

7.4.1 Source category description

7.4.2 Methodological issues

7.4.3 Source

- specific recalculations

7.4.4 Source

- specific planned improvements

7.5 Wetlands (5D) 180

7.5.1 Source category description

7.5.2 Methodological issues

7.5.3 Source

- specific planned i mprovements

7.6 Settlements (5E) 180

7.6.1 Source category description

7.6.2 Methodological issues

7.6.3 Source

- specific recalculations

7.6.4 Source

- specific planned improvements

7.7 Other Land (5F) 183

7.8 D irect N 2 

### O emissions from N fertilization (5(I)) 183

7.9 N 2 

### O emissions from drainage of soils (5(II)) 183

7.10 N 2 

### O emissions from disturbance associated with land

- use conversion to Cropland (5(III)) 183

### 7.10.1 Source category description

7.10.2 M ethodological issues

7.10.3 Source

- specific recalculation

7.11 Carbon emissions from agricultural lime application (5(IV)) 184

7.12 Biomass burning (5(V)) 184

7.12.1 Source category description 7.12.2 Methodological issues

7.12.3 Source

- specific planned im provements
7.12.4 Source

- specific recalculations

8. W ASTE 

### [CRF

SECTOR 

### 6] 187

8.1 Overview of sector 187

8.2 Solid waste disposal on land (6A) 188

8.2.1 Source category description

8.2.2 Methodological issues

8.2.3 Uncertainty and time

- seri es consistency

8.2.4 Source

- specific QA/QC and verification

8.2.5 Source

- specific recalculations

8.2.6 Source

- specific planned improvements

8.3 Wastewater handling (6B) 197

8.3.1 Source category description

8.3.2 Methodological issues

8.3.3 Uncertainty and time

- series consi stency

8.3.4 Source

- specific QA/QC and verification

8.3.5 Source

- specific recalculations

8.3.6 Source

- specific planned improvements

8.4 Waste incineration (6C) 201

8.4.1 Source category description

8.4.2 Methodological issues

8.4.3 Uncertainty and time

- series consistency

8.4.4 S ource

- specific QA/QC and verification

8.4.5 Source

- specific recalculations

8.4.6 Source

- specific planned improvements

8.5 Other waste (6D) 205

8.5.1 Source category description

8.5.2 Methodological issues

8.5.3 Uncertainty and time

- series consistency

8.5.4 Source

- spec ific QA/QC and verification

8.5.5 Source

- specific recalculations

8.5.6 Source

- specific planned improvements

9. R ECALCULATIONS AND IM PROVEMENTS 

### 207

9.1 Explanations and justifications for recalculations 207

9.2 Implications for emission levels 207

9.3 Impl

ications for emission trends, including time series consistency 211

9.4 Recalculations, response to the review process and planned improvements 212

9.4.1 Recalculations 9.4.2 Response to the UNFCCC review process

9.4.3 Planned improvements (e.g., instituti onal arrangements, inventory preparation)

10. R EFERENCES 

### 215

10.1 Introduction

215

### 10.2 Energy 216

10.3 Industrial processes 218

10.4 Solvent and other product use 222

10.5 Agriculture 223

10.6 Land use, Land use change and forestry 233

10.7 Waste 237

10.8 ANNEX 1 242

10.9 ANNEX 4 242

10.10 ANNEX 6 242

A NNEX 

### 1: K EY CATEGORIES AND UN CER TAINTY 

### 244

A1.1 Introduction

244

A1.2 Tier 1 key source assessment 245

A1.3 Uncertainty assessment (IPCC Tier 1) 248

A1.4 Tier 2 key source assessment 251

A NNEX 

### 2: D ETAILED T ABLES OF ENERGY CONS UMPTION FOR POWER GE NERATION 

### 256

A NNEX 

### 3: E STIMATION OF CARBON CONTENT OF COAL S USED IN INDUSTRY 

### 259

A NNEX 

### 4: CO 2 REFERENCE APPROACH 

### 264

A4.1 Introduction

264

A4.2 Comparison of the sectoral approach with the reference approach 265

A NNEX 

### 5: N ATIONAL ENERGY BALAN CE 

### , YEAR 

### 2007 267

A NNEX 

### 6: N ATIONAL EMISSION FAC TORS 

### 292

A NNEX 

### 7: A GRICULTURE SECTOR 

### 296

A NNEX 

### 8 : CRF

TREND TABLES FO R GREENHOUSE GASES 

### 299

A NNEX 

### 9 : M ETHODOLOGIES 

### , DATA SOURCES AND EM ISSION FACTORS 

### 326

A NNEX 

### 10 : T HE 

### N ATIONAL 

### R EGISTRY FOR 

### F OREST 

### C ARBON 

### S INKS 

### 337

A NNEX 

### 11 : T HE 

### N ATIONAL 

### R EGISTRY 

### 346

### 11

Executive Summary

ES.1. Background information on greenhouse gas inventories and climate change

The United Nations Framework Convention on Climate Change (FCCC) was ratified by Italy in the year 1994 through law no.65 of 15/01/1994. The Kyoto Protocol, adopted in December 1997, has established emission reduction objectives for Annex B Parties (i.e. industrialised countries and countries with economy in transition): in particular, the European Union as a whole is committed to an 8% reduction within the period

2008

- 2012, in comparison with base year levels. For Italy, the EU burden sharing agreement, set out in Annex II to Decision 2002/358/EC and in accordance with Article 4 of the Kyoto
Protocol, has established a reduction objective of 6.5% in the commitment per iod, in comparison

with 1990 levels. Subsequently, on 1 st 

### June 2002, Italy ratified the Kyoto Protocol through law no.120 of 01/06/2002. The ratification law prescribed also the preparation of a National Action Plan to reduce greenhouse gas emissions, whi ch was adopted by the Interministerial Committee for Economic Planning (CIPE) on 19 th 

### December 2002 (deliberation n. 123 of 19/12/2002). The Kyoto Protocol finally entered into force in February 2005. As a Party to the Convention and the Kyoto Protocol, It aly is committed to develop, publish and regularly update national emission inventories of greenhouse gases (GHGs) as well as formulate and implement programmes to reduce these emissions. In order to establish compliance with national and international com mitments, the national GHG emission inventory is compiled and communicated annually by the Institute for Environmental Protection and Research (ISPRA) to the competent institutions, after endorsement by the Ministry for the Environment, Land and Sea. The s ubmission is carried out through compilation of the Common Reporting Format (CRF), according to the guidelines provided by the United Nations Framework Convention on Climate Change and the European Union’s Greenhouse Gas Monitoring Mechanism. As a whole, a n annual GHG inventory submission shall consist of a national inventory report (NIR) and the common reporting format (CRF) tables as specified in the Guidelines on reporting and review of greenhouse gas inventories from Parties included in

Annex I to the C onvention, implementing decisions 3/CP.5 and 6/CP.5,

doc.FCCC/SBSTA/2002/L.5/Add.1. Detailed information on emission figures and estimation procedures, including all the basic data needed to carry out the final estimates, are to be provided to improve the transparency, consistency, comparability, accuracy and completeness of the inventory provided. The national inventory is updated annually in order to reflect revisions and improvements in the methodology and use of the best information available. Adjust ments are applied retrospectively to earlier years, which accounts for any difference in previously published data.

This report is compiled according to the guidelines on reporting as specified in the document FCCC/SBSTA/2002/L.5. It provides an analysis of the Italian GHG emission inventory communicated to the Secretariat of the Climate Change Convention and to the European Commission in the framework of the Greenhouse Gas Monitoring Mechanism in the year 2009, including the update for the year 2007 and t he revision of the entire time series 1990

- 2006.

T he assigned amount

for Italy, pursuant to Ar ticle 3, paragraphs 7 and 8 and calculated in

accordance with the annex to decision 13/CMP.1

, has been established together with the commitment period reserve (C PR), required in accordance with paragraph 18 of decision 15

CMP.1

, during the last in country review in 2007 . The calculated figures are reported in the

document FCCC/IRR/2007/ITA and amount to 2,416,277,898 tonnes CO 2 

### eq

. for the assigned

amount and 2,17 4,650,108 tonnes of CO 2 

### eq. for the CPR. The CRP is calculated on the basis of the assigned amount so it has not change d from the previous submission.

### 12

Emission estimates comprise the six direct greenhouse gases under the Kyoto Protocol (carbon
dioxide, me thane, nitrous oxide, hydrofluorocarbons, perfluorocarbons, sulphur hexafluoride) which contribute directly to climate change owing to their positive radiative forcing effect and four indirect greenhouse gases (nitrogen oxides, carbon monoxide, non

- methane volatile organic compounds, sulphur dioxide). This report, the CRF files and other related documents are available on website at the address http://www.sinanet.apat.it/it/sinane t/serie_storiche_emissioni

. The official inventory submissions can also be found at the UNFCCC website http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/ite ms/4303.php.

ES.2. Summary of national emission and re moval related trends

Total greenhouse gas emissions, in CO 2 

### equivalent, excluding emissions and removals of CO 2 

### from land use, land use change and forestry, increased by 7.1 % between 1990 and 2007 (from

516 to 553 millions of CO 2 

### equivalent tons), while t he national Kyoto target is a reduction of 6.5% as compared to the base year levels by the period 2008

- 2012. The most important greenhouse gas, CO 2 

### , which accounted for 86.0 % of total emissions in CO 2 

### equivalent in 2007, showed an increase by 9.3 % between 1990 and 2007. In the energy sector, specifically, emissions in 2007 were 10.2 % greater than in 1990.

CH 4 

### and N

2 

### O emissions were equal to 6.9 % and 5.8 %, respectively, of the total CO 2 

### equivalent greenhouse gas emissions in 2007. Both gases showed a decrea se from 1990 to 2007, equal to

8.4 % and 14.9 % for CH 4 

### and N 2 

### O, respectively.

Other greenhouse gases, HFCs, PFCs and SF 6 

### , ranged from 0.1 % to 1.2 % of total emissions; at present, variations in these gases are not relevant to reaching the objectives for emissions

reduction. Table ES.1 illustrates the national trend of greenhouse gases for 1990

- 2007, expressed in CO 2 

### equivalent terms, by substance and category.

### 13 1990 (base year) 1995 2000 2001 2002 2003 2004 2005 2006 2007 GHG Emissions

CO 2 equivalent ( Gg)

CO 2 emissions including net CO 2 from

LULUCF 367,036.98 359,584.64 383,389.41 375,767.27 374,906.87 359,144.61 397,091.49 394,682.39 395,617.40 404,175.53

CO 2 emissions excluding net CO 2 from

LULUCF 434,687.67 445,400.65 462,715.45 468,439.04 470,590.27 486,014.24 488,969.97 490,056.41 485,753.66 475,302.06

CH 4 emissions including CH 4 from

LULUCF 41,881.77 44,184.91 44,283.69 42,977.57 41,870.01 41,143.38 39,872.85 39,678.68 38,074.79 38,414.21

CH 4 emissions excluding CH 4 from

LULUCF 41,738.88 44,157.53 44,196.69 42,922.38 41,839.08 41,078.41 39,838.23 39,644.52 38,044.18 38,217.46

N 2 O emissions including N 2 O from

LULUCF 37,414.74 38,563.14 39,781.10 39,793.53 39,056.12 38,558.95 39,645.33 37,902.46 32,841.82 31,855.78

N 2 O emissions excluding N 2 O fr om
LULUCF 37,400.24 38,364.14 39,772.27 39,787.93 39,052.98 38,552.36 39,641.82 37,898.99 32,540.21 31,835.81

HFCs 351.00 671.29 1,985.67 2,549.75 3,099.90 3,795.82 4,514.91 5,267.03 5,956.20 6,700.69

PFCs 1,807.65 490.80 345.85 451.24 423.74 497.63 347.89 352.62 282.30 287.78

SF 6 332.92 601.45 493.43 795.34 739.72 467.56 502.14 465.39 405.87 427.55

Total (including LULUCF) 448,825.07 444,096.25 470,279.15 462,334.69 460,096.36 443,607.96 481,974.60 478,348.57 473,178.39 481,861.53

Total (excluding LUL UCF) 516,318.37 529,685.87 549,509.36 554,945.68 555,745.69 570,406.02 573,814.96 573,684.95 562,982.42 552,771.35

1990 (base year) 1995 2000 2001 2002 2003 2004 2005 2006 2007 GREENHOUSE GAS SOURCE AND

SINK CATEGORIES

CO 2 equivalent (Gg)

1. Energy 418,945.37 431,961.27 450,722.44 455,289.63 457,263.97 471,622.91 473,756.12 474,505.53 469,585.98 458,672.79

2. Industrial Processes 36,466.66 34,530.35 34,903.34 36,946.22 37,039.91 38,231.91 40,522.46 40,366.88 35,915.85 36,295.95

3. Solvent and Oth

er Product Use 2,394.46 2,179.77 2,284.53 2,210.51 2,219.20 2,166.67 2,143.88 2,139.11 2,146.55 2,132.81

4. Agriculture 40,576.25 40,348.92 39,939.85 38,953.95 38,250.04 38,101.53 37,917.46 37,241.73 36,627.42 37,210.50

5. Land Use, Land

- Use Change an d Forestry (5) - 67,493.30

- 85,589.62

- 79,230.21

- 92,610.99

- 95,649.34

- 126,798.06

- 91,840.36

- 95,336.38

- 89,804.03

- 70,909.82

6. Waste 17,935.63 20,665.57 21,659.21 21,545.38 20,972.57 20,283.00 19,475.03 19,431.70 18,706.62 18,459.31

7. Other NA NA NA NA NA NA NA NA NA NA

Table ES.1. Total greenhouse gas emissions and removals in CO 2 equivalent (Gg CO 2 eq )

### 14

ES.3. Overview of source and sink category emission estimates and trends

The energy sector is the largest contributor to national total GHG emis sions with a share, in
2007, of 83.0 %. Emissions from this sector increased by about 9.5 % from 1990 to 2007. Substances with the highest increase rates were CO 2 

### , whose levels increased by 10.2 % from

1990 to 2007 and accounts for 97.4 % of the total in the e nergy sector, and N 2 

### O which showed an

increase of 18.0 % but its share out of the sectoral total is only 1.2 %; CH 4 

### , on the other hand,

showed a decrease of 27.7 % from 1990 to 2007 but it is not relevant on total emissions, accounting only for 1.4 %. Specific ally, in terms of total CO 2 

### equivalent, the most significant

increase was observed in the transport, in the energy industries and in the other sectors, about 25.1%, 17.6% and 4.8%, respectively; in 2007 these sectors, altogether, account for 80.6% of

total emissions.

For the industrial processes sector, emissions showed a a decrease of 0.5% from the base year to 2007. Specifically, by substance, CO 2 

### emissions account for 74.2% and showed a decrease by about 1.0%, due to opposite trends, specifically an inc rease of the mineral sector production and decrease of chemical and metal production emissions. CH 4 

### decreased by 40.3%, but it accounts only for 0.2%, while N 2 

### O, whose levels share 5.2% of total industrial emissions, decreased by

71.7 % due to the fully op erational abatement technology in the adipic acid industry. A

considerable increase was observed in F

- gas emissions (about 197.6 %), whose level on total

sectoral emissions is 20.4%.

In contrast, emissions from the solvent and other use sector, which refer to CO 2 

### and N 2 

### O emissions except for gases other than greenhouse, decreased by 10.9% from 1990 to 2007. The reduction is mainly to be attributed to a decrease by 14.9% in CO 2 

### emissions, which account for

63.8% of the sector. As regards CO 2 

### , emission levels from paint application sector, which

accounts for 51.4% of total CO 2 

### emissions from this sector, decreased by 17.2%; emissions from other use of solvents in related activities, such as domestic solvent use other than painting, application of glues and adh esives, printing industries, fat edible and non edible oil extraction, vehicle dewaxing, glass wool enduction, which account for 43.6% of the total, show an increase of 2.8%. Finally, CO 2 

### emissions from metal degreasing and dry cleaning activities, decreas ed by 61.3% but they account for only 5 .0 % of the total.

The level of N 2 

### O emissions, on the other hand, did not show a significant variation from 1990 to
2007 (

- 3.0%).

For agriculture, emissions refer to CH 4 

### and N

2 

### O levels, which account for 42.0 % and 58.0 % of the sector, respectively. The decrease observed in the total emissions (

- 8.3 %) was mostly due to

the decrease of CH 4 

### emissions from enteric fermentation (

- 9.5 %), which account for 29.6 %, and to a minor decrease from manure management (

- 7.2%), which accounts for 18.4% of the sectoral

emissions.

Finally, emissions from the waste sector increased by 2.9 % from 1990 to 2007 due to an increase in the emissions from solid waste disposal ( 0.3 %), which account for 72.3 % of waste emissions

and from waste

- wat er handling, which increased of about 15.6 % and accounts for 24.1 % of the total. The most important greenhouse gas in this sector is CH 4 

### which accounts for 87.0 % of the

sectoral emissions and shows an increase of 3.9 % from 1990 to 2007. N 2 

### O levels increase d by

9.5 %, whereas CO 2 

### decreased by 49.7 %; these gases account for 11.6 % and 1.5 %, respectively.

Table ES.2 provides an overview of the CO 2 

### equivalent emission trends by IPCC source

category.

### 15

Source category 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

1A. Energy: fuel combustion 408,183 421,904 441,713 446,780 448,960 462,891 465,889 466,669 462,203 451,425

CO 2 : 1. Ene rgy Industries 134,092 137,973 146,913 150,303 157,183 158,253 157,142 159,308 159,179 157,850

CO 2 : 2. Manufacturing Industries and

Construction 88,937 87,955 88,134 85,412 81,540 86,418 86,244 81,732 82,106 78,867

CO 2 : 3. Transport 101,269 111,446 120,109 122,181 124,143 125,106 127,091 125,830 127,151 127,212

CO 2 : 4. Other Sectors 76,677 76,090 78,596 81,373 78,782 85,362 87,083 91,844 85,967 79,746

CO 2 : 5. Other 1,046 1,440 806 354 314 660 1,091 1,198 982 896

C H 4 1,548 1,701 1,494 1,456 1,345 1,343 1,359 1,297 1,318 1,412

N 2 O 4,614 5,298 5,661 5,701 5,655 5,749 5,880 5,462 5,501 5,442

1B2. Energy: fugitives from oil & gas 10,762 10,057 9,010 8,510 8,304 8,732 7,867 7,836 7,383 7,248

CO 2 3,341 3,174 2,585 2,440 2,261 2,834 2,152 2,112 2,189 2,176

CH 4 7,420 6,882 6,424 6,069 6,042 5,896 5,713 5,723 5,193 5,071

N 2 O 1 1 1 1 1 1 1 1 1 1

2. Industrial processes 36,467 34,530 34,903 36,946 37,040 38,232 40,522 40,367 35,916 36,296

CO 2 27,190 25,415 24,097 24,858 24,818 25,856 26,653 26,457 26,559 26,924

CH 4 108 113 63 59 57 58 61 64 66 65

N 2 O 6,676 7,239 7,918 8,232 7,902 7,557 8,443 7,760 2,647 1,891

HFCs 351 671 1,986 2,550 3,100 3,796 4,515 5,267 5,956 6,701

PFCs 1,808 491 346 451 424 498 348 353 282 288

SF 6 333 601 493 795 740 468 502 465 406 428

3. Solvent and other product use 2,394 2,180 2,285 2,211 2,219 2,167 2,144 2,139 2,147 2,133

CO 2 1,598 1,424 1,274 1,295 1,306 1,310 1,315 1,331 1,354 1,361

### 16

Source category 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

N 2 O 796 756 1,011 915 913 857 829 808 793 772

4. Agriculture 40,576 40,349 39,940 38,954 38,250 38,102 37,917 37,242 36,627 37,210

CH 4 : Enteric fermentation 12,179 12,267 12,165 11,340 11,030 11,056 10,836 10,844 10,629 11,027

CH 4 : Manure management 3,462 3,286 3,278 3,343 3,263 3,252 3,156 3,151 3,031 3,057

CH 4 : Rice Cul tivation 1,562 1,657 1,382 1,382 1,420 1,463 1,534 1,472 1,477 1,523

CH 4 : Field Burning of Agricultural

Residues 13 13 12 11 13 11 14 13 13 13

N 2 O: Manure management 3,921 3,782 3,862 4,000 3,847 3,816 3,731 3,725 3,618 3,797

N 2 O: Agriculture soils 19,435 19,340 19,237 18,875 18,673 18,500 18,643 18,032 17,856 17,791

N 2 O: Field Burning of Agricultural

Residues 4 4 4 4 4 4 4 4 4 4

5A. Land

- use change and forestry

- 67,493

- 85,590

- 79,230

- 92,611

- 95,649

- 126,798

- 91,840

- 95,336

- 89,804

- 70,910

CO 2 - 67,651

- 85,816

- 79,326

- 92,672

- 95,683

- 126,870

- 91,878

- 95,374

- 90,136

- 71,127

CH 4 143 27 87 55 31 65 35 34 31 197

N 2 O 15 199 9 6 3 7 4 3 302 20

6. Waste 17,936 20,666 21,659 21,545 20,973 20,283 19,475 19,432 18,707 18,459

CO 2 537 483 202 222 245 216 199 245 267 270

CH 4 15,447 18,239 19,379 19,263 18,670 17,998 17,165 17,080 16,319 16,051

N 2 O 1,952 1,944 2,079 2,061 2,058 2,069 2,111 2,107 2,121 2,138

TOTAL EMISSIONS (with LULUCF) 448,825 444,096 470,279 462,335 460,096 443,608 481,975 478,349 473,178 481,862 TOTAL EMISSIONS (without
LULUCF) 516,318 529,686 549,509 554,946 555,746 570,406 573,815 573,685 562,982 552,771
Table ES.2. Summary of emission trends by source category and gas in CO 2 equivalent (Gg CO 2 eq )

### 17

ES.4. Other information

In Table ES.3 NO X 

### , CO, NMVOC and SO 2 

### emission trends from 1990 to 2007 are summaris ed. All gases showed a significant reduction in 2007 as compared to 1990 levels. The highest reduction

is observed for SO 2 

### (

- 81.1 %), while CO and NO X 

### emissions reduced by about 51.9 % and 42.8 % respectively, NMVOC levels showed a decrease by 38.4 %.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 Indire ct greenhouse gases

and SO2 ktons

NO X 2,007 1,868 1,434 1,422 1,367 1,360 1,319 1,229 1,188 1,147

CO 6,927 6,876 4,857 4,646 4,218 4,064 3,881 3,506 3,342 3,334

NMVOC 1,939 2,001 1,565 1,500 1,431 1,373 1,319 1,248 1,221 1,194

SO 2 1,795 1,320 749 697 616 518 480 401 379 339
Table ES.3. Total emissions of indirect greenhouse gases and SO 2 (1990

- 2007) (Gg)

### 18

Sommario ( Italian )

Nel documento “Italian Greenhouse Gas Inventory 1990

- 2007. National Inventory Report 2009” si descrive la comunicazione annuale italiana dell’inventario delle emissioni dei gas serra in accordo a quanto previsto nell’ambito della Convenzione Quadro sui Cam biamenti Climatici delle Nazioni Unite (UNFCCC), del protocollo di Kyoto. Tale comunicazione è anche trasmessa all’Unione Europea nell’ambito del Meccanismo di Monitoraggio dei Gas Serra. Ogni Paese che partecipa alla Convenzione, infatti, oltre a fornire annualmente l’inventario nazionale delle emissioni dei gas serra secondo i formati richiesti, deve documentare in un report , il National Inventory Report , la serie storica delle emissioni. La documentazione prevede una spiegazione degli andamenti osservati , una descrizione dell’analisi delle sorgenti principali, key

sources , e dell’incertezza ad esse associata, un riferimento alle metodologie di stima e alle fonti dei dati di base e dei fattori di emissione utilizzati per le stime, un’illustrazione del sist ema di Quality Assurance/Quality Control a cui è soggetto l’inventario e delle attività di verifica effettuate sui dati.

Il National Inventory Report facilita, inoltre, i processi internazionali di verifica cui le stime di emissione dei gas serra sono sot toposte al fine di esaminarne la rispondenza alle proprietà di trasparenza, consistenza, comparabilità, completezza e accuratezza nella realizzazione, qualità richieste esplicitamente dalla Convenzione suddetta. Nel caso in cui, durante il processo di revi ew
, siano identificati eventuali errori nel formato di trasmissione o stime non supportate da adeguata documentazione e giustificazione nella metodologia scelta, il Paese viene invitato ad una revisione

delle stime di emissione.

I dati di emissione dei gas

- serra, così come i risultati dei processi di review , sono pubblicati sul sito web del Segretariato della Convenzione sui Cambiamenti Climatici www.unfccc.int

. La serie storica nazionale delle emissioni è anche di sponibile sul sito web all’indirizzo http://www.sinanet.apat.it/it/sinanet/serie_storiche_emissioni

. Da una analisi di sintesi della serie storica dei dati di emissione dal 1990 al 2007, si evidenzia che le emissioni nazionali totali dei sei gas serra, espresse in CO 2 

### equivalente, sono aumentate del 7.1 % nel 2007 rispetto all’anno base (corrispondente al 1990), a fronte di un impegno nazionale di riduzione del 6.5% entro il perio do 2008

- 2012. In particolare, le emissioni complessive di CO 2 

### sono pari all’ 86.0 % del totale e risultano nel 2007 superiori del 9.3 % rispetto al 1990, mentre le emissioni relative al solo settore energetico sono

aumentate del 10.2 %. Le emissioni di metano e di protossido di azoto sono pari rispettivamente a

circa il 6. 9 % e 5.8 % del totale e presentano andamenti in diminuzione sia per il metano (

- 8.4 %) che per il protossido di azoto (

- 14.9 %). Gli altri gas serra, HFC, PFC e SF 6 

### , hanno un peso complessivo

su l totale delle emissioni che varia tra lo 0. 1 % e l’ 1.2 %; le emissioni degli HFC evidenziano una forte crescita, mentre le emissioni di PFC decrescono e quelle di SF 6 

### mostrano un minore

incremento. Sebbene al momento tali variazioni non risultino determinan ti ai fini del conseguimento degli obiettivi di riduzione delle emissioni, la significatività del trend degli HFC potrebbe renderli sempre più importanti nei prossimi anni.

### 19



## Chapter 1: INTRODUCTION

1.1 Background information on greenhouse gas inventories an d climate change

In 1988 the World Meteorological Organisation (WMO) and the United Nations Environment Program (UNEP) established a scientific Intergovernmental Panel on Climate Change (IPCC) in

order to evaluate the available scientific information on climate variations, examine the social and economical influence on climate change and formulate suitable strategies for the prevention and the control of climate change. The first IPCC report in 1990, although considering the high uncertainties in the eva luation of climate change, emphasised the risk of a global warming due to an unbalance in the climate system originated by the increase of anthropogenic emissions of greenhouse gases (GHGs) caused by industrial development and use of fossil fuels. More rec ently, the scientific knowledge on climate change has firmed up considerably by the IPCC Fourth Assessment Report on global warming which states that “Warming of the climate system is unequivocal (...). There is new and stronger

evidence that most of the war ming observed over the last 50 years is attributable to human activities (...). Most of the observed increase in globally averaged temperatures since the mid

- 20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrat ions”. Hence the need of reducing those emissions, particularly for the most industrialised countries. The first initiative was taken by the European Union (EU) at the end of 1990, when the EU adopted the goal of a stabilisation of carbon dioxide emissions by the year 2000 at the level of 1990 and requested Member States to plan and implement initiatives for environmental protection and energy efficiency. The contents of EU statement were the base for the negotiation of the United Nations

Framework Conventi

on on Climate Change (UNFCC) which was approved in New York on 9 th



### May 1992 and signed during the summit of the Earth in Rio the Janeiro in June 1992. Parties to the Convention are committed to develop, publish and regularly update national emission invent ories of greenhouse gases (GHGs) as well as formulate and implement programmes addressing anthropogenic GHG emissions. Specifically, Italy ratified the convention through law no.65 of

15/1/1994. On 11/12/1997, Parties to the Convention adopted the Kyoto Pr otocol, which establishes emission reduction objectives for Annex B Parties (i.e. industrialised countries and countries with economy in transition) in the period 2008

- 2012. In particular, the European Union as a whole is committed to

an 8% reduction withi n the period 2008

- 2012, in comparison with base year levels. For Italy, the EU burden sharing agreement, set out in Annex II to Decision 2002/358/EC and in accordance with Article 4 of the Kyoto Protocol , has established a reduction objective of 6.5% in th e commitment period, in comparison with the base 1990 levels. Italy ratified the Kyoto Protocol on 1 st 

### June 2002 through law no.120 of 01/06/2002. The ratification law prescribes also the preparation of a National Action Plan to reduce greenhouse gas

emis sion, which was adopted by the Interministerial Committee for Economic Planning (CIPE) on

19 th 

### December 2002 (deliberation n. 123 of 19/12/2002). The Kyoto Protocol finally entered into force on 16 th 

### February 2005. As a Party to the Convention and the Kyot o Protocol, Italy is committed to develop, publish and regularly update national emission inventories as well as formulate and implement programmes to

reduce these emissions. In order to establish compliance with national and international commitments air emission inventories are compiled and communicated annually to the competent institutions. Specifically, the national GHG emission inventory is communicated through compilation of the Common Reporting Format (CRF), according to the guidelines provided by the United Nations Framework Convention on Climate Change and the European Union’s Greenhouse Gas Monitoring Mechanism (IPCC, 1997; IPCC, 2000; IPCC, 2003; IPCC, 2006; EMEP/CORINAIR, 2005).

### 20

The inventory is updated annually in order to reflect revisions a nd improvements in methodology and availability of new information. Recalculations are applied retrospectively to earlier years, which account for any difference in previously published data. The submission also provides for detailed information on emissio n figures and estimation methodologies in the annual National Inventory Report.

As follows, this report is compiled according to the guidelines on reporting as specified in the document FCCC/SBSTA/2002/L.5. It provides an analysis of the 200 7 Italian GHG emission inventory, and a revision of the entire time series 1990

- 2006 , communicated in the framework of the Climate Change Convention and the Kyoto Protocol. It is also the annual submission to the European Commission in the framework of the Greenhouse G as Monitoring Mechanism.

T he assigned amount for Italy, pursuant to Article 3 , paragraphs 7 and 8, of the Kyoto Protocol, and
calculated in accordance with the annex to decision 13/CMP.1, has been established during the last in country review in 2007. T h e commitment period reserve (CPR), required in accordance with paragraph 18 of decision 15 / CMP.1, has also been calculated and confirmed during the review . The

determine d figures are reported in the document FCCC/IRR/2007/ITA and amount to
2,416,277,898 to nnes CO 2 

### eq

., for the assigned amount

, and 2,174,650,108 tonnes of CO 2 

### eq.

, for the CPR. The CRP is calculated on the basis of the assigned amount so it has not change from the previous submission

s

.

Emission estimates comprise the six direct greenhouse ga ses under the Kyoto Protocol (carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons, sulphur hexafluoride) which contribute directly to climate change owing to their positive radiative forcing effect and four indirect greenhouse gase s (nitrogen oxides, carbon monoxide, non

- methane volatile organic compounds, sulphur dioxide). The CRF files, the national inventory reports and other related documents are available at the

address http://www.sinanet.apat.it/it/sinanet/serie_storiche_emissioni

. The official inventory submissions can also be found at the UNFCCC website http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/ite ms/ 4303.php.

1.2 Description of the institutional arrangement for inventory preparation

1.2.1 National Inventory System

The Legislative Decree 51 of March 7 th 

### 2008 institutes the National System for the Italian Greenhouse Gas Inventory. As required by arti

cle 5.1 of the Kyoto Protocol, Annex I Parties shall have in place a National System by the end of 2006 at the latest for estimating anthropogenic greenhouse gas emissions by sources and removals by sinks and for reporting and archiving inventory informati on according to the guidelines specified in the UNFCC Decision 20/COP.7. In addition, the Decision of the European Parliament and of the Council concerning a mechanism for monitoring Community greenhouse gas emissions (280/2004/EC) requires that Member Sta tes establish a national greenhouse gas inventory system by the end of 2005 at the latest and that the Commission adopts the EC’s inventory system by 30 June 2006. The ‘National Registry for Carbon sinks’, instituted by a Ministerial Decree on 1 st 

### April 2 008, is part of the Italian National System and includes information on units of lands subject of activities under Article 3.3 and activities elected under Article 3.4 and related carbon stock changes. The National Registry for Carbon sinks is the instrume nt to estimate, in accordance with the COP/MOP

### 21

decisions, the IPCC Good Practice Guidance on LULUCF and every relevant IPCC guidelines, the greenhouse gases emissions by sources and removals by sinks in forest land and related land

- use changes and to accou

nt for the net removals in order to allow the Italian Registry to issue the
relevant amount of removal units (RMUs). Detailed information on the Registry is included in

Annex 10, whereas additional information on activities under Article 3.3 and Article 3. 4 is reported in paragraph 1.2.2

.

The Italian National System, currently in place, is fully described in the document ‘National Greenhouse Gas Inventory System in Italy’ (APAT, 2008[a]). No changes with respect to the last year submission occurred in the National System. A summary picture is reported herebelow.

As indicated by art. 14 bis of the Legislative Decree, the Institute for Environmental Protection and

Research ( ISPRA

), former Agency for Environmental Protection and Technical Services ( APAT)

, is the single entity in charge of the development and compilation of the national greenhouse gas

emission. The Institute for Environmental Protection and Research (ISPRA) was established by

Italian Law 133/2 008 and performs the functions of three f ormer inst itutions: APAT, ICRAM (Central Institute for Applied Marine Research) and INFS (National Institute for Wildlife)

. The Ministry for the Environment, Land and Sea is responsible for the endorsement of the inventory

and for the communication to the Secretaria t of the Framework Convention on Climate Change and the Kyoto Protocol. The inventory is also submitted to the European Commission in the framework of the Greenhouse Gas Monitoring Mechanism.

The Institute develops annually a national system document wh ich includes all updated information on institutional, legal and procedural arrangements for estimating emissions and removals of greenhouse gases and for reporting and archiving inventory information. The last year report is publicly available at http://www.apat.gov.it/site/_files/NationalSystemItaly08.pdf

.

A specific unit of the Institute is responsible for the compilation of the Italian Atmospheric Emission Inventory and the I talian Greenhouse Gas Inventory in the framework of the Convention on Climate Change and the Convention on Long Range Transboundary Air Pollution. The whole inventory is compiled by the Institute ; scientific and technical institutions and consultants may h elp in improving information both on activity data and emission factors of some specific activities. All the measures to guarantee and improve the transparency, consistency, comparability, accuracy and completeness of the inventory are undertaken. ISPRA ( former APAT) bears the responsibility for the general administration of the inventory, co

ordinates participation in reviews, publishes and archives the inventory results. Specifically, ISPRA is responsible for all aspects of national inventory preparatio n, reporting and quality management. Activities include the collection and processing of data from different data sources, the selection of appropriate emissions factors and estimation methods consistent with the
IPCC 1996 Revised Guidelines, the IPCC Good Practice Guidance and Uncertainty management
and the IPCC Good Practice Guidance for land use, land

- use change and forestry, the compilation of the inventory following the QA/QC procedures, the assessment of uncertainty, the preparation of

the National In

ventory Report and the reporting through the Common Reporting Format, the response to the review process, the updating and data storage.

Different institutions are responsible for statistical basic data and data publication, which are primary to ISPRA

for carrying out emission estimates. These institutions are part of the National Statistical System (Sistan), which provides national official statistics, and therefore are asked periodically to update statistics; moreover, the National Statistical System ens ures the homogeneity of the methods used for official statistics data through a coordination plan, involving the entire public administration at central, regional and local levels.

### 22

The National Statistical System is coordinated by the Italian National Ins titute of Statistics (ISTAT) whereas other bodies, joining the National Statistical System, are the statistical offices of ministries, national agencies, regions and autonomous provinces, provinces, municipalities, research institutes,

chambers of commerce , local governmental offices, some private agencies and private subjects who have specific characteristics determined by law. The Italian statistical system was instituted on 6 th 

### September 1989 by the Legislative Decree n. 322/89, which established guiding principles and criteria for reforming public statistics. This decree addresses to all public statistical bodies and agencies which provide official statistics both at local, national and international level in order to assure homogeneity of the methods an d comparability of the results. To this end, a national statistical plan which defines surveys, data elaborations and project studies for a three

- year period shall be drawn up and updated annually, as established in the Decree n. 322/89. The procedures to be followed with relation to the annual fulfilment as well as the forms to be filled in for census, data elaborations and projects, and how to deal with sensitive

information are also defined. The plan is deliberated by the Committee for addressing and co ordinating statistical information (Comstat) and forwarded to the Commission for the assurance of statistical information; the Commission adopts the plan after endorsement of the Guarantor of the privacy of personal data. Finally, the plan is approved by a Prime Ministerial Decree after consideration of the Interministerial Committee for economic planning (Cipe). The latest Prime Ministerial Decree, which approved the three

- year plan for 200 8

- 2010 , was issued on 6 th 

### August 200 8 . The statistical

information

and results deriving from the completion of the plan are of public domain and the system is responsible for wide circulation. Ministries, public agencies and other bodies are obliged to provide the data and information specified in the annual statistical plan; the same obligations regard the private entities. All the data are protected by the principles of statistical disclosure control and can be distributed and communicated only at aggregate level even though microdata can circulate among the subjects o f the Statistical System. Sistan activity is supervised by the Commission for Guaranteeing Statistical Information (CGIS) which is an external and independent body. In particular, the Commission supervises: the impartiality and completeness of statistical information, the quality of methodologies, the compliance of surveys with EU and international directives. The Commission, established within the Presidency of the Council of Ministers, is composed of high

- profile university professors,

directors of stati stical or research institutes and managers of public administrations and bodies, which do not participate at Sistan.

The main Sistan products, which are primarily necessary for the inventory compilation, are:

• National Statistical Yearbooks, Monthly Statis tical Bulletins, by ISTAT (National Institute of Statistics);

• Annual Report on the Energy and Environment, by ENEA (Agency for New Technologies, Energy and the Environment);

• National Energy Balance (annual), Petrochemical Bulletin ( quarterly publication), by MSE (Ministry of Economic Development);

• Transport Statistics Yearbooks, by MINT (Ministry of Transportation);

• Annual Statistics on Electrical Energy in Italy, by TERNA (National Independent System Operator);

• Annual Report on Waste, by ISPRA ;

• National Forestry Inventory, by MIPAAF ( Ministry of Agriculture, Food and Forest Policies).

The national emission inventory itself is a Sistan product.

### 23

Other information and data sources are used to carry out emission estimates, which are gene rally

referred to in Table 1.1 of the following section 1.4

1.2.2 Institutional arrangement for reporting under Article 3, paragraphs 3 and 4 of Kyoto

Protocol

The ‘National Registry for Carbon sinks’ has been instituted by a Ministerial D ecree on 1 st 

### April 2008 and is part of the National Greenhouse Gas Inventory System in Italy (APAT, 2008 [a ]); at the

moment, there isn’t a fund for the activities related to art. 3.3 and 3.4 of Kyoto, considering that the fund of 2 million euros per year for each of the years 2008, 2009 and 2010 established in the Budget Law 2008 (subparagraph 335) was zeroed by the actual Government. The National Registry for Carbon sinks should have been in place from January 2008, to supply data for the first Kyoto

sub mission in January 2010. Up to now, National Registry for Carbon Sinks is not operational even though, in the last months, a technical group, formed by experts from different istitutions (ISPRA, Ministry for the Environment, Land and Sea, Ministry of Agric ulture, Food and Forest Policies and University of Tuscia), is working to set up the methodological plan of the activities and define the relative funding

.

The description of the main elements of the institutional arrangement under Article 3.3 and

activit ies elected under Article 3.4 is detailed in Annex 10

.

The forest definition adopted by Italy agrees with the Food and Agriculture Organization of the

United Nations definitions, therefore the threshold values for tree crown cover, land area and tree heig ht are applied:

a. a minimum area of land of 0.5 hectares;

b. tree crown cover of 10 per cent;

c. minimum tree height of 5 meters.

Deforestation data will be derived from administrative records, inventory data and mapping

information. These sources of information will be also used to distinguish deforestation from

harvested areas.

Regarding the selection of activities under Article 3, paragraph 4, for accounting in the first commitment period, Italy has elected forest management activity. Under SBSTA conclusion

F CCC/SBSTA/2006/L.6 and related COP/MOP2 decision 1 

### , credits from forest management are capped, in the first commitment period, to 2.78 Mt C per year times fives. Italy intends to account for Article 3.3 and 3.4 elected activities for the entire commitment p eriod.

1.2.3 National Registry System

The Italian Government modified the previous Legislative Decree 216/2006 which enforced the Directive 87/2003/CE, by the new Legislative Decree 51 of March 7th 2008. Due to this new
Decree, ISPRA (former APAT) is re sponsible for developing, operating and maintaining the national registry under Directive 2003/87/CE; the Institute performs these tasks under the supervision of the national Competent Authority for the implementation of directive 2003/87/CE, jointly estab lished by the Ministry for Environment, Land and Sea and the Ministry for Economic Development. ISPRA, as Registry Administrator, becomes responsible for the management and functioning of the Registry, including Kyoto protocol obligations.

1 FCCC/KP/CMP/2006/10/Add.1

- Decision 8/CMP.2, Forest management under Article 3, paragraph 4, of the Kyoto
Protocol: Italy

### 24

The Decree 51/2 008 also establishes that the economic resources for the technical and administrative support of the Registry will be supplied to ISPRA by operators paying a fee for the use of the Registry. The amount of such a fee will be regulated by a future Decree.

I taly carried out all required steps of the initialization process with the UNFCCC: in particular, Italy successfully performed and passed:

• SSL connectivity testing (Oct. 26 th 

### 2007);

• VPN connectivity testing (Oct. 15 th 

### 2007);

• Interoperability test according to Annex H of the UN Data Exchange Standards (DES) (Nov.

9 th 

### 2007), and submitted all required information through a complete Readiness questionnaire.

This implies that the Italian registry fulfilled all of its obligations regarding conformity with the U N DES. These obligations include having adequate transaction procedures, adequate security measures to prevent and resolve unauthorized manipulations and adequate measures for data storage and registry recovery. The registry was therefore deemed fully comp liant with the registry requirements

defined in decisions 13/CMP.1 and 5/CMP.1.

As a result, Italy could participate to the “ETS go

- live” event that took place in October 2008. After successful completion of the go

- live process on 16 th 

### October 2008, the I talian registry commenced live operations with the ITL and it’s been operational ever since.

All data referring to units holdings and transactions during the year 2008 are reported in the SEF

submission. All relevant figures are included in Annex 11. I n 2 008, no discrepant transactions, no invalid units, no CDM notifications or non

- replacements, have been detected.

Information on accounts, legal entities , Art. 6 projects, holdings and transactions is publicly

available at www.greta

- public.sinanet.apat.it

.

At present, Italy is also operating its registry under Article 19 of Directive 2003/87/CE establishing the EU Emission Trading Scheme and according to Regulation No. 2216/2004 of the European

Commis sion, which require national registries to be compliant with the UN DES document. The Italian registry is based on the GRETA registry software developed by the UK Department for Environment, Food and Rural Affairs (DEFRA) and used by many other Member Stat es. Currently, the development of this software adheres to the standards specified in Draft #7 of the UN DES document. Italy had the registry systems tested successfully with the EU Commission on February

6 th 

### 2006; the connection between the registry’s pro duction environment and the CITL was

established on March 13 th 

### 2006 and the Registry has since gone live, starting on March 28 th 

### 2006. Detailed information on the national registry is reported in Annex 1 1.

1.3 Brief description of the process of inventory pr eparation

ISPRA has established fruitful cooperation with a number of governmental and research institutions as well as industrial associations, which helps improving some leading categories of the inventory. Specifically, these activities aim at the impr ovement of provision and collection of basic data and emission factors, through plant

- specific data, and exchange of information on scientific researches
and new sources. Moreover, when in depth investigation is needed and a high uncertainty in the

estimat es is present, specific sector analyses are committed to ad hoc research teams or consultants.

ISPRA also coordinates with different national and regional authorities and private institutions for

the cross

- checking of parameters and estimates as well as w ith ad hoc expert panels in order to improve the completeness and transparency of the inventory.

### 25

The main basic data needed for the preparation of the GHG inventory are energy statistics published by the Ministry of Economic Development Activities (MSE) in the National Energy Balance (BEN), statistics on industrial and agricultural production published by the National Institute of Statistics (ISTAT), statistics on transportation provided by the Ministry of Transportation (MINT), and data supplied directly by the relevant professional associations. Emission factors and methodologies used in the estimation process are consistent with the IPCC Good Practice Guidance and supported by national experiences and circumstances. Final decisions are up to inventory e xperts, taking into account all the information available.

For the industrial sector, emission data collected through the National Pollutant Emission Register
( EPER

, E

- PRTR

), the Large Combustion Plant (LCP) Directive and in the framework of the European Emissions Trading Scheme have yielded considerable developments in the inventory of the relative sectors. In fact, these data, even if not always directly used, are taken into account as a verification of emission estimates and improve national emissions factors as well as activity data figures. In addition, final estimates are checked and verified also in view of annual environmental reports by

industries. For large industrial point sources, emissions are registered individually, when communicated, based upon detailed information such as fuel consumption. Other small plants communicate their emissions which are also considered individually.

Emission estimates are drawn up for each sector. Final data are communicated to the UNFCCC Secretariat filling in the CRF files.

The process of the inventory preparation takes place annually. In addition to a new year, the entire time series from 1990 onwards is checked and revised during the annual compilation of the inventory in order to meet the requirements of t ransparency, consistency, comparability, completeness and accuracy of the inventory. Measures to guarantee and improve these qualifications are undertaken and recalculations should be considered as a contribution to the overall improvement of the inventory

. In particular, recalculations are elaborated on account of changes in the methodologies used to carry out emission estimates, changes due to different allocation of emissions as compared to previous submissions and changes due to error corrections. The inventory may also be expanded by including categories not previously estimated if sufficient information on activity data and suitable

emission factors have been identified and collected. Information on the major recalculations is provided every year in the sectoral and general chapters of the national inventory reports; detailed explanations of recalculations are also given compiling

the relevant CRF tables.

All the reference material, estimates and calculation sheets, as well as the documentation on

s cientific papers and the basic data needed for the inventory compilation, are stored and archived at

the Institute . After each reporting cycle, all database files, spreadsheets and electronic documents

are archived as ‘read

- only

- files’ so that the document ation and estimates could be traced back during the review process or the new year inventory compilation.

Technical reports and emission figures are publicly accessible by website at the address http://www.sinanet.apat.it/it/sinanet/serie_storiche_emissioni

.

### 26

1.4 Brief general description of methodologies and data sources used

A detailed description of methodologies and data sources used in the preparation of the emission

invento ry for each sector is outlined in the relevant chapters. In Table 1.1 a summary of the activity data and sources used in the inventory compilation is reported.

Methodologies are consistent with the Revised 1996 IPCC Guidelines, IPCC Good Practice

Guidance and EMEP

- CORINAIR Emission Inventory Guidebook (IPCC, 1997; IPCC, 2000; IPCC,
2003; EMEP/CORINAIR, 200 7 ) ; national emission factors are used as well as default emission factors from international guidebooks, when national data are not available. The devel opment of national methodologies is supported by background documents.

SECTOR ACTIVITY DATA SOURCE

1 Energy
1A1 Energy Industries Fuel use Energy Balance - Ministry of Economic Development
Major national electricity producers
European Emissions Trading Scheme

1A2 Manufacturing Industries Fuel use Energy Balance - Ministry of Economic Development

and Construction Major National Industry Corporation
European Emissions Trading Scheme

1A3 Transport Fuel use Energy Balance - Ministry of Economic Development

Number of vehicles Statistical Yearbooks - National Statistical System Aircraft landing and take-off Statistical Yearbooks - Ministry of Transportation
cycles and maritime activities Statistical Yearbooks - Italian Civil Aviation Authority (ENAC)
Maritime and Airport local authorities

1A4 Residential-public-commercial sector Fuel use Energy Balance - Ministry of Economic Development

1B Fugitive Emissions from Fuel Amount of fuel treated, Energy Balance - Ministry of Economic Development
stored, distributed Statistical Yearbooks - Ministry of Transportation
Major National Industry Corporation

2 Industrial Processes Production data National Statistical Yearbooks- National Institute of Statistics

International Statistical Yearbooks-UN
European Emissions Trading Scheme European Pollutant Emission Registry

Sectoral Industrial Associations

3 Solvent and Other Product Use Amount of solvent use National Environmental Publications - Sectoral Industrial Associations

International Statistical Yearbooks - UN

4 Agriculture Agricultural surfaces Agriculture Statistical Yearbooks - National Institute of Statistics

Production data Sectoral Agriculture Associations

Number of animals
Fertiliser consumption

5 Land Use, Land Use Change Forest and soil surfaces Statistical Yearbooks - National Institute of Statistics
and Forestry Amount of biomass State Forestry Corps

Biomass burnt National and Regional Forestry Inventory
Biomass growth Universities and Research Institutes

6 Waste Amount of waste National Waste Cadastre - Institute for Environmental Protection and
Research , National Waste Observatory

Table 1.1 Main activity data and sources for the Italian Emission Inventory



### In Table 1.2 a summary of the methods and emission factors used in the compilation of the Italian

invent ory is reported. A more detailed table, as communicated to the European Community in the

### 27

framework of the monitoring mechanism of GHG emission inventory for the purpose of Article 4(1)(b) under the Implementing Provisions (EC, 2005), is included in Annex 9.

SUMMARY 3 SUMMARY REPORT FOR METHODS AND EMISSION FACTORS USED

GREENHOUSE GAS SOURCE AND SINK HFCs PFCs SF 6

CATEGORIES Method

applied (1) Emission

factor (2) Method

applied (1) Emission

factor (2) Method applied

(1) Emission

factor (2) Method

applied (1) Emission

factor (2) Method

applied (1) Emission

factor (2) Method

applied (1) Emission

factor (2)

1. Energy D,M,T1,T2,T3 CS,D D,M,T1,T2,T3 CR,CS,D D,M,T1,T2,T3 CR,CS,D

A. Fuel Combustion D,M,T1,T2,T3 CS D,M,T1,T2,T3 CR,CS,D D,M,T1,T2,T3 CR,CS,D

1. Energy Industries T3 CS T3 CR,D T3 CR,D

2. Manufacturing Industries and Construction T2 CS T2 CR,D T2 CR,D

3. Transport D,M,T1,T2 CS D,M,T1,T2 CR,CS D,M,T1,T2 CR,CS

4. Other Sectors T2 CS T2 CR T2 CR

5. Other T2 CS T2 CR T2 CR
B. Fugitive Emissions from Fuels T1,T2 CS,D T1,T2 CR,CS,D T1 D

1. Solid Fuels NA NA T1 CR,CS,D NA NA

2. Oil and Natural Gas T1,T2 CS,D T1,T2 CS,D T1 D

2. Industrial Processes D,T2 CR,CS,D,PS D CR,CS,PS D D,PS CS,D,T2 CS,D,PS CS,T2 D,PS CS,D,T3 CS,PS

A. Mineral Products D,T2 CS,D,PS NA NA NA NA

B. Chemical Industry D CR,PS D CR,CS,PS D D,PS NA NA NA NA NA NA

C. Metal Production D CR,CS,PS D CR,CS,PS NA NA D PS T2 D,PS D PS

D. Other Production NA NA

E. Production of Halocarbons and SF 6 CS PS NA NA NA NA
F. Consumption of Halocarbons and SF 6 CS,T2 CS,D,PS CS PS CS,T3 CS,PS

G. Other NA NA NA NA NA NA NA NA NA NA NA NA

3. Solvent and Other Product Use CR,CS CR,CS CS CS

4. Agriculture D,T1,T2 CS,D D,T2 CS,D

A. Enteric Fermentation T1,T2 CS,D

B. Manure Management T1,T2 CS,D T2 CS,D

C. Rice Cultivation T2 CS
D. Agricultural Soils NA NA D CS,D

E. Prescribed Burning of Savannas NA NA NA NA
F. Field Burning of Agricultural Residues D CS,D D CS,D

G. Other NA NA NA NA
5. Land Use, Land-Use Change and Forestry T1,T2 CS,D T1 D T1 D

A. Forest Land T1,T2 CS,D T1 D T1 D
B. Cropland T1 CS,D NA NA NA NA

C. Grassland T1 CS,D NA NA NA NA

D. Wetlands NA NA NA NA NA NA

E. Settlements T1 CS,D NA NA NA NA

F. Other Land NA NA NA NA NA NA

G. Other NA NA NA NA NA NA

6. Waste D CS CS,D,T2 CR,CS,D D CR,CS,D

A. Solid Waste Disposal on Land NA NA T2 CS

B. Waste-water Handling D D D CR,D

C. Waste Incineration D CS D CR D CS

D. Other NA NA CS CS NA NA

7. Other (as specified in Summary 1.A) NA NA NA NA NA NA NA NA NA NA NA NA

Use the following notation keys to specify the method applied:

D (IPCC default) T1a, T1b, T1c (IPCC Tier 1a, Tier 1b and Tier 1c, respectively) CR (CORINAIR)

RA (Reference Approach) T2 (IPCC Tier 2) CS (Country Specific)

T1 (IPCC Tier 1) T3 (IPCC Tier 3) OTH (Other)

Use the following notation keys to specify the emission factor used:

D (IPCC default) CS (Country Specific) OTH (Other)

CR (CORINAIR) PS (Plant Specific)
Where a mix of emission factors has been used, list all the methods in the relevant cells and give further explanations in the documentation box. Also use the documentation box to explain the use of notation OTH. CO 2 CH 4 N 2 O

If using more than one method within one source category, list all the relevant methods. Explanations regarding country-specific methods, other methods or any modifications to the default IPCC methods, as well as information

Table 1.2 Methods and emission factors used in the inventory preparation



### Activity data used in emission calculations and their sources are briefly described herebelow.

In general, for the energy sector, basic statistics for estimating emissions ar e fuel consumption published in the Energy Balance by the Ministry of Economic Development. Additional information for electricity production is provided by the major national electricity producers and by the major national industry corporation. On the oth er hand, basic information for road transport, maritime and aviation, such as the number of vehicles, harbour statistics and aircraft landing and

take

- off cycles are provided in statistical yearbooks published both by the National Institute of

Statistics a

nd the Ministry of Transportation. Other data are communicated by different category

associations.

The analysis of data from the Italian Emissions Trading Scheme database is used to develop

country

- specific emission factors and check activity data levels

.

### 28

For the industrial sector, the annual production data are provided by national and international statistical yearbooks. Emission data collected through the National Pollutant Emission Register (EPER , E

- PRTR ) are also used in the development of emission e stimates or taken into account as a verification of emission estimates for some specific categories. According to the Italian Decree of 23 November 2001, data from the Italian EPER are validated and communicated by ISPRA to the Ministry for the Environment , Land and Sea and to the European Commission within October of the current year for data referring to the previous year. These data are used for the compilation of the inventory whenever they are complete in terms of sectoral information; in fact, industr ies communicate figures only if they exceed specific thresholds; furthermore, basic data such as fuel consumption are not supplied and production data are not split by product but reported as an overall value. Anyway, EPER is a good basis for data checks a nd a way to facilitate contacts with industries which, in many cases, supply, under request, additional information as necessary for carrying out sectoral emission estimates. In addition, final emissions are checked and verified also taking into account f igures reported by industries in their annual environmental reports.

Both for energy and industrial processes, emissions of large industrial point sources are registered individually; communication also takes place in the framework of the European Direct ive on Large Combustion Plants, based upon detailed information such as fuel consumption. Other small plants communicate their emissions which are also considered individually.

For the other sectors, i.e. for solvents, the amount of solvent use is provide d by environmental publications of sector industries and specific associations as well as international statistics. For agriculture, annual production data and number of animals are provided by the National

Institute of Statistics and other sectoral assoc iations. For land use, land use change and forestry, forest and soil surfaces are provided by the National Institute of Statistics while statistics on forest fires are supplied by the State Forestry Corps. For waste, the main activity data are provided b y the Agency for Environmental Protection and Technical Services and the Waste Observatory.

In case basic data are not available proxy variables are considered; unpublished data are used only if supported by personal communication and confidentiality of d ata is respected. All the material and documents used for the inventory emission estimates are stored at the Agency for Environmental Protection and Technical Services. The inventory is composed by spreadsheets to calculate emission estimates; activity dat a and emission factors as well as methodologies are referenced to their data sources. A ‘reference’ database has also been developed to increase the transparency of the inventory.

1.5 Brief description of key categories

A key category analysis of the Italia n inventory is carried out according to the Tier 1 and Tier 2

methods described in the IPCC Good Practice Guidance with and without emissions and removals from the LULUCF sector (IPCC, 2000; IPCC, 2003). According to these guidelines, a key category

is def ined as an emission category that has a significant influence on a country’s GHG inventory in terms of the absolute level and trend in emissions and removals, or both. Key categories are those which, when summed together in descending order of magnitude, a dd up to over 95% of the total

emissions.

National emissions have been disaggregated into the categories proposed in the Good Practice Guidance; other categories have been added to reflect specific national circumstances. Both level

### 29

and trend analysis ha ve been applied to the last submitted inventory; a key category analysis has also been carried out for the base year emission levels.

For the base year, 1

9 sources were individuated according to the Tier 1 approach, whereas 22 sources were carried out by the Tier 2. Including the LULUCF categories in the analysis, 2 5 categories were selected jointly by the Tier 1 and the Tier 2. The description of these sources is

shown in Table 1.3 and Table1.4.

Key categories (excluding the LULUCF sector)

CO 2 station ary combustion liquid fuels L

CO 2 stationary combustion solid fuels L

CO 2 stationary combustion gaseous fuels L

N 2 O stationary combustion L

CO 2 Mobile combustion: Road Vehicles L

CO 2 Fugitive emissions from Oil and Gas Operations L

CH 4 Fugitive emis sions from Oil and Gas Operations L

CO 2 Cement production L

N 2 O Adipic Acid L

CH 4 Enteric Fermentation in Domestic Livestock L

N 2 O Manure Management L

CH 4 Manure Management L

Direct N 2 O Agricultural Soils L

Indirect N 2 O from Nitrogen used in agricul ture L

CH 4 from Solid waste Disposal Sites L

CO 2 Iron and steel production L 1

CO 2 Mobile combustion: Waterborne Navigation L1

CO 2 Limestone and dolomite use L1

N 2 O Nitric Acid L1

N 2 O Mobile combustion: Road Vehicles L2

CO 2 Emissions from solvent use L2

N 2 O Emissions from solvent use L2

N 2 O from animal production L2

CH 4 Emissions from Wastewater Handling L2

N 2 O Emissions from Wastewater Handling L2

CH 4 Mobile combustion: Road Vehicles L2
Table 1.3 Key categories (excluding LULUCF) by the IPCC Ti er 1 and Tier 2 appro aches (L=Level)

. Base year

Key categories (including the LULUCF sector)

CO 2 stationary combustion liquid fuels L

CO 2 stationary combustion solid fuels L

CO 2 stationary combustion gaseous fuels L

N 2 O stationary combustion L

CO 2 Mobile combustion: Road Vehicles L

CH 4 Fugitive emissions from Oil and Gas Operations L

CO 2 Cement production L

CH 4 Enteric Fermentation in Domestic Livestock L

CH 4 Manure Management L

N 2 O Manure Management L

Direct N 2 O Agricultural Soils L

Indirect N 2 O from Nitrogen used in agriculture L

CH 4 from Solid waste Disposal Sites L

CO 2 Forest land remaining Forest land L L1 = level key category by Tier 1 L2 = level key category by Tier 2
L = level key category by Tier 1 and Tier 2

L1 = level key category by Tier 1 L2 = level key category by Tier 2
L = level key category by Tier 1 and Tier 2

### 30

CO 2 Cropland remaining Cropland L

CO 2 Land converted to Forest Land L

CO 2 Fugitive emissions from Oil and Gas Operations L

CO 2 Mobi le combustion: Waterborne Navigation L1

CO 2 Iron and steel production L1

N 2 O Adipic Acid L1

CO 2 Limestone and Dolomite Use L1

N 2 O from animal production L2

CH 4 Emissions from Wastewater Handling L2

CO 2 Emissions from solvent use L2

CO 2 Land converte

d to Settlements L2
Table 1.4 Key categories (including LULUCF) by the IPCC Tier 1 and Tier 2 approaches (L=Level) . Base year



### Applying the category analysis to the 200 7 inventory, without considering the LULUCF sector, 2 9 key categories were totally indi viduated, both at level and trend. Results are reported in Table 1.5.

Key categories (excluding the LULUCF sector)

CO 2 stationary combustion liquid fuels L, T

CO 2 stationary combustion solid fuels L, T

CO 2 stationary combustion gaseous fuels L, T

CO 2 Mobile combustion: Road Vehicles L, T

N 2 O Mobile combustion: Road Vehicles L 2

CH 4 Fugitive emissions from Oil and Gas Operations L, T

HFC, PFC substitutes for ODS L, T

CH 4 Enteric Fermentation in Domestic Livestock L, T

Direct N 2 O Agricultural Soils L, T

Indirect N 2 O from Nitrogen used in agriculture L, T 2

CO 2 Cement production L, T2

N 2 O Manure Management L, T2

CH 4 Manure Management L, T2

CH 4 from Solid waste Disposal Sites L, T2

CO 2 Fugitive emissions from Oil and Gas Operations L2, T

N 2 O sta tionary combustion L

N 2 O Adipic Acid T

CO 2 stationary combustion other fuels L 1 , T 1

CO 2 Emissions from solvent use L2, T2

N 2 O from animal production L2, T2

CH 4 Emissions from Wastewater Handling L2, T2

N 2 O Emissions from Wastewater Handling L2, T2

C O 2 Mobile combustion: Waterborne Navigation L1, T2

CH 4 stationary combustion L2

CO 2 Limestone and Dolomite Use L 1

CO 2 Iron and steel production T 1

CO 2 Ammonia production T 1

PFC Aluminium production T 1

N 2 O Emissions from solvent use T2 Table 1.5 Key categories (excluding LULUCF) by the IPCC Tier 1 and Tier 2 approaches (L=Level, T=Trend)

. Year 200 7



### If considering emissions and removals from the LULUCF sector, 2 8 key categories were individuated as reported in Table 1.6. There are no additional categ ories as compared to the previous analysis expect for those referring to

the LULUCF sector. L1 = level key category by Tier 1

T1 = t rend key category by Tier 1 L2 = level key category by Tier 2
T2 = trend key category by Tier 2 L = level key category by Tier 1 and Tier 2
T = trend key category by Tier 1 and Tier 2

### 31 Key categories (including the LULUCF sector)

CO 2 stationary combustion liquid fuels L, T

CO 2 stationary combustion solid fuels L, T

CO 2 stationary combustion gaseous fuels L, T

CO 2 Mobile combustion: Road Vehicles L, T

CH 4 Fugitive emissions from Oil and Gas Operations L, T

HFC, PFC substitutes for ODS L, T

CH 4 Enteric Fermentation in Domestic Livestock L, T

Direct N 2 O Agricultural Soils L, T

CO 2 Forest l and remaining Forest land L, T

CO 2 Cropland remaining Cropland L, T

CO 2 Land converted to Grassland L, T

Indirect N 2 O from Nitrogen used in agriculture L, T

N 2 O Manure Management L, T2

CH 4 from Solid waste Disposal Sites L, T2

CO 2 Cement production L , T2

CO 2 Land converted to Settlements L , T 2

CH 4 Manure Management L ,T2

CO 2 stationary combustion other fuels L1, T1

CH 4 Emissions from Wastewater Handling L2, T2

CO 2 Land converted to Forest Land L2, T2

N 2 O stationary combustion L

CO 2 Mobile combus tion: Waterborne Navigation L 1

CO 2 Fugitive emissions from Oil and Gas Operations T1

N 2 O Adipic Acid T1

CO 2 Iron and steel production T1

PFC Aluminium production T1

N 2 O from animal production L2

N 2 O Emissions from Wastewater Handling T2

Table 1.6 Ke y categories (including LULUCF) by the IPCC Tier 1 and Tier 2 approaches (L=Level, T=Trend)

. Year 200 7

.



### It should be noted that higher tiers are mostly used for calculating emissions from these categories as requested by the Good Practice Guidance (IPCC, 2000).

1.6 Information on the QA/QC plan including verification and treatment of confidentiality

issues where relevant

ISPRA has elaborated an inventory QA/QC plan which describes specific QC procedures to be implemented during the inventory development pro cess, facilitates the overall QA procedures to be conducted, to the extent possible, on the entire inventory and establishes quality objectives. Particularly, an inventory QA/QC procedures manual ( APAT, 2006 [b]) has been drawn up which describes QA/QC pr ocedures and verification activities to be followed during the inventory compilation and helps in the inventory improvement. Furthermore, s pecific QA/QC procedures and different verification activities implemented thoroughly the current inventory compilati on, as part of the estimation process, are figured out in the annual QA/QC plans (APAT, 2005; APAT, 2006 [c];
APAT, 2007 [a]; APAT, 2008 [b]). These documents are publicly available at ISPRA website http://www.apat.gov.it/site/it

- IT/APAT/Pubblicazioni/Altre_Pubblicazioni.html

.

Quality control checks and quality assurance procedures together with some verification activities are applied both to the national invent ory as a whole and at sectoral level. Future planned improvements are prepared for each sector, by the relevant inventory compiler; each expert L1 = level key category by Tier 1 T1 = trend key category by Tier 1

L2 = level key category by Tier 2
T2 = trend key category by Tier 2 L = level key category by Tier 1 and Tier 2
T = trend key category by Tier 1 and Tier 2

### 32

identifies areas for sectoral improvement based on his own knowledge and in response to inventory

UNFCCC reviews and other kind of processes. The quality of the inventory has improved over the years and further investigations are planned for

all those sectors relevant in terms of contribution to total CO 2 

### equivalent emissions and with a high uncertainty.

In addit ion to routine general checks, source specific quality control procedures are applied on a case by case basis focusing on key categories and on categories where significant methodological and data revision have taken place or on new sources.

Checklists ar e compiled annually by the inventory experts and collected by the QA/QC coordinator. These lists are also registred in the ‘reference’ database. General QC procedures also include data and documentation gathering. Specifically, the inventory analyst for a source category maintains a complete and separate project archive for that source category; the archive includes all the materials needed to develop the inventory for that year and is kept in a transparent manner.

All the information used for the inventor y compilation is traceable back to its source. The inventory is composed by spreadsheets to calculate emission estimates; activity data and emission factors as well as methodologies are referenced to their data sources. Particular attention is paid to the archiving and storing of all inventory data, supporting information, inventory records as well as all the reference documents. To this end, a major improvement which increases the transparency of the inventory has been the development of a ‘reference’ data base. After each reporting cycle, all database files, spreadsheets and official submissions are archived as ‘read

- only’ mode in a master

computer.

Quality assurance procedures regard some verification activities of the inventory as a whole and at

sectoral level. Feedbacks for the Italian inventory derive from communication of data to different institutions and/or at local level. For instance, the communication of the inventory to the European Community results in a pre

- check of the GHG values before the s ubmission to the UNFCCC and relevant inconsistencies may be highlighted.

Even though official independent and public reviews prior to the Italian inventory submission are not implemented yet, emission figures are subjected to a process of re

- examination once the inventory, the inventory related publications and the national inventory reports are posted on website, specifically www.apat.gov.it , and from the communication of data to different institutions

and/or at lo cal level. In some cases, sectoral major recalculations are presented and shared with the relevant stakeholders prior to the official submission.

For istance this year, there has been a revision of the methodology and an update of emission

factors to esti

mate emissions from the aviation and maritime sectors. Emissions have also been calculated at point source level for the major airports and ports and results have been presented to

the relevant sectoral authorities which c omments have been considered befor e publishing the final figures

. This work has also been develeped in the framework of the extension of the European Emissions Trading Scheme to the aviation sector.
In addition, for the industrial sector

, different meetings have been held jointly with the industrial

associations

, the Ministries of the Environment and Economic Development and ISPRA

in the

framework

of the European Emissions Trading Scheme , specifically for assessing carbon leakage in EU energy intensive industries ; also in this context, esti mations of the emission inventory for different sectors have been presented.

### 33

In 2008 , ISPRA has finalised the provincial inventory at local scale for the years 1990, 1995, 2000
and 2005; in f

a ct, every 5 years, in the framework of the Protocol on Long

- term Financing of the Cooperative Programme for Monitoring and Evaluation of the Long

- range Transmission of Air Pollutants in Europe (EMEP) under the Convention on Long

- range Transboundary Air Pollution (CLTRAP), Parties has to report their national air emissi ons disaggregated on a 50*50 km grid. Specifically, ISPRA has applied a top

- down approach to estimate emissions at provincial areas based on proxy variables. The results were checked out by regional and local environmental agencies and authorities ; data ar e already available at ISPRA web address http://www.sinanet.apat.it/it/inventaria and a report which describes detailed methodologies to carry out estimates is under publication.

T he inventory is als o presented to a Technical Committee on Emissions (CTE), coordinated by the Ministry for the Environment, Land and Sea, where all the relevant Mini s tries and local author i ties are represented; within this task emission figures and results are shared and di scussed. Expert peer reviews of the national inventory also occur annually within the UNFCCC process, whose results and suggestions can provide valuable feedback on areas where the inventory should be improved. Specifically, in June 2007, Italy was subjec ted by the UNFCC Secretariat to the in

country review of the national initial report and the GHG inventory submitted in 2006, which

results and recommendations can be found on website at the addresses http://unfccc.int/resource/docs/2007/arr/ita.pdf

, http://unfccc.int/resource/docs/2007/irr/ita.pdf

, (UNFCCC, 2007 [a]; UNFCCC, 2007 [b]). The results of the 2008 centralised revie w are reported in UNFCCC (2009).

Moreover, at European level, voluntary reviews of the European inventory are undertaken by experts from different Member States for critical sectoral categories.

The only official review, apart from those by the UNFCCC, was performed by Ecofys, in 2000, in order to verify of the effectiveness of policies and measures undertaken by Italy to reduce greenhouse gas emissions to the levels established by the Kyoto Protocol. In this framework an independent review and checks o n emission levels were carried out as well as controls on the transparency and consistency of methodological approaches (Ecofys, 2001).

The preparation of environmental reports where data are needed at different aggregation levels or

refer to different co ntexts, such as environmental and economic accountings, is also a check for emission trends. At national level, for instance, emission time series are reported in the Environmental Data Yearbooks published by the Agency. Emission data are also published by the Ministry for the Environment, Land and Sea in the Reports on the State of the Environment and the National Communications as well as in the Demonstrable Progress Report. Moreover, figures are

communicated to the National Institute of Statistics to be published in the relevant Environmental Statistics Yearbooks as well as used in the framework of the EUROSTAT NAMEA Project. At European level, ISPRA also reports on indicators meeting the requirements of Article 3 (1)(j) of Decision N° 280/2004/EC. In pa rticular, Member States shall submit figures on specified priority indicators and should submit information on additional priority and supplementary indicators for the period from 1990 to the last submitted year and forecasts for some specified years. The national trends of these indicators are explained in the report ‘Carbon Dioxide Intensity Indicators’ (APAT, 2007 [b]; APAT, 2008 [b]). Also these reports are posted on ISPRA website http://www.apat.gov.it/site/it

- IT/APAT/Pubblicazioni/Altre_Pubblicazioni.html

.

Comparisons between national activity data and data from international databases are usually

carried out in order to find out the main differences and an explanation to them. Emission intensity indicators among countries (e.g. emissions per capita, industrial emissions per unit of value added, road transport emissions per passenger car, emi s sions from power generation per kWh of electricity

### 34

produced, emissi

ons from dairy cows per tonne of milk produced) can also be useful to provide a preliminary check and verification of the order of magnitude of the emissions. This is carried out at

Eur o pean and international level by considering the annual reports compile d by the EC and the

UNFCCC as well as related documentation available from international databases and outcome of

relevant wor

k shops. Additional comparisons between emission estimates from industrial sectors and those published by the industry itself in th

eir Environmental reports are carried out annually in order to assess the quality and the uncertainty of the estimates. The quality of the inventory has also improved by the organization and participation in sector specific workshops. Follow

- up processes are also set up in the framework of the WGI under the EC Monitoring Mechanism, which addresses to the improvement of different inventory sectors. Specifically in the last years, two workshops were held, one related to the management of uncertainty in natio nal inventories and problems on the application of higher methodologies to calculate uncertainty figures, the other on how to use data from the European emissions trading scheme in the national greenhouse gas inventories. Previous workshops addressed metho dologies to estimate emissions from the agriculture and LULUCF sectors, involving the Joint Research Centre, from the waste sector, involving the European Topic Center on Resource and Waste Management, as well as from international bunkers, involving the I nternational Energy Agency and EUROCONTROL. Presentations and documentation of the workshops are available on the website

at the address: http://air

- climate.eionet.europa.eu/meetings/pa st_html

. A national conference on the Italian emission inventory was organized by ISPRA in October 2006. Methodologies used to carry out national figures and results of time series from 1990 to 2004 were presented detailing explanations for each sector. M ore than one hundred participants from national and local authorities, Ministries, Industry, Universities and Research organizations attended the two days meeting. In 2007, in the context of the national conference on climate change a specific session wa s dedicated to the national emission inventory. In addition, a specific event was held on the r esults of

the 2005 national GHG

inventory. A specific procedure undertaken for improving the inventory regards the establishment of national expert panels (in p

articular, in road transport, land use change and forestry and energy sectors) which involve, on a voluntary basis, different institutions, local agencies and industrial associations cooperating for improving activity data and emission factors accuracy. Sp ecifically, for the LULUCF sector, following the election of the 3.3 and 3.4 activities and on account of an in

- depth analysis on the information needed to report LULUCF under the Kyoto Protocol, a Scientific
Committee, Comitato di Consultazione Scientific a del Registro dei Serbatoi di Carbonio Forestali, constituted by the relevant national experts has been established by the Ministry for the Environment, Land and Sea in cooperation with the Ministry of Agriculture, Food and Forest

Policies.

In addition t o these expert panels, ISPRA participates in technical working groups within the National Statistical System. These groups, named Circoli di qualità , coordinated by the National Institute of Statistics, are constituted by both producers and users of statis tical information with the aim of improving and monitoring statistical information in specific sectors such as transport, industry, agriculture, forest and fishing. As reported in previous sections, t hese activities improve the quality and details of basic data, as well as enable a more organized and timely communication.

Other specific activities relating to improvements of the inventory and QA/QC practises in the last year regarded the progress on the building of a unique database where information coll ected in the framework of different European directives, Large Combustion Plant, EPER and Emissions Trading, are gathered together thus highlighting the main discrepancies in information and detecting potential errors. Even though the database is not compl eted yet all the figures are considered in an overall approach and used in the compilation of the inventory.

### 35

A summary of all the main QA/QC activies over the past years which ensure the continous improvement of the inventory is presented in the document ‘ Quality Assurance/Quality Control plan for the Italian Emission Inventory. Year 2008’ (APAT, 2008 [a]).

A proper archiving and reporting of the documentation related to the inventory compilation process is also part of the national QA/QC programme.

All the material and documents used for the inventory preparation are stored at the Institute for

Environmental Protection and Research

. Information relating to the planning, preparation, and management of inventory a c tivities are

documented and archived. The archive is organised so that any skilled an a lyst could obtain rel

e vant data sources and spreadsheets, reproduce the inventory and review all decisions about assumptions and methodologies undertaken. A master docume n tation catalogue is generated for each in ventory year and it is poss ible to track changes in data and methodologies over time. Specifically, the

documentation i

n cludes:

• electronic copies of each of the draft and final inventory report, ele c tronic copies of the draft

and final CRF tables;

• electro nic copies of all the final, linked source category spreadsheets for the i n ventory estimates (including all spreadsheets that feed the emission sprea d sheets);

• results of the reviews and, in general, all documentation related to the corr e sponding inventory year submi s sion. After each reporting cycle, all database files, spreadsheets and electronic documents are archived as

‘read

- only’ mode. A ‘reference’ database is also compiled every year to increase the transparency of the inventory.

This database consist s of a number of records that references all documentation used during the inventory compilation, for each sector and submission year, the link to the electronically available documents and the place where they are stored as well as internal documentation on QA/QC procedures.

1.7 General uncertainty evaluation, including data on the overall uncertainty for the inventory totals

The IPCC Good Practice Guidance (IPCC, 2000) defines the Tier 1 and Tier 2 approaches to estimating uncertainties in national greenho use gas inventories. Quantitative estimates of the uncertainties for the Italian GHG inventory are calculated using a Tier 1 approach, which provides a calculation based on the error propagation equations. In addition, a Tier 2 approach, corresponding

to t he application of Monte Carlo analysis, has been applied to specific categories of the inventory but the results show that, with the information available at present, applying methods higher than the Tier 1 does not make a significant difference in figures

. The Tier 2 approach was applied to CO 2 

### emissions from road transport and N 2 

### O emissions from agricultural soils; in the first case measurements were available for emission factors so a low uncertainty was expected, in the other

no information on EFs was a vailable and a high uncertainty was supposed. A combination of Montecarlo and Bootstrap simulation was applied to CO 2 

### emissions, in consideration of the specific data availability assuming a normal distribution for activity data and for the emission factor of natural gas. T he overall uncertainty of CO 2 

### emissions for road transport resulted in 2.06 , lower than the Tier 1 approach which estimated a figure of 4.2; the reason of the difference is in the lower uncertainty resulting from the application of bootst rap analysis to the emission factor of diesel oil, all the other figures are very similar. For N 2 

### O emissions from agricultural soils, a Montecarlo analysis was applied assuming a normal distribution for activity data and two tests one with a lognormal and the other with a normal for emission factors; the results with the normal distribution

### 36

calculated an uncertainty figure equal to 32.44, lower than the uncertainty by the Tier 1 approach which was 102; in the case of the lognormal distribution there were problems caused by the formula specified in the IPCC guidelines which is affected by the unit and need s further study before a throughout application

. The importance of these results is that in n either of the case s does the uncertainty estimation of the na tional sectors result in an underestimation.

The results

and details of the study, ‘Evaluating uncertainty in the Italian GHG inventory’, were presented at a EU workshop on Uncertainties in Greenhouse Gas Inventories, held in Finland in September 2005, an

d they are also available on website at the address http://air

- climate.eionet.europa.eu/docs/meetings/050905_EU_GHG_Uncert_WS/meeting050905.html

. 

### A further research on uncertainty, specifically on the comparison of different methodologies to evaluate emissions uncertainty, was also carried out (Romano et al., 2004). For the Italian inventory, the application of the Tier 1 approach is described in An nex 1 considering

national total with or without emissions and removals from the LULUCF sector. Emission sources are disaggregated into a detailed level and uncertainties are therefore estimated for these categories. The Tier 1 approach estimates, for the 2007 total emission figures without LULUCF, an uncertainty

of 3. 3 % in the combined global warming potential (GWP) total emissions, whereas for the trend

between 1990 and 200 7 the analysis assesses an uncertainty of 2.6%. Including the LULUCF sector into th e national figures, the uncertainty according to the Tier 1 approach is equal to 6.4 % for the year 200 7 , whereas the uncertainty for the trend is estimated to be

5.3 %. The slight differences in the level uncertainty as compared the 2008 submission is due to the different weights of the different sources and the relative uncertainty figures.

The assessment

of uncertainty has also been applied to the base year emission levels. The results show an uncertainty of 3.5% in the combined GWP total emissions, excl uding emissions and
removals from LULUCF, whereas it increases to 7. 0 % including the LULUCF sector. QC procedures are also undertaken on the calculations of uncertainties in order to confirm the

correctness of the estimates and that there is sufficient doc umentation to duplicate the analysis. The assumptions on which uncertainty estimations are based are documented for each cat e gory. Figures used to draw up uncertainty analysis are checked both with the relevant analyst experts and

literature references and are consistent with the IPCC Good Practice Guidance (IPCC, 2000; IPCC,
2003). More in details, plant data are used to check and verify data in the industrial sector; these data also

include information from the Eu ropean Emissions T

rading S cheme, the Euro pean E

- PRTR registry

which is also collected and elaborated by the inventory team. Most of the times there is a correspondence among

activity data from

different databases so that the level of uncertainty could

be assumed lower than the one fixed at 3%; th e same occurs for emission factors coming from

measurements at plant level, even in this case the uncertainty may be assumed lower than the predetermined level

. Since the overall uncertainty of the Italian inventory is low due to the prevalence of the ener gy sector s ources out of the total which estimates derive from accurate

parameters, it has been decided to use conservative figure s, especially for energy and industrial

sectors

. For the categories w ith a high uncertainty further improvements are planned w henever

sectoral studies can be carried out . For this year , for example, researches have been implemented in

the LULUCF sector examining all available national studies and researches , regarding C content of
soils; resul ts improves the accuracy of emission inventory although not allowing the update of the default uncertainty values used for those categories.

1.8 General assessment of the completeness

The inventory covers all major sources and sinks, as well as direct and indirect gases, included in

the IPCC guidelines.

### 37 GHG Sector (2) Source/sink category (2) Explanation

Carbon 5 LULUCF 5.E.1 5.E.1 Settlements remaining Settlements

Carbon 5 LULUCF 5.E.1 5.E.1 Settlements remaining Settlements

Carbon 5 LULUCF 5.E.1 5.E.1 Settlements remaining Settlements

Carbon 5 LULUCF 5.E.2.2 Cropland converted to Settlements

Carbon 5 LULUCF 5.E.2.3 Grassland converted to Settlements

Carbon 5 LULUCF 5.E.1 5.E.1 Settlements remaining Settlements

CH4 1 Energy 1.AA.2.D 1.AA.2.D Pulp, Paper and Print

CH4 1 Energy 1.C2 Multilateral Operations

CO2 1 Energy 1.AA.2.D 1.AA.2.D Pulp, Paper and Print

CO2 1 Energy 1.C2 Multilateral Operations

N2O 1 Energy 1.AA.2.D 1.AA.2.D Pulp, Paper and Print

N2O 1 Energy 1.C2 Multilateral Operations

N2O 3 Solvent and Other Product Use 3.D.4 Other Use of N2O Sources and sinks not estimated (NE) (1)

up to now there is a lack of data concerning urban tree formations. Therefore it is not possible to give estimates on the C stock changes in living biomass

up to now there is a lack of data concerning urban tree formations. Therefore it is not possible to give estimates on the C stock changes in living biomass

up to now there is a lack of data concerning urban tree formations. Therefore it is not

possible to give estimates on the C stock changes in dead organic matter

up to now there are no sufficient data for estimating C stock changes in dead organic

matter.

up to now there are no sufficient data for estimating C stock changes in dead organic

matter.

up to now there is a lack of data concerning urban tree formations. Therefore it is not

possible to give estimates on the C stock changes in soils

emissions have not been estimated because fuel data are not available

information and statistical data are not available

emissions have not been estimated because fuel data are not available

information and statistical data are not available

emissions have not been estimated because fuel data are not available

information and statistical data are not available

no information is available on other use of N2O
Table 1.7 Source and sinks not estimated in the 200 7 inventory



### Details are reported in Table 1.7 and Table 1.8. Sectoral and background tables of CRF sheets are complete as far as the details of basic information are available. For instance , multilateral operations emissions are not estimated because no activity data are available; pulp, paper and print emissions

from the combustion of biomass are not estimated because no data on this use is available. There is

no information on other use of N 2 

### O for solvent and other product use except for the emissions reported. Allocation of emissions is not consistent with the IPCC Guidelines only where there is no data available to split the information. For instance, for fugitive emissions, CO 2 

### and CH 4 

### emissions from oil and natural gas exploration and venting are included in those from oil production because no

detailed information is available. CH 4 

### emissions from other leakage emissions are included in

distribution emission estimates. N 2 

### O emissions fro m oil and natural gas exploration and refining and storage activities are reported under category 1.B.2.C oil flaring. Further investigation will be carried out closely with industry about these figures. For industrial processes, emissions from soda

ash us e are included in glass production emissions because the use of soda is part of that specific production process.

### 38 GHG Source/sink category Allocation as per IPCC Guidelines Allocation used by the Party Explanation

CH4 1.B.2.A.1 Exploration 1.B.2.A.1 1.B.2.A.2 Emissions are included in 1.B.2.A.2 Production

CH4 1.B.2.B.1 Exploration 1.B.2.B.1 1.B.2.B.2 Emissions are included in 1.B.2.B.2 Production

CH4 1.B.2.B.5.1 at industrial plants and
power stations 1.B.2.B.5.1 1.A.1 /1.A.2 Emissions are reported under the respective sectors
where they occurr

CH4 1.B.2.B.5.2 in residential and

commercial sectors 1.B.2.B.5.2 1.A.4 Emissions are reported under the respective sectors
where they occurr

CH4 1.B.2.C.1.1 Oil 1.B.2.C.1.1 1.B.2.A.2 Emissions are included in 1.B.2.A.2 Oil production

CH4 1.B.2.C.1.2 Gas 1.B.2.C.1.2 1.B.2.B.2 Emissions are included in 1.B.2.B.2 Gas production

CH4 1.B.2.C.2.2 Gas 1.B.2.C.2.2 1.B.2.B.2 Emissions are included in 1.B.2.B.2 Gas production

CH4 2.C.1.4 Coke 2.C.1.4 1.B.1.b CH4 emissions from coke production are fugitive emissions due to the door leakage during the solid
transformation and are reported under the 1.B.1.b
category, fugitive emissions from solid fuel.

CH4 6.B.1 Industrial Wastewater 6.B.1 Industrial Wastewater/Sludge 6.B.1 Industrial

Wastewater/Wastewater Emissions are reported under 6.B.1 Industrial

Wastewater/Wastewater

CH4 1.AA.3.B Road Transportation 1.AA.3B biomass 1.AA.3B liquid fuel emissions are included in liquid fuel - gasoil/diesel

category

CO2 1.B.2.A.1 Exploration 1.B.2.A.1 1.B.2.A.2 Emissions are included in 1.B.2.A.2 Production

CO2 1.B.2.B.1 Exploration 1.B.2.B.1 1.B.2.B.2 Emissions are included in 1.B.2.B.2 Production

CO2 1.B.2.C.1.1 Oil 1.B.2.C.1.1 1.B.2.A.2 Emissions are included in 1.B.2.A.2 Oil Production

CO2 1.B.2.C.1.2 Gas 1.B.2.C.1.2 1.B.2.B.2 Emissions are included in 1.B.2.B.2 Gas production

CO2 1.B.2.C.2.2 Gas 1.B.2.C.2.2 1.B.2.B.2 Emissions are included in 1.B.2.B.2 Gas production

CO2 2.A.4.2 Soda Ash Use 2.A.4.2 2.A.7 Emissions from soda ash use are included in other processes (glass, paper,etc).

CO2 5.A.1 Forest Land remaining Forest

Land 5.A.1. - 5(V) - Biomass Burning - Wildfires 5.A.1 Carbon stock change CO2 emissions due to wildfires in forest land
remaining forest land are included in table 5.A.1,
Carbon stock change in living biomass, Losses

N2O 1.B.2.A.1 Exploration 1.B.2.A.1 1.B.2.c.2 Emissions are included in 1.B.2.c.2 oil flaring

N2O 1.B.2.A.4 Refining / Storage 1.B.2.A.4 1.B.2.C.2 Emission are included in 1.B.2.C.2 flaring oil

N2O 6.B.1 Industrial Wastewater 6.B.1 Industrial Wastewater/Sludge 6.B.1 Industrial

Wastewater/Wastewater Emissions are reported under 6.B.1 Industrial

Wastewater/Wastewater

N2O 6.B.2.1 Domestic and Commercial
(w/o human sewage) 6.B.2.1 Domestic and commercial/Wastewater 6.B.2.2 Human sewage Emissions are reported under 6.B.2.2 Human sewage

N2O 6.B.2.1 Domestic and Commercial
(w/o human sewage) 6.B.2.1 Domestic and commercial/Sludge 6.B.2.2 Human sewage Emissions are reported under 6.B.2.2 Human sewage

N2O 1.AA.3.B Road Transportation 1.AA.3B biomass 1.AA.3B liquid fuel Emissions are included in liquid fuel - gasoil/diesel

category

SF6 2.F.7 Semiconductor Manufacture 2.F.7 Semiconductor Manufacture/SF6/Amount of
fluid in operating systems 2.F.7 Semiconductor

Manufacture/SF6/Amount of

fluid in new mnufactured
products Data are included in new manufactured products

SF6 2.F.7 Semiconductor Manufacture 2.F.7 Semiconductor Manufacture/SF6/Amount of
fluid remained in products at decommissioning 2.F.7 Semiconductor

Manufacture/SF6/Amount of

fluid in new mnufactured
products Data are included in new manufactured products

SF6 2.F.7 Semiconductor Manufacture 2.F.7 Semiconductor Manufacture/SF6/Actual

emissions from stocks 2.F.7 Semiconductor

Manufacture/SF6/Actual
emissions from manufacturing Emissions are included in emissions from
manufacturing

SF6 2.F.7 Semiconductor Manufacture 2.F.7 Semiconductor Manufacture/SF6/Actual
emissions from disposal 2.F.7 Semiconductor

Manufacture/SF6/Actual
emissions from manufacturing Emissions are included in emissions from
manufacturing Sources and sinks reported elsewhere (IE) (3)

Table 1.8 Source and sinks reported elsewhere in the 200 7 inventory

### 39



## Chapter 2: TRENDS IN GREENHOUSE GAS EMISSIONS

2.1 Description and in terpretation of emission trends for aggregate greenhouse gas emissions

Summary data of the Italian greenhouse gas emissions for the years 1990

- 2007 are reported in

Tables A 8.1

- A 8 .5 of Annex 8. The emission figures presented are those sent to the UNFCCC Secretariat and to the European Commission in the framework of the Greenhouse Gas Monitoring Mechanism. Total greenhouse gas emissions, in CO 2 

### equivalent, excluding emissions and removals from LULUCF, have increased by 7.1% between 1990 and 2007, varying from 516 to 553 CO 2 

### equivalent million tons (Mt), whereas the national Kyoto target is a reduction of 6.5%, as compared the base year levels, by the period 2008

- 2012. The most important greenhouse gas, CO 2 

### , which accounts for 86.0% of total emissions in C O 2 

### equivalent, shows an increase by 9.3% between 1990 and 2007. In the energy sector, in particular,

emissions in 2007 are 10.2% greater than in 1990.

CH 4 

### and N

2 

### O emissions are equal, respectively, to 6.9% and 5.8% of the total CO 2 

### equivalent greenhouse ga s emissions. CH 4 

### emissions have decreased by 8.4% from 1990 to 2007, while N 2 

### O has decreased by 14.9%. Other greenhouse gases, HFCs account for 1.2% of total emissions, PFCs and SF 6 

### are equal to 0.1%
of total emissions; HFC emissions show a strong increas e, while PFC emissions show a decrease

and SF 6 

### emissions show a lighter increase. Although at present, variations in these gases are not relevant to reaching the emission reduction objectives, the meaningful increasing trend of HFCs

will make them even mor e important in next years. Figure 2.1 illustrates the national trend of greenhouse gases for 1990

- 2007, expressed in CO 2 

### equivalent terms and by substance; total emissions do not include emissions and removals from land use, land use change and forestry.

0 100 200 300 400 500 600 700

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007CO2eq. (Mt) excluding LULUCF 

### CO2 CH4 N2O HFCs, PFCs, SF6

Figure 2.1 National greenhouse gas emissions from 1990 to 2007 (without LULUCF) (Mt CO 2 eq.)



### The share of the different sectors in terms of total emissions remains nearly unvaried over the period 1990

- 2007 . Specifically for the year 2007 , the greatest part of the total greenhouse gas emissions is to be attributed to the energy sector, with a percentage of 83.0%, followed by agriculture and industrial processes, accounting respectively for 6.7% and 6.6% of total emissions, waste contributing with 3.3% an d use of solvents with 0.4%.

### 40

Considering total greenhouse gas emissions with emissions and removals from LULUCF, the energy sector accounts, in 2007 , for 73.5% of total emissions and removals, as absolute weight, followed by the LULUCF sector which contrib utes with 11.4%. Figure 2.2 shows total greenhouse gas emissions and removals subdivided by sector.

-140 -40 60 160 260 360 460 560

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007CO2eq. (Mt) 

### Energy Industrial Processes

Agriculture Waste

Use of solvents LULUCF

Figure 2.2 Greenhouse gas emissions and removals from 1990 to 2007 by sector (Mt CO 2 eq.)



### 2.2 Description and interpretation of emission trends by gas

2 .2.1 Carbon dioxide emissions

CO 2 

### emissions, excluding CO 2 

### emissions and removals from LULUCF, have increased by approximately 9.3% from 1990 to 2007 , ranging from 435 to 475 million tons. The most relevant emissions derive from the energy industries (3 3.2%) and transportation (26.8%).

Non

- industrial combustion accounts for 17.0% and manufacturing and construction industries for 16.6%, while the remaining emissions derive from industrial processes (5.7%) and other sectors (0.8%). The performance of CO 2 

### emissions by sector is shown in Figure 2.3.

0 100 200 300 400 500

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007CO2(Mt) Energy Industries Manufacturing Industries and Construction

Transport Non industrial combustion

Industrial processes Other

Figure 2.3 National CO 2 emissions by sector from 1990 to 2007 (Mt)

### 41

The main sectors responsible for the increase of CO 2 

### emissions are transport and energy industries; in particular, emissions from transport ha ve increased by 25.6% from 1990 to 2007 while those from energy industries increased by 17.7%. Non industrial combustion emissions have raised by 3.8% and those from industrial processes decreased by 1.0%; emissions from manufacturing

industries and constr uction show a decrease of about 11.3%, emissions in the ‘Other’ sector, mostly fugitive emissions from oil and natural gas and emissions from solvent and other product use, reduced by 30.5%.

Figure 2.4 illustrates the performance of the following economic and energy indicators:

• Gross Domestic Product (GDP) at market prices as of 2000 (base year 1990=100);

• Total Energy Consumption;

• CO 2 

### emissions, excluding emissions and removals from land

- use change and forests;

• CO 2 

### intensity , which represents CO 2 

### emissions per unit of total energy consumption.

The figures of CO 2 

### emissions per total energy unit show that CO 2 

### emissions in the 1990s essentially mirrored energy consumption. A decoupling between the curves is observed only in recent years, mainly as a result of

the substitution of fuels with high carbon contents by methane gas in the production of electric energy and in industry; nevertheless, this trend slowed in 2002, due to the increase of coal consumption in power plants.

90 95 100 105 110 115 120 125 130

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 20071990=100 GDP

Total energy consumption

CO2 emissions

CO2 Intensity

Figure 2.4 Energy

- related and eco

nomic indicators and CO 2 emissions



### 2.2.2 Methane emissions

Methane emissions (excluding LULUCF) in 2007 represent 6.9% of total greenhouse gases, equal

to 38.2 Mt in CO 2 

### equivalent, and show a decrease of approximately 3.5 Mt as compared to 1990

levels.

CH 4 

### emissions, in 2007, are mainly originated from the waste sector which accounts for 42.0% of total methane emissions, as well as from agriculture (40.9%) and energy (17.0%). Activities typically leading to emissions in the waste

- management sector are t he operation of dumping sites and the treatment of industrial waste

- water. The waste sector shows an increase in emission levels, 3.9% compared to 1990, the highest increases concern waste

- water handling (22.5%) and waste incineration (68.5%) subcategories , while the largest emission share origins from solid waste disposal on land subcategory (83.1%). Emissions in the agricultural sector regard mainly the enteric fermentation and manure management categories. The agriculture sector shows a decrease of emiss ions equal to 9 .3% as compared to

1990.

### 42

In terms of CH

4 

### emissions in the energy sector, the reduction (

- 27.7%) is the result of two contrasting factors; on the one hand there has been a considerable reduction in emissions caused by leakage from the extrac tion and distribution of fossil fuels, due to the gradual replacement of

natural

- gas distribution networks; at the same time, combustion emissions in the road transport sector have increased on account of the overall rise in consumption and, in the civil s ector, as the result of increased use of methane in heating systems. Figure 2.5 shows the emission figures by sector.

0 500 1000 1500 2000 2500

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007C H4(Gg) 

### Energy Agriculture Waste Other

Figure 2.5 National CH 4 emissions by sector from 1990 to 2007 (Gg)



### 2.2.3 Nitrous oxide emissions

In 2007 nitrous oxide emissions ( excluding LULUCF) represent 5.8% of total greenhouse gases,
with a a decrease of 14.9% between 1990 and 2007, from 37.4 to 31.8 Mt CO 2 

### equivalent. The major source of N 2 

### O emissions is the agricultural sector (67.8%), in particular the use of both

chemical and organic fertilisers in agriculture, as well as the management of waste from the raising of animals. These emissions show a decrease of 7.6% during the period 1990

- 2007. Emissions in the energy

- use sector (17.1% of the total) show an increase by 18.0% f rom 1990 to 2007; this growth can be traced primarily to the road transport sector and it is related to the introduction of catalytic converters. However, a high degree of uncertainty still exists with regard to

the N 2 

### O emission factors of catalysed automo biles. Emissions from production of nitric acid have decreased from 1990 to 2007 of 46.8%; emissions from production of adipic acid show an increase from 1990 to 2005 of 32. 6 % and a decrease from

2005 to 2007 of 87.1% because of the introduction of an abat ement technology, showing a global

reduction of 82.9 % (joint emissions in 2005 accounted for 20.5% and in 2007 for 5.9% of total emissions). Other emissions in the waste sector primarily regard the processing of industrial and domestic

waste

- water. Figure 2.6 shows national emission figures by sector.

### 43 0 20 40 60 80 100 120 140

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007N2O (Gg) Energy Agriculture

Industrial processes Waste

Solvent use

Figure 2.6 National N 2 O emissions by sector from 1990 to 2007 (Gg)



### 2.2.4 Fluorinated gas emissions

Italy has set 1990 as the base year for reduction in the emissions of the fluorinated gases covered by the Kyoto Protocol, HFCs, PFCs and SF 6 

### . Taken altogether, the emissions of fluorinated gases represent 1.3% of total greenhouse gases in CO 2 

### equivalent in 2007, and they show an increase of

197.6% between 1990 and 2007. This increase is the result of diffe rent features for the different

gases. HFCs, for instance, have increased considerably from 1990 to 2007, from 0.4 to 6.7 Mt in CO 2 

### equivalent. The main sources of emissions are the consumption of HFC

- 134a, HFC

- 125, HFC

- 32

and HFC

- 143a in refrigeration and air

- conditioning devices, together with the use of HFC

- 134a in pharmaceutical aerosols. Increases during this period are due both to the use of these substances as substitutes for gases that destroy the ozone layer and to the greater use of air conditione rs in

automobiles.

Emissions of PFCs show a decrease of 84.1% from 1990 to 2007. The level of these emissions in

2007 is 0.3 Mt in CO 2 

### equivalent, and it it is due to the use of the gases in the production of aluminium (69.5%) and in the production of semi conductors (30.5%).. Although the production of PFCs is equal to zero in Italy from the year 1999 onwards, the upward trend shown by the series is due to their consumption and to their use in metal production.

Emissions of SF 6 

### are equal to 0.4 Mt in CO 2 

### eq uivalent in 2007, with an increase of 28.4% as compared to 1990 levels. 12.6% of SF 6 

### emissions derive from the use of gas in aluminium and magnesium foundries, 78.9% from the gas contained in electrical equipments, 8.5% from the gas

use in the semiconducto

rs manufacture. From 2005 to 2006, emissions of SF 6 

### have fallen of 12.8%, showing during last year an increase of 5.3%. The National Inventory of fluorinated gases has largely improved in terms of the sources and the gases identified and a strict cooperati on with the relevant industry has been established. Higher methods are applied to estimate these emissions; nevertheless, uncertainty still regards some activity data which are considered of strategic economic importance and therefore kept confidential.

### 44 0 1000 2000 3000 4000 5000 6000 7000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007CO2eq. (Gg) SF6

PFCs

HFCs

Figure 2.7 National emissions of fluorinated gases by sector from 1990 to 2007 (Gg CO 2 eq.)



### 2.3 Description and interpretation of emission trends by source

2.3.1 Energy

Emissions from the energy sector account for 83.0% of total national greenhouse ga s emissions, excluding LULUCF.

Emissions in CO 2 

### equivalent from the energy sector are reported in Table 2.1 and Figure 2.8.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Gg CO 2 eq

Total emissions 418

, 945 431

, 961 450

, 722 455

, 290 457

, 264 471

, 623 473

, 756 474

, 506 469

, 586 458

, 673

Fuel Combustion
(Sectoral Approach) 408

, 183 421

, 904 441

, 713 446

, 780 448

, 960 462

, 891 465

, 889 466

, 669 462

, 203 451

, 425
Energy Industries 134

, 791 138

, 664 147

, 554 150

, 953 157

, 854 158

, 940 157

, 856 160

, 025 159

, 886 158

, 548

Manufacturi ng
Industries and

Construction 90

, 609 89

, 503 89

, 699 87

, 003 83

, 138 88

, 068 87

, 923 83

, 419 83

, 802 80

, 547

Transport 103

, 276 114

, 244 122

, 949 124

, 942 126

, 821 127

, 663 129

, 557 127

, 804 129

, 178 129

, 189

Other Sectors 78

, 387 77

, 982 80

, 660 83

, 517 80

, 824 87

, 520 89

, 374 94

, 130 88

, 279 82

, 173

Other 1

, 120 1

, 511 851 365 322 701 1

, 180 1

, 291 1

, 058 969
Fugitive Emissions

from Fuels 10

, 762 10

, 057 9

, 010 8

, 510 8

, 304 8

, 732 7

, 867 7

, 836 7

, 383 7

, 248

Solid Fuels 122 65 73 81 78 95 64 69 54 84

Oil and Natural

Gas 10

, 640 9

, 993 8

, 936 8

, 429 8

, 225 8

, 637 7

, 803 7

, 768 7

, 329 7

, 164

Table 2.1 Total emissions in CO 2 equivalent from the energy sector by source (1990

- 2007) (Gg CO 2 eq.)



### An upward trend is noted from 1990 to 2005, total greenhouse gas emissions, in CO 2 

### equivalent,

show an increas

e by 13.3%, while between 2005 and 2007 emissions have decreased by 3.3%, showing from 1990 to 2007 an increase of about 9.5%. Substances with the highest impact are CO 2 

### , whose levels have increased by 10.2% from 1990 to

2007 and account for 97.4% of the t otal, and N

2 

### O which shows an increase of 18.0% but its share

### 45

out of the total is only 1.2%; CH 4 

### , on the other hand, shows a decrease of 27.7% from 1990 to 2007 but this is not relevant on total emissions, accounting only for 1.4%.

It should be noted that from 1990 to 2007 the most significant increase, in terms of total CO 2 

### equivalent, is observed in the transport, in the energy industries and in the other sectors, about 25.1%, 17.6% and 4.8%, respectively; in 2007 these sectors, altogether, account for 80 .6% of total

emissions. Details on these figures are described in the specific chapter.

0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000 500,000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Gg 1 A 1 1 A 2 1 A 3 1 A 4 1 A 5 1 B

Share 1990

32.2

21.6 2.6

18.7

24.7 0.3 1 A 1

1 A 2

1 A 3

1 A 4

1 A 5

1 B Share 2007

34.6

17.6 1.6 0.2

28.2 17.9 1 A 1

1 A 2

1 A 3

1 A 4

1 A 5

1 B

Figure 2.8 Trend of total emissions in CO 2 equivalent from the energy sector (1990

- 2007) (Mt CO 2 eq.)



### 2.3.2 Industrial processes

Emissions from industrial processes account for 6.6% of total national greenhouse gas emissions, excluding LULUCF. Emission trends from industrial processes are reported in Table 2.2 and Figure 2.9.
Total emission levels, in CO 2 

### equivalent, show a decreas e of 0.5%, from the base year to 2007. Taking into account emissions by substance, CO 2 

### level decreased by 1.0%, while N 2 

### O level decreased by 71.7%; these two substances account altogether for about 79.4% of the total emissions from industrial processes. Th e increase in emissions is mostly due to an increase in the mineral products category (12.2%), for the increase in production figures especially for cement and lime. The decrease of GHG emissions in the chemical industry (

- 64.1%) is due to adipic acid prod uction. Emissions from metal production decreased by 49.5% mostly for the different materials used in the pig iron and steel production processes.

### 46

A considerable increase is observed in F

- gas emissions (197.6%), whose share on total emissions is

20.4%.

De tails for industrial processes emissions can be found in the specific chapter.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Gg CO2 eq

Total 36

, 467 34

, 530 34

, 903 36

, 946 37

, 040 38

, 232 40

, 522 40

, 367 35

, 916 36

, 296

CO2 27

, 190 25

, 415 24

, 097 24

, 858 24

, 818 25

, 856 26

, 653 26

, 457 26

, 559 26

, 924

CH4 108 113 63 59 57 58 61 64 66 65

N2O 6

, 676 7

, 239 7

, 918 8

, 232 7

, 902 7

, 557 8

, 443 7

, 760 2

, 647 1

, 891

F

- gases 2

, 492 1

, 764 2

, 825 3

, 796 4

, 263 4

, 761 5

, 365 6

, 085 6

, 644 7

, 416

HFCs 351 671 1

, 986 2

, 550 3

, 100 3

, 796 4

, 515 5

, 267 5

, 956 6

, 701

PFCs 1

, 808 491 346 451 424 498 348 353 282 288

SF 6 333 601 493 795 740 468 502 465 406 428

Table 2.2 Total emissions in CO 2 equivalent from the industrial processes sector by gas (1990

- 2007)

0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Gg 2 A 2 B 2 C 2 E 2 F

Share 1990

57.9 24.5 0.6 15.4 1.7 2 A

2 B

2 C

2 E

2 F Share 2007

65.2

8.8 0.1

6.2 19.7 2 A

2 B

2 C

2 E

2 F

Figure 2.9 Trend of total emissions in CO 2 equivalent from industrial processes (1990

- 2007) (Mt CO 2 eq.)



### 2.3.3 Solvent and other product use

Emissions from the solvent and other product use sector refer to CO 2 

### and N 2 

### O, and to other gases that are not greenhouse.

### 47

A considerable amount of emissions from this sector is, in fact, mostly to be attributed to NMVOC.

The share of CO 2 

### emissions, in this sector, is 63.8% out of the total; a decrease by 14.9% is noted
from this sector from 1990 to 2007, which is to be attributed to differe nt sources. As regards CO 2 

### , emission levels from paint application sector, which accounts for 51.4% of total CO 2 

### emissions from this sector, decreased by 17.2%; emissions from other use of solvents in related activities, such

as domestic solvent use other than painting, application of glues and adhesives, printing industries, fat edible and non edible oil extraction, vehicle dewaxing, glass wool enduction, which account for 43.6% of the total, show an increase of 2.8%. Finally, CO 2 

### emissions from metal degr easing and dry cleaning activities, decreased by 61.3% but they account for only 5 .0 % of the total. In 2007, solvent use is responsible for 0.4% of the total CO 2 

### equivalent emissions (excluding LULUCF) and for 42.7% of the total NMVOC emissions, and repre sents the main source of anthropogenic NMVOC national emissions.

N 2 

### O emissions from this sector, in 2007, represent 2.4% of the total N 2 

### O national emissions. Emissions from paint application and other use of solvents for NMVOC and CO 2 

### are about equal to

8 0.5% and 95 .0 %, respectively, of the total sector. From 1990 to 1995, a quite stable level of N 2 

### O emissions is observed, afterwards from 1995 to 1998 emissions increased by 37.5%. From 1999, there appears to be a reduction in N 2 

### O emissions,

due to a decre ase in the anaesthetic use of N 2 

### O, that has been replaced by halogen gas. Further details about this sector can be found in the specific chapter.

0 500 1,000 1,500 2,000 2,500 3,000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Gg 3 A 3 B 3 D 5 3 D 1 3 D 3

Share 1990

35.3

7.4 24.1 31.0 2.3 3 A

3 B

3 D 5

3 D 1

3 D 3 Share 2007

32.8

3.2

27.8 6.1

30.1 3 A

3 B

3 D 5

3 D 1

3 D 3

Figure 2.10 Trend of total emissions in CO 2 equivalent from the solvent and other product use sect or (1990

- 2007)
(Mt CO

2 eq.)

### 48

2.3.4 Agriculture

Emissions from the agriculture sector account for 6.7% of total national greenhouse gas emissions, excluding LULUCF. Emissions from the agriculture sector are reported in Table 2.3 and Figure 2.11.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Gg CO2 eq

Total emissions 40

, 576 40

, 349 39

, 940 38

, 954 38

, 250 38

, 102 37

, 917 37

, 242 36

, 627 37

, 210

Enteric Fermentation 12

, 179 12

, 267 12

, 165 11

, 340 11

, 030 11

, 056 10

, 836 10

, 844 10

, 629 11

, 027

Manure Management 7

, 38 3 7

, 068 7

, 140 7

, 342 7

, 110 7

, 067 6

, 886 6

, 877 6

, 649 6

, 853

Rice Cultivation 1

, 562 1

, 657 1

, 382 1

, 382 1

, 420 1

, 463 1

, 534 1

, 472 1

, 477 1

, 523

Agricultural Soils 19

, 435 19

, 340 19

, 237 18

, 875 18

, 673 18

, 500 18

, 643 18

, 032 17

, 856 17

, 791
Prescribed Burning of

Savannas 0 0 0 0 0 0 0 0 0 0
Field Burning of Agricultural Residues 17 17 16 15 17 15 18 17 17 17

Table 2.3 Total emissions in CO 2 equivalent from the agricultural sector by source (1990

- 2007) (Gg CO 2 eq.)



### Emissions refer to CH 4 

### and N 2 

### O levels, which account for 42.0% and 58.0% of the total emission of the sector, respectively. The decrease observed in the total emissions (

- 8.3%) is mostly due to the

decrease of CH

4 

### emissions from enteric fermentation (

- 9.5%) which account for 29.6% of the total

emissions. Detail ed comments can be found in the specific chapter.

0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Gg 4 D 4 A 4 B 4 C 4 F

Share 1990

47.9

30.0 18.2 3.8 0.04 4 D

4 A

4 B

4 C

4 F Share 2007

47.8

29.6 18.4 4.1 0.05 4 D

4 A

4 B

4 C

4 F

Figure 2.11 Trend of total emissions in CO 2 equivalent from agriculture (1990

- 2007) (Mt CO 2 eq.)

### 49

2.3.5 LULUCF

Emissions from the LULUCF sector are reported in Table 2.4 and Figure 2.12.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Gg CO 2 eq

Total

emissions

- removals

- 67

, 493

- 85

, 590

- 79

, 230

- 92

, 611

- 95

, 649

- 126

, 798

- 91

, 840

- 95

, 336

- 89

, 804

- 70

, 910

Forest Land

- 53

, 392

- 77

, 525

- 70

, 356

- 78

, 948

- 85

, 389

- 74

, 718

- 80

, 895

- 83

, 486

- 84

, 161

- 55

, 37 2
Cropland

- 16

, 876

- 10

, 210

- 11

, 697

- 10

, 956

- 11

, 544

- 11

, 085

- 8

, 881

- 10

, 155

- 7

, 788

- 10

, 960

Settlements 3

, 160 2

, 145 3

, 210 3

, 204 3

, 202 3

, 165 3

, 160 3

, 153 2

, 145 3

, 181

Grassland

- 385 0

- 387

- 5911

- 1

, 918

- 44

, 161

- 5

, 224

- 4

, 849 0

- 7

, 760

Wetlands 0 0 0 0 0 0 0 0 0 0

Other Land 0 0 0 0 0 0 0 0 0 0

Other 0 0 0 0 0 0 0 0 0 0

Table 2.4 Total emissions in CO 2 equivalent from the LULUCF sector by source/sink (1990

- 2007) (Gg CO 2 eq.)



### Total removals, in CO 2 

### equivalent, show an increase of 5.1%, from the base year to 2007.

CO 2 

### accounts for more than 99% to total emissions and removals of the sector. Further details for LULUCF emissions and removals can be found in the specific chapter.

-136,000 -116,000 -96,000 -76,000 -56,000 -36,000 -16,000 4,000 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Gg 5 A 5B 5C 5E

Share 1990

72.3 22.9 0.5 4.3 5A

5B

5C

5E Share 2007

71.7

14.2 10.0 4.1 5A

5B

5C

5E

Figure 2.12 Trend of total emissions and removals in CO 2 equivalent fr om LULUCF (1990

- 2007) (Mt CO 2 eq.)

### 50

2.3.6 Waste

Emissions from the waste sector account for 3.3% of total national greenhouse gas emissions, excluding LULUCF. Emissions from the waste sector are shown in Table 2.5 and Figure 2.13.

Total emissions in CO 2 

### e quivalent increased by 2.9% from 1990 to 2007. The increase is due to the increase in emissions from solid waste disposal (0.3%) due to the increase of waste production,
which accounts for 72.3% of the total, as well as from waste

- water handling (15.6%), w hich

accounts for 24.1% of the total

. Considering emissions by gas, the most important greenhouse gas is CH 4 

### which accounts for 87.0%

of the total and shows an increase of 3.9% from 1990 to 2007. N 2 

### O levels have increased by 9.5%

while CO 2 

### decreased by 49 .7%; these gases account for 11.6% and 1.5%, respectively. Further details can be found in the specific chapter.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Gg CO2 eq

Total emissions
CO2 equivalent 17

, 936 20

, 666 21

, 659 21

, 545 20

, 973 20

, 283 19

, 475 19

, 432 18

, 707 18

, 459

Solid Waste Disposal on Land 13

, 298 15

, 754 16

, 824 16

, 662 16

, 067 15

, 402 14

, 490 14

, 437 13

, 638 13

, 341

Waste

- water Handling 3

, 852 4

, 027 4

, 269 4

, 264 4

, 275 4

, 273 4

, 295 4

, 320 4

, 390 4

, 454

Waste Incineration 785 884 564 617 627 604 686 671 675 660

Other 0 0 2 3 3 4 4 4 4 5

Table 2.5 Total emissions in CO 2 equivalent from the waste sector by source (1990

- 2007) (Gg CO 2 eq.)

0 5,000 10,000 15,000 20,000 25,000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Gg 6A 6B 6C 6D

Share 1990

74.1 4.4 0.001

21.5 6A

6B

6C

6D Share 2007

72.3

24.1 0.025 3.6 6A

6B

6C

6D

Figure 2.13 Trend of total emissions in CO 2 equivalent from waste (1990

- 2007) (Mt CO 2 eq.)

### 51

2.4 Descript ion and interpretation of emission trends for indirect greenhouse gases and SO 2



### Emission trends of NO X 

### , CO, NMVOC and SO 2 

### from 1990 to 2007 are presented in Table 2.6 and Figure 2.14.

Indirect greenhouse
gases and SO

2 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

kt

NO X 2

, 007 1

, 868 1

, 434 1

, 422 1

, 367 1

, 360 1

, 319 1

, 229 1

, 188 1

, 147

CO 6

, 927 6

, 876 4

, 857 4

, 646 4

, 218 4

, 064 3

, 881 3

, 506 3

, 342 3

, 334

NMVOC 1

, 939 2

, 001 1

, 565 1

, 500 1

, 431 1

, 373 1

, 319 1

, 248 1

, 221 1

, 194

SO 2 1

, 795 1

, 320 749 697 616 518 480 401 379 339
Table 2.6 Total emissions for indirect greenhouse gases and SO 2 (1990

- 2007) (kt)



### All gases show a significant reduction in 2007 as compared to 1990 levels. The highest reduction is

observed for SO 2 

### (

- 81.1%), CO levels have reduced by 51.9%, whil e NO X 

### and NMVOC show a decrease by 42.8% and 38.4%, respectively. A detailed description of the trend by gas and sector as well as the main reduction plans can be found in the Italian National Programme for the progressive

reduction of the annual national emissions of SO 2 

### , NO X 

### , NMVOC and NH 3 

### , as requested by the

Directive 2001/81/EC. The most relevant reductions occurred as a consequence of the Directive 75/716/EC, and of the successive ones related to the transport sector, and of other European Directives which established maximum levels for sulphur content in liquid fuels and introduced emission standards for combustion installations. As a consequence, in the combustion processes, oil with high sulphur

content and coal have been substituted with oil with l ow sulphur content and natural gas.

0 1000 2000 3000 4000 5000 6000 7000 8000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007kt NOX CO NMVOC SO2

Figure 2.14 Trend of total emissions for indirect greenhouse gases and SO2 (1990

- 2007) (kt)

### 52



## Chapter 3: ENERGY [CRF sector 1]

3.1 Introduction

The aim of this section is to describe in detail the methodology use d to estimate emissions from fuel combustion for energy. These sources correspond to IPCC Tables 1A. The national emission inventory is prepared using the energy consumption information available

from national statistics and an estimate of the actual use of the fuels. The latter information is available at sectoral level in a great number of publications and it is needed to evaluate emissions of methane and nitrous oxide. Those emissions are related to the actual physical conditions of the combustion proce ss and to environmental conditions. The continuous monitoring of GHG emissions in Italy is negligible; hence, information is rarely available on actual emissions over a specific period from an individual emission source. Therefore, the majority of emissio ns is estimated from other information such as fuel consumption, distance travelled or some other statistical data related to emissions. Estimates for a particular source sector are calculated by applying an emission factor to an appropriate statistic. Th at is:

Total Emission = Emission Factor x Activity Statistic

Emission factors are typically derived from measurements on a number of representative sources and the resulting factor applied to the whole country.
For certain sectors, emissions data are a vailable for individual sites. Hence, the emission for a particular sector can be calculated as the sum of the emissions from these point sources. That is:

Emission = Σ Point Source Emissions

However, it is necessary to carry out an estimate of the fue l consumption associated with these point sources, so that the emissions from non

- point sources can be estimated from fuel consumption data without double counting. In general, the point source approach is only applied to emissions of indirect greenhouse gases for well defined point sources (e.g. power stations, cement kilns, refineries). Direct greenhouse gas emissions and most non

- industrial sources are estimated using

emission factors.

3.2 Key categories

Key category analysis , for the years 1990 and 2007, identified 12 categories at level or trend assessment with the Tier 1 and Tier 2 approach in the energy related emissions. In the case of the energy sector in Italy, a sector by sector analysis instead of a source by source analysis will better illu strate the accuracy and reliability of the emission data, given the interconnection between the underlying data of most key source categories. In the following box, the relevant key categories are listed making reference to the section of the text where th ey are quoted. With reference to the box, six of the key categories (n. 1, 2, 3, 5, 10 and 11) are linked to stationary combustion and to the same set of energy data: the energy sector CRF table 1.A.1, the industrial
sector, table 1.A.2 and the civil sect or tables 1.A.4a and 1.A.4b. Four out of six key categories refer

to CO 2 

### emissions. All these sectors refer to the national energy balance (MSE, several years [a]) for the basic energy data and the distribution among various subsectors, even if more accura te data for the electricity production sector can be found in Terna database (Terna, several years). Evolution of energy consumptions/emissions is linked to the activity data of each sector; see paragraph 3.4, 3.5

### 53

and 3.7 for the detailed analysis of those sectors. Electricity production is the most “dynamic”
sector and most of the emissions increase from 1990 to 2007, for CO 2 

### , N 2 

### O and CH

4 

### , is due to the increase of thermoelectric production, see Tables 3.2, 3.4 and 3.9 for more details.

Another consistent

group of key categories (n. 4, 6, 8 and 12) are referred to the transport sector, with basic total energy consumption reported in the national energy balance and then subdivided in the different subsectors with activity data taken from various statistical sources; see paragraph 3.6, transport, for an accurate analysis of these key sources. This sector also shows a remarkable increase in emissions, in particular CO 2 

### from air transport and road transport, as can be seen in the Table 3.18 and 3.19, respective ly. The trend of N 2 

### O and CH

4 

### emissions is linked to technological changes occurred in the period. Finally, the last group of two key categories (n.7, and 9) refers to oil and gas operations. For this sector basic overall production data are reported in the national balance but emissions are calculated with more accurate data published or delivered to ISPRA by the relevant operators, see paragraph

3.11. Most of these categories are also key categories for the years 1990 and 2007 taking into account

LULUCF e missions and removals.

Key

- categories identification in the energy sector with the IPCC Tier1 and Tier2 approaches for 2007

KEY CATEGORIES TIER with

LULUCF Relevant paragraphs Notes



### 1 CO 2 stationary combustion liquid fuels L,T X 3.4, 3.5 and 3.7 Tabl e 3.9



### 2 CO 2 stationary combustion solid fuels L,T X 3.4, 3.5 and 3.7 Table 3.9



### 3 CO 2 stationary combustion gaseous fuels L,T X 3.4, 3.5 and 3.7 Table 3.9



### 4 CO 2 mobile combustion: Road Vehicles L,T X 3.6 and 3.6.3 Tables 3.18, 3.19



### 5 N 2 O stationary comb ustion L X 3.4, 3.5 and 3.7 Table 3.9



### 6 CO 2 mobile combustion: Waterborne Navigation L1,T2 X 3.6.4 Table 3.24



### 7 CH 4 fugitive emissions from Oil and Gas Operations L,T X 3.11 Table 3.28



### 8 N 2 O mobile combustion: Road Vehicles L2 3.6 and 3.6.3 Tables 3.18 , 3.19



### 9 CO 2 fugitive emissions from Oil and Gas Operations L2,T X 3.11 Table 3.28



### 1

0 CO 2 stationary combustion other fuels L1,T1 not key

in 1990 3.4, 3.5 and 3.7 Table 3.9



### 1

1 CH 4 stationary combustion L2 not key

in 1990 3.4, 3.5 and 3.7 Table 3.9



### 1

2 CH 4 mobile combustion: Road Vehicles L2 key only

in 1990 3.6 and 3.6.3 Tables 3.18, 3.19



### 3.3 Methodology for estimation of emissions from combustion

For the pollutants and sources discussed in this section, emissions result from the combustion of

fu el. The activity statistics used to calculate emissions are fuel consumptions provided by the Ministry of Economic Development in the national energy balance (MSE, several years [a]), by Terna (Terna, several years) for the power sector and some additional data sources to characterise the technologies used at sectoral level, quoted in the relevant sections.

Emissions are calculated using sector specific spreadsheets according to the equation:

E( p,s,f ) = A( s,f ) × e( p,s,f )

### 54

where
E( p,s,f ) = Emissi

on of pollutant p from source s from fuel f (kg) A( s,f ) = Consumption of fuel f by source s (TJ

- t)
e( p,s,f ) = Emission factor of pollutant p from source s from fuel f (kg/TJ

- kg/t)

The pollutants estimated in this way are:
carbon dioxide (CO 2 

### );

NO

x 

### as ni trogen dioxide;
nitrous oxide (N 2 

### O); methane (CH

4 

### ); non methane volatile organic compounds (NMVOC);
carbon monoxide (CO); sulphur dioxide (SO 2 

### ).

The sources covered by this methodology are: Electricity (power plants and Industrial producers);
Refineries ( Combustion); Chemical and petrochemical industries (Combustion);
Construction industries (roof tiles, bricks); Other industries (metal works factories, food, textiles, others); Road Transport; Coastal Shipping; Railways;
Aircraft;
Domestic;
Commercial;

Pu blic Service; Fishing and Agriculture.

The fuels covered are listed in Table 3.2, though not all fuels occur in all sources. Sector specific tables specify the emission factors used.

Emission factors are expressed in terms of kg pollutant/ TJ based on the net calorific value of the

fuel. The carbon factors used are based on national sources and should be appropriate for Italy. Most of the emission factors have been cross checked with the results of specific studies that evaluate the

carbon content of the imported/produced fossil fuels at national level. A comparison of the current national factors with the IPCC ones was carried out and the results suggest quite limited variations in liquid fuels and some differences in natural gas, explained by basic h ydrocarbon composition,

and in solid fuels. In case of differences between IPCC and national emission factors the latter have been usually preferred.

The emission factors should apply for all years provided there is no change in the carbon content of

fue l over time. There are exceptions to this rule:

• transportation fuels have shown a significant variation around the year 2000 due to the reformulation of gasoline and diesel to comply with the EU directive, see section 3.10
for details;

• the most important imported fuels, natural gas, fuel oil and coal show variations of carbon content from year to year, due to changes in the origin of imported fuel supply; a methodology has been set up to evaluate annually the carbon content of the average fuel

used in Ita ly, see section 3.10 for details.

### 55

The Ministry of Economic Development (Ministero dello Sviluppo Economico, MSE) publishes annually energy balances (MSE, several years [a]) of fuels used in Italy. These balances compare total supply based on production, exports, imports, stock changes and known losses with the total demand. The difference between total supply and demand is reported as 'statistical difference'. In
Annex 5, 2007 data are attached, while the full time series is available on website: http://dgerm.sviluppoeconomico.gov.it/dgerm/ben.asp

. Additionally to fossil fuel, the national energy balance (BEN) reports commercial wood and straw combustion estimates for energy use, biodiese l and biogas. The estimate of GHG emissions are based on these data and on other estimates (ENEA, several years) for non commercial wood use.

Carbon dioxide emissions from biomass combustion are not included in the national total as suggested in the IPCC G uidelines (IPCC, 1997) but emissions of other GHGs and other pollutants are included. CORINAIR methodology (EMEP/CORINAIR, 2007) includes emissions from the

combustion of wood in the industrial and domestic sectors as well as the combustion of biomass in

a griculture. The inventory reports also emissions from the combustion of lubricants based on data collected from waste oil recyclers and quoted in the BEN; from 2002 onwards, this estimate is included in the column “Refinery feedstocks”, row “Productions”, see Annex 5, Table A5.1

- National energy balance, year 2007, Primary fuels. From 2004 onwards, it has been necessary to use also those quantities to calculate emissions in the reference approach, so to minimize differences with sectoral approach. From 2004 , the energy balances prepared by MSE do include those quantities in the input while estimating final consumption; this procedure summarizes a complex stock change reporting by operators.

For most of the combustion source categories, emissions are estimat ed from fuel consumption data reported in the BEN and from an emission factor appropriate to the type of combustion. However, the industrial category covers a range of sources and types, so the inventory disaggregates this category into a number of sub

- cat egories, namely:

• Other Industry;

• Other Industry Off

- road: See paragraph 3.7;

• Iron & Steel (Combustion, Blast Furnaces, Sinter Plant);

• Petrochemical industries (Combustion);

• Other combustion with contact industries: glass and tiles;

• Other industries (Metal works factories, food, textiles, others);

• Ammonia Feedstock (natural gas only);

• Ammonia (Combustion) (natural gas only);

• Cement (Combustion);

• Lime Production (non

- decarbonising).

Thus, the estimate from fuel consumption emission factors refers to stationa ry combustion in boilers and heaters. The other categories are estimated by more complex methods discussed in the relevant sections. However, for these processes, where emissions arise from fuel combustion for energy production, these are reported under IP CC Table 1A. The fuel consumption of Other Industry is estimated so that the total fuel consumption of these sources is consistent with BEN.

According to the IPCC 1996 Revised Guidelines (IPCC, 1997), electricity generation by companies primarily for thei

r own use is auto

- generation, and the emissions produced should be reported under the industry concerned. However, most national energy statistics (including Italy) report emissions from electricity generation as a separate category. The Italian inventory makes an overall calculation and then attempts to report as far as possible according to the IPCC methodology:

### 56

• auto

- generators are reported in the relevant industrial sectors of section “1.A.2 Manufacturing Industries and Construction”, including sector “1 .A.2.f. Other”;

• iron and steel auto

- generation is included in section 1.A.1c. Those reports are based on Terna (Terna, several years) estimates of fuel used for steam generation connected with electricity production.

Emissions from waste incineration fac ilities with energy recovery are reported under category 1.A.4.a (Combustion activity, commercial/institutional sector), whereas emissions from other types of waste incineration facilities are reported under category 6.C (Waste incineration). In fact, ener gy recovered by these plants is mainly used for district heating of commercial buildings. In particular, for 2007, 95% of the total amount of waste incinerated is treated in plants with energy recovery system. To estimate CO 2 

### emissions, considering the tot al amount of waste incinerated in plants with energy recovery, the carbon content is calculated, as described in paragraph 8.4.2, in the waste chapter; the value is considered constant for the whole time series. Different emission factors for municipal, in

dustrial and oils, hospital waste, and sewage sludge are applied, as reported in the waste chapter, Tables 8.20

- 8.24. Waste amount is then converted in energy content applying an emission factor equal to 9.2 Gj/t of waste. In 2007, the resulting average em ission factor is equal to 112.9 kg CO 2 

### /Gj. Emissions from landfill gas recovered are used for heating and power in commercial facilities and reported under 1.A.4.a. Biogas recovered from the anaerobic digester of animal waste is used for utilities in the a griculture sector and relative emissions are reported under 1.A.4.c In consideration of the increasing of the share of waste used to produce electricity, we plan to revise the allocation of these emissions under category 1.A.1.a.

Recalculations

In 200 6 submission, there has been an overall revision of CO 2 

### from the iron and steel industry. CO 2 

### emissions due to the consumption of coke, coal or other reducing agents as fuel used in the iron and steel industry, including fuel consumption of derived gases, have been accounted for and reported in the energy sector. On the other hand, CO 2 

### emissions from iron and steel industry referring to the carbonates used in sinter plants and basic oxygen furnaces, as well as iron and steel scraps and graphite electrodes u sed in electric arc furnaces have been accounted for, and reported in the industrial processes sector under 2C1.

In 2009 submission, main recalculations in this sector regarded the transport sector, 1

. A .3 as planned during the previous submission . The who le time series of road transport emissions ha s been recalculated because of the updated version of the model/software (COPERT4) used to estimate

emissions. Aviation emissions have been also recalculated for the whole time series because of a specific secto ral study so as maritime emissions that have been updated from 1998. More detailed information on these recalculations is reported in the respective paragraphs in 3.6. For all the energy sectors, n atural gas CO 2 

### emission factors have been updated for 2006 because of additional information collected on the chemical composition of natural gas imported; coal CO 2 

### average emission factors have also been revised from 2005 based on updated amounts of fuel imported from different countries. Fuel oil CO 2 

### average emi ssion factors have been recalculated from 1999 taking in account the percentage of low

- sulphur fuel out of the total fuel oil consumed and its specific characteristics. Moreover, from 2000, a double counting related to refinery gas fuel consumption in refi neries

, 1.A.1.b , already accounted for in the chemical sector , 1.A.2.c, has been detected and corrected.

### 57

Small changes in activity data from 2004, for oil production and gas distribution, and update of emission factors, from 2005, for minor gas distributo r companies, lead to recalculations of fugitive emissions, reported in 1

. B .2.

Recalculations affected the whole time series 1990

- 2006 for all gases. The following table shows the percentage differences between the 2009 and 2008 submissions for the total e nergy sector and by gas. Recalculation resulted for the energy sector in a reduction of emissions in the base year and in 2006 of 0.12% and 0.86% respectively, mainly due to the application of the COPERT4 model for road transport estimates, which completel y revised N 2 

### O emission factors.

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Energy -0.12 -0.19 -0.19 -0.23 -0.28 -0.16 -0.17 -0.20 -0.28 -0.30 -0.60 -0.65 -0.76 -0.79 -0.86 -0.73 -0.86

CO2 0.00 -0.08 -0.10 -0.14 -0.20 -0.09 -0.08 -0.09 -0.10 -0.07 -0.34 -0.38 -0.41 -0.41 -0.42 -0.22 -0.31

CH4 1.41 1.45 1.41 1.54 0.90 0.46 0.00 -0.27 -0.22 -1.12 -1.17 -0.11 0.04 -0.13 -1.21 0.69 -1.95

N2O -11.63 -10.99 -10.52 -10.04 -8.14 -6.45 -6.65 -7.80 -12.55 -14.66 -16.38 -18.41 -22.53 -24.34 -26.15 -31.65 -31.71 %

Source: ISPRA elaborations

Table 3.1 Emission r ecalculations in the energy sector 1990

- 2006 (%)



### 3.4 Energy industries

3.4.1 Electricity production

The source of data on fuel consumption is the annual report “Statistica l data on electricity production and power plants in Italy” (“Dati statistici sugli impianti e la produzione di energia elettrica in Italia”), edited from 1999 by the Italian Independent System Operator (Terna), a public enterprise that runs the high volta ge transmission grid. For the period 1990

- 1998 the same data were published by ENEL (ENEL, several years), the former electricity monopolist. The time series is

available since 1963. In these publications, consumptions of all power plants are reported, eit her public or privately owned. The base data are collected at plant level, on monthly basis. They include electricity production and estimation of physical quantities of fuels and the related energy content; for the biggest installations, the energy conten t is based on laboratory tests. Up to 1999, the fuel consumption was reported at a very detailed level, 17 different fuels, allowing a quite precise estimation of the carbon content. From 2000 onward, the published data aggregate all fuels in five

groups t hat do not allow for a precise evaluation of the carbon content. In Table 3.2, time series

1990

- 2007 is reported. For the purpose of calculating GHG emissions, the detailed list of fuels used was delivered to ISPRA by Terna for the years from 2000 to 2007 . The detailed list is confidential and only the output of the simulation model used to calculate emissions for the years 2006 and 2007 at the aggregated level of Table 3.2 is reported (see Annex 2).

At national level other statistics on the fuel used f or electricity production do exist, the most remarkable being the National Energy Balance (BEN), published annually (MSE, several years). Moreover the UP (Unione Petrolifera, Oil companies association) and ENI, the former national oil company, regularly pu

blish data on this issue. In the past, up to the year 1998, also the association of the industrial electricity producers (UNAPACE) published production data with the associated fuel consumption.

### 58 1990 1995 1999 2000 2001 2002 2003 2004 2005 2006 2007

national coal 58

- 96 Solids Solids Solids Solids Solids Solids Solids Solids imported coal 10,724 8,216 8,378 9,633 11,445 13,088 14,252 17,031 16,253 16,587 16,886
lignite 1,501 380 62

Natural gas, m 3 9,731 11,277 19,766 22,334 21,930 22,362 25,534 28,768 30,544 31,381 33,957

BOF(steel converter) gas, m 509 633 536 Coal Coal Coal Coal Coal Coal Coal Coal

Blast furnace gas, m 6,804 6,428 8,611 gases gases gases gases gases gases gases gases Coke gas, m 3 693 540 660 8,690 9,785 10,034 10,479 10,640 12,104 13,131 11,353

Light distillate 5 6 12 oil oil oil oil oil oil oil oil

Diesel oil 303 184 560 products products products products products products products products
Heavy fuel oil 21,798 25,355 17,511 19,352 17,186 17,694 14,993 10,522 7,941 7,629 5,292

Petroleum coke 186 189 216

Orimulsion

- - 1,688
Gases from chemical processes 444 803 1,155 Others Others Others Others Others Others Others Others

Tar 2

- - m 3 =769 m 3 =857 m 3 =955 m 3 =978 m 3 =1,321 m 3 =1,423
Heat recovered from Pyrite 146 3

- kt=10,686 kt=12,588 kt=15,031 kt=15,460 kt=16,253 kt=17,490

Other fuels 344 697 1,819 5,153 9,175 Refinery gas 211 378 409

Source: Terna, several years Table 3.2 Time series of powe r sector production by fuel, kt or 10^6 m 3



### Both BEN and Terna publications could be used for the inventory preparation, as they are part of the national statistical system and published regularly. The preference, up to date, for Terna data

arises from th

e following reasons:

- BEN data are prepared on the basis of Terna reports to IEA, so both data sets come from the

same source;

- Before being published in the BEN, Terna data are revised to be adapted to the reporting methodology: balance is done on the energ y content of fuels and the physical quantities of fuels are converted to energy using standard conversion factors; so the total energy content of the fuels is the “right” information extracted from the Terna reports and the physical quantities are changed to avoid discrepancies; the resulting information cannot be cross checked with detailed plant data (collected for the point source evaluation) based on the physical quantities;

- up to the year 1999, the types of fuel used were much more detailed in Terna database: in BEN the 17 fuels are added up (using energy content) and reported together in 12 categories: emission factors for certain fuels (coal gases or refinery by

- products) are quite different and essential information is lost with this process;

- acti vity data for “

Basic Oxygen Furnace ( BOF) converter gas” are not reported in BEN up to 1999, from the year 2000 they are added up to the blast furnace gas;

- finally, the two data sets are never the same, even considering the total energy values of

fuels or the produced electricity, there are always small differences, less than 1%

- see Annex

2 for details

- that increase the already sizable discrepancy between the reference approach and the detailed approach.

In Annex 2, there are summary tables where the dif ferences between the national energy balance and ENEL/Terna data are detailed by primary fuel for the last two years: 2006 and 2007. For the other years, see previous NIR reports. The other two statistical publications quoted before, UP (UP, several years ) and ENI (ENI, several years [a]), have direct access to fuel consumption data from the associated companies, but both rely on Terna data for the complete picture. Data from those two sources are used for cross checking and estimation of point source emis sions.

To estimate CO 2



### emissions, and also N 2 

### O and CH

4 

### emissions, a rather complex calculation sheet is used, see document, APAT, 2003 [a], in Italian, for description. The data sheet summarizes all plants existing in Italy divided by technology, about 60 typologies, and type of fuel used; the

### 59

calculation sheet can be considered a model of the national power system. For each year, a run estimates the fuel consumed by each plant type, the pollutant emissions and GHG emissions. In response to the review proce ss of the Initial report of the Kyoto Protocol and of the 2006
submission under the Convention, N 2 

### O and CH

4 

### stationary combustion emission factors have been revised for the whole time series taking into account default IPCC (IPCC, 1997; IPCC, 2000) and

COR INAIR emission factors (EMEP/CORINAIR, 2007). The energy data used for the years 2006 and 2007 are reported in Annex 2. The emission factors

used are listed in Table 3.7. The model reports the consumption and GHG emission data according to primary source (oil, coal, natural gas) so that they can be inserted in the CRF. Moreover, the model is also able to estimate the energy/emissions data related to the electricity produced and used on site by the main industrial producers. Those data are reported in the i ndustrial sector section, in the tables 1.A.1.b/c and 1.A.2. The following Table 3.3 shows an intermediate part of the process, with all energy and emissions summarized by fuel and split in the two main categories of producers: public services and industri al producers for the year 2007. From 1998 onwards, the expansion of the industrial cogeneration of electricity and the split of the national monopoly has transformed many industrial producers into “independent producers”, regularly supplying the national g rid. So part of the energy/emissions of the industrial producers are added to table 1.A.1.a, according to the best information available.

C, Kt CO
2 

### , Kt - Gg

For table 1.A.1, a. Public Electricity and Heat Production

197,048 4,150 15,205

431,819 11,117 40,735

1,132,086 17,190 62,986

15,051 255 934

12,417 159 583

68,940 1,958 7,174

25,196 658 2,411

1,882,557 33,529 122,854

5,150 114 417

3 0 0

52,513 797 2,922

2,293 39 142

83,891 1,836 6,727

38,531 2,655 9,727

6,071 374 1,371
188,454 5,815 21,306

2,071,011 39,344 144,160 TJ

Liquid fuels

Solid fuels

Natural gas
Refinery gases

Coal gases

Biomass

Other fuels (incl.waste)

Total

Industrial producers (Table 1.A.1, a-b-c) and auto-producers,
to table "1.A.2 Manufacturing Industries "
Liquid fuels

Solid fuels
Natural gas
Refinery gases

Total

General total Other refinery products
Coal gases

Biomass

Other fuels (incl.waste)

Source: ISPRA elaborations Table 3.3 Power sector, Energy/CO 2 emissions in CRF format, year 2007



### In Table 3.4, the time series of the total CO 2 

### emissions deriving from electricity generation activities is reported, including total electricity produced and specific CO 2 

### emissions for the total production and for the thermoelectric production only.

The time series clearl

y shows that although the specific carbon content of the kWh generated in Italy has constantly improved over the years, total emissions are growing due to the even bigger increase of electricity production. Specific thermoelectric emissions are nearly stab le from the year 2000 to 2002 because efficiency increases have been balanced by a growing coal share. From 2 003

### 60

a remarkable improvement is reported in emissions of thermoelectric production, due to the entry into service of more efficient plants, but the improvement was much less in total production due to the reduction of hydroelectric production.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Total electricity produced (gross) 216.9 241.5 276.6 279.0 284.4 293.9 303.3 303.7 314.1 313.9

Total CO

2 emitted, Mt 128.5 135.7 140.5 138.3 145.4 148.1 146.0 146.4 148.7 144.2

g CO 2 / kwh of gross thermo-electric production 720 693 645 640 641 624 609 596 578 556

g CO 2 / kwh of total gross production 592 562 508 496 511 504 481 482 474 459
Source: ISPRA elaborations

Table 3.4 Time series of CO 2 emissions from electricity production



### 3.4.2 Refineries

The consumption data used come from BEN (MS E, several years [a]), the same data are also reported by UP (UP, several years). The available data in BEN specify the quantities of refinery gas, petroleum coke and other liquid fuels. They are reported in Annex 5, Table A5.6.

All the fuel used in boile rs and processes, the refinery “losses” and the reported losses of crude oil and other fuels (that are mostly due to statistical discrepancies) are considered to calculate

emissions. Fuel lost in the distribution network is accounted for here and not in th e individual end

use sector. Parts of refinery losses, flares, are reported in CRF table 1.B.2.a and c, using IPCC emission factors, the other emissions are reported in CRF table 1.A.1.b. From 2002 particular attention has been paid to avoid double counti ng of the CO 2 

### emissions checking if the individual refineries report sheets already include losses in the energy balances. It is planned to further investigate this aspect as soon as the new comprehensive reporting requirements of the IPPC directive are ro utinely used. Additional investigation is also planned to find out the fuel used for steam production, part of which presently seems to be allocated to the general industry.

IPCC Tier 2 emission factors and national emission factors are used see Table 3.7 . In Table 3.5, a sample calculation for the year 2007 is reported, with energy and emission data. In Table 3.6 GHG emissions in the years 1990, 1995, 2000

- 2007 are reported.

CO 2 emissions, kt

REFINERIES Petroleum coke Ref. gas Liquid fuels Natural gas Petroleum coke Ref. gas Liquid fuels Natural gas

105,939 13,283 0 0 8,413 739

38,130 115,880 75,180 3,803 7,201 5,706 0

TOTAL 348,412 0 0 0 25.9

Consumption, TJ

Source: APAT elaborations
Table 3.5 Refineries, CO 2 emission calculation, yea r 2007

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO 2 emissions, Mt 16.3 18.6 21.8 23.6 23.6 22.7 24.2 26.1 24.9 25.9

CH 4 emissions, kt 0.46 0.53 0.59 0.67 0.68 0.64 0.64 0.67 0.67 0.70

N 2 O emissions, kt 0.49 0.56 0.60 0.63 0.63 0.61 0.64 0.68 0.65 0.67

Refinery, total, Mt CO 16.5 18.8 22.0 23.8 23.8 22.9 24.4 26.3 25.1 26.1 Source: ISPRA elaborations
Table 3.6 Refineries, GHG emission time series



### 3.4.3 Manufacture of Solid Fuels and Other Energy Industries

In Italy all the iron and steel plants are integrated, so there is no separated reporting for the different part of the process. A few coke and “manufactured gas” producing plants were operating in the early nineties and they have been reported here. Only one small manufactured gas producing plant is still in operation from 2002.

### 61

In this section, emissions from power plants which use coal gases are also reported. In particular, we refer to the electricity generated in the steel plant sites (using coal gases and other fuels). The high implied emission factor for solid fuels is due to the large use of derived steel gases and in particular blast furnace gas to produce energy. These gases are assimilated to the renewable sources and incentives are provided for their use.

3.5 Manufacturing industries and construction

Energy consumption for this sector is reported i n the BEN, see Annex 5, Tables A5.9 and A5.10. The data comprise specification of consumption for 13 sub

- sectors and more than 25 fuels. Those very detailed data, combined with industrial production data, allow for a good estimation of all the fuel used by

most industrial processes (see list in paragraph 3.3). Source category descriptions for the most important sectors are supplied in the Industrial Processes chapter (chapter 4). A more sophisticated procedure is used to estimate coal use in steel productio n and coal gases used for electricity generation, see paragraph 3.5.1 and Annex 3 for details. The balance of fuel (total consumption less industrial processes consumption) is assumed as used in boilers and heaters in small and medium size enterprises; the emissions are estimated with the emission factors listed in

Table 3.7. These factors account for the fraction of carbon oxidised equal to 0.98 for solid fuels, 0.99 for liquid fuels and 0.995 for natural gas, as suggested by the 1996 IPCC guidelines (IPCC

, 1996). During the revision of the aviation sector, for jet gasoline and jet kerosene, a fraction of carbon oxidised equal to 1 has been applied, as reported in the 2006 IPCC guidelines (IPCC, 2006).

t CO 2 / TJ t CO 2 / t t CO 2 / tep
Liquid fuels

C rude oil 72.549 3.035 3.035

Jet gasoline 70.000 3.075 2.929

Jet kerosene 71.500 3.111 2.992

Petroleum Coke 99.755 3.464 4.174

Orimulsion 77.733 2.177 3.252

TAR 80.189 3.120 3.355

Gaseous fuels, national data

Natural gas (dry) 2007 average 55.636 1.947 (sm 3 ) 2.328

Solid fuels

Steam coal, 2007 average 95.041 2.465 3.977

"sub

- bituminous" coal 96.234 2.557 4.026

Lignite 99.106 1.037 4.147

Coke 105.929 3.102 4.432

Biomass

Solid Biomass (1.124) (4.495 )

Derived Gases, national data

Re finery Gas 62.080 3.120 2.60

Coke Gas 41.900 0.380 1.753

Blast furnace

– oxygen converter Gas 261.711 1.30 10.950

Fossil fuels, national data

Fuel oil , 2007 average 76.518 3.129 3.201

Coking coal 95.702 2.963 4.004

Other fuels

Municipa l solid waste 47.877 0.718 2.003

Transport

Petrol, 1990

- 99 71.034 3.121 2.972

Petrol, test data, 2000

- 07 71.145 3.109 2.977

Gas oil, 1990

- 99 73.274 3.127 3.066

Gas oil, engines, test data, 2000

- 07 73.153 3.138 3.061

### 62

Gas oil, heating, test data, 2 000

- 07 73.693 3.141 3.083

LPG, 1990

- 99, IPCC 64.350 3.000 2.692

LPG, test data, 2000

- 07 64.936 2.994 2.717

Source: ISPRA elaborations Table 3.7 Emission Factors for Power, Industry and Civil sector



### 3.5.1 Estimation of carbon content of coals used in in dustry

The preliminary use of the CRF software underlined an unbalance of emissions in the solid fuel rows above 20%. A detailed verification pointed out to an already known fact: the combined use of
standard IPCC emission factors for coals, national emi ssion factors for coal gases and CORINAIR methodology emission factors for steel works processes can bring to double counting of emissions. The main reason for this is the extensive recovery of coal gases from blast furnaces and coke ovens for electricity generation, a specific national circumstance of Italy. To avoid double counting, a methodology has been developed: it balances energy and carbon content of coking coals used by steelworks, industry, for non energy purposes and coal gases used

for electri city generation. The detailed procedure is described in Annex 3, here we underline that a balance is made between the input coals for coke production and the quantities of derived fuels used in various sectors. The iron and steel sector gets the resulting quantities of energy and carbon after subtraction of what is used for electricity generation, non energy purposes and other industrial

sectors.

3.5.2 Time series

In the following Table 3.8, GHG emissions connected to the use of fossil fuels, process emis sions excluded, in the years 1990, 1995 and 2000

- 2007 are reported. Industrial emissions do show oscillations, connected to economic cycles.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO 2 emissions, kt 88,937 87,955 88,134 85,412 81,540 86,418 86,244 81,732 82,106 78,867

CH 4 emissions, t 6,819 7,021 5,717 5,778 5,676 5,817 5,742 6,267 6,225 6,508

N 2 O emissions, t 4,931 4,519 4,661 4,742 4,772 4,928 5,028 5,018 5,047 4,979

Industry, total, kt CO 90,609 89,503 89,699 87,003 83,138 88,068 87,923 83,419 83,802 80,547

Source: ISPRA elaborations Table 3.8 Manufacturing industry, GHG emission time series



### In Table 3.9, the emissi ons of energy industries (paragraph 3.4), manufacturing industries (paragraph 3.5) and other sectors (paragraph 3.7) are summarized according to key sources categories. From 1990 to 2007, an increase in use of natural gas instead of fuel oil and gas oil in stationary combustion plants is observed; it results in a decrease of CO 2 

### emissions from combustion of liquid fuels and an increase of emissions from gaseous fuels.

1990 2007

CO 2 stationary combustion liquid fuels kt 153,467 86,306

CO 2 station ary combustion solid fuels kt 59,395 66,727

CO 2 stationary combustion gaseous fuels kt 85,066 159,220

CH 4 stationary combustion t 1,779 4,210

N 2 O stationary combustion t 647 963

Source: ISPRA elaborations Table 3.9 Stationary combustion, GHG emissions in 1990 and 2007

### 63

3.6 Transport

This sector shows a pronounced increase in emissions over time , reflecting the huge increase in fuel consumption for road transportation. The mobility demand and particularly the road transportation share have always incre ased in the period from 1990 to 2007.

The time series of CO 2 

### , CH 4 

### and N

2 

### O emissions is reported in Table 3.10. Emissions in the table comprise all the emissions reported in table 1.A.3 of the CRF.

Emission estimates are discussed below for each sub sector

. The trend of N

2 

### O emissions is related to the evolution of the technologies in the road transport sector and the distribution between gasoline and diesel fuel consumption. Methane emission trend is due to the combined effect of technological improvements that limit VOCs from tail pipe and evaporative emissions (for cars) and the expansion of two

- wheelers fleet. It has to be underlined that in Italy there is a remarkable fleet of motorbikes and mopeds (about 10 millions vehicles in 2007) that use gasoline and is increasing every year since 1990 . Only a small part of this fleet comply with tight VOC emissions controls.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO 2 Mt 101.3 111.4 120.1 122.2 124.1 125.1 127.1 125.8 127.2 127.2

CH 4 Mt 0.90 0.99 0.75 0.71 0.65 0.61 0.55 0.49 0.47 0.45

N 2 O Mt 1.11 1.81 2.09 2.05 2.02 1.95 1.92 1.48 1.55 1.53

Total, Mt CO

2 eq. Mt 103.3 114.2 122.9 124.9 126.8 127.7 129.6 127.8 129.2 129.2

Source: ISPRA elaborations Table 3.10 GHG emissions for the transport sector (Mt)



### 3.6.1 Aviation

3.6.1.1 Source category description

The IPCC requires the estimation of emissions for category 1A3ai International Aviation and 1A3aii Domestic Aviation, including figures both from the cruise phase of the flight and the landing

and take

- off cycles (LTO). Emissions from international aviatio n are reported as a memo item, and

are not included in national totals. Civil aviation gives mainly rise to CO 2 

### emissions

. CH 4 

### and N

2 

### O emissions also occur and are estimated in this category but their contribution is insignificant

. In 2007 total GHG emiss ions from this source category were about 1.9 per cent of the national total emissions from transport, and about 0.4 per cent of the GHG national total; in terms of CO 2 

### only,

the share is almost the same.

From 1990 to 2007 GHG emissions from the sector in creased by 51% due to the expansion of the aviation transport mode. Emission fluctuations over time are therefore mostly dictated by the growth rates in the number of flights. Specifically, in 2007 GHG emissions were about 6% higher than 2006.

Civil aviat ion is not a key ca tegory in the Italian inventory

.

3.6.1.2 Methodological issues

According to the IPCC Guidelines and Good Practice Guidance (IPCC, 1997; IPCC, 2000) and the EMEP/CORINAIR Guidebook (EMEP/CORINAIR, 2007), a national technique has been

de veloped and applied to estimate emissions.

The current method estimates emissions from the following assumptions and information. Activity data comprise both fuel consumptions and aircraft movements, which are available in different level of aggregation a nd derive from different sources as specified here below:

### 64

• Total inland deliveries of aviation gasoline and jet fuel are provided in the national energy balance (MSE, several years [a]), see Annex 5 Table A5.10. This figure is the best approximation of avi

ation fuel consumption, for international and domestic use, but it is not split between domestic and international;

• Data on annual arrivals and departures of domestic and international landing and take

- off cycles at Italian airports are reported by differe nt sources: National Institute of Statistics in the statistics yearbooks (ISTAT, several years [a]), Ministry of Transport in the national transport statistics yearbooks (MINT, several years) and the Italian civil aviation in the

national aviation statisti

cs yearbooks (ENAC/MINT, several years).

As for emission and consumption factors, figures are derived by the EMEP/CORINAIR guidebook (EMEP/CORINAIR, 2007), both for LTO cycles and cruise phases, taking into account national specificities. These specificit ies derive from the results of a national study which, taking into account detailed information on the Italian air fleet and the origin

- destination flights for the year 1999, calculated national values for both domestic and international flights (Romano et al., 1999; ANPA, 2001; Trozzi et al., 2002 [a]), on the basis of the default emission and consumption factors reported in the EMEP/CORINAIR guidebook. National average emissions and consumption factors

were therefore estimated for LTO cycles and cruise bo th for domestic and international flights from

1990 to 1999. At present, the study has been updated for the years 2005, 2006 and 2007 in order to consider most recent trends in civil aviation both in terms of modelling between domestic and

international fl ights and technological progress of the fleet (TECHNE, 2009). Based on the results

, national average emissions and consumption factors were updated from 2000

.

Specifically, for the years referred to in the surveys, the current method estimates emissions f rom the number of aircraft movements broken down by aircraft type (and engine type derived when not specified from ICAO database) at each of the principal Italian

airport s considering the information

of whether the flight is international or domestic and t he relevant distance travelled. For those years, a Tier 3 method has been applied. In fact, figures on the number of flights, destination, aircraft fleet and engines has been provided by the local airport authorities, national
airlines (Alitalia, AirOne) and European Civil Aviation (EUROCONTROL), covering about 80% of the official national statistics on aircraft movements for the relevant years. Data on ‘Times in mode’

have also been supplied by the four principal airports and estimates for the other minor airports have been carried out on the basis of previous sectoral studies at local level. Consumption and

emission factors are those derived from the EMEP/CORINAIR guidebook ( EMEP/CORINAIR,
2007). Based on sample information

, estimate s have been carried ou t at national level for the relevant years considering the official statistics of the aviation sector.

In general, to carry out national estimates of greenhouse gases and other pollutants in the Italian inventory for LTO cycles, both domestic and internat ional, consumptions and emissions are calculated for the complete time series using the average consumption and emission factors multiplied by the total number of flights. The same method is used to estimate emissions for
domestic cruise; on the other hand , for international cruise, consumptions are derived by difference from the total fuel consumption reported in the national energy balance and the estimated values as

described above and emissions are therefore calculated.

Data on domestic and internation al aircraft movements from 1990 to 2007 are shown in Table 3.11

where domestic flights are those entirely within Italy. Emission factors are reported in Table 3.12 and Table 3.13. Total fuel consumptions both domestic and international are reported by LTO and

cruise in Table 3.14.

### 65

Emissions from military aircrafts are also estimated and reported under category 1.A.5 Other. The methodology to estimate military aviation emissions is simpler than the one described for civil

aviation since LTO data are not av ailable in this case. As for activity data, total consumption for military aviation is published in the petrochemical bulletin (MSE, several years [b]) by fuel. Emission factors are those provided in the EMEP/CORINAIR guidebook ( EMEP/CORINAIR, 2007). There fore, emissions are calculated by multiplying military fuel consumption data for the

EMEP/CORINAIR default emission factors shown in Table 3.13.

Flights 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Domestic 186,446 199,585 319,963 303,354 298,104 325,179 313,171 311,218 324,779 346,724

International 139,733 184,233 303,747 315,736 310,271 325,755 343,052 363,140 385,159 420,021
Source: ISTAT, several years [a]; ENAC/MINT, several years Table 3.11 Aircraft Movement Data (LTO cycles)

CO 2 a SO 2 Aviation jet fuel 849 1.0
Aviation gasoline 839 1.0
a Emission factor as kg carbon/t.

Table 3.12 CO

2 and SO

2 emission factors for Aviation (kg/t) 1990

- 2007

Units CH

4 N 2 O NO

x CO NMVOC Fuel

Domestic LTO kg/LTO 0.189 0.040 5.313 6.939 1.698 461.7

Inte rnational LTO kg/LTO 0.306 0.048 5.702 8.524 2.758 553.3

Domestic Cruise kg/t fuel

- 0.152 24.003 3.313 0.822

- International Cruise kg/t fuel

- 0.535 70.916 7.190 2.569

-
Aircraft Military a kg/t fuel 0.4 0.2 15.8 126 3.6

-

a EMEP/CORINAIR, 200 7

Tabl e 3.13 Non

- CO 2 Emission Factors for Aviation (2007)

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

kt

Domestic LTO 121 129 198 180 178 175 160 150 153 160

International LTO 123 162 250 241 208 212 204 195 212 232

Domestic cruise 387 385 464 50 2 546 629 642 588 590 587

International cruise 1,215 1,662 2,327 2,334 2,143 2,529 2,567 2,733 2,948 3,120

Source: ISPRA elaborations Table 3.14 Aviation jet fuel consumptions for domestic and international flights (kt)



### 3.6.1.3 Uncertainty and time

- seri es consistency

The combined uncertainty in CO 2 

### emissions from aviation is estimated to be about 4% in annual emissions; a higher uncertainty is calculated for CH 4 

### and N 2 

### O emissions on account of the uncertainty levels attributed to the related emission f actors. Time series of domestic emissions from the aviation sector is reported in Table 3.15. An upward trend in emission levels is observed from 1990 to 2007 which is explained by the increasing number of LTO cycles. Nevertheless, the propagation of mor e modern aircraft into the fleet slow down the tendency in the last years.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO 2 kt 1.613 1.709 2.649 2.424 2.425 2.415 2.231 2.204 2.291 2.428

CH 4 t 32 33 63 69 78 96 102 112 98 72

N 2 O t 45 48 74 68 64 68 62 62 64 68

Source: ISPRA elaborations

Table 3.15 GHG emissions from domestic aviation

### 66

3.6.1.4 Source

- specific QA/QC and verification

Data used for estimating emissions from the aviation sector, derive from different sources: local airport authorities, national airlines operators, EUROCONTROL and official statistics by different

Ministries and national authorities.

Specifically, the results of the estimation method, deriving from the 20 09 research commissioned by ISPRA, applied at national and airport level have been shared with national experts in the framework of an ad hoc working group on air emissions instituted by the national Aviation Authority (ENAC). The group is chaired by ISPRA and includes participants from ENAC, Ministry of Environment, Land and Sea, Ministry of Transport, national airlines and local airport authorities. The results reflect differences between airport, aircraft used and time in mode spent for each operation.

3.6.1.5 Source

- specific recalculations

There has been an overall recalculation of emissions from the sector due to the update of the methodological study completed in 2009. In fact, in previous submissions, constant parameters were applied for the all ti me series considering model input of the year 1999. The time series did not take into account most recent trends in civil aviation in terms of technological improvements, fleet composition and changes in the split between national and international fuel co nsumption; in particular the distribution between European and extra

- European flights has changed from 1999

with an increase of the shortest distances. As specified in the last review reports (UNFCCC, 2006; UNFCC, 2009), the ERT recommended to update these results in view of recent available national research to improve the accuracy of the inventory and correct the potential overestimation for recent

years. Aim of the revision was, principally, to revise the consumption values and relative parameters

which are very important for local air quality, in terms of pollutants such as NO X 

### , NMVOC, PM, and consequently greenhouse gases. In fact, the revision of the methodology resulted mainly in a reduction of domestic fuel consumptions for the last years, due to te chnological improvements and fleet composition for domestic flights.

Specifically, for greenhouse gases, CO 2 

### emissions were recalculated from 1990 due to a different emission factor applied with respect to previous submissions. The emission factors used a re provided in the EMEP/CORINAIR guidebook in line with the IPCC 2006 guidelines and the guidelines specified for the Emissions Trading Scheme of the aviation sector (EMEP/CORINAIR,

2007; IPCC, 2006 ; EC, 2009) and are equal to 71.5 kg/Gj for the jet fuel a nd 70.0 kg/Gj for the avio gasoline. For these fuels, an oxidation factor equal to 1 has been considered . Th is recalculation

resulted in an increase of CO 2 

### emission by 1% with respect to previous submissions.

N 2 

### O and CH

4 

### emissions were also recalculated bu t they are less important in terms of absolute

values. N

2 

### O emissions were revised applying the emission factor reported in EMEP/CORINAIR guidebook in line with the IPCC 1996 and 2006 guidelines (EMEP/CORINAIR, 2007; IPCC, 1996; IPCC, 2006) and equal to 2 k g/Tj of fuel , about 20% higher than the previous value

. The methodology was also applied to revise NMVOC estimations therefore leading to new estimates of

CH 4 

### emissions which have been calculated applying the default emission factor of 10% of total hydroca rbons (EMEP/CORINAIR, 2007; IPCC, 1996; IPCC, 2006). This revision has lead to an emission factor generally lower than the previous one.

### 67

The recalculation affected only slightly the time series up to 1999 (about +1.5%) but consistently

the estimations fr om 2000 to 2006, with differences ranging from

- 2% to

- 17%, with respect to

earlier submissions. The revision of model assumptions has lead to a recalculation of international bunkers, accordingly.

3.6.1.6 Source

- specific planned improvements

No specif ic improvements are planned for the next submission.

3.6.2 Railways

The electricity used by the railways for electric traction is supplied from the public distribution system, so the emissions arising from its generation are reported under category 1A1a Public Electricity. Emissions from diesel trains are reported under the IPCC category 1A3c Railways. These estimates are based on the gas oil consumption for railways reported in BEN (MSE, several years [a]). Carbon dioxide, sulphur dioxide and N 2 

### O em issions are calculated on fuel based emission factors using fuel consumption data from BEN. Emissions of CO, NMVOC, NO

x 

### and methane are based on the EMEP/CORINAIR methodology (EMEP/CORINAIR, 2007). The emission factors shown in Table 3.16 are aggregate fa ctors so that all factors are reported on the common basis of fuel consumption.

CO 2 CH 4 N 2 O NO

x CO NMVOC SO 2 Diesel train 857 0.14 1.2 40.5 4.9 3.6 2.8

Source: EMEP/CORINAIR, 2007

Table 3.16 Railway Emission Factors (kt/Mt 

### )

3.6.3 Road Transport

3.6. 3.1 Source category description

The IPCC requires the estimation of emissions for category 1.A.3.b Road transportation. In 2007, total GHG emissions from this category were about 93.3 per cent of the national total emissions from transport, 26.3 per cent of the energy sector and about 21.8 per cent of the GHG

national total.

From 1990 to 2007, GHG emissions from the sector increased by 25% due to the increase of vehicle fleet, total mileage and consequently fuel consumptions. In the last years, from 2004 , fuel consumption and emissions stabilised. In 2007, GHG emissions were about 0.3% higher than those

of 2006 were.

CO 2 

### for road transport is key category for 2007 with Tier 1 and Tier 2 methods at level and trend
assessment, with and without LULUCF. N 2 

### O emissions are key category at level assessment only

with Tier 2. CH 4 

### emissions are key category only for 1990 at level assessment with Tier 2 methodology.

Emissions from road transport are calculated either from a combination of total fuel consumption

da ta and fuel properties or from a combination of drive related emission factors and road traffic

data.

### 68

3.6.3.2 Methodological issues

According to the IPCC Guidelines and Good Practice Guidance (IPCC, 1997; IPCC, 2000) and the
EMEP/CORINAIR Guidebook (EM EP/CORINAIR, 2007), a national methodology has been developed and applied to estimate emissions. In particular, the model COPERT 4 (EEA, 2007) has

been used to estimate emissions for the whole time series. Methodologies are described in the following, dist inguishing emissions calculated from fuel consumption and traffic data.

3.6.3.2.1 Fuel

- based emissions

Emissions of carbon dioxide and sulphur dioxide from road transport are calculated from the consumption of gasoline, diesel, liquefied petroleum gas ( L PG) and natural gas and the carbon

- sulphur content of the fuels consumed. Consumption data for the fuel consumed by road transport in Italy are taken from the BEN (MSE, several years [a]), see Annex 5, Tables A5.9 and A5.10, in physical units (rows “III

- Road transportation” and “VI

- Public Service”, subtracting the quantities for military use in diesel oil and off

- road uses in petrol).

Emissions of CO 2 

### , expressed as kg carbon per tonne of fuel, are based on the H/C ratio of the fuel;

emissions of SO 2 

### are based on the sulphur content of the fuel. Values of the fuel

- based emission

factors for CO 2 

### from consumption of petrol and diesel fuels are shown in Table 3.17. These factors account for the fraction of carbon oxidised for liquid fuels equal to 0.99, as suggested by the 1996 IPCC guidelines (IPCC, 1996).

Values for SO 2 

### vary annually as the sulphur

- content of fuels change and are calculated every year for gasoline and gas oil and officially communicated to the European Commission in the framework

of E uropean Directives on fuel quality; these figures are also published by the refineries industrial association (UP, several years).

National emission factors t CO 2 / TJ t CO 2 / t

Mtbe 73.121

- Gasoline, 1990

- '99, interpolated emission

factor 71.034 3.121

Gasoline, test data, 2000

- 07 b 71.145 3.109

Gas oil, 1990

- '99, IPCC OECD a 73.274 3.127
Gas oil, engines, test data, 2000

- 07 b 73.153 3.138

LPG, 1990

- '99, IPCC

a Europe 64.350 3.000

LPG, test data, 2000

- 07 b 64.936 2.994

Natural gas (dry) 199 0 55.328

- Natural gas (dry) 2007 55.636

-



### a Revised 1996 IPCC Guidelines for National GHG Inventories, Reference Manual, ch1, tables 1

- 36 to 1

- 42

b Emission factor in kg carbon/tonne, based on ISPRA (APAT, 2003 [b] )

Table 3.17 Fuel

- Based Emission Fa ctors for Road Transport



### Emissions of CO 2 

### and SO 2 

### can be broken down by vehicle type based on estimated fuel consumption factors and traffic data in a manner similar to the traffic

- based emissions described below for other pollutants. The 2007 inventory u sed fuel consumption factors expressed as g of fuel per kilometre for each vehicle type and average speed calculated from the emission functions and speed

- coefficients provided by the model COPERT 4 ( EEA, 2007 ). The updated version of the

### 69

model has been us ed for the whole time series. As reported more in details in the following, the new model updates especially NO X 

### and N 2 

### O emission factors; the application to Italian data resulted in a strong increase of NO X 

### emissions and a strong decrease of N 2 

### O emissions for the whole time series.

Fuel consumptions calculated from these functions are shown in Table 3.18 for each vehicle type, emission regulation and road type in Italy. A normalisation procedure was used to ensure that the breakdown of gasoline and diesel consumption by each vehicle type calculated on the basis of the fuel consumption factors added up to the BEN figures for total fuel consumption in Italy (adjusted

for off

- road consumption).

Source: ISPRA elaborations Notes: PC, passenger cars ; LDV, light duty vehicles ; HDV, heavy duty vehicles; Moto, motorcycles; Hway, highway speed traffic; rur, rural speed traffic; urb, urban speed traffic; biodiesel included in diesel Table 3.18 Average fuel consumption and mileage for main vehicle category and road type, year 2007



### 3.6.3.2.2 Traffic

- based emissions

Emissions of NMVOC, NO X 

### , CO, CH 4 

### and N

2 

### O are calculated from emission f actors expressed in grams per kilometre and road traffic statistics estimated by ISPRA on data released from Ministry of Transport (MINT, several years). The emission factors are based on experimental measurements

of emissions from in

- service vehicles of d

ifferent types driven under test cycles with different average speeds calculated from the emission functions and speed

- coefficients provided by COPERT 4 ( EEA, 2007 ). This source provides emission functions and coefficients relating emission factors (in g/k m) to average speed for each vehicle type and Euro emission standard derived by fitting experimental measurements to polynomial functions. These functions were then used to calculate SNAP

CODE Sub

sector Type

of fuel Tons of fuel

consumed Mileage

,

km_kVEH

070101 PC Hway diesel 4,058,171 72,660,282

070101 PC Hway gasoline 2,317,954 46,377,378

070101 PC Hway lpg 299,168 4,735,048

070102 PC rur diesel 6,232,637 124,316,120

070102 PC rur gasoline 3,505,641 79,896,926

070102 PC rur lpg 285,265 6, 313,398

070103 PC urb diesel 2,471,652 32,518,256

070103 PC urb gasoline 4,053,517 50,845,958

070103 PC urb lpg 356,552 4,735,048

070201 LDV Hway diesel 1,342,239 13,039,098

070201 LDV Hway gasoline 59,924 867,572

070202 LDV rur diesel 2,172,416 35,8 57,521

070202 LDV rur gasoline 169,013 2,385,822

070203 LDV urb diesel 1,772,680 16,298,873

070203 LDV urb gasoline 175,216 1,084,465

070301 HDV Hway diesel 3,465,100 19,824,452

070301 HDV Hway gasoline 939 5,690

070302 HDV rur diesel 2,346,353 13,699,772

070302 HDV rur gasoline 2,561 17,071

070303 HDV urb diesel 1,329,668 4,721,297

070303 HDV urb gasoline 1,280 5,690

070400 mopeds gasoline 409,309 18,166,330

070501 Moto Hway gasoline 71,097 1,648,320

070502 Moto rur gasoline 325,861 11,538,242

070503 Moto urb gasoline 574,195 19,779,844

Total 581,338,476

### 70

emission factor values for each vehicle type and Euro emission standard a t each of the average speeds of the road and area types.

The road traffic data used are vehicle kilometre estimates for the different vehicle types and

different road classifications in the national road network. These data have to be further broken

down by composition of each vehicle fleet in terms of the fraction of diesel

- and petrol

- fuelled

vehicles on the road and in terms of the fraction of vehicles on the road made to the different emission regulations which applied when the vehicle was first regist ered. These are related to the age profile of the vehicle fleet. Additional data are required for the estimation of consumption of buses, because the available traffic data seldom distinguish beyond “heavy vehicles”. Moreover, traffic data on motorcycles a re not exhaustive. In both cases, the energy consumption is estimated on the basis of the oil companies’ reports on sold fuels.

It is beyond the scope of this paper to illustrate in details the COPERT 4 methodology: in brief, the

emissions from motor vehi cles fall into three different types calculated as hot exhaust emissions,

cold

- start emissions and, for NMVOC and methane, evaporative emissions. Hot exhaust emissions are emissions from the vehicle exhaust when the engine has warmed up to its normal opera ting temperature. Emissions depend on the type of vehicle, type of fuel the engine runs on, the driving profile of the vehicle on a journey and the emission regulations applied when the vehicle was first registered as this defines the type of technology th e vehicle is equipped with. For a particular vehicle, the drive cycle over a journey is the key factor which determines the amount of pollutant emitted.

Key parameters affecting emissions are acceleration, deceleration, steady speed and idling

character istics of the journey, as well as other factors affecting load on the engine such as road gradient and vehicle weight. However, studies have shown that for modelling vehicle emissions
over a road network at national scale, it is sufficient to calculate em issions from emission factors in g/km related to the average speed of the vehicle in the drive cycle ( EEA, 2007). Emission factors for average speeds on the road network are then combined with the national road traffic data.

Emissions are calculated from vehicles of the following types:

• Gasoline passenger cars;

• Diesel passenger cars;

• Gasoline Light Goods Vehicles (Gross Vehicle Weight (GVW) < = 3.5 tonnes);

• Diesel Light Goods Vehicles (Gross Vehicle Weight (GVW) < = 3.5 tonnes);

• Rigid

- axle Heavy Goods Vehicl es (GVW > 3.5 tonnes);

• Articulated Heavy Goods Vehicles (GVW > 3.5 tonnes);

• Buses and coaches;

• Mopeds and motorcycles.

Basic data derive from different sources. Detailed data on the national fleet composition is found in the yearly report from ACI (ACI, s everal years). The National Association of Cycle

- Motorcycle Accessories (ANCMA, several years) supplies useful information on mopeds fleet composition and mileages . The Ministry of Transport in the national transport yearbook ( MINT, several years)

reports passenger car mileages time series. The National Institute of Statistics carries out annually a survey on heavy goods vehicles, including annual mileages (ISTAT, several years [b]). The National Association of concessionaries of motorways and tunnels produ ces monthly statistics on highway mileages by light and heavy vehicles (AISCAT, several years). The National General Confederation of Transport and Logistics (CONFETRA, several years) and the national Central

### 71

Commitee of road transporters (Giordano, 2007) supplied useful infor mation and statistics about heavy goods vehicles fleet composition and mileages.

In the following Tables 3.19, 3.20 and 3.21 detailed data on the relevant vehicle mileages in the circulating fleet between 1990 and 2007 are reported, s ubdivided according to the main emission regulations.

1990 1995 2000 2007
pre-1972, PRE ECE 0.05 0.03 0.01 0.01

1972 -1977, ECE 15.00/.01 0.10 0.04 0.01 0.00

1978 -1986, ECE 15.02/.03 0.32 0.14 0.03 0.01

1987 -1992, ECE 15.04 0.53 0.55 0.28 0.08

91/441/EC, from 1/1/93, euro I 0.00 0.25 0.28 0.11

94/12/ EC, from 1-1-97 , euro II 0.39 0.33

98/69/EC, from 1/1/2001, euro III 0.22

98/69/EC, from 1/1/2006, euro IV, V 0.25

Total 1.00 1.00 1.00 1.00

Source: ISPRA elaborations on ACI data Table 3.19 Gasoline cars technological evolution: circulating fleet calculated as stock data multiplied by effective mileage (%)



### 1990 1995 2000 2007

pre- 1993 1.00 0.91 0.35 0.02

91/441/EC, from 1/1/93, euro I 0.09 0.10 0.02

94/12/ EC, from 1-1-97 , euro II 0.55 0.18

98/69/EC, from 1/1/2001, euro III 0.41

98/69/EC, from 1/1/2006, euro IV, V 0.36

Total 1.00 1.00 1.00 1.00

Source: ISPRA elaborations on ACI data Table 3.20 Diesel cars technological evolution: circulating fleet calculated as stock data multiplied by effective mileage (%)



### 1990 1995 2000 2007

pre -1996 1.00 0.93 0.61 0.14

from 1/1/96, Dir. 91/542 EEC, euro I 0.07 0.22 0.10

from 1/1/97, Dir. 91/542 EEC, euro II 0.17 0.26

from 1/1/2001, Dir. 99/96, euro III 0.37

from 1/1/2006, Dir. 99/96, euro IV, V 0.13

Total 1.00 1.00 1.00 1.00

Source: ISPRA elaborations on ACI data Table 3.21 Trucks technological evolution: circulating fleet for light dut y (%)



### Average emission factors are calculated for average speeds by three driving modes, urban, rural and motorway, combined with the vehicle kilometres travelled and vehicle categories.

ISPRA estimates total annual vehicle kilometres for the road networ k in Italy by vehicle type, see
Table 3.22, based on data from various sources:

- Ministry of Transport (MINT, several years) for rural roads and on other motorway; the

latter estimates are based on traffic counts from the rotating census and core census su rveys of ANAS;

- highway industrial association for fee

- motorway (AISCAT, several years);

- local authorities for built

- up areas (urban).

### 72 1990 1995 2000 2005 2006 2007
All passenger vehicles, total

mileage (10 9



### veh-km/y) 295 352 389 426 426 426

Car fleet (10 6 

### ) 27 30 32 34 35 35

Moto, total mileage (10 9



### vehkm/y) 31 39 45 49 50 51

Moto fleet (10 6 

### ) 7 7 9 10 10 10
Goods transport, total mileage

(10 9 

### veh-km/y) 69 77 93 98 102 104

Truck fleet (10 6 

### ), including

LDV 2 3 3 4 4 5

Source: ISPRA elaborations Table 3.22 Evolution of fleet consistency and mileage



### When a vehicle engine is cold, it em its at a higher rate than when it has warmed up to its designed operating temperature. This is particularly true for gasoline engines and the effect is even more

severe for cars fitted with three

- way catalysts, as the catalyst does not function properly un til the catalyst is also warmed up. Emission factors have been derived for cars and LGVs from tests performed with the engine starting cold and warmed up. The difference between the two measurements can be regarded as an additional cold

- start penalty paid on each trip a vehicle is started with the engine (and catalyst) cold. Evaporative emissions of gasoline fuel vapour from the tank and fuel delivery system in vehicles constitute a significant fraction of total NMVOC and methane emissions from road transp ort. The procedure for estimating evaporative emissions of NMVOCs and methane takes account of changes in ambient temperature and fuel volatility.

3.6.3 .3 Uncertainty and time

- series consistency

The combined uncertainty in CO 2 

### emissions from road trans port is estimated to be about 4% in annual emissions; a higher uncertainty is calculated for CH 4 

### and N

2 

### O emissions on account of the uncertainty levels attributed to the related emission factors.

The following Table 3.23 summarizes the time series of GHG emissions in CO 2 

### equivalent from road transport, highlighting the evolution of this growing source. An upward trend in CO 2 

### emission levels is observed from 1990 to 2004, which is explained by the increasing of the fleet, total mileages and fuel consumptio ns. Nevertheless, the propagation of the number of vehicles with low fuel consumption per kilometre, slows down the tendency in the last years.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO 2 kt 93,387 103,553 110,385 113,064 115,209 116,321 118,395 117,035 118,268 118,721

CH 4 kt 867 956 713 674 621 576 515 459 440 415

N 2 O kt 996 1,694 1,966 1,935 1,907 1,832 1,804 1,371 1,437 1,420

Total kt 95,249 106,204 113,064 115,672 117,737 118,729 120,713 118,865 120,145 120,556
Source: ISPRA elaborations Table 3.23 GHG emissions from road transport (kt CO 2 equivalent)



### 3.6.3.4 Source

- specific QA/QC and verification

Data used for estimating emissions from the road transport sector, derive from different sources

, including official statistics providers and industrial associations

.

### 73

A specific procedure undertaken for improving the inv entory in the sector regards the establishment of a national expert panel in road transport which involves, on a voluntary basis, different institutions, local agencies and industrial associations cooperating for improving activity data and

emission factor s accuracy. In this group, emission estimates are presented annually, and new methodologies are shared and discussed.

Besides, time series resulting from the recalculation due to the application of Copert 4 have been discussed with national experts in the framework of an ad hoc working group on air emissions inventories. The group is chaired by ISPRA and includes participants from the local authorities responsible for the preparation of local inventories, sectoral experts, the Ministry of Environment,

Land and Sea, and air quality model experts. Recalculations are comparable with those resulting from application of the new model at local level. Top

- down and bottom

- up approaches have been compared with the aim to identify the major problems and future possib le improvements in the methodology to be addressed.

3.6.3.5 Source

- specific recalculations

The transition from Copert III to Copert 4 was indeed the occasion for a general review of input data, as activity data, model parameters and emission factors. Th e new version revised both the estimation methodology and the software.

The most recent update of the software is Copert 4, version 6.1 since February 2009 (EEA, 2007)

which is a user

- friendly version enhancing import/export capabilities and the managemen t of time

series of estimates.

Methodological differences affected mainly emission estimates of heavy good vehicles, especially in terms of fleet classification, emission factors, and emission degradation parameters.

In addition, hot emission factors of regulated pollutants for conventional passenger cars and powered two wheelers and nitrous oxide and ammonia from passenger cars and light duty vehicles have been updated; particulate matter emissions have been distinguished by exhaust and not exhaust

emiss ions. Copert 4 also includes a new methodology for the estimation of evaporative emissions and a revision of heavy metal estimates due to the inclusion of emissions from tyre and brakes wear.

As regards passenger cars, light duty vehicles, mopeds and moto rcycles, the fleet classification considered in Copert 4 is the same as the older version. On the contrary, the classification regarding heavy goods trucks and buses is more detailed in Copert 4 than Copert III, so accordingly input data

for the whole seri

es were recalculated from 1990 to 2007.

The uploading of the whole time series data in the new software has been the occasion for the review of the fuel consumption time series. Diesel and gasoline fuel consumptions, for road transport, have been revised in order to avoid double counting for some years of consumptions of military diesel oil and gasoline for motor boating, which are included in the road transport row in the National Energy Balance (MSE, several years). In particular, diesel fuel has been up dated for the years from 1991 to 2000, while gasoline from 1991 to 2005. LPG activity data have been updated only in 2000 while no changes occurred for natural gas and biomass activity data.

With regard to CO 2



### emission factors, IPCC values were considere d as reference values for diesel and LPG, for years from 1990 to 1999, and H/C ratios incorporated accordingly in the Copert 4.

### 74

Hence, emission factors have been slightly changed, while from 2000 national emission factors have been used as in the previous estimates (see Table 3.17).

Methane emission values are higher in the nineties and lower from 2000 onwards, in comparison with the previous submission. The difference is mainly explained by the update in the model of hydrocarbon emission factors for all vehicles, involving both recalculation of non methane volatile organic compounds and methane emissions.

Finally, Copert 4 revised emission factors of N 2 

### O and NO X 

### for the whole time series, for all vehicles. The main update regarded heavy goods vehicles an d passenger cars diesel fuelled. New

estimates of N

2 

### O emissions result lower than the previous time series. On the other hand, nitrogen oxides show higher values in the new estimates for all the years and this, at national level, will be a problem for the compliance with the national emission ceilings European Directive.

Recalculations, in the total road transport GHG emissions

, account for

- 0.7 % in 1990 and

- 2.1% in

2006. H igher discrepancies are observed for methane (ranging from 16.6% in 1990 to

- 16.6% in 2006) and nitrous oxide (ranging from

- 38% in 1990 to

- 63.9% in 2006); carbon dioxide values are relatively homogeneous varying from

- 0.2% in 1990 to

- 0.002% in 2006.

3.6.3.6 Source

- specific planned improvements

No specific improvements are planned f or the next submission.

3.6.4 Navigation

3.6.4.1 Source category description

This source category includes all emissions from fuels delivered to water

- borne navigation.

M ainly CO 2 

### emissions derive from this category, whereas CH 4 

### and N 2 

### O emissions are l ess important. Emissions from navigation constitu ted 3.9 per cent of the total GHG in the transport sector in 200 7 and 0.9 per cent of the national total

. If considering CO 2 

### only, emissions from navigation are 1.1%

out of the national CO 2 

### emissions. GHG em issions de creased by 8.3 per cent from 1990 to 200 7

, although an increase in the number of movements is observed, on account of the reduction in fuel consumed in harbour and navigation activities

.

Navigation is a key category with respect to CO 2 

### emission s in level and trend with uncertainty.

3.6.4.2 Methodological issues

Emissions of the Italian inventory from the navigation sector are carried out according to the IPCC Guidelines and Good Practice Guidance (IPCC, 1997; IPCC, 2000) and the EMEP/CORINAI R
Guidebook (EMEP/CORINAIR, 2007 ). In particular, a national methodology has been developed following the EMEP/CORINAIR guidebook which provides details to estimate emissions from domestic navigation, specifying recreational craft, ocean

- going ships by cru

ise and harbour activities; emissions from international navigation are also estimated and included as memo item

but not included in national totals. (EMEP/CORINAIR, 2007 ). Inland, coastal and deep

- sea fishing are estimated and reported under 1.A.4.c

.

### 75

The methodology developed to estimate emissions is based on the following assumptions and

information. Activity data comprise both fuel consumptions and ship movements, which are available in different level of aggregation and derive from different sources as specified here below:

• Total deliveries of fuel oil, gas oil and marine diesel oil to marine transport are given in national energy balance (MSE, several years [a]) but the split between domestic and international is not provided;

• Naval fuel consumption f or inland waterways, ferries connecting mainland to islands and leisure boats, is also reported in the national energy balance as is the fuel for shipping (MSE, several years [a]);

• Data on annual arrivals and departures of domestic and international shippi ng calling at Italian harbours are reported by the National Institute of Statistics in the statistics yearbooks (ISTAT, several years

[a] ) and Ministry of Transport in the national transport statistics yearbooks (MINT, several years).

As for emission and consumption factors, figures are derived by the EMEP/CORINAIR guidebook (EMEP/CORINAIR, 2007), both for recreational a nd harbour activities and national cruise, taking into account national specificities. These specificities derive from the results of a n ational study which, taking into account detailed information on the Italian marine fleet and the origin

- destination movement matrix for the year 199 7 , calculated national values ( ANPA, 2001; Trozzi et al., 2002
[b]) ) on the basis of the default emission a nd consumption factors reported in the EMEP/CORINAIR guidebook. National average emissions and consumption factors were therefore estimated for harbour and cruise activities both for domestic and international shipping from 1990 to 1999. At present, as in the case of aviation, the study has been updated for the years 200 4 , 200 5 and 200 6 in order to consider most recent trends in the maritime sector both in terms of modelling between domestic and international consumptions and operational improvements in ha rbour (TECHNE, 2009). On the basis of the results, national average emissions and consumption factors were updated from 2000.

Specifically, for the years referred to in the surveys, the current method estimates emissions from the number of ships movements broken down by ship type at e ach of the principal Italian ports considering the information of whether the ship movement is international or domestic , the average

tonnage and the relevant distance travelled.

For those years, in fact, figures on the numb er of arrivals

, destination, and fleet composition have been provided by the local port authorities and by the National Institute of Statistics (ISTAT, 2009), covering about 9 0% of the official national statistics on ship movements for the relevant years. Consumption and emission factors are those derived from the EMEP/CORINAIR guidebook ( EMEP/CORINAIR, 2007) and refer to the Tier 3 ship movement methodology that takes in account origin

- destination ship movements matrices as well as technical information on the ships, as engine size, gross tonnage of ships and operational times in harbours. On the basis of sample information, estimates have been carried out at national level for the relevant years considering the

official statistics of the maritime sector.

In general, to carry out national estimates of greenhouse gases and other pollutants in the Italian inventory for harbour and domestic cruise activities, consumptions and emissions are calculated for the complete time series using the average consumption a nd emission factors multiplied by the total number of movements. On the other hand, for international cruise, consumptions are derived by difference from the total fuel consumption reported in the national energy balance and the estimated

values as describ ed above and emissions are therefore calculated.

### 76

3.6.4.3 Uncertainty and time

- series consistency

The combined uncertainty in CO 2 

### emissions from maritime is estimated to be about 4% in annual emissions; a higher uncertainty is calculated for CH 4 

### and N 2 

### O emissions on account of the uncertainty levels attributed to the related emission factors.

Estimates of fuel consumption for domestic use, in the national harbours or for travel within two
Italian destinations, and bunker fuels used for international tr avels are reported in Table 3.24. Time series of domestic GHG emissions for waterborne navigation are also shown in the same table.

An upward trend in emission levels is observed from 1990 to 1997 explained by the increasing number of ship movements. Neve rtheless, the operational improvements in harbour activities and a reduction in ship domestic movements inverted the tendency in the last years.

1990 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

F uel in domestic travels (kt) 778 706 802 843 866 818 811 787 748 741 732 740 709 673

F uel in harbours (dom+int ships) (kt) 748 693 794 824 853 814 818 800 767 766 763 759 727 690

F uel in international Bunkers (kt) 1,398 1,286 911 975 1,019 1,053 1,333 1,534 1,768 2,001 2,167 2,203 2,369 2, 468

CO 2 (kt) 5,420 5,117 5,749 5,959 6,126 5,855 5,842 5,723 5,477 5,448 5,392 5,403 5,204 4,970

CH 4 (kt CO 2

eq.) 29 32 33 33 33 32 32 32 31 31 30 30 29 29

N 2 O (kt CO

2 eq.) 39 32 33 33 33 32 32 32 31 31 30 30 29 29

Source: ISPRA elaborations

Table 3. 24 Marine fuel consumptions in domestic and international travels (kt) and GHG emissions from
domestic navigation (kt CO 2 eq.)



### 3.6.4.4 Source

- specific QA/QC and verification

Basic data to estimate emissions have been reconstructed starting from informatio n on ship movements and fleet composition coming from different sources. Data collected in the framework of the national study from the local port authorities, (TECHNE, 2009), have been compared with the official statistics supplied by ISTAT, and communica ted at international level to EUROSTAT, which are collected by ISTAT from maritime operators with a yearly survey. Differences and problems have been analysed in details and solved together with the ISTAT expert.

Besides, time series resulting from the recalculation have been presented to the national experts in the framework of an ad hoc working group on air emissions inventories. The group is chaired by ISPRA and includes participants from the local authorities responsible for the preparation of local inventories, sectoral experts, the Ministry of Environment, Land and Sea, and air quality model
experts. Top

- down and bottom

- up approaches have been compared with the aim to identify the potential problems and future improvements to be addressed.

3.6.4.5 Source

- specific recalculations

There has been an overall recalculation of emissions from the sector due to the update of the methodological study completed in 2009 referring to the years 2004

- 2006. In fact, in previous submissions, constant parameters we re applied for the all time series considering model results of the year 199 7 . The time series did not take into account most recent trends in maritime activities in terms of technological improvements, fleet composition and relevant fuel consumption, and operational times especially hotelling and manoeuvring in harbour activities.

### 77

As specified in the last review reports (UNFCCC, 2006; UNFCC, 2009), the ERT recommended to update these results in view of recent available national research to improve the acc uracy of the inventory and correct the potential overestimation for recent years. Aim of the revision was, principally, to revise the consumption values and relative parameters which are very important for local air quality, in terms of pollutants such as NO X 

### , NMVOC, CO, PM, and consequently greenhouse gases. In fact, the revision of the methodology resulted mainly in a reduction of domestic fuel consumptions for the last years, due, for cruise activities, to a different ship type distribution in domestic routes with an average gross tonnage lower than the previous years and, for in port activities, a reduction of the average hotelling and manoeuvring times. Average fuel consumption reduced in harbour from 1.54 t, calculated in the previous research study, to 1.32 t by ship and in domestic cruise from 1.73 t to 1.40 t by ship. From 1998 to 2004, values have been reconstructed by an interpolation method. Minor recalculations regarded an update of domestic ferryboat movements for 1991, 1992 and 1994 and gasoli ne emission factor for recreational crafts from 1990 to 1999.

The recalculation affected only slightly the time series up to 1997 (from +0.4% to +1.5%) but consistently the estimations from 1998 to 2006, with differences ranging from

- 1.4% to

- 14.7%,

with respect to earlier submissions. The revision of model assumptions has lead to a recalculation of international bunkers, accordingly.

3.6.4.6 Source

- specific planned improvements

Further improvements will regard a verification of activity data on ship m ovements for the last two years. In fact, origin destination data supplied by ISTAT do not match with the statistics supplied by the same Institute at international level to EUROSTAT. Besides EUROSTAT figures seems for 2006 and 2007 to be clearly underesti mated.

3.7 Other sectors

The estimation procedure follows that of the base combustion data sheet, emissions are estimated from the energy consumption data and the emission factor illustrated in Table 3.7. The category ‘Other sectors’ comprises emissions from agriculture, fisheries, residential, commercial and others. The national energy balance (see Annex 5, Tables A5.9 and A5.10, in physical units, row “DOMESTIC AND COMMERCIAL USES”, subtracting the quantities for military use in diesel oil and off

- road uses in petrol) does separate energy consumption between civil and agriculture

- fisheries, but it does not distinguish between Commercial

–Institutional and Residential. The total consumption of each fuel is subdivided on the basis of the estimations

repor ted by ENEA in its annual energy report (ENEA, several years). Emissions from 1A.4b Residential and 1A.4c Agriculture/Forestry/Fishing are disaggregated into those arising from stationary combustion and those from off

- road vehicles and other machinery.

Th e estimation of emissions from off

- road sources is discussed in paragraph 3.7.2. Emissions from fishing vessels are estimated from fuel consumption data (MSE, several years [a]) and emission

factors are shown in Table 3.7.

3.7.1 Other combustion

Emission s from military aircraft and naval vessels are reported under 1A.5b Mobile. The method of estimation is discussed in paragraphs 3.6.1 and 3.6.4.

Emissions from off

- road sources are estimated and they are reported under the relevant sectors, i.e.

Other In dustry, Residential, Agriculture and Other Transport. The methodology of these estimates is discussed in paragraph 3.7.2.

### 78

3.7.2 Other off

- road sources

This category covers emissions from a range of portable or mobile equipment powered by reciprocating di

esel or petrol driven engines. They include agricultural equipment such as tractors and combined harvesters; construction equipment such as bulldozers and excavators; domestic lawn mowers; aircraft support equipment; and industrial machines such as portabl e generators and compressors. In the CORINAIR inventory they are grouped into four main categories
(EMEP/CORINAIR, 2007):

• domestic house & garden

• agricultural power units (includes forestry)

• industrial off

- road (includes construction and quarrying)

• aircra ft support.

Those categories are mapped to the appropriate IPCC classes: Aircraft support is mapped to Other Transport and the other categories map to the off

- road vehicle subcategories of Residential, Agriculture and Manufacturing Industries and Constr uction. Estimates are calculated using a modification of the methodology given in EMEP/CORINAIR (EMEP/CORINAIR, 2007). This involves the estimation of emissions from around seventy classes

of off

- road source using the following equation for each class:

Ej = Nj

· Hj

· Pj · Lj

· Wj

· (1 + Yj

· aj /2) · ej

where Ej = Emission of pollutant from class j (kg/y) Nj = Population of class j Hj = Annual usage of class j (hours/year) Pj = Average power rating of class j (kW) Lj = Load factor of class j (-) Yj = Lifetime of class j (years) Wj = Engine design factor of class j (-) aj = Age factor of class j (y

- 1 ) ej = Emission factor of class j (kg/kWh)

For gasoline engined sources, evaporative NMVOC emissions are also estimated as:

Evj = Nj · Hj · evj

where Evj = Evaporative emission from class j kg evj = Evaporative emission factor for class j kg/h

Population data have been revised based on a survey of machinery sales (Frustaci, 1999). Machinery lifetime is estimated on the European averages, see EMEP/CORINAIR (EMEP/CORINAIR, 2007), the annual usage data were taken either from industry or published data (EEA, 2000). The emission factors used came mostly from EMEP/CORINAIR and from Samaras
(EEA, 2000). The load factors were taken from Samaras (EEA, 2000). It was possible to calculate fuel consumptions for each class based on fuel consumption factors given in EMEP/CORINAIR (EMEP/CORINAIR, 2007). Comparison with known fuel consumption

### 79

for certain groups of classes (e.g. a griculture and construction) suggested that the population method overestimated fuel consumption by factors of 2

- 3, especially for industrial vehicles.

Estimates were derived for fuel consumptions for the years 1990

- 2007 for each of the main categories:

A. Agricultural power units: Data on gas oil consumption were taken from ENEA (ENEA, several years). The consumption of gasoline was estimated using the population method for

1995 without correction. Time series is reconstructed in relation to the fuel u sed in agriculture.

B. Industrial off

- road: The construction component of the gas oil consumption was calculated from the Ministry of Production Activities data (MSE, several years [a]) on buildings and constructions. The industrial component of gas oil wa s estimated from the population approach for 1995. Time series is reconstructed in relation to the fuel use in industry.

C. Domestic house & garden: gasoline and diesel oil consumption were estimated from the EMEP/CORINAIR population approach for 1995. Tim e series is reconstructed in relation to the fuel use in agriculture.

Emissions from off

- road sources are particularly uncertain. The revisions in the population data produced higher fuel consumption estimates. The gasoline consumption increased markedly b ut is still only a tiny proportion of total gasoline sales.

3.8 International Bunkers

The methodology used to estimate the quantity of fuels used from international bunkers in aviation and maritime navigation has been illustrated in the relevant trans port paragraphs, 3.6.1 and 3.6.4. The methodology implements the IPCC guidelines according to the available statistical data.

3.9 Feedstock and non

- energy use of fuels

In Table 3.25 and 3.26 detailed data on petrochemical and other non

- energy use for

the year 2007 are given. Data are based on a detailed yearly report available by Ministry of Economic development (MSE, several years [b]). The report summarizes answers from a detailed questionnaire that all operators in Italy prepare monthly. The data a re more detailed than those normally available by international

statistics and refer to:

- input to plants (gross input);

- quantities of fuels returned to the market (with possibility to estimate the net input);

- fuels used internally for combustion;

- quantitie s stored in products. In the national energy balances, only the input and output quantities from the petrochemical plants are reported, so the output quantity could be greater than the input quantity, due to internal transformation. Therefore it is possib le to have negative values for some products mainly gasoline, refinery gas, fuel oil. The quantities of fuels stored in products, in percentage on net and gross petrochemical input, are estimated with these data, see Table 3.26 for details by product and T able 3.25 for the overall figure. As can be seen from the value reported for the year 2007 there is a sizeable difference of the estimated quantities of fuel stored in product if reference is made to “net” or “gross” input. Moreover the estimation of quant ities stored in product are quite different from those reported in the
Revised 1996 IPCC Guidelines for National GHG Inventories, Reference Manual, ch1, tables 1

- 5 (IPCC, 1997).

### 80

An attempt was made to estimate the quantities stored in products using IPCC percentage values as reported in table 1

- 5 and the fuels reported as “petrochemical input” in Table 3.26. The resulting estimate of about 6,889 kt of products for the year 2007, is more than 50% bigger than the quantities reported, 4,752, see Table 3.25.

A t national level, this methodology seems the most precise according to the available data. The European Project “Non Energy use

- CO 2 

### emissions” ENV4

- CT98

- 0776 has analysed our methodology performing a mass balance between input fuels and output products in a sample year. The results of the project confirm the reliability of the reported data (Patel and Tosato, 1997).
With reference to the data of Table 3.27, those non

- energy products are mainly outputs of refineries. The estimate refers to quantities produce d that are reported by manufacturers and summarized by BEN. The data should not be controversial. Minor differences in the overall energy content of those products do occur if the calculation is based on national data or IPCC default values.

Petroch. Input Returns to

refin./market Internal

consumption /

losses Quantity stored in

products

ALL ENERGY CARRIERS, kt 10,685 3,162 2,771 4,752

% of total input 29.6% 25.9% 44.5%
% of net input 36.8% 63.2% BREAKDOWN OF TOTAL PETROCHEMICAL FLOW

Table 3.25 Other non energy uses, year 2007

FUEL TYPE Petroch.
Input Returns to

refinery/

market Internal

consumption /

losses Quantity stored

in products % on gross

input % on net

input Emission

factor

(IPCC)

kt kt kt kt t C / t

LPG 575 568 276 -269 0.8137 Refinery gas 262 103 961 -802 0.8549
Virgin naphtha 5,862 0 0 5,862 0.8703

Gasoline 1,114 1,702 0 -588 0.8467

Kerosene 537 371 0 166 0.8485

Gas oil 591 142 0 449 0.8569

Fuel oil 619 205 455 -41 0.8678

Petroleum coke 0 0 0 0 0.955
Others (feedstock) 124 71 78 -25 0.8368

Losses 0 0 0.8368
Natural gas 1,001 0 1,001 0 0.727

total 10,685 3,162 2,771 4,752 44% 63% Table 3.26 Petrochemical, detailed data from MSE, year 2007 (MSE, detailed petrochemical breakdown)

NON ENERGY FROM REFINERIES 

### Quantity

stored in

products Energy

content

IPCC '96 Emission

factor Total energy

content, IPCC

values

kt t C / t TJ

Bitumen + tar 3,951 40.19 0.8841 158.8

lubricants 1,252 40.19 0.8038 50.3

recovered lubricant oils 179 40.19 0.8038 7.2
paraffin 79 40.19 0.8368 3.2
others (benzene, others) 664 40.19 0.8368 26.7

Totals 6,125 246.1
Table 3.27 Other non energy uses, year 2007, MSE several years [a]

### 81

3.10 Country specific issues

3.10.1 Nation

al energy balance

Italian energy statistics are based mainly on BEN, National Energy Balance, which is annually edited by MSE. The report is quite reliable, by international standards, and it may be useful to

summarize its main features:

- it is a balance, every year professional people carry out the exercise balancing final consumption data with import

- export information;

- the balance is made on the energy value of energy carriers, taking into account transformations that may occur in the energy industries ( refineries, coke plants, electricity production);

- data are collected regularly by the Ministry of Economic Development, on a monthly basis, from industrial subjects;

- oil products, natural gas and electricity used by industry, civil or transport sectors are taxed with excise duties linked to the physical quantities of the energy carriers; those excise duties are differentiated between products and between final consumption sectors (i.e. diesel oil for industrial use pays duties lower than for transportation use and higher than for electricity production; even bunker fuels have a specific registration paper that state that they are sold
without excise duties;

- from the point of view of energy consumption information this system produces highly

reliable data: BE N is always based on registered quantities of energy consumption, not on estimates; uncertainties may be present in the effective final destination of the product but total quantities are reliable;

- coal is an exception to this rule, it is not subject to ex cise duties; consumption information are estimates; anyway it is nearly all imported and it is used by a limited number of operators; all of them are monitored on a monthly basis by the Ministry of Economic Development.

3.10.2 National emission factors

Monitoring of the carbon content of the fuels used nationally is an ongoing activity at ISPRA. The principle is to analyse regularly the chemical composition of the used fuel or relevant activity
statistics, to estimate the carbon content and the emission factor. National emission factors are reported in Tables 3.7 and 3.17.

The specific procedure followed for each primary fuel (natural gas, oil, coal) is reported in Annex 6.

3.11 Fugitive emissions from solid fuels, oil and natural gas

Fugitive emissi

ons in this source category originate from the production and transformation of solid fuels, the production of oil and gas, the transmission and distribution of gas and from oil refining. Trends in fugitive emissions are summarised in Table 3.28.

Totally , fugitive emissions, in CO 2 

### equivalent, account for 1.6% out of the total emissions in the energy sector. Both CH 4 

### and CO 2 

### emissions show a reduction from 1990 to 2007 by 32% and 35%, respectively.

### 82 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO 2

Oil and natural gas 3,341 3,174 2

, 585 2

, 440 2

, 261 2

, 834 2

, 152 2

, 112 2

, 189 2

, 176

CH 4

Solid fuels 122 65 73 81 78 95 64 69 54 84

Oil and
natural gas 7

, 298 6

, 817 6

, 351 5

, 988 5

, 964 5

, 802 5

, 650 5

, 654 5

, 139 4

, 987

N 2 O

Oil and natural gas 1. 2 1

. 3 1. 1 1. 0 1. 3 1. 3 1. 3 1

. 5 1

. 4 1

. 4

Table 3.28 Fugitive emissions from oil and gas 1990

- 2007 (Gg CO 2 eq.)



### The decrease of CO 2 

### fugitive emissions is driven by the reduction in crude oil losses in refineries.

Emissions are balanced with th e amount of crude oil losses reported in the national Energy Balance (MSE, several years [a]).

The trend of CH

4 

### fugitive emissions from solid fuels is related to the extraction of coal and lignite that in Italy is quite low while the decrease of CH 4 

### fugit ive emissions from oil and natural gas is due to the reduction of losses for gas transportation and distribution, and to the gradual replacement of old pipelines. The results of key category analysis are shown in the following box.

Key

- category identific ation in the fugitive sector with the IPCC Tier1 and Tier2 approaches (without LULUCF)



### 1B2 CH

4 

### Fugitive emissions from oil and gas operations Key (L, T)

1B2 CO 2 

### Fugitive emissions from oil and gas operations Key (L2, T)

Specifically, methane emissions fro m oil and gas operations are a key category source according to the level and trend assessment with both Tier 1 and Tier 2 approaches, either including or excluding

LULUCF emission

s and removals. CO 2 

### emissions from oil and gas operations are a key category for trend assessment, with both Tier 1 and Tier 2 approaches, and level assessment with Tier 2 without LULUCF; these emissions are a key category only for trend assessment with Tier 1 when including LULUCF. Both categories are also key categories for the year 1990, either including or excluding LULUCF emission s and removals. The uncertainty in CH 4 

### , N 2 

### O and CO 2 

### emissions from oil and gas operations is estimated to be 25% as a combination of 3% and 25% for activity data and emission factors, respectively.

Fu gitive emissions from solid fuels, reported in 1.B.1, are not relevant. In fact, CH 4 

### emissions from coal mining refer to only two mines with very low production in the last ten years, one of which is underground and produces coal and the other, on the surf ace, produces lignite. The surface mine stopped the activity in 2001. CH 4 

### emissions from solid fuel transformation refer to the coke production in the iron and steel industry, which is also decreasing in the last years.

CH 4 

### emissions from coal mining have been estimated on the basis of activity data published on the National Energy Balance (MSE, several years [a]) and emission factors provided by the IPCC guidelines (IPCC, 1997). CH 4 

### emissions from coke production have been estimated on the basis of

activi ty data published in the national statistical yearbooks (ISTAT, several years) and emission factors reported in the EMEP/CORINAIR Guidebook (EMEP/CORINAIR, 2005). CO 2 

### and N 2 

### O emissions from 1.B.1 are not occurring. The uncertainty in methane emissions from coal mining and handling is estimated to be 200% as combination of 3% and 200% for activity data and emission factors, respectively.

### 83

Fugitive CO 2 

### emissions reported in 1.B.2 refer to fugitive emissions in refineries during petroleum production processes, e.g. fluid catalytic cracking and flaring, and emissions from the production of oil and natural gas. Emissions in refineries have been estimated on the basis of activity data published in the National Energy Balance (MSE, several years [a]) or supplied by industry (UP, several years) and operators especially in the framework of the European emissions trading scheme. Emissions occurring in production of oil and gas have been calculated on the basis of activity data published in the National Energy Balance (M SE, several years [a]), data published by industry (UP, several years) and data supplied by operators and emission factors published on the IPCC Good
Practice Guidance (IPCC, 2000).

CH 4 

### emissions reported in 1.B.2 refer mainly to the production of oil and natural gas and to the transmission in pipelines and distribution of natural gas. CH 4 

### emissions from the production of oil and natural gas have been calculated on the basis of activity data published in the National Energy Balance (MSE, several years [a]) and by industry (UP, several years), and emission factors published on the IPCC Good practice Guidance (IPCC, 2000). CH 4 

### emissions from the transmission in pipelines and distribution of natural gas have been estimated on the basis of activity data publish ed by industry and competent national authority and information collected annually by the Italian gas operators. More in details, emission estimates take into account the information regarding the amount of natural gas distributed (ENI, several years [a]), length of pipelines distinct by low, medium and high pressure and by type, iron, grey iron, steel or polyethylene pipelines (AEEG, several years), natural gas losses reported in the national energy balance (MSE, several years [a]) and methane emissions re ported by operators in their environmental reports (ENI, several years [b]; EDISON, several years); estimates include emissions emitted in the different phases of distribution and transmission of gas including losses in pumping stations and in reducing pre ssure stations. Emissions are verified considering emission factors reported in literature and detailed information supplied by the main operators (ENI, several years [b]; Riva, 1997). More details on the methodology used and on the basic information colle cted from operators are reported in a technical paper (Contaldi, 1999).

In response to the review process of the Initial Report under the Kyoto Protocol and of the 2006
submission under the Convention, N 2 

### O emissions from flaring in oil and gas production have been estimated on the basis of activity production data and emission factors reported in the IPCC GPG (IPCC, 2000). They amount, for the whole time series, for less than 1 kilotons of CO 2 

### equivalent.

In the submission 2009, CH 4 

### emissions from the tr ansmission in pipelines and distribution of natural gas have been recalculated from 2004 because of more detailed information was available on the amount of imported gases from Lybia and Algeria and emission factors from minor distributors of gas in urban areas have been updated. This resulted in an increase of CH 4 

### emission equal to 0.5% and 3.4% in 2004 and 2005, respectively, and a reduction of 0.9% in 2006. Moreover

CH 4 

### emissions from the production of oil from 2005 were updated on the basis of new activ ity data.

This recalculation resulted in an increase of emissions of 0.01% in 2005 and 0.2% in 2006.

For the completeness of the CRF tables pertaining to these emissions, in particular 1.B.2, the rationale beyond the values reported and not reported is ex plained below.

CO 2 

### and CH

4 

### fugitive emissions from oil exploration are included in those from production because

no detailed information is available. N 2 

### O emissions from flaring in oil exploration and in refining activities are reported under oil flaring. Emissions from transport and distribution of oil result as not occurring. CO 2 

### and CH 4 

### emissions from gas exploration are also included in those from production

while CH

4 

### emissions from other leakage are included in distribution emission estimates. Further investigation will be carried out with industry about these figures.

### 84

CO 2 

### and CH

4 

### emissions from venting are included in production, respectively for oil under 1.B.2.a and natural gas under 1.B.2.b, as not separately supplied by the relevant industries.

CO 2 

### and CH

4 

### emissions from gas flaring are also included in production under 1.B.2.b. A summary of the completeness of CO 2, 

### CH 4 

### and N 2 

### O fugitive emissions is shown in the following

Table 3.29.

1.B. 2.a. Oil i. Exploration 

### CO 2, 

### CH 4 

### Included in 1.B.2.a pr oduction
i. Exploration 

### N 2 

### O Included in 1.B.2.c oil flaring
iv. Refining 

### N 2 

### O Included in 1.B.2.c oil flaring

1.B.2.b. Natural Gas i. Exploration 

### CO 2, 

### CH 4 

### Included in 1.B.2.b production iii. Other leakage CH 4 

### Included in 1.B.2.b distribution

1.B. 2.c . Venting and flaring

i. Oil 

### CO 2, 

### CH 4 

### Included in 1.B.2.a production

ii. Gas 

### CO 2, 

### CH 4 

### Included in 1.B.2.b production

Table 3.29 Completeness of CO 2 CH 4 and N

2 O fugitive emissions

### 85



## Chapter 4: INDUSTRIAL PROCESSES [CRF sector 2]

4.1 Overview of sect or

Included in this category are by

- products or fugitive emissions, which originate from industrial processes. Where emissions are released simultaneously from the production process and from combustion, as in the cement industry, these are estimated sepa rately and included in category 1A2. All greenhouse gases as well as CO, NO

x 

### , NMVOC and SO 2 

### emissions are estimated. In 2007 industrial processes account for 5.7% of CO 2 

### emissions, 0.2% of CH 4 

### , 5.9% of N 2 

### O, 100%
of PFCs, HFCs and SF 6 

### . In term of CO 2 

### equiva lent, industrial processes share 6.6% of total national greenhouse gas emissions. The trends of greenhouse gas emissions from the industrial processes sector are summarised in Table 4.1. Emissions are reported in Gg for CO 2 

### , CH 4 

### and N

2 

### O and in Gg of CO 2 

### eq uivalent for F

gases. An increase in HFC emissions is observed from 1990 to 2007, while CO 2 

### emissions from chemical and metal industry reduced sharply.

GAS/SUBSOURCE 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO 2 (Gg)

2A. Mineral Produ cts 21,100 20,768 21,266 22,096 22,089 22,986 23,553 23,131 23,219 23,678 2B. Chemical Industry 2,199 1,230 1,062 1,034 1,082 1,243 1,328 1,317 1,308 1,311

2C. Metal Production 3,892 3,417 1,769 1,729 1,648 1,627 1,772 2,009 2,032 1,935

CH 4 (Gg) 2B. Chemical Industry 2.45 2.65 0.40 0.33 0.33 0.31 0.33 0.33 0.32 0.34

2C. Metal Production 2.71 2.71 2.61 2.50 2.38 2.46 2.58 2.72 2.81 2.75

N 2 O (Gg)

2B. Chemical Industry 21.54 23.35 25.54 26.55 25.49 24.38 27.24 25 .03 8.54 6.10

HFCs (Gg CO 2 eq.) 351 671 1,986 2,550 3,100 3,796 4,515 5,267 5,956 6,700

PFCs (Gg CO 2 eq.) 1,808 491 346 451 424 498 348 353 282 288

SF 6 (Gg CO 2 eq.) 333 601 493 795 740 468 502 465 406 428
Table 4.1 Trend in greenhouse gas emissions fro m the industrial process sector, 1990

- 2007 (Gg)



### Seven key categories have been identified for this sector, for level and trend assessment, using both the Tier 1 and Tier 2 approaches. The results are reported in the following box.

Key

- category identifica tion in the industrial processes sector with the IPCC Tier1 and Tier2 approaches

2F HFC, PFC Emissions from substitutes for ODS Key (L, T)

2A CO 2 Emissions from cement production Key (L, T2)

2B N 2 O Emissions from adipic acid Key (T)

2A CO 2 Emissions from limestone and dolomite use Key (L1)

2C CO 2 Emissions from iron and steel production Key (T1)

2B CO 2 Emissions from ammonia production Key (T1)

2C PFC Emissions from aluminium production Key (T1)



### CO 2 

### emissions from cement and limestone and dolomite use ar e included in category 2A; N 2 

### O emissions from adipic acid and CO 2 

### emissions from ammonia refer both to 2B; PFCs from aluminium production are included in 2C as CO 2 

### emissions from iron and steel production. Methane emissions from the sector are not a key so urce. All these categories, except CO 2 

### emissions from limestone and dolomite use and ammonia, are also key category sources including the LULUCF estimates in the key category assessment.

In addition CO 2 

### emissions from limestone and dolomite use is a key c ategory in the base year at level assessment with the Tier 1 approach including LULUCF and N 2 

### O emissions from nitric acid is a key category in the base year at level assessment with the Tier 1 approach excluding LULUCF.

### 86

4.2 Mineral Products (2A)

4.2.1 So urce category description

In this sector CO 2 

### emissions from the following processes are estimated and reported: cement production, lime production, limestone and dolomite use, soda ash production. Asphalt roofing and road paving with asphalt activities co ntributes are also included in this sector but they contribute only with NMVOC emissions; CO 2 

### emissions from decarbonising in glass production have been estimated and reported in “Other”.

Cement Cement production (2A1) is the main source of CO 2 

### emissions in this sector. As already mentioned, it is a key source both at level (with both the Tier 1 and Tier 2 approaches) and trend assessment (with the Tier 2 approach) and accounts for 3.77% of the total national emissions. During the last 15 years in Italy ch anges in cement production sector have occurred which have led to a more stable structure. The oldest plants were closed, wet processes were abandoned in favour of dry processes so as to improve the implementation of more modern and efficient technologies. There are 29 companies (90 plants of which: 60 full cycle and 30 grinding plants) currently operating in this sector: multinational companies and small and medium size enterprises (operating at national or only at local level) are present in the country. As for the localization of the operating plants: 47% is in northern Italy, 18% is in the central regions of the country and 35% is in the southern regions and in the islands. There are 80 active sintering rotary kilns which belong to the “dry” or of “semid ry” types. The larger size cement plants (i.e. with cement production capacity > 1 Mt/y) have been contributing with about 36% of the national cement production. In Italy different types of cement are produced, as for 2007 AITEC, the national cement associ ation, has characterised the national production as follows : 76% is CEM II (Portland composite cement); 12% is CEM IV (pozzolanic cement); 6.9% is CEM I (ordinary Portland Cement) and 4.3% is CEM III (blastfurnace cement).

Lime

CO 2 

### emissions occur also f rom processes where lime is produced and account for 0.51% of the total

national emissions. Lime production can also occur

, b eside lime industry, in different industrial sectors such as iron and steel making, pulp and paper production, soda ash production, sugar production and lime can also be used in a number of processes concerning wastewater treatment, agriculture and the neutralization of acidic emissions in the industrial flue gases. In particular the other relevant lime productions accounted for in It aly are those occurring in the iron and steel making process and in the sugar production process. Lime is basically produced by calcination of limestone (calcium carbonate) or dolomite (calcium/magnesium carbonate) at 900 °C. The process leads to quicklime and CO 2 

### emissions according to the following reaction:

CaCO 3 

### + MgCO

3 

### + heat ‡ CaO +MgO+2CO 2 

### CO 2 

### is released because of the process reaction itself and also because of combustion to provide energy to the process. CaO and MgO are called quicklime. Quicklime together with water give another product of the lime industry which is called calcium hydroxide Ca(OH) 2



### . CO 2 

### emissions estimation is related to lime production in mineral industry and it includes also the production of lime in iron and steel making facilit ies and lime production in sugar mills. The number of lime producing facilities has been relevantly changing through the years: 85 operating plants in 1990, 46 plants in 2003, 35 plants in 2007 (this figure is based on the European emission trading scheme data): 46% is in the southern regions and in the islands, 39% is in the northern regions and 15% in the central regions. The number of operating kilns has also decreased significantly through the years (about 171 in 1990, 75 in 2003). During the ‘90s lime industry

### 87

invested in technology implementation to replace the old kilns with regenerative and high efficiency kilns, rotary kilns are no longer used . As for fuel consumptions, 80% of the Italian lime industry uses natural gas, 20% uses coke.

Limestone an d dolomite use (brick and tiles; fine ceramics)

CO 2 

### emissions are also related to the use of limestone and dolomite in different industrial processes, they account for 0.53% of the total national emissions . Limestone or dolomite can be added in

different s

teps of the production process so as to obtain the desired product features (i.e. colour, porosity). Sometimes carbonates in limestone and dolomite may have to be calcined (“dead burned”) in order to be added to the manufacturing process . Limestone and dol omite are also used in paper production process. CO 2 

### emissions from limestone and dolomite use is a key source at level assessment with the Tier 1 approach.

Glass production Glass industry in Italy can be characterised with regard to four glass product t ypes: flat glass; container glass, borosilicate and lead/crystal glass. Flat glass is produced in facilities mainly located in the North; container glass is produced in facilities located all over the country; glass fibres and wool are produced in the Nort h. About 80 companies carry out activities related to glass industry in Italy, 30 companies carry out glass production processes in about 54 production units. With regard to glass chemical composition, the Italian glass production consists of 95% soda

- lime glass; 4% borosilicate glass and 1% lead/crystal glass. The main steps of the production process in glass industry are the following:

• raw materials storage and batch formulation;

• melting of the formulated batch at temperature ranging from 1400 °C to 1600 °C, in different furnaces according to the type of glass product;

• forming into glass products at specific temperature ranges;

• annealing of glass products to prevent weak glass due to stress; The formulated batch is generally melted in continuous furnaces, whose size and features are related to the types of glass production. In Italy 80% of the glass industry production is carried out using natural gas as fuel, other fossil fuels consumption is limited to low sulphur content oil.

Emissions to air are release d basically by the high temperature melting step and depend on the type of glass product, raw materials and furnaces involved in the production process. Main pollutants
are: dust, NO

x 

### , SO

x 

### , CO 2 

### ; occasionally and depending on the specific production process heavy metals, fluorides and chlorides gases could be released. CO 2 

### emissions are mainly related to the decarbonisation of carbonates used in the process (soda ash, limestone, dolomite) during the melting phase.

Soda Ash production and use

In I taly there is only one facility which operates soda ash production via Solvay process. Solvay process allows producing soda ash through the conversion of sodium chloride in to sodium carbonate using calcium carbonate and ammonia. CO 2 

### is released to air and calcium ch loride waste. Up to the second half of year 2000 in the unit for the production of peroxidates there was one sodium carbonate line and a sodium perborate line which was then converted to sodium carbonate production. Soda ash is also used in glass productio n processes.

4.2.2. Methodological issues

IPCC Guidelines and Good Practice Guidance are used to estimate emissions from this sector (IPCC, 1997; IPCC, 2000). Activity data are supplied in the national statistical yearbooks (ISTAT, several years) and by industries. Emission factors are those provided by the IPCC Guidelines (IPCC, 1997; IPCC, 2000),

### 88

by the EMEP/CORINAIR guidebook (EMEP/CORINAIR, 2007) or by other international
Guidebooks (USEPA, 1997).

Cement

CO 2 

### emissions from cement production are esti mated by the IPCC Tier 2 approach. Activity data comprise data on clinker production provided by ISTAT (ISTAT, several years). Emission factors are estimated on the basis of information provided by the Italian Cement Association (AITEC, several years) and by cement facilities in the framework of the European pollutant emission register (EPER, now E

- PRTR) and the European emission trading scheme. In this latter context, all cement production plants reported fuel consumption and emissions, split between combu stion process and decarbonising process. For the years from 1990 up to 2003 the resulting emission factor for cement production was equal to 540 kg CO 2 

### /ton clinker, based on the average CaO content in the clinker and taking into account the contribute of c arbonates and additives. This value was suggested to the operators by AITEC (AITEC, 2004) on the basis of a tool provided by the World Business Council for Sustainable Development and available on website at the following address http://www.ghgprotocol.org/standard/tools.htm

. From 2004, emission factors were based on the data reported under the frame of the EPER/EPRTR and of the European Emission Trading scheme and resulted in the following valu es: 532 kg CO 2 

### /ton clinker in 2004, 525 kg CO 2 

### /ton clinker in 2005, 526 kg CO 2 

### /ton clinker in 2006 and 531 kg

CO 2 

### /ton clinker in 2007

, based on the average CaO content in the clinker and taking into account

the contribute of carbonates and additives.

Lime

CO 2 

### emissions from lime have been estimated on the basis of production activity data supplied by ISTAT (ISTAT, several years) adding the amount of lime produced and used in the sugar and iron and steel production sectors; emission factors have been estima ted on the basis of detailed information supplied by plants in the framework of the European emission trading scheme and
checked with the industrial association (CAGEMA, 2005). The resulting values, in the last years, for the implied emission factor were 7 06 kg CO 2 

### /ton lime production in 2005; 694 kg CO 2 

### /ton lime production in 2006 and 707 kg CO 2 

### /ton lime production in 2007.

Limestone and dolomite

CO 2 

### emissions from limestone and dolomite use are related to the use of limestone and dolomite in
bricks, tile s and ceramic and paper production. In the CRF the total amount of limestone and dolomite used in these processes is reported as activity data and it has been estimated on the basis of the average content of CaCO 3 

### in the different products. Detailed produc tion activity data and

emission factors have been supplied in the framework of the European emissions trading scheme and relevant data are annually provided by the Italian bricks and tiles industrial association and by

the Italian ceramic industrial associ ations ( ANDIL, 2000; ANDIL, several years; ASSOPIASTRELLE, several years ; ASSOPIASTRELLE , 2004 ).

Soda ash

CO 2 

### emissions from soda ash production have been estimated on account of information available on the Solvay process (Solvay, 2003), whereas those fr om soda ash use are included in glass production.

Glass

CO 2 

### emissions from glass production have been estimated by production activity data (ISTAT, several years) and emission factors estimated on the basis of information supplied by plants in the

framew ork of the European emissions trading scheme.

### 89

Asphalt roofing and road paving NMVOC emissions from asphalt roofing and road paving have been estimated by production activity data (ISTAT, 1990

- 95; Federchimica and SITEB, since 1996) and default emission fac tors (EMEP/CORINAIR, 2007).

4.2.3. Uncertainty and time

- series consistency

The uncertainty in CO 2 

### emissions from cement, lime, limestone and dolomite use and glass production is estimated to be equal to 10.4% from each activity, as a combination of 3% an d 10% for activity data and emission factor, respectively. Official statistics of activity data for these categories are quite reliable when compared to the activity data reported by facilities under different data collections, thus leading to the consider ed uncertainty level for the activity data. The uncertainty level for emission factors is equal to the maximum level reported in the IPCC Good Practice Guidance (IPCC, 2000) for the cement production; this is a conservative estimation because the range of values of the emission factors of the Italian cement plants would lead to a lower uncertainty level. In Tables 4.2 and 4.3, the production of mineral products and CO 2 

### emission trend is reported.

ACTIVITY DATA 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Cement production (decarbonizing) 29,786 28,778 29,816 30,893 30,770 32,077 33,049 33,122 33,210 33,742

Glass (decarbonizing) 3,779 4,259 4,930 5,014 4,811 5,141 5,178 5,328 5,327 5,385

Lime (decarbonizing) 2,583 2,873 2,760 2,958 2,951 3,174 3,357 3,344 3,496 3,444

Limestone and dolomite use 5,397 4,907 4,843 5,014 5,240 5,359 5,714 5,792 5,747 5,712

Soda ash production and use 610 1,070 1,000 1,000 918 847 870 915 883 874

Table 4.2 Production of mineral products, 1990

– 2007 (kt)

CO 2 EMISSIONS 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Cement production (decarbonizing) 16,084 15,540 16,101 16,682 16,616 17,322 17,575 17,403 17,474 17,914

Glass (decarbonizing) 416 468 549 549 521 524 528 543 543 549

Lime (decarbonizing) 2,042 2,279 2,18 5 2,358 2,365 2,540 2,679 2,361 2,426 2,434

Limestone and dolomite use 2,375 2,159 2,131 2,206 2,306 2,358 2,514 2,548 2,529 2,513

Soda ash production and use 183 321 300 300 281 242 258 275 247 268

Table 4.3 CO 2 emissions from mineral products, 1990

– 2007 (Gg)



### Emission trends are related to the production, which are increasing, in the last years, for cement and glass and decreasing for fine ceramics.

4.2.4. Source

- specific QA/QC and verification

CO 2 

### emissions have been checked with the relevant indu strial associations. Both activity data and average emission factors are also compared every year with data reported in

the national EPER/E

- PRTR registry and in the European emissions trading scheme.

4.2.5. Source

- specific recalculations

Recalculations h

ave been done as CO 2 

### emission factors for cement and lime industries (2004

- 2006) have been changed on account of the complete information availability from emissions trading

scheme

. Consequently, a s for CO 2 

### emissions, recalculations for cement industries r esult in

- 1.52%,

- 2.70% and

- 2.56% respectively for 2004, 2005 and 2006; recalculations for lime industries result in

- 0.25 %

, - 11.56% and

- 13.20% respectively for 2004, 2005 and 2006.

### 90

4.2.6. Source

- specific planned improvements

No further improvements ar e planned.

4.3 Chemical industry (2B)

4.3.1 Source category description

CO 2 

### , CH

4 

### and N 2 

### O emissions from chemical productions are estimated and included in this sector.
In this submission, CO 2 

### emissions from calcium carbide production are also estimated and reported for the years 1990

- 1995 where production and emissions occurred.

Adipic acid Adipic acid production is a multistep process which starts with the oxidation of cyclohexanol using nitric acid and Cu catalysts according to the following reaction :

C 6 

### H 11 

### OH+2HNO

3 

### ‡ HOOC(CH

2 

### ) 4 

### COOH+N

2 

### O+2H

2 

### O+energy Adipic acid is then used to produce nylon or is fed to other production processes. Together with adipic acid, N 2 

### O is produced and CO 2 

### is one of the by

- products (Radici Chimica, 1993)

. Emissions data from adip ic acid production are provided and referenced by one plant, which is the sole producer in Italy

(Radici Chimica, several years). Specifically, for N 2 

### O, adipic acid is a key source at trend assessment, both with the Tier 1 and Tier 2 approach. These emissi ons accounted for

16.0% of total N

2 

### O emissions in 2005 and 2.45% in 2007 because the technology to reduce N 2 

### O emissions started to be fully operative at the existing producing facility.

N 2 

### O emissions have been relevantly decreasing thanks to the implement ation of a catalytic abatement system (pilot scale plant). The use of thermally stable catalysts in the pilot plant has allowed the treatment of highly N 2 

### O concentrated flue gas from the adipic acid production plant, thus reducing the volumes of treated ga s and the size of the pilot plant itself. In 2004 this system was tested for one month resulting in complete decomposition of N 2 

### O, in 2005 because of technical changes in the system the catalytic process was started only at the end of 2005; in 2006 the

aba tement system had been operating continuously for 9 months (three months were needed for maintenance and technical changes) leading to the decomposition of 95% of N 2 

### O emissions; in 2007 the operating time was 11 months (about one month was needed for maint enance operations). The abatement pilot scale plant is generally run together with the adipic acid production process;

the abatement rate for N 2 

### O emissions was 90% in 2007.

Also CO 2 

### emissions are estimated from this source.

Ammonia production In Italy onl y two plants are currently producing ammonia as a consequence of the resizing of the production at national level after the crisis of the larger fertilizer producer (Enichem Agricoltura). Ammonia is obtained after processing in ammonia converters a “synthe sis gas” which contains hydrogen and nitrogen. CO 2 

### is also contained in the synthesis gas, but it is removed in the decarbonising step within the ammonia production process, partly it is recovered as a by

- product and partly is released to atmosphere.

CO 2 

### e missions from ammonia production are also a key source, at trend assessment with the Tier 1 approach. In fact, these emissions show a relevant decrease in the last years as a consequence of the reduction in production.

Nitric acid In early ‘90s seven faci lities manufactured nitric acid, but since 2003 the production has been carried on only in three plants. Nitric acid is produced from ammonia by catalytic oxidation with air

### 91

of NH 3 

### to NO 2 

### and subsequent reaction with water. Currently the reactions involved take place in low and medium pressure processes.

N 2 

### O emissions from nitric acid production are not a key source although they also show a relevant decrease in emissions from 1990 due to a reduction in production.

Carbon black

Three facilities have been carrying out this production which consists basically on cracking of feedstock oil (a mixture of PAH) at 1200

– 1900 °C. Together with black carbon, tail gas is a by product of the process. Tail gas is a mixture of CO, H 2 

### , H 2 

### O, NO

x 

### , SO

x 

### and H 2 

### S; it is gene rally burn to reduce the emissions to air and to recover energy to be used in the production process.

CO 2 

### emissions from carbon black production have been estimated on the basis of information supplied directly by the Italian production plants.

Ethylene, Ethylene oxide, Propylene, Styrene Ethylene, ethylene oxide, propylene and styrene productions belong to the organic chemical processes. In particular, ethylene is produced in petrochemical industry by steam cracking to manufacture ethylene oxide, styrene monomer and polyethylenes. Ethylene oxide is obtained via oxidation of ethylene and it is largely used as precursor of ethylene glycol and in the manufacture of surfactants and detergents. Propylene is obtained by cracking of oil and it is used to manufact ure polypropylene but also acetone and phenol. Styrene, also known as vinyl benzene, is produced on industrial scale by catalytic dehydrogenation of ethyl benzene. Styrene is used in the rubber and plastic industry to manufacture through polymerisation pro cesses such products as polystyrene, ABS, SBR rubber, SBR latex. Except for ethylene oxide production, which has stopped since 2002, the other productions of the above mentioned chemicals still occur in Italy. As far as ethylene, ethylene oxide and propyl ene, Syndial Spa (ex Enichem) and Polimeri Europa were the main producers in Italy up to 2006. In 2007 Polimeri Europa has become the main producer for those products, while it has been the main producer of styrene since 2002.

Titanium dioxide

CO 2 

### emissio ns from dioxide titanium production have been estimated on the basis of information supplied directly by the Italian production plants. TiO 2 

### is the most used white pigment especially for paint and plastic industries. In Italy there’s only one facility wher e this production occurs and titanium dioxide is produced through the “sulphate process” which involves the use of sulphuric acid to concentrate the input raw mineral in terms of titanium dioxide content, then selective precipitation and calcination allow getting the final product.

Caprolactame production Caprolactame is a monomer used in the industrial production of nylon

- 6. It can be obtained by catalytic oxidation of toluene and cycloexane. The process releases N 2 

### O.

N 2 

### O emissions from caprolactame produ ction have been estimated and reported and are related to only one producing plant, which closed in 2003.

Calcium carbide production Calcium carbide production process takes place in electric furnaces, CaO and coke are fed to the furnace and the product i

s obtained according to the following reaction:

CaO+3C ‡ CaC

2 

### +CO In Italy CARBITALIA SPA is the only facility which can operate calcium carbide production (CARBITALIA SPA, 2009) . It produced calcium carbide up to 1995, when it had to stop the production beca use of the increasing price of electricity. The plant still exists and it is maintained, but since 1995 it has just been supplying calcium carbide bought abroad.

### 92

4.3.2. Methodological issues

Adipic acid Italian production figures and emission estimates f or adipic acid have been provided by the process operator (Radici Chimica, several years); for the whole time series. N 2 

### O emissions from adipic acid production (2B3) have been estimated using the default IPCC emission factor equal to 0.30 kg

N 2 

### O/kg adipic acid produced, from 1990 to 2003. In 2004, the N 2 

### O catalytic decomposition abatement technology has been tested so that the value of emission factor has been reduced taking into account the efficiency and the time, one month, that the technology operated. From the end of 2005 the abatement technology is fully operative; the average emission factor in 2006 is equal to 0.05 kg N 2 

### O/kg adipic acid produced and the abatement system had been operating continuously for 9 months; in 2007 the average emission factor was 0.03 kg N

2 

### O/kg adipic acid produced and the operating time of the abatement system was 11 months.

Ammonia Ammonia production data are published in the international industrial statistical yearbooks (UN, several years) and they have been checked with information reported in the national EPER/E

- PRTR registry. For the years 1990

- 2001 CO 2 

### emission factor, equal to 1.175 t CO 2 

### /t ammonia production, has been calculated on the basis of information reported by the production plants for 2002 and 2003

in the fr amework of the national EPER/E

- PRTR registry

. This value has been used for the previous years in consideration that, as communicated by the operators, no modifications to the production plants have occurred along the period (YARA, 2007) . For the years 2002

- 2007 the average emission factors result from data reported by the plants in the national EPER/PRTR. Natural gas is used as feedstock in the ammonia production plants and the amount of fuel used is included in the energy balance under the no energy final consumption sector (see Annex 5), therefore double counting does not occur.

Nitric acid With regard to nitric acid production (2B2), production figures at national level are published in the national statistical yearbooks (ISTAT, several years), while at plant level they have been collected from industry (Norsk Hydro, several years; Yara, 2007; Radici Chimica, several years). In 1990 there were seven production plants in Italy; three of them closed between 1992 and 1995, and

another one closed in 2004. The N 2 

### O average emission factors are calculated from 1990 on the basis of the emission factors provided by the existing production plants in the national EPER/E

PRTR registry, applied for the whole time series, and default IPCC emission factors for low and

me dium pressure plants attributed to the plants, now closed, where it was not possible to collect detailed information. The implied emission factor varies year by year depending on the production levels of the different plants and it is equal to 6.49 and 7.0 7 kg N 2 

### O/Mg nitric acid production, in 1990 and in 2007 respectively.

Caprolactame

N 2 

### O emissions from caprolactame have been estimated on the basis of information supplied by the only plant present in Italy, production activity data published by ISTAT (I STAT, several years), and production and emission data reported in the national EPER/E

- PRTR registry. The average emission factor is equal to 0.3 kg N 2 

### O/Mg caprolactame production. The plant closed in 2003.

Carbon Black

CO 2 

### and CH

4 

### emissions from carbon b lack production process have been estimated on the basis of information supplied by the Italian production plants in the framework of the national EPER/E

PRTR registry and the European emissions trading scheme. In 1996 a change in the production technology

in the existing plants caused a reduction of CH 4 

### , NMVOC, NO

x 

### , SO

x 

### and PM 10

### 93

emissions. In 2005, the CO 2 

### implied emission factor is equal to 2.55 t CO 2 

### /t carbon black production, in 2007 it is 2.50 t CO 2 

### /t carbon black production.

Calcium carbide

CO 2 

### emis sions from calcium carbide production process have been estimated on the basis of the activity data provided by the sole Italian producer and referred to the years from 1990 to 1995 when the production stopped. IPCC (Guidelines, 2006) CO 2 

### emission factor h as been used to estimate the

emissions.

4.3.3. Uncertainty and time

- series consistency

The uncertainty in N 2 

### O emissions from adipic and nitric acid and caprolactame production and in

CO 2 

### emissions from ammonia and for other chemical production is estima ted by 10.4%, for each activity, as combination of uncertainties equal to 3% and 10% for activity data and emission factors, respectively. Uncertainty level for activity data is an expert judgement, taking into account the basic
source of information, whil e the uncertainty level for emission factors is equal to the level reported in the IPCC Good Practice Guidance (IPCC, 2000) for the adipic and nitric acid N 2 

### O emissions and

for CO 2 

### emissions from other industrial processes.

In Tables 4.4 and 4.5, the pro duction of chemical industry, including non

- key sources, and CO 2 

### , CH 4 

### and N 2 

### O emission trends are reported.

Adipic acid emission trends are directly related to the production and for the last years to the abatement technology introduced while nitric acid emissions are related to a reduction in production, and to the closure of the plants where old technology was implemented. Adipic acid production is increasing whereas nitric acid production and emissions show a decrease in the last

years.

Total CO 2 

### emiss ions from ammonia have decreased as a result of a relevant reduction in production

while CO 2 

### emissions from other chemical production have increased.

ACTIVITY DATA 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Adipic acid 49 64 71 75 74 69 78 75 84 84

Ammonia 1,455 592 414 430 474 578 648 607 559 578

Calcium carbide 12 7

- - - - - - - - Caprolactame 120 120 111 91 78 7

- - - - Carbon black 184 208 221 208 209 210 219 214 226 234
Ethylene 1,466 1,807 1,771 1,662 1,687 1,530 1,698 1,721 1,639 1,797
Ethylene oxide 61 54 13 5

- - - - - - Nitric acid 1,037 588 556 527 542 539 616 572 526 505
Propylene 774 693 690 653 1,035 931 996 1,037 988 971

Styrene 365 484 613 563 487 545 542 520 558 549

Titanium dioxide 58 69 72 60 69 66 70 60 68 72

Table 4. 4 Production of chemical industry, 1990

– 2007 (kt)

### 94

EMISSIONS 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO 2 (Gg)

Ammonia 1,709.63 695.60 486.19 505.46 557.53 679.57 747.55 705.18 656.52 649.38

Calcium carbide 13.08 7.0 9

- - - - - - - - Carbon black 422.05 477.48 508.83 479.30 460.43 489.89 506.62 548.22 579.21 585.73

Titanium dioxide 52.80 48.11 64.70 47.00 61.60 72.00 72.00 62.01 70.57 74.28
Adipic acid 1.33 1.72 1.93 2.03 2.00 1.86 1.56 1.50 1.68 1.68

CH 4 (Gg)

Carbon black 1.84 2.08 0.11 0.10 0.10 0.10 0.10 0.10 0.10 0.10
Ethylene 0.12 0.15 0.15 0.14 0.14 0.13 0.14 0.15 0.14 0.15
Propylene 0.07 0.06 0.06 0.06 0.09 0.08 0.08 0.09 0.08 0.08
Styrene 0.01 NA NA NA NA NA NA NA NA NA
Ethylene oxi de 0.42 0.37 0.09 0.03 NA NA NA NA NA NA

N 2 O (Gg)

Nitric acid 6.73 4.22 4.09 3.94 3.27 3.67 5.82 5.44 3.95 3.58
Adipic acid 14.77 19.09 21.42 22.59 22.20 20.70 21.41 19.59 4.58 2.52
Caprolactame 0.04 0.04 0.03 0.03 0.02 0.00

- - - - Table 4.5 CO 2 , CH 4 and N

2 O emissions from chemical industry, 1990

– 2007 (Gg)



### 4.3.4. Source

- specific QA/QC and verification

Emissions from adipic acid, nitric acid, ammonia and other chemical industry production have been checked with the relevant p rocess operators and with data reported to the national EPER/E

- PRTR registry.

4.3.5. Source

- specific recalculations

Recalculations in the sector have been done because CO 2 

### emissions from calcium carbide production process have been estimated and reported for the years from 1990 to 1995. So in terms of Gg CO 2 

### equivalent emissions the time series for the Chemical industry show an increase of 13.08 (0.60%), 12.54 (0.60%), 13.19 (0.64%), 12.64 (0.87%), 10.36 (0.87%) and 7.09 (0.58%) respectively in 1990, 1991 , 1992, 1993, 1994 and 1995 which are equal to the amounts of emission reported for calcium carbide production process in the same years.

4.3.6. Source

- specific planned improvements

A detailed balance of the natural gas reported in the Energy Balance as no energy fuel consumption and the fuel used for the production processes in the petrochemical sector is planned.

4.4 Metal production (2C)

4.4.1. Source category description

The sub

- sector metal production comprises four sources: iron and steel produc tion, ferroalloys production, aluminium production and magnesium foundries; CO 2 

### emissions from iron and steel production and PFC emissions from aluminium production are key sources at Tier 1 trend

assessment.

The share of CO 2 

### emissions from metal productio n accounts, in the year 2007, for 0.4% of the

national total CO 2 

### emissions, and 7.2% of the total CO 2 

### from industrial processes.

The share of CH

4 

### emissions is, in the year 2007, equal to 0.15% of the national total CH 4 

### emissions

while N 2 

### O emissions do not occur.

### 95

The share of F

- gas emissions from metal production out of the national total F

- gas levels was

67.2% in the base

- year and has decreased to 2.7% (0.04% of the national total greenhouse gas emissions) in the year 2007.

Iron and steel The main processe s involved in iron and steel production are those related to sinter and blast furnace plants, to basic oxygen and electric furnaces and to rolling mills. The sintering process is a pretreatment step in the production of iron where fine particles of metal ores are agglomerated. Agglomeration of the fine particles is necessary to increase the passageway for the gases during the blast furnace process and to improve physical features of the blast furnace burden. Coke and a mixture of sinter, lump ore and fluxe s are introduced into the blast furnace. In the furnace the iron ore is increasingly reduced and liquid iron and slag are collected at the bottom of the furnace, from where they are tapped. The combustion of coke provides both the carbon
monoxide (CO) need ed for the reduction of iron oxide into iron and the additional heat needed to melt the iron and impurities. The resulting material, pig iron (and also scrap), is transformed into steel in subsequent furnaces which may be a basic oxygen furnace (BOF) or e lectric arc furnace (EAF). Oxygen steelmaking allows the oxidation of undesirable impurities contained in the metallic feedstock by blowing pure oxygen. The main elements thus converted into oxides are carbon, silicon, manganese, phosphorus and sulphur.

In an electric arc furnace steel is produced from polluted scrap. The scrap is mainly produced by cars shredding and does not have a constant quality. The iron and steel cycle is closed by rolling mills with production of long products, flat products and pip es. In 1990, there were four integrated iron and steel plants in Italy. In 2007, there are only three of the above mentioned plants, one of which lacks sintering facilities. Oxygen steel production represents about 40% of the total production and the arc f urnace steel the remaining 60% (FEDERACCIAI, 2008). Currently, long products represent about 50% of steel production in Italy, flat products about 40% and pipes the remaining 10%. Almost the whole flat production derives from one only integrated

iron and s

teel plant while, in steel plants equipped with electric ovens, almost all located in the northern regions, long products are produced (e.g carbon steel, stainless steels) and seamless pipes (only one plant) (FEDERACCIAI, 2008).

CO 2 

### emissions from steel pr oduction refer to carbonates used in basic oxygen furnaces and crude

iron and electrodes in electric arc furnaces. CO 2 

### emissions from pig iron production refer to carbonates used in sinter and pig iron production. CO 2 

### emissions from iron and steel producti on due to the fuel consumption in combustion processes are estimated and reported in the energy sector (1A2a) to avoid double counting.

CH 4 

### emissions from steel production refer to blast furnace charging, basic oxygen furnace, electric furnaces and rolling mills. CH 4 

### emissions from coke production are fugitive emissions during solid fuel transformation and have been reported under 1B1b.

Ferroalloys Ferroalloy is the term used to describe concentrated alloys of iron and one or more metals such as
silicon, manganese, chromium, molybdenum, vanadium and tungsten. Usually alloy formation occurs in Electric Arc Furnaces (EAF) and CO 2 

### emissions occur during oxidation of carbon still present in coke and because of consumption of the graphite electrodes. In early ‘ 90s there were thirteen plants producing various kinds of ferroalloys: FeCr, FeMn, FeSi,
SiMn, Si

- metal and other particular alloys, but since 2001 the production has been carried on only in one plant (ISPESL, 2005). The last remaining plant in Italy produ ces mainly f

e rro

- ma n ganese and s i licon

- manganese alloys.

### 96

Aluminium From primary aluminium production CO 2 

### and two PFCs (CF 4 

### and C 2 

### F 6 

### ) are emitted. PFCs are formed during a phenomenon known as the ‘anode effect’, when alumina levels are low. At present in I

taly there are two primary aluminium production plants, which use a prebake technology with point feeding (CWPB), characterised by low emissions. These plants have been progressively upgraded from a Side Work Prebake technology to Point Fed Prebake technol ogy; three old plants with Side Work Prebake technology and Vertical Stud Søderberg technology stopped operation in 1991 and 1992. Primary aluminium production passed from 232 kt in 1990 to

180 kt in 2007.

Magnesium foundries In the magnesium foundries, S F 6 

### is used as a cover gas to prevent oxidation of molten magnesium. In Italy there is only one plant, located in the north, which started its activity in September 1995.

From the end of 2007, SF 6 

### has been replaced by HFC 125, due to the enforcement of fluo rinated gases regulation (EC, 2006).

4.4.2. Methodological issues

CO 2 

### and CH

4 

### emissions from the sector have been estimated on the basis of activity data published in the national statistical yearbooks (ISTAT, several years), data reported in the framewo rk of the

national EPER/E

- PRTR registry and the European emissions trading scheme, and supplied by industry (FEDERACCIAI, several years). Emission factors reported in the EMEP/CORINAIR
Guidebook (EMEP/CORINAIR, 2007), in sectoral studies (APAT, 2003; CTN/A CE, 2000) or supplied directly by industry (FEDERACCIAI, 2004) have been used.

Iron and steel

CO 2 

### emissions from iron and steel production refer to the carbonates used in sinter plants, in blast furnaces and in steel making plants to remove impurities; th ey are also related to the steel and pig iron scraps, and graphite electrodes consumed in electric arc furnaces. Basic information for this sector derives from different sources in the period 1990

- 2007. Activity data are supplied by official statistics p ublished in the national statistics yearbook (ISTAT, several years) and by the sectoral industrial association (FEDERACCIAI, several years). For the integrated plants, emission and production data have been communicated by the two largest plants for the years 1990

- 1995 in the framework of the CORINAIR emission inventory, distinguished by sinter, blast furnace and BOF, and by combustion and processes emissions. From

2000 CO 2 

### emission and production data have been supplied by all the plants in the framework of the ETS scheme, for the years 2000

- 2004 disaggregated for sinter, blast furnace and BOF plants, from 2005 specifying carbonates and fuels consumption and related CO 2 

### emissions. For 2002

- 2006 data have also been supplied by all the four integrated iron and steel plants in the framework of the European EPER registry not distinguished for combustion and processes. Qualitative information and documentation available on the plants allowed us to reconstruct their history including closures

or modifications of

part of the plants; additional qualitative information regarding the plants collected and checked for other environmental issues or directly asked to the plant allowed us to individuate the main driving of the emission trends for pig iron and steel produc tions.

Time series of c arbonates used in basic oxygen furnaces have been reconstruct ed on the basis of the above mentioned information resulting in no emissions in the last years. Indeed, as regards the largest Italian producer of pig iron and steel, lime production has increased significantly from 2000 to 2007 by about 250,000 over 370,000 tonnes and the amount introduced in basic oxygen furnaces was, in 2004, about 490,000t (ILVA, 2006).

### 97

Concerning the electric arc furnaces, additional information on the consumption of scraps, pig iron, graphite and electrodes and their average carbon content have been supplied together with the steel production by industry for a typical plant in 2004 (FEDERACCIAI, 2004) and checked with other sectoral study (APAT, 2003). On the basis of these figures an average emission factor has been

calculated.

On account of t

he amount of carbonates estimated in sinter plants

, average emission factor was equal in 1990 to 0.15 t CO 2 

### /t pig iron production, while in 2007 it reduced to 0. 071 t CO 2 

### /t pig iron production. The reduction is driven by the increase in the use of lime instead of carbonates in sinter and blast furnaces in the Italian plants. Emissions are reported under pig iron because they are

emitted as CO 2 

### in the blast furnace s producing pig iron.

CO 2 

### average emission factor in basic oxygen furnaces results in 1990 equal to 0.079 t CO 2 

### /t steel production, while from 2003 is null.

CO 2 

### average emission factor in electric arc furnaces, equal to 0.035 t CO 2 

### /t steel production, has been calculated on the basis of equation 3.6B of the IPCC Good Practice Guidance (IPCC, 2000) taking into account the pig iron and graphite electrodes used in the furnace. The same emission

factor has been used for the whole time series. Implied emissio n factors for steel production reduced from 0.053 to 0.022 t CO 2 

### /t steel production,
from 1990 to 2007, due to the reduction in the basic oxygen furnaces.

CO 2 

### emissions due to the consumption of coke, coal or other reducing agents used in the iron and

ste el industry have been accounted for as fuel consumption and reported in the energy sector, including fuel consumption of derived gases; in Annex 3, the energy and carbon balance in the iron and steel sector, with detailed explanation, is reported.

CH 4 

### emis sions from steel production have been estimated on the basis of emission factors derived from the IPPC specific BREF Report (IPPC, 2001 available at http://eippcb.jrc.es ), sectoral study (APAT, 2003) and the EMEP/CORIN AIR Guidebook (EMEP/CORINAIR, 2007) and refer to blast furnace, basic oxygen

furnace, electric furnaces and rolling mills.

Ferroalloys

CO 2 

### emissions from ferroalloys have been estimated on the basis of activity data published in the national statistical y

earbooks (ISTAT, several years) until 2001. Time series of ferroalloys activity data have been updated from 2002 on the basis of information provided by industry concerning the production of Si

- Mn steel (FEDERACCIAI, several years) and on the basis of prod uction data

communicated to E

- PRTR register from the only plant of ferroalloys production in 2007. Emission factors have been updated according to the IPCC Guidelines (IPCC, 2006) taking into consideration the different types of ferroalloys produced while the splitting up of national production in different types of ferroalloys was obtained from U. S. Geological Survey (USGS, several years). Implied emission factors for ferroalloys reduced from 1.97 to 1.60 t CO 2 

### /t ferroalloys production,

from 1990 to 2007 , as a consequence of the sharp reduction in ferroalloys production, which is characterized by high emission factors (ferro

- silicon and silicon

- metal alloys). The simultaneous reduction of total production (from about 200 kt to 100 kt) has resulted in CO 2 

### emissions decreasing from 408 Gg in 1990 to 174 Gg in 2007.

Aluminium production PFC emissions from aluminium production, key source at trend assessment calculated with Tier 1, have been estimated using both IPCC Tier 1 and Tier 2 methodologies. These em issions, specifically CF 4 

### and C 2 

### F 6 

### , have been calculated on the basis of information provided by national statistics (ENIRISORSE, several years; ASSOMET, several years) and the national primary aluminium producer (ALCOA, several years), with reference to t he document drawn up by the
International Aluminium Institute (IAI, 2003) and the IPCC Good Practice Guidance (IPCC, 2000).

### 98

The Tier 1 has been used to calculate PFC emissions relating to the entire period 1990

- 1999. From the year 2000, the more accurate T ier 2 method has been followed, based on default technology specific slope and overvoltage coefficients. Regarding the Tier 1 methodology, the emission factors for CF 4 

### and C 2 

### F 6 

### were provided, whereas

for the Tier 2 site

- specific values and, where they were not available, default coefficients were provided (ALCOA, 2004). In the following tables (Tables 4.6, 4.7, 4.8, 4.9) the EFs and the default parameters used are reported; site specific values are confidential but they have been supplied to the inventory t

eam.

Technology specific emissions (kg CF 4 / t Al)

1990

- 1993 1994

- 1997 1998

– 2000

Center Work Prebake 0.4 0.3 0.2

Point Fed Prebake 0.3 0.1 0.08

Side Work Prebake 1.4 1.4 1.4 Vertical Stud Søderberg 0.6 0.5 0.4 Horizontal Stud Søderberg 0.7 0 .6 0.6

Table 4.6 Historical default Tetrafluoromethane (CF 4 ) emission values by reduction technology type

Technology multiplier factor

Center Work Prebake 0.17

Point Fed Prebake 0.17

Side Work Prebake 0.24
Vertical Stud Søderberg 0.06

Ho rizontal Stud Søderberg 0.09
Table 4.7 Multiplier factor for calculation of Hexafluoroethane (C 2 F 6 ) by technology type

Baked Anode Properties (weight percent) Sulphur Ash Impurities

Portovesme ssv* ssv DV** = 0.4

Fusina DV = 1.6 ssv DV = 0.4

* site specific value

** default value

Table 4.8 Coefficients used for estimation with the Tier 2 methodology by plant

Pitch content
in green

anodes Hydrogen

content in pitch Recovered

tar Packing coke

consumption Sulphur

content of packing coke Ash cont ent

of packing

coke (weight%) (weight%) (kg/t BAP) (t Pcc/ t BAP) (weight%) (weight%)

Portovesme ssv* ssv DV** = 0 DV = 0.05 DV = 3 DV = 5

Fusina ssv DV = 4.45 DV = 0 DV = 0.05 DV = 3 DV = 5
* site specific value

** default value

Table 4.9 Coeffic ients used for estimation with the Tier 2 methodology by plant



### CO 2 

### emissions from aluminium production have been also estimated on the basis of activity data provided by industrial association (ENIRISORSE, several years; ASSOMET, several years) and

defaul t emission factor reported by industry (ALCOA, 2004) and by the IPCC Guidelines (IPCC, 1997) which refer to the prebaked anode process; emission factor has been assumed equal to 1 .55 t

CO 2 

### /t primary aluminium production for the whole time series.

Magnesiu m foundries

For SF 6 

### used in magnesium foundries, according to the IPCC Guidelines (IPCC, 1997), emissions are estimated from consumption data made available by the company (Magnesium products of Italy, several years), assuming that all SF 6 

### used is emitted. In 2007, SF 6 

### has been used partially, replaced in November by HFC 125, due to the enforcement of fluorinated gases regulation (EC, 2006).

### 99

4.4.3. Uncertainty and time

- series consistency

The combined uncertainty in PFC emissions from primary aluminium pr oduction is estimated to be about 11% in annual emissions, 5% and 10% concerning respectively activity data and emission factors; the uncertainty for SF 6 

### emissions from magnesium foundries is estimated to be about 7%, 5% for both activity data and emission factors. The uncertainty in CO 2 

### emissions from the sector is estimated to be 10.4%, for each activity, while for CH 4 

### emissions about 50%.

In Table 4.10 emission trends of CO 2 

### , CH 4 

### and F

- gas from metal production are reported. The decreasing of CO 2 

### emissio ns from iron and steel sector is driven by the use of lime instead of limestone and dolomite to remove impurities in pig iron and steel while CO 2 

### emissions from aluminium and ferroalloys are driven by the production levels.

In Table 4.11 the emission tren d of F

- gases per compound from metal production is given. PFC

emissions from

aluminium production decreased on the basis of the closure of three old plants in 1991 and 1992 and the update of technology for the two plants still operating. The decreasing of

SF 6 

### consumption in the magnesium foundry from 2003 is due to the abandonment of recycling plant and the optimisation of mixing parameters.

EMISSIONS 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO 2 (Gg)

Iron and steel 3,124 2,898 1,230 1, 239 1,187 1,133 1,281 1,533 1,562 1,483
Aluminium production 359 276 294 291 295 297 303 303 301 278
Ferroalloys 408 244 245 199 165 197 188 172 169 174

CH 4 (Gg)

Pig iron 2.13 2.10 2.02 1.89 1.75 1.82 1.91 2.06 2.07 2.00

Steel 0.58 0.60 0.60 0.61 0.62 0.63 0.67 0.67 0.74 0.75

PFC (Gg CO 2 eq.)

Aluminium production 1,673 298 199 234 199 268 157 181 154 200

SF 6 (Gg)

Magnesium foundries

- - 0.0072 0.0188 0.0167 0.0057 0.0039 0.0035 0.0026 0.0023

Table 4 .10 CO 2 , CH 4 and F

- gas emissions from metal production, 1990

– 2007 (Gg)

COMPOUND 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Gg CO 2 eq.

CF 4 (PFC

- 14) 1,289.2 235.8 168.1 198.1 168.1 226.4 133.1 153.0 130.6 170.9

C 2 F 6 (PFC

- 16) 384.1 61.7 30.6 36 .0 30.6 41.2 24.2 27.8 23.8 29.3

Total PFC emissions from aluminium production 1,673.4 297.5 198.7 234.1 198.6 267.6 157.3 180.8 154.4 200.1

Total SF 6 emissions from magnesium foundries 0.0 0.0 172.1 449.9 400.1 135.2 94.3 84.7 61.2 53.9

Total F

- gas emi ssions from metal production 1,673.4 297.5 370.8 684.0 598.7 402.8 251.5 265.5 215.6 254.0

Table 4.11 Actual F

- gas emissions per compound from metal production in Gg CO 2 equivalent, 1990

– 2007



### The consistency of the time series of PFC emissions from alu minium production has been verified, as two different methodologies have been used on the basis of the information provided by the industry (ALCOA, 2004). In Table 4.12 two time

- series are reported, one calculated with only the Tier 1 methodology and the o ther calculated with both the Tier 1 and Tier 2 methodologies as mentioned above. Notwithstanding it is good practice to maintain consistency of the methodology throughout the time series, the ERTs in the last review processes noted that this approach is

t ransparent, accurate and conservative (UNFCCC, 2007; UNFCCC, 2009). In fact, the trend of PFC

### 100

emissions calculated with the Tier 1 methodology shows lower values compared to those calculated with the Tier 2 methodology; from 2004 C 2 

### F 6 

### values calculated wit h Tier 1 rise up.

COMPOUND 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Tier 1

CF 4 (t) 198.3 36.3 19.0 18.8 19.0 19.1 19.5 19.3 19.4 18.0

C 2 F 6 (t) 41.8 6.7 3.2 3.2 3.2 3.3 3.3 3.3 3.3 3.1

Tier 1 and Tier 2

CF 4 (t) 198.3 36.3 25.9 30.5 25.9 34.8 20.5 23.5 20.1 26.3

C 2 F 6 (t) 41.8 6.7 3.3 3.9 3.3 4.5 2.6 3.0 2.6 3.2

Table 4.12 Comparison between PFC emissions from aluminium production in tonnes, calculated with only the Tier 1 methodology and with both the Tier 1 an d Tier 2 methodologies



### 4.4.4. Source

- specific QA/QC and verification

Emissions from the sector are checked with the relevant process operators. In this framework, primary aluminium production supplied by national statistics ( ENIRISORSE, several years;

AS SOMET, several years, ) and the only national producer ALCOA (ALCOA, several years), in addition with data reported in a site

- specific study (Sotacarbo, 2004) have been checked, in order to
avoid the use of different time series. Moreover, emissions from ma gnesium foundries are annually checked with those reported in the national EPER/E

- PRTR registry while for the iron and steel sector emissions reported in the national EPER/E

- PRTR registry and for the Emission Trading Scheme are compared and checked.

4.4.5 . Source

- specific recalculations

Recalculations in the sector have been done because iron and steel activity data for 2004 and 2006

and ferroalloys activity data and emission factors have been updated. Ferroalloys activity data have been updated from 20 02 to 2007 on the basis of information provided by industry and emission factors have been updated for the whole time series according to the IPCC Guidelines (IPCC, 2006). In terms of CO 2 

### emissions from ferroalloys production it results in a

decrease of 18 .21% in 1990 and an increase of 30.60% in 2007.

Additional data supplied by the integrated iron and steel plants allowed to refine CO 2 

### emission estimates for 2004 and to improve 2006 estimates. This review process has resulted in an increase

of CO 2 

### emissi

ons in iron and steel equal to 7.83% for 2004 and in a decrease equal to 7.00% in

2006. CH

4 

### emissions from iron and steel production show an increase of 0.03% in 2006.

4.4.6. Source

- specific planned improvements

We plan to check the average emission fac tor of CO 2 

### from electric arc furnaces with ETS data communicated for the years 2005, 2006 and 2007 in the next submission.

4.5 Other production (2D)

4.5.1. Source category description

Only indirect gas and SO 2 

### emissions occur from these sources.

### 101

In th is sector, non

- energy emissions from pulp and paper as well as food and drink production, especially wine and bread, are reported. CO 2 

### from food and drink production (e.g. CO 2 

### added to water or beverages) can be of biogenic or non

- biogenic origin but only information on CO 2 

### emissions of non

- biogenic origin should be reported in the CRF. According to the information provided by industrial associations, CO 2 

### emissions do not occur, but only NMVOC emissions originate from these activities. CO 2 

### emissions from fo od and beverage included in previous submissions have been removed since they originated from sources of carbon that are part of a closed cycle. As regards the pulp and paper production, NO X 

### and NMVOC emissions as well as SO 2 

### are estimated.

4.6 Productio n of halocarbons and SF 6 

### (2E)

4.6.1. Source category description

The sub

- sector production of halocarbons and SF 6 

### consists of two sources, “By

- product emissions” and “Fugitive emissions”, identified as non

- key sources. Only two production plants are pres ent in Italy, located in Porto Marghera and Spinetta Marengo. Within by

- product emissions, HFC

- 23

emissions are released from HCFC

- 22 manufacture, whereas C 2 

### F 6 

### , CF

4 

### and HFC 143a emissions are released from the production of CFC 115, SF 6 

### and HFC 134a, respe ctively. Production of HFC
125, HFC 134a, HFC 227ea and SF 6 

### lead to fugitive emissions of the same gases. CFC115 and SF 6 

### productions stopped in 1998 and in 2005, respectively.

The share of F

- gas emissions from the production of halocarbons and SF 6 

### in the n ational total of F

gases was 24.3% in the base

- year, 1990, and 0.25% in 2007; the share in the national total greenhouse gas emissions was 0.12% in the base

- year and 0.003% in 2007.

4.6.2. Methodological issues

For both source categories ”By

- product emis sions” and “Fugitive emissions”, the IPCC Tier 2 method is used, based on plant

- level data. The communication is supplied annually by the only national producer, and includes productions, emissions, import and export data for each gas (Solvay, several year

s).

4.6.3. Uncertainty and time

- series consistency

The uncertainty in F

- gas emissions from production of halocarbons and SF 6 

### is estimated to be about

11% in annual emissions.

HFC

- 23 emissions from HCFC

- 22 had already been drastically reduced in 1988 due to the installation of a thermal afterburner in the plant located in Spinetta Marengo. Productions and emissions from 1990 to 1995 are constant as supplied by industry; from 1996, untreated leaks have
been collected and sent to the thermal afterburner, thu s allowing reduction of emissions to zero. This information is yearly directly updated by the producer, and it is also reported in the framework of the European EPER registry, confirming that the technology is fully operating, PFC by

- product emissions and SF 6 

### fugitive emissions, from the same plant, are constant from 1990 to 1995 and from 1996 to 1998, reducing to zero from 1999 due to the stop of the CFC 115 production and the use of the thermal afterburner mentioned above. Besides SF 6 

### production stopped

from the 1 st 

### of January 2005. Regarding fugitive emissions, emissions of HFC

- 125 and HFC

- 134a have been cut in 1999 thanks to a rationalisation in the new production facility located in Porto Marghera, whereas HFC

- 143 released as by

- products from the produ

ction of HFC

- 134a has been recovered and commercialised.

### 102

In Table 4.13 an overview of the emissions from production of halocarbons and SF 6 

### is given for the

1990

- 2007 period, per compound.

COMPOUND 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Gg C O 2 eq.

HFC 23 351.0 351.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

HFC 143a 0.0 22.8 3.8 3.8 0.0 3.8 3.8 4.2 4.6 4.6

CF 4 97.5 97.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

PFC C2÷C3 36.8 36.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Total F

- gas by product

emissions 485.3 508.1 3.8 3.8 0.0 3.8 3.8 4.2 4.6 4.6

HFC 125 0.0 28.0 2.8 5.6 5.6 11.2 2.8 3.4 3.9 5.0

HFC 134a 0.0 39.0 15.6 15.6 15.6 7.8 11.7 12.6 12.4 8.8

HFC 227ea 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

SF 6 119.5 119.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Total F

- gas fug itive

emissions 119.5 186.5 18.4 21.2 21.2 19.0 14.5 16.0 16.3 13.9

Total F

- gas emissions from production of halocarbons

and SF 6 604.8 694.6 22.2 25.0 21.2 22.8 18.3 20.2 20.8 18.4

Table 4.13 Actual emissions of F

- gases per compound from production of ha locarbons and SF 6 in Gg CO

2 equivalent, 1990

– 2007



### 4.6.4. Source

- specific QA/QC and verification

Emissions from production of halocarbons and SF 6 

### have been checked with data reported to the

national EPER/E

- PRTR registry.

4.6.5. Source

- specific recalcul ations

No recalculations have been done.

4.6.6. Source

- specific planned improvements

No further improvements are planned.

4.7 Consumption of halocarbons and SF 6 

### (2F)

4.7.1. Source category description

The sub

- sector consumption of halocarbons and SF 6 

### consists of three sources, “ HFC, PFC emissions from ODS substitutes”, key category at level and trend assessment, both Tier 1 and 2 approaches, “PFC, HFC, SF 6 

### emissions from semiconductor manufacturing”, “SF 6 

### emissions from electrical equipment”

, that ar e non

- key categories.

Potential emissions are also reported in this section. The share of F

- gas emissions from the consumption of halocarbons and SF 6 

### in the national total of F

- gases was 8.6% in the base

- year 1990
and 96.3% in 2007; the share in the nati onal total greenhouse gas emissions was 0.04% in the base

year and 1.3% in 2007.

### 103

4.7.2. Methodological issues

The methods used to calculate F

- gas emissions from the consumption of halocarbons and SF 6 

### are presented in the following box:

Sub

- sources of F

- g as emissions and calculation methods
Source category Sub

- source Calculation method

HFC, PFC emissions from ODS

substitutes Refrigeration and air conditioning
equipment (2F1) IPCC Tier 2a

Foam blowing (2F2) IPCC Tier 2a

Fire extinguishers (2F3) IPCC Ti er 2a

Aerosols/metered dose inhalers (2F4) IPCC Tier 2a

PFC, HFC, SF

6 emissions from semiconductor manufacturing (2F6) IPCC Tier 2a

SF 6 emissions from electrical equipment (2F7) IPCC Tier 3c



### Basic data have been supplied by industry: specifically, for the mobile air conditioning equipment the national motor company and the agent’s union of foreign motor

- cars vehicles have provided the yearly consumptions (FIAT, several years; IVECO, several years; UNRAE, several years; CNH, several years); for the o ther air conditioning equipment the producers supply detailed table of consumption data by gas (Solvay, several years); pharmaceutical industry has provided aerosols/metered dose inhaler data (Sanofi Aventis, several years; Boehringer Ingelheim, several

ye ars; Chiesi Farmaceutici, several years; GSK, several years; Lusofarmaco, several years; Menarini, several years); the semiconductor manufacturing industry has supplied consumption data for four national plants (ST Microelectronics, several years; MICRON, several years); finally, for

the sub

- source fire extinguishers, the European Association for Responsible Use of HFCs in Fire Fighting has been contacted (ASSURE, 2005). Losses rates have been checked with industry and they are distinguished by domestic equ ipment, small and large commercial equipment, industrial chillers, mobile air conditioning equipment, foaming, aerosols and fire extinguishers. Refrigeration activities, such as commercial, transport, industrial and other stationary, are all reported under

domestic refrigeration because no detailed information is available to split consumptions and emissions in the different sectors. Anyway, appropriate losses rates have been applied for each gas taking into account the equipment where refrigerants are gene rally used. Therefore implied product life factors, especially for HFC 134a, result from the weighted average of different losses rates, from 0.7% for domestic refrigeration to 10% for large chillers.

SF 6 

### emissions from electrical equipment have been estim ated according to the IPCC Tier 2a approach from 1990 to 1994, and IPCC Tier 3c from 1995. SF 6 

### leaks from installed equipment have been estimated on the basis of the total amount of sulphur hexafluoride accumulated and average leakage rates; leakage data p ublished in environmental reports have also been used for major electricity producers (ANIE, several years). Additional data on SF 6 

### used in high voltage gas

insulated transmission lines have been supplied by the main energy distribution companies (ACEA,

20 04; AEM, several years; EDIPOWER, 2003; EDIPOWER, 2007; EDISON, several years; ENDESA, 2004; ENDESA, several years [a] and [b]; ENEL, several years; TERNA, 2006). The IPCC Tier 1a method has been used to calculate potential emissions, using production, imp ort, export and destruction data provided by the national producer (Solvay, several years; ST Microelectronics, several years; MICRON, several years). From 2008, in compliance with article 6 of the fluorinated gases European regulation (EC, 2006), producer s, importers and exporters have communicated to the Ministry of the Environment and to the Commission the required data;

### 104

unfortunately, only few companies have reported data and we expect that more information will be available next year (General Gas, 2008 ; Mariel, 2008; Safety Hi Tech, 2008; Solvay, 2008). As regard PFC potential emissions, since no production occurs in Italy, export has been reasonably assumed negligible, whereas import corresponds to consumption of PFCs by semiconductor
manufactures, tha t use these substances.

4.7.3. Uncertainty and time

- series consistency

The combined uncertainty in F

- gas emissions from HFC, PFC emissions from ozone depletion substances (ODS) substitutes and PFC, HFC, SF 6 

### emissions from semiconductor manufacturing is

e stimated to be about 58% in annual emissions, 30% and 50% concerning respectively activity data and emission factors; the uncertainty in SF 6 

### emissions from electrical equipment is estimated to be about 11 % in annual emissions, 5% and 10% concerning respec tively activity data and emission

factors.

In Table 4.14 an

overview of the emissions from consumption of halocarbons and SF 6 

### is given for

the 1990

- 2007 period, per compound. HFC emissions from refrigeration and air conditioning equipment increased from 19 94 driven by the increase of their consumptions, especially HFC 134a consumption for mobile air conditioning. HFC emissions from ODS substitutes started in 1996 and they continue to increase, especially HFC 134a from foam blowing and from aerosols. Emissio ns from semiconductor manufactures are driven by the consumption data provided by the producers, one started in 1995 and the second one

in 1998. SF 6 

### emissions from electrical equipment increased from 1995 to 1997 and decreased in the following years; from 2004 emissions are enough stable: they are driven by emissions from manufacturing due to the amount of fluid filled in the new manufacturing products while emissions from stocks are slightly increasing.

COMPOUND 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007
Gg CO 2 eq.

HFC 23 0.0 1.6 7.1 8.6 10.3 12.2 14.3 17.0 19.2 20.8

HFC 32 0.0 0.0 52.6 80.9 113.7 150.6 191.3 235.3 276.5 316.7

HFC 125 0.0 1.8 371.5 564.8 791.3 1,048.0 1,332.8 1,643.2 1,932.3 2,215.3

HFC 134a 0.0 224.3 1,128.6 1,302.3 1,448.8 1, 591.2 1,735.5 1,888.8 2,056.4 2,221.0

HFC 143a 0.0 2.7 206.3 308.6 430.2 570.2 727.6 901.5 1,062.0 1,220.7

Total HFC emissions from refrigeration and air
conditioning equipment 0.0 230.5 1,766.1 2,265.2 2,794.2 3,372.2 4,001.3 4,685.7 5,346.4 5,994.6

HF C 134a emissions from foam blowing 0.0 0.0 64.2 88.0 118.8 158.6 210.2 234.1 247.4 259.0

HFC 227ea emissions from fire extinguishers 0.0 0.0 19.6 26.5 35.8 47.4 61.3 79.9 97.7 114.6

HFC 134a emissions from

aerosols/metered dose inhalers 0.0 0.0 108.4 137 .6 123.7 186.2 215.2 240.2 237.3 307.7

Total HFC emissions from

ODS substitutes 0.0 0.0 192.2 252.1 278.3 392.3 486.7 554.2 582.4 681.3

HFC 23 0.0 0.0 5.1 7.4 6.2 8.6 8.6 7.0 6.5 5.4

HFC 134a 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

CF 4 0.0 24.4 64.8 10 7.8 106.2 117.1 127.3 96.8 87.0 71.5

C 2 F 6 0.0 34.6 82.0 99.1 108.0 97.7 52.6 62.8 30.8 11.4

C 3 F 8 0.0 0.0 0.0 9.0 10.2 13.2 9.6 3.5 3.5 0.1

C 4 F 8 0.0 0.0 0.4 1.2 0.8 2.0 1.2 8.7 6.6 4.6

SF 6 0.0 0.0 20.9 49.4 53.3 60.5 75.2 61.5 46.5 36.3

Total PFC, HFC, SF 6 emissions from semiconductor 0.0 59.0 173.2 273.9 284.6 299.0 274.5 240.4 181.0 129.4

### 105

COMPOUND 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007
manufacturing

SF 6 emissions from electrical
equipment 213.4 482.0 300.4 296.0 286.3 271.9 332.6 319.1 298.1 337.4

Total F

- gas emissions from
consumption of halocar

bons

and SF 6 213.4 771.4 2,432.0 3,087.3 3,643.4 4,335.4 5,095.1 5,799.4 6,408.0 7,142.6

Table 4.14 Actual F

- gas emissions per compound from the consumption of halocarbons and SF 6 in Gg CO

2 equivalent, 1990

- 2007



### In Table 4.15 an overview of the potential emissions is given for the 1990

- 2007 period, per compound. Negative values for HFC compounds in some years are derived from the circumstance that in those years import data are equal to zero and exports are greater than production data

because of the avai lability of stocks; the formula suggested by the UNFCCC guidelines to calculate potential emissions does not consider stock variations.

COMPOUND 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Gg CO 2 eq.

HFC 32 0.0 0.0 10.4 3.3

- 5.2 29.3 70.2 31.9 129 .4 139.1

HFC 125 0.0 148.4 268.8 1,671.6 803.6

- 123.2 2,200.8 1,131.2 1,456.0 4,704.0

HFC 134a 0.0 1,739.4 2,107.3 4,371.9 2,960.1 4,551.3 4,308.2 5,575.7 6,026.8 5,825.3

HFC 143a 0.0 11.4 68.4 258.4 79.8 547.2 972.8 801.8 1.691.0 1.417.4

HFC 227ea 0.0 0.0 72.5 133.4 89.9 0.0 0.0 0.0 0.0 0.0

Total HFC potential emissions 0.0 1,899.2 2,527.4 6,438.6 3,928.2 5,004.6 7,552.0 7,540.6 9,303.2 12,085.8

CF 4 0.0 0.0 55.8 158.6 167.4 183.9 186.1 148.9 159.9 141.3

C 2 F 6 0.0 0.0 65.5 147.9 164.5 134.0 114.7 111. 4 67.8 54.9

C 3 F 8 0.0 0.0 0.0 33.9 36.8 47.0 40.3 17.9 17.9 1.5

C 4 F 8 0.0 0.0 0.5 4.6 2.6 6.1 5.4 29.0 28.8 53.5

Total PFC
potential emissions 0.0 0.0 121.8 345.0 371.4 371.0 346.5 307.2 274.4 251.2

SF 6 3,752.3 3,675.8 3,919.6 5,903.3 3,689.2 3,211.2 2,9 43.2 1,541.8 2,182.9 1,985.9

Total F

- gas potential emissions 3,752.3 5,575.0 6,568.8 12,686.9 7,988.8 8,586.7 10,841.7 9,389.6 11,760.5 14,322.9

Table 4.15 Potential F

- gas emissions per compound from the consumption of halocarbons and SF 6 , in Gg CO

2 equi valent, 1990

– 2007



### 4.7.4. Source

- specific QA/QC and verification

This source category is covered by the general QA/QC procedures. Where information is available, emissions from production of halocarbons and SF 6 

### have been checked with data reported to th e
national EPER/E

- PRTR registry.

4.7.5. Source

- specific recalculations

Due to updated

information supplied by the main national company, FIAT, HFC 134a emissions from air conditioning equipments have been updated for 2006.
Moreover, semiconductor manufac turing industry has supplied updated data from 2004. Other minor modifications have regarded emissions from electrical equipments, due to updated data from main energy distribution companies from 2001.

In Table 4.16 recalculat ions from the previous subm ission are reported for each gas.

### 106

COMPOUND 2001 2002 2003 2004 2005 2006

HFC 23

HFC 32

HFC 125

HFC 134a 1.19%

HFC 143a

Total HFC emissions from refrigeration and air conditioning equipment

HFC 134a emissions from foam blowing

HFC 227ea emissions from fire extinguishers

HFC 134a emissions from aerosols/metered

dose inhalers
Total HFC emissions from ODS substitutes

HFC 23

- 2 .50%

- 2.50%

- 2.50%

HFC 134a

CF 4 14.04% 14.04% 14.04%

C 2 F 6

- 22.69%

- 22.69%

- 22.69%

C 3 F 8

- 18.60%

- 18.60%

- 18.60%

C 4 F 8

- 13.00%

- 13.00%

- 13.00%

SF 6 7.66% 7.66% 7.66%

Total PFC, HFC, SF 6

emissions from

semiconduc tor manufacturing

SF 6 emissions from electrical equipment 0.13% 0.73% 1.07% 1.59% 0.26% 4.46%

Total F

- gas emissions from consumption of

halocarbons and SF 6 0.01% 0.06% 0.07% 0.16%

- 0.06% 0.63%

Table 4.16 Comparison between recalculated and p revious F

- gas emissions from the consumption of halocarbons

and SF

6 per gas in percentage, 1990

- 2006



### 4.7.6. Source

- specific planned improvements

Further investigation is planned on account of the implementation of the European Regulation on these gases.

### 107



## Chapter 5: SOLVENT AND OTHER PRODUCT USE [CRF sector 3]

5.1 Overview of sector

In this sector all non

- combustion emissions from other industrial sectors than the manufacturing and energy industry are reported. The indirect CO 2 

### emissions, related to Non

- Methane Volatile Organic Compound (NMVOC) emissions from so lvent use in paint application, degreasing and dry cleaning, chemical products manufacturing or processing and other use, have been estimated.

N 2 

### O emissions from this sector have also been estimat ed. These emissions arise from the use of

N 2 

### O in medical applications, such as anaesthesia, and in food industry, where N 2 

### O is used as a propelling agent in aerosol cans, specifically those for whipped cream.

In 2007, solvent use is responsible for 0.29% of the total CO 2 

### emissions (excluding LULUCF) and

42.68% of total NMVOC emissions, and represents the second source of anthropogenic NMVOC

national emissions.

N 2 

### O emissions, in 2007, share 2.42% of the total N 2 

### O national emissions.

GAS/SUBSOURCE 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

NMVOC (Gg)

3A. Paint application 270.79 252.60 226. 07 229. 60 226. 37 221. 65 221. 30 219. 24 223. 47 224. 16

3B. Degreasing and dry cleaning 56.66 34.12 26.40 25.70 25.02 24.36 23.72 23.10 22.50 21.92

3C. Chemical products 77.21 88.25 103.64 89. 72 85

. 43 79

. 75 80

. 06 72. 70 78. 08 78. 53

3D. Other 185.23 170.13 156.21 160.19 167.61 174.23 176.80 184.82 188.43 190.43

CO 2 (Gg)

3A. Paint application 844.07 787.35 704.65 715.67 705.61 690.88 689.79 683.37 696.57 698.72

3B. Degreasing and dry
cleaning 176.62 106.34 82.27 80.09 77.98 75.93 73.94 72.01 70.14 68.33

3D. Other 577.36 530 .29 486.90 499.31 522.44 543.07 551.09 576.08 587.32 593.56

N 2 O (Gg)

3D. Other (use of N 2 O

for anaesthesia and
aerosol cans) 2.57 2.44 3.26 2.95 2.95 2.76 2.67 2.61 2.56 2.49
Table 5.1 Trend in NMVOC, CO 2 and N 2 O emissions from the solvent use sector, 1990

– 2007 (Gg)



### CO 2 

### emissions from the sector is a key source both for level and trend assessment calculated with the Tier 2 approach, especially because of the high level of uncertainty in the estimates and a reduction of emissions in the years. On the other hand, N 2 

### O emissions from the use of the gas in

anaesthesia and aerosol cans are a key source for trend assessment calculated with Tier 2 approach

too. Both these sources are not key categories if including the LULUCF sector in the uncertainty analysis. The results are reported in the following box.

Key

- source identification in th e solvent and other product use sector with the IPCC Tier1 and Tier2 approaches (without LULUCF)

3 CO 2 Solvent and other product use Key (L2, T2)

3D N 2 O Use of N 2 O in anaesthesia and aerosol cans Key (T2)

### 108

5.2 Source category description

In accord ance with the indications of the IPCC Guidelines (IPCC, 1997), the carbon contained in

oil

- based solvents, or released from these products, has been considered both as NMVOC and CO 2 

### emissions as final oxidation of NMVOC. Emissions from the following sub

- se ctors are estimated: solvent use in paint application (3A), degreasing and dry cleaning (3B), manufacture and processing of chemical products (3C), other solvent use, such as printing industry, glues application, use of domestic products (3D).

CO 2 

### emission

s have been estimated and included in this sector, as they are not already accounted for in the energy and industrial processes sectors.

N 2 

### O emissions from the use of N 2 

### O for anaesthesia and from aerosol cans (3D) have been

estimated. Emissions of N 2 

### O from fire extinguishers do not occur.

Emissions of N

2 

### O from other use of N 2 

### O (3D) have not been estimated because no information on activity data and emission factors is available at present.

5.3 Methodological issues

Emissions of NMVOC from solvent use hav e been estimated according to the methodology reported in the EMEP/CORINAIR guidebook , applying both national and international emission factors (Vetrella, 1994; EMEP/CORINAIR, 2005). Country specific emission factors provided by

several accredited sources have been used extensively, together with data from the national EPER Registry; in particular

, for paint application (Offredi, several years; FIAT, several years), solvent use in dry cleaning (ENEA/USLRMA, 1995), solvent use in textile finishing and in th e tanning industries (TECHNE, 1998; Regione Toscana, 2001; Regione Campania, 2005; GIADA 2006). Basic information from industry on percentage reduction of solvent content in paints and other products has been applied to EMEP/CORINAIR emission factors in or der to evaluate the reduction in emissions during the considered period. Emissions from domestic solvent use have been calculated using a detailed methodology, based on VOC content per type of consumer product. As regards household and car care products, i nformation on VOC content and activity data has been supplied by the Sectoral

Association of the Italian Federation of the Chemical Industry (Assocasa, several years) and by the Italian Association of Aerosol Producers (AIA, several years [ a ] and [ b ] ).

As regards cosmetics and toiletries, basic data have been supplied by the Italian Association of Aerosol Producers too (AIA, several years [ a ] and [ b ] ) and by the national Institute of Statistics and

industrial associations (ISTAT, several years [ a ]

, [ b ] , [c] and [d] ; UNIPRO, several years ); emission factors time series have been reconstructed on the basis of the information provided by the European Commission (EC, 2002). The conversion of NMVOC emissions into CO 2 

### emissions has been carried out considering tha t carbon content is equal to 85% as indicated by the European Environmental Agency for the CORINAIR project (EEA, 1997), except for CO 2 

### emissions from the

3C sub

- sector which are not calculated to avoid double

- counting. These emissions are, in fact,

alread y accounted for in sectors 1A2c and 2B.

Emissions of N

2 

### O have been estimated taking into account information available by industrial associations. Specifically, the manufacturers and distributors association of N 2 

### O products has supplied data on the use of N 2 

### O for anaesthesia from 1994 to 2008 (Assogastecnici, several years). For previous years, data have been estimated by the number of surgical beds published by national statistics (ISTAT, several years [a]).

Moreover, the Italian Association of Aerosol Pro ducers (AIA, several years [ a ] and [ b ] ) has provided data on the annual production of aerosol cans. It is assumed that all N 2 

### O used will eventually be released to the atmosphere, therefore the emission factor for anaesthesia is 1 Mg

### 109

N 2 

### O/Mg product use, whi le the emission factor used for aerosol cans is 0.025 Mg N 2 

### O/Mg product
use, because the N 2 

### O content in aerosol cans is assumed to be 2.5% on average (Co.Da.P., 2005).

N 2 

### O emissions have been calculated multiplying activity data, total quantity of N 2 

### O used for anaesthesia and total aerosol cans, by the related emission factors.

5.4 Uncertainty and time

- series consistency

The combined uncertainty in CO 2 

### emissions from solvent use is estimated equal to 58% due to an uncertainty by 30% and 50% in activity d ata and emission factors, respectively. For N 2 

### O emissions, the uncertainty is estimated equal to 51% due to an uncertainty in activity data of N 2 

### O use of 50%

and 10% in the emission factors.

The decrease in NMVOC emission levels from 1990 to 2007 is about 13%, mainly due to the reduction of emissions in degreasing and dry cleaning. The European Directives (EC, 1999; EC, 2004) regarding NMVOC emission reduction in this sector entered into force in Italy respectively in January 2004 and in March 2006, establi shing a reduction of the solvent content in products. Figure

5.1 shows emission trends from 1991 to 2007 wit h respect to 1990 by sub

- sector

. From 2000, the reduction in N 2 

### O emissions is due to a decrease in the anaesthetic use of N 2 

### O that has been replaced by halogen gas.

-80% -60% -40% -20% 0% 20% 40%

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Paint application Degreasing and dry cleaning Chemical products Other use of solvent

Figure 5.1 Trend of NM V OC emissions from 1991 to 2007 as compared to 1990



### 5.5 Source

- specific QA/QC and verification

Data production and consumption time series for some activities (paint application in constructions and buildings, polyester processing, polyurethane processing, pharmaceutical products, paints manufacturing, glues manufacturing, textile finishing, leather tanning, fat edible and non edible oil extraction, application of glues and adhesives) are checked with data acqu ired by the National
Statistics Institute (ISTAT, several years [ a ]

, [ b ] and [ c ] ), the Sectoral Association of the Italian Federation of the Chemical Industry (AVISA, several years) and the Food and Agriculture Organization of the United Nations (FAO, seve ral years).

### 110

In the framework of the MeditAIRaneo project, ISPRA (ex APAT) commissioned t o Techne Consulting S.r.l. a survey to collect national information on emission factors in the solvent sector. The results, published in the report “ Rassegna dei fattor i di emissione nazionali ed internazionali

relativamente al settore solventi ” (TECHNE, 2004), have been used to verify and validate the

emission estimates. At the end of 2008, ISPRA has commissioned to Techne Consulting S.r.l. a survey to compare emission factors with the last update published in the EMEP/CORINAIR guidebook (EMEP/CORINAIR, 2008 )

. The results are reported in “ Fattori di emissione per

l’utilizzo di solventi

” (TECHNE, 2008) and have been used to update e mission factors for

p olyurethane and p ol ystyrene foam processing activities

.

5.6 Source

- specific recalculations

In Table 5.2 the comparison for NMVOC between total recalculations and previous estimations is given in percentages from 1990 to 2006. No recalculations have been carried out for N 2 

### O

emissions

. For NMVOC, the main modification occurred 3C category where emission factors for the

p olyurethane and p olystyrene foam processing activities have been modified. These recalculation s
did not affect CO 2 

### emissions. Other modifications are due to the update of 2006 activity data , in particular, referring to the Pharmaceutical products manufacturing

, Paints manufacturing

, Glass

wool enduction

, Domestic solvent use and Vehicles dewaxing

, Paint application

- coil coating

, Leather tanning activity data for 2000 and Domestic solvent use average emission factor for 2004

- 2006.

SUBSOURCE

Year 3C. Chemical

products 3D. Other use of solvents

and related activities

1990 29

. 67% 0

. 00%

1991 43

. 70% 0

. 00%

1992 58

. 18% 0

. 00%

1993 73

. 63% 0

. 00%

1994 71

. 18% 0

. 00 %

1995 49

. 57% 0

. 00%

1996 48

. 47% 0

. 00%

1997 50

. 46% 0

. 00%

1998 53

. 21% 0

. 00%

1999 56

. 38% 0

. 00%

2000 70

. 03% 0

. 00%

2001 53

. 71% 0

. 00%

2002 47

. 72% 0

. 00%

2003 46

. 39% 0

. 00%

2004 51

. 05%

- 0

. 06%

2005 40

. 16%

- 0

. 05%

2006 43

. 63%

- 0

. 28%

Table 5.2 Differences between NMVOC emissions in the updated time series and the 2008 submission

### 111



## Chapter 6: AGRICULTURE [CRF sector 4]

6.1 Overview of sector

In this chapter information on the estimation of greenhouse gas (GHG) emissions from the Agriculture sector, as reported under the IPCC Category 4 in the Common Reporting Format 2



### (CRF), is given. Emissions from enteric fermentation (4A), manure management (4B), rice cultivation (4C), agriculture soils (4D) and field burning of agriculture residues (4F) are included in this sector. Methane (CH 4 

### ) and nitrous oxide (N 2 

### O) emissions are estimated and reported. Savannas areas (4E) are not present in Italy. Emissions from other sources (4G) have not been estimated. CO 2 

### and F

- gas emissions do not occur. To provide update inf

ormation on the characteristics of the agriculture sector in Italy

, figures from the Farm Structure Survey 2007 (FSS 2007) are reported . In Italy

, there are 1.7 millions of agricultural holdings with a Utilized Agricultural Area (UAA) of 12.7 million hecta re s , +0.3% more

than FSS 2005. Between 2000 (Agricultural Census) and 2007

, agricultural hol dings have decreased by 22% (474, 000 units). Moreover, at national level

, the average size of the agricultural holding s varied from 7.4 hectare in 2005 to 7.6 hecta res in 2007. With respect to 2000 Agricultural Census, holding s have gained 1.5 hectares of UAA. The distribution of agricultural holding s by type confirms a typical family conduction system which characterized the Italian agriculture. Direct

conduction of

holdings by farmers is around 1.6 million (93.9% of total agricultural holding s with UAA) which hold 10 million hectares of UAA (78.8% of total) (EUROSTAT, 2007[a], [b]; ISTAT, 2008[a]).

6.1.1 Emission trends

Emission trends per gas
In 2007, 6.7% o

f the Italian GHG e

missions

, without emissions and removals from LULUCF

, (7.9% in 1990) originated from the agriculture sector, which is the second source of emissions, after the energy sector (83%). For the agriculture sector, the trend of GHGs from 1990 to 20 07 shows a decrease of 8.3% due to reduction in activity data

, such as the number of animals and cultivated surface/crop production (see Figure 6.1). CH 4 

### a nd N

2 

### O emissions have decreased by 9.3% and 7.6%, respectively (see Table 6.1). In 2007, the agricult ure sector has been the dominant national

source for CH

4 

### and N 2 

### O emissions, sharing 40.9% and 67.8%, respectively.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Gg CO 2 eq.

CH 4 17,216 17,223 16,837 16,076 15,726 15,782 15,540 15,480 15,149 15,619

N 2 O 23,360 23,126 23,103 22,878 22,524 22,319 22,378 21,761 21,478 21,591

Total 40,576 40,349 39,940 38,954 38,250 38,102 37,917 37,242 36,627 37,210

Table 6.1 Emissions of GHG and trend from 1990 to 2007 for the Agriculture sector (Gg CO 2 eq.)

2 http://unfccc.int/national_report s/annex_i_ghg_inventories/national_inventories_submissions/items/4303.php

### 112 0 5.000 10.000 15.000 20.000 25.000 30.000 35.000 40.000 45.000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007CO2 eq. (Gg) CH4 N20

Figu re 6.1 Trend of GHG emissions for the Agriculture sector from 1990 to 2007 (Gg CO 2 eq.)



### Emission trends per sector

T otal GHG emissi

ons and trends by sub category from 1990 to 2007 are presented in Table 6.2 (expressed in Gg. CO 2 

### eq.). CH 4 

### emissions from e nteric fermentation (4A) and N 2 

### O emissions from direct agriculture soils (4D) are the most relevant source categories. In 2007, their individual share

in nation al GHG emissions without LULUCF w as 2.8 % and 3.9 %, respectively.

Table 6.2 Total GHG emissions and trend from 1990 to 2007 for the Agriculture sector

GHG emissions [Gg CO 2 e quivalent] by sub category Year

4A 4B 4C 4D 4F TOTAL

1990 12,179 7,383 1,562 19,435 17 40,576

1991 12,449 7,376 1,493 20,035 19 41,371

1992 12,071 7,081 1,551 20,142 18 40,862

1993 11,944 7,038 1,627 20,537 17 41,163

1994 12,051 6,920 1,664 19,989 18 40, 641

1995 12,267 7,068 1,657 19,340 17 40,349

1996 12,323 7,119 1,623 19,015 18 40,097

1997 12,377 7,138 1,615 20,004 16 41,150

1998 12,292 7,253 1,533 19,323 18 40,418

1999 12,429 7,344 1,497 19,508 17 40,795

2000 12,165 7,140 1,382 19,237 16 39,940

2001 11,340 7,342 1,382 18,875 15 38,954

2002 11,030 7,110 1,420 18,673 17 38,250

2003 11,056 7,067 1,463 18,500 15 38,102

2004 10,836 6,886 1,534 18,643 18 37,917

2005 10,844 6,877 1,472 18,032 17 37,242

2006 10,629 6,649 1,477 17,856 17 36,627

2007 11,027 6,853 1,523 17,791 17 37,210

### 113

6.1.2 Key categories

In 2007, CH

4 

### from enteric fermentation, N 2 

### O and CH

4 

### from manure management, and N 2 

### O from agricultural soils, both direct and indirect emissions were ranked among the top

- 10 level key sources with the Tier 2 analysis, including the uncertainty (L2). N 2 

### O from agricultural soils, both
direct and indirect emissions, and CH 4 

### enteric ferment ation are ranked among the top

- 10 trend key sources with the Tier 2 analysis, including the uncerta inty (T2). In the following box , key and non

key sources from the agriculture sector are shown

, with a level and/or trend assessment ( IPCC Tier

1 and Tier 2 approaches )

. These sources are also key categories when including the LULUCF sector in the analysis.

Key

- source identification in the agriculture sector with the IPCC Tier1 and Tier2 approaches

4A CH

4 Emissions from enteric fermentation Key (L, T)

4B CH

4 Emissions from manure management Key (L, T2)

4B N 2 O Emissions from manure management Key (L, T2)

4D1 N 2 O Direct soil emissions Key (L, T)

4D2 N 2 O Emissions from animal production Key (L2, T2)

4D3 N 2 O Indirect soil emissions Key (L, T 2 )

4C CH

4 Rice culti

vation Non

- key

4F CH

4 Emissions from field burning of agriculture residues Non

- key

4F N 2 O Emissions from field burning of agriculture residues Non

- key



### 6.1.3 Activities

Emission factors used for the preparation of the national inventory reflect the cha racteristics of the

Italian agriculture sector. Information from national research studies is considered. Activity data are mainly collected from the National Institute of Statistics (ISTAT, Istituto Nazionale di Statistica ). Every year, national and inter national references, and personal communications used for the preparation of the agriculture inventory are kept in the National References Database. Improvements for the Agriculture sector are described in the Italian Quality Assurance/Quality Control plan

(ISPRA, 2009). Moreover, a n internal report describes the procedure for preparing the agriculture UNFCCC/CLRTAP national emission inventory ( Cóndor, 2009)

. In the last years, results

from different research project s have improved the quality of the agric ulture national inventory (

MeditAIRaneo project and convention signed between ISPRA and the Ministry for the Environment, Land and Sea). Furthermore, suggestions from the inventory review process es have been considered (ISPRA, 2009; UNFCCC, 2009). Methodol ogies for the preparation of agriculture national inventory under the Convention on Long

- Range Transboundary Air Pollution (CLRTAP) and the United Nations Framework Convention on Climate Change (UNFCCC) are kept

consistent. S ynergies among international co nventions and European directives while preparing the agriculture invent ory are implemented (Cóndor et al ., 2008[b]; Cóndor et al ., 2007[b]; Cóndor and
De Lauretis, 2007; Cóndor, 2006). The national agriculture UNFCCC/CLRTAP emission inventory is used eve ry 5 years to prepare a more disaggregated inventory by region and provin ce as requested by CLRTAP (Cóndor et al

., 2008[c]). A database with the time series for all sectors and pollutants has been published (ISPRA,
2008[a], [b]). Furthermore, the same meth odologies are used for estimating emission scenario s and projections for the years 2010, 2015 and 2020 (MINAMBIENTE, 2007).

6.1.4 Agricultural statistics

The Italian National Statistical System (SISTAN 3 

### ) revises every year the National Statistical Plan that covers three years and includes the system of agricultural statistics among others. In this

3 SISTAN, Sistema Statistico Nazionale (http://www.sistan.it/)

### 114

framework, the Agriculture , Forestry and Fishing Quality Panel has been established under

coordination of the Agriculture service of ISTAT, where the produce rs and use rs of agricultural

statisti cs (mainly public institutions) meet every year in order to monitor and improve national statistics. Among those producing statistics, ISTAT plays a major role in the agricultural sector collecting comprehensive data thro ugh different surveys as reported by Greco and Martino (2001):

• Structural surveys (Farm Structure Survey, survey on economic results of the farm, survey on the production means) ;

• Conjunctural surveys 4 

### (survey on the area and production of the cultivation, livestock number, milk production, slaughter, etc.) ;

• General Agricultural Census 5



### , carried out every 10 years (1990, 2000, 2010)

.

Detailed information on the agriculture sector is found every two years in the Farm Structure Survey

– FSS 6 

### (ISTAT, 2008[a]; ISTAT, 2007[a]; ISTAT, 2006[a]). Furthermore, the quality

report s of the FSS 2005 and FSS 2007 ha ve been obtained from ISTAT (ISTAT, 2008[b]; ISTAT, 2007[e]). The m

ain agricultural statistics sources, used in the agriculture emission inventory, are

availab le online, as reported in the following box:

Main activity data sources used for the Agriculture emission inventory

Agricultural statistics Time series Web site

Livestock number Table 6.3; 6.4; 6.7 http://www.istat.it/agricoltura/datiagri/consistenza/

Milk production Table 6.3 http://www.istat.it/agricoltura/datiagri/latte/

Fertilizers Table 6.30 http://www.istat.it/agricoltura/datiagri/mezzipro/

Crops production/surface Table 6.26; 6.32; 6.33 http://www.istat.it/agricoltura/datiagri/coltivazioni/



### 6.2. Enteric fermentation (4A)

6.2.1. Source category description

Methane is produced as a by

- product of enteric fermentation, which is a digestive process where carbohydrates are degraded by microorganisms into simple molecules.

Methane emissions from enteric fermentation are a major key source, both in terms of level and trend for Tier 1 and Tier 2 approaches. All livestock categories have been estimated except camels and llamas, which are not present in Italy. Methane emissions from poultry do not occ ur, and emissions from rabbits are estimated and included in “Other” as suggested by IPCC guidelines. In
2007, CH

4 

### emissions from this category were 525.07 Gg, which repres ent 70.6% of CH 4 

### emissions for the agriculture sector (70.7% in 1990) and 28.9% for national CH 4 

### emissions (29.2% in 1990). Methane emissions from this source mainly consist of cattle emissions: dairy c attle (208.13 Gg) and

non

- dairy cattle (205.03 Gg); these sub

- categories sources represented 39.6% (42.3% in 1990) and
39.0% (40.2% in 199 0), respectively, of total enteric fermentation emissions.

6.2.2. Methodological issues

Methane emissions from enteric fermentation are estimated by defining an emission factor for each livestock category, which is multiplied by the population of the sa me category. Data for each livestock category are collected from ISTAT (several years [a], [b], [c], [f]; ISTAT, 1991; 2009[a]; 2007[a],[b]). Livestock categories provided by ISTAT are classified according to the type of production, slaughter or breeding, and the age of animals. In Table 6.20, activity data for the

4 http://www.istat.it/agricoltura/datiagri/

5 http://www.census.istat.it/

6 Indagine sulla struttura e produzione delle aziende agricole (SPA), survey carried out every two years in agricultural farms.

### 115

livestock categories are shown. In the following box, livestock categories and source of information are provided. In order to have a consistent time series, it was necessary to reconstruct the n umber of animals for some categories. Reconstruction used information available from other official sources
such as FAO (2009) and UNA (2009).

Activity data for the different livestock categories

Livestock category Source

Cattle ISTAT

Buffalo ISTAT

She ep ISTAT

Goats ISTAT

Horses ISTAT/FAO(a)

Mules and asses ISTAT/FAO(a)

Swine ISTAT

Poultry ISTAT/UNA(b)

Rabbits ISTAT(c )

(a) Reconstruction of a consistent time series
(b) For 1990 data from the census and reconstruction for brood

- rabbits and other rabbits based on meat production (UNA, 2009)
(c) For 1990 data from the census and reconstruction based on a production index (ISTAT, 2009[f]; 2007[b])



### Dairy cattle

Methane emissions from enteric fermentation for dairy cattle are estimated using a Tier 2 approach, as suggested in the Good Practice Guidance (IPCC, 2000). Feeding characteristics are described in a national publication (

CRPA, 2004[a]) and have been discussed in a specific working group, in the framework of the MeditAIRaneo project (CR PA, 2006[a]; CRPA, 2005) . Parameters used for the calculation of the emission factor are presented in the following box:

Parameters for the calculation of dairy cattle emission factors from enteric fermentation

Parameters Value Reference

Average weight (kg) 602.7 CRPA, 2006

Coefficient NEm (dairy cattle) 0.335 NRC, 2001; IPCC, 2000

Pasture (%) 5 CRPA, 2006[a]; ISTAT, 2003

Weight gain (kg day

- 1 ) 0.051 CRPA, 2006[a]; CRPA, 2004[b]

Milk fat content (%) 3.59

- 3.71 ISTAT, several years [a], [b], [d], [e]; ISTAT, 2009[b]

Hours of work per day 0 CRPA, 2006

Portion of cows giving birth 0.90

- 0.97 AIA, 2009

Milk production (kg head

- 1 day

- 1 ) 11.5

- 17.4 CRPA, 2006[a]; ISTAT, 2009[b]; OSSLATTE/ISMEA, 2003; ISTAT, several years [a], [b], [c] [d], [e],
[f];OSSLAT TE, 2001 Digestibility of feed (%) 65 CRPA, 2006[a]; CRPA, 2005

Methane conversion rate (%) 6 CRPA, 2006

MJ/kg methane 55.65 IPCC, 2000



### In a national publication, an analysis of the different milk production statistics has been described (Cóndor et al ., 2005). Milk used for dairy production and milk used for calf feeding contributes to total milk production. This value has been reconstructed with national and ISTAT publications, as well as personal communication with ISTAT (ISTAT, 2009[e]). For calc ulating milk production (kg

head

- 1 

### d

- 1 

### ), total production has been divided by the number of animals and by 365 days, as suggested by the IPCC (2000). Therefore, lactating and non

- lactating periods are included in the

estimation of the CH 4 

### dairy cattle EF (

CRPA, 2006[a]). In Table 6.3, the time series of the dairy cattle population, fat content in milk, portion of cows giving birth and milk production are

### 116

presented. Further information on parameters used for dai ry cattle estimations with the T ier 2 approach are found in Annex 5.1.

In Table 6.6, the time series of the dairy cattle emission factors (EF) is presented. In 2007, the CH 4 

### dairy cattle EF was 113.19 kg CH 4 

### head

- 1 

### year

- 1 

### with an average milk production of 6,3 2 0 kg head

- 1



### year - 1 

### (17.3 kg head

- 1 

### day

- 1 

### ) . This value is close to the default EF of 109 kg CH 4 

### head

- 1 

### year - 1 

### with a milk production of 6,000 kg head

- 1 

### year - 1 

### reported by the IPCC (2006).

Table 6.3 Parameters used for the estimation of the CH 4 emission factor for dairy cattle



### Non

- dairy cattle

For non

- dairy cattle, CH

4 

### emissions from enteric f ermentation are estimated with a Tier 2 approach (IPCC, 2000). The estimation of the EF uses country

- specific data, disaggregated livestock categories (see Table 6.4), and is based on dry matter intake (kg head

- 1 

### day

- 1 

### ) calculated as percentage of live wei

ght (CRPA, 2000; INRA, 1988; NRC, 1984; NRC, 1988; Borgioli, 1981; Holter and Young, 1992; Sauvant, 1995). Dry matter intake is converted in to gross energy (MJ

head

- 1 

### day

- 1 

### ) using 18.45 MJ/kg dry matter (IPCC, 2000). Emission factors for each category have been calculated with equa tion 4.14 from IPCC (2000). In T able 6.5, parameters used for the

estimation of non

- dairy cattle EF are shown. Since 2006 submission, average weights have been updated with information from the Inter

- regional project on nitrogen b alance project (CRPA, 2006[a]; Regione Emilia Romagna, 2004).

For reporting purposes, some animal categories are aggregated, such as the non

- dairy and swine categories. For example, the non

- dairy cattle category is composed of the different sub

- categories as shown in Table 6.4. For this reason, the gross energy intake, CH 4 

### conversion factor and EFs for this category are calculated as a weighted average. Year Dairy cattle

(head) Fat content in milk

(%) Portion of cows

giving birth Milk production yield
(kg hea d

- 1 d - 1 )

1990 2,641,755 3.59 0.973 11.5

1991 2,339,520 3.59 0.971 13.0

1992 2,146,398 3.59 0.961 13.9

1993 2,118,981 3.63 0.955 13.8

1994 2,011,919 3.64 0.963 14.5

1995 2,079,783 3.64 0.948 14.8

1996 2,080,369 3.65 0.948 15.2

1997 2,078,388 3.66 0. 946 15.5

1998 2,116,176 3.71 0.931 15.3

1999 2,125,571 3.69 0.919 15.3

2000 2,065,000 3.65 0.926 15.1

2001 2,077,618 3.65 0.915 14.9

2002 1,910,948 3.67 0.913 16.2

2003 1,913,424 3.67 0.913 16.2

2004 1,838,330 3.71 0.899 16.8

2005 1,842,004 3.71 0. 910 17.2

2006 1,821,370 3.69 0.901 17.4

2007 1,838,783 3.71 0.897 17.3

### 117

Table 6.4 Non

- dairy cattle population classified by type of production and age

<1 year 1

- 2 years

Males 1

- 2 years

Females >2 years

Males >2 years Females

Parameters Others(*
) breedin

g for
slaught

er breeding for

slaughter all br eeding for
slaughter Others

Average weight (kg) 236 557 557 405 444 700 540 540 557

Percentage weight ingested 2.0 1.9 2.1 2.1 2.1 2.4 2.1 2.1 1.9

Dry matter intake (kg head -

1 day - 1 ) 4.8 10.7 11.6 8.5 9.3 17.1 11.5 11.5 10.6

Gross Energy (MJ head - 1 day - 1 ) 89.4 197.31 214.78 156.92 171.21 315.50 212.18 212.18 195.26

CH 4 conversion (%) 4 4.5 4 6 4 6 6 6 6

(*) It has been considered that calves for slaughter of <1 year, do not emit CH 4 emissions, as they are milk fed. Therefore, the average weight for th e category “others” of <1 year take into account fattening male cattle, fattening heifer and heifer for replacement. Table 6.5 Main parameters used for non

- dairy cattle CH 4 emission factor estimations



### National characteristics of Italian breeding are ref lected in EFs and are also related to the age classification of animals and dry matter intake. In T able 6.6, implied emission factors (IEF) for non

dairy cattle are shown. In 2007, the non dairy

- cattle EF was 46.13 kg CH 4 

### head

- 1 

### year - 1 

### while IPCC

default E F is 48 kg CH

4 

### head

- 1 

### year - 1 

### (IPCC, 1997). The interannual decrease 2005/2006 of the IEF

for non

- dairy cattle is related to the reduction in the number of animals for some categories (see Table 6.4) and increase of the ‘ less than 1 year ’ for the slaughter category (no emissions).

<1 year 1

- 2 years Males 1

- 2 years Females >2 years

Males >2 years Females

Year for slaughter ot hers breedin

g for slaughter breeding for

slaughter all breedin

g for slaughter others TOTAL

1990 300,000 2,127,959 72,461 708,329 749,111 186,060 128,958 467,216 57,654 312,649 5,110,397

1991 300,000 2,060,091 71,191 732,421 1,077,802 197,078 82,957 498,136 5 9,281 503,041 5,581,998

1992 300,000 2,036,527 65,656 654,622 1,019,928 197,507 102,182 464,814 49,749 534,632 5,425,617

1993 300,000 2,002,856 63,214 639,922 995,481 175,146 95,929 449,996 47,921 551,683 5,322,148

1994 300,000 1,794,806 63,926 651,708 1,040,424 145,475 107,640 451,864 31,569 569,429 5,156,841

1995 458,936 1,796,034 27,871 783,300 684,881 154,548 155,116 430,564 40,198 657,856 5,189,304

1996 405,986 1,802,849 29,877 721,711 700,560 166,137 119,478 416,038 34,167 696,760 5,093,563

1997 354,006 1,910,283 62,983 600,315 699,133 160,238 162,187 413,383 63,765 668,553 5,094,846

1998 392,432 1,865,075 25,454 611,973 677,915 166,266 115,269 413,456 60,962 684,530 5,013,332

1999 385,251 1,807,169 28,133 655,749 708,152 179,488 101,922 410,06 2 46,392 713,872 5,036,190

2000 408,000 1,783,000 27,521 641,479 736,000 160,000 93,000 500,000 51,000 588,000 4,988,000

2001 496,264 1,498,068 25,528 595,029 709,941 181,550 75,365 591,000 46,000 442,525 4,661,270

2002 409,970 1,617,127 26,194 610,550 647,656 176,481 65,948 541,233 59,582 444,408 4,599,149

2003 412,682 1,594,994 27,598 643,277 673,246 158,094 78,890 520,237 48,873 433,388 4,591,279

2004 445,231 1,509,387 28,458 663,316 648,308 149,053 71,762 460,765 38,385 451,606 4,466,271

2005 500, 049 1,418,545 26,424 615,921 588,660 181,971 102,081 466,566 37,971 471,733 4,409,921

2006 540,223 1,407,401 26,091 608,152 584,680 182,719 78,328 395,066 54,022 419,083 4,295,765

2007 519,034 1,410,357 26,852 625,902 593,369 189,704 79,936 498,091 59,96 1 440,845 4,444,051

### 118

Buffalo

Data collected in the framework of the MeditAIRaneo project have allowed the implementation of the Tier2 approach for the buffalo category (IPCC, 2000). Two different country specific CH 4 

### EFs,

for cow buffalo and other buffaloes have been developed . Detailed description of the methodology, parameters and assumptions are reported in Cóndor et al . (Cóndor et al ., 2008 [a] ). In 2007, the cow

buffalo CH

4 

### EF was 73.50 kg CH 4 

### head

- 1 

### year - 1 

### and for other buffaloes the value was 56.0 kg CH 4 

### head

- 1 

### year

- 1



### . The IEF in the CRF is an average EF for the buffalo category (67.08 kg CH 4 

### head

- 1



### year - 1 

### ).

In the following boxes, parameters used for the Tier 2 approach are presented:

Parameters for the calculation of CH 4 cow buffalo emissi on factors from enteric fermentation

Parameters Value Reference

Average body weight (kg) 630 Infascelli, 2003; Consorzio per la tutela del formaggio mozzarella di bufala campana, 2002
Coefficient NEm, cattle/buffalo (lactating) 0.335 IPCC, 2000

Pasture (%) 2.90 ISTAT, 2003; Zicarelli, 2001; expert judgement

Weight gain (kg day

- 1 ) 0.27 Estimations

Milk fat content (%) 7.7

- 8.1 ISTAT, several years [a], [b], [d], [e]; ISTAT, 2009[b]

Hours of work per day 0 Our estimation

Proportion of calving cows 0.84

- 0.89 Barile, 2005; De Rosa and Trabalzi, 2004

Milk production (kg head

- 1 day

- 1 ) 1.9

- 4.4 ISTAT, 2009[b]; OSSLATTE/ISMEA, 2003; ;OSSLATTE, 2001; ISTAT, several years [a], [b], [c] [d], [e], [f]
Digestibility of feed (%) 65 Infascelli, 2003; Masucci et al ., 1997, 1999;

Methane conversion rate (%) 6 CRPA, 2006

MJ/kg methane 55.65 IPCC, 2000

Parameters for the calculation of other buffalo emission factors from enteric fermentation

Parameter Calves
(3 months

- 1 year) Sub

- adult buffaloes
(1

- 3 years)

Ave rage body weight (kg) 130 405

Dry matter intake (% of body weight head

- 1 day

- 1 ) 3.0 2.5

Dry matter intake (kg head

- 1 day

- 1 ) 3.9 10.1

Gross Energy (MJ head

- 1 day

- 1 ) 71.68 186.58

CH 4 conversion (%) 6 6

CH 4 emission factor (kg head

- 1 year - 1 ) 21.16 (*) 73.42

(*) original CH

4 emission factor was 28.208 kg CH4 head

- 1 year -

1 ; a correction factor of 9/12 has been applied in order to consider the time between 3 months and 1 year, therefore the final emission factor was 21.16 kg CH 4 head

- 1 year -

1

.



### Rabbits

M ethane emissions from rabbits have been estimated using a country

- specific EF suggested by the Research Centre on Animal Production (CRPA). Daily dry matter intake for brood

- rabbits and rabbits are 0.13 kg day

- 1 

### and 0.11 kg day

- 1 

### , respectively. Besides, 0. 6% as CH 4 

### conversion rate has been assumed (CRPA, 2004[c]).

Other livestock categories

A Tier 1 approach, with IPCC default EFs, has been used to estimate CH 4 

### emissions from swine, sheep, goats, horses, mules and asses (IPCC, 1997). In Table 6.6, emissi on factors for all livestock categories (dairy cattle, non

- dairy cattle, buffalo, swine, sheep, goats, horses, mules and asses, and rabbit) are presented. In Table 6.7, time series from livestock number are shown.

### 119

Table 6.6 Average CH 4 emission factors for enteric fermentation (kg CH 4 head - 1 year - 1 )

Tab le 6.7 Ti me series of number of animals from 1990 to 2007 Year Dairy

cattle Non

dairy

cattle Buffa

lo Sheep Goats Horses Mules

and asses Sows Other

swine Rabbits

1990 92.8 45.6 61.7 8.0 5.0 18.0 10.0 1.5 1.5 0.08

1991 97.7 47.5 62.9 8.0 5.0 18.0 10.0 1.5 1.5 0.08

1992 100.9 47.5 62.4 8.0 5.0 18.0 10.0 1.5 1.5 0.08

1993 100.6 47.4 65.5 8.0 5.0 18.0 1 0.0 1.5 1.5 0.08

1994 103.4 48.7 65.6 8.0 5.0 18.0 10.0 1.5 1.5 0.08

1995 104.3 47.4 63.2 8.0 5.0 18.0 10.0 1.5 1.5 0.08

1996 105.8 47.5 62.4 8.0 5.0 18.0 10.0 1.5 1.5 0.08

1997 106.7 47.8 62.9 8.0 5.0 18.0 10.0 1.5 1.5 0.08

1998 106.4 47.0 62.0 8.0 5 .0 18.0 10.0 1.5 1.5 0.08

1999 106.3 47.3 64.9 8.0 5.0 18.0 10.0 1.5 1.5 0.08

2000 105.3 47.0 65.7 8.0 5.0 18.0 10.0 1.5 1.5 0.08

2001 104.6 46.7 68.2 8.0 5.0 18.0 10.0 1.5 1.5 0.08

2002 109.1 46.5 66.4 8.0 5.0 18.0 10.0 1.5 1.5 0.08

2003 109.0 46.6 6 6.2 8.0 5.0 18.0 10.0 1.5 1.5 0.08

2004 111.5 46.3 68.3 8.0 5.0 18.0 10.0 1.5 1.5 0.08

2005 112.9 46.4 71.0 8.0 5.0 18.0 10.0 1.5 1.5 0.08

2006 113.24 44.7 69.7 8.0 5.0 18.0 10.0 1.5 1.5 0.08

2007 113.19 46.1 67.1 8.0 5.0 18.0 10.0 1.5 1.5 0.08

Year Buffalo Sheep Goats Horses Mules

and

asses Sows Other

swine Rabbits Poultry

1990 94,500 8,739,253 1,258,962 287,847 83,853 650,919 7,755,602 14,893,771 173,341,562

1991 83,300 8,397,070 1,260,980 314,125 66,255 711,500 7,837,300 15,877,391 173,060,622

1992 103,200 8,460,557 1,355,485 315,848 56,946 691,400 7,553,000 16,398,563 172,683,589

1993 100,900 8,669,560 1,408,767 323,305 49,383 702,900 7,645,200 16,530,691 173,261,404

1994 108,300 9,964,108 1,658,051 323,986 43,063 677,100 7,346,300 16,905,054 178,659,192

1995 148,404 10,667,971 1,372,937 314,778 37,844 689,846 7,370,830 17,110,587 184,202,416

1996 171,558 10,943,457 1,419,225 312,080 34,120 726,155 7,44 4,937 17,433,566 183,044,930

1997 161,491 10,893,711 1,351,003 313,000 30,000 693,366 7,599,426 17,609,737 186,815,499

1998 186,276 10,894,264 1,331,077 290,000 33,500 707,644 7,614,981 17,705,163 198,799,819

1999 200,481 11,016,784 1,397,329 288,000 33 ,000 691,590 7,722,893 18,020,802 196,573,062

2000 192,000 11,089,000 1,375,000 280,000 33,000 708,000 7,599,000 17,873,993 176,722,211

2001 193,774 8,311,383 1,024,769 285,000 33,000 697,491 8,068,771 18,343,782 209,187,654

2002 185,438 8,138,309 987,8 44 277,819 28,913 751,159 8,415,099 18,505,272 205,524,395

2003 222,268 7,950,981 960,994 282,936 28,507 736,637 8,420,087 18,226,335 196,511,409

2004 210,195 8,106,043 977,984 277,767 28,932 724,891 8,247,181 21,199,217 191,315,963

2005 205,093 7,954,1 67 945,895 278,471 30,254 721,843 8,478,427 22,153,475 188,595,022

2006 230,633 8,227,185 955,316 287,123 31,013 771,751 8,509,352 21,801,133 177,535,443

2007 293,947 8,236,668 920,085 315,725 34,557 753,721 8,519,214 22,748,051 188,871,886

### 120

6.2.3. Uncertainty and time

- series consistency

Uncertainty related to CH 4 

### emission

s from enteric fermentation was 28% for annual emissions, resulting from the combination of 20% of uncertainty for both ac tivity data and emission factors.
In 2007, livestock CH 4 

### emissions from enteric fermentation have been 9.5% (525.07 Gg) lower than in 1990 (579.93 Gg), while from 1990 to 2007 cattle livestock has decreased by 19% (from 7,752,152 to 6,282,834 heads). Dairy cattle and non

- dairy cattle have decreased by 30.4% (from 2,641,755 to 1,838,783) and 13 % (from 5,110,397 to 4,444,051), respectively. The decrease in cattle number is driving down CH 4 

### emissions, particularly as emissions per head from cattle are 10

times greater than emissions per head of sheep or goat. In 2007, cattle contribute with 82.4% to total

CH 4 

### emissions from enteric fermentation. In Table 6.8, emission trends from the enteric fermentation category are shown. Emissions from swine, as reported in the CRF submission 2009 are represented by other swine and sow category (13.91 Gg).

Year Dairy

cattle Non

dairy

cattle Buffalo Sheep Goats Horses Mules

and asses Sows Other

swine Rabbits TOTAL

1990 245.11 233.00 5.83 69.91 6.29 5.18 0.84 0.98 11.63 1.16 579.93

1991 228.61 265.10 5.24 67.18 6.30 5.65 0.66 1.07 11.76 1.23 592.81

1992 216.49 257.52 6.44 67.68 6.78 5.69 0.57 1.04 11.33 1.27 574.81

1993 213.23 252.38 6.61 69.36 7.04 5.82 0.49 1.05 11.47 1.28 568.74

1994 207.94 251.21 7.10 79.71 8.29 5.83 0 .43 1.02 11.02 1.31 573.87

1995 216.88 246.22 9.38 85.34 6.86 5.67 0.38 1.03 11.06 1.33 584.15

1996 220.10 241.79 10.71 87.55 7.10 5.62 0.34 1.09 11.17 1.35 586.80

1997 221.80 243.78 10.15 87.15 6.76 5.63 0.30 1.04 11.40 1.37 589.39

1998 225.18 235.38 11.54 87.15 6.66 5.22 0.34 1.06 11.42 1.38 585.33

1999 225.85 238.33 13.00 88.13 6.99 5.18 0.33 1.04 11.58 1.40 591.84

2000 217.40 234.48 12.61 88.71 6.88 5.04 0.33 1.06 11.40 1.39 579.30

2001 217.22 217.91 13.22 66.49 5.12 5.13 0.33 1.05 12.10 1.42 539 .99

2002 208.45 213.95 12.31 65.11 4.94 5.00 0.29 1.13 12.62 1.44 525.24

2003 208.65 214.17 14.71 63.61 4.80 5.09 0.29 1.10 12.63 1.42 526.47

2004 204.92 206.60 14.36 64.85 4.89 5.00 0.29 1.09 12.37 1.65 516.01

2005 207.95 204.65 14.57 63.63 4.73 5.01 0.30 1.08 12.72 1.72 516.37

2006 206.26 192.10 16.08 65.82 4.78 5.17 0.31 1.16 12.76 1.69 506.13

2007 208.13 205.03 19.72 65.89 4.60 5.68 0.35 1.13 12.78 1.77 525.07

Table 6.8 Trend of

CH 4 emissions from enteric fermentation (Gg)



### 6.2.4. Source

- specifi c QA/QC and verification

Since 2006 submission, results from the MeditAIRaneo project focus ing on the assessment of critical points of the enteric fermentation category have been incorporated (CRPA, 2006[a]; Valli et

al ., 2004). In Table 6.9, a list of pa rameters from the QA/QC plan is reported

.

6.2.5. Source

- specific recalculations

For the whole time series some corrections have been identified: a parameter used for calculating the cow buffalo EF, the average weight of the category of ‘ less than 1 year ’ for slaughter, and the Bo parameter for the buffalo category.

### 121

In Table 6.10, new and old dairy cattle and buffalo EFs, from 2008 and 2009 submissions, are

shown.

Year of

submission Sub

category Parameter

2009 2010 Activities

Dairy cattle Fat conte nt v Data from 2007 fat parameter has been collected (ISTAT web
site) Dairy cattle Portion cow

giving birth v Data from 2007 has been collected (AIA, 2008)

Dairy

cattle/buffalo Milk

production v Data from 2007 on milk production has been collected (IS TAT
web site)
Table 6.9 Improvements for the enteric fermentation category according to the QA/QC plan

Table 6.10 Dairy cattle and buffalo CH 4 emission factors for the enteric fermentation category (kg head - 1 year - 1 )



### 6.2.6. Source

- specific planned improvements

In the framework of collaboration between ISPRA ( former APAT ) and ISTAT (Agriculture Service) we expect to continuosly update and improve activity data.

6.3. Manure management (4B)

6.3.1 Source category description

In 2007, CH

4 

### emissions from manure management were 145.57 Gg, which represents 19.6% of CH 4 

### emissions for the agriculture sector (20.1% in 1990) and 8.0% of national CH 4 

### emissions (8.3% in Dairy cattle Buffalo

Year EF 2008 submission EF 2009 submission EF 2008 submission EF 2009 submission

1990 92.8 92.8 61.7 61.7

1991 97.7 97.7 62 .9 62.9

1992 100.9 100.9 62.4 62.4

1993 100.6 100.6 65.5 65.5

1994 103.4 103.4 65.6 65.6

1995 104.3 104.3 63.2 63.2

1996 105.8 105.8 62.4 62.4

1997 106.7 106.7 62.9 62.9

1998 106.4 106.4 62.0 62.0

1999 106.3 106.3 64.9 64.9

2000 105.3 105.3 65.7 6 5.7

2001 104.6 104.6 68.2 68.2

2002 109.1 109.1 66.4 66.4

2003 109.0 109.0 66.2 66.2

2004 111.5 111.5 68.3 68.3

2005 112.9 112.9 71.0 71.0

2006 113.2 113.2 69.7 69.7

2007 113.2 67.1

### 122

1990). CH

4 

### emissions from swine were 66.42 Gg and from cattle 56.33 Gg; these sub

- categories

rep resented 45.6% and 38.7% of total CH 4 

### manure management emissions, respectively.
In 2007, N

2 

### O emissions from manure management were 12.25 Gg, which represents 17.6% o f total

N 2 

### O emissions for the agriculture sector (16.8% in 1990) and 11.9% of national N

2 

### O emissions (10.5% in 1990). In 2007, N 2 

### O emissions from this source mainly consist o f the solid storage source (10.79 Gg), which accounts for 88.1% of the N 2 

### O manure management source. Since the 2006 submission, parameters related to the estimation of CH 4 

### and N 2 

### O emissions have been updated: average weight, production of slurry and solid manure and the nitrogen excretion

rates. The source of the updating has been the I nter

- regional project on nitrogen balance and other

national research studies. In this section references are provided. Methane and nitrous oxide emissions from manure management are key sources. Nitrous oxide emissions are key sources at level for Tier 1 and Tier 2, and trend assessment (Tier 2), while CH 4 

### emissions are key sources at level for Tier 1 and Tier 2, and Tier 2 trend assessment.

6.3.2. Methodological issues

The IPCC Tier 2 approach has been used for estimating CH 4 

### EFs for manure management of cattle, buffalo and swine. For estimating slurry and solid manure EFs and the specific conversion factor, a detailed methodology ( Method 1 ) has been applied at a regional basis (cattle and buffalo categories). Then, a simplified methodology, for estimat ing EF time series, has been followed ( Method 2 ). Livestock population activity data are collected from ISTAT (see Table 6.3; Table 6.4;

Table 6.7).

Methane emissions (cattle and buffalo)

Method 1: Regional basis

Methane emissions estimations for manur e management are drawn up on a regional basis and depend on specific manure management practices and environmental conditions (Safley et al

., 1992; Steed and Hashimoto, 1995; Husted, 1994). In particular, the following factors are used: average regional mo nthly temperatures (UCEA, 2008), amount of slurry and solid manure produced per livestock category (CRPA, 2006[a]; Regione Emilia Romagna, 2004) and management techniques for the application of slurry and solid manure for agricultural purposes in Italy (CR PA,
1993). For cattle and buffalo, the estimation of the EF begins with the calculation of the methane emission

rate (g CH

4 

### m - 3 

### day

- 1 

### ), which is obtained from an equation presented for slurry (Husted, 1994) and
solid manure (Husted, 1993). Then the methan e emission rate is transformed to g m

- 3 

### month

- 1 

### . The equations used are presented below (CRPA, 2006[a]; CRPA, 1997[a]): For slurry:

CH 4 

### (g m
- 3 

### day

- 1 

### ) = e (0.68+0.12*average regional monthly temperature) 

### Eq. 6.1

For solid manure:

CH 4 

### (g m
- 3 

### day

- 1 

### ) = e (- 2.3+0. 1* monthly storage temperature) 

### Eq. 6.2 The monthly storage temperature from the solid manure is estimated with the following equation
(Husted, 1994):

T solid manure storage = 6,7086e 0. 1014t (°C) (average regional monthly temperature)



### For temperatures below 10°C emissions are considered negligible.

### 123

The volume of slurry and solid manure produced per livestock category was obtained (m 3 

### head

- 1 

### )

with the average production of slurry and solid manure per livestock category per day (m 3 

### head

- 1



### day

- 1 

### ) and the days of storage of slurry and solid manure. These days are related to the temporal application dynamics of slurry and solid manure under Italian conditions (CRPA, 1997[a]). On the other hand, the production of solid manure and slurry have b een estimated assuming a distribution of housing systems in Italy, which will be updated with information coming from the Farm Structure Survey (

FSS) 2005 . Emission factors for slurry and solid manure (g CH 4 

### head

- 1 

### month

- 1 

### )
are calculated for each month, a nd are obtained with the methane emission rates (Eq. 6.1 and 6.2), and the volume of slurry and solid manure produced. The annual EF for each livestock category is the sum of slurry and solid manure EFs (kg CH 4 

### head

- 1 

### year - 1 

### ). Then, to correlate CH 4 

### emissi on production and volatile solid (VS) production a specific conversion factor has been estimated. Later, this factor is used for the simplified methodology ( Method 2 ). The specific conversion factor values for slurry and solid manure are 15.32 g CH 4 

### /kg VS and 4.80 g CH 4 

### /kg VS, respectively.

Method 2: National basis

A simplified methodology ( Method 2 ) for estimating methane EFs from manure management has been used for the whole time series. Slurry and solid manure EF s (kg CH 4 

### head

- 1 

### year - 1 

### ) have been

calc ulated with Equations 6.3 and 6.4, respectively. These equations include the specific conversion factor, previously estimated on a regional basis. Furthermore, the production of volatile solids (kg

head

- 1 

### day

- 1 

### ) has been estimated with the slurry and solid manure production, and the factors proposed by Husted: 47g VS/kg (slurry) and 142 g VS/kg, (solid manure). The daily VS excreted, estimated for slurry and solid manure, are summed and used for estimating the methane producing potential (Bo). In Table 6.11, EF estimations are presented.

EF slurry = 15.32 gCH 4 

### /Kg VS • VS production slurry (kg VS head

- 1 

### day

1 

### ) • 365 days Eq. 6.3

EF manure = 4.8 gCH 4 

### /Kg VS • VS production slurry (kg VS head

- 1 

### day

1 

### ) • 365 days Eq. 6.4

Livestock category Slurry
(kg CH

4 head- 1 yr - 1 ) Solid manure

(kg CH

4 head - 1 yr - 1 ) CH 4 manure management

EF (kg CH

4 head - 1 yr - 1 )

Calf ( vitelli ) 6.22 0.00 6.22

Cattle ( bovini ) 5.07 3.49 8.56

Female cattle ( bovine ) 2.87 4.18 7.05

Other dairy cattle ( altre

vacche ) 4.01 6.65 10.66

Dairy ca ttle ( vacche da latte ) 5.64 9.41 15.04

Cow buffalo ( bufale ) 4.99 10.26 15.25

Other buffaloes ( altri
bufalini ) 3.13 3.16 6.29

Table 6.11 Methane manure management emission factors for cattle and buffalo in 2007 (kg CH 4 head- 1 yr - 1 )



### Since the 2006 submi ssion, the average production of slurry and solid manure per livestock category per day (m 3 

### head

- 1 

### day

- 1 

### ) has been updated with results from the Inter

- regional project on nitrogen balance project (Regione Emilia Romagna, 2004). Based on the type and distri bution of housing systems for the different animal categories, and the average weight of animals, a time series of slurry and solid manure production has been obtained. In Table 6.12 the disaggregated manure management EFs for cattle and buffalo are shown. However, in Table 6.14 the average EFs for the main categories (dairy, non

- dairy and buffalo) are shown.

### 124

Year Calf Cattle Female cattle Other dairy

cattle Dairy cattle Cow buffalo Other

buffaloes

1990 6.22 8.11 6.71 10.66 15.04 15.25 6.34

1991 6.22 8.0 6 6.91 10.66 15.04 15.25 6.34

1992 6.22 8.01 6.86 10.66 15.04 15.25 6.34

1993 6.22 7.99 6.83 10.66 15.04 15.25 6.33

1994 6.22 8.20 6.93 10.66 15.04 15.25 6.33

1995 6.22 8.56 6.71 10.66 15.04 15.25 6.33

1996 6.22 8.29 6.76 10.66 15.04 15.25 6.32

1997 6.22 8.33 6.62 10.66 15.04 15.25 6.32

1998 6.22 8.16 6.65 10.66 15.04 15.25 6.32

1999 6.22 8.22 6.71 10.66 15.04 15.25 6.31

2000 6.22 8.27 6.80 10.66 15.04 15.25 6.31

2001 6.22 8.48 7.07 10.66 15.04 15.25 6.31

2002 6.22 8.23 6.99 10.66 15.04 15.25 6.3 0

2003 6.22 8.38 6.94 10.66 15.04 15.25 6.30

2004 6.22 8.34 6.98 10.66 15.04 15.25 6.30

2005 6.22 8.61 6.95 10.66 15.04 15.25 6.30

2006 6.22 8.52 6.87 10.66 15.04 15.25 6.29

2007 6.22 8.56 7.05 10.66 15.04 15.25 6.29

Table 6.12 Methane manure managem ent emission factors for cattle and buffalo (kg CH 4 head - 1 yr - 1 )



### Since the 2006 submission, a reduction of CH 4 

### emissions has been considered for the manure

management category on account of biogas production . A national census on biogas production/technol

ogy can be found in CRPA (2008) and CRPA/AIEL (2008). Activity data are collected every year from the National Electric Network

- TERNA 7 

### (2009 ). Further information on biogas activity data can be found in Annex 7.

Reduction of CH 4 

### emissions are assumed fo r cattle and swine livestock categories, and distributed according to the contribution of emissions from each category. This reduction is evident in the implied emission factor (IEF) reported in the CRF. In 2007, IEFs, for dairy cattle and non

- dairy

cattle

, were 13.63 kg CH 4 

### head

- 1 

### year - 1 

### and 7.04 kg CH 4 

### head

- 1 

### year - 1 

### , respectively. IPCC default emissions factors for cool temperature are 14 kg CH 4 

### head

- 1 

### year

- 1 

### and 6 kg CH

4 

### head

- 1 

### year - 1



### , respectively (IPCC, 1997).

The IEF for non

- dairy cattle and buffalo re presents a weighted average. The non

- dairy cattle IEF includes: calf, cattle, female cattle and other dairy cattle. The buffalo category includes: cow buffalo and other buffaloes categories. In the following box, EF s and IEF s are presented.
Differences, as mentioned before, are related to the amount of CH 4 

### reductions from biogas recovery. Moreover, interannual decrease 2005/2006 of the non

- dairy IEF reflects the strong increase of biogas recovery.

Livestock category EF (kg CH

4 head

- 1 yr - 1 ) IEF(*)

(kg CH

4 h ead

- 1 yr - 1 )

Dairy cattle 15.04 13.63

Non

- dairy cattle 7.77 7.04

Buffalo 11.97 11.97

(*) IEF as reported in the CRF submission 2009

7 TERNA, Rete Elettrica Nazionale

### 125

For reporting purposes, the estimation of the methane producing potential (Bo), has been estimated with Equation 4.17 fr om IPCC (2000). Moreover, the average methane conversion factors (MCF), for each manure management system (classified by climate) is estimated with data coming from the Agriculture Census from 1990 and 2000 and the FSS 2005 (ISTAT, 2007[a]). Average MCFs h ave not been used for estimating manure management EF, but they are useful to verify the EF accuracy. In the following box, estimated country

- specific VS and Bo parameters, and IPCC default values are shown. Differences are mainly attributed to country

- spe cific characteristics.

Livestock category VS country

- specific (*) (kg dm head

- 1 yr - 1 ) VS IPCC default

(kg DM head

- 1 yr - 1 ) Bo country

- specific (*)

(CH 4 m 3 /kg VS) Bo IPCC default

(CH 4 m 3 /kg VS)

Dairy cattle 6.37 4.13 0.14 0.24

Non

- dairy cattle 2.85 2.68 0.13 0.17

Buffalo 5.14 2.68 0.13 0.10

Swine 0.32 0.50 0.46 0.45

(*) IEF as reported in the CRF submission 2009



### Methane emissions (swine)

For the estimation of CH 4 

### emissions for swine, a country

- specific methane emission rate has been experimentally det ermined by the Research Centre on Animal Production (CRPA, 1996). The estimation of the EF considers: the structure of the storage for slurry (tank and lagoons), type of breeding and seasonal production of biogas.

Different parameters have been considere d, such as the livestock population, average weight for fattening swine and sows, and methane emission rate . Methane emission rates used are 41 normal

litre CH

4 

### /100 kg live weight/day for fattening swine and 47 normal litre CH 4 

### /100 kg live weight/day for s

ows including piglets (CRPA, 1997[a]). Then, a reduction of emissions of 8% for covered storage structures has been applied to the methane emission rate . In Table 6.13, characteristics of swine breeding and EFs are shown.

Since the 2006 submission, param eters such as: average weight of sows, production of slurry (t

year - 1 

### per t live weight) and volatile solid content in the slurry (g SV/kg slurry w.b.) have been updated. Moreover, the slurry production has considered the different swine categories (classi fied by weight and housing characteristics). Volatile solid content has been determined experimentally

from 598 measurements carried out by CRPA (2006[a]).

In 2007, the EF from sow was 22.21 kg CH 4 

### head

- 1 

### year

- 1 

### and for the other swine category was 8.33 kg CH 4 

### head

- 1 

### year

- 1 

### (average EF swine of 7.91 kg CH 4 

### head

- 1 

### year

- 1 

### ). In Table 6.14 the time series

of EF s for the disaggregated swine category (sow and other swine) are shown. The IEF as reported in the CRF submission 2009 is 7.16 kg CH 4 

### head

- 1 

### year - 1 

### . The d ifference between the EF and the IEF for the swine category is due to the reduction in CH 4 

### because of biogas recovery.

For reporting purposes, the VS daily excretion and Bo have been estimated by a procedure to verify the EF accuracy. The VS daily excreti on has been estimated for each sub

- category with the following parameters: animal number, production of slurry (t/a/t live weight) and the volatile solids content in the slurry (g VS/kg slurry w.b.). Methane producing potential (Bo) has been estimated

with Equation 4.17 from the IPCC (2000).

### 126

Livestock category Average weight (kg) Breed live weight

(t) Methane emission rate with

8% emission reduction (nl CH

4 /100 kg live weight) Emission factor
(kg CH

4 head - 1

yr - 1 )

Other swine 84 569,829 13,768 8.3 3

20

- 50 kg 35 65,142 13,768 3.48

50

- 80 kg 65 98,279 13,768 6.46

80

- 110 kg 95 135,778 13,768 9.44

110 kg and more 135 264,089 13,768 13.41

Boar 200 6,543 13,768 19.86

Sow 172 146,994 15,783 22.21

Piglets 10 17,279 15,783 1.14

Sow 172.1 129,715 15,78 3 19.60

TOTAL 7.91

Table 6.13 Methane manure management parameters and emission factors for swine in 2007



### The fundamental characteristic of Italian swine production is the high live weight of the animals slaughtered as related to age; the optimum wei ght for slaughtering to obtain meat suitable for producing the typical cured meats is between 155 and 170 kg of live weight. Such a high live weight must be reached in no less than nine months of age. Other two specific characteristics which

have to be con

sidered are the feeding situation, to obtain high quality meat, and the concentration of Italian pig production, which is limited to a small area ( Lombardia, Emilia

- Romagna, Piemonte and

Veneto ), representing 75% of national swine resources (Mordenti et al ., 1997). These peculiarities of Italian swine production influence the methane EF for manure management as well as nitrogen excretion factors used for the estimating of N 2 

### O emissions.

Other livestock categories

Methane EFs used for calculating the othe r livestock categories are those proposed by IPCC. Since the yearly average temperature in Italy is 13 °C, EFs are characteristic of the "cold" climatic region (IPCC, 1997). In Table 6.14, the average methane EF s for cattle, buffalo and swine categories ar e shown. For the other categories

, the EFs are as follows:

• rabbits, 0.080 kg CH 4 

### head

- 1 

### year - 1



### • sheep, 0.22 kg CH 4 

### head

- 1 

### year

- 1



### • goats, 0.145 kg CH 4 

### head

- 1 

### year - 1



### • horses, 1.48 kg CH 4 

### head

- 1 

### year - 1



### • mules and asses, 0.84 kg CH 4 

### head

- 1 

### year

- 1



### • hen, 0.082 kg CH 4 

### head

- 1 

### year - 1



### • broilers, 0.079 kg CH 4 

### head

- 1 

### year - 1



### • other poultry, 0.079 kg CH 4 

### head

- 1 

### year - 1

### 127

(*) These are the EFs used for estimating methane emissions from manure management. They do not include CH 4 reduction. Table 6.14 Average methane EF for manure management (kg CH 4 head- 1 year - 1 )



### Nitrous oxide emissions

Nit rous oxide emissions have been estimated with equation 4.18 from IPCC, as suggested in the IPCC (2000). Different parameters have been used for the estimation : number of livestock species,

country

- specific nitrogen excretion rates per livestock category, t he fraction of total annual excretion per livestock category related to a manure management system and EFs for manure management systems (IPCC, 1997). Liquid system, solid storage and other management systems (chicken

- dung drying process system)

have been considered according to their significance and major distribution in Italy. For these management systems, the following EFs have been used : 0.001 kg N 2 

### O

- N/kg N excreted, 0.02 kg

N 2 

### O

- N/kg N excreted and 0.02 kg N 2 

### O

- N/kg N excreted, respectively (CRPA, 2000; CRPA, 1997[b]). The chicken

- dung drying process system has been considered since 1995 since it has been significantly widespread in poultry breeding (CRPA, 2000; CRPA, 1997[b]).

When estimating emissions from manure management, the amount related to manu re excreted while grazing is subtracted and reported in “Agricultural soils” under soil emissions

- animal production (see Table 6.15). Since 2006 submission, different parameters such as the nitrogen excretion rates (CRPA, 2006[a]; GU, 2006; Xiccato et al ., 2005), the slurry and solid manure production, and the average weight (CRPA, 2006[a]; GU, 2006; Regione Emilia Romagna, 2004) have been updated. In Table 6.15, nitrogen excretion rates used for the estimation of N 2 

### O are shown. The nitrogen

excretion rat e for swine as reported in CRF submission 2009 is 11.67 kg head

- 1 

### yr - 1 

### . This last parameter is a weighted average, where sow (28.2 kg head

- 1 

### yr - 1 

### ) and other swine (12.81 kg head

- 1



### yr - 1 

### ) categories have been considered. Year Dairy cattle Non

- dairy cattle Buffalo Sows Other swine

kg CH 4 head - 1 year - 1 (*)

1990 15.04 7.47 12.17 22.14 8.54

1991 15.04 7.61 11.94 22.03 8.42

1992 15.04 7.59 12.02 22.01 8.41

1993 15.04 7.59 11.93 22.05 8.43

1994 15.04 7.73 11.90 21.96 8.42

1995 15.04 7.82 11.95 21.96 8.52

1996 15.04 7.79 11.92 21.95 8.54

1997 15.04 7.70 11.90 22.05 8.34

1998 15.04 7.66 12.06 22.04 8.36

1999 15.04 7.72 1 2.12 22.12 8.44

2000 15.04 7.67 11.71 21.97 8.43

2001 15.04 7.72 13.74 22.20 8.55

2002 15.04 7.66 14.07 22.27 8.21

2003 15.04 7.69 12.98 22.19 8.20

2004 15.04 7.73 12.87 22.22 8.27

2005 15.04 7.78 12.29 22.30 8.35

2006 15.04 7.67 11.96 22.16 8.35

2007 15.04 7.77 11.97 22.21 8.33

### 128

(*) average N excr etion for swine is 11.67 kg head

- 1 yr - 1

Table 6.15 Average weight and nitrogen excretion rates in 2007



### Since the 2006 submission, country

- specific annual nitrogen excretion rates have been incorporated

with information from the Inter

- regional nitrogen bal ance project. The nitrogen balance project involved Emilia Romagna, Lombardia, Piemonte and Veneto regions, where animal breeding is concentrated. The nitrogen balance methodology was followed, as suggested by IPCC. As a result, estimations of nitrogen exc retion rates 8 

### and net nitrogen arriving to the field 9 

### were obtained. In order to get reliable information on feed consumption and characteristics, and composition of the feed ratio, the project considered territorial and dimensional representation of Itali an breeding. Final annual nitrogen excretion rates used for the UNFCCC/CLRTAP agriculture national inventory are reported in CRPA (2006[a]). In Table 6.16, nitrogen excretion rates for the main livestock categories are shown. For the other livestock catego ries nitrogen excretion is the same for the whole
time series, as shown below:

• sheep, 16.2 kg head

- 1 

### year - 1



### • goats, 16.2 kg head

- 1 

### year - 1



### • horses, 50.0 kg head

- 1 

### year - 1



### • mules and asses, 50.0 kg head

- 1 

### year - 1



### • hen, 0.66 kg head

- 1 

### year - 1 

### • broilers, 0.36 kg h ead

- 1 

### year

- 1



### • other poultry, 0.825 kg head

- 1 

### year - 1



### • rabbits, 1.0 kg head

- 1 

### year - 1



### • fur animals, 4.1 kg head

- 1 

### year - 1



### The same N excretion rate has been applied for the whole time series

, for the dairy cattle category.

This figure is the result of a nation al i nter

- regional project on nitrogen balance, which is not possible to develop annually. Further explanation on the efforts to improve the modelling of N excretion is given in the following section 6.3.6.

Year Dairy cattle Non

- dairy cattle Buffalo Sows Other swine

1990 116.0 50.00 93.94 28.10 13.13

1991 116.0 51.43 92.27 27.94 12.94

1992 116.0 50.97 92.89 27.92 12.93

8 Nitrogen excretion = N consumed

– N retained

9 Net nitrogen to field= (N consumed

– N retained)

– N volatilized Livestock

category Average weight (kg) N excreted

Housing
(Ricoveri) (kg head

- 1 yr - 1 ) N excreted

Grazing
( Pascolo ) (kg head

- 1 yr - 1 ) TOTAL

Nitrogen

excreted (kg head

- 1 yr - 1 )

Non

- dairy cattle 383 48.58 1.27 49.84

Dairy cattle 603 110.20 5.80 116.00

Buffalo 514 89.92 2.69 92.61

Other s wine 84 12.81 0.00 12.81

Sow 172 28.18 0.00 28.18 (*)

Sheep 47 1.62 14.58 16.20 (*)

Goat 47 1.62 14.58 16.20

Horses 500 20.00 30.00 50.00

Mules and asses 300 20.00 30.00 50.00

Poultry 1.8 0.53 0.00 0.53

Rabbit 1.6 1.02 0.00 1.02

### 129

Year Dairy cattle Non

- dairy cattle Buffalo Sows Other swine

1993 116.0 50.82 92.24 27.97 12.97

1994 116.0 51.83 92.04 27.85 12.95

1995 116.0 49.86 92.42 27.86 13.10

1996 116.0 49.83 92.17 27.84 13.12

1997 116.0 49.81 92.04 27.98 12.82

1998 116.0 49.19 93.21 27.96 12.86

1999 116.0 49.62 93.68 28.06 12.98

2000 116.0 50.08 90.76 27.87 12.96

2001 116.0 50.69 105.23 28.17 13.14

2002 116.0 50.39 107.58 28.27 12.61

2003 116.0 50.53 99.82 28.16 12.60

2004 116.0 50.04 99.01 28.20 12.72

2005 116.0 49.76 94.91 28.30 12.84

2006 116.0 48.52 92.59 28.12 12.84

2007 116.0 49.84 92.61 28.18 12.81

Table 6.16 Nitrogen excretion rates for all livestock categories (kg head - 1 yr - 1 )



### Since the 2006 submiss ion, new average weight data has been used for UNFCCC/CLRTAP agriculture national inventory. For a verification purpose, a time series reported by ISTAT in the yearbooks (animal weight before slaughter) has been collected (CRPA, 2006[a]). For the specific case of sheep and goats, a detailed analysis was applied with information coming from the National Association for Sheep Farming 10 

### (ASSONAPA, 2006). Then, to estimate the average weight for sheep and goat, breed distribution in Italy and consistency for ea ch breed w ere considered (CRPA, 2006[a]; PROINCARNE, 2005). As mentioned before, s lurry and solid manure production parameters were updated since the 2006 submission. These parameters consider characteristics from Italian breeding, for slurry and solid man ure effluents, housing systems and the distribution for the different animal categories (CRPA, 2006[a]; Bonazzi et al ., 2005; APAT, 2004[a]; APAT, 2004[b]).

6.3.3. Uncertainty and time

- series consistency

Uncertainty of CH 4 

### and N

2 

### O emissions from manure m anagement has been estimated equal to 102% for annual emissions, as a combination of 20% and 100% for activity data and emission factors, respectively.
In 2007, livestock CH 4 

### emissions from manure management were 11.7% (145.57 Gg CH 4 

### ) lower than in 1990 ( 164.86 Gg CH 4 

### ). From 1990 to 2007, dairy and non

- dairy cattle livestock population decreased by 30.4% and 13%, respectively, whereas swine increased by 10.3%. Consequently, manure management emissions have mainly been driven down by the reduction in the nu mber of

cattle. We have to consider that cattle CH 4 

### emissions contribute with 38.7% (in 1990 with 47.3%) to total manure management emissions and swine with 41.4% (in 1990 with 41.4%). In Table 6.17,

CH 4 

### emission trends from manure management are shown. Th ese CH

4 

### emissions considered the

reduction of CH

4 

### because of biogas recovery.

10 ASSONAPA, Associazio ne Nazionale della Pastorizia Ufficio Centrale dei Libri Genealogici e dei Registri Anagrafici.

### 130

Year Dairy

cattle Non

dairy

cattle Buffalo Sows Other

swine Sheep Goats Horses Mules

and

asses Poultry Rabbits TOTAL

1990 39.74 38.18 1.15 14.41 53.78 1.90 0.18 0.43 0.07 13.8 2 1.19 164.86

1991 35.12 42.40 0.99 15.64 53.06 1.83 0.18 0.46 0.06 13.80 1.27 164.82

1992 32.26 41.15 1.24 15.20 51.18 1.84 0.20 0.47 0.05 13.77 1.31 158.67

1993 31.86 40.36 1.20 15.49 51.67 1.89 0.20 0.48 0.04 13.82 1.32 158.32

1994 29.93 39.40 1.29 14.70 49.50 2.17 0.24 0.48 0.04 14.24 1.35 153.34

1995 30.85 40.01 1.77 14.94 49.85 2.32 0.20 0.47 0.03 14.67 1.36 156.48

1996 30.88 39.14 2.04 15.73 50.08 2.38 0.21 0.46 0.03 14.57 1.39 156.90

1997 30.89 38.76 1.92 15.11 50.25 2.37 0.20 0.46 0.03 14.87 1.40 156.26

1998 31.52 38.00 2.25 15.44 50.46 2.37 0.19 0.43 0.03 15.85 1.41 157.94

1999 31.62 38.47 2.43 15.13 51.67 2.40 0.20 0.43 0.03 15.67 1.44 159.48

2000 30.80 37.92 2.25 15.42 51.14 2.41 0.20 0.41 0.03 14.09 1.42 156.10

2001 30.78 35.43 2.66 1 5.25 54.51 1.81 0.15 0.42 0.03 16.68 1.46 159.18

2002 28.17 34.54 2.61 16.40 53.46 1.77 0.14 0.41 0.02 16.39 1.48 155.39

2003 28.11 34.47 2.89 15.96 53.97 1.73 0.14 0.42 0.02 15.68 1.45 154.84

2004 26.73 33.38 2.70 15.57 52.58 1.76 0.14 0.41 0.02 15.27 1.69 150.26

2005 26.44 32.74 2.52 15.36 53.87 1.73 0.14 0.41 0.03 15.05 1.77 150.06

2006 25.21 30.31 2.76 15.73 52.04 1.79 0.14 0.42 0.03 14.18 1.74 144.34

2007 25.05 31.28 3.52 15.16 51.26 1.79 0.13 0.47 0.03 15.07 1.81 145.57

Table 6.17 Trend in CH 4 emissions from manure management (Gg)



### In 200 7 , N 2 

### O emissions from manure management were 3.2 % (1 2.25 Gg N 2 

### O) lower than in 1990 (12.65 Gg N

2 

### O). The major contribution is given by the solid storage system with 8 8.1 % (in 1990
with 95.1%). In Table 6.18, N 2 

### O emissions for the manure management systems are shown.

Year Liquid system Solid storage Other TOTAL

1990 0.62 12.03 0.00 12.65

1991 0.62 12.01 0.00 12.63

1992 0.59 11.50 0.00 12.09

1993 0.59 11.39 0.00 11.98

1994 0.57 11.37 0.00 11.93

1995 0.57 11. 54 0.09 12.20

1996 0.56 11.61 0.17 12.34

1997 0.56 11.63 0.25 12.44

1998 0.56 11.72 0.42 12.70

1999 0.56 11.80 0.53 12.89

2000 0.54 11.36 0.56 12.46

2001 0.54 11.59 0.78 12.90

2002 0.52 11.04 0.84 12.41

2003 0.52 10.90 0.89 12.31

2004 0.51 10.64 0 .89 12.03

2005 0.51 10.54 0.97 12.02

2006 0.50 10.22 0.95 11.67

2007 0.51 10.79 0.94 12.25

Table 6.18 Trend in N 2 O emissions due to manure management, (Gg)

### 131

6.3.4. Source

- specific QA/QC and verification

In Table 6.19, past and future improvements in a greement with the QA/QC plan are presented.

Year of

submission Category/sub
category Parameter

2009 2010 Activities

Livestock categories Type of housing v A query on the type of housing of different livestock categories has been introduced in the Farm and structure survey 2005. Results need to be further
analysed and are expected to be incorporated in a coming submission. Livestock categories Slurry and

solid manure

storage

facilities v We expect to get more detailed data from the Farm and Structure Survey 2007, where a query related to
storage facilities for slurry and solid manure have been incorporated. Livestock categories Production

methods v D ifferent queries have been incorporated in a specific
section of the 2010 Agricultural Census. Grazing, housing, storage systems and land spreading

information will be collected.
Livestock categories Biogas v Data on biogas from 2007 has been collected ( web
site GSE)

Table 6.19 Improvements for manure management category according to the QA/QC plan



### 6.3.5. Source

- specific recalculations

In Table 6.20, parameters used for the 2009 submission are shown. Recalculations affected both

CH 4 

### and N 2 

### O emissions

. A

reduction of CH

4 

### occurred because of an update of biogas recover ed for cattle and swine categories (see section 6.3.2).

For N 2 

### O emissions

, t he liquid and solid manure production parameters have been updated for the

year s 2004 and 2006.

6.3.6. Source

- sp

ecific planned improvements

A national publication describes how future agricultural surveys will contribute to improving the national agriculture emission inventory (Cóndor et al

. , 2005). We expect to analyse results obtained

from the FSS 2005 which are related to the type of housing of cattle, swine and poultry categories. Results coming from the convention between ISPRA and the Ministry for the Environment, Land and Sea on the type of housing for swine and poultry have been already considered. A new qu

ery on liquid and manure storage systems has been incorporated in the FSS 2007

. Therefore, information from the FSS 2005 and FSS 2007 on housing and storage systems, respectively, will be analysed and updated in future submissions. Furthermore, we expect t hat in the Italian Agricultural Census 2010 detailed information on production systems will be obtained with

and ad hoc survey. Finally, a specific research on land spreading practices has started in 2009.

For the dairy cattle category

, the suggestions b

y the review process (UNFCCC, 2009) have been

taken into consideration. For this category, t he same N excretion rate is actually applied to the
whole time series, but t his figure is the result of a specific i nter

- regional project on nitrogen
balance, which

is not possible to develop annually. Nevertheless, w e have tried to individuate a proper proxy variable

, in collaboration with dairy

- cattle breeding experts (CRPA, 2009), and information related to N excretion and milk production parameters has been acqui red

. At present,

i nitial results do not supply reliable information to make a correlation between these parameters but

we continue on consul ting with experts in order to get more additional figures and individuate a way to model this information.

### 132

Table 6.20. Parameters used for the different livestock categories in 2009 submission (*) Categories included in less than 1 year are: calf ( vitelli carne bianca ), fattening male cattle
( bovin i maschi ingrasso ), fattening heifer ( manze ingrasso ) and heifer for replacement ( manze rimonta );
(**) values are variable for the time series.

Livestoc k category Average weight
(kg)

Submission 2009 N exretion
(kgN head

- 1 yr - 1 )

Submission 2009

DAIRY CATTLE ( vacche da latte ) 603 116

NON

- DAIRY CATTLE

Less than 1 year (*) 213(**) 25.0 (**)

From 1 year

- less than 2 years

Male for reproduction 557 6 6.8

for slaughter 557 66.8

Female for breeding 405 67.6

for slaughter 444 53.3

From 2 years and more

Male for reproduction 700 84.0

for slaughter and work 700 84.0

Female Breeding heifer

( manze da allevamento ) 540 90.2

Slaughter heifer ( man ze da macello ) 540 64.8

Other dairy cattle ( altre vacche) 557 54.1

BUFFALO Cow buffalo ( bufale ) 630 116

Other buffaloes ( altri bufalini ) 313 52.2

OTHER SWINE Weight less than 20 kg 10

From 20 kg weight and under 50 kg 35 5.3

From 50 kg and more

Boar ( verri ) 200 30.5

For slaughter ( macello )

from 50 to 80 kg 65 9.9

from 80 to 110 kg 95 14.5

from 110 kg and more 135 20.6

SOW ( scrofe ) 172.1 28.2 (**)

SHEEP Sheep ( pecore ) 51 16.2

Other sheep ( altri ovini ) 21 16.2

GOAT Goat ( capre ) 54 16.2

Other goat ( altri caprini ) 15 16.2

EQUINE Horses ( cavalli ) 550 50.0

Mules and asses ( altri equine ) 300 50.0

POULTRY Broilers ( polli da carne ) 1.2 0.36

Hen ( galline da uova ) 1.8 0.66

Other poultry ( atri avicoli ) 3.3 0.83

RABBIT Female rabb its (f attrici ) 4 2.5

Other rabbit (

altri conigli ) 1.3 0.8

### 133

6.4. Rice cultivation (4C)

6.4.1. Source category description

For the rice cultivation category, only CH 4 

### e missions are estimated, other GHGs do not occur; N 2 

### O from fertilisation during cultivation has been estimated and reported in “Agricultural soils” under

direct soil emissions

- synthetic fertilizers. In 2007, CH 4 

### emissions from rice cultivation were 72.52 Gg, which represents 9.8 % of CH 4 

### emissions for the agriculture sector (9.1% in 1990) and 4.0% for

national CH

4 

### emissions (3.7% in 1990). In Italy, CH

4 

### emissions from rice cultivati on are estimated only for an irrigated regime, other categories suggested by IPCC (rainfed, deep water and “other”) are not present. Methane emissions, reported in the CRF, represent two water regimes: the single aeration and multiple aeration categories, where CH 4 

### emissions were 12.93 Gg and 59.58 Gg, respectively.
In response to UNFCCC review processes from 2004 and 2005 (UNFCCC, 2005; 2004) and in consultation with an expert in CH 4 

### emissions and rice cultivation ( Wassmann, 2005 ), a detailed methodology has been implemented. New activity data and parameters have been used for t he

estimation of CH

4 

### emissions for rice cultivation (Cóndor et al ., 2007[a]). For this purpose, an expert group on rice cultivation together with the C.R.A.

–Experimental Institute of Cereal Research

– Rice Research Section of Vercelli was established. Di fferent national experts from the rice

cultivation sector were also contacted 11



### . The quality of the Italian rice emission inventory has been verified with the DNDC 12 

### model. Initial results have found a high correspondence between the EFs used for the Italia n inventory and those simulated with DNDC model (Leip and Bocchi, 2007).

6.4.2. Methodological issues

For the estimation of CH 4 

### emissions from rice cultivation a detailed methodology has been implemented following the IPCC guidelines (IPCC, 2006). We ha ve considered country

- specific circumstances, therefore, we have used an adjusted integrated emission factor (kg CH 4 

### m - 2 

### day

- 1 

### ), cultivation period of rice (days) and annual harvested area (ha) cultivated under specific conditions.

Information of the cultiv ated surface is collected from 100% of rice farmers . Every year, data are collected timeliness by the Ente Nazionale Risi

–ENR (National Rice Institute) (ENR, 2007). Later

th ese data are

published in the ENR web site and also provided to ISTAT. In the fol lowing box,

information related to the collection of data is shown.

Parameters used for the calculation of CH 4 emissions from rice cultivation

Parameters Reference

Cultivated surface with “dry

- seeded” technique (%) Centro Ricerche sul Riso, 2007

Culti vated surface

–national (ha) ISTAT, 2009[d]; ISTAT, several years [a],[b]; ENR, 2009

Cultivated surface by rice varieties (ha) ENR, 2009

Cultivation period of rice varieties (days) ENR, 2009

Methane emission factor (kg CH 4 m - 2 d

- 1 ) Leip et al ., 2002; S chutz et al ., 1989[a], [b]

Crop production (t yr

- 1 ) ISTAT, several years [a],[b]; ISTAT, 2009[d]

Yield (t ha

- 1 ) Estimations based on cultivated surface and crop production data
Straw incorporation (%) Expert judgement (Tinarelli, 2005; Lupotto et al ., 2005)

Agronomic practices (%) ISTAT, 2006[b]; Tinarelli, 2005; Lupotto et al ., 2005;
Zavattaro et. al, 2004; Baldoni & Giardini, 1989; Tinarelli,
1973; 1986 Scaling factors (SFw, SFp, SFo) IPCC, 2006; Yan et. al, 2005

11 Stefano Bocchi, Crop Science Department (University of Milan); Aldo Ferrero, Department of Agronomy, Forestry and Land Management (University of Turin); Anton ino Spanu, Department of agronomic science and agriculture genetics (University of Sassari).

12 DNDC, Denitrification Decomposition model

### 134

Rice cultivation practice

In Italy, rice is sown from mid

- April to the end of May and harvested from mid

- September to the end of October; the only practised system is the controlled flooding system, with variations in water regimes (Regione Emilia Romagna, 2005; Mannini, 2004; Tos sato & Regis, 2002). In Table 6.21, water regimes descriptions are presented. Normally, the aeration periods are very variable in number and time, depending on different circumstances, as for example, the type of herbicide, which is used (Baldoni & Giardin i, 1989). Another water regime system, present in southern Italy, is the sprinkler irrigation, which exist only on experimental plots and could contribute to the diffusion of rice cultivation in areas where water availability is a limiting factor (Spanu et al ., 2004; Spanu & Pruneddu, 1996).

Type of
seeding April May June July August September

- October Description

15

- 30 April Flooding

and wet

seeded (*) 10 may Herbicide

treatment. Fertilizer

application
(1/3), soil is

saturated but

not flooded.

Panicle

formation Final aeration Harvest 2 aeration periods during rice

cultivation, as
minimum, not including the final

aeration

IPCC classification: Intermittently

flooded

– multiple

aeration Wet

seeded

“classic

”

1oaeration

-

AR 2o aeration

AA 3o final

a eration

15 April
Flooding

and wet

seeded (*) First

application

of
herbicides,

the soil is dry. Approxima
tely, on 15

may flooding

and after some days seeding At the end of

June,

fertilization

treatment Fertilizer

applic ation
(1/3), soil is

saturated but

not flooded.

Panicle

formation Final aeration Harvest 2 aeration periods
during rice
cultivation, as
minimum, not
including the final

aeration. In some cases, between April
and May, even 3 aeration periods are practised.

IPCC classification: Intermittently

flooded

– multiple

aeration Wet

seeded

“red

rice

control

”

1° aeration

– AC
Approx.

after 10 days

2° aeration

- AR 3oaeration

-

AA Final aeration

15 April Dry

- seeded Approxima

tely, on 15

may flooding Herbic ide

treatment Fertilizer

application
(1/3), soil is

saturated but

not flooded.

Panicle

formation Harvest 1 aeration period during rice

cultivation, as
minimum, not including the final

aeration.

IPCC classification: Intermittently

flooded

– single

aer ation Dry

seeded

with delay

floodin

g

1o aeration

AA 2o final

aeration

### 135

Table 6.21 Water regimes in Italy and classification according to IPCC guidelines
(*) the first fertilization (2/3) during the initial part of the rice cultivation, generally on July there is a second period f or the fertilization (1/3), normally there is no aeration during the second fertilization period. Aeration periods mostly last between 5

- 15 days and are classified as follows: AC= aeration to control red rice ( lotta al crodo ); AR = drained, aeration in ord er promote rice rooting,
( asciutta di radicamento ); AA= drained, tillering aeration ( asciutta di accestimento ).



### In general, rice seeds are mechanically broadcasted in flooded fields. However, in Italy for the last 15 years, seeds are also drilled to dry soil in rows. The rice which has been planted in dry soil is generally managed as a dry crop until it reaches the 3

- 4 leaf stage. After this period, the rice is flooded and grows in continuous submersion, as in the conventional system (Ferrero & Nguyen,

2 004; Russo, 1994). During the cultivation period, water is commonly kept at a depth of 4

- 8 cm, and drained away 2

- 3 times during the season to improve crop rooting, to reduce algae growth and to allow application of

herbicides. Rice fields are drained at the end of August to allow harvesting, once in a year (Ferrero & Nguyen, 2004; Baldoni & Giardini, 1989; Tinarelli, 1973; 1986). Nitrogen is generally the most limiting plant nutrient in rice production and is subject to losses because of the reduction pr ocesses (denitrification) and leaching. Sufficient nitrogen should be applied pre

- plant or pre

- flood to assure that rice plant needs no additional nitrogen until panicle initiation or panicle differentiation stage. When additional nitrogen is required, it should be top

dressed at either of these plant stages or whenever nitrogen deficiency symptoms appear. The

above

- mentioned applications are usually used in two or three periods; the first period is always before sowing, that is on dry soil, while the other s occur during the growing season (Russo, 2001;

Russo, 1993; Russo et al ., 1990; Baldoni & Giardini, 1989). In Italy, another type of fertilization practise is the incorporation of straw. The incorporation period can vary according to weather conditions, b ut probably mainly incorporated approximately one month before flooding (Russo, 1988; Russo 1976). Rice straw are often burned in the field, otherwise incorporated into the soil or buried. For other agronomic practice, a recent national publication has bee n considered for understanding fertilizer and crop residues management (Zavattaro et al ., 2004).

Methane emission factor

An analysis on recent and past literature, for the CH 4 

### daily emission factor (kg CH 4 

### m - 2 

### d

- 1 

### ), has

been done . Different scientific pu blications related to the CH 4 

### daily emission factor measurements in Italian rice fields have been revised (Marik et al ., 2002; Leip et al ., 2002; Dan et al ., 2001;

Butterbach

- Bahl et al ., 1997; Schutz, 1989[a], [b]; Holzapfel

- Pschorn & Seiler, 1986), other publications are indirectly related with CH 4 

### production (Kruger et al ., 2005; Weber et al ., 2001; Dannenberg & Conrad, 1999; Roy et al ., 1997). Butterbach

- Bahl et al . have presented interesting

results associated to the difference in EF of two cultivation periods (1990 and 1991). In these consecutive years, fields planted with rice cultivar Lido showed a level of CH 4 

### emissions 24

- 31% lower than fields planted with cultivar Roma. Marik et al . have published detailed information on agronomic practices (ferti lized fields) related to measurements of CH 4 

### emission factor for years 1998 and 1999; values are similar to those presented in previous publications (Schutz, 1989[a], [b]; Holzapfel

- Pschorn & Seiler, 1986). Leip et al ., have also published specific CH 4 

### emi ssion factors for a particular agronomic practice, which has been presented in Table 6.21, the so called dry

seeded with delay flooding ( semina interrata a file ). The dry

– seeded technique could bring interesting benefits in emission reduction, since experi mentally it has been determined lower emission rates compared with a normal practice.

The estimation of CH 4 

### emissions for the rice cultivation category considers an irrigated regime, which includes intermittently flooded with single aeration and multiple aeration regimes. The CH 4 

### emission factor has been adjusted with the following parameters: daily integrated emission factor for continuously flooded fields without organic fertilizers, scaling factor to account for the

### 136

differences in water regime in the ri ce growing season (

SFw ), scaling factor to account for the differences in water regime in the preseason status ( SFp ) and scaling factor which varies for both types and amount of amendment applied ( SFo ). Scaling factor parameters have been updated according to a recent publication (Yan et al ., 2005) and new IPCC 2006 Guidelines (IPCC, 2006). Assumptions of agronomic practices are described in Table 6.21. Parameters used for CH 4 

### emission

estimations are shown in Table 6.22.

Rice cultivation water regimes:
Intermittently flooded Single aeration Multiple aeration Multiple aeration

Type of seeding Dry

- seeded Wet

- seeded (classic) Wet

- seeded ( red rice

control )

Surface (ha) 46,773 87,840 93,897

Daily EF (g CH

4 m - 2 d - 1 ) 0.20 0.28 0.28

SFw 0.06 0.52 0.52

SFp 0.68 0.68 0.68

SFo 2.2 2.2 2.2

Adjusted daily EF (g CH 4 m - 2 d - 1 ) 0.18 0.21 0.21

Days of cultivation (days) 138 156 1556

Seasonal EF (g CH 4 m - 2 yr - 1 ) 24.48 33.16 33.16

Methane emissions (Gg) 12.93 27.81 31.78

Table 6.22 Parameters used for estimating CH 4 emissions from rice cultivation in 2007



### 6.4.3. Uncertainty and time

- series consistency

Uncertainty of emissions from rice cultivation has been estimated equal to 20% as a combination of 3% and 20% for activity data and emissions factor, respectively

. In 2007, CH

4 

### emissions from rice cultivation were 2.5% (72.52 Gg CH 4 

### ) lower than in 1990 (74.39 Gg CH

4 

### ). In Italy, the driving force of CH 4 

### emissions from rice cultivation is the harvest area and the percentage of single aerated surface. Methane emissio ns have decreased by 2.5% and the harvest area has increased by 7.9%, from 215,442 ha year

- 1 

### in 1990 to 232,549 ha year

- 1 

### in 2007. The percentage of single aerated surfaces have increased from 1% (1990) to 22.7% (2007);
therefore, emissions have verified a slow decrease. Water regime trends have been calculated together with expert judgement expertise (Tinarelli, 2005; Lupotto et al ., 2005) and national
available statistics (Centro Ricerche sul Riso, 2007). In Table 6.24, CH 4 

### emissions from rice

cultivation

and harvested area are shown.

6.4.4. Source

- specific QA/QC and verification

In Table 6.23, improvements according to the QA/QC plan are shown.

Year of

submission Category/su
b category Parameter

2009 2010 Activities

Activity data Days of

cultivati on and

cultivars v Update data 2004, 2005, 2006 and collected 2007. Updated rice production statistics has been provided for the years 2004, 2005,
2006 (ENR, 2008)

Rice Emission factor v v We have contact DG Joint Research Centre Institute for

Environment and Sustainabil ity

- Climate Change Unit, which have been in charge of measuring rice paddy fields in Italy. New

measurements have been done in 2007 and 2008. Data is still not

available.
Table 6.23 Improvements for the rice cultivation category according to the QA/QC p lan

### 137

6.4.5. Source

- specific recalculations

In Table 6.24, CH 4 

### emission from 2007 and 2008 submissions are presented. Period of cultivation of rice varieties have been updated for the year s 2003

- 2006 . For the year s 2004

- 2006 updated information on rice prod uction has been provided (ENR, 2009).

Year Harvested area (10 9 m 2 yr - 1 ) Emissions 2008

submission (Gg) Emissions 2009 submission (Gg)

1990 2.15 74.4 74.4

1991 2.06 71.1 71.1

1992 2.16 73.9 73.9

1993 2.32 77.5 77.5

1994 2.36 79.2 79.2

1995 2.39 78. 9 78.9

1996 2.38 77.3 77.3

1997 2.33 76.9 76.9

1998 2.23 73.0 73.0

1999 2.21 71.3 71.3

2000 2.20 65.8 65.8

2001 2.18 65.8 65.8

2002 2.19 67.6 67.6

2003 2.20 69.6 69.7

2004 2.30 73.0 73.0

2005 2.24 70.0 70.1

2006 2.29 69.9 70.3

2007 2.33 72.5

Table 6.24 Harvest area and CH 4 emissions from the rice cultivation sector



### 6.4.6. Source

- specific planned improvements

Lack of experimental data and knowledgement about the occurrence and duration of drainage periods in Italy is the major cause of uncert ainty. Moreover, it is not easy to quantify the surface where the traditional or the different number of aerations is practiced, which depends on the degree and the type of infestation, and the positive or negative results of the herbicide treatment applic ation (Spanu, 2006). In Table 6.21, a general classification has been done for the most common agronomic practices in Italy. Since the 2006 submission, a trend in water regime has been calculated together with expert judgement expertise (Tinarelli, 2005; L upotto et al ., 2005) and
available statistics (Centro Ricerche sul Riso, 2007). Provincial estimations on the basis of the relation between emissions and temperature would result in further possible improvements, even if

enhancement would be limited since the largest Italian rice production is in the Po valley, where monthly temperatures of the rice paddies are similar. In 1990, Piemonte and Lombardia regions represented 94.8% of the national surface area of rice cultivation, while in 2006 they represented
93.9% (ENR, 2009; Confalonieri and Bocchi , 2005 ).

6.5. Agriculture soils (4D)

6.5.1. Source category description

In 2007, N 2 

### O emissions from agricultural soils were 57.39 Gg, representing 82.4% of emissions for the agriculture sector ( 83.2 % in 1990) a nd 55.9 % for national N 2 

### O emissions ( 52.0 % in 1990). N 2 

### O emissions from this source mainly consist of direct soil emissions with 28.04 Gg and indirect soil emissions with 24.28 Gg.

Direct N

2 

### O emissions from agricultural soils are key sources at level and trend assessment, both with Tier 1 and Tier 2 approaches. Indirect N 2 

### O emissions are key sources at level for Tier 1 and

### 138

Tier 2, and trend assessment (Tier 2). Animal Production is a key source at level and trend assessment with the Tier 2 approach, taking into account the uncertainty. In Italy, agricultural soil emissions are estimated for direct and indirect soils and animal production. For direct soil emissions the following sources have been estimated: synthetic fertilizers, animal waste applied to soi

l, N

- fixing crops and cultivation of histosols. For indirect soil emissions, atmospheric deposition and nitrogen leaching and run

- off have been estimated. Nitrous oxide emissions from Animal Production are calculated together with the manure management cat egory on the basis of nitrogen excretion, and reported in agricultural soils under “Animal Production”.
ISPRA ( former APAT) is in charge of collecting, elaborating and reporting the UNFCCC/CLRTAP agriculture national emission inventory (APAT, 2005), where consistent methodologies and parameters are used. Since the 2006 submission, the UNFCCC/CLRTAP inventory has updated country specific nitrogen excretion rates and EFs. Moreover, the nitrogen balance coming from the CLRTAP emission inventory feeds the UNFC CC inventory, specifically for the estimation of

FRAC GASM 

### and FRAC GASF 

### parameters, used for calculating F AM 

### and F SN



### .

6.5.2. Methodological issues

Methodologies used for estimating N 2 

### O emissions from “Agricultural soils” follow the IPCC approach. Emissio n factors suggested by the IPCC (1997) and by the Research Centre on Animal Production (

CRPA, 2000; CRPA, 1997[b]) have been used. Activity data used for estimations are shown in the following box.

Data used for estimating agricultural soil emissions

Dat a Reference

Fertilizer distributed (t/yr) ISTAT, 2009[c]; ISTAT, several years [a], [b]

Nitrogen content (%) ISTAT, 2009[c]; ISTAT, several years [a], [b]

N excretion rates (kg head

- 1 yr - 1 ) CRPA, 2006[a]; GU, 2006; Xiccato et al ., 2005

Cultivated su rface (ha yr

- 1 ) ISTAT, 2009[d]; ISTAT, several years [a], [b]

Annual crop production (t yr

- 1 ) ISTAT, 2009 [d]; ISTAT, several years [a], [b]

N fixed by type of species (kg N ha

- 1 ) Erdamn,1959 in Giardini, 1983

Residue/crop product ratio by crop ty pe CESTAAT, 1988

Crop residue production (t dry matter ha

- 1 yr - 1 ) CRPA/CNR, 1992

Dry matter content by crop type CRPA/CNR, 1992

Protein content in dry matter by crop type CESTAAT, 1988

Livestock data ISTAT, 2009[a]; ISTAT, several years [a], [b]



### In Table 6.32 and Table 6.33, time series of cultivated surface and crop production used for the preparation of the inventory are shown. In Table 6.30 the time series of the N content from

fertilizers are shown.

For estimating N 2 

### O direct soil emissions, the IPCC approach has been followed, and some modifications have been included because of country

- specific peculiarities (IPCC, 2000; IPCC,
1997). N

2 

### O

- N emissions have been estimated from the amount of synthetic fertilizers (F SN 

### ), animal waste applied to s

oil (F AM 

### )

, 

### c rop residues (F CR 

### ), N

- fixing crops (F BN 

### ) and c ultivation of histosols ( F OS 

### ). Then default IPCC emission factors (IPCC, 2000) have been applied. Afterwards N 2 

### O

- N

emissions were converted to N 2 

### O emissions, multiplying by the 44/28 coefficient. An imal Production emissions have been estimated according to the methodology described in section 6.3.2, for manure management. Indirect emissions have been estimated as suggested by IPCC (1997). As requested in the review process (UNFCCC, 2005), a review of the FRAC LEACH 

### parameter was done. Italy has verified that the IPCC default value is similar to the country specific reference value reported for the main regional basin authority

- Po Valley (ADBPO, 2001; ADBPO, 1994).

### 139

Direct emissions

Synthetic fertili zers (F SN 

### )

The total use of synthetic fertilizer (expressed in t N year

- 1 

### ) has been estimated for each type of fertilizer (see Table 6.25). The calculation of synthetic fertilizer use (F SN 

### ) has been obtained by multiplying the total use of fertilizer by ( 1

- FRAC GASF 

### ). FRAC GASF 

### parameter has been estimated for the whole time series, following the IPCC definition where the total N

- NH 3 

### and N

- NOx emissions from fertilizers are divided by the total nitrogen content of fertilizers. N 2 

### O emissions for synthetic fe rtilizers have been obtained multiplying F SN 

### by the emission factor 0.0125 kg N

- N 2 

### O/kg N (IPCC, 1997). In 2007, the total use of synthetic fertilizers was 760,063 t N, while F SN 

### parameter was 869,044 t N (see Table 6.27)

. 

### In the 2007 submission, a specific ation for “Other nitrogenous fertilizers” was introduced (ENEA, 2006). This improvement has been introduced since 1998, because of activity data availability. In Table 6.30, the time series of N content from fertilizers is presented

.

T able 6.25 Total use o f synthetic fertilizer in 2007 (t N yr - 1 )



### Animal waste applied to soil ( 

## F AM 

### ) The manure nitrogen corrected for NH 3 

### and NO

x 

### emissions, excluding manure produced during grazing (kg N yr

- 1 

### ), has been calculated with the IPCC methodology (IPCC, 1997), using country

specific nitrogen excretion rate s (CRPA, 2006[a]; GU, 2006; Xiccato et al ., 2005). A country

specific FRAC GASM 

### parameter has been estimated and used for the calculation of the animal waste applied to soil. In the 2009 submission FRAC GASM 

### (direct) and FRAC GASM 

### (indirect) have been reported ( see T

able 6.27)

. The estimation has followed the IPCC definition; therefore, the NH 3 

### and

NO

x 

### emissions from animal manure have been divided by the total nitrogen excreted. The F AM 

### (t yr
1 

### ) value has been estimate d by summing the F AM 

### for each livestock cat egory; then emissions have been calculated with emission factor 0.0125 kg N

- N 2 

### O/kgN (IPCC, 1997). In 2007, F AM 

### parameter was 447,969 t N. In the 2009 submission the time series of F AM 

### has been updated due to a revision

of CLRTAP

- NH 3 

### agriculture inventory ( see recalculation section 6.5.5).

T ype of fertilizers Fertilizers distributed (t/yr) Nitrogen content (%) Total use of synthetic

fertilizers (t N yr - 1 )

Ammonium sulphate 168,883 20.7% 35,039

Calcium cianamide 14,387 19.8% 2,847

Ammonium nitrat e < 27% 369,152 22.4% 82,760

Ammonium nitrate > 27% 127,106 47.7% 60,646

Calcium nitrate 64,414 15.7% 10,120

Urea 732,213 46.0% 336,686

Other nitric nitrogen (

Altri azotati nitrico ) 146,247 27.0% 4,989

Other ammoniacal nitrogen ( Altri azotati

ammonia cale ) - - 17,881

Other amidic nitrogenous ( Altri azotati

ammidico ) - - 17,412

Phosphate nitrogen 382,757 14.5% 55,674

Potassium nitrogen 110,070 16.4% 18,047

NPK nitrogen 883,037 9.5% 83,694

Organic mineral 396,219 8.7% 34,277

TOTAL 3,394,485 760,073

### 140

N

- fixing crops (F BN 

### ) Nitrogen input from N

- fixing crops (F BN 

### , kg N yr

- 1 

### ) has been calculated with a country

- specific methodology. Peculiarities that are present in Italy have been considered: N

- fixing crops and legumes f orage. F

BN 

### has been calculated with two parameters: cultivated surface and nitrogen fixed per hectare (Erdamn 1959 in Giardini, 1983). Emissions have been calculated using the emission factor 0.0125 kg N_N2O/kgN (IPCC, 1997). In Table 6.26, cultivated surf ace from N

- fixing species (ha yr

- 1 

### ) and nitrogen fixed by each species (kg N ha

- 1 

### yr - 1 

### ) are presented. In 2007, F BN 

### parameter was 160,757 t N (time series Table 6.27).

Crop residues (F CR 

### ) For the estimation of nitrogen input from crop residues (F CR ), a co untry

- specific methodology has been used. For all crops, the total amount of crop residues has been estimated (t dry matter yr

- 1 ), using the following parameters: annual crop production (t yr

- 1 ), residue/crop product ratio, and dry matter content by type o f crop (%), while, when cultivated surface (ha) has been used as activity data, only the crop residue production (t dry matter ha

- 1 yr

- 1) parameter has been used to assess total amount of crop residues. The nitrogen content from cereals, legumes, tubers an d roots and legumes forages crop residues (t N

yr

- 1 ) has been estimated multiplying the total amount of crop residue as dry matter by the reincorporated fraction (1

- FRAC BURN, where FRAC BURN is the fraction of crop residue that is

b urned rather than left o n field equal to 0.1 kg N/kg crop

- N), and the nitrogen content for each crop type. The nitrogen content has been obtained converting protein content in dry matter, dividing by

factor 6.25. The F

CR parameter has been obtained by adding the nitrogen content of cultivars crop
residues. In 2007, F

CR parameter was 124,377 t N (see Table 6.27). Emissions are calculated with emission factor 0.0125 kg N

- N 2 O/kg N (IPCC, 1997). The time series of crop residues production

is shown in Table 6.32.

Nitrogen

fixed 1990 1995 2000 2005 2006 2007

(kg N ha

1 yr - 1 ) (ha)

Bean, fresh seed
( fagiolo ) 40 29,096 23,943 23,448 23,146 22,017 22,130

Bean, dry seed (

fagiolo ) 40 23,002 14,462 11,046 8,755 8,179 6,923

Broad bean, fresh seed
( fava ) 40 16,564 14,180 11,998 9,484 9,694 9,792

Broad bean, dry seed
( fava ) 40 104,045 63,257 47,841 48,507 44,617 49,972

Pea, fresh seed
( pisello ) 50 28,192 21,582 11,403 11,636 12,589 11,805

Pea, dry seed (

pisello ) 72 10,127 6,625 4,498 11,134 13,625 12,957

Chickpea ( cece ) 40 4,624 3,023 3,996 5,256 5,188 5,299

Lentil ( lenticchia ) 40 1,048 1,038 1,016 1,786 1,738 1,806

Tare ( veccia ) 80 5,768 6,532 6,500 6,500 6,500 6,500

Lupin ( lupino ) 40 3,303 3,070 3,000 3,000 3,000 3,000

soya bean ( soia) 58 521,169 195,191 252,647 152,331 176,134 13 0,335

Alfalfa ( erba medica) 194 987,000 823,834 810,866 779,430 766,316 705,370

Clover grass ( trifoglio) 103 224,087 125,009 114,844 103,677 101,499 98,772

TOTAL 1,958,025 1,301,746 1,307,102 1,164,642 1,171,097 1,064,660

Table 6.26. Cultivated surf ace and nitrogen fixed by each variety

### 141

Cultivation of histosols (F

os 

### )

In Italy, the area of organic soils cultivated annually (histosols) is estimated to be 9,000 hectares (CRPA, 1997[b]). This value has been multiplied by 8 kg N

- N 2 

### O ha

- 1 

### yr - 1 

### , as sugge sted by IPCC (2000). The data for surface area, reproduced in the national soil map of the year 1961, have been supplied by the Experimental Institute for the study and protection of soil in Florence (ISSDS).

These values have been verified with related da ta for Emilia Romagna region, where this type of soil is most prevalent.

(*) FRAC GASM (indirect)

is reported in the Table4.Ds2 as “other fractions”

Table 6.27 Parameters used for the estimation of direct and indirect N 2 O emissions



### Animal production

As mentioned in section 6.3.2, when estimating N 2 

### O emissions from manu re management, the amount related to manure excreted while grazing is subtracted and reported in “Agricultural soils” under animal production

. In Table 6.15, nitrogen excretion rates (kg head

- 1 

### yr - 1 

### ) used for estimations are presented. Nitrous oxide emissio ns are estimated with the total nitrogen excreted from grazing (include all livestock categories), number of animals, and an EF of 0.02 kg N 2 

### O

- N/kg N excreted (IPCC, 1997).

Indirect emissions

For indirect emissions from agricultural soils the following parameters have been estimated:

• Atmospheric deposition

• Nitrogen leaching and run

- off Year F

SN (t N) F

AM (t N) F

BN (t N) F

CR (t N) F

os (ha) FRAC GASF FRAC GASM (direct) FRAC GASM

(indirect) (*)

1990 691,723 473,804 254,654 147,541 9,000 0.087 0.319 0.328

1991 764,911 47 3,328 240,032 149,041 9,000 0.087 0.319 0.328

1992 808,237 454,552 228,560 152,456 9,000 0.086 0.315 0.324

1993 860,390 451,435 211,235 141,823 9,000 0.090 0.311 0.321

1994 795,479 445,199 201,884 141,799 9,000 0.091 0.301 0.311

1995 726,343 453,400 19 1,018 142,216 9,000 0.089 0.298 0.308

1996 691,890 454,385 190,601 145,826 9,000 0.085 0.295 0.305

1997 782,973 456,905 194,257 147,351 9,000 0.086 0.293 0.303

1998 703,640 463,906 202,718 150,090 9,000 0.089 0.292 0.302

1999 716,405 469,741 191,722 15 0,228 9,000 0.091 0.290 0.300

2000 715,366 457,670 189,545 0 9,000 0.089 0.286 0.296

2001 737,063 467,276 182,928 137,779 9,000 0.089 0.299 0.307

2002 745,286 453,088 177,529 142,457 9,000 0.090 0.297 0.305

2003 750,296 452,633 175,154 119,184 9,000 0. 090 0.295 0.304

2004 765,064 440,978 172,532 143,172 9,000 0.091 0.294 0.302

2005 710,888 440,822 176,624 145,247 9,000 0.088 0.293 0.302

2006 710,021 431,635 175,243 128,431 9,000 0.092 0.290 0.299

2007 689,044 447,969 160,575 124,377 9,000 0.093 0.29 2 0.301

### 142

The estimation of N 2 

### O emissions due to atmospheric deposition of NH 3 

### and NO

x 

### has followed the IPCC approach (IPCC, 1997). Parameters which have been used are: total use of synthetic fertilizer, t N yr - 1 

### , FRAC GASF 

### emission factor, total N excreted by livestock (kg head

- 1 

### yr - 1 

### ), FRAC GASM 

### emission factor (see Table 6.27) and emission factor 0.01 kg N 2 

### O

- N per kg NH 3 

### - N + NO

x 

### - N emitted (IPCC, 2000; IPCC, 1997).

The estimation of N 2 

### O emissions due to nitrogen leaching and run

- off has followed the IPCC approach (IPCC, 1997). Parameters which have been used are: total use of synthetic fertilizer, t N

yr - 1 

### (see Table 6.25), total N excreted by livestock (kg head

- 1 

### yr - 1 

### ), FRAC LEACH 

### emi ssion factor 0.3 N/kg nitrogen of fertilizer or manure and the emission factor 0.025 Kg N 2 

### O

- N per kg nitrogen leaching/run

- off (IPCC, 2000; IPCC, 1997). As mentioned above, the FRAC LEACH 

### IPCC default value has been compared with the country specific FRAC LE ACH 

### (ADBPO, 2001; ADBPO, 1994).

In the 2009 submi s sion the time series of for Atmospheric deposition has been updated due to a

revision of CLRTAP

- NH 3 

### agriculture inventory (see recalculation section 6.5.5).

6.5.3. Uncertainty and time

- series consistency

Uncertainty for N 2 

### O emissions from agricultural soils (direct soil emissions, indirect soil emissions and animal production) has been estimated to be 102%, as combination of 20% and 100% for activity data and emission factor, respectively. In the Table 6. 28, time series of N 2 

### O emission are reported.

T able 6.28 Nitrous oxide emission trends from Agricultural soils (Gg)



### In 2007, N

2 

### O emissions from agricultural so ils were 8.5% (57.39 Gg N 2 

### O) lower than in 1990 (62.69 Gg N

2 

### O). In 2007, major contributions come from direct soil emissions (28.04 Gg) and indirect soil emissions (24.28 Gg). Indirect N 2 

### O emissions from nitrogen leaching and run

- off sub

category has the h

ighest individual contribution with respect to total 4D N 2 

### O emissions (19.10 Gg

N 2 

### O; 33%). N 2 

### O emissions from leaching and run

- off are related to the nitrogen content in Year Direct Soil Emissions Animal Production Indirect Soil emissions TOTAL

Gg

1990 30.91 5.60 26.19 62.69

1991 32.08 5.45 27.10 64.63

1992 32.40 5.47 27.10 64.97

1993 32.82 5.59 27.85 66.25

1994 31. 23 6.27 26.97 64.48

1995 29.83 6.44 26.12 62.39

1996 29.24 6.58 25.52 61.34

1997 31.18 6.52 26.83 64.53

1998 29.98 6.50 25.85 62.33

1999 30.13 6.59 26.21 62.93

2000 29.71 6.60 25.74 62.06

2001 30.07 5.18 25.64 60.89

2002 29.94 5.03 25.27 60.24

200 3 29.52 4.93 25.22 59.68

2004 30.00 4.98 25.15 60.14

2005 29.06 4.90 24.21 58.17

2006 28.50 5.02 24.08 57.60

2007 28.04 5.06 24.28 57.39

### 143

fertilizers and animal wastes. Therefore, emissions are mainly linked to the use of fe rtilizers and the

trend of livestock number. In 2007, the second individual source with respect to total N 2 

### O emissions w

as the direct emissions of synthetic fertilizers with 13.53 Gg (23.6%), followed by animal wastes applied to soils, with 8.80 Gg (15.3%) . In Table 6.29, a time series of N 2 

### O emissions is presented. We should highlight that between 1996 and 1997 there has been a high increase in nitrogen fertilizers in Italy, then emissions

from N 2 

### O could be identifi ed as outlier (see Table 6.30).

Direc t N

2 O emissions Indirect N 2 O emissions

Year Synthetic

fertilizer Animal

Wastes Applied to

Soils N

- fixing

Crops Crop

Residue Cultivation

of Histosols Animal

Production Atmospheric

Deposition Nitrogen

Leaching and

Run

- off

(Gg) (Gg) (Gg)

1990 13.59 9.31 5.00 2.90 0.11 5.60 5.97 20.22

1991 15.03 9.30 4.71 2.93 0.11 5.45 6.03 21.07

1992 15.88 8.93 4.49 2.99 0.11 5.47 5.86 21.23

1993 16.90 8.87 4.15 2.79 0.11 5.59 5.94 21.91

1994 15.63 8.74 3.97 2.79 0.11 6.27 5.77 21.20

1995 14.27 8.91 3.75 2.79 0.11 6.44 5.66 20.45

1996 13.59 8.93 3.74 2.86 0.11 6.58 5.52 20.00

1997 15.38 8.97 3.82 2.89 0.11 6.52 5.65 21.18

1998 13.82 9.11 3.98 2.95 0.11 6.50 5.58 20.27

1999 14.07 9.23 3.77 2.95 0.11 6.59 5.64 20.57

2000 14.05 8.99 3.72 2.84 0.11 6.60 5.46 20.28

2001 14.48 9.18 3.59 2.71 0.11 5.18 5.48 20.16

2002 14.64 8.90 3.49 2.80 0.11 5.03 5.34 19.93

2003 14.74 8.89 3.44 2.34 0.11 4.93 5.30 19.92

2004 15.03 8.66 3.39 2.81 0.11 4.98 5.23 19.92

2005 13.96 8.66 3.47 2.85 0.11 4.90 5.08 19.13

2006 13.95 8.48 3.44 2.52 0.11 5.02 5.05 19.03

2007 13.53 8.80 3.15 2.44 0.11 5.06 5.18 19.10
Table 6.29 Nitrous oxide emission trends from Agricultural soils (Gg)



### 6.5.4. Source

- specific QA/QC and verification

Synthetic fertilizers and nitrogen content are compared w ith the international FAO agriculture database statistics (FAO, 2009). In Table 6.30, national and FAO time series of total nitrogen applied are reported. Differences between national data and FAO database are related to the

difference in data elaboration (ISTAT, 2004) and could be attributed to different factors. First, national data are more disaggregated by substance than FAO data and the national nitrogen content
is considered for each substance, while FAO utilises default values. Besides, differences c ould also derive from different products classification. In Table 6.3 1 , activity data used for N 2 

### O estimations have been provided. In Table 6.3 2 , the QA/QC plan for this category is presented.

6.5.5. Source

- specific recalculations

Updates of N

2 

### O emissi

ons occurred due to the revision of NH 3 

### estimates for the CLRTAP

- NH 3 

### agriculture inventory. Emission factor s for cattle and buffalo for estimating N

- NH 3 

### emission

s from the spreading phase have been revised. Consequently, the fraction of livestock nitrogen excretion

that volatilizes as NH 3 

### and NO

x 

### from the CRLTAP

- NH 3 

### inventory has changed. This update is linked to the UNFCCC inventory, then N 2 

### O e missions, for the sub

- categories animal waste applied

### 144

to soil and atmospheric deposition (volatized nitrogen from fertilizers, animal manures and other)

, have changed.

Table 6.30 Total annual N content in fertilizer applied from 1990 to 2006

Tabl e 6.3 1 Cultivated surface, crop production and total residue production time series

Year of

s ubmission Activities Year National data (t N) FAO database (Nitrous fertilizer consumption, Mt)

1990 757,509 878,960

1991 837,402 906,720

1992 884,121 910,000

1993 945,290 917,900

1994 875,536 879,200

1995 797,500 875,000

1996 756,057 876,000

1997 856,945 855,000

1998 772,227 845,000

1999 788,243 868,000

2000 785,593 828,000

2001 808,964 773,161

2002 819,352 785,314

2003 824,649 Not available

2004 841,363 Not available

2005 779,846 Not available

2006 781, 824 Not available

2007 760,073 Not available

Year Cultivated surface (ha) Crop production (t) Total residue production (dry matter)

1990 2,128,674 82,247,958 20,719,032

1991 1,9

45,347 83,683,020 21,282,647

1992 1,831,020 86,462,112 21,505,656

1993 1,623,307 80,844,539 20,516,890

1994 1,568,346 81,267,156 20,465,054

1995 1,484,453 81,343,949 20,466,710

1996 1,484,242 83,163,618 21,302,559

1997 1,548,889 83,792,787 20,778,350

1998 1,622,647 84,466,234 21,453,885

1999 1,494,345 87,413,587 21,412,200

2000 1,491,315 82,090,948 20,685,353

2001 1,438,578 77,979,120 19,813,878

2002 1,350,329 82,289,945 20,647,499

2003 1,338,109 66,503,842 17,301,569

2004 1,314,187 81,403,175 21,351,753

2005 1,338,663 84,706,239 20,800,493

2006 1,352,385 71,186,530 19,239,493

2007 1,242,481 67,956,014 18,761,665

### 145 Year of

s ubmission Activities

2009 2010

Direct

emissions Sewage

sludge v A new study is being carried out for the land spreading category. We expect results for the end of 2009. Italy is aware that sewage sludge is
applied to soils but no reliable information is available to estimate emissions in the agriculture sector. Currently, the total amount of nitrogen present in the sewage sludge and its emissions are estimated in the waste

sector Activity data Fertilizer v Verify outcomes from ISPRA /MINAMBIENTE pro ject for the use of slow

release fertilizers.

Table 6.3 2 Improvements for the agricultural soils category in the QA/QC plan



### 6.5.6. Source

- specific planned improvements

Italy is aware that sewage sludge is applied to soils but no reliable information is available to estimate emissions in the agriculture sector. Anyway, the total amount of nitrogen present in the sewage sludge and its emissions are estimated in the waste sector (section 8.3, CRF 6B).

6.6. Field burning of agriculture residues (4F)

6. 6.1. Source category description

Methane and nitrous oxide emissions from field burning agriculture residues have not been

identified as a key source. In 2007, CH 4 

### emissions from this source were 0.61 Gg, which represents only 0.082% of emissions for the agriculture sector. N 2 

### O emissions were 0.013 Gg, which represents 0.019% of emissions for the agriculture sector.

6.6.2. Methodological issues

A country

- specific methodology has been used for estimating emissions from field burning of agriculture residu

es. Different IPCC parameters have been considered, such as amount of residues produced, amount of dry residues, total biomass burned, and total carbon and nitrogen released. Activity data used for estimating burning of agriculture residues have been summa rised in the following box (see Table 6.33).

Data used for estimating field burning of agriculture residues emission

Data Reference

Annual crop production ISTAT, 2009[d]; ISTAT, several years [a], [b]

Removable residues/product ratio CESTAAT, 1988

Fixed residues/removable residues ratio ENEA, 1994

Fraction of dry matter in residues IPCC, 1997; CRPA/CNR, 1992; CESTAAT, 1988; Borgioli, 1981

Fraction of the field where “fixed” residues are burned ANPA

- ONR, 2001; CESTAAT, 1988; IPCC, 1997

Fraction of residues oxidized during burning IPCC, 1997

Fraction of carbon from the dry matter of residues IPCC, 1997

Raw protein content from residues (dry matter fraction) CESTAAT, 1988; Borgioli, 1981

IPCC Default Emission rates (CH 4 , N 2 0) IPCC, 1997



### The same methodology has been used to estimate emissions from burning of agriculture residues, fixed and removable, but they are reported in two different sectors. Emissions from fixed residues, stubble ( stoppie ), burnt on open fields, are reported in this ca tegory (4F) while emissions from

### 146

removable residues ( asportabili ) burnt off

- site, are reported under the waste sector (waste

incineration

- 6C category).

Table 6.33 Time series of activity data used for field burning of agricultural residues (t)



### The methodology for estimating emissions refers to fixed residues burnt. The same steps have been followed to calculate emissions from removable residues burnt reported in 6C. Parameters taken into consideration are the following: a) Amount of “fixed” burnab le residues 13 

### (t), estimated with annual crop production, removable residues/product ratio, and “fixed” residue/removable residues ratio. b) Amount of dry residues in “fixed” residue 14 

### (t dry matter), calculated with amount of burnable

residues and fraction of dry matter.
c) Amount of “fixed” dry residues oxidized 15 

### (t dry matter), assessed with amount of dry residues
in the “fixed” residues, fraction of the field where “fixed” residues are burned, and fraction of residues oxidized during burning. d) Amount of carbon f rom stubble burning release in air 16 

### (t C), calculated with the amount of “fixed” dry residue oxidized and the fraction of carbon from the dry matter of residues.
e) C

- CH

4 

### from stubble burning 17 

### (t C

- CH 4 

### ), calculated with the amount of carbon from stubble

burni ng release in air and default emissions rate for C

- CH 4 

### , equal to 0.005 (IPCC, 1997).
In 2007, final CH 4 

### emissions from on field burning of agriculture residues (0.61 Gg CH 4 

### ) have been estimated multiplying the C

- CH 4 

### value (0.459 Gg C

- CH 4 

### ) by the coefficien

t 16/12. In Table 6.34, parameters used for the estimation of CH 4 

### emissions from on field burning of agriculture residues

are shown.

13 Quantità di residuo "fisso" bruciabile (produzione totale) (ton)

14 Quantità di residuo secco nel residuo "fisso" (t onnellate di sostanza secca)

15 Quantità residuo secco "fisso" ossidato (ton di sost. secca)

16 Quantità di carbonio rilasciato in aria dalla combustione delle stoppie (tonnellate di carbonio)

17 Emissione di C

- CH4 dalla combustione delle stoppie (tonnellate di C

- CH4) Year Wheat Barley Maize Oats Rye Rice Sorghum

1990 8,108,500 1,702,500 5,863,900 298,400 20,800 1,290 ,700 114,200

1991 9,415,700 1,792,900 6,237,700 359,400 18,800 1,235,600 149,500

1992 8,938,400 1,742,087 7,394,100 333,100 22,586 1,271,600 178,700

1993 8,169,800 1,634,200 8,028,900 372,200 22,800 1,305,100 226,800

1994 8,251,401 1,467,378 7,483,438 354,660 20,295 1,360,519 236,060

1995 7,946,081 1,387,069 8,454,164 301,322 19,780 1,320,851 214,802

1996 8,424,492 1,350,494 9,547,541 351,622 20,400 1,359,697 209,191

1997 6,758,351 1,179,575 10,004,700 310,706 19,000 1,442,400 173,570

1998 8,338,301 1,359,076 9,054,600 362,627 20,100 1,407,100 159,872

1999 7,742,782 1,313,323 10,017,178 331,150 12,363 1,427,130 202,370

2000 7,427,660 1,261,560 10,139,639 317,926 10,292 1,245,555 215,200

2001 6,413,329 1,125,720 10,556,185 310,087 8,588 1,272,952 2 13,992

2002 7,547,763 1,190,326 10,554,423 328,759 9,631 1,378,796 215,072

2003 6,229,454 1,020,838 8,702,289 306,425 6,941 1,448,212 158,217

2004 8,638,721 1,156,620 11,368,007 337,694 7,851 1,525,509 215,394

2005 7,717,129 1,214,054 10,427,930 429,15 3 7,876 1,444,818 184,915

2006 7,181,720 1,297,395 9,626,373 394,866 8,590 1,449,973 221,392

2007 7,170,180 1,225,282 9,809,265 361,147 8,953 1,540,097 193,243

### 147

Table 6.34 Parameters used for the estimation of CH 4 emissions from agriculture residues in 2007



### For estimating N 2 

### O emissions, the same amount of “fixed” dry residue oxidized described above has been used; further parameters are: a) Amount of nitrogen from stubble burning release in air 18 

### (t N ), calculated with the amount of “fixed” dry residue oxidized and the fraction of nitrogen from the dry matter of residues. The fraction of nitrogen has been calculated considering raw protein content from residues (dry matter fraction) divided by 6.25. b) N

- N 2 

### O from stubble burning 19 

### (t N

- N 2 

### O), calculated with the amount of nitrogen from stubble burning release in air and the default emissions rate for N

- N 2 

### O, equal to 0.007 (IPCC, 1997).

In 2007, final N 2 

### O emissions from on field burning of agriculture resid ues (0.013 Gg N 2 

### O) are estimated by multiplying the N

- N 2 

### O value (0.008 Gg N) with the coefficient 44/28. Table 6.35 shows parameters for the estimation of CH 4 

### emissions from field burning of agriculture residues.

Table 6.35 Parameters used for the estimation of nitrous oxide from agriculture residues in 2007



### 6.6.3. Uncertainty and time

- series consistency

Uncertainties for CH 4 

### and N 2 

### O emissions from field burning of agriculture residues are esti mated to be 54% as a result of 50% and 20% for activity data and emission factor, respectively. In 2007, CH 4

18 Quantità di azoto rilasciato in aria dalla combustione delle stoppie (ton di azoto)

19 Emissione di N

- N2O dalla combustione delle stoppie (tonnellate di N

- N2O) Crop Annual crop

production
(t 1000) Amount of

“fixed” burnable

residues
(t 1000) Amount of dry

residue in the

“fixed” re sidues (t 1000 dry
matter) Amount of “fixed”

dry residues

oxidized (t 1000 dry
matter) Amount of

carbon from

stubble burning
(t 1000 C) C

- CH 4 from stubble
burning
(t C

- CH

4 )

Wheat ( frumento ) 7,170 1,237 1,055 92 45 224

Rye ( segale ) 9 2 1 0 0 0

Barley ( orzo ) 1,225 245 210 19 7 35

Oats ( avena ) 361 63 54 5 2 10

Rice ( riso ) 1,540 258 194 87 36 180

Maize ( granoturco) 9,809 981 409 0 0 0

Sorghum (

sorgo da granella ) 193 68 56 5 2 9

TOTAL 20,308 2,853 1,979 208 92 459

Crop Amount of

“fixed” dry

residue oxidized (t 1000 dry
matter) Raw protein

content from

residues (dry matter
fraction) Fraction of

nitrogen from the dry matter

of residues Amount of

nitrogen from stubble burning (t
1000 N) N

- N 2 O from stubble

burning
(t N

- N 2 O)

Wheat ( frumento ) 92 0.030 0.005 0.44 3 3.1

Rye ( segale ) 0 0.036 0.006 0.001 0.0

Barley ( orzo ) 19 0.037 0.006 0.112 0.8

Oats ( avena ) 5 0.04 0.006 0.031 0.2

Rice ( riso ) 87 0.041 0.007 0.571 4.0

Maize ( granoturco) 0 0.007 0.000 0.0

Sorghum (

sorgo da granella ) 5 0.037 0.006 0.030 0.2

TOTA L 208 1.188 8.3

### 148

emissions from field burning of agriculture residues were 0.61 Gg CH 4 

### and N

2 

### O emissions were 0.013 Gg N 2 

### O (see Table 6.36). Variation in emissions trend is related to cereal production trends.

Table 6.36 CH

4 and N

2 O emission trends from field burning of agriculture residues (Gg)



### 6.6.4. Source

- specific QA/QC and verification

In response to the review process (UNFCCC, 2007[a]) and in order to verify the national assumption, which considered that 10% of the cultivated surface (cereals) are burned in Italy, a specific elaboration of data was done. ISTAT has pro vided information regarding the regional practise of field burning (cereals). The source of information has been the FSS 2003 . We have confirmed the assumption with data coming from national agricultural statistics (ISTAT, 2007[c]).

6.6.5. Source

- specific recalculations

For the year s 2004

- 2006 updated information on rice production has been provided (ENR, 2009).

6.6.6. Source

- specific planned improvements

No specific improvements are planned

.

Year CH 4 (Gg) N 2 O (Gg)

1990 0.623 0.013

1991 0.677 0.014

1992 0.662 0.014

1993 0.635 0.013

1994 0.641 0.013

1995 0.616 0.013

1996 0.642 0.013

1997 0.575 0.012

1998 0.643 0.013

1999 0.621 0.013

2000 0.578 0.012

2001 0.534 0.011

2002 0.601 0.013

2003 0.546 0.012

2004 0.669 0.014

2005 0.621 0.013

2006 0.604 0.013

2007 0.612 0.013

### 149



## Chapter 7: L AND 

## U SE 

## , L AND 

## U SE 

## C HANGE AND 

## F ORESTRY 

## [CRF SECTO R 

## 5]

7.1 Overview of sector

CO 2 

### emissions and removals occur as a result of changes in land

- use and from forests. The sector is responsible for 70.9 Mt of CO 2 

### removals from the atmosphere in 2007.

The 2003 IPCC Good Practice Guidance for LULUCF has been entirely applied for all the categories of this sector as detailed data were available from national statistics and from researches at national and regional level, whereas for category 5A (Forest Land) estimates were supplied by a growth model, applied to national forestry inventory data, with country specific used emission

factors.

CO 2 

### emissions from forest fires have been included in the calculation of the net carbon stocks reported in 5A. Greenhouse gas removals and emissions in the main categories of the LULUCF sector in 2007 are shown in Figure 7.1:

-145,000 -120,000 -95,000 -70,000 -45,000 -20,000 5,000 30,000 55,000 80,000

Forest Land Cropland Grassland SettlementsGg CO2 eq. removals

emissions

Figure 7.1 Greenhouse gas removals and emissions in LULUCF sector in 2007 [Gg CO 2 eq.]



### In Table 7.1 emissions and removals time series is reported.

### 150

GHG Gas Source and Sink Categories 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO 2 - 67,651

- 85,816

- 79,326

- 92,672

- 95,683

- 126,870

- 91,878

- 95,374

- 90,136

- 71,127

A. Forest Land

- 53,549

- 77,555

- 70,452

- 79,009

- 85,423

- 74,789

- 80,933

- 83,523

- 84,194

- 55,588

B. Cropland

- 16,876

- 10,406

- 11,697

- 10,956

- 11,544

- 11,085

- 8,881

- 10,155

- 8,087

- 10,960

C. Grassland

- 385 NO

- 387

- 5,911

- 1,918

- 44,161

- 5,224

- 4,849 NO

- 7,760

D. Wetlands NO NO NO NO NO NO NO NO NO NO

E. Settlements 3,160 2,145 3,210 3,204 3,202 3,165 3,160 3,153 2,145 3,181

F. Other Land NO NO NO NO NO NO NO NO NO NO

G. Other NA NA NA NA NA NA NA NA NA NA

CH 4 142.89 27.37 87.00 55.19 30.93 64.97 34.62 34.16 30.62 196.75

A. Forest Land 142.89 27.37 87.00 55.19 30.93 64.97 34.62 34.16 30.62 196.75

B. Cropland 0 0 0 0 0 0 0 0 0 0

C. Grassland 0 0 0 0 0 0 0 0 0 0

D. Wetlands 0 0 0 0 0 0 0 0 0 0

E. Settlements 0 0 0 0 0 0 0 0 0 0

F. Other Land 0 0 0 0 0 0 0 0 0 0

G. Other 0 0 0 0 0 0 0 0 0 0

N 2 O 14.50 199.00 8.83 5.60 3.14 6.59 3.51 3.47 301.62 19.97

A. Forest Land 1 4.50 2.78 8.83 5.60 3.14 6.59 3.51 3.47 3.11 19.97

B. Cropland 0 196.23 0 0 0 0 0 0 298.51 0

C. Grassland 0 0 0 0 0 0 0 0 0 0

D. Wetlands 0 0 0 0 0 0 0 0 0 0

E. Settlements 0 0 0 0 0 0 0 0 0 0

F. Other Land 0 0 0 0 0 0 0 0 0 0

G. Other 0 0 0 0 0 0 0 0 0 0

LULUCF (

Gg CO2 equivalent )

- 67,493

- 85,590

- 79,230

- 92,611

- 95,649

- 126,798

- 91,840

- 95,336

- 89,804

- 70,910

Table 7.1 Trend in greenhouse gas emissions from the LULUCF sector in the period 1990

- 2007

### 15 1

CO 2 

### emissions and removals in LULUCF sector, in the period 1990

- 2007, are shown in the figure 7.2:

0 30.000 60.000 90.000 120.000 150.000 180.000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007Gg CO2 

### removals

emissions

Figure 7.2 CO 2 removals and emissions in LULUCF sector in the period 1990

- 2007 [Gg CO 2 ]



### The outcome of the key category analysis for 2007, according to a level and/or trend assessment ( IPCC Tier 1 and Tier 2 approaches ), is listed in the T able 7.2. CO 2



### emissions and removals from forest land remaining forest land, conversion to forest land, cropland remaining cropland, conversion to cropland, land converted to grassland and land converted to settlem ents have been identified as key sources or sinks. Concerning CH 4 

### or N 2 

### O emissions, no categories have resulted as a key source.

gas categories 2007

5.A.1 CO 2 Forest land remaining forest land key (L, T)

5.A.2 CO 2 Land converted to forest land key (L2 , T2)

5.B.1 CO 2 Cropland remaining cropland key (L, T)

5.B.2 CO 2 Land converted to cropland Non

- key

5.C.1 CO 2 Grassland remaining Grassland Non

- key

5.C.2 CO 2 Land converted to Grassland key (L, T)

5.D CO 2 Wetlands Non

- key

5.E CO 2 Settlements remainin g Settlements Non

- key

5.E CO 2 Land converted to Settlements key (L,T2)

5.A.1 CH

4 Forest land remaining forest land Non

- key

5.A.1 N 2 O Forest land remaining forest land Non

- key

5.B.2 N 2 O Land converted to cropland Non

- key

Table 7.2 Key categories identi fication in LULUCF sector



### For the land use conversion, land use change matrices have been used; the matrices have allowed to point out the average areas of transition land, separately for each initial and final land use (i.e. forest land, grassland, etc. ). LUC matrices for each year of the period 1990

– 2007 have been assembled based on time series of national land use statistics for forest lands, croplands, grasslands, wetlands and settlement areas. Annual figures for areas in transition between different land uses have been derived by a hierarchy of basic assumptions (informed by expert judgement) of known patterns of land

- use changes in Italy as well as the need for the total national area to remain constant. Growth in

### 152

forest land area as detected by the National Forest Inventory is used as the basis. The rule then assumes that new forest land area can only come from grassland and no deforestation is occurring. Settlements area can only come from grassland or cropland. New cropland area can only come from

grassland area, as new grassland area can only come from cropland area. Changes in carbon stocks associated with the transitions have been reported as a whole in a single year (i.e. the year of conversion). While this may be valid for losses of abovegroun d biomass due to some land conversions, soil carbon is in a steady state equilibrium in natural ecosystems and change in land use is expected to affect soil carbon sequestration dynamics and consequently soil carbon stocks. Current approaches assume that a fter a cultivation of a forest or grassland, there is an initial carbon loss over the first years which rapidly reduces to a lower subsequent loss rate in the following years (Davidson and Ackerman 1993). This loss could be attributed to the response of th e faster

- cycling C pools that contribute most of the decomposition flux, commonly described by first

- order decomposition kinetics (Olson, 1963). In a similar way, soils are expected to gain carbon in cropland converted to grassland (Guo & Giffort 2002, Pos t and Kwon 2000) at fast rates in the first stages of the conversion (Reeder 1998). However because the dynamics of soil carbon storage and release are complex and still not well understood, the magnitude and timing of the response of the soil carbon to ch ange in land use should be considered affected by a large uncertainty. On this basis and by considering the spatial resolution of data we used, we conclude that a reasonable approach, in calculating the effect of land use change, could be assuming that the changes in carbon stocks carbon occur in the first year after the land conversion, in spite of considering them over the time period (20 years as default) specified by IPCC GPG LULUCF (2003). From a technical point of view, we are confident to account, by this method, for the larger part of the total amount of carbon exchanged to the atmosphere; a severe effort and enhanced quality data would be required to obtain the necessary high degree of spatial disaggregation of areas affected by the land use change every year in a 20 years time period. The contribution from stock changes is thus applied in the first year following the relevant land

use change, and it is applied only once, for the year in which it is determined. In the following Table 7.3, the land u se matrices for each year of the period 1990 –2007 are reported.

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 1990 9.058 7.747 11.045 57 1.340 887 30.134

Forest 9.058 9.058

Grassland 96 7.747 0 0 7.747
Cropland 9 11.045 8 11.045

Wetland 57 57

Settlements 1.340 1.340

Other Land 887 887

Final sum 9.154 7.659 11.028 57 1.348 887 30.134 19891990

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 1991 9.154 7.659 11.028 57 1.348 887 30.134

Forest 9.154 9.154

Grassland 96 7.659 0 0 7.659
Cropland 41 11.028 8 11.028

Wetland 57 57

Settlements 1.348 1.348

Other Land 887 887

Final sum 9.250 7.605 10.979 57 1.356 887 30.1341991 1990

### 153 Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 1992 9.250 7.605 10.979 57 1.356 887 30.134

Forest 9.250 9.250

Grassland 96 7.605 0 0 7.605
Cropland 42 10.979 8 10.979

Wetland 57 57

Settlements 1.356 1.356

Other Land 887 887

Final sum 9.345 7.551 10.928 57 1.365 887 30.1341992 1991

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 1993 9.345 7.551 10.928 57 1.365 887 30.134

Forest 9.345 9.345

Grassland 96 7.551 17 8 7.551
Cropland 0 10.928 0 10.928

Wetland 57 57

Settlements 1.365 1.365

Other Land 887 887

Final sum 9.441 7.430 10.945 57 1.373 887 30.134 19921993Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 1994 9.441 7.430 10.945 57 1.373 887 30.134

Forest 9.441 9.441

Grassland 96 7.430 43 8 7.430
Cropland 0 10.945 0 10.945

Wetland 57 57

Settlements 1.373 1.373

Other Land 887 887

Final sum 9.537 7.284 10.988 57 1.381 887 30.134 19931994Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 1995 9.537 7.284 10.988 57 1.381 887 30.134

Forest 9.537 9.537

Grassland 96 7.284 34 8 7.284
Cropland 0 10.988 0 10.988

Wetland 57 57

Settlements 1.381 1.381

Other Land 887 887

Final sum 9.632 7.145 11.022 57 1.389 887 30.1341995 1994Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 1996 9.632 7.145 11.022 57 1.389 887 30.134

Forest 9.632 9.632

Grassland 96 7.145 0 0 7.145
Cropland 64 11.022 8 11.022

Wetland 57 57

Settlements 1.389 1.389

Other Land 887 887

Final sum 9.728 7.114 10.949 57 1.398 887 30.1341996 1995

### 154Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 1997 9.728 7.114 10.949 57 1.398 887 30.134

Forest 9.728 9.728

Grassland 96 7.114 9 8 7.114
Cropland 0 10.949 0 10.949

Wetland 57 57

Settlements 1.398 1.398

Other Land 887 887

Final sum 9.824 7.001 10.958 57 1.406 887 30.1341997 1996Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 1998 9.824 7.001 10.958 57 1.406 887 30.134

Forest 9.824 9.824

Grassland 96 7.001 68 8 7.001
Cropland 0 10.958 0 10.958

Wetland 57 57

Settlements 1.406 1.406

Other Land 887 887

Final sum 9.920 6.829 11.026 57 1.414 887 30.1341998 1997Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 1999 9.920 6.829 11.026 57 1.414 887 30.134

Forest 9.920 9.920

Grassland 96 6.829 97 8 6.829
Cropland 0 11.026 0 11.026

Wetland 57 57

Settlements 1.414 1.414

Other Land 887 887

Final sum 10.015 6.628 11.123 57 1.422 887 30.1341999 1998Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 2000 10.015 6.628 11.123 57 1.422 887 30.134

Forest 10.015 10.015

Grassland 96 6.628 0 0 6.628
Cropland 9 11.123 8 11.123

Wetland 57 57

Settlements 1.422 1.422

Other Land 887 887

Final sum 10.111 6.541 11.106 57 1.431 887 30.1342000 1999

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 2001 10.111 6.541 11.106 57 1.431 887 30.134

Forest 10.111 10.111

Grassland 96 6.541 0 0 6.541
Cropland 132 11.106 8 11.106

Wetland 57 57

Settlements 1.431 1.431

Other Land 887 887

Final sum 10.207 6.578 10.965 57 1.439 887 30.134 20002001

### 155Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 2002 10.207 6.578 10.965 57 1.439 887 30.134

Forest 10.207 10.207

Grassland 96 6.578 0 0 6.578
Cropland 43 10.965 8 10.965

Wetland 57 57

Settlements 1.439 1.439

Other Land 887 887

Final sum 10.303 6.525 10.914 57 1.447 887 30.134 20012002Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 2003 10.303 6.525 10.914 57 1.447 887 30.134

Forest 10.303 10.303

Grassland 96 6.525 0 0 6.525
Cropland 990 10.914 8 10.914

Wetland 57 57

Settlements 1.447 1.447

Other Land 887 887

Final sum 10.398 7.419 9.916 57 1.455 887 30.134 20022003Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 2004 10.398 7.419 9.916 57 1.455 887 30.134

Forest 10.398 10.398

Grassland 96 7.419 0 0 7.419
Cropland 117 9.916 8 9.916

Wetland 57 57

Settlements 1.455 1.455

Other Land 887 887

Final sum 10.494 7.441 9.791 57 1.464 887 30.1342004 2003Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 2005 10.494 7.441 9.791 57 1.464 887 30.134

Forest 10.494 10.494

Grassland 96 7.441 0 0 7.441
Cropland 109 9.791 8 9.791

Wetland 57 57

Settlements 1.464 1.464

Other Land 887 887

Final sum 10.590 7.454 9.674 57 1.472 887 30.134 20042005

### 156Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 2006 10.590 7.454 9.674 57 1.472 887 30.134

Forest 10.590 10.590

Grassland 96 7.454 52 8 7.454
Cropland 0 9.674 0 9.674

Wetland 57 57

Settlements 1.472 1.472

Other Land 887 887

Final sum 10.686 7.297 9.726 57 1.480 887 30.134 20052006Final

Forest Grassland Cropland Wetland Settlements Other Land Initial sum



### 2007 10.686 7.297 9.726 57 1.480 887 30.134

Forest 10.686 10.686

Grassland 97 7.297 0 0 7.297
Cropland 174 9.726 8 9.726

Wetland 57 57

Settlements 1.480 1.480

Other Land 887 887

Final sum 10.782 7.375 9.544 57 1.488 887 30.134 20062007

Table 7.3 Land use change matrices for the years 1990

- 2007



### 7.2 Forest Land (5A)

7.2.1 Source category description

Under this category, CO 2 

### emissions, from living biomass, dead organic matter and soils, from forest land remaining forest land and from land converted in forest land have been reported. Net carbon stocks change by land converted in forest land, for the living biomass, dead or ganic matter and soils sectors, is included in the assessment of carbon stocks change in living biomass, dead organic matter and soils for forest land remaining forest land.

Forest land removals share 72% of total CO 2 

### 2007 LULUCF emissions and removals, wh ile the

mean forest land removals for the years 1990

- 2007 is 81% of total mean CO 2 

### LULUCF emissions and removals; in particular the living biomass removals represent 46%, while the removals from dead organic matter and soils stand for 8% and 46% of total 2 007 forest land

CO 2 

### removals, respectively.

Forest Land 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

- living biomass 39 47 46 48 49 47 48 48 49 41

- dead organic

matter 8 8 9 8 8 9 8 8 8 9

- soils 53 45 45 44 43 45 44 43 43 49

Table 7.4 Per centage contribution of carbon pools to forest land category, in 1990

- 2007



### CO 2 

### removals from forest land remaining forest land have identified as key category (sinks) in level and in trend assessment (Tier 1); CO 2 

### emissions and removals from land converti ng to forest land have identified as key category in level and in trend assessment (Tier 2); Concerning the CH 4 

### or N 2 

### O emissions, neither forest land nor land converting to forest land have resulted as a key source.

### 157

7.2.2 Methodological issues

Forest L and remaining Forest Land All the data concerning the growing stock and the related carbon are assessed by a model (Federici et al., 2008), estimating the evolution in time of the Italian forest carbon pools, according to the GPG classification and definit ion: living biomass, both aboveground and belowground, dead organic matter, including dead wood and litter, and soils as soil organic

matter. The model has been applied at regional scale (NUTS2) because of availability of any forest

related statistical dat a: input data for the forest area, per region and inventory typologies 20 

### , were the First Italian National Forest Inventory (IFN) data and the Inventory of Forests and Carbon pools (INFC)

. The Italian Ministry of Agriculture and Forests (MAF) and the Experi mental Institute for Forest Management (ISAFA) carried out the first National Forest Inventory in 1985. As a result of the first IFN based on a regular sampling grid of 3 km by 3 km, the global Italian extent of forest

resources was about 8.7 million hecta res (MAF/ISAFA, 1988). A second national forest inventory, using a grid of 1 km by 1 km, had been launched in 2001. A first inventory phase, consisting in interpretation of orthophotos, w as followed by a ground survey, in order to assess
the forest use, an

d to detect the main attributes of Italian forests. The final result, regarding forest surfaces, has been used (INFC, 2007). The estimation for 1990 was calculated through a linear interpolation between the 1985 and 2005 data. By assuming that the defined trend may well represent the near future, it was possible to extrapolate data for 2006

- 2007.
Additional source of information was the National Statistics Institute (ISTAT), which had provided annual data on forest area extent, till 2005. In 2006, the Nat ional Statistics Institute has officially recognized the INFC data, suspending the annual assessment on forest area extent.

To estimate the growing stock of Italian forest, from 1990 to 2007, the following methodology was applied:

1. the initial growing stoc k volume is the 1985 growing stock data (MAF/ISAFA, 1988);

2. starting from 1985, for each year, the current increment per hectare [m 3 

### ha

- 1 

### ] is computed with the derivative Richards function 21 

### , for each forest typology by the Italian yield tables collection;

3. s tarting from 1986, for each year the growing stock per hectare [m 3 

### ha

- 1 

### ] is computed, from the previous year growing stock volume, with the addition of the calculated increment (“y” value of the derivative Richards) for the current year and subtraction of the losses due to harvest, mortality and fire for the current year.

20 The inventory typolo gies are classified in 4 main categories: Stands, Coppices, Plantations and Protective Forests. The typologies for each category are:

Stands : norway spruce, silver fir, larches, mountain pines, mediterranean pines, other conifers, european beech, turkey o ak,
other oaks, other broadleaves

. Coppices: european beech, sweet chestnut, hornbeams, other oaks, turkey oak, evergreen oaks, other broadleaves, conifers

. Plantations: eucalyptuses coppices, other broadleaves coppices, poplar stands, other broadleaves stands, conifers stands,

others

. Protective Forests: rupicolous forest, riparian forests, shrublands

21 In the followed approach the Richards function is fitted through the data of growing stock [m 3 ] and increment [m 3 y - 1 ] obtained by the data of the natio nal forestry inventory and yield tables collection. The independent variable, x, represents the growing stock of the stand, while the dependent variable y is the correspondent increment computed with the Richards function

- first derivative.

0

1 y

a y y k

dt dy

+

   

         

− ⋅⋅ = n

n (first derivative)

where the general constrain for the parameters are the following:

a
, k >0

- 1 =v=8 and v ?0 The constant y 0 is derived from the data of age and volume reported in the yield tables: more precisely y 0 has the value of the volume for the age 1. After choosing the function, it is fitted to the measurements by non

- linear regress ion. The minimization of the deviation is performed by the least squares method. The model performances were evaluated against the data by validation statistics according to Jabssen and Heuberger (1995).

### 158

The relationship can be summarized as follows:

i iiiiii

i 

### A D

M F H I V

v −−−−+

= − 1



### where : 

# ( )

11

−− 

### ⋅ = ii i 

### A v f I

in which the current increment is estimated year by year applying the derivative R ichards

function and

above reported function Richards the is year previous for the pology forest ty specific a to referred area total the is A hectare per me stock volu growing year previous the is year current for the pology forest ty specific a to referred area total the is A forest protective for the grazing and drain of rate annual the is D mortality of rate annual the is Mi year current for the stock growing burned of amount total the is F year current for the stock growing harvested of amount total the is H year current for the stock growing of increment current total the is I me stock volu growing year previous total the is V year current for the stock growing of hectare per volume the is

1

- i 1 i i i i 1

- i



### f v v

i i

−



### The average rate of mortality, the fraction of standing biomass per year, used for the calculation was 0.0116, concerning the evergreen forest, and 0.0117, for deciduous forest, according to the GPG (IPCC, 200 3). The rate of draining and grazing, applied to protective forest, has been set as 3% following an expert judgement ( Federici et al., 2008) because of total absence of referable data.

Total commercial harvested wood, for construction and energy purposes, has been obtained
from national statistics (ISTAT , several years [a]); even if data on biomass removed in commercial harvest published by ISTAT are probably underestimated, particularly concerning fuelwood consumption ( ( APAT

- ARPA Lombardia, 2007 , UNECE

–FAO, Timber Committee, 2008). Data of wood use for construction and energy purposes, reported in m 3 

### , are disaggregated at NUTS2 level, in sectoral statistics (ISTAT , several years [a]) or at NUTS1 level for coppices and high forests in national statisti cs (ISTAT, several years [c]). These figures

have been subtracted, as losses, to growing stock volume, as abovementioned. Carbon amount released by forest fires has been included in the overall assessment of carbon stocks change. Not having data on the fra ction of growing stock oxidised as consequence of fires, the most conservative hypothesis has been adopted; all growing stock of burned forest areas has been assumed to be completely oxidised and so released. Moreover, not having data on forest typologies of burned areas, the total value of burned forest area coming from national statistics has been subdivided and assigned to forest typologies based on their respective weight on total national forest area. Finally, the amount of burned growing stock has bee n calculated multiplying average growing stock per hectare of forest typology for the assigned burned area. Assessed value has been subtracted to total growing stock of respective typology, as aforesaid. In the figure 7.3, losses of carbon due to harvest a nd forest fires, referred to forest land category and reported as percentage on total aboveground carbon, are shown.

### 159 0.00 0.50 1.00 1.50 2.00 2.50

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

% Losses in aboveground carbon by harvest

Losses in aboveground carbon by fires

Figure 7.3 Losses by harvest and fires in relation to aboveground carbon



### In the following Table 7.5, values of burned growing stocks and respective CO 2 

### rele ased, for different categories (stands, coppices, plantations, protective forests) are shown.

Year burned growing stock

m 3 CO 2 released Gg

stands coppice plantations protective total stands coppice plantations protective total

1990 3,605,243 5,008,295 558,556 1,312,728 10,484,822 4,486 7,264 588 1,985 14,106

1991 769,375 1,054,229 199,019 351,979 2,374,602 959 1,526 207 532 3,191

1992 1,190,733 1,879,681 265,177 604,804 3,940,395 1,487 2,717 273 913 5,290

1993 3,278,021 3,655,253 1,374,661 1,540,808 9,848,743 4,094 5,275 1,400 2,325 13,203

1994 1,256,586 913,725 892,145 723,258 3,785,713 1,572 1,317 901 1,091 5,070

1995 592,225 1,125,952 64,213 229,956 2,012,346 742 1,620 65 347 2,694

1996 607,844 574,687 86,259 196,597 1,465,386 763 826 86 296 1,961

1997 1,844,170 2,710,183 241,607 641,728 5,437,688 2,318 3,891 241 967 7,274

1998 2,268,656 1,823,976 659,442 945,449 5,697,523 2,855 2,616 657 1,424 7,620

1999 906,408 1,281,072 410,996 414,620 3,013,095 1,142 1,835 409 624 4,030

2000 2,298,337 2,207,523 618,394 910,445 6,034,700 2,899 3,160 613 1,370 8,068

2001 1,331,146 1,500,629 376,182 566,232 3,774,190 1,681 2,146 373 852 5,045

2002 616,383 1,043,236 69,219 351,051 2,079,889 779 1,490 69 528 2,780

2003 1,497,546 2,026,409 523,450 699,212 4,746,616 1,896 2,893 518 1,051 6,344

2004 532,580 771,111 62,493 331,883 1,698,067 675 1,100 62 499 2,270

2005 535,665 913,009 36,918 320,715 1,806,308 680 1,301 37 482 2,414

2006 453,576 752,789 46,616 274,666 1,527,647 577 1,072 46 413 2,042

2007 4,718,965 4,421,439 1,197,777 1,695,183 12,033,364 5,998 6,290 1,187 2,545 16,081

Table 7.5 Burned growing stocks and CO 2 released for the years 1990

- 2007

### 160

Once estimated the growing stock, the amount of aboveground tree biomass (dry mat ter), belowground biomass (dry matter) and dead mass (dry matter), from 1990 to 2007, can be

assessed. In the following, the default value of carbon fraction of dry matter (0.5 t d.m.) has been applied to obtain carbon amount from biomass. With regard to t he aboveground biomass:

1. starting from the 1985 growing stock data, reported in the IFN, the amount of aboveground woody tree biomass (d.m) [t] was calculated, for every forest typology, through the relation:

A WBD BEF GS

⋅ ⋅ ⋅ = (d.m.) biomass tree d Abovegroun



### where: GS = volume of g

rowing stock (MATT/ISAFA, 1988) [m 3 

### ha

1 

### ]

BEF = Biomass Expansion Factors which expands growing stock volume to volume of aboveground woody biomass ( ISAFA, 2004) WBD = Wood Basic Density for conversions from fresh volume to dry weight (d.m) [t

m - 3 

### ] (Giorda no, 1980)

A = forest area occupied by specific typology [ ha ] (MATT/ISAFA, 1988)

The BEF were derived for each forest typology and wood basic density (WBD) values were different for the main tree species:

2. starting from 1985, for each year, current incremen t per hectare [m

3 

### ha

1 

### y

- 1 

### ] is computed with the derivative Richards function, for every specific forest typology by the Italian yield tables collection;

3. starting from 1986, for each year growing stock per hectare [m 3 

### ha

- 1 

### ] is computed, from the previous y

ear growing stock volume, adding the calculated increment (“y” value of the derivative Richards) for the current year and subtracting losses due to harvest, mortality and fire for the current year, as described above.

Re

- applying the relation:

A WBD BEF GS

⋅ ⋅ ⋅ = biomass tree d Abovegroun



### it is possible to obtain the aboveground woody tree biomass (d.m) [t] for each forest typology, for each year, starting from the 1986.

In Table 7.6 biomass expansion factors for the conversions of volume to aboveground tree

biomass and wood basic densities are reported.

### 161 BEF WBD Inventory typology aboveground biomass / growing stock Dry weigth t/ fresh volume

norway spruce 1.29 0.38

silver fir 1.34 0.38

larches 1.22 0.56

mountain pines 1.33 0.47

mediterranean pines 1.53 0 .53

other conifers 1.37 0.43

european beech 1.36 0.61

turkey oak 1.45 0.69

other oaks 1.42 0.67

other broadleaves 1.47 0.53stands

partial total 1.35 0.51

european beech 1.36 0.61

sweet chestnut 1.33 0.49

hornbeams 1.28 0.66

other oaks 1.39 0.65

turkey oak 1.23 0.69

evergreen oaks 1.45 0.72

other broadleaves 1.53 0.53

conifers 1.38 0.43coppices

partial total 1.39 0.56

eucalyptuses coppices 1.33 0.54

other broadleaves coppices 1.45 0.53

poplars stands 1.24 0.29

other broadleaves stands 1.53 0.53

conifers stands 1.41 0.43

others 1.46 0.48plantations

partial total 1.36 0.40

rupicolous forest 1.44 0.52

riparian forest 1.39 0.41

shrublands 1.49 0.63protective

partial total 1.46 0.56

Total 1.38 0.53

Table 7.6 Biomas s Expansion Factors and Wood Basic Densities



### Belowground biomass was estimated applying a Root/Shoot ratio 

### to the aboveground biomass



### . The belowground biomass is computed, as:

A R WBD GS

⋅

⋅ ⋅ = (d.m.) biomass d Belowgroun



### where: GS = volume of g

rowing stock [m

3 

### ha

- 1 

### ]

R = Roo t/Shoot ratio which converts growing stock biomass in belowground biomass WBD = Wood Basic Density [t d.m. m

- 3 

### ] A = forest area occupied by specific typology [ha] Also in this case, the BEFs and WBDs were derived for each forest typology:

### 162 R WBD Inventory typo logy Root/shoot ratio Dry weigth t/ fresh

volume

norway spruce 0.29 0.38

silver fir 0.28 0.38

Larches 0.29 0.56

mountain pines 0.36 0.47

mediterranean pines 0.33 0.53

other conifers 0.29 0.43

european beech 0.20 0.61

turkey o ak 0.24 0.69

other oaks 0.20 0.67

other broadleaves 0.24 0.53stands

partial total 0.28 0.50

european beech 0.20 0.61

sweet chestnut 0.28 0.49

Hornbeams 0.26 0.66

other oaks 0.20 0.65

turkey oak 0.24 0.69

evergreen oaks 1.00 0.72

other broadleaves 0.24 0.53

Conifers 0.29 0.43coppices

partial total 0.27 0.57

eucalyptuses coppices 0.43 0.54

other broadleaves coppices 0.24 0.53

poplars stands 0.21 0.29

other broadleaves stands 0.24 0.53

conifers stands 0.29 0.43

Others 0 .28 0.48plantations

partial total 0.25 0.40

rupicolous forest 0.42 0.52

riparian forest 0.23 0.41

Shrublands 0.62 0.63protective

partial total 0.50 0.58

Total 0.30 0.54

Table 7.7 Root/Shoot ratio and Wood Basic Densities



### The net carbon stock change of l iving biomass has been calculated according to the GPG for LULUCF (IPCC, 2003), from the aboveground tree biomass and belowground biomass:

biomass d Belowgroun biomass d Abovegroun biomass Living 

## C

C C Δ + Δ = Δ

where the total amount of carbon has been obtained from the biomass (d.m.), multiplying by the conversion factor carbon content / dry matter.

The deadwood mass was assessed applying a dead mass conversion factor (DCF 10 

### ) of respectively 0.2 for evergreen forests and 0.14 for deciduous forests, as reported in table 3.2.2 of
GPG (IPCC 2003).

The d ead mass [t] is:

A DCF WBD BEF

⋅

⋅ ⋅ ⋅ = GS (d.m.) mass Dead



### where:

### 163

GS = volume of g

rowing stock [m

3 

### ha

- 1 

### ]

BEF = Biomass Expansion Factors for the conversions of volume to aboveground woody tree

biomass WBD = Wood Basic Density [t d.m. m

- 3 

### ]

DCF = Dead mass Conversion Factor w hich converts aboveground woody biomass in dead

mass A = forest area occupied by specific typology [ ha ]

The total litter carbon amount is estimated from the aboveground carbon amount with linear
relations, deduced from the results of the European project CANIF 22 

### ( CArbon and NItrogen cycling in Forest ecosystems) which has reported such relations for a number of European forest

stands. The total litter carbon amount has been estimated from aboveground carbon amount with

linear relations differentiated per fo restry use: stands (resinous, broadleaves, mixed stands) and coppices. The relationship is based on the widely reported findings that litter production increase linearly with NPP (Waring and Runnings, 1998). In our calculation, applying such relationship a t stand level, the annual rate of accumulation of litter C is 0.0723 t C ha

- 1 

### yr - 1 

### which

is in accordance with the default value reported in GPG LULUCF based on 20 years time period
(1.4 t C ha

- 1 

### yr - 1



### , T 3.2.1 ). In Table 7.8 the different relations used to obtain litter carbon amount per ha [t C ha

- 1 

### ] from the aboveground carbon amount per ha [t C ha

- 1 

### ] have been reported:

Table 7.8 Relations litter

- aboveground carbon per ha

22 CANIF project: http://www.bgc

- jena.mpg.de/bgc

- pro cesses/research/Schulze_Euro_CANIF.html Inventory typology Relation litter

– aboveground C per

ha

norway spruce 5045106590

. . +

⋅ = x y

silver fir 5045106590

. . +

⋅ = x y

larches 5045106590

. . +

⋅ = x y

mountain pines 5045106590

. . +

⋅ = x y

mediterranean pines 5045106590

. . +

⋅ = x y

other conifers 5045106590

. . +

⋅ = x y

european beech 3665902990

. . +

⋅ −= x y

turkey oak 3665902990

. . +

⋅ −= x y

other o aks 3665902990

. . +

⋅ −= x ystands

other broadleaves 3665902990

. . +

⋅ −= x y

european beech 3665902990

. . +

⋅ −= x y

sweet chestnut 3665902990

. . +

⋅ −= x y

hornbeams 3665902990

. . +

⋅ −= x y

other oaks 3665902990

. . +

⋅ −= x y

turkey oak 3665902990

. . +

⋅ −= x y

evergreen oaks 3665902990

. . +

⋅ −= x y

other broadleaves 3665902990

. . +

⋅ −= x ycoppices

conifers 5045106590

. . +

⋅ = x y

eucalyptuses coppices 3665902990

. . +

⋅ −= x y

other broadleaves
coppices 3665902990

. . +

⋅ −= x y

poplar s stands 3665902990

. . +

⋅ −= x y

other broadleaves stands 3665902990

. . +

⋅ −= x y

conifers stands 5045106590

. . +

⋅ = x yplantations

others 3285701650

. . +

⋅ −= x y

rupicolous forest 3285701650

. . +

⋅ −= x y

riparian forest 3665902990

. . +

⋅ −= x yprotective

shrublands 3665902990

. . +

⋅ −= x y

### 164

The dead organic matter carbon pool is defined, in the GPG, as the sum of the dead wood and

the litter.

litter mass dead Matter Organic Dead 

## C

C C Δ + Δ = Δ

The total amount of carbon for d ead organic matter has been obtained from the dead organic matter (d.m.), multiplying by the conversion factor carbon content / dry matter.

The total soil carbon amount is estimated from the aboveground carbon amount, with linear
relations, deduced from national CONECOFOR Programme data (Corpo Forestale, 2005; Cutini, 2002), per forestry use

–stands (resinous, broadleaves, mixed stands) and coppices. In Table 7.9 the different relations used to obtain soil carbon amount per ha [t C ha

- 1 

### ] from the abovegr ound carbon amount per ha [t C ha

- 1 

### ] have been reported:

Table 7.9 Relations soil

- aboveground carbon per ha



### Land converted in Forest Land The area of land converted to forest land is always coming from grassland. There is no occurrence for other conversion. Carbon stocks change due to grassland conver ting to forest land has been estimated and reported.

Inventory typology Relation soil

– aboveground C per ha

norway spruce 874 57 4041 0

. . +

⋅ = x y

silver fir 874 57 4041 0

. . +

⋅ = x y

larches 874 57 4041 0

. . +

⋅ = x y

mountain pines 874 57 4041 0

. . +

⋅ = x y

mediterranean pines 874 57 4041 0

. . +

⋅ = x y

other conifers 874 57 4041 0

. . +

⋅ = x y

european beech 0746598430

. . +

⋅ = xy
turkey oak 0746598430

. . +

⋅ = xy

other oaks 0746598430

. . +

⋅ = xystands

other broadleaves 0746598430

. . +

⋅ = xy
european beech 356 65 3922 0

. . +

⋅ = x y

sweet chestnut 356 65 3922 0

. . +

⋅ = x y

hornbeams 356 65 3922 0

. . +

⋅ = x y

other oaks 356 65 3922 0

. . +

⋅ = x y

turkey oak 356 65 3922 0

. . +

⋅ = x y
evergreen oaks 356 65 3922 0

. . +

⋅ = x y

other broadleaves 356 65 3922 0

. . +

⋅ = x ycoppices

conifers 8745740410

. . +

⋅ = x y
eucalyptuses coppices 356 65 3922 0

. . +

⋅ = x y

other broadleaves
coppices 356 65 3922 0

. . +

⋅ = x y

poplars stands 0746598430

. . +

⋅ = xy

other broadleaves stands 0746598430

. . +

⋅ = xy

conifers stands 8745740410

. . +

⋅ = x yplantations

others 6383376470

. . +

⋅ = x y
rupicolous forest 6383376470

. . +

⋅ = x y

riparian forest 0746598430

. . +

⋅ = xyprotective

shrublands 356

65 3922 0

. . +

⋅ = x y

### 165

The carbon stock change of living biomass has been calculated taking into account the increase

and the decrease of carbon stock related to the areas in transition to forest land. Net carbon stock change in dead organic matter and soil has been calculated as well. SOC reference value for grassland has been currently revised and set to 70. 8 tC ha

- 1 

### , after a review of the latest papers reporting data on soil carbon in mountain meadows, pastures, set

- aside la nds as well as soil not disturbed since the agricultural abandonment, in Italy (Viaroli and Gardi 2004, CRPA 2009,
IPLA 2007, ERSAF 2008, Del Gardo et al 2003, LaMantia et al

2007, Benedetti et al

2004, Masciandaro and Ceccanti 1999, Xiloyannis 2007).

The total amount of carbon for dead organic matter has been obtained from the dead organic matter (d.m.), multiplying by the conversion factor carbon content / dry matter.

In Table 7.10 carbon stock changes due to conversion to forest land, for the living bi omass, dead organic matter and soil pools, have been reported:

### 166 Carbon stock change in living biomass

Increase Decrease Net change Net C stock change in dead
organic matter Net C stock

change in

mineral soils

year Gg C

1990 239.73

- 179.92 59.80 12 .69 201.10

1991 240.44

- 142.13 98.30 17.06 225.27

1992 240.96

- 150.97 90.00 16.22 245.73

1993 241.42

- 178.07 63.35 14.13 251.38

1994 241.59

- 150.36 91.23 16.53 271.01

1995 241.71

- 143.01 98.70 16.88 295.55

1996 241.96

- 139.36 102.60 17.61 320.72

1997 241.95

- 154.12 87.83 15.86 339.02

1998 241.78

- 158.14 83.64 15.37 354.03

1999 241.84

- 147.17 94.67 16.92 375.27

2000 241.96

- 158.34 83.62 15.79 390.01

2001 241.90

- 145.57 96.33 17.01 411.50

2002 241.80

- 136.16 105.64 17.94 437.55

2003 241.77

- 154.2 1 87.56 16.00 455.31

2004 241.73

- 145.60 96.13 16.90 477.60

2005 241.63

- 142.22 99.41 17.06 501.43

2006 241.51

- 140.74 100.77 17.27 525.44

2007 244.02

- 187.73 56.29 12.93 531.85

Table 7.10 Carbon stock changes in land converting to forest land



### CO 2 

### e missions due to wildfires in forest land remaini ng forest land are included in T able 5.A.1, carbon stocks change in living biomass, decrease. Values of burned growing stocks and respective CO 2 

### released, for different categories (stands, coppices, plantatio ns, protective forests) , are reported in the previous T able 7.5.

7.2.3 Uncertainty and time

- series consistency

Estimates of removals by forest land are based on application of the above

- described model. To assess the overall uncertainty related to the ye ar 1990

– 2007, the Tier 1 Approach has been followed. The uncertainty linked to the year 1985 has been computed (the first National Forest Inventory was carried out in 1985) with the relation:

1985 1985 1985 1985 1985 2

1985 1985 2

1985 1985 2

1985 1985 2

1985 1985 2

1985 1985

1985

S V L V D V BG V AB V S V S E L V L E D V D E BG V BG E AG V AG E

E

+++ +    
   

⋅ +    
   

⋅ +    
   

⋅ +    
   

⋅ +    
   

⋅

=



### where the terms

1985 AG 

### V

, 1985

BG 

### V

, 1985

D 

### V

, 1985

L 

### V e

1985

S 

### V stand for the 1985 carbon stocks of the

five pools, aboveground, belowground, dead mass, litter and soil, while, with the letter E, the

related uncert ai nties have been indicated. In T able 7.11 the relations for assessing the overall uncertainties associated to the carbon pools have been reported:

### 167

Table 7.11 Relations for assessing uncertainties of the C pools



### where the term NFI

E stands for the uncertainty as sociated to the growing stock data given by

the first National Forest Inventory,

1 

### BEF E 

### points to uncertainty related to biomass expansion

factors for the aboveground biomass, 

### BD E is the basic density uncertainty and th e term CF E



### indicates the conversion factor uncertainty, where GPG default values have been used (IPCC, 2003). In the relation for the belowground carbon pool, the term

2 

### BEF E 

### stands for the

uncertainty related to the ex pansion factor used in the assessing of belowground biomass from growing stock data; GPG default value have been used (IPCC, 2003). Concerning the dead mass
relation, DEF

E 

### is the uncertainty of dead mass expansion factor, from the GPG (I PCC, 2003),

while

1985 

### LS E 

### and

1985



### SS E 

### are the uncertainties related to the litter and soil carbon stock data

deduced from the CANIF Project 23 

### data and the CONECOFOR Programme (Corpo Forestale, 2005) respectively. Finally the terms

1985 

### LR E 

### and

1985



### SR E 

### are defined as the uncertainties

related to linear regressions used to assessing the litter and soil carbon stocks. In Table 7.12, the values of carbon stocks in the five pools, for the 1985, and th e abovementioned uncertainties are reported:

23 CANIF project: http://medias.obs

- mip.fr/ricamare/interface/projet/canif.html Carbon pool Relation for uncertainty assessing

Aboveground 2222

1985 1 CF E BD E BEF E NFI E AG E +++

=

Belowground 2222

1985 2 CF E BD E BEF E NFI E BG E +++

=

Dead mass 2

1985 2

1985 1985 DEF

E AG E D E + =

Litter 2

5 2

1985 1985 LR

E LS E L E + =

Soil 2

5 2

1985 1985 SR

E SS E S E + =

### 168 Aboveground biomass V AG 137.8

Belowground biomass V BG 31.5

Dead mass V D 20.8

Litter V L 27.4Carbon stockst CO2eq. ha-1

Soil V S 264.7

Growing stock E NFI 3.2%

Current increment (Richards) 24 E NFI 51.6%

Harvest

25 E H 30%

Fire 26 E F 30%

Drain and grazing E D 30%

Mortality E M 30%

BEF E BEF1 30%

R E BEF2 30%

DCF E DEF 30%

Lit ter (stock + regression) E L 161%

Soil (stock + regression) E S 152%

Basic Density E BD 30%Uncertainty

C Conversion Factor E CF 2%

Table 7.12 Carbon stocks and uncertainties for year 1985 and current increment related uncertainty



### The uncertainties related to the carbon pools and the overall uncertainty for 1985 has been computed and shown in Table 7.13, using the relations in Table 7.11.

Aboveground biomass 

### E AG 

### 42.59%

Belowground biomass 

### E BG 

### 42.59%

Dead mass 

### E D 

### 52.10%

Litter 

### E L 

### 161.22%

Soil 

### E S 

### 152.05%

Overall uncertainty 

### E 1985 

### 84.91%

Table 7.13 Uncertainties for the year 1985



### The overall uncertainty related to 1985 (the year of the first National Forest Inventory) has been propagated through the years, till 2007, following Tier 1 approach. The equations for the year s following 1985 are similar to the one for the 1985 uncertainty estimate, with the exception of the terms linked to aboveground biomass: the biomass increment was estimated with the methodology described in paragraph 7.2.2; therefore, the related uncertainty, e.g. for 1986, is expressed by the following formula :

24 The current increment is estimated by the Richards function (first derivative); uncertainty has been assessed
considering the standard error of the linear regression between the estimated values and the corresponding current increment values reported in the National Forest Inventory

25 Good Practice Guidance default value (IPCC, 2003)

26 Good Practice Guidance default value (IPCC, 2003)

### 169 

# ( ) ( ) ( ) ( ) ( ) ( )



# ( ) ( ) 

# ( ) ( ) 222 2 2 2 2 2 2 2

1986 CF E BD E BEF E

V D VV H V I V NFI V VEVEVE

H V H E I V I E NFI V NFI E

AG E

MOR F MM DD FF
+++    

 

   

 

−+−+−+−++ ⋅ +

⋅ +

⋅ +

⋅ +

⋅ +

⋅

=



### The uncertainties related to the carbon pools and the overall uncertainty f or 1986 are shown in

Table 7.14:

Aboveground biomass 

### E AG 

### 42.67%

Belowground biomass 

### E BG 

### 42.67%

Dead mass 

### E D 

### 52.16%

Litter 

### E L 

### 161.22%

Soil 

### E S 

### 152.05%

Overall uncertainty 

### E 1986 

### 84.75%

Table 7.14 Unce rtainties for the year 1986



### Following the Tier 1 approach and the abovementioned methodology, the overall uncertainty in the estimates produced by the described model has been quantified; in Table 7.15 the

uncertainties of the 1985

- 2007 period are reporte d.

1985 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

%

84.9 88.0 87.3 86.55 86.39 86.17 86 85.88 85.7 85.5 81.4

Table 7.15 Overall uncertainties 1985

- 2007



### The overall uncertainty in the model estimates between 1990 and 2007 has been assessed wi th the following relation: 

# ( ) ( )

2006 1990 2

2006 2005 2
1990 1990

20061990 VV VE VE

E

+ ⋅ +

⋅

=

−



### where the terms V stands for the growing stock [ m 3 

### ha

- 1 

### CO

2 

### eq ] while the uncertainties have been indicated with the letter E. The overall uncertainty related to the year 1990

– 2007 is equal

to 61.35%. Th

e table reporting the uncertainties referring to all the categories (Forest Land, Cropland, Grassland, Wetlands, Settlements, Other Land) is shown in Annex 1. A comparison between carbon in the aboveground biomass pool, estimated with the described

methodo logy, and the new INFC data about 2006 aboveground carbon stock of the whole Italian

forest results in 0.26 % difference (Table 7.16).

INFC aboveground carbon stock Estimated aboveground carbon stock

t C t C

486,018,500 484,753,744

Table 7.16 Comparison between estimated and INFC preliminary 2006 aboveground carbon stock

### 170

7.2.4 Source

- specific QA/QC and verification

Systematic quality control activities have been carried out in order to ensure completeness and consistency in time series and correctness in the sum of sub

- categories; where possible, activity data comparison among different sources (FAO database 27 

### , ISTAT data 28 

### ) ha s been made. Data entries have been checked several times during the compilation of the inventory; particular

attention has been f

ocussed on the categories showing significant changes between two years in succession. Land use matrices have been accurately checked and cross

- checked to ensure that data were properly reported. Regarding both soil and litter, a validation of the applied methodology has been done in Piemonte region, comparing results of a regional soil inventory with data obtained with the abovementioned methodology. Results show a good agreement between the two dataset either in litter and soil. An interregional project, named INEMAR 29



### , developed to carry out atmospheric emission inventories at local scale, has added a module to estimate forest land emission and removals, following the abovementioned methodology. The module will be applied, at local scale with local data, i n seven of the 20 I talian region s and the

results will constitute a good validation of the used methodology.

Further identification of critical issues and uncertainties in the estimations derived from the participation at workshops and pilot projects (MATT , 2002). Specifically, the European pilot project to harmonise the estimation and reporting of EU member states, in 2003, led to a comparison among national approaches and problems related to the estimation methodology
and basic data needed (JRC, 2004). Th e estimate methodology has been presented and discussed during several national workshops; findings and comments collected have been used in the refining estimation process.

7.2.5 Source

- specific recalculations

Recalculations of emissions and removals have been carried out on the basis of the IPCC Good Practice Guidance for LULUCF (IPCC, 2003 ). Moderate deviations from the precedent sectoral estimates occurred, essentially because of the release of official INFC forest surfaces, resulting in an average decrease of 6.6% in living biomass, 14.7% in dead organic matter and 15.3% in soils carbon pools estimates , and of 11.3 % in total forest land category, as shown in the F igure 7.4. As well as soils carbon pools estimates, the different SOC reference level u sed for grassland in conversion to forestland results in a significant decrease in reported carbon stock change for land converting to forest land; this resulted in a reassessment of carbon stock change in forestland remaing forestland.

27 F AO, 2005. FAOSTAT, http://faostat.fao.org

28 ISTAT, several years [a], [b], [c]

29 INEMAR: INventario EMissioni Aria : http://www.ambiente.regione.lombardia.it/inemar/e_inemarhome.htm

### 171 -20.0 -17.5 -15.0 -12.5 -10.0 -7.5 -5.0 -2.5 0.0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

%

living biomass -net change

dead organic matter

soils

forest land

Figure 7.4 Dif

ference between current and 2007 submission carbon pools estimates



### 7.2.6 Source

- specific planned improvements

The final result of the INFC has allowed a more precise evaluation of the estimated time series
of the forest areas; the INFC data related to th e soils survey will definitely constitute a robust database, allowing refined estimates and lower related uncertainty. The ‘National Registry for Carbon sinks’, instituted by a Ministerial Decree on 1 st 

### April 2008, is part of the Italian National System a

nd includes information on units of lands subject of activities under Article

3.3 and activities elected under Article 3.4 and related carbon stock changes. The National Registry for Carbon sinks is the instrument to estimate, in accordance with the COP/MO P decisions, the IPCC Good Practice Guidance on LULUCF and every relevant IPCC guidelines, the greenhouse gases emissions by sources and removals by sinks in forest land and related

land

- use changes and to account for the net removals in order to allow the Italian Registry to

issue the relevant amount of RMUs. Activities planned in the framework of the National Registry for Forest Carbon Sinks should also provide data to improve estimate of carbon sequestration due to Afforestation/reforestation activities (with a special focus on soil organic content), and should allow to refine the estimate of forest land category. Specifically, for the LULUCF sector, following the election of the 3.3 and 3.4 activities and on account of an in

depth analysis on the informa tion needed to report LULUCF under the Kyoto Protocol, a
Scientific Committee, Comitato di Consultazione Scientifica del Registro dei Serbatoi di

Carbonio Forestali, constituted by the relevant national experts has been established by the Ministry for the Environment, Land and Sea in cooperation with the Ministry of Agriculture,

Food and Forest Policies. An expert panel on forest fires has been set up, in order to obtain geographically referenced data on burned area; the overlapping of land use map and geo referenced data should assure the

estimates of burned areas in the different land uses. The fraction of CO 2 

### emissions due to forest fires, now included in the estimate of the forest land remaining forest land, will be pointed out. In addition to these exp ert panels, ISPRA participate s in technical working groups, denominated Circoli di qualità , within the National Statistical System (Sistan). Concerning LULUCF sector, this group, coordinated by the National Institute of Statistics, is constituted by both p roducers and users of statistical information with the aim of improving and monitoring statistical information for forest sector. These activities should improve the quality and details of basic data, as well as enable a more organized and timely communica tion.

### 172

In the next submissions an upgrade of the used model is foreseen to achieve the above cited improvements and to obtain more accurate estimates of the carbon stored in the dead wood, litter and soil pools, using the outcomes of research projects on ca rbon stocks inventories, with a special focus on the Italian territory.

7.3 Cropland (5B)

7.3.1 Source category description

Under this category, CO 2 

### emissions from living biomass, dead organic matter and soils, from cropland remaining cropland and from land converted in cropland have been reported. Cropland removals share 12.4% of total CO 2 

### LULUCF emissions and removals, in particular the living biomass removals represent 97%, while the emissions from soils stand for 3% of total cropland CO 2 

### emissions a nd removals. Removals are almost entirely due to cropland remaining cropland, while only land converting to cropland category is responsible for emissions.

CO 2 

### emissions and removals from cropland remaining cropland have been identified as key category in level and in trend assessment (Tier 1). Concerning N 2 

### O emissions, the category land converting to cropland has not resulted as a key source.

7.3.2 Methodological issues

Cropland remaining Cropland Cropland includes all annual and perennial crops; the ch ange in biomass has been estimated only for perennial woody crops, since, for annual crops, increase in biomass stocks in a single year is assumed equal to biomass losses from harvest and mortality in that same year. Activity data for cropland remaining cr opland have been subdivided into annual and perennial woody

crops. The estimates of carbon stocks changes are applied to aboveground biomass only, according to the GPG (IPCC, 2003), as there is not sufficient information to estimate carbon stocks change i n dead organic matter pools. To assess change in carbon in cropland biomass, the Tier 1 based on highly aggregated area estimates for generic perennial woody crops, has been used; therefore

default factors of aboveground biomass carbon stock at harvest, ha rvest/maturity cycle, biomass
accumulation rate, biomass carbon loss, for the temperate climatic region have been applied, even though they are not very representative of the Mediterranean area, where the most common woody crops are c rops like olive groves or vineyards that have, for instance, different harvest/maturity cycles. Furthermore these crops are unlikely totally removed after an amount of time equal to a nominal harvest/maturity cycle (30 years for temperate climate region), as implied by the bas ic assumption of Tier 1, since the croplands are abandoned or consociated with annual crops. The biomass clearing is relatively unusual. Bio mass carbon losses have been estimated, taking into account the pruning of woody cropland, using the same country

- sp ecific methodology developed for estimating emissions from field burning of agriculture residues (§ 6.6.2). Net changes in cropland C stocks obtained are equal to 4.693 Tg C for 1990, and 3.079 Tg C for

2007 , as well as concerns living biomass pool.

Accord ing to the LULUCF GPG (IPCC, 2003), the change in soil C stocks (Equation 3.3.4) is the result of a change in practices or management between the two time periods and concentration of soil carbon is only driven by the change in practice or management. It w asn’t possible to point out different sets of relative stock change factors [F LU 

### (land use), F MG 

### (management), F

I 

### (input factor)] for the period 1990

- 2007 under investigation; therefore, as no management changes can be documented, resulting change in carbo n stock has been reported as

zero.

### 173

No CO 2 

### emissions from organic soils or from application of carbonate containing lime or dolomite to agricultural soils have occurred.

Land converted to Cropland In accordance with the GPG methodology, estimates of carbo n stock change in living biomass have been provided, since there is not sufficient information to estimate carbon stock change in dead organic matter pool. Concerning soil carbon pool, changes in carbon stocks associated with the transitions have been repo rted as a whole in a single year (i.e. the year of conversion): dynamics of soil carbon storage and release are complex and still not well understood, even if current approaches assume that after a cultivation of a forest or grassland, there is an initial carbon loss over the first years which rapidly reduces to a lower subsequent loss rate in the following years (Davidson and Ackerman 1993). On this basis and by considering the spatial resolution of data we used, we conclude that a reasonable approach, in calculating the effect of transition to cropland, could be assuming that the changes in carbon stocks carbon occur in the first year after the land conversion, in spite of considering them over the time period (20 years as default) specified by IPCC GPG LU LUCF (2003).

CO 2 

### emissions from cultivated organic soils (CRPA, 1997) in cropland remaining cropland have been estimated, using default emission factor for warm temperate, reported in Table 3.3.5 of GPG (IPCC, 2003).

N 2 

### O emissions arising from the convers ion of land to cropland have been also estimated, and reported in Table 5(III)

- N 2 

### O emissions from disturbance associated with land

- use conversion to cropland. The carbon stocks change, for land converted to cropland, is equal to the carbon stocks change due to the removal of biomass from the initial land use plus the carbon stocks from one year of growth in cropland following the conversion. The Tier 1 has been followed, assuming that the amount of biomass is cleared and some type of cropland system is pl

anted soon thereafter. At Tier 1, carbon stocks in biomass immediately

after the conversion are assumed to be zero. The average area of land undergoing a transition from non cropland, only grassland in Italian case, to cropland, during each year, from 1990 to 2007, has been estimated through the construction of the land use change matrices, one for each year; the matrices allow to point out the average areas of transition land separately for each initial and final land use (i.e. forest land, grassland, etc. ). The GPG equation 3.3.8 (IPCC, 2003) has been used to estimate the change in carbon stocks resulting from the land use change. The carbon stocks change per area for land converted to cropland is assumed, following the Tier1, equal to loss in carbon stock s in biomass immediately before conversion to cropland. For the Italian territory, only conversion from grassland to cropland has occurred; therefore the default estimates for standing biomass grassland, as dry matter, reported in Table 3.4.2 of GPG
(IPCC , 2003) for warm temperate

–dry have been used, equal to 1.6 t d.m. ha

- 1 

### . Changes in carbon stocks from one year of cropland growth have been obtained by the default biomass carbon stocks reported in Table 3.3.8, for temperate region. In accordance to nat ional expert judgement, it has been assumed that t he final crop type, for the areas of transition land, is annual cropland. As pointed out in the land use matrices reported above, in Table 7.3, conversion of lands into cropland has taken place only in a f ew years during the period 1990

- 2007. C emissions [Gg C] due to change in carbon stocks in living biomass in land converted to cropland, are reported in

Table 7.17:

Conversion Area D C converted land

year kha Gg C

1990 0 0

1991 0 0

1992 0 0

### 174

1993 17 21.9

1994 43 55.5

1995 34 44.5

1996 0 0

1997 9 11.2

1998 68 88.7

1999 97 125.9

2000 0 0

2001 0 0

2002 0 0

2003 0 0

2004 0 0

2005 0 0

2006 52 67.7

2007 0 0

Table 7.17 Change in carbon stock in living biomass in land converted to cropland



### Cha nges in carbon stocks in mineral soils in land converted to cropland have been estimated following land use changes, resulting in a change of the total soil carbon content. Initial land use
soil carbon stock [SOC (0

- T) 

### ] and soil carbon stock in the inventor y year [SOC 0 

### ] for the cropland

area have been estimated from the reference carbon stocks. SOC reference value for cropland has been currently revised and set to 56

. 7 tC/ha on the basis

of new references . It replace s the previous value (44. 5 tC/ha) fixed f or cropland and grassland according to an expert judgement. The new value has been drawn up by analysing a collection of the latest papers reporting data on soil carbon under the most common agricultural practices in Italy, including woody cropland

cultiva tions such as vineyards and olive orchards (Triberti et al 2008, Ceccanti et al

2008,

Monaco et al

2008, Martiniell o 2007, Lugato and Berti 2008, Francaviglia 2006, IPLA 2007,
ERSAF 2008, Del Gardo et al 2003, Puglisi et al , 2008, Lagomarsino et al 2009, P erucci et al
2008). Whenever the soil carbon stock was not reported in the papers, it has been calculated at the default depth of 30 cm from the soil carbon content, the bulk density, and the stoniness according to the following formula (Batjes 1996):



# ( )

i ii K

i i d 

### S

D P T

−

⋅⋅⋅ = 

# ∑

= 

### 1

1 

### r



### where d 

### T is the overall soil carbon stock (gcm

- 2 

### ) and, for each K layer of the soil profile,
i 

### r is the

soil bulk density (gcm

- 3 

### ),
i 

### P is the soil carbon content (gCg

- 1 

### ),
i 

### D is the layer thickness (cm),

i 

### S is the volume of the gravel > 2mm.

If not available in the papers, soil bulk density has been calculated on the basis of the soil organic matter and texture (Adam 1973):



###        

− +         =

m 

### X X

rr r 100

100

0 

### where r soil bulk density (gcm

- 3 

### ), X , percent by weight of organic matter, r 0 

### average bulk
density of organic matter (0.224 gcm

- 3 

### ) and r m 

### bulk density of the mineral matter usually estimated at 1.33 gcm

- 3 

### or determined on the “mineral bulk density chart” (Rawls and
Brakensiek, 1985). Since soil carbon stocks are derived from experimental measurements under some representative cropland managements, the effect of the practices is intended to be included into the values and consequently no stock change factors (F LU 

### , F MG 

### , F I 

### ) have been applied on the soil

### 175

carbon stock. Each soil carbon stock was assigned to the geographical area where the relative soil carbon content has been measured and the overall values have been averaged by means of weights resulting from the pro portional relevance of the indag ated area (ha) over the entire

I talian territory. The annual change in carbon stocks in mineral soils has been, at last, assessed as described in the equation 3.3.3 of the GPG (IPCC, 2003), only for the years where conversio n has taken place. C emissions [Gg C] due to change in carbon stocks in soils in land converted to cropland

are reported in Table 7.18.

Conversion Area Carbon stock

year k ha Gg C

1990 0 0

1991 0 0

1992 0 0

1993 17

- 238.4

1994 43

- 602.6

1995 34

- 483.4

1996 0 0

1997 9

- 121.7

1998 68

- 963.4

1999 97

- 1,367.2

2000 0 0.0

2001 0 0

2002 0 0

2003 0 0

2004 0 0

2005 0 0

2006 52

- 735.3

2007 0 0

Table 7.18 Change in carbon stock in soil in land converted to cropland



### No CO 2 

### emissions from organ ic soils or from application of carbonate containing lime or dolomite to agricultural soils have occurred.

7.3.3 Source

- specific recalculations

In response to the 2005 submission review process and in agreement with the GPG LULUCF, starting from 2006 inv

entory submission, soil emissions from cropland remaining cropland previously calculated on the only basis of changes in area surfaces and not to changes in management practices have been deleted because not related to a real change in carbon content

in so ils . Notable d

eviations from the precedent sectoral estimates occurred, essentially due to estimates of carbon losses by pruning (in cropland remaining cropland) and to the revision of SOC reference value for cropland. This results in mean decrease of 90% in cropland category, in the period 1990

- 2006.

7.3.4 Source

- specific planned improvements

Additional researches will be made to collect more country

- specific data on woody crops. Improvements will concern the implementation of the estimate of carbon chan ge in cropland biomass at a higher disaggregate level, with the subdivision of the activity data in the main categories of woody cropland (orchards, citrus trees, vineyards, olive groves) and the

### 176

application of different biomass accumulation rates and harv est/maturity cycles for the various categories. Further investigation will be made to obtain ancillary information about the final crop types, concerning the areas in transition to cropland, in order to obtain a more precise estimate of the

carbon stocks change. Activities planned in the framework of the National Registry for Forest Carbon Sinks should also provide data to improve estimate of carbon sequestration due to Afforestation/reforestation activities (with a special focus on soil organic content), and should allow to refine the estimate of soil organic content in cropland category.

7.4 Grassland (5C)

7.4.1 Source category description

Under this category, CO 2 

### emissions, from living biomass, dead organic matter and soils, from grassland remaining grassland and from land converted in grassland have been reported. Grassland category is responsible for 7,760 Gg of CO 2 

### removals in 2007, with 1

, 243 Gg of CO 2 

### emissions due to living biomass pool and 9

, 003 Gg of CO 2 

### removals due the soils pool. In the

per iod 1990

- 2007 mean grassland emissions share 3.8% of absolute CO 2 

### LULUCF emissions and removals, in particular the living biomass emissions represent 12%, while the removals from soils stand for 88% of absolute total grassland CO 2 

### emissions and removals.

7.4.2 Methodological issues

Grassland remaining Grassland Forage crops, permanent pastures, and lands once used for agriculture purposes, but in fact set

aside since 1970 have been considered as grasslands. To assess change in carbon in grassland

biomas s, the Tier 1 has been used; therefore no change in carbon stocks in the living biomass pool has been assumed; in accordance to the GPG no data regarding the dead organic matter pool have been provided, since not enough information is available. According

to the LULUCF GPG (IPCC, 2003), the estimation method is based on changes in soil C stocks over a finite period following changes in management that impact soil C (Equation 3.4.8). Soil C concentration for grassland systems is driven by the change in prac tice or management, reflecting in different specific climate, soil and management combination, applied for the respective time points. It wasn’t possible to point out different sets of relative stock change factors [F LU 

### (land use), F MG 

### (management), F I 

### (in put factor)] for the period 1990

- 2007 under investigation; therefore, as no management changes can be documented, resulting change in carbon stock has been reported as zero.

No CO 2 

### emissions from organic soils or from application of carbonate containing li me have

occurred.

Land converted to Grassland In accordance with the GPG methodology, estimates of carbon stocks change in living biomass and soils have been provided, since there is not sufficient information to estimate carbon stocks change in dead org

anic matter pool. Only conversion from cropland to grassland has occurred.

The assessment of emissions and removals of carbon due to conversion of other land uses to grassland requires estimates of the carbon stocks prior to and following conversion and th e estimates of land converted during the period over which the conversion has an effect. In accordance with the GPG methodology, estimates of carbon stock change in living biomass has been provided, since there is not sufficient information to estimate ca rbon stock change in dead organic matter pool. Concerning soil carbon pool, changes in carbon stocks associated with

the transitions have been reported as a whole in a single year (i.e. the year of conversion), assuming, as for the other categories in tran sition, that the changes in carbon stocks carbon

### 177

occur in the first year after the land conversion, in spite of considering them over the time period (20 years as default) specified by IPCC GPG LULUCF (2003). As a result of conversion to grassland, it is a

ssumed that the dominant vegetation is removed entirely, after which some type of grass is planted or otherwise established; alternatively grassland can result from the abandonment of the preceding land use, and the area is taken over by grassland. The Tie r 1 has been followed, assuming that carbon stocks in biomass immediately after the conversion are equal to 0 t C ha

- 1



### . The annual area of land undergoing a transition from non grassland, only cropland in Italian case, to grassland during each year, from 1990 to 2007, has been pointed out, for each initial and final land use, through the use of the land use change matrices, one for each year. Changes in biomass carbon stocks have been accounted for in the year of conversion. The GPG equation 3.4.13 (IPCC, 2003) has been used to estimate the change in carbon stocks, resulting from the land use change. Concerning Italian territory, only conversion from cropland to grassland has occurred; therefore the default biomass carbon stocks present on land converted t o grassland, as dry matter, as supplied by Table 3.4.9 of the GPG for warm temperate

–dry, have been used, equal to 6.1 t d.m. ha

- 1 

### . Since, according to national expert judgement, it has been assumed that lands in conversion to grassland are mostly annual crops, carbon stocks in biomass immediately before conversion have been obtained by the default values reported in the Table 3.3.8 of the GPG, for annual cropland. As pointed out above in the land use matrices, see Table 7.3, the conversion of lands into grassland have taken place only in a few years during the period 1990

- 2007. C emissions [Gg C] due to change in carbon stocks in living biomass in land converted to grassland, are reported in

Table 7.19:

### 178 Conversion Area C before D C growth D C

year k ha t C ha - 1 t C ha - 1 Gg C

1990 9 5 3.05

- 16.8

1991 41 5 3.05

- 79.6

1992 42 5 3.05

- 82.5

1993 0 5 3.05 0

1994 0 5 3.05 0

1995 0 5 3.05 0

1996 64 5 3.05

- 125.4

1997 0 5 3.05 0

1998 0 5 3.05 0

1999 0 5 3.05 0

2000 9 5 3.05

- 16.9

2001 132 5 3.05

- 258. 3

2002 43 5 3.05

- 83.8

2003 990 5 3.05

- 1930.0

2004 117 5 3.05

- 228.3

2005 109 5 3.05

- 211.9

2006 0 5 3.05 0

2007 174 5 3.05

- 339.1

Table 7.19 Change in carbon stock in living biomass in land converted to grassland



### Changes in carbon stocks in mine ral soils in land converted to grassland have been estimated following land use changes, resulting in a change of the total soil carbon content. Initial land use
soil carbon stock [SOC (0

- T) 

### ] and soil carbon stock in the inventory year [SOC 0 

### ] for the grassl and

have been estimated from the reference carbon stocks. SOC reference value for grassland has been currently revised and set to 70. 8 tC/ha on the basis

of new references . It replace s the previous value (44. 5 tC/ha coming from an expert judgement

reporte d also for cropland) and make s the current estimate consistent with the SOC stocks reported for grassland in temperate regions, 60

- 150 tC/ha (Gardi 2007). The new value has been drawn up by analysing a collection of the latest papers reporting data on soil carbon in mountain meadows, pastures, set

- aside lands as well as soil not disturbed since the agricultural abandonment, in Italy (Viaroli and Gardi 2004, CRPA 2009, IPLA 2007, ERSAF 2008, Del

Gardo et al 2003, LaMantia et al 2007, Benedetti et al

2004, Ma sciandaro and Ceccanti 1999, Xiloyannis 2007). Whenever the soil carbon stock was not reported in the papers, it has been calculated at the default depth of 30 cm from the soil carbon content, the bulk density, and the stoniness according to the following formula (Batjes 1996):



# ( )

i ii K

i i d 

### S

D P T

−

⋅⋅⋅ = 

# ∑

= 

### 1

1 

### r



### where d 

### T is the overall soil carbon stock (gcm

- 2 

### ) and, for each K layer of the soil profile,
i 

### r is the

soil bulk density (gcm

- 3 

### ),
i 

### P is the soil car

bon content (gCg

- 1 

### ),
i 

### D is the layer thickness (cm),

i 

### S is the volume of the gravel > 2mm. If not available in the papers, soil bulk density has been

calculated on the basis of the soil organic matter and texture (A dam 1973):



###        

− +         =

m 

### X X

rr r 100

100

0

### 179

where r soil bulk density (gcm

- 3 

### ), X , percent by weight of organic matter, r 0 

### average bulk density of organic matter (0.224 gcm

- 3 

### ) and r m 

### bulk density of the mineral matter usually estimated at 1.33 gcm

- 3 

### or determined on the “mineral bulk density chart” (Rawls and Brakensiek, 1985). Since soil carbon stocks are derived from experimental measurements under some representative cropland managements, the effect of the practices is intended to be included into the values and consequently no stock change factors (F LU 

### , F MG 

### , F I 

### ) have been applied on the soil carbon stock. Each soil carbon stock was assigned to the geographical area where the relative soil carbon content has been measured and the overall values have been averaged by means of weights resulting from the pro portional relevance of the indagated area (ha) over the entire

I talian territory. With the stock change factors, the grassland soil carbon stock [t C] for the inventory year
[SOC 0 

### ] and the cropland land use soil carbon stock [SOC (0

- T) 

### ] have been estimated, starting
from the soil carbon stock for unit of area [t C ha

- 1 

### ]. The inventory time period has been established, as abovementioned, in 1 year. The annual change in carbon stocks in mineral soils has been, at last, assessed as described in the equation 3.3 .3 of the GPG, only for the years

where conversion has taken place. C emissions [Gg C] due to change in carbon stocks in soils in land converted to grassland, are reported in Table 7.20:

Conversion Area Carbon stock

year k ha Gg C

1990 9 121.9

1991 41 576.2

1992 42 597.6

1993 0 0

1994 0 0

1995 0 0

1996 64 908.3

1997 0 0

1998 0 0

1999 0 0

2000 9 122.4

2001 132 1,870.4

2002 43 607.0

2003 990 13,973.8

2004 117 1,653.0

2005 109 1,534.4

2006 0 0

2007 174 2,455.4

Table 7.20 Change in car bon stock in soil



### 7.4.3 Source

- specific recalculations

In response to the 2005 submission review process, as already reported in previous submissions and in agreement with the GPG LULUCF, emissions from grassland remaining grassland previously calculated on the only basis of changes in area surfaces and not to changes in management practices have been deleted, because not related to a real change in carbon content

in soils. Recalculations of emissions and removals have been carried out on the basis of

LUL UCF Good Practice Guidance (IPCC, 2003 ). Remarkable d eviations from the precedent sectoral estimates occurred, essentially due to the revision of SOC reference value for grassland. This results in mean increase of 26% in grassland category, in the period 1 990

- 2006.

### 180

7.4.4 Source

- specific planned improvements

Concerning land in transition to grassland, further investigation will be made to obtain additional information about different types of management activities on grassland, and the crop types of land c

onverting to grassland, to obtain a more accurate estimate of the carbon stocks change

. Activities planned in the framework of the National Registry for Forest Carbon Sinks should also provide data to improve estimate of carbon sequestration due to Affores tation/reforestation activities (with a special focus on soil organic content), and should allow to refine the estimate of soil organic content in grassland category.

7.5 Wetlands (5D)

7.5.1 Source category description

Under this category, activity dat a from wetlands remaining wetlands are reported.

7.5.2 Methodological issues

Lands covered or saturated by water, all or part of year, which harmonize with the definitions of

the Ramsar Convention on Wetlands 30 

### have been included in this category (MAMB, 1 992). No data were available on flooded lands, therefore reservoirs or water bodies regulated by human activities have not been considered. Concerning land converted to wetland, during the period

1990

- 2007, no land has been in transition to wetlands.

7.5. 3 Source

- specific planned improvements

Improvements will concern the acquirement of data about flooded lands and the implementation

of the GPG method to estimate CO 2 

### , CH 4 

### and N 2 

### O emissions from flooded lands.

7.6. Settlements (5E)

7.6.1 Source category description

Under this category, activity data from settlements and from land converted to settlements are reported; CO 2 

### emissions, from living biomass and soil, from land converted in settlements have been also reported. In the period 1990

- 2007 mean set tlements emissions share 3.1% of absolute

CO 2 

### LULUCF emissions and removals.

7.6.2 Methodological issues

Up to now there is a lack of data concerning urban tree formations. Therefore it is not possible to give estimates on the carbon stocks changes in l iving biomass, dead organic matter and soil for this category. Therefore only activity data have been reported. Settlements time series has been developed through a linear interpolation between the 1990 and 2000 data, obtained by the

Corine Land Cover 31 

### map s, relatively to the class “ Artificial surfaces ”. By assuming that the defined trend may well represent the near future, it was possible to extrapolate data for the years

2001

- 2007.

30 Ramsar Convention on Wetlands: http://www.ramsar.org/ (Ramsar, 2005)

31 Corine Land Cover, http://www.clc2000.sinanet.apat.it/ (APAT, 2004)

### 181

Land converted to Settlements The average area of land undergoing a tra nsition from non

- settlements to settlements during each year, from 1990 to 2007, has been estimated with the land use change matrices that have also permitted to specify the initial and final land use. The GPG equati on 3.6.1 approach (IPCC, 2003) has been used to estimate the change in carbon stocks, resulting from the land use change. The annual change in carbon stocks, for land converted to settlements, is assumed equal to carbon stocks in living biomass immediately following conversion to settlements min us the carbon stocks in living biomass in land immediately before conversion to settlements, multiplied for the area of land annually converted. The default assumption, for Tier 1, is that carbon stocks in living biomass following conversion are equal to z ero. As reported in the table 7.3, only conversions from grassland and cropland to settlements have

occurred in the 1990

- 2007 period. Concerning grassland converted to settlements, no change in carbon stocks has been computed, as in Tier 1 no change in ca rbon stocks in the grassland living biomass pool has been assumed. For what concerns cropland in transition to settlements, carbon stocks, for each year and for crops type (annual or perennial), have been estimated, using as

default coefficients the factor s shown in the following table 7.21:

Biomass carbon stock

t C ha - 1

Annual cropland 5

Perennial woody cropland 63

Table 7.21 Stock change factors for cropland



### As indicated in the land use matrices of Table 7.3, the conversion of lands into settlemen ts has taken place only in a few years during the period 1990

- 2007. In Table 7.22 C stocks [Gg C] related to change in carbon stocks in living biomass in cropland (annual and perennial) converted to settlements are reported:

### 182 annual crops to settlements perennial crops to settlements

Year Conversion Area Carbon stock Conversion Area Carbon stock Total Carbon stock

k ha Gg C k ha Gg C Gg C

1990 2.19

- 10.94 6.07

- 382.5

- 393.5

1991 2.17

- 10.87 6.09

- 383.4

- 394.3

1992 2.16

- 10.80 6.10

- 384.3

- 395.1

1993 0 0 0 0 0

1994 0 0 0 0 0

1995 0 0 0 0 0

1996 1.97

- 9.87 6.29

- 396.0

- 405.9

1997 0 0 0 0 0.0

1998 0 0 0 0 0

1999 0 0 0 0 0

2000 1.95

- 9.77 6.31

- 397.3

- 407.0

2001 1.98

- 9.89 6.28

- 395.7

- 405.6

2002 1.99

- 9.94 6.27

- 395.1

- 405.0

2003 2.16

- 10.8 2 6.09

- 384.0

- 394.8

2005 2.19

- 10.94 6.07

- 382.5

- 393.4

2005 2.22

- 11.09 6.04

- 380.6

- 391.7

2006 0 0 0 0 0

2007 2.23

- 13.37 6.03

- 386.0

- 399.4 Table 7.22 Change in carbon stocks in living biomass in cropland converted to settlements



### Change s in soil carbon stocks from land converting to settlements have been also estimated. In

Table 7.23 soil C stocks [Gg C] of cropland (annual and perennial) and grassland conver ted to settlements are reported.

annual crops to settlements perennial crops to settlem ents grassland to settlements

Year Conversion Area Carbon stock Conversion Area Carbon stock Conversion Area Carbon stock

k ha Gg C k ha Gg C k ha Gg C

1990 2.19

- 124.04 6.07

- 344.3 0 0

1991 2.17

- 123.25 6.09

- 345.0 0 0

1992 2.16

- 122.47 6.10

- 345.8 0 0

1993 0 0 0 0 8.26

- 584.91

1994 0 0 0 0 8.26

- 584.91

1995 0 0 0 0 8.26

- 584.91

1996 1.97

- 111.93 6.29

- 356.4 0 0

1997 0 0 0 0 8.26

- 584.91

1998 0 0 0 0 8.26

- 584.91

1999 0 0 0 0 8.26

- 584.91

2000 1.95

- 110.77 6.31

- 357.5 0 0

2001 1.98

- 112.16 6.28

- 356.1 0 0

2002 1.99

- 112.72 6.27

- 355.6 0 0

2003 2.16

- 122.73 6.09

- 345.6 0 0

2004 2.19

- 124.10 6.07

- 344.2 0 0

2005 2.22

- 125.79 6.04

- 342.5 0 0

2006 0 0 0 0 8.26

- 584.91

2007 2.23

- 126.33 6.03

- 342.0 0 0

Table 7.23 Change in carbon stocks in soil in cropland and grassland converted to settlements

### 183

7.6.3 Source

- specific recalculations

Estimates of soil carbon stock changes resulting from transition of cropland and grassland to settlements have been provided. S ignificant deviations from the p recedent sectoral estimates occurred, essentially due to the revision of SOC reference value for cropland and grassland. This

results in mean increase of emissions equal to 28% in settlements category, in the period 1990

- 2006.

7.6.4 Source

- specific planne d improvements

Further investigation will be made to obtain additional statistics about settlements, comparing the added information with the time series developed from Corine Land Cover data (APAT, 2004). Urban tree formations will be probed for informat ion, in order to estimate carbon stocks. Moreover improvements will concern acquirement of data sufficient to give estimates of carbon stocks changes in dead organic matter for land in transition to settlements.

7.7 Other Land (5F)

Under this category, CO 2 

### emissions, from living biomass, dead organic matter and soils, from land converted in other land should be accounted for; no data is reported since the conversion to other land is not occurring.

7.8 Direct N 2 

### O emissions from N fertilization (5(I))

N 2 

### O emissions from N fertilization of cropland and grassland are reported in the agriculture sector; therefore only forest land should be included in this table; no data have been reported, since no fertilizers are applied to forest land.

7.9 N 2 

### O emission

s from drainage of soils (5(II))

As regards to N

2 

### O emissions from N drainage of forest or wetlands soils no data have been reported, since no drainage is applied to forest or wetlands soils.

7.10 N

2 

### O emissions from disturbance associated with land

- use c onversion to Cropland (5(III))

7.10.1 Source category description

Under this category, N 2 

### O emissions from disturbance of soils associated with land

- use conversion to cropland are reported, according to the GPG (IPCC, 2003). N 2 

### O emissions from cropland re maining cropland are included in the agriculture sector of the good practice guidance. The good practice guidance provides methodologies only for mineral soils.

7.10.2 Methodological issues

N 2 

### O emissions from land use conversions are derived from mineral ization of soil organic matter resulting from conversion of land to cropland. The average area of land undergoing a transition

from non

- cropland to cropland during each year, from 1990 to 2007, has been estimated with

### 184

the land use change matrices; as above mentioned , only conversion from grassland to cropland has occurred in the Italian territory. The GPG equation 3.3.14 has been used to estimate the

emissions of N 2 

### O from mineral soils, resulting from the land use change. Changes in carbon stocks in mineral soils in land converted to cropland have been estimated following land use changes, resulting in a change of the total soil carbon content. Assuming the GPG default values, 15 and 0.0125 kg N 2 

### O

- N/kg N for the C/N ratio and for calculating N 2 

### O

emissions fro m N in the soil respectively, N 2 

### O emissions have been estimated.

In Table 7.24 N 2 

### O emissions resulting from the disturbance associated with land

- use conversion to cropland are reported:

Year Conversion Area Carbon stock N net

- min N 2 O net

- min - N N 2 O emis sions

k ha Gg C kt N kt N 2 O

- N Gg N 2 0

1990 0 0 0 0 0

1991 0 0 0 0 0

1992 0 0 0 0 0

1993 17 238 15.9 0.199 0.312

1994 43 603 40.2 0.502 0.789

1995 34 483 32.2 0.403 0.633

1996 0 0 0 0 0

1997 9 122 8.1 0.10141 0.159

1998 68 963 64.2 0.803 1.262

1999 97 1,367 91.1 1.139 1.790

2000 0 0 0 0 0

2001 0 0 0 0 0

2002 0 0 0 0 0

2003 0 0 0 0 0

2004 0 0 0 0 0

2005 0 0 0 0 0

2006 52 735 49 0.613 0.96

2007 0 0 0 0 0

Table 7.24 N 2 O emissions from land

- use conversion to cropland



### 7.10.4 Source

- specifi c recalculations

Several differences are recognisable in the comparison between 2008 and 2009 submission, essentially due to the revision of SOC reference value for cropland and grassland and the consequent variation of carbon stocks in soils for land con verting from grassland to cropland.

This results in mean increase of emissions equal to 24%, in the period 1990

- 2006.

7.11 Carbon emissions from agricultural lime application (5(IV))

Carbon emissions from agricultural lime application are not estimated, since no lime application is occurring.

7.12 Biomass Burning (5(V))

7.12.1 Source category description

Under this source category, CH 4 

### and N 2 

### O emissions from forest fires are estimated, in

accordance with the IPCC method.

### 185

National statistics on areas affected by fire per region and forestry use, high forest (resinous, broadleaves, resinous and associated broadleaves) and coppice (simple, compound and degraded), were used (ISTAT, several years [a]).

CO 2 

### emissions due to forest fires in forest land rem aining forest land are included in table 5.A.1 of the CRF, under carbon stock change in living biomass

- decrease.

7.12.2 Methodological issues

In Italy, in consideration of national regulations, forest fires do not result in changes in land use;

theref ore conversion of forest and grassland does not take place. Anyway CO 2 

### emissions due to forest fires in forest land remaining forest land are included in table 5.A.1 of the CRF, under carbon stock change in living biomass

- decrease. The total biomass redu ction due to forest
fires, and subsequent emissions, have been estimated following the methodology reported in paragraph 7.2.2.

IPCC method was followed for CH 4 

### and N

2 

### O emissions, multiplying the amount of C released
from 1990 to 2007, calculated on the ba sis of regional parameters (Bovio, 1996), by the emission factors suggested in the IPCC guidelines (IPCC, 1997).

In Table 7.25 CH 4 

### and N 2 

### O emissions resulting from biomass burning are reported:

CH 4 emissions N 2 O emissions

year Gg Gg

1990 6.80 0.047

1991 1.74 0.012

1992 2.88 0.020

1993 7.18 0.049

1994 2.90 0.020

1995 1.30 0.009

1996 1.06 0.007

1997 3.53 0.024

1998 4.11 0.028

1999 2.02 0.014

2000 4.14 0.028

2001 2.63 0.018

2002 1.47 0.010

2003 3.09 0.021

2004 1.65 0.011

2005 1.63 0.011

2006 1.46 0.010

2007 9.37 0.064

Table 7.25 CH

4 and N

2 O emissions from biomass burning



### 7.12.3 Source

- specific planned improvements

An expert panel on forest fires has been set up, in order to obtain geographically referenced data
on burned area; the overl apping of land use map and georeferenced data should assure the estimates of burned areas in the different land uses, with a particular focus on grassland fires in

order to provide estimates of CO 2 

### emissions. Activities planned in the framework of the

Nati onal Registry for Forest Carbon Sinks should also provide data to improve estimate of emissions by biomass burning.

### 186

7.12.4 Source

- specific recalculations

No variations of CH 4 

### and N

2 

### O emissions from forest fires between the previous and the current

sub mission are noticeable, except for the year 2006, where an increase of 10% has been evidenced, due to a change in the official statistics of burned area for 2006.

### 187



## Chapter 8: WASTE [CRF sector 6]

8.1 Overview of sector

The waste sector comprises fou r source categories:

1 solid waste disposal on land (6A);

2 wastewater handling (6B);

3 waste incineration (6C);

4 other waste (6D). The waste sector share of GHG emissions in the national greenhouse total is presently 3.34% (and was 3.47% in the base year 1990). The trend in greenhouse gas emissions from the waste sector is summarised in Table 8.1. It clearly shows that methane emissions from solid waste disposal sites (landfills) are by far the largest source category within this sector; in fact these emissions r ank among the top

- 10 key level and key trend sources. Emissions from waste incineration facilities without energy recovery are reported under category 6C, whereas emissions from waste incineration facilities, which produce electricity or heat for energetic purposes, are reported under category 1A4a (according to the IPCC reporting guidelines).
Under 6D, CH

4 

### and NMVOC emissions from compost production are reported. Emissions from methane recovered, used for energy purposes, in landfills and wastewater

treatm ent plants are estimated and reported under category 1A4a.

GAS/SUBSOURCE 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO 2 (Gg)

6C. Waste incineration 536.90 483.02 201.57 222.26 244.97 215.76 199.23 244.69 267.49 270.17

CH 4 (Gg)

6A. Solid waste disposal on land 633.22 750.21 801.16 793.42 765.11 733.44 690.02 687.46 649.42 635.27
6B. Wastewater handling 94.67 105.37 109.62 110.74 111.19 110.60 110.98 111.55 113.97 115.95

6C. Waste incineration 7.65 12.91 11.94 12.98 12.59 12.85 16.20 14.14 13.47 12.89
6D. Other (compost production) 0.01 0.02 0.10 0.12 0.16 0.18 0.18 0.20 0.21 0.22

N 2 O (Gg)

6B. Wastewater handling 6.01 5.85 6.35 6.25 6.26 6.29 6.34 6.38 6.44 6.51

6C. Waste inciner

ation 0.28 0.42 0.36 0.39 0.38 0.38 0.47 0.42 0.40 0.39

Table 8.1 Trend in greenhouse gas emissions from the waste sector 1990

– 2007 (Gg)



### In the following box, key and non

- key sources of the waste sector are presented based on level,

trend or both. Meth

ane emissions from landfills result as a key source at level assessment calculated with Tier 1 and Tier 2, whereas at trend assessment taking into account uncertainty; methane and nitrous oxide emission from wastewater handling is a key source at level and trend assessment, when taking into account uncertainty. When including the LULUCF sector in the key source analysis, the same results are observed

for methane emission

s from landfills and wastewater handling , whereas nitrous oxide is a key source only at

trend level considering the uncertainty.

Key

- source identification in the waste sector with the IPCC Tier 1 and Tier 2 approaches (without LULUCF)

6A CH

4 Emissions from solid waste disposal sites Key (L, T2)

6B CH

4 Emissions from wastewater handling Key (L2, T2)

6B N 2 O Emissions from wastewater handling Key (L2, T2)

6C CO 2 Emissions from waste incineration Non

- key

6C CH

4 Emissions from waste incineration Non

- key

6C N 2 O Emissions from waste incineration Non

- key

6D CH

4 Emissions from other waste (compost p roduction) Non

- key

### 188

8.2 Solid waste disposal on land (6A)

8.2.1 Source category description

The source category Solid waste disposal on land is a key category for CH 4 

### , both in terms of

level and trend. The share of CH 4 

### emissions in the national methane t otal is presently 34.91% (and was 31.86 % in the base year 1990). For this source category, also NMVOC emissions are estimated; it has been assumed that non

methane volatile organic compounds are 1.3 weight per cent of methane (Gaudioso et al., 1993):

this assumption refers to US EPA data (US EPA, 1990). Methane is emitted from the degradation of waste occur in municipal landfills, both managed and unmanaged. The main parameters that influence the estimation of emissions from landfills are, apart from the

am ount of waste disposed into managed landfill, the waste composition, the fraction of methane in the landfill gas and the amount of landfill gas collected and treated. These parameters are strictly dependent on the waste management policies throughout the w aste streams which start from its generation, flow through collection and transportation, separation for resource recovery, treatment for volume reduction, stabilisation, recycling and energy recovery and terminate at

landfill sites. The disposal of munici

pal solid waste (MSW) in landfill sites is still the main disposal practice: the percentage of municipal solid waste disposed in landfills dropped from 91% in 1990 to 52% in 2007. This trend is strictly dependent from policies that have been taken in the l ast 20 years in waste management. In fact, at the same time, waste incineration has fairly increased, whereas composting and mechanical and biological treatment have shown a remarkable rise due to the enforcement of legislation ( Figure 8.1). Also recyclabl e waste collection, which at the beginning of nineties was a scarce practice and waste were mainly disposed in bulk in landfills or incineration plants, has increased: in 2007, the percentage of municipal solid waste separate
collection is 27.5%, but still far from legislative targets (fixed 40% in 2007).

0% 20% 40% 60% 80% 100%199019911992199319941995199619971998199920002001200220032004200520062007

Solid Waste disposal on land* Waste Incineration Other treatments

Figure 8.1 Percentage of municipal solid waste treatment and disposal, 1990

– 2007 (%)

*except sludge



### In particular, in Italy the first legal provision concerning waste management was issued in 1982
(D ecree of President of the Republic 10 September 1982, n.915), as a consequence of the transposition of some European Directives on waste ( EC, 1975; EC, 1976; EC, 1978 ). In this decree, uncontrolled waste dumping as well as unmanaged landfills are forbidden , but the

### 189

enforcement of these measures has been concluded only in 2000. Thus, from 2000 municipal solid wastes are disposed only into managed landfills. For the year 2007, the MSW landfills in Italy are 269, disposing 20,250 kt of wastes.
Since 1999, the number of MSW landfills has diminished from 786 to 269, despite the decrease of the amount of wastes disposed of is less strong. This because both uncontrolled landfills and small controlled landfills have been progressively closed, especially in the south of the country, preferring the use of modern and larger plants, which cover large territorial areas.

Concerning the composition of waste which is disposed in municipal landfills, this has been changed within the years, because of the modification of wast e production due to the life

- style changing and not for a forceful policy on waste management.

The Landfill European Directive (EC, 1999) has been transposed in national decree only in 2003 by the Legislative Decree 13 January 2003, n. 36 and applied to t he Italian landfills since July 2005, but the effectiveness of the policies will be significant in the future. Moreover, a recent law decree (Legislative Decree 30 December 2008, n.208) shift to December 2009 the end of the temporary condition regarding wa ste acceptance criteria, thus the composition of waste accepted in landfills is hardly changing.

Finally, methane emissions are expected only from non hazardous waste landfills due to biodegradability of wastes disposed; in the past, law’s disposition for ced only this category to have a collecting gas system. Investigation has been carried out on C&D waste landfills to prove that inert typology do not generate methane emissions. No references demonstrating methane emissions from other than municipal solid waste landfills have been found. Anyway, a preliminary investigation on characterization of C&D waste is carrying out and possible results could be applied in the next year submission.

8.2.2 Methodological issues

Emission estimates from solid waste dispo sal on land have been carried out using the IPCC Tier 2 methodology, through the application of the First Order Decay Model (FOD).

Parameter values used in the landfill emissions model are: 1) total amount of waste disposed;
2) fraction of Degradable Organic Car bon (DOC); 3) fraction of DOC dissimilated (DOC F 

### );
4) fraction of methane in landfill gas (F); 5) oxidation factor (O X 

### ); 6) methane correction factor (MCF);
7) methane generation rate constant (k); 8) landfill gas recovered (R).

The assumption that all the landfills, both managed and unmanaged, started operation in the same year, and have the same parameters, has been considered, although characteristics of individual sites can vary substantially. Moreover, the share of waste disposed of into uncontrolled landfills has grad ually decreased, as specified previously, and in the year 2000 it has been assumed equal to 0; nevertheless, emissions still occur due to the waste disposed in the past years. The unmanaged sites have been

considered shallow.

M unicipal solid waste

Basic data on waste production and landfills system are those provided by the national Waste Cadastre. The Waste Cadastre is formed by a national branch, hosted by ISPRA , and by regional

### 190

and provincial branches

. The basic information for the Cadastre is mainly r epresented by the data reported through the Uniform Statement Format (MUD), complemented by th at provided by regional permits, provincial communications and by registrations in the national register of companies involved in waste management activities.

Th ese figures are elaborated and published by ISPRA yearly s ince 1999: the yearbooks report waste production data, as well as data concerning landfilling, incineration, composting and

g enerally waste life

- cycle data (ANPA

- ONR, several years; APAT

- ONR, severa l years).

For inventory purposes, a database of waste production, waste disposal in managed and unmanaged landfills and sludge disposal in landfills was created and it has been assumed that waste landfilling started in 1950.

The complete database from 1 975 of waste production, waste disposal in managed and unmanaged landfills and sludge disposal in landfills is reconstructed on the basis of different sources (MATTM, several years; FEDERAMBIENTE, 1992; AUSITRA

- Assoambiente, 1995;

ANPA

- ONR, 1999 [a], [b]; APAT , 2002; APAT

- ONR, several years ), national legislation (Legislative Decree 5 February 1997, n.22), and regression models based on population (Colombari et al, 1998).

Since waste production data are not available before 1975, they have been reconstruct ed on the basis of proxy variables. Gross Domestic Product data have been collected from 1950 (ISTAT, several years [a]) and a correlation function between GDP and waste production has been derived from 1975; thus, the exponential equation has been applied from 1975 back to 1950.

Consequently the amount of waste disposed into landfills has been estimated, assuming that from 1975 backwards the percentage of waste landfilled is constant and equal to 80%; this percentage has been derived from the analysis of available data . As reported in the Figure 8.2, in the period 1973

–1996 data are available for specific years (available data are reported in dark blue, whereas estimated data are reported in light blue). The trend is strictly dependent by national polici

es adopted for waste management and from news stories happened in those years: above all Seveso incident. From 1973 waste disposal on landfill was decreasing because of the increment of incineration practice: in 1976, Seveso incident affected the use of in cineration as final waste treatment, and for some years onwards, waste disposal on land became again the most common practice. Reasonable, before 1973, the percentage of waste disposal on land has been set equal to 80%.

88.0 92.6 88.2

67.9 78.5

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.019731974197519761977197819791980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007

Figure 8.2 Percentage of MSW disp osal on land (%)

### 191

In Table 8.2, the time series of activity data from 1990 is reported.

ACTIVITY DATA 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

MSW Production (Gg) 22,231 25,780 28,959 29,409 29,864 30,034 31,150 31,664 32,523 32,548

MSW Dispose d of (%) 91.1 85.5 75.7 68.0 63.1 59.9 57.0 54.4 53.9 52.0

- in managed landfills 62.1 70.6 75.7 68.0 63.1 59.9 57.0 54.4 53.9 52.0

MSW Disposed in managed landfills (Gg) 13,797 18,196 21,917 20,003 18,848 17,996 17,742 17,226 17,526 16,912

MSW Disp osed in unmanaged
landfills (Gg) 6,462 3,849 0 0 0 0 0 0 0 0

Total MSW to landfills (Gg) 20,260 22,044 21,917 20,003 18,848 17,996 17,742 17,226 17,526 16,912

Table 8.2 Trend of MSW production and MSW disposed in landfills, 1990

– 2007



### Sludge from urban wastewater plants

In addition to municipal solid waste, sludge from urban wastewater handling plants have also been considered, because they can be disposed in the same landfills, once they meet specific requirements.

The fraction of sludge disposed in landfill sites has been estimated to be 75% in 1990, decreasing to 55% in 2007.

On the basis of their characteristics, sludge from urban wastewater handling plants are also used in agriculture, spreading on land, and in compost production, or treated in i ncineration plants. The percentage of each treatment (landfilling, soil spreading, composting, incinerating and stocking), has been reconstructed within the years starting from 1993: for th at year, data on tonnes of sludge treated in a given way are avail able from a survey conducted by the National Institute of Statistics on urban wastewater plants (ISTAT, 1998 [a] and [b]; De Stefanis P. et al., 1998). Before 1993 the percentage has been considered constant, whereas from 1993 onwards

each percentage has b

een varied on the basis of data known for specific years (especially for sludge use in agriculture and for compost production (MATTM, 2005; APAT

- ONR, several years).

The total production of sludge from urban wastewater plants, to which apply the percentag es mentioned above, has been estimated from the equivalent inhabitants treated in wastewater treatment plants, distinguished in primary and secondary plants (MATTM, 1989; ISTAT, 1991;
ISTAT, 1993; ISTAT, 1998 [a] and [b]), applying the specific per capita sludge production (Masotti, 1996; ANPA, 2001; ApS, 1997).

As for the waste production, also sludge production has been reconstructed from 1950. Starting from the number of wastewater treatment plants in Italy in 1950, 1960, 1970 and 1980 (ISTAT,
1987), th e equivalent inhabitants have been derived.

To summarize, from 1990 both data on equivalent inhabitants and sludge production are available (published or estimated), thus it is possible to calculate a per capita sludge production: the parameter result equ

al on average to 80 kg inhab.

- 1 

### yr - 1 

### . Consequently, this value has been multiplied to equivalent inhabitants from 1990 back to 1950.

In Table 8.3, time series of equivalent inhabitants treated in urban wastewater plants, as well as sludge production is re ported.

### 192

ACTIVITY DATA 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Total equivalent inhabitants
(*1000) 46,509 60,114 65,016 65,996 66,977 67,957 68,938 70,761 73,905 77,048

Equivalent inhabitants treated with primary system

(*1000) 2,105 3,235 4,6 10 4,680 4,749 4,819 4,888 5,018 5,241 5,464

Equivalent inhabitants treated with secondary system

(*1000) 44,404 56,879 60,406 61,317 62,228 63,139 64,050 65,744 68,664 71,585

Per capita primary sludge production (g SS /inhab.* year) 37 37 37 37 37 37 37 37 37 37

Per capita secondary sludge
production (g SS /inhab.* year) 55 55 55 55 55 55 55 55 55 55

Primary sludge production (kt) 28 44 62 63 64 65 66 68 71 74

Secondary sludge production (kt) 891 1,142 1,213 1,231 1,249 1,268 1,286 1,320 1,378 1,437

Total sludge production (kt) 920 1,186 1,275 1,294 1,313 1,333 1,352 1,388 1,449 1,511

Total sludge production

- 25% dry solid (kt) 3,679 4,742 5,100 5,177 5,253 5,330 5,407 5,550 5,797 6,043

Sewage sludge landfilled (kt) 2,764 3,479 3,170 3,194 3,022 3, 117 3,258 3,241 3,239 3,339

Table 8.3 Trend of equivalent inhabitants treated in urban wastewater plants and sludge production, 1990

– 2007



### Waste composition

One of the most important parameter that influences the estimation of emissions from landfills is the waste composition.

An in

- depth survey has been carried out, in order to diversify waste composition over the years. On the basis of data available on waste composition (Tecneco, 1 972; CNR, 1980; Ferrari, 1996),
three slots (1950

–1970; 1971

–1990; 1991

–2007) have been individuated to which different waste composition has been assigned. The moisture content and the organic carbon content are from national studies (Andreottola and
Cossu, 1988; Muntoni and Polettini, 2002).
In Tables 8.4, 8.5 and 8. 6 waste composition of each national survey mentioned above is reported. Waste types containing most of the DOC and thus involved in methane emissions are highlighted in bold type.

WASTE COMPONENT Composition by weight (wet waste)

Food 34.1%

Garden and park 3.8%
Paper, paperboard 31.0%

Plastic 3.0%

Inert 28.1%
Table 8.4 Waste composition 1950

- 1970 (TECNECO, 1972)

WASTE COMPONENT Composition by weight (wet waste)

Food 37.9% Garden and park 4.2%
Paper, paperboard, textile and wood 22.3%

Plastic 7. 2%

Metal 3.0%

Inert 7.1% Screened waste ( < 2 cm) 18.3%
Table 8.5 Waste composition 1971

- 1990 (CNR, 1980)

### 193

WASTE COMPONENT Composition by weight (wet waste)

Food 26.3% Garden and park 4.5% Paper, paperboard 30.1%
Textile, leather 5.1%

Plastic 15.0 %

Metal 3.1%

Inert 6.3% Bulky waste 0.6%

Various 1.6%
Screened waste ( < 2 cm) 7.4%
Table 8.6 Waste composition 1991

- 2007 (FERRARI, 1996)



### Since sludge is not included in waste composition, because it usually refer s to waste production

and not to was te landfilled, they have been added to each waste composition, recalculating the percentage of waste type. On the basis of the waste composition, waste stream have been categorized in three main types: rapidly biodegradable waste, moderately biodegradable waste and slowly biodegradable waste, as reported in Table 8.7. Methane emissions have been estimated separately for each mentioned biodegradability class and the results have been consequently added up.

Waste biodegradability Rapidly biodegradable Modera tely biodegradable Slowly biodegradable

Food X Sewage sludge X Garden and park X
Paper, paperboard X
Textiles, leather X

Wood X Table 8.7 Waste biodegradability



### Degradable organic carbon (DOC) and Methane generation potentia l (L 0 

### )

Degradable organic carbon (DOC) is the organic carbon in waste that is accessible to biochemical decomposition , and should be

expressed as Gg C per Gg waste. The DOC in bulk waste is estimated based on the composition of waste and can be calculated from a weighted average of the degradable carbon content of various components of the waste stream. The following equation estimates DOC using default carbon content values

.

DOC = 

## Σ i 

### (DOC i 

### * W i 

### )

Where: DOC = fraction of degradable organic carbon in bulk waste, kg C/ kg of wet waste

DOC i 

### = fraction of degradable organic carbon in waste type i

, W i 

### = fraction of waste type i by waste category

Degradable organic carbon in waste type i can be caluculated as following:

DOC i 

### = C i 

### * (1

- u

i 

### ) * W i



### Where:

C i 

### = organic carbon content in dry waste type i , kg C/ kg of waste type i

u i 

### = moisture content in waste type i

W i 

### = fraction of waste type i by waste category

### 194

In Tables 8.8, 8.9 and 8.10, on ly for waste type generating landfill gas emissions, new composition (including sludge), moisture content, organic carbon content and consequently degradable organic carbon both in waste type i and in bulk waste are reported.

WASTE COMPONENT Composition b y weight (wet waste) Moisture

content Organic carbon

content (dry matter) DOC i (kg C/ t MSW )

Food 32

. 7% 60% 48% 62

. 72 Garden and park 3

. 6% 50% 48% 8

. 71 Paper, paperboard 29

. 7% 9% 50% 135

. 09
Sludge 4

. 2% 75% 48% 5

. 07

DOC 211

. 59
Table 8.8 Degradable O rganic Carbon calculation, 1950

- 1970

WASTE COMPONENT Composition by weight (wet waste) Moisture

content Organic carbon

content (dry matter) DOC i (kg C/ t MSW )

Food 33

. 3% 60% 48% 63

. 95 Garden and park 3

. 7% 50% 48% 8

. 88
Paper, paperboard, textile and

woo d 19

. 6% 9% 50% 89

. 19 Sludge 12

. 1% 75% 48% 14

. 52

DOC 176

. 54 Table 8.9 Degradable Organic Carbon calculation, 1971

- 1990

WASTE COMPONENT Composition by weight
(wet waste) Moisture

content Organic carbon

content (dry matter) DOC i (kg C/ t MSW )

Food 22

. 9 % 60% 48% 43

. 98 Garden and park 3

. 9% 50% 48% 9

. 36 Paper, paperboard 26

. 2% 8% 44% 106

. 19
Textile, leather 4

. 5% 10% 55% 22

. 11
Sludge 12

. 9% 75% 48% 15

. 53

DOC 197

. 18
Table 8.10 Degradable Organic Carbon calculation, 1991

- 2007



### Once known the degradabl e organic carbon, the methane generation potential value (L 0 

### ) is calculated as following:

L 0 

### = MCF * DOC * DOC F 

### * F * 16/12

Where:

MCF = methane correction factor

DOC F 

### = fraction of DOC dissimilated F = fraction of methane in landfill gas

Fraction of de gradable organic carbon (DOC F 

### ) is an estimate of the fraction of carbon that is ultimately degraded and released from landfill , and reflects the fact that some degradable organic carbon does not degrade, or degrades very slowly, under anaerobic conditions in the

landfill.

DOC F 

### value is dependent on many factors like temperature, mois ture, pH, composition of waste:

the default value 0.5 has been used. The methane correction factor (MCF) accounts for that unmanaged SWDS produce less CH 4 

### from a given amount of waste than managed SWDS, because a larger fraction of waste decomposes aerobically in the top layers of managed SWDS. The MCF

, in relation to solid

waste management

, is specific to that area and should be interpreted as the ‘waste management

correction fa ctor’, which reflects the management aspect that it encompasses.

### 195

The MCF value used for unmanaged landfill is the default IPCC values reported for uncategorised landfills: in fact, in Italy, before 2000 existing unmanaged landfills were most ly
shallow, bec ause they resulted in uncontrolled waste dumping instead of real deep unmanaged landfills. To be conservative, the default IPCC values reported for uncategorised landfills has

been used. Finally, it is assumed that landfill gas composition is 50% carbon di oxide and 50% methane. The following Table 8.11 summarize the methane generation potential values (L 0 

### ) generated, distinguished for managed and unmanaged landfills.

L 0 (m 3 CH 4 tMSW

- 1 ) 1950

- 1970 1971

- 1990 1991

- 2007

Rapidly biodegradable

- Man aged landfill 90.5 85.1 81.8

- Unmanaged landfill 54.3 51.1 49.1
Moderately biodegradable

- Managed landfill 118.2 118.2 118.2

- Unmanaged landfill 70.9 70.9 70.9
Slowly biodegradable

- Managed landfill 224.1 224.1 205.9

- Unmanaged la ndfill 134.5 134.5 123.5
Table 8.11 Methane generation potential values by waste composition and landfill typology



### Methane generation rate constant (k)

The methane generation rate constant k in the FOD method is related to the time taken for DOC

in wast e to decay to half its initial mass (the ‘half life’ or t1⁄2).

The maximum value of k applicable to any single solid waste disposal site (SWDS) is determined by a large number of factors associated with the composition of the waste and the

conditions at the site. The most rapid rates are associated with high moisture conditions and rapidly degradable material such as food waste. The slowest decay rates are associated with dry

site cond i tions and slowly degradable waste such as wood or paper. Thus, for each ra pidly, moderately and slowly biodegradable fraction, a different maximum methane generation rate constant has been assigned, as reported in Table 8.12. Values are suggested by national experts Andreottola and Cossu (Andreottola and Cossu, 1988),

and refer to a study in which k values have been determined through experimental tests ( Ham

, 1979 ); despite these figures are not from national experimental tests, they well adjust to the

Italian landfills.

WASTE TYPE Half life Methane generation

rate constant

Rapi dly biodegradable 1 year 0.69

Moderately biodegradable 5 years 0.14

Slowly biodegradable 15 years 0.05

Table 8.12 Half

- life values and related methane generation rate constant



### Landfill gas recovered (R) Landfill gas recovered data have been reconstruct ed on the basis of information on extraction plants (De Poli and Pasqualini, 1991; Acaia et al., 2004; Asja, 2003) and electricity production (TERNA, several years). Only managed landfills have a gas collection system, and t he methane extracted can be used for energy or can be flared

. In Figure 8.3 m

ethane recovery distinguished in flared amount and energy purposes is reported.

### 196 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000199019911992199319941995199619971998199920002001200220032004200520062007tons

Methane recovery - flared - energy purposes

Figure 8.3 Methane recovery distinguished in flared amount and energy purposes (tons) 

### 8.2.3. Uncertainty and time

- series consiste ncy

The combined uncertainty in CH 4 

### emissions from solid waste disposal sites is estimated to be 36.1% in annual emissions, 20% and 30% for activity data and emission factors, respectively, as suggested by the IPCC Good Practice Guidance (IPCC, 2000).

The time series of CH 4 

### emissions is reported in Table 8.13; emissions from the amount used for energy purposes are estimated and reported under category 1A4a.

EMISSIONS 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Managed Landfills

Methane p roduced (Gg) 575.1 770.1 965.7 1013.1 1027.5 1029.7 1030.9 1038.2 1042.9 1055.7

Methane recovered (Gg) 108.9 144.1 203.4 245.2 281.6 311.9 355.8 360.5 403.2 427.3

Methane recovered (%) 18.9 18.7 21.1 24.2 27.4 30.3 34.5 34.7 38.7 40.5

CH 4 net emissions (Gg) 414.2 556.1 677.2 682.1 662.6 637.6 599.7 602.0 568.3 558.2

NMVOC net emissions (Gg) 5.5 7.3 8.9 9.0 8.7 8.4 7.9 7.9 7.5 7.4

Unmanaged Landfills

Methane produced (Gg) 222.0 196.7 125.6 112.8 103.9 97.1 91.5 86.6 82.2 78.1

Methan e recovered (Gg) 0 0 0 0 0 0 0 0 0 0

CH 4 net emissions (Gg) 219.1 194.2 124.0 111.3 102.6 95.9 90.3 85.5 81.1 77.1

NMVOC net emissions (Gg) 2.9 2.6 1.6 1.5 1.4 1.3 1.2 1.1 1.1 1.0

Table 8.13 Methane produced, recovered and CH 4 and NMVOC net emissions, 1 990

– 2007 (Gg)



### Whereas waste production continuously increases, from 2001 solid waste disposal on land has decreased as a consequence of waste management policies (see Tables 8.2). At the same time,

the increase in the methane

- recovered percentage has le d to a reduction in net emissions. Further reduction is expected in the future because of the increasing in waste recycling.

8.2.4. Source

- specific QA/QC and verification

The Waste Cadastre system, as reported above, requires continuous and systematic kn owledge exchange and QA/QC checks in order to ensure homogeneity of information concerning waste production and management throughout the entire Italian territory. Moreover, the methodology, as well as the parameters used in the calculation of the emission s from landfills, have been presented and discussed at the 10 th 

### International Trade Fair on Material and Energy Recovery and Sustainable Development , Ecomondo 2006 (Ecomondo, 2006).

### 197

8.2.5. Source

- specific recalculations

No recalculations occurred.

8.2.6 . Source

- specific planned improvements

Improvements are expected due to the entering into force of the landfill directive (EC, 1999). The application of the Directive would implement the availability of data regarding the main parameters influencing the e stimation of emission from landfills: the waste composition, the fraction of methane in the landfill gas and the amount of landfill gas collected and treated (EEA,

2005 ). In particular, an update of waste composition is available, referring to a 35% separa te collection waste, and will be used in next inventory submissions. Moreover, a preliminary investigation on characterization of C&D waste is on going and possible results could be applied in the next year submission.

8.3 Wastewater handling (6B)

8.3.1. Source category description

Under source category 6B, CH 4 

### and N

2 

### O are estimated both from domestic

- commercial and

industrial wastewaters.

In Table 8.14 a n

emissions reporting scheme is shown.

6.B.1 Industrial wastewater

Wastewater

Sludge Emissions from sludge are reported in 6.B.1 Industrial

wastewater/wastewater

6.B.2 Domestic and commercial wastewater

6.B.2.1 Domestic and commercial wastewater

Wastewater N 2 O emissions are reported in 6.B.2.2 H uman sewage Sludge N 2 O emissions are reported in 6.B.2.2 Human sewage

6.B.2.2 Human sewage Table 8.14 Emissions reporting scheme



### The principal by

- product of the anaerobic decomposition of the organic matter in wastewater is methane gas. Normally, CH 4 

### emissions are not encountered in untreated wastewater because even small amounts of oxygen tend to be toxic to the organisms responsible for the production of methane. Occasionally, however, as a result of anaerobic decay in accumulated bottom deposits, methane can be produced. On the contrary, in treatment plants, methane is produced

from the anaerobic tr

eatment process used to stabilis ed wastewater sludge. Actually, in Italy 84% of population is served by sewer systems, wher eas 74.8% of population is served by wastewater treatment plants ( COVIRI, 2005 ). In unsewered areas, onsite systems, such as Imhoff tanks, are usually used. The minor percentage of population served by wastewater treatment plants implies a fraction of wast ewater directly discharged in the soil or in surface water without any treatment. On the basis of the characteristics of the influent, the plant typology is usually distinguished in ‘primary’ (only physical

- chemical unit operations such as sedimentation), ‘secondary’ (biological unit process) or ‘advanced’ treatments, defined as those additional treatments needed to remove suspended and dissolved substances remaining after conventional secondary

treatment. In Italy wastewater handling is managed mainly usin g a secondary treatment, with aerobic biological units: a standard design facility consists of bar racks, grit chamber, primary sedimentation, aeration tanks (with return sludge), settling tank, chlorine contact chamber. The

### 198

stabilization of sludge occurs in aerobic or anaerobic reactors; where anaerobic digestion is used, the reactors are covered and provided of gas recovery.

As a consequence of these considerations, it is assumed that domestic and commercial

wastewaters are treated 95% aerobically and 5% anaerobically : 5% of anaerobically systems

refer to those case s where, notwithstanding aerobic treatments, CH 4 

### emissions can occur due to

a bad management.

For high strength organic waste, such as some industrial wastewater, anaerobic process is

recommen

ded also for wastewater besides sludge treatment.

It is assumed that industrial wastewaters are treated 85% aerobically and 15% anaerobically (IRSA

- CNR, 1998). Emissions from methane recovered, used for energy purposes, in wastewater treatment plants

are e stimated and reported under category 1A4a. A percentage of 2.4 % of domestic and commercial wastewater is currently treated in Imhoff tanks, where the digestion of sludge occurs anaerobically without gas recovery. Therefore, very few emissions from sludge d isposal do occur.

8.3.2. Methodological issues

Regarding N 2 

### O emissions, the default approach suggested by the IPCC Guidelines ( IPCC, 1997) , and updated in the Good Practice Guidance ( IPCC, 2000 ), based on population and per capita intake protein has bee n followed. Fraction of nitrogen protein (Frac NPR 

### ) 0.16 kg N kg

- 1



### protein and emission factor (EF 6 

### ) 0.01 kg N

- N 2 

### O kg

- 1 

### N produced have been used, whereas the time series of the protein intake is from the yearly FAO Food Balance (FAO, several years).

The methane estimation concerning industrial wastewaters makes use of the IPCC method based on wastewater output and the respective degradable organic carbon for each major industrial wastewater source. No country specific emission factors of methane per Chemi cal Oxygen Demand (COD) are available so the default value of 0.25 kg CH 4 

### kg

- 1 

### COD, suggested in the IPCC Good Practice Guidance ( IPCC, 2000 ), has been used for the whole time series.

As recommended by the IPCC Good Practice Guidance ( IPCC, 2000 ) for key source categories, data have been collected for several industrial sectors (iron and steel, refineries, organic chemicals, food and beverage, paper and pulp, textiles and leather industry). The total amount of organic material, for each industry selected, has been calculated multiplying the annual production (t year

- 1 

### ) by the amount of wastewater consumption per unit of product (m 3 

### t - 1 

### ) and by the degradable organic component (kg COD (m 3 

### )
- 1 

### ). Moreover, the fraction of industrial degradable organic component removed as sludge has been assumed equal to zero. The yearly industrial productions are reported in the national statistics (ISTAT, several years [a], [b] and [c]), whereas the wastewater consumption factors and the degradable organic component are

either from Good Practice Guidance (IPCC, 2000) or from national references. National data have been used in the calculation of the total amount of both COD produced and wastewater output specified as follows: refineries (UP, several years), organic chemicals
(F EDERCHIMICA, several years), beer (Assobirra, several years) , wine, milk and sugar sectors ( ANPA

- ONR, 2001 ), pulp and paper sector ( ANPA

- FLORYS, 2001 ; Assocarta, several years)

, and leather sector ( ANPA

- FLORYS, 2000 ; UNIC, several years).

In Table 8.15 de tail ed reference s for 2007 are reported: for the se national data, slightly differences within the years can occur.

### 199 Wastewater generation (m 3 /t) References COD (g/l) References

Coke 1.5 IPCC, 2000 0.1 IPCC, 2000

Petroleum Refineries UN IONE PETROLIFERA s upplies Total COD generated per year

Organic Chemicals 22.33 FEDERCHIMICA,
several years 3 IPCC, 2000

Paints 5.5 IPCC, 2000 5.5 IPCC, 2000

Plastics and Resins 0.6 IPCC, 2000 3.7 IPCC, 2000
Soap and Detergents 3 IPCC, 2000 0.9 IPCC, 2000
Vegetables, Fr uits and

Juices 20 IPCC, 2000 5.2 IPCC, 2000

Sugar Refining 4 ANPA

- ONR, 2001 2.5 ANPA

- ONR, 2001
Vegetable Oils 3.1 IPCC, 2000 1.2 IPCC, 2000
Dairy Products 3.9 ANPA

- ONR, 2001 2.7 ANPA

- ONR, 2001
Wine and Vinegar 3.8 ANPA

- ONR, 2001 0.2 ANPA

- ONR, 2001

Be er and Malt 7 Assobirra, several years 2.9 IPCC, 2000
Alcohol Refining 24 IPCC, 2000 11.0 IPCC, 2000
Meat and Poultry 13 IPCC, 2000 4.1 IPCC, 2000

Fish Processing 13 same value of Meat and Poultry 2.5 IPCC, 2000

Paper 34 ANPA

- FLORYS, 2001;

Assocarta, s everal years 0.1 ANPA

- FLORYS,

2001; Assocarta, several years

Pulp 34 ANPA

- FLORYS, 2001; Assocarta, several years 0.1 ANPA

- FLORYS,
2001; Assocarta,
several years
Textiles (dyeing) 60 IPCC, 1995 1.0 IPCC, 2000
Textiles (bleaching) 350 IPCC, 1995 1.0 IPCC, 2000

Leather 0.1 UNIC, 2004 4.03 UNIC, 2004 Table 8.15 Wastewater generation and COD values, 2007.



### CH 4 

### emissions from sludge generated by domestic and commercial wastewater treatment have been calculated using the IPCC default method on the basis of na tional information on anaerobic sludge treatment system (IPCC, 1997; IPCC 2000). A recent survey by the National Institute of Statistics (ISTAT, 2004) has provided information on urban wastewater treatment plants in Italy for the year 1999: an investigatio n on previous references has been done and data on primary treatment plants using Imhoff tanks are also available for 1987 (ISTAT, 1991; ISTAT, 1993) and 1993 (ISTAT, 1998 [a] and [b] ).

CH 4 

### emissions have been calculated on the basis of the equivalent inha bitants treated in Imhoff tanks, the organic loading in biochemical oxygen demand per person equal to 60 g BOD 5 

### capita

1 

### d

- 1 

### , as defined by national legislation and expert estimations ( Legislative Decree 11 May 1999,

no.152 ; Masotti, 1996; Metcalf and Eddy , 1991 ), the fraction of BOD 5 

### that readily settles equal to 0.3 (ANPA, 2001; Masotti, 1996 ), and the IPCC emission factor default value of 0.6 g CH 4 

### g1 

### BOD 5



### .

8.3.3. Uncertainty and time

- series consistency

The combined uncertainty in CH 4 

### emissions from w

astewater handling is estimated to be about

104% in annual emissions 100% and 30% for activity data and emission factor respectively, as derived by the IPCC Good Practice Guidance ( IPCC, 2000 ). The uncertainty in N 2 

### O emissions

is 30% both for activity data and emission factor as suggested in the GPG ( IPCC, 2000 ). The amount of total industrial wastewater production is reported, for each sector, in Table 8.16; as previously noted only the 15% of industrial flows are treated anaerobically (IRSA

- CNR,
1998).

CH 4 

### emission trend for industrial wastewater handling for different sectors is shown in Table
8.17, whereas the emission trend for N 2 

### O emissions both from industrial wastewater handling and human sewage is shown in Table 8.18.

### 200

Concerning CH

4 

### emissions from i

ndustrial wastewater, neither wastewater flow nor average COD value change much over time, therefore emissions are stable and mainly related to the production data

.

The CH

4 

### emission trend from wastewater and sludge generated by domestic and commercial

was tewater treatment is reported in Table 8.19.

8.3.4. Source

- specific QA/QC and verification

Where information is available, wastewater flows and COD concentrations are checked with those reported yearly by the industrial sectoral reports or technical docu mentation developed in the framework of the Integrated Pollution and Prevention Control (IPPC) Directive of the European Union ( http://eippcb.jrc.es ).

Moreover, the methodology, as well the parameters used in the calc ulation of the emissions from wastewater handling, has been presented and discussed at the 10 th 

### International Trade Fair on Material and Energy Recovery and Sustainable Development , Ecomondo 2006 (Ecomondo,
2006).

Wastewater production
(1000 m 3 ) 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Iron and steel 9,534 7,778 6,756 7,244 6,098 5,741 6,093 6,861 7,032 7,091
Oil refinery NA NA NA NA NA NA NA NA NA NA

Organic chemicals 210,936 212,317 215,049 214,670 214,525 214,573 214,869 214,735 214,972 215 ,265

Food and beverage 179,120 177,383 182,736 184,631 182,777 178,950 185,702 185,657 182,693 180,401

Pulp and paper 377,167 402,952 387,285 325,024 339,015 344,689 351,975 366,025 365,649 368,979

Textile industry 108,460 103,047 101,572 100,120 93,714 86,021 79,079 75,492 78,272 79,796

Leather industry 23,623 25,002 27,216 25,580 24,875 22,310 19,706 19,218 20,680 20,534

Total 908,840 928,479 920,614 857,269 861,004 852,283 857,424 867,989 869,297 872,066

Table 8.16 Total industrial wastewater produ ction by sector, 1990

– 2007 (1000 m 3 )

CH 4 Emissions (Gg) 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Iron and steel 0.036 0.029 0.025 0.027 0.023 0.022 0.023 0.026 0.026 0.027
Oil refinery 5.850 5.625 4.250 4.750 4.750 4.750 4.750 4.750 4.750 4. 750
Organic chemicals 23.794 23.911 24.173 24.205 24.210 24.172 24.204 24.177 24.227 24.274
Food and beverage 22.946 22.112 22.871 23.334 23.536 22.739 23.251 23.197 23.220 23.085
Pulp and paper 0.923 0.986 1.055 0.885 0.923 0.939 0.958 0.997 0.996 1.00 5
Textile industry 4.067 3.864 3.809 3.755 3.514 3.226 2.965 2.831 2.935 2.992
Leather industry 3.192 3.378 3.677 3.456 3.361 3.368 2.975 2.901 3.122 3.100

Total 60.81 59.91 59.86 60.41 60.32 59.22 59.13 58.88 59.28 59.23

Table 8.17 CH

4 emissions from anaerobic industrial wastewater treatment, 1990

– 2007 (Gg)

N 2 O Emissions (Gg) 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Industrial Wastewater 0.227 0.232 0.230 0.214 0.215 0.213 0.214 0.217 0.217 0.218
Human Sewage 5.787 5.619 6.115 6.040 6.04 2 6.079 6.123 6.162 6.222 6.294

Total 6.01 5.85 6.35 6.25 6.26 6.29 6.34 6.38 6.44 6.51

Table 8.18 N 2 O emissions from industrial wastewater handling and human sewage, 1990

– 2007 (Gg)

### 201

Domestic and Commercial

Wastewater 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Wastewater (5% treated anaerobically)

Organic loading in wastewater (t year

- 1 ) 49.83 63.83 68.84 69.94 71.05 72.17 73.30 75.42 78.88 82.34

CH 4 emissions (Gg) 29.90 38.30 41.31 41.97 42.63 43.30 43.98 45.25 47.33 49.40

Sludge (generated by Imhoff tanks)

Eq. inhabitants treated in Imhoff tanks
(10 3 millions) 1.005 1.818 2.144 2.123 2.091 2.050 1.999 1.880 1.870 1.855

Organic loading in sludge (t year

- 1 ) 6.606 11.942 14.087 13.946 13.739 13.468 13.132 12.352 12.287 12 .187

CH 4 emissions (Gg) 3.96 7.17 8.45 8.37 8.24 8.08 7.88 7.41 7.37 7.31

Table 8.19 CH

4 emissions from sludge generated by domestic and commercial wastewater treatment, 1990

– 2007 (Gg)



### 8.3.5. Source

- specific recalculations

Minor recalculations due to some new updated data published occur. However, the recalculation

is not relevant.

8.3.6. Source

- specific planned improvements

No specific activities are planned.

8.4 Waste incineration (6C)

8.4.1. Source category description

Existing incinerators i

n Italy are used for the disposal of municipal waste, together with some industrial waste, sanitary waste and sewage sludge for which the incineration plant has been authorized from the competent authority. Other incineration plants are used exclusively fo r industrial and sanitary waste, both hazardous and not, and for the combustion of waste oils, whereas there are few plants that treat residual waste from waste treatments, as well as sewage sludge.
As mentioned above, emissions from waste incineration fac ilities with energy recovery are reported under category 1A4a (Combustion activity, commercial/institutional sector), whereas emissions from other types of waste incineration facilities are reported under category 6C
(Waste incineration). For 2007, nearly 95% of the total amount of waste incinerated is treated in plants with energy recovery system. A complete database of the incineration plants is now available, updated with the information reported in the yearly report on waste production and management pu blished by ISPRA (APAT

ONR, several years). Emissions from removable residues from agricultural production are included in the IPCC category 6C: the total residues amount and carbon content have been estimated by both IPCC

and national factors. The detaile d methodology is reported in Chapter 6 (6.6.2).

CH 4 

### emissions from biogenic, plastic and other non

- biogenic wastes have been calculated.

8.4.2. Methodological issues

Regarding GHG emissions from incinerators, the methodology reported in the IPCC Good

Pra ctice Guidance (IPCC, 2000) has been applied, combined with that reported in the

### 202

CORINAIR Guidebook (EMEP/CORINAIR, 2005). A single emission factor for each pollutant has been used combined with plant specific waste activity data.

Emissions have been calcu lated for each type of waste: municipal, industrial, hospital, sewage sludge and waste oils. A complete data

base of these plants has been built, on the basis of various sources available for the period of the entire time series, extrapolating data for the years for which there was no information (MATTM, several years; ANPA

- ONR, 1999 [a] and [b]; APAT, 2002; APAT

ONR, several years; AUSITRA

- Assoambiente, 1995; Morselli, 1998; FEDERAMBIENTE,
1998; FEDERAMBIENTE, 2001; AMA

- Comune di Roma, 1996; ENI S.p.A., 200 1; COOU, several years). For each plant a lot of information is reported, among which the year of the construction and possible upgrade, the typology of combustion chamber and gas treatment section, if it is provided of energy recovery (thermal or electric ), and the type and amount of waste incinerated (municipal, industrial, etc.). Different procedures were used to estimate emission factors, according to the data available for each type of waste, expect CH 4 

### emission factor that is derived from EMEP Corinai r ( EMEP/CORINAIR, 2005 ).

Specifically:

1 for municipal waste, emission data from a large sample of Italian incinerators were used
(FEDERAMBIENTE, 1998);

2 for industrial waste and waste oil, emission factors have been estimated on the basis of

the allowed lev

els authorized by the Ministerial Decree 19 November 1997, n. 503 of the Ministry of Environment;

3 for hospital waste, which is usually disposed of alongside municipal waste, the emission factors used for industrial waste were also applied;

4 for sewage sludg

e, in absence of specific data, reference was made to the emission limits prescribed by the Guidelines for the authorisation of existing plants issued on the Ministerial Decree 12 July 1990.

In Table 8.20, emission factors are reported in kg per tons of w aste treated, for municipal, industrial, hospital waste, waste oils and sewage sludge.

NMVOC (kg/t) CO

(kg/t) CO 2 fossil

(kg/t) N 2 O

(kg/t) NO

x

(kg/t) SO 2

(kg/t) CH 4 (kg/t)

Municipal waste 0.46 0.07 289.26 0.1 1.15 0.39 0.06
Hospital waste 7.4 0.075 120 0 0.1 0.604 0.026 0.06
Sewage sludge 0.25 0.6 0 0.227 3 1.8 0.06

Waste oils 7.4 0.075 3000.59 0.1 2 1.28 0.06

Industrial waste 7.4 0.56 1200 0.1 2 1.28 0.06

Table 8.20 Waste incineration emission factors



### Here below (Tables 8.21, 8.22, 8.23, 8.24), det ail data and calculation for specific emission factors are reported. Emission factors have been estimated on the basis of a study conducted by

ENEA (De Stefanis, 1999 ), based on emission data from a large sample of Italian incinerators
( FEDERAMBIENTE, 1998 ; AMA

- Comune di Roma, 1996), legal thresholds ( Ministerial Decree 19 November 1997, n. 503 of the Ministry of Environment ; Ministerial Decree 12 July

1990 ) and expert judgements. In detail, as regard CO 2 

### emission factor for municipal waste, it has been cal culated considering a carbon content equal to 23%; moreover, on the basis of the IPCC Guidelines (IPCC, 1997) and referring to the average content analysis on a national scale (FEDERAMBIENTE, 1992), a

distinction was made between CO 2 

### from fossil fuels (gen erally plastics) and CO 2 

### from renewable organic sources (paper, wood, other organic materials). Only emissions from fossil fuels, which are equivalent to 35% of the total, were included in the inventory.

### 203

CO 2 

### emission factor for industrial, oils and hospita l waste has been derived as the average of values of investigated industrial plants. On the other hand, CO 2 

### emissions from the incineration of sewage sludge were not included at all, while all emissions relating to the incineration of hospital and industri

al waste were considered.

Municipal waste Average concentration values (mg/Nm

3 ) Standard specific flue

gas volume (Nm 3 /KgMSW) E.F. (g/t)

SO 2 78.00 5 390

NO

x 230.00 1,150

CO 14.00 70

N 2 O 100

CH 4 59.80

NMVOC 460.46
C content, % weight 23

C O 2 826.5 (kg/t)
Table 8.21 Municipal waste emission factors

Industrial and oil waste Average concentration values (mg/Nm

3 ) Standard specific flue

gas volume (Nm 3 /KgMSW) E.F. (g/t)

SO 2 160.00 8 1,280

NO

x 250.00 2,000

CO 70.00 560

N 2 O 100

CH 4 59.80

NMVOC 7,400

CO 2 1,200 (kg/t)

Table 8.22 Industrial waste and oils emission factors

Hospital waste Average concentration
values (mg/Nm

3 ) Standard specific flue

gas volume (Nm 3 /KgMSW) E.F. (g/t)

SO 2 3.24 8 26

NO

x 75.45 604

CO 9.43 75

N 2 O 100

CH 4 59.80

NMVOC 7,400

CO 2 1,200 (kg/t)
Table 8.23 Hospital waste emission factors

Sewage sludge Average concentration
values (mg/Nm

3 ) Standard specific flue

gas volume (Nm 3 /KgMSW) E.F. (g/t)

SO 2 300 6 1

, 800

NO

x 500 3

, 000

CO 100 600

N 2 O 100

CH 4 59

. 80

NMVOC 7

, 400

CO 2 1

, 200 (kg/t)
Table 8.24 Sewage sludge emission factors



### CH 4 

### and N

2 

### O emissions from agriculture residues removed, collected and burnt ‘off

- site’, as a way to reduce the amount of waste residues, are reported in the waste incineration sub

- sector.

### 204

Removable residues from agriculture production are estimated for each crop type (cereal, green crop, permanent cultivation) taking into account the amount of crop produced, the ratio of removable residue in the crop, th e dry matter content of removable residue, the ratio of removable residue burned, the fraction of residues oxidised in burning, the carbon and nitrogen content of the residues. Most of these wastes refer especially to the prunes of olives and wine,

because of th

e typical national cultivation. We report in the agriculture sector, under 4.F, emissions due to stubble burning, which are emissions only from the agriculture residues burned

on field. Under the waste sector the burning of removable agriculture resi dues that are collected and could be managed in different ways (disposed in landfills, used to produce compost or used to produce energy) is reported

. At the moment no information is available to detail the final management of these wastes so we consider t he total amount all burnt.

The methodology is the same used to calculate emissions from residues burned on fields, in the category 4F, described in details in Chapter 6.

On the basis of carbon and nitrogen content of the residues, CH 4 

### and N

2 

### O emissions have been calculated, both accounting nearly for 100% of the whole emissions from waste incineration.

CO 2 

### emissions have been calculated but not included in the inventory as biomass. All these parameters refer both to the IPCC Guidelines (IPCC, 1997) and c ountry

- specific values (CESTAAT, 1988; Borgioli, 1981).

8.4.3. Uncertainty and time

- series consistency

The combined uncertainty in CO 2 

### emissions from waste incineration is estimated to be about
25.5% in annual emissions, 5% and 25% for activity data and emission factors respectively. As regards N

2 

### O and CH

4 

### emissions, the combined uncertainty is estimated to be about 100% and

20.6% in annual emissions.

The time series of activity data, distinguished in Municipal Solid Waste and other, is shown in

Table 8. 25; CO 2 

### emission trends for each type of waste category are reported in Table 8.26, both for plants without energy recovery, reported under 6C, and plants with energy recovery, reported under 1A4a. In Table 8.27 N 2 

### O and CH

4 

### emissions are summarized, includ ing those from open burning.

In the period 1990

- 2007, total CO 2 

### emissions have increased by 172.9%, but whereas emissions from plants with energy recovery have increased by nearly 383%, emissions from plants without energy recovery decreased by 49.7%. Whi le CO 2 

### emission trend reported in 6C is influenced by the amount of waste incinerated in plant without energy recovery, CH 4 

### and N

2 

### O emission trend are related to the open burning, as already reported above.

SUBSOURCE 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

MSW Production (Gg) 22,231 25,780 28,959 29,409 29,864 30,034 31,150 31,664 32,523 32,548

MSW Incinerated (%) 4.6% 5.6% 8.0% 8.8% 9.0% 9.5% 9.9% 10.2% 10.1% 10.1%

- in energy recovery plants 2.8% 4.6% 7.5% 8.3% 8.7% 9.3% 9.7% 10.0% 10.0% 10 .0%

MSW to incineration (Gg) 1,026 1,437 2,325 2,599 2,698 2,853 3,088 3,220 3,269 3,300

Industrial, Sanitary, Sewage Sludge
and Waste Oil to incineration (Gg) 691 773 737 930 883 1,134 1,637 1,746 1,797 1,744

Total Waste to incineration (6C and 1A4a) ( Gg) 1,716 2,209 3,062 3,528 3,581 3,987 4,725 4,966 5,066 5,043

Table 8.25 Waste incineration activity data, 1990

– 2007 (Gg)

### 205

SUBSOURCE 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Incineration of domestic or
municipal wastes (Gg) 115.47 72.64 4 7.30 43.63 31.04 18.21 15.61 15.02 6.62 8.35

Incineration of industrial wastes (except flaring) (Gg) 283.31 272.85 113.09 140.84 183.64 151.11 138.35 185.58 200.31 201.08

Incineration of hospital wastes (Gg) 135.46 136.12 40.36 37.11 29.86 45.78 44.76 43 .72 60.33 60.33

Incineration of waste oil (Gg) 2.66 1.41 0.82 0.67 0.43 0.65 0.51 0.36 0.24 0.41

Waste incineration (6C) (Gg) 537 483 202 222 245 216 199 245 267 270

Waste incineration reported under
1A4a (Gg) 569 835 1.331 1.598 1.546 1.923 2.634 2.765 2.804 2.747

Total waste incineration (Gg) 1,105 1,318 1,532 1,820 1,791 2,139 2,833 3,009 3,072 3,017

Table 8.26 CO

2 emissions from waste incineration (without and with energy recovery), 1990

– 2007 (Gg)

GAS/SUBSOURCE 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

N 2 O (Gg)

Waste incineration (6C) 0.28 0.42 0.36 0.39 0.38 0.38 0.47 0.42 0.40 0.39
MSW incineration reported under

1A4a 0.05 0.08 0.13 0.16 0.16 0.19 0.25 0.26 0.27 0.26

CH 4 (Gg)

Waste incineration (6C) 7. 65 12.91 11.94 12.98 12.59 12.85 16.20 14.14 13.47 12.89
MSW incineration reported under

1A4a 0.03 0.05 0.08 0.10 0.09 0.11 0.15 0.16 0.16 0.16

Table 8.27 N 2 O and CH 4 emissions from waste incineration, 1990

– 2007 (Gg)



### 8.4.4. Source

- specific QA/QC and v erification

For the incineration plants reported in the EPER register, verification on emissions has been

carried out. Moreover, the methodology, as well as the parameters used in the calculation of the emissions from incineration, have been presented and discussed at the 10 th 

### International Trade Fair on Material and Energy Recovery and Sustainable Development , Ecomondo 2006 (Ecomondo,
2006).

8.4.5. Source

- specific recalculations

For the year 2006, activity data from the incineration plants, which treat industrial waste, have been updated on the basis of new information published by ISPRA (APAT

- ONR, several years).

The main differences are related to CO 2 

### emissions and account for 14.3%.
In 2005, data has been update for one incineration pla nt that treats industrial waste.

8.4.6. Source

- specific planned improvements

As reported for solid waste disposal on land, the waste composition is very important to improve CO 2 

### emission factor on the basis of carbon content.

8.5 Other waste (6D)

8.5.1. Source categ

ory description

Under this source category CH 4 

### emissions from compost production have been reported. The amount of waste treated in composting plants has shown a great increase from 1990 to 2007 (from 363,319 tons to 7,488,147 tons).

### 206

Information on input waste to composting plants are published yearly by ISPRA since 1996, including data for 1993 and 1994 (ANPA, 1998; APAT

- ONR, several years), while for 1987 and 1995 only data on compost production are available (MATTM, several years; AUSITRA

Assoambiente, 1995); on the basis of this information the whole time series has been

reconstructed.

8.5.2. Methodological issues

The composting plants are classified in two different kinds: the plants that treat a selected waste (food, market, garden waste, sewage slu dge and other organic waste, mainly from the agro

- food industry); and the mechanical

- biological treatment plants, that treat the unselected waste to produce compost, refuse derived fuel (RDF), and a waste with selected characteristics for landfilling or in cinerating system. It is assumed that 100% of the input waste to the composting plants from selected waste is treated as compost, while in mechanical

- biological treatment plants 30% of the input waste is treated as compost on the basis of national studies and references (Favoino and Cortellini, 2001; Favoino and Girò, 2001). Since no methodology is provided by the IPCC for these emissions, literature data (Hogg, 2001) have been used for the emission factor, 0.029 g CH4 kg

- 1 

### treated waste, equivalent to comp ost production. NMVOC emissions have also been estimated: emission factor (51 g NMVOC kg

- 1 

### treated waste) is from international scientific literature too (Finn and Spencer, 1997).

In Table 8.28 CH 4 

### and NMVOC emissions are reported.

GAS 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CH 4 (Gg) 0.011 0.023 0.097 0.125 0.157 0.179 0.176 0.200 0.213 0.220

Compost production (6D)

NMVOC (Gg) 0.018 0.040 0.168 0.216 0.272 0.309 0.305 0.346 0.369 0.380

Compost production (6D) 0.011 0.023 0 .097 0.125 0.157 0.179 0.176 0.200 0.213 0.220

Table 8.28 CH

4 and NMVOC emissions from compost production, 1990

– 2007 (Gg)



### 8.5.3. Uncertainty and time

- series consistency

The uncertainty in CH 4 

### emissions from compost production is estimated to be about 100% in annual emissions, 10% and 100% concerning activity data and emission factors respectively.

8.5.4. Source

- specific QA/QC and verification

T he methodology, as well as the parameters used in the calculation of the emissions from compost production, h

ave been presented and discussed at the 10 th 

### International Trade Fair on Material and Energy Recovery and Sustainable Development , Ecomondo 2006 (Ecomondo,
2006).

8.5.5. Source

- specific recalculations

No recalculation has been done.

8.5.6. Source

- specif

ic planned improvements

No specific activities are planned.

### 207



## Chapter 9: RECALCULATIONS AND IMPROVEMENTS

9.1 Explanations and justifications for recalculations

To meet the requirements of transparency, consistency, comparability, completeness and

accura cy of the inventory, the entire time series from 1990 onwards is checked and revised every year during the annual compilation of the inventory. Measures to guarantee and improve these qualifications are undertaken and recalculations should be considered as a contribution to the overall improvement of the inventory. Recalculations are elaborated on account of changes in the methodologies used to carry out emission estimates, changes due to different allocation of emissions as compared to previous

submission

s, changes due to error corrections and in consideration of new available information. The complete revised CRFs from 1990 to 200 6 have been submitted as well as the CRF for the year 200 7 and recalculation tables of the CRF have been filled in. Explanator y information on the major recalculations between the 200 8 and 200 9 submissions for year 2006 are reported in

Table 9.1. The revisions that lead to relevant changes in GHG emissions are pointed out in the specific sectoral chapters and summarized in the fo llowing section 9.4.1.

9.2 Implications for emission levels

The time series reported in the 200 8 submission and the series reported this year (200 9 submission) are shown in Table 9.2 by gas and sector. Specifically, by gas, the comparison and

difference s in emission levels are reported in Table 9.3. Improvements in the calculation of emission estimates have led to a recalculation of the entire time series of the national inventory. Considering the total GHG emissions without LULUCF,

the emission levels of the base year show a minor decrease in comparison with t he last year submission (

- 0.11%) whereas emissions for the year 200 6 showed a decrease equal to 0.87 %

. Considering the national total with the LULUCF sector , the base year has increased by 2.53

, an d

the 200 6 emission levels in creased by 3.83 %. Detailed explanations of these recalculations are provided in the sectoral chapters. Changes in the base year levels are related

, primarly, to the energy sector due to an overall

revision of the emissions fro m transport; specifically, emissions from road transport have been revised on account of the application of the new version of COPERT 4 and emissions from civil aviation have been updated from the results of a recent study on the aviation sector. In the

in dustrial sector, revisions are due to an update of the emission factor for ferroalloys following the 2006 IPCC guidelines. The LULUCF sector was also affected by a revision due to an update of activity data for forest land and of grassland and cropland of carbon organic contents in soils ; in addition, losses in cropland remaining cropland have been added

. For 200 6 , changes affected the energy sector, due to the same methodological revis ion for road transport and civil aviation , as for 1990, a nd a reconside ration of the emissions from navigation due to a new national study . In the industrial sector, revisions are due to the update of the emission factor for ferroalloys following the 2006 IPCC guidelines and new information for cement and lime coming from the European Emissions Trading Scheme; there was also an update of F

- gas emissions due to new communication of semiconductor manufacturing industry. The LULUCF sector was also affected by a revision

, as for 1990, in terms of update of activity

data for forest land and of grassland and cropland of carbon soil organic contents and the

addition of losses in cropland remaining cropland. To a minor extent, modifications were due to the update of activity data in the agriculture and waste sectors.

### 208 Methods (2) Emission factors (2) Activity data (2)

Sectors/Totals CO2 The whole time series has been revised due to the application of the updated version of COPERT model

(COPERT 4) for road transport estimates. The whole time series has been revised on the basis of a new methodological

study for civil aviation. Figures of the navigation sector have

been revised from 1998 on the basis of a new methodological study revision of LPG emission factor and ferroalloys emission

factor

Sectors/Totals CO2 Losses in Cropland remaining Cropland (Living Biomass)

have been estimated Update of Grassland and

Cropland Soil Organic Content Update of AD - official forest

inventory data release

Sectors/Totals CH4 The whole time series has been revised due to the

application of the updated version of COPERT model

(COPERT 4) for road transport estimates. The whole time series has been revised on the basis of a new methodological

study for civil aviation. Figures of the navigation sector have

been revised from 1998 on the basis of a new methodological study update of emission factor for reheating furnaces in the iron

and steel sector

Sectors/Totals N2O The whole time series has been revised due to the

application of the updated version of COPERT model (COPERT 4) for road transport estimates. The whole time

series has been revised on the basis of a new methodological

study for civil aviation. Figures of the navigation sector have

been revised from 1998 on the basis of a new

methodological study Update of Grassland and

Cropland Soil Organic

Contents

Sectors/Totals HFCs Update of emissions communicated by

semiconductor manufacturing

industry

Sectors/Totals HFC-23 Update of emissions

communicated by semiconductor manufacturing

industry

Sectors/Totals HFC134a Update of HFC134a consumption communicated

by FIAT industry

Sectors/Totals PFCs Update of emissions

communicated by

semiconductor manufacturing industry

Sectors/Totals CF4 Update of emissions

communicated by semiconductor manufacturing

industry

Sectors/Totals C2F6 Update of emissions

communicated by semiconductor manufacturing

industry

Sectors/Totals C3F8 Update of emissions

communicated by semiconductor manufacturing

industry

Sectors/Totals c-C4F8 Update of emissions

communicated by semiconductor manufacturing

industry

Sectors/Totals SF6 Update of activity data for electrical equipment

1 Energy CO2 The whole time series has been revised due to the

application of the updated version of COPERT model

(COPERT 4) for road transport estimates. The whole time series has been revised on the basis of a new methodological

study for civil aviation. Figures of the navigation sector have

been revised from 1998 on the basis of a new methodological study update of residual oil, natural gas and steam coal emission

factor revision of refinery gas fuel

consumption in petroleum

refining already accounted for

in the chemical sector

1 Energy CH4 The whole time series has been revised due to the application of the updated version of COPERT model

(COPERT 4) for road transport estimates. The whole time

series has been revised on the basis of a new methodological study for civil aviation. Figures of the navigation sector have

been revised from 1998 on the basis of a new methodological study update of emission factor for

reheating furnaces in the iron

and steel sector revision of refinery gas fuel consumption in petroleum

refining already accounted for

in the chemical sector

1 Energy N2O The whole time series has been revised due to the

application of the updated version of COPERT model (COPERT 4) for road transport estimates. The whole time

series has been revised on the basis of a new methodological

study for civil aviation. Figures of the navigation sector have

been revised from 1998 on the basis of a new

methodological study revision of refinery gas fuel

consumption in petroleum refining already accounted for

in the chemical sector

1.AA Fuel Combustion -

Sectoral Approach CO2 The whole time series has been revised due to the

application of the updated version of COPERT model

(COPERT 4) for road transport estimates. The whole time series has been revised on the basis of a new methodological

study for civil aviation. Figures of the navigation sector have

been revised from 1998 on the basis of a new methodological study update of residual oil, natural gas and steam coal emission

factor revision of refinery gas fuel

consumption in petroleum

refining already accounted for

in the chemical sector

1.AA Fuel Combustion -

Sectoral Approach CH4 The whole time series has been revised due to the

application of the updated version of COPERT model

(COPERT 4) for road transport estimates. The whole time series has been revised on the basis of a new methodological

study for civil aviation. Figures of the navigation sector have

been revised from 1998 on the basis of a new methodological study update of emission factor for reheating furnaces in the iron

and steel sector revision of refinery gas fuel

consumption in petroleum

refining already accounted for

in the chemical sector

1.AA Fuel Combustion -

Sectoral Approach N2O The whole time series has been revised due to the

application of the updated version of COPERT model (COPERT 4) for road transport estimates. The whole time

series has been revised on the basis of a new methodological

study for civil aviation. Figures of the navigation sector have

been revised from 1998 on the basis of a new

methodological study revision of refinery gas fuel

consumption in petroleum refining already accounted for

in the chemical sector

1.AA.1 Energy Industries CO2 update of residual oil, natural gas and steam coal emission

factor revision of refinery gas fuel

consumption in petroleum

refining already accounted for

in the chemical sector

1.AA.1 Energy Industries CH4 revision of refinery gas fuel

consumption in petroleum refining already accounted for

in the chemical sector

1.AA.1 Energy Industries N2O revision of refinery gas fuel

consumption in petroleum

refining already accounted for

in the chemical sector

1.AA.2 Manufacturing

Industries and

Construction CO2 update of fuel oil, natural gas

and steam coal emission factors update of cement

production

1.AA.2 Manufacturing

Industries and

Construction CH4 update of emission factor for

reheating furnaces in the iron

and steel sector update of cement production

1.AA.2 Manufacturing

Industries and

Construction N2O update of cement production

1.AA.3 Transport CO2 The whole time series has been revised due to the

application of the updated version of COPERT model

(COPERT 4) for road transport estimates. The whole time series has been revised on the basis of a new methodological

study for civil aviation. Figures of the navigation sector have

been revised from 1998 on the basis of a new methodological study

1.AA.3 Transport CH4 The whole time series has been revised due to the

application of the updated version of COPERT model

(COPERT 4) for road transport estimates. The whole time

series has been revised on the basis of a new methodological

study for civil aviation. Figures of the navigation sector have

been revised from 1998 on the basis of a new

methodological study

1.AA.3 Transport N2O The whole time series has been revised due to the

application of the updated version of COPERT model

(COPERT 4) for road transport estimates. The whole time series has been revised on the basis of a new methodological

study for civil aviation. Figures of the navigation sector have

been revised from 1998 on the basis of a new methodological study

1.AA.4 Other Sectors CO2 revision of residual oil, natural gas and coal emission factors update of industrial and urban

solid waste

1.AA.4 Other Sectors CH4 update of industrial and urban

solid waste

1.AA.4 Other Sectors N2O update of industrial and urban

solid waste

1.B Fugitive Emissions

from Fuels CH4 update of emission factor for

minor gas distributors update of activity data (distribution among different

sources of oil production and gas consumption)

1.B.2 Oil and Natural Gas CH4 update of emission factor for minor gas distributors update of activity data

(distribution among different sources of oil production and

gas consumption)

1.C1 International Bunkers CO2 revision of the whole time series for aviation and maritime

due to a new methodological study

1.C1 International Bunkers CH4 revision of the whole time series for aviation and maritime

due to a new methodological study

1.C1 International Bunkers N2O revision of the whole time series for aviation and maritime due to a new methodological study

1.C3 CO2 Emissions from

Biomass CO2 update of urban solid waste in

residential combustion Specify the sector and

source/sink category (1) where

changes in estimates have

occurred: GHG RECALCULATION DUE TO

CHANGES IN:

Addition/removal/

reallocation of

source/sink categories Other changes in data

(e.g. statistical or

editorial changes, correction of errors)

### 209 2 Industrial Processes CO2 revision of the emission factor
according to 2006 IPCC
guidelines for ferroalloys
production update of activity data for pig
iron, steel and ferroalloys
production

2 Industrial Processes CH4 update of steel and pig iron
production

2 Industrial Processes HFCs Update of emissions
communicated by
semiconductor manufacturing
industry

2 Industrial Processes HFC-23 Update of emissions
communicated by
semiconductor manufacturing
industry

2 Industrial Processes HFC134a Update of HFC134a
consumption communicated
by FIAT industry

2 Industrial Processes PFCs Update of emissions
communicated by
semiconductor manufacturing
industry

2 Industrial Processes CF4 Update of emissions
communicated by
semiconductor manufacturing
industry

2 Industrial Processes C2F6 Update of emissions
communicated by
semiconductor manufacturing
industry

2 Industrial Processes C3F8 Update of emissions
communicated by
semiconductor manufacturing
industry

2 Industrial Processes c-C4F8 Update of emissions

communicated by
semiconductor manufacturing
industry

2 Industrial Processes SF6 Update of activity data for
electrical equipment

2.A Mineral Products CO2 changes in EF due to use of

data collected from the
European emissions trading

scheme for cement and lime

production

2.C Metal Production CO2 revision of the emission factor
according to 2006 IPCC
guidelines for ferroalloys
production. change in EF for
pig iron production update of steel, pig iron and
ferroalloys production

2.C Metal Production Recovery

/CO2 HFC emissions have

been added from 2007

2.C Metal Production CH4 update of steel and pig iron
production

2.C Metal Production Recovery

/CH4 HFC emissions have

been added from 2007

2.C Metal Production N2O HFC emissions have

been added from 2007

2.C Metal Production Recovery

/N2O HFC emissions have

been added from 2007

2.C Metal Production HFCs HFC emissions have

been added from 2007

2.C Metal Production HFCs HFC emissions have

been added from 2007

2.C Metal Production PFCs HFC emissions have

been added from 2007

2.C Metal Production SF6 HFC emissions have

been added from 2007

2.F Consumption of

Halocarbons and SF6 HFCs Update of emissions
communicated by
semiconductor manufacturing
industry

2.F Consumption of

Halocarbons and SF6 HFCs Update of emissions
communicated by
semiconductor manufacturing

industry

2.F Consumption of

Halocarbons and SF6 HFC-23 Update of emissions
communicated by
semiconductor manufacturing
industry

2.F Consumption of

Halocarbons and SF6 HFC134a Update of HFC134a
consumption communicated
by FIAT industry

2.F Consumption of

Halocarbons and SF6 HFC134a Update of HFC134a
consumption communicated
by FIAT industry

2.F Consumption of

Halocarbons and SF6 PFCs Update of emissions
communicated by
semiconductor manufacturing
industry

2.F Consumption of

Halocarbons and SF6 PFCs Update of emissions
communicated by
semiconductor manufacturing
industry

2.F Consumption of

Halocarbons and SF6 CF4 Update of emissions
communicated by
semiconductor manufacturing
industry

2.F Consumption of

Halocarbons and SF6 CF4 Update of emissions

communicated by
semiconductor manufacturing
industry

2.F Consumption of

Halocarbons and SF6 C2F6 Update of emissions
communicated by
semiconductor manufacturing
industry

2.F Consumption of

Halocarbons and SF6 C2F6 Update of emissions
communicated by

semiconductor manufacturing
industry

2.F Consumption of

Halocarbons and SF6 C3F8 Update of emissions
communicated by
semiconductor manufacturing
industry

2.F Consumption of

Halocarbons and SF6 C3F8 Update of emissions
communicated by
semiconductor manufacturing

industry

2.F Consumption of

Halocarbons and SF6 c-C4F8 Update of emissions
communicated by
semiconductor manufacturing
industry

2.F Consumption of

Halocarbons and SF6 c-C4F8 Update of emissions
communicated by
semiconductor manufacturing
industry

2.F Consumption of

Halocarbons and SF6 SF6 Update of emissions
communicated by
semiconductor manufacturing
industry Update of activity data for
electrical equipment

2.F Consumption of

Halocarbons and SF6 SF6 Update of emissions
communicated by
semiconductor manufacturing
industry Update of activity data for
electrical equipment

3 Solvent and Other

Product Use CO2 Update of emission factor of

domestic solvent use Update of different activity

data

4 Agriculture CH4 Update days of cultivation by
variety of rice/Update
information on solid/liquid
production Update rice production

4 Agriculture N2O update spreading EF in the

NH3 national emissioni
inventory

4.B Manure Management CH4 Update information on
solid/liquid production

4.B Manure Management N2O Update information on
solid/liquid production

4.C Rice Cultivation CH4 update days of cultivation by
variety of rice Update rice production

4.D Agricultural Soils N2O update spreading EF in the

NH3 national emissioni
inventory

4.F Field Burning of
Agricultural Residues CH4 Update rice production

4.F Field Burning of
Agricultural Residues N2O Update rice production

5 LULUCF CO2 Losses in Cropland remaining Cropland (Living Biomass)

have been estimated Update of Grassland and
Cropland Soil Organic Content Update of AD - official forest
inventory data release

5 LULUCF CH4 Update of activity data

(burned area)

5 LULUCF N2O Update of activity data

(burned area)

5.A Forest Land CO2 Losses in Cropland remaining Cropland (Living Biomass)

have been estimated Update of Grassland and
Cropland Soil Organic Content Update of AD - official forest
inventory data release

5.A Forest Land CH4 Update of activity data

(burned area)

5.A Forest Land N2O Update of activity data

(burned area)

5.B Cropland CO2 Update of activity data

5.B Cropland N2O Update of Grassland and
Cropland Soil Organic

Contents

5.E Settlements CO2 Update of Grassland and
Cropland Soil Organic

Contents

6 Waste CO2 Update activity data from
incineration plants

6 Waste CH4 Update activity data from
incineration plants and update
of activity data from leather
industry, food and beverages,
organic chemicals and

domestic (wastewater) and
update of rice production

6 Waste N2O Update activity data from
incineration plants and update
of activity data from leather
industry, food and beverages
and organic chemicals
(wastewater) and update of
rice production

6.B Wastewater Handling CH4 Update of activity data from
leather industry, food and
beverages, organic chemicals

and domestic wastewater

6.B Wastewater Handling N2O Update of activity data from
leather industry, food and
beverages, organic chemicals

6.C Waste Incineration CO2 Update of activity data from
incineration plants

6.C Waste Incineration CH4 Update of activity data from
incineration plants and rice
production

6.C Waste Incineration N2O Update of activity data from
incineration plants and rice
production Table 9.1 E

xplanations of the main recalculations in the 200 9 submission (year 2006)

### 210 TABLE 10 EMISSION TRENDS (SUMMARY) Italy (Sheet 5 of 5) 2007

Base year (

1990 ) 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

CO2 emissions including net CO2 from

LULUCF 367,037 348,232 350,168 361,573 338,908 359,585 346,789 362,122 377,855 378,212 383,389 375,767 374,907 359,145 397,091 394,682 395,617 404,176

CO2 emissions excluding net CO2 from

LULUCF 434,688 433,831 433,418 427,116 420,095 445,401 438,910 443,112 454,389 459,592 462,715 468,439 470,590 486,014 488,970 490,056 485,754 475,302

CH4 emissions including CH4 from LULUCF 41,882 43,091 42,498 42,889 43,406 44,185 44,199 44,567 44,290 44,257 44,284 42,978 41,870 41,143 39,873 39,679 38,075 38,414

CH4 emissions excluding CH4 from LULUCF 41,739 43,055 42,437 42,738 43,345 44,158 44,177 44,493 44,204 44,214 44,197 42,922 41,839 41,078 39,838 39,645 38,044 38,217
N2O emissions including N2O from LULUCF 37,415 38,430 37,888 38,535 37,875 38,563 38,161 39,386 39,405 40,101 39,781 39,794 39,056 38,559 39,645 37,902 32,842 31,856

N2O emissions excluding N2O from LULUCF 37,400 38,427 37,882 38,423 37,624 38,364 38,158 39,330 39,006 39,542 39,772 39,788 39,053 38,552 39,642 37,899 32,540 31,836

HFCs 351 355 359 355 482 671 450 756 1,182 1,524 1,986 2,550 3,100 3,796 4,515 5,267 5,956 6,701

PFCs 1,808 1,452 850 707 477 491 243 252 270 258 346 451 424 498 348 353 282 288

SF6 333 356 358 370 416 601 683 729 605 405 493 795 740 468 502 465 406 428

Total (including LULUCF) 448,825 431,917 432,120 444,430 421,563 444,096 430,525 447,812 463,608 464,756 470,279 462,335 460,096 443,608 481,975 478,349 473,178 481,862
Total (excluding LULUCF) 516,318 517,476 515,303 509,710 502,439 529,686 522,622 528,671 539,655 545,535 549,509 554,946 555,746 570,406 573,815 573,685 562,982 552,771

Base year (

1990 ) 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

1. Energy 418,945 418,508 417,774 414,371 408,283 431,961 427,889 432,025 443,395 448,402 450,722 455,290 457,264 471,623 473,756 474,506 469,586 458,673

2. Industrial Processes 36,467 36,131 35,532 32,697 31,363 34,530 31,480 31,969 32,422 32,862 34,903 36,946 37,040 38,232 40,522 40,367 35,916 36,296

3. Solvent and Other Product Use 2,394 2,334 2,334 2,293 2,210 2,180 2,279 2,280 2,367 2,348 2,285 2,211 2,219 2,167 2,144 2,139 2,147 2,133

4. Agriculture 40,576 41,371 40,862 41,163 40,641 40,349 40,097 41,150 40,418 40,795 39,940 38,954 38,250 38,102 37,917 37,242 36,627 37,210
5. Land Use, Land-Use Change and Forestry(5) -67,493 -85,559 -83,183 -65,280 -80,876 -85,590 -92,097 -80,859 -76,048 -80,779 -79,230 -92,611 -95,649 -126,798 -91,840 -95,336 -89,804 -70,910

6. Waste 17,936 19,132 18,800 19,187 19,942 20,666 20,876 21,247 21,054 21,126 21,659 21,545 20,973 20,283 19,475 19,432 18,707 18,459

7. Other NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
Total (including LULUCF)(5) 448,825 431,917 432,120 444,430 421,563 444,096 430,525 447,812 463,608 464,756 470,279 462,335 460,096 443,608 481,975 478,349 473,178 481,862

Italy

2006

Base year (

1990 ) 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

CO2 emissions including net CO2 from

LULUCF 355,494 332,668 336,172 344,954 322,441 342,202 332,898 344,400 358,867 356,363 367,151 361,413 359,381 361,446 378,435 378,332 375,678

CO2 emissions excluding net CO2 from

LULUCF 434,783 434,201 433,842 427,712 420,928 445,845 439,328 443,568 454,875 459,911 464,276 470,178 472,395 487,837 491,055 491,834 488,039

CH4 emissions including CH4 from LULUCF 41,757 42,963 42,370 42,752 43,327 44,145 44,199 44,590 44,309 44,349 44,378 42,986 41,867 41,151 39,963 39,628 38,186
CH4 emissions excluding CH4 from LULUCF 41,614 42,926 42,310 42,601 43,266 44,118 44,177 44,516 44,222 44,307 44,291 42,931 41,836 41,086 39,928 39,594 38,158

N2O emissions including N2O from LULUCF 38,024 39,002 38,443 39,010 38,168 38,814 38,547 39,824 39,970 40,741 40,891 41,080 40,702 40,409 41,703 40,432 35,245
N2O emissions excluding N2O from LULUCF 38,009 38,998 38,437 38,955 38,062 38,731 38,545 39,797 39,801 40,509 40,882 41,075 40,699 40,403 41,700 40,429 35,120

HFCs 351 355 359 355 482 671 450 756 1,182 1,524 1,986 2,550 3,100 3,796 4,515 5,267 5,932

PFCs 1,808 1,452 850 707 477 491 243 252 270 258 346 451 424 498 350 361 282

SF6 333 356 358 370 416 601 683 729 605 405 493 795 738 465 492 460 390

Total (including LULUCF) 437,766 416,796 418,552 428,149 405,311 426,925 417,021 430,551 445,203 443,639 455,244 449,276 446,211 447,764 465,458 464,480 455,713

Total (excluding LULUCF) 516,898 518,289 516,155 510,701 503,630 530,457 523,426 529,617 540,956 546,914 552,274 557,980 559,191 574,084 578,039 577,945 567,922

Base year (

1990 ) 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

1. Energy 419,446 419,285 418,585 415,321 409,437 432,672 428,617 432,907 444,627 449,754 453,425 458,276 460,747 475,373 477,884 478,017 473,681

2. Industrial Processes 36,544 36,165 35,572 32,736 31,399 34,590 31,556 32,032 32,489 32,889 34,965 36,993 37,002 38,162 40,641 41,119 36,783

3. Solvent and Other Product Use 2,394 2,334 2,334 2,293 2,210 2,180 2,279 2,280 2,367 2,348 2,285 2,211 2,219 2,167 2,144 2,139 2,148
4. Agriculture 40,578 41,373 40,864 41,164 40,642 40,350 40,098 41,151 40,419 40,796 39,940 38,954 38,250 38,100 37,895 37,239 36,642
5. Land Use, Land-Use Change and Forestry(5) -79,132 -101,493 -97,603 -82,552 -98,319 -103,532 -106,405 -99,066 -95,753 -103,275 -97,030 -108,704 -112,979 -126,320 -112,582 -113,465 -112,209

6. Waste 17,936 19,132 18,800 19,187 19,942 20,666 20,876 21,247 21,054 21,126 21,659 21,545 20,973 20,283 19,475 19,431 18,668

7. Other NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Total (including LULUCF)(5) 437,766 416,796 418,552 428,149 405,311 426,925 417,021 430,551 445,203 443,639 455,244 449,276 446,211 447,764 465,458 464,480 455,713 GREENHOUSE GAS SOURCE AND SINK

CATEGORIES GREENHOUSE GAS EMISSIONS

GREENHOUSE GAS SOURCE AND SINK

CATEGORIES

CO2 equivalent (Gg)

GREENHOUSE GAS EMISSIONS CO2 equivalent (Gg)

CO2 equivalent (Gg) CO2 equivalent (Gg)

Table 9.2 Comparison between the 200 8 and 200 9 submitted time series by gas and sector

### 211 Base

year 1990 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Net CO

2 emissions/removals
(Gg CO 2

- eq.) 2007

subm

355,494 342,202 332,898 344,400 358,867 356,363 367,151 361,413 359,381 361,446 378,435 378,332 375,678

2008

subm 367,037 359,585 346,789 362,122 377,855 378,212 383,389 375,767 374,907 359,145 3 97,091 394,682 395,617 Difference 3.25% 5.08% 4.17% 5.15% 5.29% 6.13% 4.42% 3.97% 4.32%

- 0.64% 4.93% 4.32% 5.31%

CO 2 emissions
(without LULUCF) (Gg CO2

- eq.) 2007

subm
434,783 445,845 439,328 443,568 454,875 459,911 464,276 470,178 472,395 487,837 491,0 55 491,834 488,039

2008

subm 434,688 445,401 438,910 443,112 454,389 459,592 462,715 468,439 470,590 486,014 488,970 490,056 485,754
Difference

- 0.02%

- 0.10%

- 0.10%

- 0.10%

- 0.11%

- 0.07%

- 0.34%

- 0.37%

- 0.38%

- 0.37%

- 0.42%

- 0.36%

- 0.47%

CH 4 emissions
( Gg CO 2 - eq.) 2007

subm 41,757 44,145 44,199 44,590 44,309 44,349 44,378 42,986 41,867 41,151 39,963 39,628 38,186

2008

subm 41,882 44,185 44,199 44,567 44,290 44,257 44,284 42,978 41,870 41,143 39,873 39,679 38,075 Difference 0.30% 0.09% 0.00%

- 0.05%

- 0.04%

- 0.21%

- 0.21%

- 0.02% 0.01%

- 0.02%

- 0.23% 0.13%

- 0.29%

CH 4 emissions (without LULUCF)
(Gg CO 2 - eq.) 2007

subm

41,614 44,118 44,177 44,516 44,222 44,307 44,291 42,931 41,836 41,086 39,928 39,594 38,158

2008

subm 41,739 44,158 44,177 44,493 44,204 44 ,214 44,197 42,922 41,839 41,078 39,838 39,645 38,044
Difference 0.30% 0.09% 0.00%

- 0.05%

- 0.04%

- 0.21%

- 0.21%

- 0.02% 0.01%

- 0.02%

- 0.23% 0.13%

- 0.30%

N 2 O emissions
(Gg CO 2 - eq.) 2007

subm 38,024 38,814 38,547 39,824 39,970 40,741 40,891 41,080 40,702 4 0,409 41,703 40,432 35,245

2008

subm 37,415 38,563 38,161 39,386 39,405 40,101 39,781 39,794 39,056 38,559 39,645 37,902 32,842
Difference

- 1.60%

- 0.65%

- 1.00%

- 1.10%

- 1.41%

- 1.57%

- 2.71%

- 3.13%

- 4.04%

- 4.58%

- 4.93%

- 6.26%

- 6.82%

N 2 O emissions
(witho ut LULUCF)
(Gg CO 2 - eq.) 2007

subm
38,009 38,731 38,545 39,797 39,801 40,509 40,882 41,075 40,699 40,403 41,700 40,429 35,120

2008

subm 37,400 38,364 38,158 39,330 39,006 39,542 39,772 39,788 39,053 38,552 39,642 37,899 32,540
Difference

- 1.60%

- 0.95%

- 1.00%

- 1.17%

- 2.00%

- 2.39%

- 2.71%

- 3.13%

- 4.04%

- 4.58%

- 4.93%

- 6.26%

- 7.35%

HFCs (Gg CO

2 - eq.) 2007

subm 351 671 450 756 1,182 1,524 1,986 2,550 3,100 3,796 4,515 5,267 5,932

2008

subm 351 671 450 756 1,182 1,524 1,986 2,550 3,100 3,796 4,515 5,267 5,95 6
Difference 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.40% PFCs (Gg CO

2 - eq.) 2007

subm 1,808 491 243 252 270 258 346 451 424 498 350 361 282

2008

subm 1,808 491 243 252 270 258 346 451 424 498 348 353 282 Difference 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%

- 0.60%

- 2.38%

- 0.04%

SF 6 (Gg CO 2 - eq.) 2007

subm 333 601 683 729 605 405 493 795 738 465 492 460 390

2008

subm 333 601 683 729 605 405 493 795 740 468 502 465 406
Difference 0.00% 0.00% 0.00 % 0.00% 0.00% 0.00% 0.00% 0.05% 0.28% 0.62% 2.15% 1.13% 4.11%

Total
(with LULUCF)
(Gg CO2

- eq.) 2007

subm
437,766 426,925 417,021 430,551 445,203 443,639 455,244 449,276 446,211 447,764 465,458 464,480 455,713

2008

subm 448,825 444,096 430,525 447,812 463,608 464,756 470,279 462,335 460,096 443,608 481,975 478,349 473,178
Difference 2.53% 4.02% 3.24% 4.01% 4.13% 4.76% 3.30% 2.91% 3.11%

- 0.93% 3.55% 2.99% 3.83%

Total
(without LULUCF)
(Gg CO2

- eq.) 2007

subm
516,898 530,457 523,426 529,617 540,956 54 6,914 552,274 557,980 559,191 574,084 578,039 577,945 567,922

2008

subm 516,318 529,686 522,622 528,671 539,655 545,535 549,509 554,946 555,746 570,406 573,815 573,685 562,982 Difference

- 0.11%

- 0.15%

- 0.15%

- 0.18%

- 0.24%

- 0.25%

- 0.50%

- 0.54%

- 0.62%

- 0.64%

- 0.73%

- 0.74%

- 0.87%
Table 9.3 Differences in time series between the 200 9 and 200 8 submissions due to recalculations



### 9.3 Implications for emission trends, including time series consistency

Recalculations account for an improvement in the overall emission trend and consistency in time

series.

### 212

In comparison with the time series submitted in 200 8 , emission levels of the base year, total

emissions in CO 2 

### equivalent without LULUCF, slightly changed (- 0.11%) due to a revision in the energy and industr ial sectors as previously described

. If considering emission levels with LULUCF, an increase by 2.53 % is observed between the 200 8

and 200 9 total figures in CO 2 

### equivalent, mainly due to the update of land use areas. For the year 200 6 , changes affected n egatively CO 2 

### , CH 4 

### and N

2 

### O emissions (- 0. 47%,

- 0.30 %,

- 7.35%, respectively). The trend ‘base year

- year 200 6 ’ does not show a significant change from the previous to this year

submission. Improvements in methodologies used to compile the inventory guarant ee better estimates and minor changes from one year to another for the entire time series.

9.4 Recalculations, response to the review process and planned improvements

This chapter summarises the recalculations and improvements made to the Italian GHG i nventory

since the 200 8 submission. In addition to a new year, the inventory is updated annually by a revision of the existing activity data and emission factors in order to include new information available; the update could also

reflect the revision of methodologies. Revisions always apply to the whole time series. The inventory may also be expanded by including categories not previously estimated if sufficient information on activity data and suitable emission factors have been identified and collected

.

9.4.1 Recalculations

The key differences that have occurred in emission estimates since the last year submission are reported in Table 9.2 and Table 9.3. A more detailed recalculation for the year 200 6 , Table 8(a) of the CRF (year 2006), is reported in Table 9.4. Besides the usual updating of activity data, recalculations may be distinguished in methodological changes, source allocation and error corrections. All sectors were involved in methodological changes. Specifically:
Energy. Major recalcula tions occurred in this sector, especially in transport concerning road as well

as aviation and maritime sectors. The whole time series of road transport emissions have been

recalculated using

the updated version of the model to estimate emissions , COPERT 4 . Aviation emissions have also been recalculated for the whole time series as a consequence of a specific sectoral study so as maritime emissions that have been updated from 1998 . In addition, CO 2 

### emission factors for natural gas , coal and fuel oil were re vised from 2006, 2005 and 1999, respectively, on account of additional information collected on amount of imported fuels and their specific chemical composition.

Industrial sector

. Recalculations are due to the update of the emission factor for ferroalloys

. In addition, new information from the European Emissions Trading Scheme and sectoral industry was used to update emission factors for cement and lime and F

- gas emissions of semiconductor manufacturing industry. Solvent and other product use sector . A min or update of activity data and a revision of emission

factor for domestic use occurred in this sector

. Agriculture . Besides the update of different basic data, revision concerned some parameters used to

calculate emissions for manure management, rice produ ction and agricultural soils

. LULUCF . The main changes concerned the update of activity data, related to land use areas, and the estimation of losses in cropland remaining cropland.

Waste

. Minor r evisions concerned the update of activity data in wastewater handling and

incineration sectors.

### 213

9.4.2 Response to the UNFCCC review process

In 200 8 , the Italian GHG inventory was subject to the centralised review of the 2007 and 2008 Inventory submissions

. Following the recommendations of the review processes d ifferent improvements have been carried

out. The main improvement s regard ed the update of the method for estimating emissions from transportation. Specifically, the new version of the programme to estimate emissions from road transport was applied to revi se all the time series, an update of the method for estimating the fuel split for national and international aviation was carried out and a new study was finalised for the

maritime sector.

The assumptions and rationale underlying the uncertainty analysis in the Italian inventory have been extensively detailed . Exhaustive results of uncertainty and key category analysis for the base year have been reported.

Verification and QA/ QC procedures were explained more in detail for the energy sector, especially for those sectors mostly affected by recalculations and a further improvement is planned for the

next submission

. An independent review of the complete inventory is still under consideration but sectoral emission s
have been

actually presented different in stitutions, local agencies and industrial sectors and methodologies shared, leading in some cases to a revision of the estimates before submission.

The description of country specific methods and the rationale behind the choice of emission factors,

activ ity data and other related parameters should have improved the transparency of the present

NIR.

9.4.3 Planned improvements (e.g., institutional arrangements, inventory preparation)

The main institutional and legal arrangements required under the Kyoto P rotocol have been finalized except for the institution of a basic independent review of the inventory before its submission which is still under consideration. In addition, progress will regard collection and assessment of supplementary information related to activities under article 3, paragraph 3 and 4, of the Kyoto Protocol required for future reporting. General priority will concern the improvement of the transparency in the NIR, especially a further revision of the energy chapter.

Other s ector specifi

c improvements are identified in the relevant chapters and specified in the 200 9 QA/QC plan; they can be summarized in the following.

For the energy and industrial sectors, a major progress will regard the finalisation of a unique

database where informatio n collected in the framework of different directives, Large Combustion
Plant, EPER

- PRTR and Emissions Trading, are gathered together thus highlighting the main discrepancies in information and detecting potential errors. For the agriculture and waste sect ors, improvements will be related to the availability of new information on emission factors, activity data as well as parameters necessary to carry out the estimates; specifically, a study on the best available technologies used in agriculture practises a nd availability of information on waste composition and other parameters following the entering into force of the European landfill directive.
For the LULUCF; a ctivities planned in the framework of the National Registry for Forest Carbon Sinks should pro vide data to improve estimate of emissions by biomass burning and the final results

### 214

of the INFC data related to the soils survey will definitely constitute a robust database for forest fires, allowing refined estimates and lower related uncertainty

. Fina lly, efforts will be further addressed to the comparison between local inventories and national inventory. Further analyses will concern the collection of statistical data and information to estimate uncertainty in specific sectors by implementing the Tie r 2 approach of the IPCC Good Practice

Guidance.

TABLE 8(a) RECALCULATION - RECALCULATED DATA Recalculated year: Inventory 2006

Submission 2009 v1.3

ITALY

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LULUCF

375,677.88 395,617.40 19,939.52 5.31 3.54 4.21 38,185.63 38,074.79 -110.84 -0.29 -0.02 -0.02 35,245.20 32,841.82 -2,403.38 -6.82 -0.43 -0.51
1. Energy 458,983.83 457,573.05 -1,410.78 -0.31 -0.25 -0.30 6,639.76 6,510.52 -129.24 -1.95 -0.02 -0.03 8,057.44 5,502.41 -2,555.04 -31.71 -0.45 -0.54

1.A. Fuel Combustion Activities 456,795.15 455,384.37 -1,410.78 -0.31 -0.25 -0.30 1,406.65 1,317.56 -89.09 -6.33 -0.02 -0.02 8,056.07 5,501.03 -2,555.04 -31.72 -0.45 -0.54

1.A.1. Energy Industries 159,108.26 159,178.95 70.69 0.04 0.01 0.01 135.11 135.00 -0.11 -0.08 0.00 0.00 575.17 571.85 -3.32 -0.58 0.00 0.00

1.A.2. Manufacturing Industries and Construction 82,083.35 82,106.25 22.90 0.03 0.00 0.00 130.81 130.72 -0.09 -0.07 0.00 0.00 1,564.16 1,564.64 0.47 0.03 0.00 0.00

1.A.3. Transport 128,531.09 127,151.03 -1,380.07 -1.07 -0.25 -0.29 561.56 472.75 -88.81 -15.81 -0.02 -0.02 4,104.94 1,554.70 -2,550.24 -62.13 -0.45 -0.54

1.A.4. Other Sectors 86,090.83 85,966.53 -124.30 -0.14 -0.02 -0.03 576.49 576.41 -0.08 -0.01 0.00 0.00 1,737.61 1,735.66 -1.95 -0.11 0.00 0.00

1.A.5. Other 981.61 981.61 2.67 2.67 74.19 74.19

1.B. Fugitive Emissions from Fuels 2,188.68 2,188.68 5,233.11 5,192.96 -40.15 -0.77 -0.01 -0.01 1.38 1.38

1.B.1. Solid fuel NA NA 53.79 53.79 NA NA

1.B.2. Oil and Natural Gas 2,188.68 2,188.68 5,179.32 5,139.17 -40.15 -0.78 -0.01 -0.01 1.38 1.38

2. Industrial Processes 27,465.77 26,559.08 -906.69 -3.30 -0.16 -0.19 65.85 65.86 0.02 0.02 0.00 0.00 2,646.53 2,646.53

2.A. Mineral Products 24,048.00 23,219.30 -828.70 -3.45 -0.15 -0.18 NA NA NA NA

2.B. Chemical Industry 1,307.98 1,307.98 6.79 6.79 2,646.53 2,646.53

2.C. Metal Production 2,109.79 2,031.80 -77.99 -3.70 -0.01 -0.02 59.06 59.07 0.02 0.03 0.00 0.00 NA NA,NO

2.D. Other Production NA NA

2.G. Other NA NA NA NA NA NA

3. Solvent and Other Product Use 1,355.66 1,354.03 -1.62 -0.12 0.00 0.00 792.52 792.52
4. Agriculture 15,137.27 15,149.19 11.92 0.08 0.00 0.00 21,504.86 21,478.23 -26.63 -0.12 0.00 -0.01

4.A. Enteric Fermentation 10,628.73 10,628.73

4.B. Manure Management 3,029.06 3,031.15 2.09 0.07 0.00 0.00 3,620.87 3,618.16 -2.71 -0.07 0.00 0.00

4.C. Rice Cultivation 1,466.86 1,476.63 9.77 0.67 0.00 0.00

4.D. Agricultural Soils (4) NA NA 17,880.03 17,856.09 -23.94 -0.13 0.00 -0.01

4.E. Prescribed Burning of Savannas NO NO NO NO

4.F. Field Burning of Agricultural Residues 12.62 12.68 0.06 0.49 0.00 0.00 3.96 3.99 0.02 0.61 0.00 0.00

4.G. Other NA NA NA NA

5. Land Use, Land-Use Change and Forestry (net) (5) -112,361.49 -90,136.26 22,225.23 -19.78 4.70 27.47 30.62 3.1470401 11.457108 0.000665 125.02 301.62 176.59 141.25 0.04

5.A. Forest Land -94,883.76 -84,194.42 10,689.34 -11.27 2.26 27.47 30.62 3.1470401 11.457108 0.000665 2.79 3.11 0.32 11.46 0.00

5.B. Cropland -18,758.01 -8,086.51 10,671.51 -56.89 2.26 NO NO 122.24 298.509882 176.27 144.21 0.04

5.C. Grassland NO NO NO NO NO NO

5.D. Wetlands NO NO NO NO NO NO

5.E. Settlements 1,280.29 2,144.67 864.38 67.51 0.18 NO NO NO NO

5.F. Other Land NO NO NO NO NO NO

5.G. Other NA NA NA NA NA NA

6. Waste 234.11 267.49 33.38 14.26 0.01 0.01 16,315.29 16,318.61 3.32 0.02 0.00 0.00 2,118.82 2,120.52 1.69 0.08 0.00 0.00

6.A. Solid Waste Disposal on Land NA,NO NA,NO 13,637.88 13,637.88

6.B. Waste-water Handling 2,390.45 2,393.47 3.02 0.13 0.00 0.00 1,996.26 1,996.26 0.00 0.00 0.00 0.00

6.C. Waste Incineration 234.11 267.49 33.38 14.26 0.01 0.01 282.49 282.78 0.30 0.11 0.00 0.00 122.56 124.26 1.70 1.38 0.00 0.00

6.D. Other NA NA 4.47 4.47 NA NA

7. Other (as specified in Summary 1.A) NA NA NA NA NA NA

Memo Items:

International Bunkers 15,764.40 17,274.95 1,510.55 9.58 0.27 0.32 20.19 18.52 -1.67 -8.29 0.00 0.00 99.40 128.32 28.92 29.10 0.01 0.01
Multilateral Operations NE NE NE NE NE NE

CO 2 Emissions from Biomass 14,994.38 14,993.25 -1.13 -0.01 0.00 0.00

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Total Actual Emissions 5,932.24 5,956.20 23.97 0.40 0.00 0.01 282.41 282.30 -0.11 -0.04 0.00 0.00 389.84 405.87 16.04 4.11 0.00 0.00

2.C.3. Aluminium Production 154.36 154.36

2.E. Production of Halocarbons and SF 6 20.83 20.83 NA,NO NA,NO NA,NO NA,NO

2.F. Consumption of Halocarbons and SF 6 5,911.41 5,935.37 23.97 0.41 0.00 0.01 128.05 127.94 -0.11 -0.09 0.00 0.00 328.61 344.64 16.04 4.88 0.00 0.00

2.G. Other NA NA NA NA NA NA

9,303.15 9,303.15 274.44 274.44 2,182.88 2,182.88

Difference Difference

(%)

Total CO 2 Equivalent Emissions with Land Use, Land-Use Change and Forestry 17,465.19 3.83

Total CO 2 Equivalent Emissions without Land Use, Land-Use Change and Forestry -4,939.78 -0.87 CO 2 equivalent (Gg)

455,713.20 473,178.39

567,922.20 562,982.42 Potential Emissions from Consumption of

Previous submission Latest submission SF 6

CO 2 equivalent (Gg) (%) CO 2 equivalent (Gg) (%) CO 2 equivalent (Gg) (%) GREENHOUSE GAS SOURCE AND SINK

CATEGORIES HFCs PFCs Total National Emissions and Removals GREENHOUSE GAS SOURCE AND SINK

CATEGORIES CO 2 CH 4 N 2 O

CO 2 equivalent (Gg) (%) CO 2 equivalent (Gg) (%) CO 2 equivalent (Gg) (%)

Table 9.4 Recalculated data of the year 200 6

### 215



## Chapter 10: REFERENCES

References for the main chapters and the annexes are listed here and are organised by chapter and

annex.

10.1 INTRODUCTION

APAT, 2 005. Quality Assurance/Quality Control plan for the Italian Inventory. September 2005.

Internal document.

APAT, 2006 [a]. Quality Assurance/Quality Control plan for the Italian Emission Inventory.

Procedures Manual. June 2006

APAT, 2006 [b]. Quality Assu rance/Quality Control plan for the Italian Emission Inventory. Year

2006. June 2006

APAT, 2007 [a]. Quality Assurance/Quality Control plan for the Italian Emission Inventory. Year 2007. May 2007.

APAT, 2007 [b]. Carbon Dioxide Intensity Indicators. May 2 007.

APAT, 2008 [a]. National Greenhouse Gas Inventory System in Italy. April 2008. Internal

document.

APAT, 2008 [b]. Quality Assurance/Quality Control plan for the Italian Emission Inventory. Year 2008. April 2008. Internal document.

APAT, 2008 [c]. C arbon Dioxide Intensity Indicators. April 2008. Internal document.

EC, 2005. Commission decision of 10 February 2005 laying down rules implementing Decision No 280/2004/EC concerning a mechanism for monitoring Community greenhouse gas emissions and

for im plementing the Kyoto Protocol. 2005/166/EC.

Ecofys, 2001. Evaluation of national climate change policies in EU member states. Country report on Italy, The Netherlands 2001.

EMEP/CORINAIR, 200 7 . Atmospheric Emission Inventory Guidebook. Technical report N o 16/2007

.

ENEA/MAP/APAT, 2004. Energy data harmonization for CO 2 

### emission calculations: the Italian

case. Rome 23/02/04. EUROSTAT file n. 200245501004.

IPCC, 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Emission Inventories.

Three volu mes: Reference Manual, Reporting Manual, Reporting Guidelines and Workbook. IPCC/OECD/IEA. IPCC WG1 Technical Support Unit, Hadley Centre, Meteorological Centre, Meteorological Office, Bracknell, UK.

### 216

IPCC, 2000. Good Practice Guidance and Uncertainty Mana gement in National Greenhouse Gas Inventories. IPCC National Greenhouse Gas Inventories Programme, Technical Support Unit, Hayama, Kanagawa, Japan.

IPCC, 2003. Good Practice Guidance for Land Use, Land

- Use Change and Forestry. IPCC Technical Support Unit, Kanagawa, Japan.

Liburdi R., De Lauretis R., Corrado C., Di Cristofaro E., Gonella B., Romano D., Napolitani G., Fossati G., Angelino E., Peroni E., 2004. La disaggregazione a livello provinciale dell’inventario nazionale delle emissioni”. Rapporto APAT CTN

- ACE 2004.

Romano D., Bernetti A., De Lauretis R., 2004. Different methodologies to quantify uncertainties of

air emissions. Environment International vol 30 pp 1099

- 1107.

UNFCCC, 2007 [a]. Report of the individual review of the greenhouse gas invento ry of Italy

submitted in 2006. FCCC/ARR/2006/ITA. UNFCCC, 11 December 2007.

UNFCCC, 2007 [b]. Report of the review of the initial report of Italy. FCCC/IRR/2007/ITA.
UNFCCC, 10 December 2007.

UNFCCC , 2009. Report of the individual review of the greenhous e gas inventories of Italy

submitted in 2007 and 2008. FCCC/ARR/200 8 /ITA. UNFCCC, 16 January 2009.

10.2 ENERGY [CRF sector 1]

ACI, several years. Annuario statistico. Automobile Club d’Italia, Roma.

htt p://www.aci.it/index.php?id=54

.

AEEG, several years. Qualità del servizio gas. Autorità per l’energia elettrica e il gas. http://www.autorita.energia.it/cgi

- bin/sinte si_cont_gas/sintesi_datigas

.

AISCAT, several years. Aiscat in cifre. Data and reports available on website at: http://www.aiscat.it/pubb_ci fre.htm?ck=1&sub=3&idl=4&nome=pubblicazioni&nome_sub=aiscat

%20in%20cifre

.

ANCMA, several years. Data available on website at: http://www.ancma.it/it/publishing.asp

.

ANPA, 2001. Redazione di inventar i nazionali delle emissioni in atmosfera nei settori del trasporto aereo e marittimo e delle emissioni biogeniche. Rapporto finale. Gennaio 2001.

APAT, 2003 [a]. Indicatori e modelli settoriali finalizzati alla preparazione di inventari delle

emissioni de l sistema energetico nazionale nel breve e medio periodo. Tricarico A., Rapporto

Tecnico N° 01/2003.

APAT, 2003 [b]. Analisi dei fattori di emissione di CO 2 

### dal settore dei trasporti. Ilacqua M., Contaldi M., Rapporti n° 28/2003.

CONFETRA, several years. Il trasporto merci su strada in Italia. Data and reports available on

website at: http://www.confetra.it/it/centrostudi/statistiche.htm

.

### 217

Contaldi M., 1999. Inventario delle emissioni di metano da uso gas naturale. ANPA, internal

document.

E C , 2009. Proposal for a Commission Decision amending Decision 2007/589/EC as regards th einclusion of monitoring and reporting guidelines for emissions and tonne

- kilometre data from

aviario activit ies. Commission of the European Communities, 2009 (draft).

EDISON, sev

eral years. Rendiconto ambientale e della sicurezza.

EEA, 2000. COPERT III, Computer Programme to Calculate Emissions from Road Transport

- Methodology and Emission Factors, European E nvironment Agency, Technical report No 49,

November 2000.

EEA, 2007. COPERT 4

, Computer programme to calculate emissions from road transpor t. European Environment Agency, December 2007. http://lat.eng .auth.gr/copert/docs.htm

.

EMEP/CORINAIR, 2007. Atmospheric Emission Inventory Guidebook. Technical report No

16/2007.

ENAC/MINT, several years. Annuario Statistico. Ente Nazionale per l’Aviazione Civile, Ministero delle Infrastrutture e dei Trasporti.

ENEA, several years. Rapporto Energia Ambiente. Ente per le Nuove tecnologie, l’Energia e
l’Ambiente, Roma.

ENEL, several years. Dati statistici sull’energia elettrica in Italia. ENEL.

ENI, several years [a]

. La congiuntura economica ed energetica. E NI.

ENI, several years [b] . Health Safety Environment report. ENI.

Frustaci F., 1999. Metodi di stima ed analisi delle emissioni inquinanti degli off

- road. Thesis in

Statistics.

Giordano R., 2007. Trasporto merci: criticità atttuali e potenziali svilupp i nel contesto europeo.

National road transporters central commitee

.

IPCC, 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Emission Inventories. Three volumes: Reference Manual, Reporting Manual, Reporting Guidelines and Workbook.

IPCC/OECD

/IEA. IPCC WG1 Technical Support Unit, Hadley Centre, Meteorological Centre, Meteorological Office, Bracknell, UK.

IPCC, 2000. Good Practice Guidance and Uncertainty Management in National Greenhouse Gas

Inventories. IPCC National Greenhouse Gas Inventori es Programme, Technical Support Unit, Hayama, Kanagawa, Japan.

IPCC 2006, 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T.

and Tanabe K. (eds).Published: IGES, Japan

ISTAT, several years [a]

. Annuario Statistico Italiano. Istituto Nazionale di Statistica.

### 218

ISTAT, 2009. Personal comunication.

ISTAT, several years [b]. Trasporto merci su strada

. Istituto Nazionale di Statistica. http://www.istat.it/dati/dataset/20070109_00/

.

MSE, several years [a]. Bilancio Energetico Nazionale (BEN). Ministero delle Attività Produttive, Direzione Generale delle Fonti di Energia ed industri e di base. http://dgerm.sviluppoeconomico.gov.it/dgerm/ben.asp

.

MSE, several years [b]. Bollettino Petrolifero Trimestrale (BPT). Ministero delle Attività

Produttive.

MINT, several year s. Conto Nazionale delle Infrastrutture e dei Trasporti (CNT). Ministero delle Infrastrutture e dei Trasporti. http://www.trasporti.gov.it/page/NuovoSito/site.php?o=vd&id=3011

.

Patel M.K., Tosato G.C., 1997. Understanding Non

- energy Use and Carbon Storage in Italy in the

Context of the Greenhouse Gas Issue.

Romano D., Gaudioso D., De Lauretis R., 1999. Aircraft Emissions: a comparison of methodologies based on different data availability. Environmental Monitoring and Assessment. Vol. 56 pp. 51

- 74.

Riva A., 1997. Methodology for methane emission inventory from SNAM transmission system. Snam Spa Italy.

Techne, 2009. Stima delle emissioni in atmosfera nel settore del trasporto aereo e marittimo

. Final report. TECHNE Consulting, March 2009.

Terna, several years. Dati statistici sugli impianti e la produzione di energia elettrica in Italia.

Gestore Rete Trasmissione Nazionale. www.terna.it

.

Trozzi C., Vaccaro R., De Lauretis R., Romano D., 2002 [a]. Air pollutant emissions estimate from global air traffic in airport and in cruise: methodology and case study. Presented at Transport and

Air Pollution 2002.

Trozzi C., Vaccaro R., De Lauretis R., 2002 [b]. Air pollutant emissions estimate from global ship traffic in port and in cruise: methodology and case study. Presented at Transport and Air Pollution

2002.

UP, several years. Previsioni di domanda energetica e petrolifera in Italia. Unione P etrolifera.

10.3 INDUSTRIAL PROCESSES [CRF sector 2]

ACEA, 2004. Personal Communication. ACEA.

AEM, several years. Rapporto Ambientale. AEM.

AITEC, 2004. Posizione dell’industria cementiera in merito al Piano Nazionale di Allocazione delle

emissioni di gas ad effetto serra. Roma 19/03/2004.

### 219

AITEC, several years . L’industria Italiana del Cemento. Associazione italiana tecnico economica

del cemento.

ALCOA, 2004. Primary Aluminium in Italy. ALCOA.

ALCOA, several years. Personal Communication. ALCOA.

ANDIL, 2000. Primo rapporto ambientaledell’industria italiana dei laterizi. Assolaterizi, Associazione nazionale degli industriali dei laterizi.

ANDIL, several years. Indagine conoscitiva sui laterizi. Assolaterizi, Associazione nazionale degli

industrial i dei laterizi.

ANIE, several years. Personal Communication. ANIE Federazione.

APAT, 2003. Il ciclo industriale dell’acciaio da forno elettrico. Agenzia per la Protezione dell’Ambiente e per i servizi tecnici, Rapporti 38/2003.

ASSOMET, several years. I metalli non ferrosi in Italia. Associazione nazionale industrie metalli

non ferrosi.

ASSOPIASTRELLE, 2004. L’industria italiana delle piastrelle di ceramica e la Direttiva 2003/87.

ASSOPIASTRELLE, several years. Indagine statistica nazionale. Industria italiana delle piastrelle di ceramica. Assopiastrelle, Associazione nazionale dei produttori di piastrelle di ceramica e di

materiali refrattari.

ASSURE, 2005. Personal Communication. European Association for Responsible Use of HFCs in Fire Fighting.

Boe hringer Ingelheim, several years

. Personal Communication. Boehringer Ingelheim Istituto De Angeli.

CAGEMA, 2005. Politiche e misure per la riduzione delle emissioni di gas serra: il settore della
calce. Associazione dell’industria italiana della calce, de l gesso e delle malte.

CARBITALIA SPA, 2009, Personal Communication

Chiesi Farmaceutici, several years . Personal Communication. Chiesi Farmaceutici S.p.A.

CNH, several years . Personal Communication. Case New Holland.

CTN/ACE, 2000. Rassegna delle infor mazioni disponibili sulle emissioni di diossine e furani dal settore siderurgico e della metallurgia ferrosa. A cura di Pasquale Spezzano.

EC, 2006. Regulation n. 842/2006 of the European Parliament and of the Council of 17 May 2006

on certain fluorinated greenhouse gases.

EDIPOWER, 2003. Rapporto Ambientale 2003. EDIPOWER.

### 220

EDIPOWER, 2007. Rapporto di Sostenibilità 2007. EDIPOWER.

EDISON, several years. Bilancio Ambientale. EDISON.

EMEP/CORINAIR, 2007. Atmospheric Emission Inventory Guidebook. Technica l report No

16/2007.

ENDESA, 2004. Personal Communication. ENDESA.

ENDESA, several years [a]. Rapporto ambiente e sicurezza. ENDESA.

ENDESA, several years [b]. Rapporto di sostenibilità. ENDESA.

ENEL, several years. Rapporto ambientale. ENEL.

ENIRISOR

SE, several years. Statistiche metalli non ferrosi. ENIRISORSE

FEDERACCIAI, 2004. Personal Communication

.

FEDERACCIAI, 2008. Rapporto ambientale Federacciai 2007

FEDERACCIAI, several years. La siderurgia in cifre. Federazione Imprese Siderurgiche Italia ne.

FIAT, several years

. Personal Communication.

General Gas, 2008. Personal Communication. General Gas S.r.l.

GSK, several years

. Personal Communication. GlaxoSmithKline S.p.A.

IAI, 2003. The Aluminium Sector Greenhouse Gas Protocol (Addendum to the W BCSD/WRI Greenhouse Gas Protocol). Greenhouse Gas Emission Monitoring and Reporting by the Aluminium Industry. International Aluminium Institute, May 2003.

ILVA, 2006 . Analisi ambientale iniziale. Rev. 2, March 2006. IPPC permitting process.

IPCC, 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Emission Inventories. Three volumes: Reference Manual, Reporting Manual, Reporting Guidelines and Workbook. IPCC/OECD/IEA. IPCC WG1 Technical Support Unit, Hadley Centre, Meteorological Centre,

Meteo rological Office, Bracknell, UK.

IPCC, 2000. Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories. IPCC National Greenhouse Gas Inventories Programme, Technical Support Unit,
Hayama, Kanagawa, Japan.

IPCC 2006, 2006 IP CC Guidelines for National Greenhouse Gas Inventories, Prepared by the National Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T. and Tanabe K. (eds).Published: IGES, Japan.

IPPC, 2001. Best Available Techniques Reference Document on the Production of Iron and Steel. Integrated Pollution Prevention and Control. European Commission. December 2001.

### 221

ISPESL, 2005. Profilo di rischio e soluzioni. Metallurgia. Produzione ferroleghe. Edited by A.

Borroni

ISTAT, several years. A

nnuario Statistico Italiano. Istituto Nazionale di Statistica.

IVECO, several years . Personal Communication.

Lusofarmaco, several years . Personal Communication. Istituto Luso Farmaco d’Italia S.p.A.

Magnesium products of Italy, several years. Personal C ommunication. Meridian Technologies Inc.

- Magnesium Products of Italy.

Mariel, 2008. Personal Communication. Mariel S.r.l.

Menarini, several years

. Personal Communication. Industrie farmaceutiche riunite.

MICRON, several years . Personal Communication. Micron Technology Italia S.r.l.

Norsk Hydro, several years. Personal Communication.

Radici Chimica, 1993. Progetto CORINAIR. Produzione acido adipico: descrizione del processo utilizzato da Radici Chimica. Radici Group, Novara.

Radici Chimica, several y ears. Personal Communication.

Safety Hi Tech, 2008. Personal Communication. Safety Hi Tech S.r.l.

Sanofi Aventis, several years

. Personal Communication. Sanofi Aventis Italia.

Siteb, several years. Rassegna del bitume.

Solvay, 2003. Bilancio di Sosten ibilità Solvay 2002. Solvay Solexis S.p.A.

Solvay, several years. Personal Communication. Solvay Solexis S.p.A.

Solvay, 2008. Personal Communication. Solvay Fluor Italia.

Sotacarbo, 2004. Progetto integrato miniera centrale. Studio di fattibilità sito d i Portovesme.

ST Microelectronics, several years. Personal Communication. ST Microelectronics.

TERNA, 2006. Rapporto di Sostenibilità 2006. TERNA.

UN, several years. Industrial Commodity Statistics Yearbook. United Nation.

UNFCCC, 2007. Report of the r eview of the initial report of Italy. FCCC/IRR/2007/ITA 10

December 2007.

UNFCCC, 2009. Report of the individual review of the greenhouse gas inventories of Italy submitted in 2007 and 2008. FCCC/ARR/2008/ITA 16 January 2009.

### 222

UNRAE, several years. Perso nal Communication. Unione Nazionale Rappresentanti Autoveicoli

Esteri.

USEPA, 1997. “Compilation of Air Pollutant Emission Factors”. AP

- 42, U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards. Research Triangle Park, North

C arolina. October 1997.

USGS, several years. Mineral yearbook. Ferroalloys.

YARA , 2007 (technical documentations from IPPC permit issuing process)

10.4 SOLVENT AND OTHER PRODUCT USE [CRF sector 3]

AIA, several years [ a ] . Personal Communication. Associ azione Italiana Aerosol.

AIA, several years [ b ] . Relazioni annuali sulla produzione italiana aerosol. Associazione Italiana

Aerosol.

Assocasa, several years. Personal Communication.

Assogastecnici, several years. Personal Communication

.

AVISA, several years. Personal Communication

. Co.Da.P., 2005. Personal Communication.

EEA, 1997. CORINAIR 94 Summary Report, Report to the European Environment Agency from the European Topic Centre on Air Emission.

EC, 1999. Council Directive 1999/13/EC of 11 March 199 9 on the limitation of emissions of volatile organic compounds due to the use of organic solvents in certain activities and installations. Official Journal of the European Communities 29 March 1999.

EC, 2002. Screening study to identify reduction in VOC e missions due to the restrictions in the VOC content of products. Final Report of the European Commission, February 2002.

EC, 2004. Directive 2004/42/EC of the European Parliament and of the Council of 21 April 2004 on the limitation of emissions of volatile organic compounds due to the use of organic solvents in decorative paints and varnishes and vehicle refinishing products and amending Directive

1999/13/EC

. Off

icial Journal of the European Communities 30 April 2004.

EMEP/CORINAIR, 2007. Atmospheric Emission Inventory Guidebook. Technical report No

16/2007.

EMEP/CORINAIR, 2008. Atmospheric Emission Inventory Guidebook. Draft

.

ENEA/USLRMA, 1995. Lavanderie a se cco.

FAO, several years. Food balance. http://faostat.fao.org

.

### 223

FIAT, several years. Rendiconto Ambientale. Gruppo Fiat.

GIADA, 2006. Progetto Giada and Personal Communication. ARPA Veneto

– Provincia di

Vicenza.

IPCC, 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Emission Inventories. Three volumes: Reference Manual, Reporting Manual, Reporting Guidelines and Workbook. IPCC/OECD/IEA. IPCC WG1 Technical Support Unit, Hadley Centre, Meteorological C entre, Meteorological Office, Bracknell, UK.

ISTAT, several years [ a ] . Annuario Statistico Italiano.

ISTAT, several years [ b ] . Bollettino mensile di statistica.

ISTAT, several years [ c ]

. http://www.istat.it

.

ISTAT, several years [ d ] . Personal communication.

Offredi P., several years. Professione Verniciatore del Legno. Personal communication.

Regione Campania, 2005. Inventario regionale delle emissioni di inquinanti dell’aria della Regione Campania, marzo 2005.

Re gione Toscana, 2001. Inventario regionale delle sorgenti di emissione in aria ambiente, febbraio

2001.

TECHNE, 1998. Personal communication.

TECHNE, 2004. Progetto MeditAiraneo. Rassegna dei fattori di emissione nazionali ed

internazionali relativamente al settore solventi. Rapporto Finale, novembre 2004.

TECHNE, 2008. Fattori di emissione per l’utilizzo di solventi . Rapporto Finale, marzo 2008.

UNIPRO, several years. Rapporto Annuale

- Consumi cosmetici in Italia.

Vetrella G., 1994. Strategie ottimali per la riduzione delle emissioni di composti organici volatili.

Thesis in Statistics.

10.5 AGRICULTURE [CRF sector 4]

ADBPO, 1994. Piano delle direttive e degli interventi urgenti per la lotta all’eutrofizzazione delle acque interne e del mare Adriatic o. Autorità di bacino del fiume Po. Parma

- Italia.

ADBPO, 2001. Progetto di Piano stralcio per il controllo dell'Eutrofizzazione (PsE).Autorità di bacino del fiume Po. Relazione generale. Parma

- Italia.

AIA, 2009. Controlli della produttività del latte in Italia

- Statistiche Ufficiali

- Anno 2007.

Associazione Italiana Allevatori. Italia. http://www.aia.it/bollettino/bollettino.htm

### 224

ANPA

- ONR, 2001. I rifiuti del comparto agro

- alimentare, Stud io di settore. Agenzia Nazionale per la Protezione dell’Ambiente. Rapporto n. 11/2001. Roma

– Italia.

APAT, 2004[a]. Linee guida per l’utilizzazione agronomica degli effluenti di allevamento, Fase 2 Effluenti zootecnici, Risultati di una indagine campionar ia sulle caratteristiche degli effluenti di allevamento, a cura di CRPA. Reggio Emilia

–Italia.

APAT, 2004[b]. Linee guida per l’utilizzazione agronomica degli effluenti di allevamento, Fase 2 Effluenti zootecnici, Risultati di una indagine campionaria sulle tipologie di stabulazione e di stoccaggio, a cura di CRPA. Reggio Emilia

–Italia.

APAT, 2005. Methodologies used in Italy for the estimation of air emission in the agriculture sector. Technical report 64/2005. Rome

- Italy.

ASSONAPA, 2006. Databas e of goat and sheep animal consistency and breeds. Associazione Nazionale della Pastorizia Ufficio Centrale dei Libri Genealogici e dei Registri Anagrafici, Italy. http://www.assonapa.com/

.

Baldoni R., Giardini L., 1989. Coltivazione erbacee. Editor Patro n, p 1072. Bologna

- Italia.

Barile, V.L., 2005. Improving reproductive efficiency in female buffaloes. Livest. Prod. Sci. 92,

83–194.

Bonazzi G., Crovetto M., Della Casa G., Schiavon S., Sirri F., 2005, Evaluation of Nitrogen and Phosphorus in Livesto ck manure: Southern Europe (Italy). In Workshop: Nutrients in livestock manure, Bruxelles, 14 February 2005.

Borgioli E., 1981. Nutrizione e alimentazione degli animali domestici. Edagricole, p. 464.

Butterbach

- Bahl K., Papen H., Rennenberg H., 1997. Imp act of rice transport through cultivars on methane emission from rice paddy fields. Plant, Cell and Environment. 20:1175

- 1183.

Centro Ricerche sul Riso, 2007. Personal communication with the Rice Research Centre from the

Ente Nazionale Risi

–information requested on dry seeding surface cultivation, Maurizio Tabacchi,

Italia.

CESTAAT, 1988. Impieghi dei sottoprodotti agricoli ed agroindustriali, Vol. 1. Centro Studi sull’Agricoltu

ra, l’Ambiente e il Territorio , p. 311.

Cóndor G. R., Vitullo, M., De Laur etis, R., 2005. Contribution of ISTAT statistics to the National Air Emission Inventory of the Agriculture sector. In: Convegno "AGRISTAT

- Statistiche Agricole" 30

- 31 Maggio 2005. Florence

- Italy.

Cóndor R.D. 2006. Agricoltura. Oral presentation “Camb iamenti Climatici e inquinamento

atmosferico. L’inventario nazionale delle emissioni come strumento di conoscenza e verifica dello
stato dell’ambiente”, 23

- 24 October 2006 Rome

- Italy. http://www.apat.gov.it/site/_files/Doc_emissioni/RocioCondor.pdf

.

Cóndor, R. D., De Lauretis, R. 2007. Agriculture air emission inventory in Italy: synergies among

conventions and directives. In: Ammonia Conference abstract book. Ed. G.J. M onteny, E. Hartung,

### 225

M. van den Top, D. Starmans. Wageningen Academic Publishers. 19

- 21 March 2007, Ede

- The

Netherlands.

Cóndor, R. D., De Lauretis, R., Lupotto, E., Greppi, D., Cavigiolo S. 2007[a]. Methane emission inventory for the rice cultivation se ctor in Italy. In: Proceeding of the Fourth Temperate Rice
Conference”. Ed. S. Bocchi, A. Ferrero, A. Porro. 25

- 28 June Novara

– Italy.

Cóndor, R. D., Vitullo, M. De Lauretis, 2007[b]. Emissioni ed assorbimenti di gas serra dai settore Agricoltura e Uso de l Suolo e Foreste in Italia. Dipartimento Stato dell’Ambiente e Metrologia Ambientale, APAT. Poster presented “Conferenza Nazionale sui Cambiamenti Climatici 2007”

. 12

- 13 September, Rome

- Italy. http://www.apat.gov.it/site/_files/CNCC2007Sintesilavori.pdf

Cóndor, R.D., Valli L., De Rosa G., Di Francia A., De Lauretis R. 2008[a]. Estimation of the

methane emission factor for the Italian Mediterranean buffalo. International Journa l of Animal

Biosciences 2:1247

- 1253.

Cóndor R., De Lauretis R., Romano D., Vitullo M. 2008[b]. Inventario nazionale delle emissioni di particolato e principali fonti di emissione. In: Atti 3° Convegno Nazionale sul Particolato Atmosferico. Il particolato atmosferico: la conoscenza per l’informazione e le e le strategie di

intervento Bari 6

- 8 Ottobre, Italia. http://pm2008.vglobale.it/index.php/fd=cyan/ff=contributi

sc ientifici.htm

Cóndor, R.D., Cristofaro, E. De Lauretis, R. 200 8[c]

. Agricoltura: inventario nazionale delle emissioni e disaggregazione provinciale. Istituto superiore per la protezione e la ricerca ambientale, ISPRA Rapporto tecnico 85/2008. Roma, Itali a. http://www.apat.gov.it/site/it

- IT/APAT/Pubblicazioni/Rapporti/Documento/rapporto_85_2008.html

Cóndor, R.D., 2009. Procedura per la preparazi one, caricamento e reporting dell’inventario nazionale delle emissioni settore: agricoltura. Internal report ISPRA. Rome, Italy.

Confalonieri R., Bocchi S. 2005. Evaluation of CropSyst for simulating the yield of flooded rice in northern Italy. European J ournal of Agronomy. 2005, 23, 315 – 326.

Consorzio per la tutela del formaggio Mozzarella di Bufala Campana, 2002. Modello di Regolamento per la gestione igienica ed alimentare dell'allevamento bufalino in relazione alla produzione della mozzarella di buf ala campana DOP. Edit. Consorzio per la tutela del formaggio mozzarella di bufala campana (Campana Mozzarella Consortium). CRPA/CNR, 1992. Indagine sugli scarti organici in Emilia Romagna.

CRPA, 1993. Manuale per la gestione e utilizzazione agronomica de i reflui zootecnici. Regione Emilia Romagna, Assessorato agricoltura.

CRPA, 1996. Biogas e cogenerazione nell’allevamento suino. Manuale pratico. ENEL, Direzione
studi e ricerche, Centro ricerche ambiente e materiali. Milano

–Italia.

CRPA, 1997 [a]. Pia ni Regionali di Risanamento e tutela della qualità dell’aria. Quadro delle azioni degli enti locali per il settore zootecnico delle aree padane. Allegato 2. Relazione di dettaglio sulla metodologia adottata per la quantificazione delle emissioni di metano . Febbraio

1997.

### 226

CRPA, 1997 [b]. Piani Regionali di Risanamento e tutela della qualità dell’aria. Quadro delle azioni degli enti locali per il settore zootecnico delle aree padane. Relazione di dettaglio sulla metodologia adottata per la quantificazione delle emissioni di protossido di azoto. Settembre 1997.

CRPA, 2000. Aggiornamento dell’inventario delle emissioni in atmosfera di ammoniaca, metano e protossido di azoto dal comparto agricolo. Centro Ricerche Produzioni Animali. Gennaio 2000.

CRPA, 2004[ a]. L’alimentazione della vacca da latte. Edizioni L’Informatore Agrario. Terza
edizione, Centro Ricerche Produzioni Animali.

CRPA, 2004[b]. Personal communication, expert in dairy cattle feeding from the Research Centre
on Animal Production (CRPA), Maria Teresa Pacchioli.

CRPA, 2004 [c] . Personal communication, expert in greenhouse gases emissions from the agriculture sector from the Research Centre on Animal Production (CRPA), Laura Valli.

CRPA, 2005. Personal communication, working group with experts i n animal feeding from the

Research Centre on Animal Production (CRPA), Maria Teresa Pacchioli and Paola Vecchia.

CRPA, 2006[a]. Progetto MeditAIRaneo: settore Agricoltura. Relazione finale. Technical report on the framework of the MeditAIRaneo project for the Agriculture sector, Reggio Emilia

- Italia.

CRPA, 2006[b], Predisposizione di scenari di emissione finalizzati alla progettazione di interventi per la riduzione delle emissioni nazionali di ammoniaca ed alla valutazione di misure e di progetti per la tutela della qualità dell’aria a livello regionale. Final report. Reggio Emilia

–Italy.

CRPA, 2008. Le scelte politiche energetico

- ambientali lanciano il biogas. L’Informatore Agrario 3/2008, p.28

- 32
CRPA, 200 9. Personal Communication. E xpe rt in the ag ricultural emission inventory from the Research Centre on Animal Production (CRPA) , Laura Valli

.

CRPA/AIEL, 2008. Energia dal biogas prodotto da effluenti zootecnici, biomasse dedicate e di scarto. Ed. Associazione Italiana Energie Ambientali (AIEL).

Da n J., Krüger M., Frenzel P., Conrad R., 2001. Effect of a late season urea fertilization on methane emission from a rice field in Italy. Agri. Ecos. Env. 83: 191 –199.

Dannenberg S., Conrad R, 1999. Effect of rice plants on methane production and rhizosphe ric metabolism in paddy soil. Biogeochemistry 45: 53 –71.

De Rosa, M., Trabalzi, F., 2004. Technological innovation among buffalo breeders of southern lazio, Italy. Agricoltura Mediterranea. Vol. 134, 58

- 67.

ENEA, 1994. Personal communication , expert in a

griculture sector. Ente nazionale per l'energia, l'ambiente e le nuove tecnologie (ENEA), Andrea Sonnino.

ENEA, 2006. Valutazione della possibilità di sostituzione dell'urea con altri fertilizzanti azotati. Final report. Rome, Italy.

ENR , 2007. Persona l communication, surface statistic from the Ente Nazionale Risi (ENR), Enrico
Losi (mail 05/06/2007).

### 227

ENR, 2009. Information available on rice surface, rice surface by variety and time of cultivation. Ente Nazionale Risi, Italy. http://www.enterisi.it/ser_database.jsp

.

EUROSTAT, 2007[a]. Farm structure in Italy

–2005. Statistics in Focus Agriculture and Fisheries

22/2007 Product KS

- SF

- 07

- 022 European Comunities.

EUROSTAT, 2007[b]. Agriculture. Ma in statistics 2005

- 2006. Product Ks

- ED

- 07

- 002

- En

- C. European Comunities.

FAO, 2009. FAOSTAT, the FAO Statistical Database, http://faostat.fao.org/

.

Ferrero A., Nguyen N.V., 2004. C onstraints and opportunities for the sustainable development of

rice

- based production systems in Europe. In proceedings: FAO Rice Conference, 12

- 13 February 2004, FAO, Rome, Italy.

Gazzetta Ufficiale della Repubblica Italiana, 2006. Criteri e norme tecniche generali per la disciplina r

egionale dell’utilizzazione agronomica degli effluenti di allevamento e di acque reflue di cui all’articolo 38 del decreto legislativo 11 maggio 1999 N. 152. G.U. n. 109 del 12/05/06

- Suppl. Ordinario n.120. Ministero delle Politiche Agricole e Forestali. Italy. http://www.guritel.it/icons/freepdf/SGFREE/2006/05/12/SG109.pdf

.

Giardini L., 1983. Agronomia Generale, Patron, Bologna.

Greco, M., Martino, L. 2001. The agricultura l statistical system in Italy. In: Conference on Agricultural and Environmental Application, Rome 4

- 8 June. Italy 46

- 461pp

Holter J.B., Young A.J., 1992. Methane prediction in dry and lactating holstein cows, Journal of Dairy Science, 8(75), pp. 2165

- 2175.

Holzapfel

- Pschorn A., Seiler W., 1986. Methane emission during a cultivation period from an Italian Rice Paddy. Journal of Geophysical Research Vol. 91 No D11 11,803

- 11,814.

Husted S., 1993. An open chamber technique for determination of methane emissi on from stored livestock manure. Atmospheric Environment 11 (27).

Husted S., 1994. Seasonal variation in methane emissions from stored slurry and solid manures, J.

Env. Qual. 23, pp. 585

- 592.

Infascelli, F., 2003. Nuove acquisizioni sulla nutrizione e su ll'alimentazione della bufala. In: II Congresso Nazionale sull'Allevamento del Bufalo Monterotondo

- Roma, pp. 1

- 18.

INRA, 1988. Alimentation des bovines, ovins et caprins, Paris, p.471.

IPCC, 2000. Good Practice Guidance and Uncertainty Management in Na tional Greenhouse Gas Inventories. IPCC National Greenhouse Gas Inventories Programme, Technical Support Unit, Hayama, Kanagawa, Japan.

IPCC, 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Emission Inventories.

Three volumes: Reference Man ual, Reporting Manual, Reporting Guidelines and Workbook.

### 228

IPCC/OECD/IEA. IPCC WG1 Technical Support Unit, Hadley Centre, Meteorological Centre, Meteorological Office, Bracknell, UK.

IPCC, 2006. 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T. and Tanabe K. (eds). Published: IGES, Japan.

Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA). 2008[a]. Serie storiche dal

19 80 al 2006 delle emissioni nazionali di inquinanti atmosferici, Rete del Sistema Informativo

Nazionale Ambientale

- SINANET. http://www.sinanet.apat.it/it/s inanet/serie_storiche_emissioni/NFR%201980

- 2006/view

Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA). 2008[b]. Database della disaggregazione a livello provinciale dell'Inventario nazionale delle emissioni:1990

- 1995

- 2000

- 2005. Istitu

to Superiore per la Protezione e la Ricerca Ambientale,

ISPRA. http://www.sinanet.apat.it/it/inventaria/disaggregazione_prov2005/

Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA). 2009. Quality Assurance/Quality Control plan for the Italian Inventory. Year 2009.

ISTAT, 1991. Caratteristiche strutturali delle aziende agricole, fascicoli provinciali, 4° Censimento generale dell'Agricoltura (20 ottobre 19 90

- 22 febbraio 1991), Roma

–Italia.

ISTAT, several years [a]. Statistiche dell’agricoltura, zootecnia e mezzi di produzione

–Annuari (1990

- 1993), Istituto Nazionale di Statistica, Roma

–Italia.

ISTAT, several years [b]. Statistiche dell’agricoltura

– Annuari (1994

- 2000), Istituto Nazionale di
Statistica, Roma

– Italia.

ISTAT, several years [c]. Struttura e produzioni delle aziende agricole

–Informazione (1995

- 1999), Istituto Nazionale di Statistica, Roma

– Italia.

ISTAT, several years [d]. Statistic he sulla pesca e zootecnia

–Informazione (1998

- 2001), Istituto
Nazionale di Statistica, Roma

– Italia.

ISTAT, several years [e]. Statistiche sulla pesca, caccia e zootecnia

–Informazione (1996

- 1997),
Istituto Nazionale di Statistica, Roma

– Italia.
ISTAT, several years [f]. Annuario Statistico Italiano

- Annuario (1990; 1993

- 1994; 1997

- 2003),
Istituto Nazionale di Statistica, Roma

– Italia.

ISTAT, 2003. 5o Censimento Generale dell’Agricoltura. Caratteristiche strutturali delle aziende agricole. Fascicolo N azionale: dati regionali, provinciali e comunali. Istituto Nazionale di Statistica,

Roma

- Italia.

ISTAT, 2004. Personal communication, expert in agriculture statistics

- fertilizers from the National

Institute of Statistics (ISTAT), Mario Adua.

ISTAT, 20 06 [a]. Struttura e produzioni delle aziende agricole Anno 2005. Statistiche in breve (27 dicembre 2006). Statistiche Servizio Agricoltura

–Allevamenti e pesca. Istituto Nazionale di
Statistica, Roma

–Italia. http://www.istat.it/salastampa/comunicati /non_calendario/20061227_00/testointegrale.pdf.

### 229

ISTAT, 2006[b]. Personal communication, expert in agriculture statistics from the National Institute of Statistics (ISTAT), Giampaola Bellini.

ISTAT, 2007[a]. Farm and structure survey from 2005. Informatio n on the number of animals at a provincial level. Istituto Nazionale di Statistica, Roma

– Italia.

ISTAT, 2007[b]. Annuario Statistico Italiano 2007

- Capitolo 13 Agricoltura. Istituto Nazionale di
Statistica, Roma

– Italia.

ISTAT, 2007[c]. Personal communi cation with N. Mattaliano. E

- mail request for elaboration SPA 2003 data on burning residues

- cereals. Istituto Nazionale di Statistica, Roma

– Italia.

ISTAT, 2007[d]. Personal communication with F. Piersimoni. Update of data on livestock collected

on 1 Dec ember for the year 2001. Istituto Nazionale di Statistica, Roma

– Italia.

ISTAT, 2007[e]. “Indagine sulla struttura e produzione delle aziende agricole. Anno 2005” . Prodotto DCSSD1.1.1. Rapporto di qualità su SPA 2005. Istituto Nazionale di Statistica, Ro ma

– Italia.

ISTAT, 2008 [a] . Struttura e produzioni delle aziende agricole. Anno 2007 (03 Dicembre 2008).
Istituto Nazionale di Statistica, Roma

–Italia. http://www.istat.it/salastampa/comunicati/non_calendario/20081203_00/testointegrale20081203.pdf

ISTAT, 2008[b]. Indagine sulla struttura e produzione delle aziende agricole. Anno 2007. Rapporto sulla Qualità. Istituto Nazionale di Statistica, Roma

- Italia.

ISTAT, 2009[a]. Dati annuali sulla consistenza del bestiame, periodo di riferimento 2002

- 2007. Statistiche Servizio Agricoltura

–Allevamenti e pesca. Istituto Nazionale di Statistica, Roma

– Italia. http://www.istat.it/agricoltura/datiagri/consistenza/

ISTAT, 2009[b]. Dati annuali e mensili sul settore lattiero caseario, periodo di riferimento 2002

- 2008. Statistiche Servizio Agricoltura

–Allevamenti e pesca. Istituto N azionale di Statistica, Roma

–Italia. http://www.istat.it/agricoltura/datiagri/latte/

ISTAT, 2009[c]. Dati congiunturali sui mezzi di produzione 2000

- 2007. Istituto Nazionale di
Statistica, Roma

– Italia. http://www.istat.it/agricoltura/datiagri/mezzipro/elecon.html

ISTAT, 2009[d]. Dati congiunturali sulle coltivazioni 1999

- 2008. Istituto Nazionale di Statistica,

Roma

– Italia. http://www.istat.it/agricoltura/datiagri/coltivazioni/

ISTAT, 2009[e]. Personal communication with G. D'Acuti: E

- mail request of national milk production from 2007. I stituto Nazionale di Statistica, Roma

– Italia.

ISTAT, 2009[f]. Personal communication with C. Manzi: E

- mail request of rabbit production data
for 2007. Istituto Nazionale di Statistica, Roma

– Italia.

Kruger M., Frenzel P., Kemnitz D., Conrad R., 2005. Ac tivity, structure and dynamics of the methanogenic archaeal community in a flooded Italian rice field. FEMS Microbiology Ecology 51:

323–331.

### 230

Leip, A., S. Russo, K.A. Smith, F. Conen, and G. Bidoglio, 2002. Rice cultivation by direct drilling and delayed flooding reduces methane emissions. In: van Ham et al. (eds): Non

- CO2 Greenhouse Gases (NCGG

- 3): Scientific understanding, control options and policy aspects. p. 457

- 458.

Leip, A. Bocchi, S. 2007. Contribution of rice production to greenhouse gas emission s in Europe. In: Proceeding of the Fourth Temperate Rice Conference”. Ed. S.Bocchi, A. Ferrero, A. Porro. 25

- 28 June Novara

– Italy.

Lupotto E., Greppi D., Cavigiolo S., 2005. Personal communication, group of experts in rice paddy cultivation and agronomi c practices from the C.R.A.

–Experimental Institute of Cereal Research

– Rice Research Section of Vercelli (Consiglio per la Ricerca e sperimentazione in Agricoltura, Istituto sperimentale per la Cerealicoltura, Sezione specializzata per la Risicoltura) I talia.

Mannini P., 2004. Risparmio idrico/metodi e sistemi irrigui. La sommersione. In: Supplementi di Agricoltura 18. Le buone pratiche agricole per risparmiare acqua. Assessorato Agricoltura, Ambiente e Sviluppo Sostenibile, Regione Emilia Romagna. pp.1 54

- 157. http://www.ermesagricoltura.it/rivista/2004/supp_18/supp18154.pdf.

Marik T., Fischer H., Conen F., Smith K., 2002. Seasonal variations in stable carbon and hydrogen isotope ratios in methane from rice fields. Global Biogeochemical Cycles, vol. 16, No4

Masucci, F., Di Francia, A., Proto, V., 1997. In vivo digestibility, rate of particulate passage and dry matter rumen degradability in buffaloes and sheep. In: V World Buffalo Congress, Caserta (Italy)

13

- 16 October, 296

- 301.

Masucci, F., Di Franci

a, A., Gioffrè, F., Zullo, A., Proto, V., 1999. Prediction of digestibility in buffalo. In: XIII ASPA Congress, Piacenza (Italy) 21

- 24 June 345

- 347.

MINAMBIENTE, 2007 . Fourth National Communication under the UN Framework Convention on Climate Change Italy , November 2007. http://unfccc.int/resource/docs/natc/itanc4.pdf

Mordenti A., Pacchioli M.T., Della Casa, G. 1997. Production and nutrition techniques in the control of meat quality in heavy pigs. XXXII International Symposium on Animal Production: Advances in Technology, Accuracy and Management Milano, 29 th 

### September –1 st 

### October 1997. pag 81.

NRC, 1984. Nutrient Requirements of beef cattle

- Sixth revised Edition. Not. Ac. Press, Washingto n.

NRC, 1988. Nutrient Requirements of swine

- Ninth revised Edition. Not. Ac. Press, Washington.

NRC, 2001. Nutrient Requirements of dairy cattle Ninth edition, Nat. Acad. Press, Washington,

D.C. USA.

OSSLATTE, 2001. Annuario del latte, Edizione 2001. Capitolo 3: La produzione di latte secondo l’ISTAT e l’AIA, Osservatorio sul mercato dei prodotti lattiero

- caseari del latte.

OSSLATTE/ISMEA, 2003. Il mercato del latte, rapporto 2003. Capitolo 3: La struttura degli allevamenti e la produzione di latte s econdo l’ISTAT. Osservatorio sul mercato dei prodotti lattiero

caseari del latte e l’Istituto di Servizi per il Mercato Agricolo ed Alimentare.

### 231

PROINCARNE, 2005. Personal communication, expert in goat and sheep breeding. Associazione

Produttori Carni Bovi ne dell'Emilia Romagna , Stefano Ronchi.

Regione Emilia Romagna, 2004 L. R. 28/98

–P.S.A. 2001

- N. PROG. 3

TAB. B3

- Bilancio dell'azoto nelle specie di interesse zootecnico, Relazione finale, a cura di C.R.P.A., September 2004, Reggio Emilia, Italy.

Regione Emilia Romagna, 2005. Disciplinari di produzione integrata 2005 Norme tecniche di

coltura

- Tecnica agronomica

- Colture erbacee

–RISO. Direzione Agricoltura, Regione Emilia Romagna. http://www.ermesagricoltura.it/wcm/ermesagricoltura/consigli_tecnici/disciplinari/sezione_disciplin ari/s_norme_coltura/s_erbacee/s_riso/TCD08_riso.pdf

Roy R., Detlef Kluber H., Conrad R., 1997. Early initiation of methane production in anoxic rice soil despite the presence of oxidants. FEMS Microbiology Ecology 24:311

- 320.

Russo S., 1976. Influenza dell’interramento della paglia su crescita e produzion e del riso. Rivista Il Riso Anno XXV No 1 p19

- 36.

Russo S., 1988. L’interramento delle paglie come fattore di fertilità e di risparmio energetico. In proceedings: 10o Convegno Internazionale sulla Risicoltura. Vercelli 16

- 18 Novembre 1998, Vercelli, Italy

.

Russo S., Ferrari G., Raso G., 1990. Ricerche sull’efficienza dell’azoto con la somministrazione frazionata. L’informatore Agrario p 27

- 29.

Russo S., 1993. Prove di concimazione con azoto frazionato in risaia. L’informatore Agrario 8/93 p

87

- 94.

Russo S., 1994. Semina interrata con sommersione ritardata: un’alternativa all’impianto della risaia tradizionale. L’informatore Agrario 12/94 p 39

- 46.

Russo S., 2001. Concimazione più sostenibile in risaia e concimi organo

- minerali. L’informatore Agrario 10/2 001 p 23

- 26.

Safley L.M., Casada M.E., Woodbury J., Roos K.F., 1992. Global methane emissions from livestock and poultry manure. USEPA, Washington D.C., EPA/400/191/048.

Sauvant D., 1995. Les émission de méthane par les ruminants: processus, modélisation

, quantification et spatialisation. Le dossier de l’environnement de l’INRA, 10 pp. 7

- 15.

Spanu A., Pruneddu G., 1996. The influence of irrigation volumes on sprinkler

- irrigated rice (Oryza sativa) production. Agricoltura Mediterranea, Vol 126, 377

- 382.

Spanu A., Murtas A., Ledda L., Ballone F., 2004. Confronto tra varietà di riso sottoposte a irrigazione turnata. L’informatore Agrario 18/2004 p 61

- 62.

Spanu A., 2006. Personal communication, expert in rice cultivation from Università degli Studi di

Sassa ri, Sardegna

- Italy.

### 232

Schütz H.

, Holzapfel

- Pschorn A., Conrad R., Rennenberg H., Seiler W., 1989 [a]. A 3

- year continuous record on the influence of daytime, season and fertilizer treatment on methane emission rates from an Italian rice padd., Journal of. Geophysical Research 94, D13, pp. 16405

- 16415.

Schütz H.

, Seiler W.,Conrad R., 1989 [b]. Processes involved in formation and emission of methane in rice paddies. Biogeochemistry, 7, pp. 33

- 53.

Steed Jr. J., Hashimoto A.G., 1995. Methane emissions from typical manure management systems, Bioresource Technology 50 pp. 123

- 130.

TERNA, 2009. National production data from biogas. http://www. terna.it/default/Home/SISTEMA_ELETTRICO/statistiche/dati_statistici/tabid/418/Defa ult.aspx

Tinarelli, A., 1973. La coltivazione del riso Editorial Edagricole, First edition p. 425.

Tinarelli, A., 1986. Il riso. Editorail Edagricole, Second edition p. 426.

Tinarelli, 2005. Personal communication, Italian expert in rice cultivation

–Antonio Tinarelli, participated in the working group with the Experimental Institute of Cereal Research

– Rice
Research Section of Vercelli, Italia.

Tossato S., Regis F. 2002. Collana monografica di manuali naturalistico

- agronomici, con riferimento alle principali colture geneticamente modificate. Volume 6. Il Riso. Agenzia Regionale per la Protezione Ambientale Piemonte (ARPA Piemonte), Piemonte, Italy.

UCEA, 2007. Tempe rature data, Ufficio Centrale di Ecologia Agraria. http://www.politicheagricole.it/ucea/forniture/index3.htm

Unione Nazionale Avicoltura (UNA) 2009. Poultry production information.

www.unionenazionaleavicoltura.it

UNFCCC, 2004. Report of the Individual review of the GHG Inventory submitted in the year 2004 (4
March 2005). http://unfccc.int/files/national_reports/annex_i_ghg_inventories/inventory_review_reports/application/p

df/2004_ irr_centralized_review_italy.pdf

UNFCCC, 2005. Report of the individual review of the greenhouse gas inventory of Italy submitted in

2005 

### (24 November 2005). http://unfccc.int/resource/docs/ 2005/arr/ita.pdf

UNFCCC, 2007. Report of the review of the initial report of Italy (FCCC/IRR/2007/ITA; 10

December 2007. http://unfccc.int/resource/docs/2007/irr/ita.pdf

UNFCCC, 2009. Report of the individual review of the greenhouse gas inventories of Italy submitted in 2007 and 2008 (FCCC/ARR/2008/ITA; 16 January 2009). http://unfccc.int/resource/docs/2009/arr/ita.pdf



### Valli L., Cóndor R., De Lauretis R. 2004. MeditAIRanean Project: Agri culture sector. In: The quality of greenhouse gas emission inventories for agricultural soils. Report on the Expert Meeting on improving the quality of GHG emissions inventories for Category 4D. Joint Research Centre,

21

- 22 October, 2004. http://carbodat1. jrc.it/ccu/pweb/leip/home/ExpertMeetingCat4D/index.htm.

### 233

Wassmann, R. 2005. Personal communication, expert in methane from rice paddies (Forschungszentrum Karlsruhe IMK

- IFU, Garmisch

- Partenkirchen, Germany). E

- mail

communication received on 16/08/2005.

We ber S., Lueders T., Friedrich M.W., Conrad R., 2001. Methanogenic populations involved in the degradation of rice straw in anoxic paddy soil. FEMS Microbiology Ecology 38:11

- 20.

Xiccato G., Schiavon S., Gallo L., Bailoni L., Bittante G., 2005. Nitrogen ex cretion in dairy cow, beef and veal cattle, pig, and rabbit farms in Northern Italy. Ital. J.Anim.Sci. Vol. 4 (Suppl.), 103

- 111.

Yan X., Yagi K., Akiyama H., Akimoto H., 2005. Statistical analysis of the major variables controlling methane emission from r ice fields. Global Change Biology (2005) 11, 1131 –1141.

Zavattaro L., Romani M., Sacco D., Bassanino M., C.Grignani, 2004. Fertilization management of paddy fields in Piedmont (NW Italy) and its effects on the soil and water quality. In proceedings:

Chall enges and opportunities for sustainable rice

- based production systems. Torino, Italy 13

- 15 September 2004.

Zicarelli, L., 2001. Evoluzione dell'allevamento bufalino in Italia. In Proc. I Congresso Nazionale
sull'Allevamento del Bufalo Eboli, Salerno, Ita ly, pp. 1

- 19.

10.6 LAND USE, LAND USE CHANGE AND FORESTRY [CRF sector 5]

APAT, 2004. Corine (Coordination of Information on the Environment) Land Cover Programme.

URL: http://www.clc2000.sinanet.apat. it/

APAT, 2008 [a]. National Greenhouse Gas Inventory System in Italy. April 2008. Internal

document.

APAT, 2008 [b]. Quality Assurance/Quality Control plan for the Italian Emission Inventory. Year 2008. April 2008. Internal document.

APAT

- ARPA Lomb ardia, 2007. Stima dei consumi di legna da ardere per riscaldamento ed uso domestico in Italia, Rapporto Finale

Adams, W.A. 1973. The effect of organic matter on the bulk and true densities of some uncultivated podzolic soils. J. Soil Sci. 24:10 –17

Batj es, 1996. Total carbon and nitrogen in the soils of the world. Eur. J. Soil Sci. 47 : 151

- 163

Benedetti A., Pompili L., Nisini L., 2004. Ruolo attivo dell’agricoltura nei processi di mitigazione del cambiamento climatico globale. Rapporto del progetto Cli magri

- Cambiamenti climatici e agricoltura,

–CRA

- Istituto Sperimentale per la Nutrizione delle Piante

Bovio G., 1996. Stima della biomassa bruciata e della CO 2 

### prodotta da incendi boschivi in Italia.

Schweizerische Zeitschrift für Forstwesen

- Journal Fore stier Suisse, 147, 4

### 234

Ceccanti B., Doni S., Macci C., Cercignani G., Masciandaro G., 2008. Characterization of stable

humic

– enzyme complexes of different soil ecosystems through analytical isoelectric focussing technique (IEF), Soil Biology & Biochemistry 40 (2008) 2174 –2177

CESTAAT, 1988. Impieghi dei sottoprodotti agricoli ed agroindustriali, Vol. 1. Centro Studi sull’Agricoltura, l’Ambiente e il Territorio, p. 311

Corpo Forestale, 2005. CONECOFOR Programme. http://www2.corpoforestale.it/web/guest/serviziattivita/controlloecosistemiforestali

CRPA, 1997. Piani Regionali di Risanamento e tutela della qualità dell’aria. Quadro delle azioni degli enti local

i per il settore zootecnico delle aree padane. Relazione di dettaglio sulla metodologia adottata per la quantificazione delle emissioni di protossido di azoto. Settembre 1997

CRPA, 2009. Progetto Salvaguardia e valorizzazione del prato stabile irriguo in area Parmigiano

Reggiano attraverso l'ottimizzazione della risorsa idrica e azotata, Personal communication

Cutini A., 2002. Litterfall and Leaf Area Index in the CONECOFOR Permanent monitoring Plots
Mosello, R., B. Petriccione and A. Marchetto (Guest Edi tors)

- Long

- term ecological research in Italian forest ecosystems, J. Limnol., 61 (Suppl. 1) pp. 62

- 68

Davidson E.A., Ackerman I.L., 1993. Changes in soil carbon inventory following cultivation of previously untilled soil. Biogeochemistry 20, pp. 161 –194

Del Gardo I., Six J., Peressotti A., Cotrufo M.F., 2003. Assessing the impact of land

- use change on soil C sequestration in agricultural soils by means of organic matter fractionation and stable C isotopes. Global Change Biology (2003) 9, 1204 –1213

ERSA F, 2008. Stock di carbonio nei suoli regionali. Progetto Kyoto

- Ricerca sui cambiamenti climatici e il controllo dei gas serra in Lombardia

- GS3

FAO, 2004 [a]. Global Forest Resources Assessment Update 2005, Specification of National Reporting Tables for FRA 2005, Forest Resources Assessment Programme. Food and Agriculture Organization of the United Nations.

FAO, 2004 [b]. Global Forest Resources Assessment 2005. Global

Forest Resources Assessment

2005 –Italy

–Country Report , UN/ECE

- FAO, submitted. F ood and Agriculture Organization of

the United Nations.

FAO, 2005. FAOSTAT database. URL: http://faostat.fao.org/ . Food and Agriculture Organization

of the United Nations

Francaviglia R., Aromolo R., Benedetti A., Beni C., Biondi F.A., Dell’Abate M.T., Figliolia A., Mecella G., Pompili L., 2006. Qualità funzionali alla conservazione della fertilità integrale dei suoli. Rapporto del Progetto Conservazione e valorizzazione della risorsa suolo: definizione delle quali tà del suolo ai fini della gestione agricola e forestale ecocompatibile

–CRA

- Istituto Sperimentale per la Nutrizione delle Piante

Federici S, Vitullo M, Tulipano S, De Lauretis R, Seufert G, 2008. An approach to estimate carbon stocks change in forest c arbon pools under the UNFCCC: the Italian case. iForest 1: 86

- 95 URL: http://www.sisef.it/iforest/

.

### 235

Gardi C, Stefano Brenna, Silvia Solaro et al, 2007 “The Carbon Sequestration Potential of Soils:

Some Data fr om Northern Italian Regions” Ital. J. Agron. 2:163

- 170.

Giord ano G., 1980. Tecnologia del legno. Hoepli. Milano.

Guo L.B., Giffort R.M., 2002. Soil carbon stocks and land

- use change: a meta analysis. Global Change Biology 8, pp. 345

- 360.

IPCC, 1997. Rev ised 1996 IPCC Guidelines for National Greenhouse Gas Emission Inventories

. Three volumes: Reference Manual, Reporting Guidelines and Workbook. IPCC/OECD/IEA. IPCC WG1 Technical Support Unit, Hadley Centre, Meteorological Office, Bracknell, UK.

IPCC, 200 3. Good Practice Guidance for Land Use, Land

- Use Change and Forestry. IPCC Technical Support Unit, Kanagawa, Japan.

IPLA 2007, Realizzazione della parte piemontese della Carta dei Suoli nazionale a scala 1:250.000,

Personal communication

ISAFA, 2004. Ris elvItalia Project

, Personal communication

ISTAT, several years [a]. Statistiche forestali. Istituto Nazionale di statistica, Roma.

ISTAT, several years [b]. Statistiche dell’agricoltura. Istituto Nazionale di statistica, Roma.

ISTAT, several years [c] . Annuario Statistico Italiano. Istituto Nazionale di statistica, Roma.

Janssen P. H. M., Heuberger P.S.C., 1995. Calibration of process oriented models. Ecological Modelling 83 pp. 55

- 66.

JRC, 2004. Pilot Project to test and learn harmonisation of repor ting of EU member states under the UNFCCC on Land Use change and Forestry (LUCF). Joint Research Centre IES

Lagomarsino A., Moscatelli M.C., Di Tizio A., Mancinelli R., Grego S., Marinari S., 2009. Soil

biochemical indicators as a tool to assess the short

- term impact of agricultural management on changes in organic C in a Mediterranean environment. Ecological indicators 9 (2009) 518 –527

La Mantia T, Oddo G, Rühl J, Furnari G, Scalenghe R, 2007. Variazione degli stock di carbonio in seguito ai processi di abbandono dei coltivi: il caso studio dell’isola di Pantelleria (TP). Forest@ 4 (1): 102

- 109. URL: http://www.sisef.it/

.

Lugato E., Berti A., 2008. Potential carbon sequestration in a cultivated soil under different c limate change scenarios: A modelling approach for evaluating promising management practices in north

east Italy. Agriculture, Ecosystems and Environment 128 (2008) 97 –103

MAF/ISAFA, 1988. Inventario Forestale Nazionale. Sintesi metodologica e risultati. M inistero dell’Agricoltura e delle foreste. Istituto Sperimentale per l’assestamento forestale e per l’Alpicoltura, Trento.

### 236

MAF/ISAFA, 2004. Inventario nazionale delle foreste e del carbonio, preliminary results. Personal communication. Ministero dell’Agri coltura e delle foreste. Istituto Sperimentale per l’assestamento forestale e per l’Alpicoltura, Trento

MAMB, 1992. Inventario delle zone umide del territorio italiano (a cura di G. De Maria, Servizio
Conservazione Natura, Ministero dell’ambiente e del t erritorio)

Martiniello P., 2007. Biochemical parameters in a Mediterranean soil as effected by wheat

– forage rotation and irrigation. Europ. J. Agronomy 26 (2007) 198 –208

Masciandaro G., Ceccanti B., 1999. Assessing soil quality in different agro

- ecosyst ems through

biochemical and chemico

- structural properties of humic substances. Soil & Tillage Research 51 (1999) 129±137

MATT, 2002. Third National Communication under the UN Framework Convention on Climate Change. Ministry for the Environment and Territo ry. October 2002.

Monaco Stefano, Hatch D. J., Sacco D., Bertora C., Grignania C., 2008. Changes in chemical and biochemical soil properties induced by 11

- yr repeated additions of different organic materials in

maize

- based forage systems. Soil Biology & Biochemistry 40 (2008) 608 –615

Olson J.S., 1963. Energy storage and the balance of producers and decomposers in ecological

systems. Ecology 44 (2), pp. 322

- 331

Perucci p., Monaci E., Onofri A., Dischetti C., Casacci C., 2008. Changes in physico

- chemical and biochemical parameters of soil following addition of wood ash: A field experiment. Europ. J. Agronomy 28 (2008) 155 –161

Petrella F., Piazzi M. 2006

– Carbonio nei suoli degli ecosistemi semi

- naturali piemontesi.

Sherwood N.123, June 2006

Post W.M., K won K.C., 2000. Soil carbon sequestration and land

- use change: processes and potential. Global Change Biology 6, pp. 317

- 327

Puglisi E., Fragoulis G., Del Re A.A.M., Spaccini R., Piccolo A., Gigliotti G., Said

- Pullicino D.,
Trevisan M., 2008. Carbon dep osition in soil rhizosphere following amendments with compost and its soluble fractions, as evaluated by combined soil

– plant rhizobox and reporter gene systems. Chemosphere 73 (2008) 1292 –1299

Ramsar, 2005. The Ramsar Convention on Wetlands of Internation al Importance especially as

Waterfowl Habitat http://www.ramsar.org/ United Nations Educational, Scientific and Cultural Organization (UNESCO).

Rawls W.J., Brakensiek, D.L. 1985. Prediction of soil water properties for hydrologic modeling, in Proceedings of Symposium on Watershed Management, ASCE, pp. 293

- 299

Reeder J.D., Schuman G.E., Bowman R.A., 1998. Soil C and N changes on conservation reserve program lands in the Central Great Plains. Soil & Tillage Research 4 7, pp. 339

- 349.

Schulze E

- D (ed.), 2000. Carbon and nitrogen cycling in European forest ecosystems, Ecological Studies 142, 500 pp + CD, Springer: Berlin, Heidelberg, New York

### 237

Tabacchi G, De Natale F, Di Cosmo L, Floris A, Gagliano C, Gasparini P, Genchi L, Scrinzi G, Tosi V. 2007. Le stime di superficie 2005

–Parte 1. Inventario Nazionale delle Foreste e dei

Serbatoi Forestali di Carbonio. MiPAF

- Corpo Forestale dello Stato

- Ispettorato Generale, CRA

- ISAFA, TN. :1

- 413, versione 2

Triberti L., Na

stri A., Giordani G., Comellini F., Baldoni G, Toderi G., 2008. Can mineral and organic fertilization help sequestrate carbon dioxide in cropland? Europ. J. Agronomy 29 (2008)

13–20

UNECE

–FAO, Timber Committee , 2008

- Italian statement on potential wood supply, communication by national correspondent , March 2008

UNFCCC, 2005. Report of the individual review of the greenhouse gas inventory of Italy submitted in 2005 (24 November 2005). URL: http://unfccc.int/resource/docs/2005/arr/ita.pdf

.

UNFCCC, 2007. Report of the review of the initial report of Italy. FCCC/IRR/2007/ITA.
UNFCCC, 10 December 2007. URL: http://unfccc.int/res ource/docs/2007/arr/ita.pdf

.

Viaroli P., Gardi C., 2004. Censimento e caratterizzazione pedologica e vegetazionale dei “Prati Stabili” presenti nel Parco Regionale Fluviale del Taro. Relazione tecnica

- Università degli Studi di

Parma

- Dipartimento di S cienze Ambientali

Xiloyannis C., 2007. La valutazione del contenuto e composizione del carbonio organico del suolo di sistemi agricoli. Relazione tecnica

- Università degli Studi della Basilicata

- Dipartimento di
Scienze dei sistemi colturali, forestali e dell’ambiente

Waring RH, Running SW (1998). Forest ecosystems, analysis at multiple scales. Academic Press,
New York, USA.

10.7 WASTE [CRF sector 6]

Acaia et al., 2004. Emissioni atmosferiche da discariche di rifiuti in Lombardia: stato attuale e

scen ari tecnologici di riduzione. RS

–Rifiuti Solidi vol. XVIII n. 2, pp. 93

- 112.

AMA

- Comune di Roma, 1996. Nuovo impianto per l’incenerimento dei rifiuti ospedalieri. Rapporto

AMA.

Andreottola G., Cossu R., 1988. Modello matematico di produzione del biogas in uno scarico

controllato. RS

–Rifiuti Solidi vol. II n. 6, pp. 473

- 483.

ANPA, 1998. Il sistema ANPA di contabilità dei rifiuti, prime elaborazioni dei dati. Agenzia Nazionale per la Protezione dell’Ambiente.

ANPA

- FLORYS, 2000. Industria conciaria, St udio di settore. Agenzia Nazionale per la Protezione

dell’Ambiente.

ANPA

- FLORYS, 2001. Industria della carta e cartone, Studio di settore. Agenzia Nazionale per la

Protezione dell’Ambiente.

### 238

ANPA

- ONR, 1999 [a]. Primo Rapporto sui rifiuti speciali. Agenzia Nazionale per la Protezione

dell’Ambiente.

ANPA

- ONR, 1999 [b]. Secondo Rapporto sui Rifiuti Urbani e sugli Imballaggi e rifiuti di imballaggio. Agenzia Nazionale per la Protezione dell’Ambiente.

ANPA, 2001. Guida alla progettazione dei sistemi di collet tamento e depurazione delle acque reflue urbane. Agenzia Nazionale per la Protezione dell’Ambiente. Rapporto n. 1/2001.

ANPA

- ONR, 2001. I rifiuti del comparto agro

- alimentare, Studio di settore. Agenzia Nazionale per la Protezione dell’Ambiente. Rapporto n. 11/2001.

APAT, 2002. Annuario dei dati ambientali. Agenzia per la Protezione dell’Ambiente e per i servizi Tecnici. Rapporto n. 7/2002.

APAT

- ONR, several years. Rapporto Rifiuti. Agenzia per la Protezione dell’Ambiente e per i servizi

Tecnici.

ApS, 1 997. Technical Paper. Azienda Po Sangone.

Asja, 2003. Dichiarazione Ambientale 2003. Asja Ambiente Italia S.p.A., 2003.

Assobirra, several years. Rapporti Annuali e Dati Statistici. Also available on the website http://www.assobirra.it.

Assocarta, sever

al years. Rapporto Ambientali. Also available on the website http://www.assocarta.it.

AUSITRA

- Assoambiente, 1995. Impianti di trattamento dei rifiuti solidi urbani e assimilabili. Indagine a cura di Merzagora W., Ferrari S.P. Borgioli E., 1981. Nutrizione e alimentazione degli animali domestici. Ed Agricole, p. 464.

CESTAAT, 1988. Impieghi dei sottoprodotti agricoli ed agroindustriali, Vol. 1. Centro Studi sull’Agricoltura, l’Ambiente e il Territorio, edizione fuori commercio, p. 311.

CNR, 1980. Indagine sui Rifiuti Solidi Urbani in Italia. Consiglio Nazionale delle Ricerche, Progetto Finalizzato Energetica.

Colombari et al., 1998. Le emissioni di metano dalle discariche di rifiuti in Italia: stima e scenari

futuri. ENEA RT/AMB/98/30.

COOU, several year s, Consorzio Olii Usati, also available on the web

- site http://www.coou.it.

COOU, 2006, Personal Communication. Consorzio Olii Usati.

COVIRI, 2005. Relazione annuale al parlamento sullo stato dei servizi idrici, Anno 2005. Autorità di vigilanza sulle ris orse idriche e sui rifuti.

De Poli F., Pasqualini S., 1991. Landfill gas: the Italian situation. ENEA, atti del convegno Sardinia 91, Third International Landfill Symposium.

De Stefanis P., 1999. Personal communication.

### 239

De Stefanis P. et al., 1998. Gest ione dei rifiuti ad effetto serra. ENEA

- CNR, atti della Conferenza Nazionale Energia e Ambiente, Rome 25

- 18 November 1998.

Decree of President of the Republic 10 September 1982, n.915. Attuazione delle direttive

75/442/CEE relativa ai rifiuti e 76/403/CEE relativa ai rifiuti tossici e nocivi. G.U. 15 dicembre

1982, n. 343, S.O.

EC, 1975. Council Directive 1975/442/EC. Council Directive 75/442/EC of 15 July 1975 on waste framework. Official Journal of the European Communities 25 July 1975.

EC, 1976. Counc il Directive 1976/403/EC. Council Directive 76/403/EC of 6 April 1976 on treatment and disposal of PCBs and PCTs. Official Journal of the European Communities 26 April

1976.

EC, 1978. Council Directive 1978/319/EC. Council Directive 78/319/EC of 20 March 1978 on toxic and dangerous waste. Official Journal of the European Communities 31 March 1978.

EC, 1999. Council Directive 1999/31/EC. Council Directive 99/31/EC of 26 April 1999 on the landfill of waste. Official Journal of the European Communities 16 Ju ly 1999.

Ecomondo, 2006. Conference Proceedings, 10 th 

### International Trade Fair on Material and Energy Recovery and Sustainable Development, Rimini 8

–10 november 2006.

EEA, 2005. Waste management in Europe and the Landfill Directive. Background paper fr om the ETC/RWM to the ETC/ACC workshop ‘Inventories and Projections of Greenhouse Gas Emissions from Waste’, European Environment Agency, April 2005.

EMEP/CORINAIR, 2007. Atmospheric Emission Inventory Guidebook. Technical report No

16/2007.

ENI S.p.A. 2 001. Rapporto Salute Sicurezza Ambiente. FAO, several years. Food balance, available on the website http://faostat.fao.org

.

Favoino E., Cortellini L., 2001. Composting and biological treatment in southern European

c ountries: an overview. Conference Proceedings Soil and Biowaste in Southern Europe. Rome 18

- 19 January, 2001.

Favoino E., Girò F., 2001. An assessment of effective, optimised schemes for source separation of organic waste in Mediterranean districts. Confe rence Proceedings Soil and Biowaste in Southern Europe. Rome 18

- 19 January, 2001.

FEDERAMBIENTE, 1992. Analisi dei principali sistemi di smaltimento dei rifiuti solidi urbani.

FEDERAMBIENTE, 1998. Impianti di smaltimento: analisi sui termocombustori RSU

–prima edizione. Indagine a cura di Motawi A.

FEDERAMBIENTE, 2001. Impianti di smaltimento: analisi sui termoutilizzatori RU. Indagine a
cura di Morabito L., GEA n. 5/2001.

FEDERCHIMICA, several years. Rapporto Responsible Care. Federazione Nazionale de ll’Industria

Chimica.

Ferrari G., 1996. I rifiuti città per città. GEA, July 1996.

### 240

Finn L., Spencer R., 1997. Managing biofilters for consistent odor and VOC treatment. Biocycle, January 1997 Vol. 38 Iss.1.

Gaudioso et al., 1993. Emissioni in atmosfera dalle discariche di rifiuti in Italia. RS, Rifiuti Solidi vol. VII n. 5, Sept.

- Oct. 1993.

Ham, R.K., 1979. Predicting gas generation from landfills. Waste Age, 11, 50.

Hogg D., 2001. Biological treatment of waste: a solution for tomorrow. ISWA Beacon Con ference.

IPCC, 1995. IPCC Guidelines for National Greenhouse Gas Emission Inventories. Three volumes: Reference Manual, Reporting Manual, Reporting Workbook. IPCC/OECD/IEA. IPCC WG1 Technical Support Unit, Hadley Centre, Meteorological Centre, Meteorologi cal Office, Bracknell,

UK.

IPCC, 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Emission Inventories. Three volumes: Reference Manual, Reporting Manual, Reporting Guidelines and Workbook. IPCC/OECD/IEA. IPCC WG1 Technical Support Unit, Had ley Centre, Meteorological Centre, Meteorological Office, Bracknell, UK.

IPCC, 2000. Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories. IPCC National Greenhouse Gas Inventories Programme, Technical Support Unit,
Haya ma, Kanagawa, Japan.

IRSA

- CNR, 1998. Personal Communication.

ISTAT, several years [a]. Annuario Statistico. Istituto Nazionale di Statistica.

ISTAT, several years [b]. Bollettino mensile di statistica. Istituto Nazionale di Statistica.

ISTAT, several y

ears [ c ]

. Information available on the website http://www.istat.it

.

ISTAT, 1987. Approvvigionamento idrico, fognature e impianti di depurazione in Italia

–anno 1987. Collana d’informazione n. 20, ed. 1991.

ISTAT, 199 1. Statistiche ambientali 1991. Istituto nazionale di statistica.

ISTAT, 1993. Statistiche ambientali 1993. Istituto nazionale di statistica.

ISTAT, 1998 [a]. Il processo di depurazione e la qualità delle acque reflue urbane. Indagine sugli impianti di d epurazione delle acque reflue urbane, anno 1993. Istituto nazionale di statistica.

ISTAT, 1998 [b]. Caratteristiche strutturali degli impianti di depurazione delle acque reflue urbane. Indagine sugli impianti di depurazione delle acque reflue urbane, anno 1993. Istituto nazionale di

statistica.

ISTAT, 2004. Sistema di Indagini sulle Acque, SIA

–anno 1999. Istituto nazionale di statistica, also available at website http://acqua.istat.it.

Legislative Decree 5 February 1997, n. 22. Attuazione delle diretti ve 91/156/CEE sui rifiuti 91/698/CEE sui rifiuti pericolosi e 94/62/CEE sugli imballaggi e sui rifiuti di imballaggio. G.U. 15
febbraio 1997, n. 38, S.O.

### 241

Legislative Decree 11 May 1999, n. 152. Disposizioni sulla tutela delle acque dall’inquinamento e

rec epimento della direttiva 91/271/CEE concernente il trattamento delle acque reflue urbane e della direttiva 91/676/CEE relativa alla protezione delle acque dall’inquinamento provocato dai nitrati provenienti da fonti agricole. G.U. 29 maggio 1999, n. 124, S .O.

Legislative Decree 13 January 2003, n. 36. Attuazione della direttiva 1999/31/EC relativa alle
discariche di rifiuti. G.U. 12 marzo 2003, n. 59

–S.O. 40/L.

Legislative Decree 30 December 2008, n.208. Misure straordinarie in materia di risporse idric he e protezione dell’ambiente. G.U. 31 dicembre 2008, n. 304, S.O.

Masotti L., 1996. Depurazione delle acque. Edizioni Calderoni.

MATTM, several years. RSA

- Rapporto sullo stato dell’ambiente 1989, 1992, 1997, 2001. Ministero

dell’Ambiente e della Tutela del Territorio e del Mare.

MATTM, 2005. Personal Communication.

Metcalf and Eddy, 1991. Wastewater engineering: treatment, disposal and reuse. Mc Graw Hill,

third edition.

Ministerial Decree 12 July 1990. Linee Guida per il contenimento delle emissioni inquinanti degli impianti industriali e la fissazione dei valori minimi di emissione. G.U. 30 luglio 1990, n. 176.

Ministerial Decree 19 November 1997, n. 503. Regolamento recante norme per l’attuazione delle

Direttive 89/369/CEE e 89/429/CEE concernenti la prevenzione dell’inquinamento atmosferico provocato dagli impianti di incenerimento dei rifiuti urbani e la disciplina delle emissioni e delle condizioni di combustione degli impianti di incenerimento di rifiuti urbani, di rifiuti speciali non pericolo si, nonché di taluni rifiuti sanitari. G.U. 29 gennaio 1998, n. 23.

Morselli L., 1998. L’incenerimento dei rifiuti, ricognizione sulla realtà regionale. Università degli Studi di Bologna, Dipartimento di chimica industriale e dei materiali e Regione Emili a Romagna, Assessorato Territorio, Programmazione e Ambiente.

Muntoni A., Polettini A., 2002. Modelli di produzione del biogas

- limiti di applicazione e

sens i tività. Conference proceedings, Università degli Studi di Roma La Sapienza “Gestione del biogas da discarica: controllo, recupero e monitoraggio. Rome, December 2002.

Tecneco, 1972. Indagine Nazionale sullo smaltimento dei Rifiuti Solidi Urbani. Dispense 1995 Prof. Liuzzo, Università degli Studi di Roma “La Sapienza”.

TERNA, several years. Dati sta tistici sull’energia elettrica in Italia. Rete Elettrica Nazionale.

UNIC, several years. Rapporto Ambientale. Unione Nazionale Industria Conciaria.

UP, several years. Statistiche economiche, energetiche e petrolifere. Unione Petrolifera.

US EPA, 1990. A

ir emissions Species Manual, vol. I: Volatile Organic Compound Species Profiles,

Second Edition. EPA

- 450/2

- 90

- 001a (United States Environmental Protection Agency

–Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711), January 199 0.

### 242

10.8 ANNEX 1

IPCC, 2000. Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories. IPCC National Greenhouse Gas Inventories Programme, Technical Support Unit, Hayama, Kanagawa, Japan.

IPCC, 2003. Good Practice Guidanc e for Land Use, Land

- Use Change and Forestry. IPCC Technical Support Unit, Kanagawa, Japan.

10.9 ANNEX 4

ENEA, 2002 [a]. Calcolo delle emissioni di CO 2 

### dal settore energetico, metodo di riferimento IPCC.
Contaldi M., La Motta S.

ENEA, 2002 [b]. Calcolo delle emissioni di CO 2 

### , reference approach

- manuale d’uso per la compilazione del foglio elettronico 1a(b) e 1a(d) del common reference framework (CRF). La Motta
S. and Ancona P., Ente per le Nuove tecnologie, l’Energia e l’Ambiente.

ENEA, several years . Rapporto Energia Ambiente. Ente per le Nuove tecnologie, l’Energia e
l’Ambiente, Roma.

ENEL, several years. Environmental Report. ENEL. www.enel.it

.

IPCC, 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Emission Inventories. Three volumes: Reference Manual, Reporting Manual, Reporting Guidelines and Workbook. IPCC/OECD/IEA. IPCC WG1 Technical Support Unit, Hadley Centre, Meteorological Centre, Meteorological Office, Bracknell, UK.

MSE, several years [a]. Bilancio Energetico Nazionale (BEN). Ministero dello Sviluppo Economico, Direzione Generale delle Fonti di Energia ed industrie di base, also available on website http://dgerm.svilup poeconomico.gov.it/dgerm/ben.asp

MSE, several years [b]. Bollettino Petrolifero Trimestrale (BPT). Ministero dello Sviluppo

Economico.

10.10 ANNEX 6

APAT, 2003. Analisi dei fattori di emissione di CO 2 

### dal settore dei trasporti. Ilacqua M., Contaldi

M. , Rapporti n° 28/2003.

EEA, 2000. COPERT III, Computer Programme to Calculate Emissions from Road Transport

- Methodology and Emission Factors, European Environment Agency, Technical report No 49,

November 2000.

EMEP/CORINAIR, 2007. Atmospheric Emission Inventory Guidebook. Technical report No

16/2007.

IPCC, 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Emission Inventories. Three volumes: Reference Manual, Reporting Manual, Reporting Guidelines and Workbook.

IPCC/OECD/IEA. IPCC WG1 Tech nical Support Unit, Hadley Centre, Meteorological Centre, Meteorological Office, Bracknell, UK.

### 243

### 244



## ANNEX 1: KEY CATEGORIES AND UNCERTAINTY

A1.1 Introduction

The IPCC Good Practice Guidance (IPCC, 2000) recommends as good practice the identification of key categories in national GHG inventories. A key source category is defined as an emission source

t hat has a significant influence on a country’s GHG inventory in terms either of the absolute/relative level of emissions or the trend in emissions, or both. The concept of key sources was originally derived for emissions excluding the LULUCF sector and exp anded in the IPCC Good Practice Guidance for LULUCF (IPCC, 2003) to cover also LULUCF emissions by sources and removals by

sinks. In this document whenever the term key category is used, it includes both sources and sinks.

The key (source) categories have been identified for the inventory excluding LULUCF, following the guidance in GPG2000 . The key category analysis has then been repeated for the full inventory including the LULUCF categories. Key categories therefore are those found in the accumulative 95 % of the total annual emissions in the last reported year or belonging to the total trend, when ranked in descending order of magnitude. The assessment of national key categories is important because key categories should receive special consideration in t erms of methodological aspects and quality assurance and quality control

verification. Two different approaches are reported in the IPCC Good Practice Guidance according to whether or not a country has performed an uncertainty analysis of the inventory: th e Tier 1 and Tier 2. When using the Tier 1, key categories are identified by means of a pre

- determined cumulative emissions threshold, usually fixed at 95% of the total. The threshold is based on an evaluation of

several inventories and is aimed at establ ishing a general level where key categories should cover up to 90% of inventory uncertainty. If an uncertainty analysis is carried out at category level for the inventory, the Tier 2 can be used to identify key categories. The Tier 2 approach is a more de tailed analysis that builds on the Tier 1; in fact, the results of the Tier 1 are multiplied by the relative uncertainty of each source/sink category. Key categories are those that represent 95% of the uncertainty contribution, instead of applying the

pre

- determined cumulative emissions threshold. So the factors which make a source or a sink a key category have a high contribution to the total, a high contribution to the trend and a high uncertainty. If both the Tier 1 and Tier 2 are applied it is good prac tice to use the results of the Tier 2 analysis. For the Italian inventory, a key category analysis has been carried out according to both the Tier 1 and Tier 2 methods, excluding and including the LULUCF sector. National emissions have been disaggregated, as far as possible, into the categories proposed in the Good Practice; other categories have been added to reflect specific national circumstances. Both level and trend analysis have been applied. For the base year, the level assessment of key categories h as been carried out. Summary of the results of the key category analysis, for the base year and 200 7 , is reported in

Tables 1.3

–1.6 of chapter 1

. The tables indicate whether a key category derives from the level
assessment or the trend assessment, accordi ng to Tier 1, Tier 2 or both the methods. For the base year, 1

9 sources were individuated according to the Tier 1 approach, whereas 22 sources were carried out by the Tier 2. Including the LULUCF categories in the analysis, 2 5 categories were selected join tly by the Tier 1 and the Tier 2. For the year 200 7 , 17 sources were individuated by the Tier 1 approach accounting for 95% of the
total emissions, without LULUCF; for the trend 1 3 key sources were selected. Jointly for both the
Tier 1 level and trend, 29 key sources were totally individuated. Repeating the key category analysis for the full inventory including the LULUCF categories, 20 categories were individuated accounting for 95% of the total emissions and removals in 200 7 , and,

### 245

in trend assessment , 1 7 key categories are observed. Jointly for both the Tier 1 level and trend, 2 2 key categories were totally individuated. The application of the Tier 2 to the 200 7 emission levels gives as a result 2 1 key categories accounting for the 95% of the total l evels uncertainty; when applying the trend analysis the key categories de creased to 2 0 with differences with respect to the previous list. The application of the Tier 2 including the LULUCF categories results in 2 1 key categories, for the year 200 7 , accoun

ting for the 95% of the total levels uncertainty; for the trend analysis including LULUCF categories, the key categories decreased to 20 . Jointly for both the level and trend, 22 key categories were totally individuated.

A1.2 Tier 1 key category assessm ent

As described in the IPCC Good Practice Guidance (IPCC, 2000), the Tier 1 method for identifying key categories assesses the impacts of various categories on the level and the trend of the national emission inventory. Both level and trend assessment sh ould be applied to an emission GHG inventory. As concerns the level assessment, the contribution of each source or sink category to the total national inventory level is calculated as follows:

on Contributi Total Estimate Category Sink or Source Assessment Level Category Key =



### Therefore, key categories are those wh ich, when summed in descending order of magnitude, add up

to over 95% of the total emission. As far as the trend assessment is concerned, the contribution of each source and sink category’s trend can be assessed by the following equation:



## ( ) Trend Total

- Trend Category Sink or Source Assessment Level Category Sink or Source Assessment Trend Category Sink or Source

⋅ =



### where the source or sink category trend is the change in the category emissions over time, computed by subtracting the base year estimate for a generic category from the current year estimate and dividing by the current year estimate; the total t rend is the change in the total inventory emissions over time, computed by subtracting the base year estimate for the total inventory from the current year estimate and dividing by the current year estimate. As differences in trend are more significant to the overall inventory level for larger source categories, the results of the trend difference is multiplied by the results of the level assessment to provide appropriate weighting

. Thus, key categories will be those where the category trend diverges sign ificantly from the total trend, weighted by the emission level of the category. Both level and trend assessments have been carried out for the Italian GHG inventory. For the base year, a level assessment is computed.
In this section, detailed results are reported for the 200 7 inventory. The results of the Tier 1 method are shown in Table A1.1, reporting level and trend assessment without LULUCF categories, and in Table A1.2 where results of the key categories analysis with the LULUCF categories are reporte d. Regarding the trend assessment, as already mentioned, the equation reported above does not enable quantification in case the emission or removal estimates for the current year are equal to zero. In this case, since it is important to investigate into th e trend and the transparency of the estimate, the results of the level assessment or other qualitative criteria can be taken into account. In the Italian

### 2 46

inventory this occurs only for N 2 

### O from other production in the chemical industry and SF 6 

### from the

pro duction of SF 6



### .

CATEGORIES 2007 Gg

CO 2 eq Level

assessment Cumulative

Percentage CATEGORIES % Contribution

to trend Cumulative

Percentage

CO2 stationary combustion gaseous fuels 159,220 0.288 0.29 CO2 stationary combustion liquid fuels 0.38 0.38

CO2 Mobile combustion: Road Vehicles 118,721 0.215 0.50 CO2 stationary combustion gaseous fuels 0.33 0.72
CO2 stationary combustion liquid fuels 86,306 0.156 0.66 CO2 Mobile combustion: Road Vehicles 0.09 0.81

CO2 stationary combustion solid fuels 66,727 0.121 0.78 HFC, PFC substitutes for ODS 0.03 0.84
CO2 Cement production 17,914 0.032 0.81 N2O Adipic Acid 0.02 0.86
CH4 from Solid waste Disposal Sites 13,341 0.024 0.84 CO2 stationary combustion solid fuels 0.02 0.88

CH4 Enteric Fermentation in Domestic Livestock 11,027 0.020 0.86 CH4 Fugitive emissions from Oil and Gas Operations 0.01 0.89
Direct N2O Agricultural Soils 8,694 0.016 0.87 CO2 stationary combustion other fuels 0.01 0.90
Indirect N2O from Nitrogen used in agriculture 7,527 0.014 0.89 CH4 Enteric Fermentation in Domestic Livestock 0.01 0.91

HFC, PFC substitutes for ODS 6,677 0.012 0.90 CO2 Iron and Steel production 0.01 0.92
CH4 Fugitive emissions from Oil and Gas Operations 4,987 0.009 0.91 PFC Aluminium production 0.01 0.93
CO2 Mobile combustion: Waterborne Navigation 4,970 0.009 0.92 Direct N2O Agricultural Soils 0.01 0.93
CO2 stationary combustion other fuels 4,210 0.008 0.92 CO2 Fugitive emissions from Oil and Gas Operations 0.01 0.94
N2O stationary combustion 3,841 0.007 0.93 CO2 Ammonia production 0.01 0.95
N2O Manure Management 3,797 0.007 0.94 Indirect N2O from Nitrogen used in agriculture 0.01 0.95
CH4 Manure Management 3,057 0.006 0.94 N2O Nitric Acid 0.01 0.96

CO2 Limestone and Dolomite Use 2,513 0.005 0.95 CH4 from Solid waste Disposal Sites 0.00 0.96
CH4 Emissions from Wastewater Handling 2,435 0.004 0.95 CO2 Mobile combustion: Waterborne Navigation 0.00 0.97
CO2 Lime production 2,434 0.004 0.96 CO2 Mobile combustion: Aircraft 0.00 0.97

CO2 Mobile combustion: Aircraft 2,428 0.004 0.96 CO2 Cement production 0.00 0.97
CO2 Fugitive emissions from Oil and Gas Operations 2,176 0.004 0.96 CH4 Manure Management 0.00 0.98
N2O Emissions from Wastewater Handling 2,019 0.004 0.97 CH4 Mobile combustion: Road Vehicles 0.00 0.98

CO2 Mobile combustion: Other 1,990 0.004 0.97 N2O Manure Management 0.00 0.98
CO2 Other industrial processes 1,931 0.003 0.97 HFC-23 from HCFC-22 Manufacture and HFCs fugitive 0.00 0.98
N2O from animal production 1,570 0.003 0.98 N2O Mobile combustion: Road Vehicles 0.00 0.99
CH4 from Rice production 1,523 0.003 0.98 CO2 Emissions from solvent use 0.00 0.99
CO2 Iron and Steel production 1,483 0.003 0.98 CH4 Emissions from Wastewater Handling 0.00 0.99

N2O Mobile combustion: Road Vehicles 1,420 0.003 0.99 CO2 Emissions from Waste Incineration 0.00 0.99

CO2 Emissions from solvent use 1,361 0.002 0.99 N2O from animal production 0.00 0.99

N2O Nitric Acid 1,109 0.002 0.99 CH4 stationary combustion 0.00 0.99
CH4 stationary combustion 963 0.002 0.99 CO2 Lime production 0.00 0.99
N2O Adipic Acid 782 0.001 0.99 N2O stationary combustion 0.00 0.99

N2O Emissions from solvent use 772 0.001 0.99 CH4 from Rice production 0.00 1.00
CO2 Ammonia production 649 0.001 1.00 PFC, HFC, SF6 Semiconductor manufacturing 0.00 1.00

CH4 Mobile combustion: Road Vehicles 415 0.001 1.00 SF6 Production of SF6 0.00 1.00

SF6 Electrical Equipment 337 0.001 1.00 SF6 Electrical Equipment 0.00 1.00

CH4 Emissions from Waste Incineration 271 0.000 1.00 CH4 Emissions from Waste Incineration 0.00 1.00

CO2 Emissions from Waste Incineration 270 0.000 1.00 N2O Emissions from solvent use 0.00 1.00
PFC Aluminium production 200 0.000 1.00 CO2 Other industrial processes 0.00 1.00
PFC, HFC, SF6 Semiconductor manufacturing 129 0.000 1.00 SF6 Magnesium production 0.00 1.00

N2O Mobile combustion: Other 123 0.000 1.00 CH4 Industrial Processes 0.00 1.00

N2O Emissions from Waste Incineration 120 0.000 1.00 CH4 Fugitive emissions from Coal Mining and Handling 0.00 1.00

CH4 Fugitive emissions from Coal Mining and Handling 84 0.000 1.00 CO2 Mobile combustion: Other 0.00 1.00

CH4 Industrial Processes 65 0.000 1.00 CO2 Limestone and Dolomite Use 0.00 1.00
SF6 Magnesium production 54 0.000 1.00 N2O Emissions from Waste Incineration 0.00 1.00
N2O Mobile combustion: Waterborne Navigation 36 0.000 1.00 N2O Emissions from Wastewater Handling 0.00 1.00
CH4 Mobile combustion: Waterborne Navigation 29 0.000 1.00 N2O Mobile combustion: Other 0.00 1.00

N2O Mobile combustion: Aircraft 21 0.000 1.00 N2O Other industrial processes 0.00 1.00

HFC-23 from HCFC-22 Manufacture and HFCs fugitive 18 0.000 1.00 N2O Mobile combustion: Waterborne Navigation 0.00 1.00
CH4 Agricultural Residue Burning 12.8 0.000 1.00 N2O Mobile combustion: Aircraft 0.00 1.00

CH4 Emissions from Other Waste 4.6 0.000 1.00 CH4 Emissions from Other Waste 0.00 1.00
N2O Agricultural Residue Burning 4.1 0.000 1.00 CH4 Mobile combustion: Waterborne Navigation 0.00 1.00

CH4 Mobile combustion: Other 3.5 0.000 1.00 CH4 Mobile combustion: Other 0.00 1.00

CH4 Mobile combustion: Aircraft 1.5 0.000 1.00 CH4 Agricultural Residue Burning 0.00 1.00
N2O Fugitive emissions from Oil and Gas Operations 1.4 0.000 1.00 CH4 Mobile combustion: Aircraft 0.00 1.00

N2O Other industrial processes 0.0 0.000 1.00 N2O Agricultural Residue Burning 0.00 1.00

SF6 Production of SF6 0.0 0.000 1.00 N2O Fugitive emissions from Oil and Gas Operations 0.00 1.00 TIER 1

Table A1.1 Results of the key categories analysis (Tier1) without LULUCF categories . Year 2007

### 247 CATEGORIES 2007 Gg

CO 2 eq Level

assessment Cumulative

Percentage CATEGORIES % Contribution

to trend Cumulative

Percentage

CO2 stationary combustion gaseous fuels 159,220 0.253 0.25 CO2 stationary combustion liquid fuels 0.35 0.35

CO2 Mobile combustion: Road Vehicles 118,721 0.188 0.44 CO2 stationary combustion gaseous fuels 0.30 0.66

CO2 stationary combustion liquid fuels 86,306 0.137 0.58 CO2 Mobile combustion: Road Vehicles 0.08 0.74
CO2 stationary combustion solid fuels 66,727 0.106 0.68 CO2 Land converted to Grassland 0.03 0.77
CO2 Forest land remaining Forest Land 53,384 0.085 0.77 CO2 Cropland remaining Cropland 0.03 0.80

CO2 Cement production 17,914 0.028 0.80 HFC, PFC substitutes for ODS 0.03 0.83
CH4 from Solid waste Disposal Sites 13,341 0.021 0.82 N2O Adipic Acid 0.02 0.85

CH4 Enteric Fermentation in Domestic Livestock 11,027 0.017 0.84 CO2 Forest land remaining Forest Land 0.01 0.87
CO2 Cropland remaining Cropland 10,960 0.017 0.85 CO2 stationary combustion solid fuels 0.01 0.88

Direct N2O Agricultural Soils 8,694 0.014 0.87 CH4 Fugitive emissions from Oil and Gas Operations 0.01 0.89

CO2 Land converted to Grassland 7,760 0.012 0.88 CO2 stationary combustion other fuels 0.01 0.90
Indirect N2O from Nitrogen used in agriculture 7,527 0.012 0.89 CH4 Enteric Fermentation in Domestic Livestock 0.01 0.91

HFC, PFC substitutes for ODS 6,677 0.011 0.90 CO2 Iron and Steel production 0.01 0.92
CH4 Fugitive emissions from Oil and Gas Operations 4,987 0.008 0.91 PFC Aluminium production 0.01 0.93

CO2 Mobile combustion: Waterborne Navigation 4,970 0.008 0.92 Direct N2O Agricultural Soils 0.01 0.93
CO2 stationary combustion other fuels 4,210 0.007 0.92 CO2 Fugitive emissions from Oil and Gas Operations 0.01 0.94

N2O stationary combustion 3,841 0.006 0.93 Indirect N2O from Nitrogen used in agriculture 0.01 0.95
N2O Manure Management 3,797 0.006 0.94 CO2 Ammonia production 0.01 0.95

CO2 Land converted to Settlements 3,181 0.005 0.94 N2O Nitric Acid 0.01 0.96

CH4 Manure Management 3,057 0.005 0.95 CO2 Land converted to Forest Land 0.01 0.96

CO2 Limestone and Dolomite Use 2,513 0.004 0.95 CH4 from Solid waste Disposal Sites 0.00 0.97

CH4 Emissions from Wastewater Handling 2,435 0.004 0.95 CO2 Mobile combustion: Waterborne Navigation 0.00 0.97
CO2 Lime production 2,434 0.004 0.96 CO2 Mobile combustion: Aircraft 0.00 0.97

CO2 Mobile combustion: Aircraft 2,428 0.004 0.96 CH4 Manure Management 0.00 0.98

CO2 Land converted to Forest Land 2,204 0.003 0.96 CO2 Cement production 0.00 0.98
CO2 Fugitive emissions from Oil and Gas Operations 2,176 0.003 0.97 CH4 Mobile combustion: Road Vehicles 0.00 0.98

N2O Emissions from Wastewater Handling 2,019 0.003 0.97 N2O Manure Management 0.00 0.98

CO2 Mobile combustion: Other 1,990 0.003 0.97 HFC-23 from HCFC-22 Manufacture and HFCs fugitive 0.00 0.98

CO2 Other industrial processes 1,931 0.003 0.98 CO2 Emissions from solvent use 0.00 0.99
N2O from animal production 1,570 0.002 0.98 N2O Mobile combustion: Road Vehicles 0.00 0.99

CH4 from Rice production 1,523 0.002 0.98 CO2 Emissions from Waste Incineration 0.00 0.99
CO2 Iron and Steel production 1,483 0.002 0.98 CH4 Emissions from Wastewater Handling 0.00 0.99

N2O Mobile combustion: Road Vehicles 1,420 0.002 0.99 N2O from animal production 0.00 0.99

CO2 Emissions from solvent use 1,361 0.002 0.99 CH4 stationary combustion 0.00 0.99

N2O Nitric Acid 1,109 0.002 0.99 CO2 Lime production 0.00 0.99

CH4 stationary combustion 963 0.002 0.99 CO2 Land converted to Settlements 0.00 0.99
N2O Adipic Acid 782 0.001 0.99 N2O stationary combustion 0.00 0.99

N2O Emissions from solvent use 772 0.001 1.00 CH4 from Rice production 0.00 1.00
CO2 Ammonia production 649 0.001 1.00 PFC, HFC, SF6 Semiconductor manufacturing 0.00 1.00

CH4 Mobile combustion: Road Vehicles 415 0.001 1.00 SF6 Production of SF6 0.00 1.00

SF6 Electrical Equipment 337 0.001 1.00 SF6 Electrical Equipment 0.00 1.00

CH4 Emissions from Waste Incineration 271 0.000 1.00 CH4 Emissions from Waste Incineration 0.00 1.00

CO2 Emissions from Waste Incineration 270 0.000 1.00 N2O Emissions from solvent use 0.00 1.00
PFC Aluminium production 200 0.000 1.00 CO2 Other industrial processes 0.00 1.00

CH4 Forest land remaining Forest Land 197 0.000 1.00 SF6 Magnesium production 0.00 1.00
PFC, HFC, SF6 Semiconductor manufacturing 129 0.000 1.00 CH4 Industrial Processes 0.00 1.00

N2O Mobile combustion: Other 123 0.000 1.00 CH4 Fugitive emissions from Coal Mining and Handling 0.00 1.00

N2O Emissions from Waste Incineration 120 0.000 1.00 CO2 Mobile combustion: Other 0.00 1.00
CH4 Fugitive emissions from Coal Mining and Handling 84 0.000 1.00 CH4 Forest land remaining Forest Land 0.00 1.00

CH4 Industrial Processes 65 0.000 1.00 CO2 Limestone and Dolomite Use 0.00 1.00
SF6 Magnesium production 54 0.000 1.00 N2O Emissions from Waste Incineration 0.00 1.00

N2O Mobile combustion: Waterborne Navigation 36 0.000 1.00 N2O Emissions from Wastewater Handling 0.00 1.00
CH4 Mobile combustion: Waterborne Navigation 29 0.000 1.00 N2O Mobile combustion: Other 0.00 1.00

N2O Mobile combustion: Aircraft 21 0.000 1.00 N2O Other industrial processes 0.00 1.00

N2O Forest land remaining Forest Land 20 0.000 1.00 N2O Mobile combustion: Waterborne Navigation 0.00 1.00
HFC-23 from HCFC-22 Manufacture and HFCs fugitive 18 0.000 1.00 N2O Mobile combustion: Aircraft 0.00 1.00

CH4 Agricultural Residue Burning 12.8 0.000 1.00 N2O Forest land remaining Forest Land 0.00 1.00

CH4 Emissions from Other Waste 4.6 0.000 1.00 CH4 Emissions from Other Waste 0.00 1.00

N2O Agricultural Residue Burning 4.1 0.000 1.00 CH4 Mobile combustion: Waterborne Navigation 0.00 1.00

CH4 Mobile combustion: Other 3.5 0.000 1.00 CH4 Mobile combustion: Other 0.00 1.00

CH4 Mobile combustion: Aircraft 1.5 0.000 1.00 CH4 Agricultural Residue Burning 0.00 1.00

N2O Fugitive emissions from Oil and Gas Operations 1.4 0.000 1.00 CH4 Mobile combustion: Aircraft 0.00 1.00
N2O Other industrial processes 0.0 0.000 1.00 N2O Agricultural Residue Burning 0.00 1.00

SF6 Production of SF6 0.0 0.000 1.00 N2O Fugitive emissions from Oil and Gas Operations 0.00 1.00
CO2 Land converted to Cropland 0.0 0.000 1.00 CO2 Land converted to Cropland 0.00 1.00

N2O Land converted to Cropland 0.0 0.000 1.00 N2O Land converted to Cropland 0.00 1.00 TIER 1

Table A1.2 Results of the key categories analysis (Tier1) with LULUCF categories . Year 2007



### The application of the Tier 1, excluding LULUC F categories, gives as a result 17 key sources accounting for the 95% of the total levels; when applying the trend analysis, excluding LULUCF categories, the key sources decreased to 1 4 with some differences with respect to the previous list
(Table A1.1).

The Tier 1 key category level assessment, repeated for the full inventory including the LULUCF categories, results in 20 key categories (sources and sinks) and 1 7 key categories outcome from the trend analysis, with LULUCF categories, presenting some diffe rences with respect to the list resulting from level assessment (Table A1.2).

### 248

A1.3 Uncertainty assessment (IPCC Tier 1)

The Tier 2 method for the identification of key categories implies the assessment of the uncertainty analysis to an emission inventor y. As already mentioned, the IPCC Tier 1 has been applied to the Italian GHG inventory to estimate uncertainties in national greenhouse gas inventories for the base year and the last submitted year. In this section, detailed results are reported for the 20 07 inventory. The results of the approach are reported in Table A1.3, for the year 200 7 , excluding the LULUCF

sector. The uncertainty analysis has also been repeated including the LULUCF sector in the national totals.

Details on the Tier 1 method used for LULUCF are described in the relevant chapter, chapter 7; in the following Table A1.4, the results by category, concerning only CO 2 

### emissions and removals, are reported whereas in Table A1.5, the results include CO 2 

### , CH 4 

### , N 2 

### O emissions and removals. Finally , in Table A1.6 figures of inventory total uncertainty, including the LULUCF sector, are

shown.

Tier 1 Uncertainty calculation and reporting

IPCC Gas Base year Year t Activity data Emission factor Combined Combined Type A Type B Uncertainty Uncertainty Uncertainty
Sorce category emissions emissions uncertainty uncertainty uncertainty uncertainty sensitivity sensitivity in trend in in trend in introduced into

1990 2007 as % of total national emissions national emissions the trend in total
Gg Gg national emissions introduced by introduced by national emissions in year t emission factor activity data
uncertainty uncertainty

CO2 stationary combustion liquid fuels CO2 153,467 86,306 3% 3 % 0.042 0.007 -0.151 0.167 -0.005 0.007 0.008 CO2 stationary combustion solid fuels CO2 59,395 66,727 3% 3 % 0.042 0.005 0.006 0.129 0.000 0.005 0.005
CO2 stationary combustion gaseous fuels CO2 85,066 159,220 3% 3 % 0.042 0.012 0.132 0.308 0.004 0.013 0.014
CO2 stationary combustion other fuels CO2 1,779 4,210 3% 3 % 0.042 0.000 0.004 0.008 0.000 0.000 0.000
CH4 stationary combustion CH4 647 963 3% 50% 0.501 0.001 0.001 0.002 0.000 0.000 0.000 N2O stationary combustion N2O 3,434 3,841 3% 50% 0.501 0.003 0.000 0.007 0.000 0.000 0.000

CO2 Mobile combustion: Road Vehicles CO2 93,387 118,721 3% 3 % 0.042 0.009 0.036 0.230 0.001 0.010 0.010

CH4 Mobile combustion: Road Vehicles CH4 867 415 3% 40% 0.401 0.000 -0.001 0.001 0.000 0.000 0.000

N2O Mobile combustion: Road Vehicles N2O 996 1,420 3% 50% 0.501 0.001 0.001 0.003 0.000 0.000 0.000 CO2 Mobile combustion: Waterborne Navigation CO2 5,420 4,970 3% 3 % 0.042 0.000 -0.002 0.010 0.000 0.000 0.000
CH4 Mobile combustion: Waterborne Navigation CH4 29 29 3% 50% 0.501 0.000 0.000 0.000 0.000 0.000 0.000
N2O Mobile combustion: Waterborne Navigation N2O 39 36 3% 100% 1.000 0.000 0.000 0.000 0.000 0.000 0.000

CO2 Mobile combustion: Aircraft CO2 1,613 2,428 3% 3 % 0.042 0.000 0.001 0.005 0.000 0.000 0.000

CH4 Mobile combustion: Aircraft CH4 1 2 3% 50% 0.501 0.000 0.000 0.000 0.000 0.000 0.000

N2O Mobile combustion: Aircraft N2O 14 21 3% 100% 1.000 0.000 0.000 0.000 0.000 0.000 0.000

CO2 Mobile combustion: Other CO2 1,894 1,990 3% 5 % 0.058 0.000 0.000 0.004 0.000 0.000 0.000

CH4 Mobile combustion: Other CH4 5 4 3% 50% 0.501 0.000 0.000 0.000 0.000 0.000 0.000

N2O Mobile combustion: Other N2O 131 123 3% 100% 1.000 0.000 0.000 0.000 0.000 0.000 0.000
CH4 Fugitive emissions from Coal Mining and Handling CH4 122 84 3% 200% 2.000 0.000 0.000 0.000 0.000 0.000 0.000
CO2 Fugitive emissions from Oil and Gas Operations CO2 3,341 2,176 3% 25% 0.252 0.001 -0.003 0.004 -0.001 0.000 0.001 CH4 Fugitive emissions from Oil and Gas Operations CH4 7,298 4,987 3% 25% 0.252 0.002 -0.005 0.010 -0.001 0.000 0.001
N2O Fugitive emissions from Oil and Gas Operations N2O 1 1 3% 25% 0.252 0.000 0.000 0.000 0.000 0.000 0.000
CO2 Cement production CO2 16,084 17,914 3% 10% 0.104 0.003 0.001 0.035 0.000 0.001 0.001
CO2 Lime production CO2 2,042 2,434 3% 10% 0.104 0.000 0.000 0.005 0.000 0.000 0.000

CO2 Limestone and Dolomite Use CO2 2,375 2,513 3% 10% 0.104 0.000 0.000 0.005 0.000 0.000 0.000
CO2 Iron and Steel production CO2 3,124 1,483 3% 10% 0.104 0.000 -0.004 0.003 0.000 0.000 0.000
CO2 Ammonia production CO2 1,710 649 3% 10% 0.104 0.000 -0.002 0.001 0.000 0.000 0.000
CO2 Other industrial processes CO2 1,856 1,931 3% 10% 0.104 0.000 0.000 0.004 0.000 0.000 0.000 N2O Adipic Acid N2O 4,579 782 3% 10% 0.104 0.000 -0.008 0.002 -0.001 0.000 0.001

N2O Nitric Acid N2O 2,086 1,109 3% 10% 0.104 0.000 -0.002 0.002 0.000 0.000 0.000
N2O Other industrial processes N2O 11 0 3% 10% 0.104 0.000 0.000 0.000 0.000 0.000 0.000

CH4 Industrial Processes CH4 108 65 3% 50% 0.501 0.000 0.000 0.000 0.000 0.000 0.000 PFC Aluminium production PFC 1,673 200 5% 10% 0.112 0.000 -0.003 0.000 0.000 0.000 0.000
SF6 Magnesium production SF6 0 54 5% 5 % 0.071 0.000 0.000 0.000 0.000 0.000 0.000
SF6 Electrical Equipment SF6 213 337 5% 10% 0.112 0.000 0.000 0.001 0.000 0.000 0.000

SF6 Production of SF6 SF6 120 0 5% 10% 0.112 0.000 0.000 0.000 0.000 0.000 0.000
PFC, HFC, SF6 Semiconductor manufacturing PFC-HFC 0 129 30% 50% 0.583 0.000 0.000 0.000 0.000 0.000 0.000

HFC, PFC substitutes for ODS HFC 134 6,677 30% 50% 0.583 0.007 0.013 0.013 0.006 0.005 0.008
HFC-23 from HCFC-22 Manufacture and HFCs fugitive HFC 351 18 5% 10% 0.112 0.000 -0.001 0.000 0.000 0.000 0.000

CH4 Enteric Fermentation in Domestic Livestock CH4 12,179 11,027 20% 20% 0.283 0.006 -0.004 0.021 -0.001 0.006 0.006
CH4 Manure Management CH4 3,462 3,057 20% 100% 1.020 0.006 -0.001 0.006 -0.001 0.002 0.002
N2O Manure Management N2O 3,921 3,797 20% 100% 1.020 0.007 -0.001 0.007 -0.001 0.002 0.002
CH4 Agricultural Residue Burning CH4 13 13 50% 20% 0.539 0.000 0.000 0.000 0.000 0.000 0.000 N2O Agricultural Residue Burning N2O 4 4 50% 20% 0.539 0.000 0.000 0.000 0.000 0.000 0.000
Direct N2O Agricultural Soils N2O 9,581 8,694 20% 100% 1.020 0.016 -0.003 0.017 -0.003 0.005 0.006
Indirect N2O from Nitrogen used in agriculture N2O 8,118 7,527 20% 100% 1.020 0.014 -0.002 0.015 -0.002 0.004 0.005
CH4 from Rice production CH4 1,562 1,523 3% 20% 0.202 0.001 0.000 0.003 0.000 0.000 0.000 N2O from animal production N2O 1,736 1,570 20% 100% 1.020 0.003 -0.001 0.003 -0.001 0.001 0.001
CH4 from Solid waste Disposal Sites CH4 13,298 13,341 20% 30% 0.361 0.009 -0.002 0.026 -0.001 0.007 0.007
CH4 Emissions from Wastewater Handling CH4 1,988 2,435 100% 30% 1.044 0.005 0.001 0.005 0.000 0.007 0.007
N2O Emissions from Wastewater Handling N2O 1,864 2,019 30% 30% 0.424 0.002 0.000 0.004 0.000 0.002 0.002

CO2 Emissions from Waste Incineration CO2 537 270 5% 25% 0.255 0.000 -0.001 0.001 0.000 0.000 0.000

CH4 Emissions from Waste Incineration CH4 161 271 5% 20% 0.206 0.000 0.000 0.001 0.000 0.000 0.000

N2O Emissions from Waste Incineration N2O 88 120 5% 100% 1.001 0.000 0.000 0.000 0.000 0.000 0.000

CH4 Emissions from Other Waste CH4 0 5 10% 100% 1.005 0.000 0.000 0.000 0.000 0.000 0.000

CO2 Emissions from solvent use CO2 1,598 1,361 30% 50% 0.583 0.001 -0.001 0.003 0.000 0.001 0.001

N2O Emissions from solvent use N2O 796 772 50% 10% 0.510 0.001 0.000 0.001 0.000 0.001 0.001

TOTAL 516,318 552,771 0.033 0.026 Table A1.3 Results of the uncertainty analysis excluding LULUCF (Tier1) . Year 2007

### 249

Tier 1 Uncertainty calculation and reporting: CO 2

IPCC Gas Base year Year t Type A Type B

Sorce category emissions emissions sensitivity sensitivity

1990 2007

Gg CO 2 eq Gg CO 2 eq % % % % % % % % %

A. Forest Land CO 2 -53,549 -55,588 30% 54% 61% 48% -1% 82% -1% 35% 35%

B. Cropland CO 2 -16,876 -10,960 75% 75% 106% 16% -10% 16% -8% 17% 19%
- living biomass CO 2 -17,206 -11,290 75% 75% 106% 17% -10% 17% -8% 18% 19%

- soils CO 2 330 330 75% 75% 106% 0% 0% 0 % 0 % 1% 1 %

C. Grassland CO 2 -385 -7,760 75% 75% 106% 12% 11% 11% 8 % 12% 15% - living biomass CO 2 62 0 75% 75% 106% 0% 0% 0 % 0 % 0% 0 %

- soils CO 2 -447 0 75% 75% 106% 0% -1% 0 % -1% 0% 1 %

D. Wetlands CO 2 0 0 0 % 0% 0% 0 % 0 % 0% 0 %

E. Settlements CO 2 3,160 3,181 75% 75% 106% 5% 0% 5 % 0 % 5% 5 %

F. Other Land CO 2 0 0 0 % 0% 0% 0 % 0 % 0% 0 %

G. Other CO 2 0 0 0 % 0% 0% 0 % 0 % 0% 0 %

TOTAL -67,651 -71,127 52% 43% Uncertainty in trend in LULUCF
emissions introduced by emission
factor uncertainty Uncertainty in trend in LULUCF

emissions introduced by activity
data uncertainty Uncertainty introduced

into trend in total

LULUCF emissions Combined uncertainty as %

of total LULUCF emissions in
the year t Combined
uncertainty Emission factor
uncertainty Activity data
uncertainty

a the combined uncertainty has been calculated as explained in Cha pter 7, 7.2.3 Uncertainty and time series consistency; in order to provide estimate of uncertainties in trend in national emissions introduced by emission factor and activity data, values for the uncertainty related to activity data and

emission factor hav

e been assigned by expert judgment, taking into account the final combined uncertainty Table A1.4 Results of the uncertainty analysis for the LULUCF sector

– CO 2 (Tier1)



### Tier 1 Uncertainty calculation and reporting: CO 2 

### +CH 4 

### +N 2 

### O

IPCC Gas

Sorce category Base year

emissions Year t

emissions Type A sensitivity Type B

sensitivity

1990 2007 Activity

data
uncertainty Emission

factor
uncertainty Combined

uncertainty Combined

uncertainty

as % of

total

LULUCF

emissions
in the year

t Uncertainty

in trend in

LULUCF

e missions

introduced by emission

factor
uncertainty Uncertainty

in trend in

LULUCF

emissions

introduced by activity

data
uncertainty Uncertainty

introduced

into trend

in total

LULUCF

emissions

Gg CO 2 eq G g CO 2 eq % % % % % % % % %

A. Forest Land CO 2 - 53,392

- 53,392 30% 54% 61% 49% 0% 79% 0% 34% 34%

B. Cropland CO 2 - 16,876

- 16,876 75% 75% 106% 27% 0% 25% 0% 27% 27%

- living biomass CO 2 - 17,206

- 17,206 75% 75% 106% 27% 0% 25% 0% 27% 27%

- soils CO 2 330 330 75% 75% 106% 1% 0% 0% 0% 1% 1%

C. Grassland CO 2 - 385

- 385 75% 75% 106% 1% 0% 1% 0% 1% 1%

- living biomass CO 2 62 62 75% 75% 106% 0% 0% 0% 0% 0% 0%

- soils CO 2 - 447

- 447 75% 75% 106% 1% 0% 1% 0% 1% 1%

D. Wetlands CO 2 0 0 0% 0% 0 % 0% 0% 0% 0%

E. Settlements CO 2 3,160 3,160 75% 75% 106% 5% 0% 5% 0% 5% 5%

F. Other Land CO 2 0 0 0% 0% 0% 0% 0% 0% 0%

G. Other CO 2 0 0 0% 0% 0% 0% 0% 0% 0%

TOTAL

- 67,493

- 67,493 56% 43%
Table A1.5 Results of the uncertainty analysis f or the LULUCF sector

– CO 2, CH 4 , N 2 O (Tier1)

### 250

Tier 1 Uncertainty calculation and reporting

IPCC Gas Base year Year t Activity data Emission factor Combined Combined Type A Type B Uncertainty Uncertainty Uncertainty Sorce category emissions emissions uncertainty uncertainty uncertainty uncertainty sensitivity sensitivity in trend in in trend in introduced into

1990 2007 as % of total national emissions national emissions the trend in total Gg Gg national emissions introduced by introduced by national emissions

in year t emission factor activity data uncertainty uncertainty

CO2 stationary combustion liquid fuels CO2 153,467 86,306 3% 3% 0.042 0.006 -0.131 0.146 -0.004 0.006 0.007
CO2 stationary combustion solid fuels CO2 59,395 66,727 3% 3% 0.042 0.004 0.006 0.113 0.000 0.005 0.005 CO2 stationary combustion gaseous fuels CO2 85,066 159,220 3% 3% 0.042 0.011 0.116 0.270 0.003 0.011 0.012
CO2 stationary combustion other fuels CO2 1,779 4,210 3% 3% 0.042 0.000 0.004 0.007 0.000 0.000 0.000 CH4 stationary combustion CH4 647 963 3% 50% 0.501 0.001 0.000 0.002 0.000 0.000 0.000
N2O stationary combustion N2O 3,434 3,841 3% 50% 0.501 0.003 0.000 0.007 0.000 0.000 0.000

CO2 Mobile combustion: Road Vehicles CO2 93,387 118,721 3% 3% 0.042 0.008 0.032 0.201 0.001 0.009 0.009

CH4 Mobile combustion: Road Vehicles CH4 867 415 3% 40% 0.401 0.000 -0.001 0.001 0.000 0.000 0.000

N2O Mobile combustion: Road Vehicles N2O 996 1,420 3% 50% 0.501 0.001 0.001 0.002 0.000 0.000 0.000
CO2 Mobile combustion: Waterborne Navigation CO2 5,420 4,970 3% 3% 0.042 0.000 -0.001 0.008 0.000 0.000 0.000 CH4 Mobile combustion: Waterborne Navigation CH4 29 29 3% 50% 0.501 0.000 0.000 0.000 0.000 0.000 0.000
N2O Mobile combustion: Waterborne Navigation N2O 39 36 3% 100% 1.000 0.000 0.000 0.000 0.000 0.000 0.000

CO2 Mobile combustion: Aircraft CO2 1,613 2,428 3% 3% 0.042 0.000 0.001 0.004 0.000 0.000 0.000

CH4 Mobile combustion: Aircraft CH4 1 2 3% 50% 0.501 0.000 0.000 0.000 0.000 0.000 0.000

N2O Mobile combustion: Aircraft N2O 14 21 3% 100% 1.000 0.000 0.000 0.000 0.000 0.000 0.000

CO2 Mobile combustion: Other CO2 1,894 1,990 3% 5% 0.058 0.000 0.000 0.003 0.000 0.000 0.000

CH4 Mobile combustion: Other CH4 5 4 3% 50% 0.501 0.000 0.000 0.000 0.000 0.000 0.000

N2O Mobile combustion: Other N2O 131 123 3% 100% 1.000 0.000 0.000 0.000 0.000 0.000 0.000 CH4 Fugitive emissions from Coal Mining and Handling CH4 122 84 3% 200% 2.000 0.000 0.000 0.000 0.000 0.000 0.000
CO2 Fugitive emissions from Oil and Gas Operations CO2 3,341 2,176 3% 25% 0.252 0.001 -0.002 0.004 -0.001 0.000 0.001 CH4 Fugitive emissions from Oil and Gas Operations CH4 7,298 4,987 3% 25% 0.252 0.002 -0.005 0.008 -0.001 0.000 0.001
N2O Fugitive emissions from Oil and Gas Operations N2O 1 1 3% 25% 0.252 0.000 0.000 0.000 0.000 0.000 0.000 CO2 Cement production CO2 16,084 17,914 3% 10% 0.104 0.003 0.001 0.030 0.000 0.001 0.001
CO2 Lime production CO2 2,042 2,434 3% 10% 0.104 0.000 0.000 0.004 0.000 0.000 0.000

CO2 Limestone and Dolomite Use CO2 2,375 2,513 3% 10% 0.104 0.000 0.000 0.004 0.000 0.000 0.000
CO2 Iron and Steel production CO2 3,124 1,483 3% 10% 0.104 0.000 -0.003 0.003 0.000 0.000 0.000 CO2 Ammonia production CO2 1,710 649 3% 10% 0.104 0.000 -0.002 0.001 0.000 0.000 0.000
CO2 Other industrial processes CO2 1,856 1,931 3% 10% 0.104 0.000 0.000 0.003 0.000 0.000 0.000 N2O Adipic Acid N2O 4,579 782 3% 10% 0.104 0.000 -0.007 0.001 -0.001 0.000 0.001

N2O Nitric Acid N2O 2,086 1,109 3% 10% 0.104 0.000 -0.002 0.002 0.000 0.000 0.000 N2O Other industrial processes N2O 11 0 3% 10% 0.104 0.000 0.000 0.000 0.000 0.000 0.000

CH4 Industrial Processes CH4 108 65 3% 50% 0.501 0.000 0.000 0.000 0.000 0.000 0.000 PFC Aluminium production PFC 1,673 200 5% 10% 0.112 0.000 -0.003 0.000 0.000 0.000 0.000
SF6 Magnesium production SF6 0 54 5% 5% 0.071 0.000 0.000 0.000 0.000 0.000 0.000 SF6 Electrical Equipment SF6 213 337 5% 10% 0.112 0.000 0.000 0.001 0.000 0.000 0.000

SF6 Production of SF6 SF6 120 0 5% 10% 0.112 0.000 0.000 0.000 0.000 0.000 0.000 PFC, HFC, SF6 Semiconductor manufacturing PFC-HFC 0 129 30% 50% 0.583 0.000 0.000 0.000 0.000 0.000 0.000

HFC, PFC substitutes for ODS HFC 134 6,677 30% 50% 0.583 0.006 0.011 0.011 0.006 0.005 0.007 HFC-23 from HCFC-22 Manufacture and HFCs fugitive HFC 351 18 5% 10% 0.112 0.000 -0.001 0.000 0.000 0.000 0.000

CH4 Enteric Fermentation in Domestic Livestock CH4 12,179 11,027 20% 20% 0.283 0.005 -0.003 0.019 -0.001 0.005 0.005 CH4 Manure Management CH4 3,462 3,057 20% 100% 1.020 0.005 -0.001 0.005 -0.001 0.001 0.002
N2O Manure Management N2O 3,921 3,797 20% 100% 1.020 0.006 -0.001 0.006 -0.001 0.002 0.002 CH4 Agricultural Residue Burning CH4 13 13 50% 20% 0.539 0.000 0.000 0.000 0.000 0.000 0.000
N2O Agricultural Residue Burning N2O 4 4 50% 20% 0.539 0.000 0.000 0.000 0.000 0.000 0.000 Direct N2O Agricultural Soils N2O 9,581 8,694 20% 100% 1.020 0.014 -0.003 0.015 -0.003 0.004 0.005
Indirect N2O from Nitrogen used in agriculture N2O 8,118 7,527 20% 100% 1.020 0.012 -0.002 0.013 -0.002 0.004 0.004 CH4 from Rice production CH4 1,562 1,523 3% 20% 0.202 0.000 0.000 0.003 0.000 0.000 0.000
N2O from animal production N2O 1,736 1,570 20% 100% 1.020 0.003 0.000 0.003 0.000 0.001 0.001 CH4 from Solid waste Disposal Sites CH4 13,298 13,341 20% 30% 0.361 0.008 -0.001 0.023 0.000 0.006 0.006
CH4 Emissions from Wastewater Handling CH4 1,988 2,435 100% 30% 1.044 0.004 0.001 0.004 0.000 0.006 0.006 N2O Emissions from Wastewater Handling N2O 1,864 2,019 30% 30% 0.424 0.001 0.000 0.003 0.000 0.001 0.001

CO2 Emissions from Waste Incineration CO2 537 270 5% 25% 0.255 0.000 -0.001 0.000 0.000 0.000 0.000

CH4 Emissions from Waste Incineration CH4 161 271 5% 20% 0.206 0.000 0.000 0.000 0.000 0.000 0.000

N2O Emissions from Waste Incineration N2O 88 120 5% 100% 1.001 0.000 0.000 0.000 0.000 0.000 0.000

CH4 Emissions from Other Waste CH4 0 5 10% 100% 1.005 0.000 0.000 0.000 0.000 0.000 0.000

CO2 Emissions from solvent use CO2 1,598 1,361 30% 50% 0.583 0.001 -0.001 0.002 0.000 0.001 0.001

N2O Emissions from solvent use N2O 796 772 50% 10% 0.510 0.001 0.000 0.001 0.000 0.001 0.001
CO2 Forest land remaining Forest Land CO2 52,546 53,384 30% 54% 0.616 0.052 -0.005 0.090 -0.002 0.038 0.038 CH4 Forest land remaining Forest Land CH4 143 197 30% 54% 0.616 0.000 0.000 0.000 0.000 0.000 0.000
N2O Forest land remaining Forest Land N2O 15 20 30% 54% 0.616 0.000 0.000 0.000 0.000 0.000 0.000 CO2 Cropland remaining Cropland CO2 16,876 10,960 75% 75% 1.061 0.018 -0.012 0.019 -0.009 0.020 0.022

CO2 Land converted to Forest Land CO2 1,003 2,204 75% 75% 1.061 0.004 0.002 0.004 0.001 0.004 0.004 CO2 Land converted to Cropland CO2 0 0 75% 75% 1.061 0.000 0.000 0.000 0.000 0.000 0.000

CO2 Land converted to Grassland CO2 385 7,760 75% 75% 1.061 0.013 0.012 0.013 0.009 0.014 0.017 N2O Land converted to Cropland N2O 0 0 75% 75% 1.061 0.000 0.000 0.000 0.000 0.000 0.000

CO2 Land converted to Settlements CO2 3,160 3,181 75% 75% 1.061 0.005 0.000 0.005 0.000 0.006 0.006

TOTAL 590,446 630,478 0.064 0.053 Table A1.6 Results of the uncertainty analysis including LULUCF (Tier1) . Year 2007



### Emission sources of the Italian inventory are disaggregated into a detailed level, 5 7 sources, according to the IPCC list i n the Good Practice Guidance and taking into account national circumstances and importance. Considering the LULUCF, sources and sinks of the Italian inventory are disaggregated into 6 6 categories. Uncertainties are therefore estimated for these categories. To estimate uncertainty for both activity data and emission factors, information provided in the IPCC Good Practice Guidance as well as expert judgement have been used; standard deviations have also

been considered whenever measurements were available.

T he assumptions on which uncertainty estimations are based on are documented for each category. Figures to draw up uncertainty are checked with the relevant analyst experts and literature references and they are consistent with the IPCC Good Practice Guidan ce (IPCC, 2000). The general approach followed for quantifying a level of uncertainty to activity data and emission factors is to set values within a range low, medium and high according to the confidence the expert
relies on the value. For instance, a l ow value (e.g. 3

- 5%) has been attributed to activity data derived from the energy balance and statistical yearbooks, medium

- high values within a range of 20

- 50% for all the data which are not directly or only partially derived from census or sample surveys or data which are simple estimations. For emission factors, the uncertainties set are usually higher than those for activity data; figures suggested by the IPCC good practice guidance (IPCC, 2000) are used

### 251

when the emission factor is a default value or wh en appropriate, low values are attributed to measured data whereas the uncertainty values are high in all other cases. For the base year, the uncertainty estimated by the Tier 1 approach is equal to 3.5%; if considering

the LULUCF sector the overall uncer tainty increases to 7. 0 %.

In 200 7 , the Tier 1 approach suggests an uncertainty of 3. 3 % in the combined GWP total emissions. The analysis also estimates an uncertainty of 2.6 % in the trend between 1990 and 200 7. Specifically, for the LULUCF sector, the u ncertainty value resulting from Tier 1 approach is 55% in the combined GWP total emissions for the year 200 7 , whereas the uncertainty in the trend is 43 %.

Similar values result from Tier 1 approach in uncertainty related to CO 2 

### total emissions for the year

2007 , and uncertainty in the trend. Details of the figures are shown in Tables A1. 4 and A1. 5. Including the LULUCF sector in the total uncertainty assessment, the Tier 1 approach shows an uncertainty of

6.4 % in the combined GWP total emissions for the yea r 200 7 , whereas the uncertainty in the trend between 1990 and 200 7 is equal to 5.3 %. Results are shown in Table A1.6.

Further investigation is needed to better quantify the uncertainty values for some specific source,

nevertheless it should be noted that a conservative approach has been followed.

A1.4 Tier 2 key source assessment

The Tier 2 method can be used to identify key categories when an uncertainty analysis has been carried out on the inventory. It is helpful in prioritising activities to improve inventory quality and to reduce overall uncertainty. Under the Tier 2, the source or sink category uncertainties are incorporated by weighting the Tier 1 level and trend assessment results with the source category’s relative uncertainty.

Therefore the f

ollowing equations:

Level Assessment, with Uncertainty = Tier 1 Level Assessment · Relative Category Uncertainty

Trend Assessment, with Uncertainty = Tier 1 Trend Assessment · Relative Category Uncertainty

The Tier 2 analysis has been applied both to t he base and the current year submission; in this section detailed results are reported for the 200 7 inventory. The results of the Tier 2 key category analysis, without LULUCF categories, are provided in Table
A1.7, for 2006, while in Table A1.8 the results of the analysis, including LULUCF categories, are

shown. The application of the Tier 2 to the base year gives as a result 2 2 key categories accounting for the 95% of the total levels uncertainty. The application of the Tier 2 to the inventory including th e LULUCF categories results in 2 1 key categories accounting for the 95% of the total levels uncertainty. For the year 200 7 , the application of the Tier 2 gives as a result 2 1 key categories accounting for the 95% of the total levels uncertainty; when apply ing the trend analysis the key categories increased to

22 with differences with respect to the previous list. The application of the Tier 2 to the inventory including the LULUCF categories results in 2 1 key categories accounting for the 95% of the total le vels uncertainty; for the trend analysis including LULUCF categories, the key categories decreased to 20 with differences with respect to the previous list.

Results are also shown for the base year key categories , see tables A1.9 A1.10

.

### 252 CATEGORIES Level

assessment with
uncertainty Relative level

assessment with
uncertainty Cumulative

Percentage CATEGORIES Trend

assessment

with
uncertainty Relative Trend

assessment

with
uncertainty Cumulative

Percentage

Direct N2O Agricultural Soils 0.0160 0.127 0.13 CO2 stationary combustion gaseous fuels 0.0137 0.144 0.14

Indirect N2O from Nitrogen used in agriculture 0.0139 0.110 0.24 CO2 Mobile combustion: Road Vehicles 0.0098 0.103 0.25
CO2 stationary combustion gaseous fuels 0.0122 0.097 0.33 CO2 stationary combustion liquid fuels 0.0084 0.088 0.34

CO2 Mobile combustion: Road Vehicles 0.0091 0.072 0.41 HFC, PFC substitutes for ODS 0.0084 0.088 0.42

CH4 from Solid waste Disposal Sites 0.0087 0.069 0.48 CH4 from Solid waste Disposal Sites 0.0073 0.077 0.50

HFC, PFC substitutes for ODS 0.0070 0.056 0.53 CH4 Emissions from Wastewater Handling 0.0067 0.070 0.57

N2O Manure Management 0.0070 0.056 0.59 CH4 Enteric Fermentation in Domestic Livestock 0.0061 0.064 0.63

CO2 stationary combustion liquid fuels 0.0066 0.053 0.64 Direct N2O Agricultural Soils 0.0056 0.059 0.69

CH4 Enteric Fermentation in Domestic Livestock 0.0056 0.045 0.68 CO2 stationary combustion solid fuels 0.0055 0.058 0.75

CH4 Manure Management 0.0056 0.045 0.73 Indirect N2O from Nitrogen used in agriculture 0.0047 0.049 0.80

CO2 stationary combustion solid fuels 0.0051 0.041 0.77 N2O Manure Management 0.0022 0.023 0.82

CH4 Emissions from Wastewater Handling 0.0046 0.037 0.81 CH4 Manure Management 0.0021 0.022 0.85
N2O stationary combustion 0.0035 0.028 0.83 N2O Emissions from Wastewater Handling 0.0017 0.017 0.86

CO2 Cement production 0.0034 0.027 0.86 CO2 Cement production 0.0015 0.016 0.88

N2O from animal production 0.0029 0.023 0.88 CH4 Fugitive emissions from Oil and Gas Operations 0.0014 0.015 0.89
CH4 Fugitive emissions from Oil and Gas Operations 0.0023 0.018 0.90 CO2 Emissions from solvent use 0.0012 0.012 0.91

N2O Emissions from Wastewater Handling 0.0015 0.012 0.91 N2O Emissions from solvent use 0.0011 0.011 0.92

CO2 Emissions from solvent use 0.0014 0.011 0.93 N2O from animal production 0.0010 0.011 0.93

N2O Mobile combustion: Road Vehicles 0.0013 0.010 0.94 N2O Adipic Acid 0.0008 0.008 0.94

CO2 Fugitive emissions from Oil and Gas Operations 0.0010 0.008 0.94 CO2 Fugitive emissions from Oil and Gas Operations 0.0007 0.007 0.94

CH4 stationary combustion 0.0009 0.007 0.95 CO2 Mobile combustion: Waterborne Navigation 0.0004 0.004 0.95

N2O Emissions from solvent use 0.0007 0.006 0.96 CH4 Mobile combustion: Road Vehicles 0.0004 0.004 0.95

CH4 from Rice production 0.0006 0.004 0.96 CO2 Iron and Steel production 0.0004 0.004 0.96

CO2 Limestone and Dolomite Use 0.0005 0.004 0.96 CO2 stationary combustion other fuels 0.0004 0.004 0.96
CO2 Lime production 0.0005 0.004 0.97 N2O Mobile combustion: Road Vehicles 0.0004 0.004 0.96

CO2 Mobile combustion: Waterborne Navigation 0.0004 0.003 0.97 N2O stationary combustion 0.0004 0.004 0.97

CO2 Other industrial processes 0.0004 0.003 0.97 PFC Aluminium production 0.0003 0.003 0.97
CO2 stationary combustion other fuels 0.0003 0.003 0.98 CH4 stationary combustion 0.0003 0.003 0.97

CH4 Fugitive emissions from Coal Mining and Handling 0.0003 0.002 0.98 N2O Nitric Acid 0.0002 0.002 0.98

CH4 Mobile combustion: Road Vehicles 0.0003 0.002 0.98 CO2 Ammonia production 0.0002 0.002 0.98

CO2 Iron and Steel production 0.0003 0.002 0.98 CO2 Limestone and Dolomite Use 0.0002 0.002 0.98

N2O Mobile combustion: Other 0.0002 0.002 0.99 CO2 Lime production 0.0002 0.002 0.98

N2O Emissions from Waste Incineration 0.0002 0.002 0.99 CO2 Mobile combustion: Aircraft 0.0002 0.002 0.99

CO2 Mobile combustion: Other 0.0002 0.002 0.99 CH4 Fugitive emissions from Coal Mining and Handling 0.0002 0.002 0.99

N2O Nitric Acid 0.0002 0.002 0.99 PFC, HFC, SF6 Semiconductor manufacturing 0.0002 0.002 0.99

CO2 Mobile combustion: Aircraft 0.0002 0.001 0.99 CO2 Mobile combustion: Other 0.0002 0.002 0.99

N2O Adipic Acid 0.0001 0.001 0.99 CO2 Other industrial processes 0.0002 0.002 0.99
PFC, HFC, SF6 Semiconductor manufacturing 0.0001 0.001 0.99 CO2 Emissions from Waste Incineration 0.0002 0.002 0.99

CO2 Emissions from Waste Incineration 0.0001 0.001 1.00 CH4 from Rice production 0.0001 0.001 1.00

CO2 Ammonia production 0.0001 0.001 1.00 HFC-23 from HCFC-22 Manufacture and HFCs fugitive 0.0001 0.001 1.00

CH4 Emissions from Waste Incineration 0.0001 0.001 1.00 CH4 Emissions from Waste Incineration 0.0001 0.001 1.00

SF6 Electrical Equipment 0.0001 0.001 1.00 N2O Emissions from Waste Incineration 0.0001 0.001 1.00

N2O Mobile combustion: Waterborne Navigation 0.0001 0.001 1.00 SF6 Electrical Equipment 0.0001 0.001 1.00

CH4 Industrial Processes 0.0001 0.000 1.00 CH4 Industrial Processes 0.0000 0.001 1.00

PFC Aluminium production 0.0000 0.000 1.00 N2O Mobile combustion: Other 0.0000 0.000 1.00

N2O Mobile combustion: Aircraft 0.0000 0.000 1.00 SF6 Production of SF6 0.0000 0.000 1.00
CH4 Mobile combustion: Waterborne Navigation 0.0000 0.000 1.00 CH4 Agricultural Residue Burning 0.0000 0.000 1.00

CH4 Agricultural Residue Burning 0.0000 0.000 1.00 N2O Mobile combustion: Waterborne Navigation 0.0000 0.000 1.00

CH4 Emissions from Other Waste 0.0000 0.000 1.00 N2O Mobile combustion: Aircraft 0.0000 0.000 1.00
SF6 Magnesium production 0.0000 0.000 1.00 SF6 Magnesium production 0.0000 0.000 1.00

N2O Agricultural Residue Burning 0.0000 0.000 1.00 CH4 Emissions from Other Waste 0.0000 0.000 1.00

HFC-23 from HCFC-22 Manufacture and HFCs fugitive 0.0000 0.000 1.00 N2O Agricultural Residue Burning 0.0000 0.000 1.00

CH4 Mobile combustion: Other 0.0000 0.000 1.00 CH4 Mobile combustion: Waterborne Navigation 0.0000 0.000 1.00

CH4 Mobile combustion: Aircraft 0.0000 0.000 1.00 N2O Other industrial processes 0.0000 0.000 1.00

N2O Fugitive emissions from Oil and Gas Operations 0.0000 0.000 1.00 CH4 Mobile combustion: Other 0.0000 0.000 1.00

SF6 Production of SF6 0.0000 0.000 1.00 CH4 Mobile combustion: Aircraft 0.0000 0.000 1.00

N2O Other industrial processes 0.0000 0.000 1.00 N2O Fugitive emissions from Oil and Gas Operations 0.0000 0.000 1.00 TIER 2

Table A1.7 R esults of the key categories analysis (Tier2) without LULUCF categories . Year 2007

### 253 CATEGORIES Level

assessment

with
uncertainty Relative level

assessment

with
uncertainty Cumulative

Percentage CATEGORIES Trend

assessment

with
uncertainty Relative Trend

assessment with
uncertainty Cumulative

Percentage

CO2 Forest land remaining Forest Land 0.0521 0.256 0.26 CO2 Forest land remaining Forest Land 0.038 0.226 0.23
CO2 Cropland remaining Cropland 0.0184 0.091 0.35 CO2 Cropland remaining Cropland 0.022 0.127 0.35

Direct N2O Agricultural Soils 0.0141 0.069 0.42 CO2 Land converted to Grassland 0.017 0.099 0.45

CO2 Land converted to Grassland 0.0131 0.064 0.48 CO2 stationary combustion gaseous fuels 0.012 0.070 0.52

Indirect N2O from Nitrogen used in agriculture 0.0122 0.060 0.54 CO2 Mobile combustion: Road Vehicles 0.009 0.050 0.57
CO2 stationary combustion gaseous fuels 0.0107 0.053 0.59 CO2 stationary combustion liquid fuels 0.007 0.043 0.62

CO2 Mobile combustion: Road Vehicles 0.0080 0.039 0.63 HFC, PFC substitutes for ODS 0.007 0.043 0.66

CH4 from Solid waste Disposal Sites 0.0076 0.038 0.67 CH4 from Solid waste Disposal Sites 0.006 0.038 0.70

HFC, PFC substitutes for ODS 0.0062 0.030 0.70 CH4 Emissions from Wastewater Handling 0.006 0.034 0.73
N2O Manure Management 0.0061 0.030 0.73 CO2 Land converted to Settlements 0.006 0.034 0.76

CO2 stationary combustion liquid fuels 0.0058 0.029 0.76 CH4 Enteric Fermentation in Domestic Livestock 0.005 0.031 0.80

CO2 Land converted to Settlements 0.0054 0.026 0.79 Direct N2O Agricultural Soils 0.005 0.029 0.82

CH4 Enteric Fermentation in Domestic Livestock 0.0049 0.024 0.81 CO2 stationary combustion solid fuels 0.005 0.028 0.85

CH4 Manure Management 0.0049 0.024 0.83 CO2 Land converted to Forest Land 0.004 0.025 0.88
CO2 stationary combustion solid fuels 0.0045 0.022 0.86 Indirect N2O from Nitrogen used in agriculture 0.004 0.024 0.90

CH4 Emissions from Wastewater Handling 0.0040 0.020 0.88 N2O Manure Management 0.002 0.011 0.91

CO2 Land converted to Forest Land 0.0037 0.018 0.89 CH4 Manure Management 0.002 0.011 0.92
N2O stationary combustion 0.0031 0.015 0.91 N2O Emissions from Wastewater Handling 0.001 0.009 0.93

CO2 Cement production 0.0030 0.015 0.92 CO2 Cement production 0.001 0.008 0.94
N2O from animal production 0.0025 0.012 0.94 CH4 Fugitive emissions from Oil and Gas Operations 0.001 0.007 0.95
CH4 Fugitive emissions from Oil and Gas Operations 0.0020 0.010 0.95 CO2 Emissions from solvent use 0.001 0.006 0.95

N2O Emissions from Wastewater Handling 0.0014 0.007 0.95 N2O Emissions from solvent use 0.001 0.005 0.96

CO2 Emissions from solvent use 0.0013 0.006 0.96 N2O from animal production 0.001 0.005 0.96

N2O Mobile combustion: Road Vehicles 0.0011 0.006 0.96 N2O Adipic Acid 0.001 0.004 0.97

CO2 Fugitive emissions from Oil and Gas Operations 0.0009 0.004 0.97 CO2 Fugitive emissions from Oil and Gas Operations 0.001 0.004 0.97
CH4 stationary combustion 0.0008 0.004 0.97 CO2 Mobile combustion: Waterborne Navigation 0.000 0.002 0.97

N2O Emissions from solvent use 0.0006 0.003 0.98 CH4 Mobile combustion: Road Vehicles 0.000 0.002 0.98
CH4 from Rice production 0.0005 0.002 0.98 CO2 Iron and Steel production 0.000 0.002 0.98

CO2 Limestone and Dolomite Use 0.0004 0.002 0.98 CO2 stationary combustion other fuels 0.000 0.002 0.98

CO2 Lime production 0.0004 0.002 0.98 N2O Mobile combustion: Road Vehicles 0.000 0.002 0.98
CO2 Mobile combustion: Waterborne Navigation 0.0003 0.002 0.98 N2O stationary combustion 0.000 0.002 0.98
CO2 Other industrial processes 0.0003 0.002 0.99 PFC Aluminium production 0.000 0.002 0.99

CO2 stationary combustion other fuels 0.0003 0.001 0.99 CH4 stationary combustion 0.000 0.001 0.99
CH4 Fugitive emissions from Coal Mining and Handling 0.0003 0.001 0.99 N2O Nitric Acid 0.000 0.001 0.99

CH4 Mobile combustion: Road Vehicles 0.0003 0.001 0.99 CO2 Ammonia production 0.000 0.001 0.99

CO2 Iron and Steel production 0.0002 0.001 0.99 CO2 Limestone and Dolomite Use 0.000 0.001 0.99

N2O Mobile combustion: Other 0.0002 0.001 0.99 CO2 Lime production 0.000 0.001 0.99

CH4 Forest land remaining Forest Land 0.0002 0.001 0.99 CO2 Mobile combustion: Aircraft 0.000 0.001 0.99

N2O Emissions from Waste Incineration 0.0002 0.001 0.99 CH4 Fugitive emissions from Coal Mining and Handling 0.000 0.001 0.99

CO2 Mobile combustion: Other 0.0002 0.001 0.99 CH4 Forest land remaining Forest Land 0.000 0.001 0.99

N2O Nitric Acid 0.0002 0.001 0.99 PFC, HFC, SF6 Semiconductor manufacturing 0.000 0.001 0.99

CO2 Mobile combustion: Aircraft 0.0002 0.001 1.00 CO2 Mobile combustion: Other 0.000 0.001 1.00
N2O Adipic Acid 0.0001 0.001 1.00 CO2 Other industrial processes 0.000 0.001 1.00

PFC, HFC, SF6 Semiconductor manufacturing 0.0001 0.001 1.00 CO2 Emissions from Waste Incineration 0.000 0.001 1.00

CO2 Emissions from Waste Incineration 0.0001 0.001 1.00 CH4 from Rice production 0.000 0.001 1.00
CO2 Ammonia production 0.0001 0.001 1.00 HFC-23 from HCFC-22 Manufacture and HFCs fugitive 0.000 0.000 1.00

CH4 Emissions from Waste Incineration 0.0001 0.000 1.00 CH4 Emissions from Waste Incineration 0.000 0.000 1.00
SF6 Electrical Equipment 0.0001 0.000 1.00 N2O Emissions from Waste Incineration 0.000 0.000 1.00
N2O Mobile combustion: Waterborne Navigation 0.0001 0.000 1.00 SF6 Electrical Equipment 0.000 0.000 1.00

CH4 Industrial Processes 0.0001 0.000 1.00 CH4 Industrial Processes 0.000 0.000 1.00
PFC Aluminium production 0.0000 0.000 1.00 N2O Mobile combustion: Other 0.000 0.000 1.00

N2O Mobile combustion: Aircraft 0.0000 0.000 1.00 SF6 Production of SF6 0.000 0.000 1.00
CH4 Mobile combustion: Waterborne Navigation 0.0000 0.000 1.00 CH4 Agricultural Residue Burning 0.000 0.000 1.00
N2O Forest land remaining Forest Land 0.0000 0.000 1.00 N2O Forest land remaining Forest Land 0.000 0.000 1.00

CH4 Agricultural Residue Burning 0.0000 0.000 1.00 N2O Mobile combustion: Waterborne Navigation 0.000 0.000 1.00

CH4 Emissions from Other Waste 0.0000 0.000 1.00 N2O Mobile combustion: Aircraft 0.000 0.000 1.00
SF6 Magnesium production 0.0000 0.000 1.00 SF6 Magnesium production 0.000 0.000 1.00

N2O Agricultural Residue Burning 0.0000 0.000 1.00 CH4 Emissions from Other Waste 0.000 0.000 1.00

HFC-23 from HCFC-22 Manufacture and HFCs fugitive 0.0000 0.000 1.00 N2O Agricultural Residue Burning 0.000 0.000 1.00

CH4 Mobile combustion: Other 0.0000 0.000 1.00 CH4 Mobile combustion: Waterborne Navigation 0.000 0.000 1.00

CH4 Mobile combustion: Aircraft 0.0000 0.000 1.00 N2O Other industrial processes 0.000 0.000 1.00
N2O Fugitive emissions from Oil and Gas Operations 0.0000 0.000 1.00 CH4 Mobile combustion: Other 0.000 0.000 1.00

SF6 Production of SF6 0.0000 0.000 1.00 CH4 Mobile combustion: Aircraft 0.000 0.000 1.00
N2O Other industrial processes 0.0000 0.000 1.00 N2O Fugitive emissions from Oil and Gas Operations 0.000 0.000 1.00
CO2 Land converted to Cropland 0.0000 0.000 1.00 CO2 Land converted to Cropland 0.000 0.000 1.00

N2O Land converted to Cropland 0.0000 0.00 1.00 N2O Land converted to Cropland 0.00 0.00 1.00 TIER 2

Table A1.8 Results of the key categories analysis (Tier2) with LULUCF categories . Year 2007

### 254

CATEGORIES Level

assessment with
uncertainty Relative level

assessment with
uncertainty Cumulative

Percentage

Direct N2O Agricultural Soils 0.0189 0.145 0.14

Indirect N2O from Nitrogen used in agriculture 0.0160 0.123 0.27

CO2 stationary combustion liquid fuels 0.0126 0.097 0.36
CH4 from Solid waste Disposal Sites 0.0093 0.071 0.44

N2O Manure Management 0.0077 0.059 0.49

CO2 Mobile combustion: Road Vehicles 0.0077 0.059 0.55

CO2 stationary combustion gaseous fuels 0.0070 0.054 0.61
CH4 Manure Management 0.0068 0.052 0.66

CH4 Enteric Fermentation in Domestic Livestock 0.0067 0.051 0.71
CO2 stationary combustion solid fuels 0.0049 0.037 0.75

CH4 Emissions from Wastewater Handling 0.0040 0.031 0.78
CH4 Fugitive emissions from Oil and Gas Operations 0.0036 0.027 0.81

N2O from animal production 0.0034 0.026 0.83
N2O stationary combustion 0.0033 0.026 0.86

CO2 Cement production 0.0033 0.025 0.88

CO2 Emissions from solvent use 0.0018 0.014 0.90

CO2 Fugitive emissions from Oil and Gas Operations 0.0016 0.012 0.91

N2O Emissions from Wastewater Handling 0.0015 0.012 0.92

N2O Mobile combustion: Road Vehicles 0.0010 0.007 0.93

N2O Adipic Acid 0.0009 0.007 0.94

N2O Emissions from solvent use 0.0008 0.006 0.94

CH4 Mobile combustion: Road Vehicles 0.0007 0.005 0.95
CO2 Iron and Steel production 0.0006 0.005 0.95

CH4 stationary combustion 0.0006 0.005 0.96
CH4 from Rice production 0.0006 0.005 0.96

CO2 Limestone and Dolomite Use 0.0005 0.004 0.96
CH4 Fugitive emissions from Coal Mining and Handling 0.0005 0.004 0.97

CO2 Mobile combustion: Waterborne Navigation 0.0004 0.003 0.97

N2O Nitric Acid 0.0004 0.003 0.97

CO2 Lime production 0.0004 0.003 0.98
CO2 Other industrial processes 0.0004 0.003 0.98

PFC Aluminium production 0.0004 0.003 0.98
CO2 Ammonia production 0.0003 0.003 0.99

CO2 Emissions from Waste Incineration 0.0003 0.002 0.99

N2O Mobile combustion: Other 0.0003 0.002 0.99

CO2 Mobile combustion: Other 0.0002 0.002 0.99

N2O Emissions from Waste Incineration 0.0002 0.001 0.99

HFC, PFC substitutes for ODS 0.0002 0.001 0.99

CO2 stationary combustion other fuels 0.0001 0.001 1.00

CO2 Mobile combustion: Aircraft 0.0001 0.001 1.00

CH4 Industrial Processes 0.0001 0.001 1.00
N2O Mobile combustion: Waterborne Navigation 0.0001 0.001 1.00

HFC-23 from HCFC-22 Manufacture and HFCs fugitive 0.0001 0.001 1.00

CH4 Emissions from Waste Incineration 0.0001 0.000 1.00

SF6 Electrical Equipment 0.0000 0.000 1.00
CH4 Mobile combustion: Waterborne Navigation 0.0000 0.000 1.00

N2O Mobile combustion: Aircraft 0.0000 0.000 1.00

SF6 Production of SF6 0.0000 0.000 1.00

CH4 Agricultural Residue Burning 0.0000 0.000 1.00

CH4 Mobile combustion: Other 0.0000 0.000 1.00
N2O Agricultural Residue Burning 0.0000 0.000 1.00

N2O Other industrial processes 0.0000 0.000 1.00

CH4 Mobile combustion: Aircraft 0.0000 0.000 1.00

N2O Fugitive emissions from Oil and Gas Operations 0.0000 0.000 1.00

CH4 Emissions from Other Waste 0.0000 0.000 1.00
SF6 Magnesium production 0.0000 0.000 1.00

PFC, HFC, SF6 Semiconductor manufacturing 0.0000 0.000 1.00 

### TIER 2

Table A1.

9 Results of the key categories analysis (Tier2) with out LULUCF ca tegories. Year 1990

### 255

CATEGORIES Level

assessment with
uncertainty Relative level

assessment

with
uncertainty Cumulative

Percentage

CO2 Forest land remaining Forest Land 0.0548 0.264 0.26

CO2 Cropland remaining Cropland 0.0303 0.146 0.41
Direct N2O Agricultural Soils 0.0165 0.080 0.49

Indirect N2O from Nitrogen used in agriculture 0.0140 0.068 0.56

CO2 stationary combustion liquid fuels 0.0110 0.053 0.61

CH4 from Solid waste Disposal Sites 0.0081 0.039 0.65
N2O Manure Management 0.0068 0.033 0.68

CO2 Mobile combustion: Road Vehicles 0.0067 0.032 0.71

CO2 stationary combustion gaseous fuels 0.0061 0.029 0.74
CH4 Manure Management 0.0060 0.029 0.77

CH4 Enteric Fermentation in Domestic Livestock 0.0058 0.028 0.80

CO2 Land converted to Settlements 0.0057 0.027 0.83

CO2 stationary combustion solid fuels 0.0043 0.021 0.85
CH4 Emissions from Wastewater Handling 0.0035 0.017 0.87

CH4 Fugitive emissions from Oil and Gas Operations 0.0031 0.015 0.88

N2O from animal production 0.0030 0.014 0.89

N2O stationary combustion 0.0029 0.014 0.91
CO2 Cement production 0.0028 0.014 0.92

CO2 Land converted to Forest Land 0.0018 0.009 0.93

CO2 Emissions from solvent use 0.0016 0.008 0.94

CO2 Fugitive emissions from Oil and Gas Operations 0.0014 0.007 0.95
N2O Emissions from Wastewater Handling 0.0013 0.006 0.95

N2O Mobile combustion: Road Vehicles 0.0008 0.004 0.96

N2O Adipic Acid 0.0008 0.004 0.96

CO2 Land converted to Grassland 0.0007 0.003 0.96

N2O Emissions from solvent use 0.0007 0.003 0.97

CH4 Mobile combustion: Road Vehicles 0.0006 0.003 0.97

CO2 Iron and Steel production 0.0006 0.003 0.97

CH4 stationary combustion 0.0005 0.003 0.98
CH4 from Rice production 0.0005 0.003 0.98

CO2 Limestone and Dolomite Use 0.0004 0.002 0.98

CH4 Fugitive emissions from Coal Mining and Handling 0.0004 0.002 0.98
CO2 Mobile combustion: Waterborne Navigation 0.0004 0.002 0.98

N2O Nitric Acid 0.0004 0.002 0.99

CO2 Lime production 0.0004 0.002 0.99

CO2 Other industrial processes 0.0003 0.002 0.99
PFC Aluminium production 0.0003 0.002 0.99

CO2 Ammonia production 0.0003 0.001 0.99

CO2 Emissions from Waste Incineration 0.0002 0.001 0.99

N2O Mobile combustion: Other 0.0002 0.001 0.99

CO2 Mobile combustion: Other 0.0002 0.001 0.99

N2O Emissions from Waste Incineration 0.0001 0.001 1.00

CH4 Forest land remaining Forest Land 0.0001 0.001 1.00

HFC, PFC substitutes for ODS 0.0001 0.001 1.00
CO2 stationary combustion other fuels 0.0001 0.001 1.00

CO2 Mobile combustion: Aircraft 0.0001 0.001 1.00

CH4 Industrial Processes 0.0001 0.000 1.00

N2O Mobile combustion: Waterborne Navigation 0.0001 0.000 1.00
HFC-23 from HCFC-22 Manufacture and HFCs fugitive 0.0001 0.000 1.00

CH4 Emissions from Waste Incineration 0.0001 0.000 1.00

SF6 Electrical Equipment 0.0000 0.000 1.00

CH4 Mobile combustion: Waterborne Navigation 0.0000 0.000 1.00

N2O Mobile combustion: Aircraft 0.0000 0.000 1.00

SF6 Production of SF6 0.0000 0.000 1.00

N2O Forest land remaining Forest Land 0.0000 0.000 1.00
CH4 Agricultural Residue Burning 0.0000 0.000 1.00

CH4 Mobile combustion: Other 0.0000 0.000 1.00

N2O Agricultural Residue Burning 0.0000 0.000 1.00

N2O Other industrial processes 0.0000 0.000 1.00

CH4 Mobile combustion: Aircraft 0.0000 0.000 1.00
N2O Fugitive emissions from Oil and Gas Operations 0.0000 0.000 1.00

CH4 Emissions from Other Waste 0.0000 0.000 1.00

SF6 Magnesium production 0.0000 0.000 1.00

PFC, HFC, SF6 Semiconductor manufacturing 0.0000 0.000 1.00
CO2 Land converted to Cropland 0.0000 0.000 1.00

N2O Land converted to Cropland 0.0000 0.00 1.00 

### TIER 2

Table A1. 10 Results of the key categories analysis (Tier2) with LULUCF categories. Year 1990

### 256



## ANNEX 2: DETAILED TABLES OF E NERGY CONSUMPTION FO R

POWER GENERATION

The detailed breakdown of total fuels consumed for electricity genera tion in the years 2006 and 2007 is reported in the attached tables A2.1 and A2.2. The consumption of municipal solid waste (MSW) is separated from the biomass consumption, since the use of this fuel for electricity generation is expanding. A specific EF is used to estimate CO 2 

### emissions from this source, see table 3.7. Energy data of previous years have not been changed (see previous reports). In each table, annual data from three different sources are reported:

- output of the model used to estimate consump tion and emissions for each plant type;

- detailed report by Terna;

- data available in the national energy balance. For each source, three types of data are presented: electricity produced, physical quantities of consumed fuels and amount of energy used.

As c an be noticed from the following tables, there are not negligible differences in total consumption figures between Terna and BEN. Both data sets are supposed to be based on the same data. As already said in paragraph 3.4, differences can be explained by th e process of adapting Terna data to BEN methodology: BEN considers for each fuel always the same heat value, adjusting the physical quantities accordingly. This calculation process combined with the reduction of fuel types from 17 to 12 adds rounding error s and this may be responsible for the small difference between the energy consumption value,

- 1.8% in 2006 and 0.1% in 2007 (refer to last row of each table). Differences between those two data sets and the model output are also present, they can be impro ved (i.e. reduced) depending on the modeller choice: a compromise between Terna and the BEN data according to cross check done with other sources (UP or point source data). In the case of power generation the consumption expressed in energy units is the re ference value that is optimised, since emission factors refer to the energy content of each fuel. There are also discrepancies in the estimates of the total electricity produced, see the last row of each table; they are rather small and can be due to diffe rent evaluation of the kind of fuel used. The total electricity produced (not shown in the table, see also Annex 5) is the same for both estimates. In conclusion the main question of the accuracy of the underlying energy data of three key sources

is conne cted to the discrepancies between BEN and Terna in the estimates of electricity produced and of the energy content of the used fuels. The difference is small but it should not occur because

both data sets are derived from the same source. On the basis of t his consideration, we decided to base the inventory on Terna data that are expected to be more reliable. In particular because the emission factors used are based on the energy content of the fuel we have made an effort to reproduce with the model the Tern a energy consumption figure and ignored discrepancies in the electricity production or in the physical quantities of fuel used.

### 257 Table A2.1

- Energy consumption for electricity production, year 2006

Fuels Model output TERNA BEN

Gwe, gross kt TJ Gwe, gro ss kt T.o.e./TJ Gwe, gross kt / Mmc kcal / TJ

Coal 44,195.78 16,589.56 423,529,146.44 44,207.40 16,587.00 423,462,640.00 44,206.98 15,939.00 101,213.00

Coke oven gas 1,503.50 698.88 13,392,406.91 1,534.40 721.00 13,388,800.00 1,512.79 742.00 13,187,968.00

Blast furnace gas 4,372.00 11,454.81 40,258,605.67 4,319.90 11,859.00 40,250,080.00 4,319.77 10,268.00 38,664,344.00

Oxi converter gas 382.00 487.00 3,749,173.43 397.10 551.00 3,765,600. 00 419.77 3,734,039.39

sum 6,257.50 12,640.68 57,400,186.01 6,251.40 13,131.00 57,404,480.00 6,252.33 11,010.00 55,586,351.39

Coal, sum 480,929,332.45 480,867,120.00 479,061,543.39

Light distillates 59.00 6.35 29 2,050.00 59.20 7.00 292,880.00 26.74 7.00 72.00

Light fuel oil 736.76 190.60 8,033,903.77 738.30 188.00 8,075,120.00 836.05 189.00 1,928.00

Fuel oil

- high sulfur

content 30,041.50 7,046.11 287,263,361.34 30,039.00 6,942.70 287,189,760.00 9,453.49 1,983.00 19,433.00

Fuel oil

- low sulfur

content 31,943.02 7,008.00 68,678.00

Refinery gas 2,146.00 307.71 14,290,570.48 2,146.00 300.00 14,267,440.00 2,204.65 276.00 3,310.00

Petr oleum coke 847.90 191.67 6,656,015.00 847.90 192.00 6,652,560.00 847.67 192.00 1,591.00

Oriemulsion 0.00 0.00 0.01

- - -

sum 33,831.15 7,742.44 316,535,900.60 33,830.30 7,629.00 316,477,760.00 45,311.63 7,668.00 397,530,208.00

Gas from chemical proc. 547.00 1,241.38 5,359,656.14 546.60 1,083.00 5,355,520.00 1,755.81 1,987.00 17,047,888.61

Heavy residuals/ tar 11,299.38 9,010.00 81,050,389.84 11,296.80 8,345.00 81,044, 080.00

Others 181.28 178.22 1,300,458.98 181.40 138.00 1,304,152.80

sum 12,027.66 10,429.60 87,710,504.96 12,024.80 87,703,752.80 1,755.81 1,987.00 17,047,888.61

Oil+residuals, sum 45,858.81 18,172.04 404,246,40 5.56 45,855.10 404,181,512.80 47,067.44 9,655.00 414,578,096.61

Natural gas 158,078.69 31,115.95 1,089,130,974.15 158,078.80 31,381.00 1,088,802,320.00 158,079.00 31,543.00 1,121,835,000.00

Biogas 1,335.07 14,476,640.00 1,336.30 1,292.00 14,489,977.33

Biomass 2,491.91 32,508,518.16 2,491.70 2,884.00 32,505,843.28 3,827.91 4,392.00 45,940,320.00

Municipal waste 2,915.08 45,994,958.58 2,916.60 3,832.00 46,018,973.14 2,916.28 4,182. 00 43,747,904.00

Grand total 261,132.84 2,067,286,828.90 261,137.30 2,066,865,746.55 262 ,349.93 2,105,162,864.00

GRTN/BEN differences

- 0.5 %

- 1.8%

### 258 Table A2.2

- Energy consumption for electricity production, year 2007

Fuels Model output TERNA BEN

Gwe, gross kt TJ Gwe, gross kt T.o.e./TJ Gwe, gross kt / Mmc kcal / TJ

Coal 44,140.22 16,885.61 431,821,728.00 44,112.30 16,886.00 431,830,640.00 44,206.98 15,939.00 106,213.00

Coke oven gas 1,616.50 746.72 14,309,114.66 1,618.10 766.00 14,309,280.00 1,512.79 742.00 13,187,968.00

Blast furnace gas 3,855.00 9,972.95 35,050,533.89 3,856.00 11,316.00 35,103,760.00 4,319.77 10,268.00 38,664,344.00

Oxi converter gas 170.00 2 06.38 1,588,855.29 170.00 271.00 1,548,080.00 419.77 3,734,039.39

sum 5,641.50 10,926.05 50,948,503.84 5,645.30 11,353.00 50,961,120.00 6,252.33 11,010.00 55,586,351.39

Coal, sum 482,770,231.84 482,791,760.00 49 9,981,543.39

Light distillates 59.00 6.35 292,050.00 53.00 7.00 292,880.00 26.74 7.00 72.00

Light fuel oil 681.04 177.01 7,461,022.71 673.60 176.00 7,489,360.00 836.05 189.00 1,928.00

Fuel oil

- high sulfur

content 19,028.44 4,586.12 186,895,628.14 19,024.80 4,523.00 186,355,360.00 9,453.49 1,983.00 19,433.00

Fuel oil

- low sulfur

content 31,943.02 7,008.00 48,000.00

Refinery gas 2,053.00 354.41 17,052,100.50 2,052.50 352.00 17,070,720.00 2,204.65 276.00 3,310.00

Petroleum coke 999.00 225.82 7,842,150.00 998.90 226.00 7,824,080.00 847.67 192.00 1,591.00

Oriemulsion 0.00 0.00 0.00

- - -

sum 22,820.48 5,349.71 219,542,951.36 22,865.30 5,292.00 219,450,800.00 45,311.63 7,668.00 311,013,456.00

Gas from chemical proc. 535.00 1,141.58 4,807,038.56 535.10 1,125.00 4,727,920.00 1,755.81 1,987.00 17,047,888.61

Heavy residuals/ tar 11,770.88 9,325. 75 83,890,743.63 11,772.00 8,591.00 83,763,680.00

Others 236.79 190.38 2,427,804.53 213.50 176.00 2,468,560.00

sum 12,542.67 10,657.71 91,125,586.72 12,432.50 92,760,723.49 1,755.81 1,987.00 17,047,888.61

Oil+ residuals, sum 35,363.14 16,007.42 310,668,538.08 35,297.80 312,211,523.49 47,067.44 9,655.00 328,061,344.61

Natural gas 172,651.02 33,886.18 1,184,599,634.93 172,645.90 33,957.00 1,183,737,280.00 158,079.00 31,543.00 1, 146,939,000.00

Biogas 1,447.39 15,522,640.00 1,447.00 1,392.00 15,518,457.42

Biomass 2,480.60 32,767,168.16 2,481.50 2,757.00 32,779,069.23 3

, 930 .23 4

, 446 .00 46,505,160.00
Municipal waste 3,025.57 48,065,052.38 3,024.90 4,872.00 48,054,367.28 3

, 023 .26 5

, 005 .00 52,352,300.00

Grand total 264,749.45 2,074,393,265.39 264,654.70 2,075,092,457.42 262,559.23 2,073,839,348.00

GRTN/BEN differences 0.8% 0.1%

### 259



## ANNEX 3: ESTIMATION OF CARBON CONTENT OF COALS USED IN

INDUSTRY

The preliminary use of the CRF software in 2001 underlined an unbalance of emissions in the solid fuel rows above 20%. A detailed verification pointed out to an already known fact for Italy: the

combined use of standard IPCC emission f actors for coals, national emission factors for coal gases and CORINAIR methodology emission factors for steel works processes produces double counting

of emissions. The main reason for this is the specific national circumstance of extensive recovery of c oal gases from blast furnaces, coke ovens and oxygen converters for electricity generation. The emissions from those gasses are separately accounted for and reported in the electricity generation section. Another specific national circumstance is the con centration of steel works, since the year 2001, in two sites, with integrated steel plants, coke ovens and electricity self

- production. Limited quantities of pig iron are produced also in one additional location. This has allowed for careful check of the

p rocesses involved and the emissions estimates at site level and, with reference to other countries, may or may not have exacerbated the unbalances in carbon emissions due to the use of standard EF developed for other industrial sites.

To avoid the double counting a specific methodology has been developed: it balances energy and carbon content of coking coals used by steelworks, industry, for non energy purposes and coal gasses used for electricity generation.

A balance is made between the coal used for c oke production and the quantities of derived fuels used in various sectors. The iron and steel sector gets the resulting quantities of energy and carbon after subtraction of what is used for electricity generation, non energy purposes and other industrial

sectors. The base statistical data are all reported in the BEN (with one exception) and the methodology starts with a verification of the energy balance reported in the BEN, see also Annex 5, table A5.3/.4, that seldom presents problems, and then apply th e standard EFs to the energy carriers, trying to balance the carbon inputs with emissions. The exception mentioned refers to the recovered gases of BOFs (Basic Oxygen Furnace) that are used to produce electricity but were not accounted for by

BEN from the year 1990 up to 1999. From the year 2000 those gases are (partially, only in one plant) included in the estimate of blast furnace gas. The data used to estimate the emissions from 1990 to 1999 are reported by GRTN

- ENEL. The consideration of the BOF gase s does not change the following discussion, because its contribution to the total emissions is quite limited. Table A3.1 summarises the quantities of coal and coal by

- products used by the energy system in the year 2007, all the data mentioned can be found in “enclosures 1/a, 2/a and 3/a” of BEN, see also

Annex 5. In the first box from top of the table we can see the quantities of coke, coke gas and blast furnace gas uses by the different sectors. In the second box are reported the quantities of the same ene rgy carriers that are self

- used, used for the production of coke or wasted. Then in the final part of the table, the two coloured groups of cells report the verification of the input

- output of two processes, coke ovens and the blast furnaces. The input

– ou tput is generally balanced for all the considered years, the small differences can be explained by statistical discrepancies. The following data are just memo summary of the quantities of fuels imported or exported by the system.

If we now look at Table A3 .2, in the first two boxes from the top we find the same energy data of table A3.1 valuated for their carbon content, according to the standard EF reported in Table 3.7 of the NIR. Then in the coloured cells we find the balance of carbon inputs and outputs of two processes coke oven and blast furnaces.

### 260

coke coke gas Blast furnace gas NOTES


### 9,314 For blast furnace



### 0 3,368 8,391 For electricity production



### 26,204 0 59 For steel industries



### 295 0 0 For other industries use



### 0 0 For domestic use


### 35,813 3,368 8,450 Total consumption



### 437 213 17 Consumption for production of secondary fuels



### 0

- 2 0 Losses of transformation



### 36,249 3,579 8,468 Total consumption + losses and prod.

Energy balance coke ovens Energy balance, blast furnace



### 1,314

- 846.9 Difference in energy consumption



### 3.6%

- 10.0% Unbalance in %



### 36,674 Coke oven output


### 7,074 Transformation losses, coke ovens


### 1,672 non energy use 

### 45,421 sub total 

### 45,421 Coking coal input to coke ovens 

### 11,117 Blast furn ace coal input


### 1,840 import + stock change

Table A3.1 Energy balance, 2007, Tcal



### So in the end the methodology actually foresees as a first step the calculation of the total carbon inputs (imported fuels plus standard IPCC EFs), see table A3.2 column “total according to BEN”. A second step foresees the use for the electric sector of the value directly calculated from the coal gasses used and the calculation of a “balance” quantity for blast furnaces, see column “total used for

CRF” in Table A3.2. The balance is the resulting quantity of emissions after subtraction of carbon emissions estimated for coke ovens, electricity production, other coal uses and non energy uses. The resulting carbon quantities are correct but, when reported in the CRF format, t hey seem to be produced using very low EFs for coal produced CO 2 

### , near to the natural gas EF, for the steel making process and quite high carbon emissions for the coal used to produce electricity.

Further investigations are planned, with a verification of the carbon content of the imported coals and of the coal gasses produced at various stages of the process, coke gas, blast furnace gas and BOF gas.

coke coke gas Blast furnace gas + oxi gas NOTES Total according to

BEN Total used

for CRF

4.13 From bla st furnace (no direct emissions, transformed in coal gasses)

0.00 0.66 8.50 From electricity prod. 9.90 10.31

11.61 0.00 0.07 From steel industries 11.68 12.27

0.13 0.00 0.00 From other industries use 0.13 0.13

0.00 0.00 From domestic use 0.00 0.00

15.87 0.66 8.56 Total emissions, final uses 25.84 22.71

0.17 0.06 0.02 Consumption for production of secondary

fuels 0.23

-

### 261

0.00 0.00 0.00 Losses of transformation 0.00

-
16.04 0.70 8.58 Total consumption + losses and prod. 26.07

Carbon balanc e, coke

ovens Carbon balance,

blast furnace

1.2

- 1.2 Difference in physical emissions

8%

- 14% Unbalance in %

Emissions Efs

(t CO 2 /Tcal)

14.68 400.4 Carbon in produced coke

2.83 400.4 Transformation losses

0.67 400.4 non en ergy use 0.67 0.67

18.19 sub total

17.61 400.4 Coal input to coke ovens

4.96 452.5 Coal input to blast furnace

0.82 452.5 Coke import + stock change

23.38 Total carbon input 23.38 23.38

Table A3.2 Carbon balance, 2007, Mt CO 2



### The flow chart of carbon cycle for the year 2007 is reported below. CO 2 

### emissions from primary input fuels and from final fuel consumptions are compared. Emissions related to fuel input data are enhanced in light

- blue whereas emissions estimated from final fuel con sumptions are highlighted in yellow. Emissions from the use of coke in blast furnaces result from differences between emissions from final consumption of coke and the value of the carbon balance for 2007.

### 262

CO 2 

### emission calculation

Year 2007

INPUT

Clinker production/Construction

industries

Thermoelectric power
plants

Anthracite

used in steel plant

185 kt CO 2 

### Steam coal
47,221 kt

CO 2 2,049 kt 

### CO 2

41,043 kt



### CO 2

4,130 kt 

### CO 2



### Blast furnace / Electric

Arc Furnace Sub

bituminous

coal and lignite

278 kt CO 2

185 kt 

### CO 2 278 kt 

### CO 2

### 263 * It results from the carbon balance:
= 11,858 kt CO 2 

### –3,428 kt CO 2

Coke

I mports/Stock
change

839 kt 

### CO 2

Coking coal

18,362 kt



### CO 2 Lime

Coke

oven Coke Steam coal

and

Anthracite

Blast

Furnace

Burned in coke

oven and blast

furnaces Reheating furnaces

and thermoelectric
power plants Coke Oven by products

(no energy) Basic Oxygen

Furnace (BOF) Pig

Iron

Reheating furnaces

and thermoelectric
power plants Blast Furnace

gas

Burned in coke

oven and blast

furnaces Reheating furnaces

and thermoelectric power plants Iron Ore,
Pellets,

Sinter

Industrial,

Domestic and

civil uses BOF steel

gas Burned in coke oven

Coke Oven Gas * 8,430 kt CO 2

37 kt 

### CO 2 590 kt 

### CO 2 133 kt 

### CO 2 16 kt 

### CO 2 9,518 kt 

### CO 2 302 kt 

### CO 2 175 kt 

### CO 2

Energy

transformation losses

### 264



## ANNEX 4: CO 2 

## REFERENCE APPROACH

A4.1 Introduction

The IPCC Reference Approach is a ‘top down’ invent ory based on data on production, imports, exports and stock changes of crude oils, feedstock, natural gas and solid fuels. Estimates are made of the carbon stored in manufactured products, the carbon consumed as international bunker fuels

and the emission

s from biomass combustion. The methodology followed is that outlined in the IPCC Guidelines (IPCC, 1997); table 1.A(b) of the Common Reporting Format “Sectoral background data for energy

- CO 2 

### from Fuel

Combustion Activities

- Reference Approach” is a self sustaining explanation of the methodology. However it was necessary to make a few adaptations to allow full use of the Italian energy and emission factor data (ENEA, 2002 [a]), and these are described in the following. The BEN (MSE, several years [

a]) reports the energy balances for all primary and secondary fuels, with data on imports, exports and production. See Annex 5, Tables A5.1

- A5.10, for an example of the year 2007 and to the web site of the Ministry of Economic Development for the whole tim e series http://dgerm.sviluppoeconomico.gov.it/dgerm/

.

Starting from those data and using the emission factors reported in chapter 3, Table 3.7, it is possible to estimate the total carbon ente ring in the national energy system. It has been developed a direct connection between relevant cells of the CRF tables and the BEN tables and a procedure to insert some additional activity data needed. The ‘missing’ data refer to import

– export of lubric ants, petrol additives, asphalt, other chemical products with energy content, energy use of exhausted lubricants and the evaluation of marine and

aviation bunkers fuels used for national traffic. Those ‘missing’ data are in fact reported in the BEN but al l mixed up together with other substances as sulphur and petrochemicals. The aggregate data do not allow the use of the proper emission factor so inventory is based on more detailed statistics from foreign trade surveys. The carbon stored in products is es timated according to the procedure illustrated in the paragraph 3.9 and directly subtracted to the emission balance by the CRF software in the current version used by Italy. It may be the case to underline that no direct subtraction of the energy content o f the feedstock is performed by CRF. In the cases, as Italy, where those products are not considered in the energy balances this bring to an unbalanced control sheet, as discussed in the following.

With reference to table 1.A(b) of the CRF 2007, we make r eference to the BEN tables reported in Annex 5. In particular the following data are reported and used for the Reference Approach : 1) crude oil imports and production;
2) natural gas data import; 3) import

- export data of petrol, aviation fuel, other kero sene, diesel, fuel oil, LPG and virgin naphtha; 4) import

- export data of bitumen and motor oil derive from foreign trade statistics, estimated by an ENEA consultant for the period 1990

- 1998. BPT data (MSE, several years [b]) are
used from 1999 onwards; 5) import

- export data of petroleum coke and refinery feedstock are also found in BEN; it has to be underlined that the data reported as “feedstock production” have been ignored up to year 2003 because it is explicitly excluded by the IPCC methodology.

### 265

Fro m 2004 onward a careful check with the team in charge to prepare the energy balances induced the inventory team to revise its position on this matter ( 1 

### ); 6) all coal data are available in BEN, coke import

- export included;
7) total natural gas import

- ex port balance reflects BEN estimate (energy section), but the detailed quantities coming from different countries (relevant for the carbon EF estimate, see paragraph 3.9) are from foreign trade statistics or “Rete Gas”, the national gas grid monopoly, fisca l budgets; the estimated quantities of natural gas used by various sectors show not negligible variations from source to source, with particular reference to the underground stocked quantities; when available we use the estimates of AEEG (Authority

for ele ctricity and gas) for consumption of the distribution / storage system and BEN for final consumption; 8) from 1990 to 2007 biomass consumption data are those reported in the BEN; it is well known that other estimates show much bigger, up to 50% more, quant ities of used biomass, for example ENEA (ENEA, several years); but the same source quotes BEN biomass consumption estimates as official statistics up to the year 2007 pending further investigations; the inventory follows the same methodology.

The followin g additional information is needed to complete table 1.A(b) of CRF 2007 and it is

found in other sources: 1) Orimulsion, this fuel is mixed up with imported fuel oil (on the base of the energy content), the quantities used for electricity generation are repo rted by ENEL (ENEL, several years), the former electricity monopoly, presently the only user of this fuel, in their environmental report. This fuel is not used any more since 2004.
2) Motor oils and bitumen. a) Data on those materials are mixed up in the no ene rgy use by BEN, detailed data are available in BPT (MSE, several years [b]). The quantities of those materials are quite relevant for the no energy use of oil. b) In the BEN those materials are estimated in bulk with other products to have an

energy content of about 5100 kcal/kg. Average OECD data 9000 kcal/kg for bitumen and 9800 kcal/kg for motor oils. In the CRF those products are estimated with the OECD energy content and this may explain part of the unbalance between imported oil and used products.

For f urther information see the paper by ENEA (ENEA, 2002 [b]) in Italian.

A4.2 Comparison of the sectoral approach with the reference approach

The detailed inventory contains a number of sources not accounted for in the IPCC Reference Approach and so gives a

higher estimate of CO 2 

### emissions. The unaccounted sources are:

• Land use change and forestry

• Offshore flaring and well testing

• Waste incineration

• Non

- Fuel industrial processes

1 The feedstock production data refers to petrochemical feedstock and other fuel streams coming back to the refineries

fro m the internal market. Those quantities do not contain additional carbon inputs but because those quantities are not properly subtracted to the final fuel consumption section of the energy balances they should be accounted for also as
inputs. A more precis e solution would be to reduce the quantities of fuels consumed by the industrial sector, but this is not possible because the team in industry Ministry has only a few details about the origin of those fuel streams returned

to refineries. Since 2004 those f uel streams are needed to close the energy balances, which now are much more precise
than before. Not considering them in the CRF as input will increase the difference between reference and sectoral approach in the oil section, while with those fuels as in puts the difference is nearly zero. The inventory team considers those fuels as “stock changes” of petrochemical input.

### 266

First of all, the IPCC Reference total can be compared with the IPCC Table 1A total plus the fugitive emissions arising from fuel consumption reported in 1B1 Solid Fuel Transformation and in Table 2 Industrial Processes (Iron and Steel and Ammonia Production). Results show the IPCC

Reference totals are between 0

- 4 percent lower than the comparable ‘bottom up’ totals. The highest

difference between the two approaches is observed in 1999 and is equal to 3.1 ; input data have been
checked in details, the difference could be attributed to higher thermo electric fuel input registered by EN EL/TERNA than the figure reported in the energy balance and higher quantities of petcoke calculated from cement production data than those r eported in the energy balance.

Differences between emissions estimated by the reference and sectoral approach are r eported in the following Table A4.1.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Sectoral approach 402.02 414.90 434.56 439.62 441.96 455.80 458.65 459.91 455.38 444.57

Reference approach 396.06 406.64 426.15 429.98 432.63 447.16 452.23 453.80 4 50.33 438.06

Δ %

- 1.48%

- 1.99%

- 1.93%

- 2.19%

- 2.11%

- 1.90%

- 1.40%

- 1.33%

- 1.11%

- 1.46%
Table A4.1 Reference and sectoral approach CO 2 emission estimates 1990

- 2007 (Mt) and percentage differences



### There are a number of reasons why the totals differ and th ese arise from differences in the methodologies and the statistics used. Explanations for the discrepancies:

1. The IPCC Reference Approach is based on statistics of production, imports, exports and stock changes of fuels whilst the ‘bottom

- up’ approach uses fuel consumption data. The two sets of statistics can be related using mass balances (MSE, several years [a]), but these show that some fuel is unaccounted for. This fuel is reported under ‘statistical differences’ which consist of

measurement errors and losses. A significant proportion of the discrepancy between the IPCC Reference approach and the ‘bottom up’ approach arises from these statistical differences particularly with liquid fuels.

2. In the power sector in the detailed approach statistics from pro ducers are used, instead for the reference approach the BEN data are used. The two data sets are not connected; in the BEN sections used only the row data of imports

- exports are contained. But if one considers the process of “balancing” the import

–produc tion data with the consumption ones and the differences between the two data sets, a sizable part of the discrepancy may be connected to this reason only. An investigation is planned as soon as resources become available.

3. The ‘bottom up’ approach only incl udes emissions from the no energy use of fuel where they can be specifically identified and estimated such as with fertilizer production and iron and steel production. The IPCC Reference approach implicitly treats the non

- energy use of fuel as if it

were combustion. A correction is then applied by deducting an estimate of carbon stored from

non

- energy fuel use. The carbon stored is estimated from an approximate procedure which does not identify specific processes. The result is that the IPCC Reference a pproach is based on a higher estimate of non

- energy use emissions than the ‘bottom

- up’ approach.

The IPCC Reference Approach uses data on primary fuels such as crude oil and natural gas liquids which are then corrected for imports, exports and stock chang es of secondary fuels. Thus the estimates obtained will be highly dependent on the default carbon contents used for the primary

fuels.

The ‘bottom

- up’ approach is based wholly on the consumption of secondary fuels where the carbon

contents are known with greater certainty. In particular the carbon contents of the primary liquid fuels are likely to vary more than those of secondary fuels. Carbon content of solid fuels and of natural gas is quite precisely accounted for, a specific methodology for estimate carbon content of liquid fuel imports is at the moment only planned.

### 267



## ANNEX 5: NATIONAL ENERGY BALANCE, YEAR 2007

The following table reproduces the part expressed in amount of energy consumed of the National Energy Balance (BEN) of the year 2007.

The complete balance, containing the physical quantities as well as the amount of energy and a consistent time series from the year 1998 onwards, is also available on the website: http://dgerm.svilu ppoeconomico.gov.it/dgerm/

.

Sectors and fuel definition have been translated here in English, but, of course, the tables on Internet are in Italian language. Definitions are very similar to their English equivalents so this

should not be an obstacle to i ndependent verifications of energy data sources for previous years.

The national energy balance is comprised of two “sets” of tables: from page 2 to page 10 the energy vectors are represented in physical quantities (kt) while from page 12 to page 20 they are expressed in energy equivalents (10^9 kcal). Recalling what already said in Annex 2 related to the BEN reporting methodology (that prefers to use always the same lower heat value for each primary fuel in various years, to better follow the

variable ene rgy content of each shipment), we make reference here to the second set of tables. This means, for example, that the primary fuel quantities of two shipments of imported coal are “adjusted” using their energy content as the main reference (see Table A5.1) and the value reported in page 2 of the national energy balance (non reproduced here) is an “adjusted” quantity of kt. This process is routinely applied for most primary sources, including imported and nationally produced natural gas.

For the final uses o f energy (Tables A5.7

- 8 and Tables A5.9

- 10) the same methodology is applied but it runs the other way: the physical quantities of energy vectors are the only values actually measured on the market and the energy content is actually estimated using fixed av erage estimates of lower heat value. Experience on the measure of the actual energy content of fuels shows minor variations from one to another year, especially for liquid fuels.

In the case of natural gas the use of a fixed heat value to summarize all tr ansactions was particularly complicated due to the fact that we use fuel from four main different sources: Russia, Netherlands, Algeria and national production. From 2003

- 2004 onwards Norway and Libya have also been added to the supply list. The big custom ers were actually billed according to the measured heat value of the natural gas delivered. After the end of the state monopoly on this market the system has recently been changed. From 2004 onwards, the price makes reference to the energy content of natur al gas and the metered physical quantities of gas delivered to all final customers are billed according to an energy content variable from site to site and from year to year. The BEN still tries to summarize all production and consumption using only one co nventional heat value.

So for the estimations of liquid fuels used in the civil and transportation sector the most reliable data is the physical quantity and this is used to calculate emissions, using updated data for the
emission factors, estimated from samples of marketed fuels. For this reason we attach also the copies of tables, page 8 and 9 of BEN (see Tables A5.9

- 10), mirror sheet of the tables, page 18 and 19 of BEN (see Tables A5.7

- 8), that are the base for our

emission calculation in the civil an d transport sectors.

### 268 Table A5.1

–National Energy Balance, year 2007, Primary fuels, 10 9 

### kcal

PRIMARY SOURCES

BALANCE Coking

coal Steam

coal Coal other

uses Lignite Subproduct

s (a) Natural

Gas Crude oil Refinery

feedstocks Hydraulic

Energy (e) G eotherma

l Energy Wind and

Photovoltai
c Energy Waste Biomass (f) TOTAL

PRIMARY

SOURCES

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Conversion factor (b) 7.400 6.350 7.400 2.500 2.500 8.250 10.000 10.000 2.200 2.200 2.200 2.500 2.500

1. PRODUCTIONS (c) 1,003 4,395 80,075 58,600 16,050 72,193 12,252 8,961 12,513 29,768 295,810

2. IMPORTS 46,539 117,240 1,487 10 610,088 881,580 78,660 6,925 1,742,529

3. EXPORTS 561 12,130 8,040 25 20,756

4. Stock changes (d) 681

- 883 296

- 10,799 350

- 670

- 11,024

5. TOTAL RESOURCES 45,858 119,126 1,191 10 4,395 700,400 927,700 87,340 72,193 12,252 8,961 12,513 36,668 2,028,607

6. Transformations
(Enclosure 1/a) 45,421 103,212 4,395 282,920 1,015,040 72,193 12,252 8,961 12,513 13,090 1,569,997

7. Consumptions and Losses
(Encl.2/a) 437 1 12,708 13,146

8. Final Consumptions (Enclosure 3/a) 15,913 1,191 10 404,772 23,578 445,464

a) Agriculture 1,576 2,198 3,774

b) Industry 15,913 1,124 10 158,097 3,300 178,444

c) Services 4,876 1,585 6,461

d) Domestic and civil uses 67 232,477 16,495 249,039

Total (a+b+c+d) 15,913 1,191 10 397,026 23,578 437,718

e) Non energy uses 7,746 7,746

TOTAL ENERGY
CONSUMPTIONS (7+8) 437 15,914 1,191 10 417,480 23,578 458,610

9. Non energy final uses

### 269 PRIMARY SOURCES

BALANCE Coking

coal Steam

coal Coal other

uses Lignite Subproduct

s (a) Natural

Gas Crude oil Refinery

feedstocks Hydraulic

Energy (e) G eotherma

l Energy Wind and

Photovoltai
c Energy Waste Biomass (f) TOTAL

PRIMARY

SOURCES

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Conversion factor (b) 7.400 6.350 7.400 2.500 2.500 8.250 10.000 10.000 2.200 2.200 2.200 2.500 2.500

10. BUNKERS

12. TOTAL USES 45,858 119,126 1,191 10 4,395 700,400 1,015,040 72,193 12,252 8,961 12,513 36,668 2,028,607

(a)

- Including secondary products, heat recovered, oxygen furnace gas and compressed gas expansion evaluated at the the rmic equivalent of 2200 kcal/kWh, used by electric energy production

(b)

- Lower heat value has been adopted for all fuels

(c)

- Oil products include: returns from petrolchimical industry, some reclassification of feedstocks and r egeneration of lubricant oils

(d)

- In the "TOTAL RESOURCES", this entry is considered negative

(e)

- Pumping excluded

(f)

- Biomass production include: total wood removals (from and outside forest); biomass used by electric energy production; biodiesel (202 kt)

### 270 Table A5.2

- National Energy Balance, year 2007, Secondary fuels, 10 9 

### kcal

SECONDARY SOURCES

BALANCE Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace Gas (g) Non

energy
use of

coal products Gas

works

Gas L. P. G. Refinery

gas (h) Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil /

Diesel

Oil Residual
Oil, HS
(i) Residual
Oil, LS Petroleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECOND

ARY

SOURCE

S

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Conversion
factor (b) 0.860 7.500 7.187 4.250 0.900 7.400 4.250 11.000 12.000 10.400 10.500 10.400 10.300 10.200 9.800 9.800 8.300 6.004

1.

PRODUCTION
S (c) 265,071 975 33,973 3,579 8,467 1,635 25,839 45,396 26,468 225,404 41,954 1,957 421,066 93,698 76,401 12,367 38,456 1,322,706

2. IMPORTS 42,081 488 3,062 16,324 23,390 2,709 4,982 2,616 13,352 6,135 16,621 26,452 5,344 163,556

3. EXPORTS 2,277 30 1,545 303 6,358 6,115 99,162 3,817 577 103,826 41,738 6,066 1,411 18,354 291,579

4. Stock changes (d)

- 323 792 1,196

- 1,155

- 884 1,164 836

- 1,323 2,352 398 1,525 4,578

5. TOTAL

RESOURCES 304,874 1,433 35,813 3,579 8,467 1,332 35,013 45,396 42,547 130,106 44,003 2,832 329,756 59,418 84,604 37,010 23,921 1,190,105

6.

Transformations
(Encl.1/a) 9,314 3,368 8,391 4,076 68 1,794 24,316 40,347 1,874 93,548

7. Consumptions

and Losses (Encl.2/a) 38,861 211 17 330 27,700 286 209 1 14 7,497 9,646 9,115 24 93,909

8. Final Consumptions
(Encl.3/a) 266,014 1,433 26,499 59 1,332 34,683 13,620 42,193 129,897 44,002 2,832 322,645 5,055 27,212 26,021 3,050 967,064

a) Agriculture 4,867 704 137 23,725 29,433

b) Industry 119,989 375 26,499 59 4,048 2,100 2,415 177 10 4,590 4,340 24,694 26,021 3,050 218,367

c) Services 38,026 10,384 124,657 43,825 260,568 477,460

### 271 SECONDARY SOURCES

BALANCE Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace Gas (g) Non

energy
use of

coal products Gas

works

Gas L. P. G. Refinery

gas (h) Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil /

Diesel

Oil Residual Oil, HS
(i) Residual Oil, LS Petroleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECOND

ARY

SOURCE

S

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Conversion factor (b) 0.860 7.500 7.187 4.250 0.900 7.400 4.250 11.000 12.000 10.400 10.500 10.400 10.300 10.200 9.800 9.800 8.300 6.004

d) Domestic

and civil uses 103,132 1,058 19,404 113 24,755 1,254 149,716

Total (a+b+c+d) 266,014 1,433 26,499 59 34,540 2,100 127,209 44,002 123 313,638 4,340 25,948 26,021 3,050 874,976

e) No energetic uses 1,332 143 11,520 42,193 2,688 2,709 9,007 715 1,264 20,517 92,088

TOTAL

ENERGY

CONSUMPTIO
NS (7+8) 304,875 1,433 26,499 211 76 1,332 35,013 41,320 42,479 130,106 44,003 2,832 322,659 12,552 36,858 35,136 3,074 1,040,458

9. Non energy

final uses 20,516 20,516

10. BUNKERS 5,304 22,550 7,399 330 35,583

12. TOTAL

USES 304,875 1,433 35,813 3,579 8,467 1,332 35,013 45,396 42,547 130,106 44,003 2,832 329,756 59,418 84,604 37,010 23,921 1,190,105

(g)

- Real quantity of blast furnace gas in trasformations is 10 .316 Mmc with l.h.v. of 813 kcal/mc

(h)

- Including residuals gas of chemical processes

(i)

- Including heavy residuals used for electricity production through gasification

### 272 Table A5.3

- National Energy Balance, year 2007, Primary fuels used by transfo rmation industries, "Enclosure 1/a", 10 9 

### kcal

PRIMARY SOURCES

TRANSFORMATIONS Coking

coal Steam coal Coal other

uses Lignite Subproduct
s (a) Natural Gas Crude oil Refinery

feedstocks Hydraulic

Energy (e) Geothermal

Energy Wind and

Photovoltai

c Ene rgy Waste Biomass TOTAL

PRIMARY

SOURCES

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Conversion factor (b) 7.400 6.350 7.400 2.500 2.500 8.250 10.000 10.000 2.200 2.200 2.200 2.500 2.500

1) INPUT QUANTITY

a) Charcoal pit 1,975 1,975

b) Coking 45,421 45,421

c) Town gas Workshop

d) Blast furnaces

e) Petroleum refineries 1,015,040 1,015,040

f) Hydroelectric power plants 72,193 72,193

g) Geothermal power plants 12,252 12,252
h) Thermoelectric power plants 103,212 4,395 282,920 12,513 11,115 414,155

i) Wind / Photovol taic power plants 8,961 8,961

TOTAL 45,421 103,212 4,395 282,920 1,015,040 72,193 12,252 8,961 12,513 13,090 1,569,997

2) OUTPUT QUANTITY

A) Obtained sources

a) Charcoal pit 988 988

b) Coking 36,674 36,674

c) Town gas Workshop

d) Blast furnaces

e) Petroleum refineries 970,554 970,554

f) Hydroelectric power plants 28,221 28,221

g) Geothermal power plants 4,789 4,789

### 273 PRIMARY SOURCES

TRANSFORMATIONS Coking

coal Steam coal Coal other

uses Lignite Subproduct s (a) Natural Gas Crude oil Refinery

feedstocks Hydraulic

Energy (e) Geothermal

Energy Wind and

Photovoltai

c Ene rgy Waste Biomass TOTAL

PRIMARY

SOURCES

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Conversion factor (b) 7.400 6.350 7.400 2.500 2.500 8.250 10.000 10.000 2.200 2.200 2.200 2.500 2.500

h) Thermoelectric power plants 37,936 1,688 148,475 2,601 3,379 194,079

i) Wind / Photovoltaic power plants 3,503 3,503

Sub

- Total A 36,674 37,936 1,688 148,475 970,554 28,221 4,789 3,503 2,601 4,367 1,238,808

B) Losses of

transformation

a) Charcoal pit 987 987

b) Coking 7,074 7,074

c) Town gas Workshop

d) Blast furnaces

e) Petroleum refineries 6,030 6,030

f) Hydroelectric power

p lants 43,972 43,972
g) Geothermal power plants 7,463 7,463

h) Thermoelectric power plants 65,276 2,707 134,445 9,912 7,736 220,076
i) Wind / Photovoltaic power plants 5,458 5,458

Sub

- Total B 7,074 65,276 2,707 134,445 6,030 43,972 7,463 5,458 9,912 8,723 291,060

C) Non energy products

a) Coke ovens (c) 1,673 1,673

b) Town Gas Workshop

c) Petroleum refineries
(d) 38,456 38,456

Sub

- Total C 1,673 38,456 40,129

TOTAL A+B+C 45,421 103,212 4,395 282,920 1,015,040 72,193 12,252 8,961 12,513 13,090 1,569,997

### 274 PRIMARY SOURCES

TRANSFORMATIONS Coking

coal Steam coal Coal other

uses Lignite Subproduct s (a) Natural Gas Crude oil Refinery

feedstocks Hydraulic

Energy (e) Geothermal

Energy Wind and

Photovoltai

c Ene rgy Waste Biomass TOTAL

PRIMARY

SOURCES

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Conversion factor (b) 7.400 6.350 7.400 2.500 2.500 8.250 10.000 10.000 2.200 2.200 2.200 2.500 2.500

(a)

- See note (a) in the table of the Balance

(b)

- Lower heat value has been adopted for all fuels

(c)

- Including tars, benzol and ammonic sulphate

(d)

- Including solvent gasoline, turpentine, lubricants, white oils, insulating oils, vaseline, paraffin, bitumen and other products

(e)

- Pumping excluded



### Table A5.4

- National Energy Balance, year 2007, Secondary fuels used by transformation industries, "Enclosure 1/a", 10 9 

### kcal

SECONDARY SOURCES

TRANSFORMATIO

NS Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace

Gas Non

energy
use of

coal products Gas

works

Gas L. P. G. Refinery

gas Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil

/ Diesel

Oil Residual
Oil, HS Residual

Oil, LS Petroleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECON

DARY

SOURC

ES

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Conversion factor
(b) 0.860 7.500 7.187 4.250 0.900 7.400 4.250 11.000 12.000 10.400 10.500 10.400 10.300 10.200 9.800 9.800 8.300 6.004

1) INPUT QUANTITY

a) Charcoal pit

b) Coking

c) Town gas Workshop

d) Blast furnaces 9,314 9,314

e) Petroleum

refineries

### 275 SECONDARY SOURCES

TRANSFORMATIO

NS Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace

Gas Non

energy
use of

coal products Gas

works

Gas L. P. G. Refinery

gas Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil

/ Diesel

Oil Residual Oil, HS Residual

Oil, LS Petroleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECON

DARY

SOURC

ES

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Conversion factor
(b) 0.860 7.500 7.187 4.250 0.900 7.400 4.250 11.000 12.000 10.400 10.500 10.400 10.300 10.200 9.800 9.800 8.300 6.004

f) Hydroelectr.power plants
g) Geothermal power plants

h)

Thermoelectr. power plants 3,368 8,391 4,076 68 1,794 24,316 40,347 1,874 84,234
i) Wind / Photovoltaic power plants

TOTAL 9,314 3,368 8,391 4,076 68 1,794 24,316 40,347 1,874 93,548

2) OUTPUT
QUANTITY

A) Obtained sources

a) Charcoal pit

b) Coking

c) Town gas Workshop

d) Blast furnaces 9,314 9,314

e) Petroleum

refineries

f) Hydroelectric power plants
g) Geothermal

power plants

### 276 SECONDARY SOURCES

TRANSFORMATIO

NS Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace

Gas Non

energy
use of

coal products Gas

works

Gas L. P. G. Refinery

gas Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil

/ Diesel

Oil Residual Oil, HS Residual

Oil, LS Petroleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECON

DARY

SOURC

ES

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Conversion factor
(b) 0.860 7.500 7.187 4.250 0.900 7.400 4.250 11.000 12.000 10.400 10.500 10.400 10.300 10.200 9.800 9.800 8.300 6.004

h) Thermoelectric power plants 1,372 3,317 1,765 46 579 10,400 16,139 859 34,477

i) Wind / Photovoltaic power plants

Sub

- Total A 9,314 1,372 3,317 1,765 46 579 10,400 16,139 859 43,791

B) Losses of

transformation

a) Charcoal pit

b) Coking

c) Town gas

Wor kshop

d) Blast furnaces

e) Petroleum

refineries

f) Hydroelectric power plants

g) Geothermal power plants
h) Thermoelectric power plants 1,996 5,074 2,311 22 1,215 13,916 24,208 1,015 49,757

i) Wind / Photovoltaic power plants

Sub

- Total B 1,996 5,074 2,311 22 1,215 13,916 24,208 1,015 49,757

C) Non energy products

a) Coking

### 277 SECONDARY SOURCES

TRANSFORMATIO

NS Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace

Gas Non

energy
use of

coal products Gas

works

Gas L. P. G. Refinery

gas Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil

/ Diesel

Oil Residual Oil, HS Residual

Oil, LS Petroleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECON

DARY

SOURC

ES

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Conversion factor
(b) 0.860 7.500 7.187 4.250 0.900 7.400 4.250 11.000 12.000 10.400 10.500 10.400 10.300 10.200 9.800 9.800 8.300 6.004

b) Town Gas Workshop

c) Petro leum

refineries

Sub

- Total C

TOTAL A+B+C 9,314 3,368 8,391 4,076 68 1,794 24,316 40,347 1,874 93,548

### 278 Table A5.5

- National Energy Balance, year 2007, P rimary fuels losses, "Enclosure 2/a", 10 9 

### kcal

PRIMARY SOURCES

CONSUMPTIONS AND
LOSSES (d) Coking

coal Steam

coal Coal other

uses Lignite Subproduct

s (a) Natural

Gas Crude oil Refinery

feedstocks Hydraulic

Energy Geothermal

Energy Wind and

Photovol tai
c Energy Waste Biomass TOTAL

PRIMARY

SOURCES

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Conversion factor (b) 7.400 6.350 7.400 2.500 2.500 8.250 10.000 10.000 2.200 2.200 2.200 2.500 2.500

1) Consumptions for production

of primary sources

a) Biomass

b) Coal

c) Lignite

d) Nuclear fuels

e) Natural Gas 792 792

f) Natural gas liquids

g) Crude oil

h) Hydraulic Energy

i) Geothermal Energy

Sub

- total 792 792

2) Consumptions for production

of secondary sources (c)

a) Charcoal pit

b) Coke ovens 437 437

c) Town Gas Workshop

d) Blast furnaces

e) Petroleum refineries 2,492 2,492

f) Hydraulic power plants

### 279 PRIMARY SOURCES

CONSUMPTIONS AND LOSSES (d) Coking

coal Steam

coal Coal other

uses Lignite Subproduct

s (a) Natural

Gas Crude oil Refinery

feedstocks Hydraulic

Energy Geothermal

Energy Wind and

Photovol tai
c Energy Waste Biomass TOTAL

PRIMARY

SOURCES

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Conversion factor (b) 7.400 6.350 7.400 2.500 2.500 8.250 10.000 10.000 2.200 2.200 2.200 2.500 2.500

g) Geothermal power plants

h) Thermoel ectric power plants

i) Nuclear power plants

Sub

- total 437 2,492 2,929

3) Consumptions and Losses

of

transport and distribution 9,430 9,430

4) Differences :

- Statistics

- of conversion 1

- 6

- 5

TOTAL (1+2+3+4) 437 1 12,708 13,146

(a)

- See note (a ) in the table of the Balance

(b) Lower heat value has been adopted for all fuels

(c) Consumptions for internal uses of energy industries

(d) Excluding losses of transformation considered in the balance of transformations

### 280 Table A5.6

- National E nergy Balance, year 2007, Secondary fuels losses, "Enclosure 2/a", 10 9 

### kcal

SECONDARY SOURCES

CONSUMPTIO

NS AND

LOSSES Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace

Gas Non

energy
use of

coal products Gas

works

Gas L. P. G. Refinery

gas Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil

/ Diesel

Oil Residual
Oil, HS Residual

Oil, LS Petroleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECON

DARY

SOURC

ES

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Conversion
factor (b) 0.860 7.500 7.187 4.250 0.900 7.400 4.250 11.000 12.000 10.400 10.500 10.400 10.300 10.200 9.800 9.800 8.300 6.004

1) Consumptions for production

of primary

sources

a) Biomass

b) Coal 34 34

c) Lignite 2 2

d) Nuclear fuels 5 5

e) Natural Gas 293 293

f) Natural gas liquids

g) Crude oil

h) Hydraulic
Energy 1,709 1,709

i) Geothermal
Energy

Sub

- total 2,043 2,043

2) Consumptions for production

of secondary sources (c)

a) Charcoal pit

b) Coke ovens 146 211 17 374

c) Town Gas Workshop 194 194

d) Blast

furnaces

### 281 SECONDARY SOURCES

CONSUMPTIO

NS AND

LOSSES Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace

Gas Non

energy
use of

coal products Gas

works

Gas L. P. G. Refinery

gas Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil

/ Diesel

Oil Residual Oil, HS Residual

Oil, LS Petroleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECON

DARY

SOURC

ES

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Conversion factor (b) 0.860 7.500 7.187 4.250 0.900 7.400 4.250 11.000 12.000 10.400 10.500 10.400 10.300 10.200 9.800 9.800 8.300 6.004

e) Petroleum

refineries 5,005 330 27,696 281 210 11 7,497 9,642 9,113 24 59,809

f) Hydraulic power plants 446 446

g) Geothermal power plants 281 281

h)

Thermoelectric power plants 10,098 10,098

i) Wind /

Photovoltaic power plants 2

Sub

- total 16,172 211 17 330 27,696 281 210 11 7,497 9,642 9,113 24 71,202

3) Consumptions

and Losses of

tra nsport and

distribution 20,647 20,647

4) Differences :

- Statistics 1

- 1

- of

conversion

- 2 4 5

- 1 1 3 4 2 1 17

T OTAL
(1+2+3+4) 38,861 211 17 330 27,700 286 209 1 14 7,497 9,646 9,115 24 93,909

### 282 Table A5.7

- National Energy Balance, year 2007, Primary fuels used by end use sectors, "Enclosure 3/a", 10 9 

### kcal

PRIMARY SOURCES

FINAL

CONSUMPTIONS Coking

coal Steam coal Coal other

uses Lignite Subproduct

s Natural

Gas Crude oil Refinery

feedstocks Hydraulic

Energy Geothermal

Energy Wind and

Photovoltai
c Energy Waste Biomass TOTAL

PRIMARY

SOURCES

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Conversion facto

r (a) 7.400 6.350 7.400 2.500 2.500 8.250 10.000 10.000 2.200 2.200 2.200 2.500 2.500

1) AGRICULTURE

AND FISHING

I

- Agriculture 1,576 2,198 3,774

II

- Fishing

Sub

- Total 1,576 2,198 3,774

2) INDUSTRY

I

- Iron and steel industry 10,636 481 18,554 29,671

II

- Other industry 5,277 643 10 139,543 3,300 148,773

a) Mining in dustry 289 289

b) Non

- Ferrous

Metals 22 3,968 3,990

c) Metal works

factories 22,853 22,853
d) Food Processing,
Beverages 14,842 14,842

e) Textile and clothing 9,125 9,125
f) Construction
industries (cement,
bricks) 5,277 599 10 7,912 3,300 17,098

g) Glass and pottery 24,857 24,857

h) Chemical 22 27,704 27,726

i) Petrochemical

l) Pulp, paper and print 19,643 19,643

m) Other industries 8,350 8,350

n) Building and

civil works

### 28 3 PRIMARY SOURCES

FINAL

CONSUMPTIONS Coking

coal Steam coal Coal other

uses Lignite Subproduct

s Natural

Gas Crude oil Refinery

feedstocks Hydraulic

Energy Geothermal

Energy Wind and

Photovoltai
c Energy Waste Biomass TOTAL

PRIMARY

SOURCES

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Conversion facto

r (a) 7.400 6.350 7.400 2.500 2.500 8.250 10.000 10.000 2.200 2.200 2.200 2.500 2.500

Sub

- To tal 15,913 1,124 10 158,097 3,300 178,444

3) SERVICES

I

- Railways

II

- Navigation

III

- Road transportation 4,876 1,585 6,461

IV

- Civil aviation

V

- Other transportation

VI

- Public Service

Sub

- Total 4,876 1,585 6,461

4) DOMESTIC AND

COMMERCIA L

USES 67 232,477 16,495 249,039

TOTAL (1+2+3+4) 15,913 1,191 10 397,026 23,578 437,718

5) NON ENERGY
USE (b)

I

- Chemical industry

II

- Petrochemical 7,747 7,747

III

- Agriculture

IV

- Other sectors

Sub

- Total 7,747 7,747

TOTAL
(1+2+3+4+5) 15,913 1,191 10 404,773 23,578 445,465

(a)

- Lower heat value has been adopted for all fuels

(b)

- Non energy uses of energetic sources

### 284 Table A5.8

- National Energy Balance, year 2007, Secondary fuels used by end use sectors, "Enclosure 3/a", 10 9 

### kcal

SECONDARY SOURCES

FINAL

CONSUMPTIONS Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace

Gas Non

energy
use of

coal products Gas

works

Gas L. P. G. Refinery

gas Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil

/ Diesel

Oil Residual
Oil, HS Residual

Oil, LS Pet roleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECON

DARY

SOURC

ES

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Conversion factor 0.860 7.500 7.187 4.250 0.900 7.400 4.250 11.000 12.000 10.400 10.500 10.400 10.300 10.200 9.800 9.800 8.300 6.004

1)

AGRICULTURE

AND FISHING

I

- Agriculture 4,867 682 126 21,410 27,085

II

- Fishing 22 11 2,315 2,348

Sub

- Total 4,867 704 137 23,725 29,433

2) INDUSTRY

I

- Iron and steel industry 18,642 26,204 59 275 82 686 17 45,965

II

- Other industry 101,347 375 295 3,773 2,100 2,415 177 10 4,508 4,340 24,008 26,004 3,050 172,402

a) Mining industry 939 44 204 39 137 1,363
b) Non

- Ferrous

Metals 4,751 43 198 61 441 5,494

c) Metal works

factories 24,322 825 336 177 10 1,367 1,078 3,136 31,251
d) Food Processing,
Beverages 11,055 300 418 510 137 5,762 18,182

e) Textile and clothing 7,779 209 459 49 1,891 10,387
f) Construction
industries (cement,

bricks ) 7,725 101 891 479 960 274 25,896 3,050 39,376

g) Glass and

pottery 4,995 693 163 2,489 8,340

h) Chemical 21,319 75 43 77 224 1,284 108 23,130

### 285 SECONDARY SOURCES

FINAL

CONSUMPTIONS Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace

Gas Non

energy
use of

coal products Gas

works

Gas L. P. G. Refinery

gas Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil

/ Diesel

Oil Residual Oil, HS Residual

Oil, LS Pet roleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECON

DARY

SOURC

ES

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Conversion factor 0.860 7.500 7.187 4.250 0.900 7.400 4.250 11.000 12.000 10.400 10.500 10.400 10.300 10.200 9.800 9.800 8.300 6.004

i) Petrochemical 1,383 198 2,100 2,079 1,009 4,488 11,257

l) Pulp, paper and print 9,158 88 204 1,891 11,341

m) Other

industries 6,375 108 132 337 1,068 2,215 10,235

n) Building and

civil works 1,546 500 2,046

Sub

- Total 119,989 375 26,499 59 4,048 2,100 2,415 177 10 4,590 4,340 24,694 26,021 3,050 218,367

3) SERVICES

I

- Railways

4,543 1,071 5,614

II

- Navigation 30 2,315 2,345

III

- Road transportation 4,279 10,351 124,226 253,082 391,938

IV

- Civil

aviation 95 158 42,650 42,904

V

- Other transportation 20,002 20,002

VI

- Public

Service 9,076 33 (c) 273 1,175 4,100 (c) 14,657

Sub

- Total 38,026 10,384 124,657 43,825 260,568 477,460

4) DOMESTIC

AND

COMMERCIAL

USES 103,132 1,058 19,404 113 24,755 1,254 149,716

TOTAL
(1+2+3+4) 266,014 1,433 26,499 59 34,540 2,100 127,209 44,002 123 313,638 4,340 25,948 26,021 3,050 874,976

5) NON
ENERGY USE (b)

### 286 SECONDARY SOURCES

FINAL

CONSUMPTIONS Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace

Gas Non

energy
use of

coal products Gas

works

Gas L. P. G. Refinery

gas Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil

/ Diesel

Oil Residual Oil, HS Residual

Oil, LS Pet roleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECON

DARY

SOURC

ES

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Conversion factor 0.860 7.500 7.187 4.250 0.900 7.400 4.250 11.000 12.000 10.400 10.500 10.400 10.300 10.200 9.800 9.800 8.300 6.004

I

- Chemical industry

II

- Petrochemical 143 11,520 42,193 2,688 2,709 9,007 715 1,264 240 70,479

III

- Agriculture 163 163

IV

- Other sectors 1,169 20,277 21,446

Sub

- Total 1,332 143 11,520 42,193 2,688 2,709 9,007 715 1,264 20,517 92,088

TOTAL
(1+2+3+4+5) 266,014 1,433 26,499 59 1,332 34,683 13,620 42,193 129,897 44,002 2,832 322,645 5,055 27,212 26,021 23,567 967,064

(c) 490 10 9 kcal of diesel and 22 10 9 kcal of LPG used for heating for Public Service

### 287 Table A5.9

- National Energy Balance, year 2007, Primary fuels used by end use sectors, "Enclosure 3/a", quan tity

PRIMARY SOURCES

FINAL

CONSUMPTIONS Coking

coal Steam

coal Coal other

uses Lignite Subproduct

s Natural

Gas Crude oil Refinery

feedstocks Hydraulic

Energy Geothermal

Energy Wind and

Photovoltai
c Energy Waste Biomass TOTAL

PRIMARY

SOURCES

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Unit of measurement kt kt kt kt Mmc kt kt GWh GWh GWh kt kt

1) AGRICULTURE

AND FISHING

I

- Agriculture 191 879

II

- Fishing

Sub

- Total 191 879

2) INDUSTRY

I

- Iron and steel industry 1,675 65 2,249

II

- Other industry 831 87 4 16,914 1,320

a) Mining industry 35

b) Non

- Ferrous Metals 3 481

c) Metal works

factories 2,770

d) Food Processing,
Beverages 1,799

e) Textile and clothing 1,106

f) Construction
industries (cement, bricks) 831 81 4 959 1,320

g) Glass and pottery 3,013

h) Chemical 3 3,358

i) Petrochemical
l) Pulp, pape

r and print 2,381

m) Other industries 1,012

n) Building and civil

works

Sub

- Total 2,506 152 4 19,163 1,320

3) SERVICES

I

- Railways

### 288 PRIMARY SOURCES

FINAL

CONSUMPTIONS Coking

coal Steam

coal Coal other

uses Lignite Subproduct

s Natural

Gas Crude oil Refinery

feedstocks Hydraulic

Energy Geothermal

Energy Wind and

Photovoltai
c Energy Waste Biomass TOTAL

PRIMARY

SOURCES

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Unit of measurement kt kt kt kt Mmc kt kt GWh GWh GWh kt kt

II

- Navigation

III

- Road transportation 591 202 (b)

IV

- Civil aviation

V

- Other transportation

VI

- Public Service

Sub

- Total 591 202

4) DOMESTIC AND

COMMERCIAL USES 9 28,179 6,598 (b)

TOTAL (1+2+3+4) 2,506 161 4 48,124 8,999

5) NON ENERGY USE (a)

I

- Chemical industry

II

- Petrochemical 939

III

- Agriculture

IV

- Other sectors

Sub

- Total 939

TOTAL (1+2+3+4+5) 2,506 161 4 49,063 8,999

(a)

- Non energy uses of energetic sources
(b)

- Biodiesel for road transport: 202 kt; biodiesel for domestic and commercial uses: 0 kt

### 289 Table A5.10

- National Energy Balance, year 2007, Secondary fuels used by end use sectors, "Enclosure 3/a", quantity

SECONDARY SOURCES

FINAL

CONSUMPTIO

NS Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace

Gas Non

energy
use of

coal products Gas

work s
Gas L. P. G. Refinery

gas Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil

/ Diesel

Oil Residual
Oil, HS Residual

Oil, LS Petroleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECON

DARY

SOURC

ES

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Unit of

measurement GWh kt kt Mmc Mmc kt Mmc kt kt kt kt kt kt kt kt kt kt

1)

AGRICULTUR

E AND

FISHING

I

- Agriculture 5,659 62 12 2,099

II

- Fishing 2 1 227

Sub

- Total 5,659 64 13 2,326

2) INDUSTRY

I

- Iron and steel industry 21,676 3,646 66 25 8 70 2

II

- Other

indus try 117,844 50 41 343 175 230 17 1 442 443 2,450 3,133 508
a) Mining industry 1,092 4 20 4 14

b) Non

- Ferrous

Metals 5,525 6 18 6 45

c) Metal works

factories 28,281 75 32 17 1 134 110 320
d) Food Processing,
Beverages 12,855 40 38 50 14 588

e) Textile and clothing 9,045 19 45 5 193
f)

Construction

industries (cement, bricks) 8,982 14 81 47 98 28 3,120 508

### 290 SECONDARY SOURCES

FINAL

CONSUMPTIO

NS Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace

Gas Non

energy
use of

coal products Gas

work s
Gas L. P. G. Refinery

gas Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil

/ Diesel

Oil Residual Oil, HS Residual

Oil, LS Petroleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECON

DARY

SOURC

ES

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Unit of

measurement GWh kt kt Mmc Mmc kt Mmc kt kt kt kt kt kt kt kt kt kt

g) Glass and

pottery 5,808 63 16 254

h) Chemical 24,789 10 6 7 22 131 13

i)

Petrochemical 1,609 18 175 198 103 458
l) Pulp, paper and print 10,649 8 20 193

m) Other

industries 7,412 15 12 33 109 226

n) Building and

civil works 1,797 49

Sub

- Total 139,520 50 3,687 66 368 175 230 17 1 450 443 2,520 3,135 508

3) SERVICES

I

- Railways

5,283 105

II

- Navigation 34 227

III

- Road transportation 4,976 941 11,831 24,812

IV

- Civil

aviation 111 15 4,101

V

- Other transportation 23,258

VI

- Public

Service 10,554 3 (c) 26 113 402 ( c)

Sub

- Total 44,216 944 11,872 4,214 25,546

4) DOMESTIC

AND

COMMERCIAL

USES 119,921 141 1,764 11 2,427 128

### 291 SECONDARY SOURCES

FINAL

CONSUMPTIO

NS Electric

Energy Char

coal Coke Coke

oven gas Blast

furnace

Gas Non

energy
use of

coal products Gas

work s
Gas L. P. G. Refinery

gas Light

Distillate

s (naphtha) Gasoline Jet fuel Kerosene Gas Oil

/ Diesel

Oil Residual Oil, HS Residual

Oil, LS Petroleu

m Coke Non

energy
use of petroleu

m products TOTAL

SECON

DARY

SOURC

ES

15 16 17 18 20 21 19 22 23 24 25 26 27 28 29 30 31 32 33

Unit of

measurement GWh kt kt Mmc Mmc kt Mmc kt kt kt kt kt kt kt kt kt kt

TOTAL
(1+2+3+4) 309,316 191 3,687 66 3,140 175 12,115 4,231 12 30,749 443 2,648 3,135 508

5) NON

ENERGY USE

I

- Chemical industry

II

- Petrochemical 13 960 4,057 256 263 883 73 129 40

III

- Agriculture 22

IV

- Other

sectors 158 3,377

Sub

- Total 180 13 960 4,057 256 263 883 73 129 3,417

TOTAL
(1+2+3+4+5) 309,316 191 3,687 66 180 3,153 1,135 4,057 12,371 4,231 275 31,632 516 2,777 3,135 3,925

(c) 48 kt of gas oil and 2 kt of LPG used for heating for Public Service

### 292



## ANNEX 6: NATIONAL EMISSION FACTORS

Monitoring of the carbon content of the fuels used nationally is an ongoing activity at APAT. The principle is t

o analyse regularly the chemical composition of the used fuel or relevant activity statistics, to estimate the carbon content and the emission factor. For each primary fuel (natural gas, oil, coal) a specific procedure has been established.

Natural gas

IP CC methodology reports an emission factor for this energy carrier. Initially to estimate the methane content of the fuel, so that the correct emission factor for fugitive emissions could be evaluated a proper investigation has been performed among main use rs. Routine checks are performed by final uses to estimate chemical composition of natural gas and its energy value. It has been found that the national market is characterized by the commercialisation of natural gas of highly variable composition. Since 1 990 natural gas has been produced nationally or imported by pipelines from Russia, Algeria and Netherlands. Moreover an NGL facility is importing gas from Algeria and Libya. From 2003

- 2004 onwards Norway and Libya have also been added to the supply
list, t hank to updated pipeline connection. Sizeable additional NGL facilities are under construction. Each of those natural gas es has peculiar properties and it is regularly analysed at the import gates, for budgetary reasons. Energy content for cubic meters and percentage of methane can vary considerably: national produced gas sold to the grid is almost 99% methane (% moles), the one coming from Algeria has less than 85% of methane and significant quantities of propane

- butane. Carbon content varies significantly also. Natural gas properties are quite stable with reference to the country of origin and chemical composition and speciation of gas from each country is regularly published by SNAM, the main national operators. Other information is also available from t he final distribution companies. So, for each year, the average methane and carbon content of the natural gas used in Italy are estimated using the international trade statistical data and a national emission factor is estimated.

The list of factors for th

e years of interest is reported in Table A6.1. In the 2009 submission the average emission factor for 2006 has been updated.

Table A6.1 Natural gas carbon em ission factors t CO 2 / TJ t CO 2 / 10 3 std cubic mt t CO 2 / tep

Natural gas (dry) IPCC 55.780 1.925 2.334

Natural gas (dry) 1990 55.328 1.942 2.315

Natural gas (dry) 1995 55.423 1.961 2.319

Natural gas (dry) 1998 55.423 1.970 2.319

Natural gas (dry) 1999 55.437 1.971 2.319

Natural gas (dry) 2000 55.472 1.971 2.321

Natural gas (dry) 2001 55.421 1.960 2.319

Natural gas (dry) 2002 55.974 1.96 5 2.342

Natural gas (dry) 2003 55.594 1.961 2.326

Natural gas (dry) 2004 55.595 1.945 2.326

Natural gas (dry) 2005 55.590 1.944 2.326

Natural gas (dry) 2006 55. 666 1.949 2.3 29

Natural gas (dry) 2007 55.636 1.947 2.328

### 293

Diesel oil, petrol and LPG, national production APAT has made an investigation of the carbon content of the main transportation fuels sold in Italy: petrol, diesel and LPG. The job has been aimed to test the average fuels sold in the ye ar 2000 and to collect the available information on previous years fuels. The aim of this work is the verification of CO 2 

### emission factors of the Italian energy system and specifically of the transportation sector. The results of analysis of fuel samples p erformed by “Stazione Sperimentale Combustibili” (APAT, 2003) are checked against the emission factors used in the Reference Approach of the Intergovernmental Panel for Climate Change (IPCC, 1997) and the emission factors considered in the COPERT III prog ramme of the European Environment Agency (EEA, 2000). Those two methodologies are widely used to prepare data at the international level but, when applied to the Italian data set produce results with significant differences, around 2

- 4%. The reason

has bee n traced back to the emission factors that are referred to the energy content of the fuel for IPCC and to the physical quantities for the COPERT methodology. The results of the study performed by APAT link the chemical composition of the fuel to the LHV

f or a series of fuels representative of the national production in the years 2000

- 2001, allowing for more precise evaluations of the emission factors.

IPCC

- OECD emission factors for diesel fuels and IPCC

- Europe for LPG are almost identical to the experimen

tal results (less than 1% difference), and it has been decided to use IPCC emission factors for the period 1990

- 1999 and the measured EF from the year 2000 onwards. Relevant quantities (about 50%) of LPG used in Italy are imported. The measured values ref er only to the products produced in Italy, IPCC emission factors is used as a default. For petrol instead the IPCC

- OECD emission factors is quite low and it has to be upgraded, the reason may be linked to the extensive use of additives in recent years to r each a high octane number after the lead has been phased out. For 2000 and the following years the experimental factor will be used, for the period 1990

- 1999 it has been decided to use an interpolate factor between IPCC

emission factors and the measured va lue, using the LHV as the link between the national products

and the international database. No other information was available. The list of emission factors for the different years is reported in Table A6.2.

Table A6.2 Fuels, national production, carbon emission factors



### Fuel oil, imported and produced

With reference to fuel oil the main information available was a sizable difference in carbon content between high sulphur and light sulphur brands. IPCC emission factors generally refer to the light sulphur product.

The data where elaborated from literature and from an exte nsive series of samples (more than 400) analysed by ENEL and made available to APAT. t CO2 / TJ t CO2 / t t CO2 / tep

Petrol, IP CC / OECD 68.559 3.071 2.868
Petrol, IPCC Europe 72.270 3.148 3.024
Petrol (Italian National Energy Balance),
interpolated emission factor 1990

- 1999 71.034 3.121 2.972

Petrol, experimental averages 2000

- 2007 71.145 3.109 2.977

Gas oil, IPCC / OECD 73.2 74 3.175 3.066
Gas oil, IPCC Europe 73.260 3.108 3.065

Gas oil, 1990

- 1999 73.274 3.127 3.066
Gas oil, engines, experimental averages 2000

- 2007 73.153 3.138 3.061
Gas oil, heating, experimental averages 2000

- 2007 73.693 3.141 3.083

LPG, IPCC / OECD 6 2.392 2.952 2.610

LPG, IPCC / Europe 64.350 3.000 2.692

LPG, 1990

- 1999 64.350 3.000 2.692
LPG, experimental averages 64.936 2.994 2.717

### 294

Carbon content varies to a certain extent also between the medium sulphur content and the very low sulphur products, but the main discrepancies refer to the high sulphur t ype. According to the available statistical data, it was possible to trace back to the year 1990 the produced and imported quantities of fuel oil, divided between high and low sulphur products and to estimate the average carbon emission factor for the yea rs of interest, see Table A6.3 for details. In 2009 submission on the basis of more detailed data available on the amount of low and high sulphur fuel oil sold emission factor have been slightly updated from 1999.

T able A6.3 Fuel oil, average of national and imported products, carbon emission factors



### Coal imports Italy has only negligible national production of coal, most is imported from various countries and there are not negligible differences in carbon content. The variations in carbon content can be linked to the hydrogen content and to the LHV of the coal. An additional national circumstance refers to the absence of long term import contracts. The quantities shipped by the main exporters change considerably f rom year to year; moreover new suppliers have been added to the list in the last few years. So an attempt was made to find out a methodology that allow for a more precise estimation of the carbon content of this fuel. It is possible, using literature dat a for the coals and detailed statistical records of international trade, to find out the weighted average of carbon content and of the LHV of the fuel imported to Italy each year. The actually still unresolved problem is how to properly link

statistical da ta, referred to the coal “as is” without specifying the moisture and ash content of the product, to the literature data that refer to sample coals. We envisage improving the quality of the collected statistical data including moisture content of

coals but presently we overcome this obstacle with the following procedure:

- using an ample set of experimental data on coals imported in a couple of years on an extensive series of samples, more than 200, analysed by ENEL (the main electricity producing company in Italy) it was possible to correlate “as is” LHV and carbon content to the average properties of the coals imported in the same period of time and calculated from literature data (EMEP/CORINAIR, 200 7 );

- for each inventory year it is possible to calculate th e weighted average of LHV and carbon content of imported coals using available literature data;

- using this calculated data and the correlation found out it is possible to estimate the carbon content of the average “as is” coal reported in the statistics.

U sing this methodology and the available statistical data, it was possible to trace back to the year 1990 the average LHV of the imported coal and estimate the average carbon EF for each year, see T CO 2 / TJ T CO 2 / T T CO 2 / TEP

Fuel oil, average 1990 76.565 3.111 3.203

Fuel oil, average 1995 76.650 3.127 3.207

Fuel oil, average 1998 76.741 3.139 3.211

Fuel oil, average 1999 76. 547 3.1 24 3.2 03

Fuel oil, average 2000 75

. 898 3.124 3.176

Fuel oil, average 2001 75.889 3.122 3.175

Fue l oil, average 2002 75.942 3.125 3.177

Fuel oil, average 2003 76.151 3.131 3.186

Fuel oil, average 2004 76.170 3.132 3.187

Fuel oil, average 2005 76.306 3.133 3.193

Fuel oil, average 2006 76.280 3.134 3.196

Fuel oil, average 2007 76.518 3.129 3.201

### 295

table A6.4 for same details. The results do not show impress ive changes from year to year, any way a noticeable difference in the emission factor is highlighted in the table.

This methodology can be questioned and certainly can be improved; we continue to use it because, in our view, its use improves the quality o f our reporting. In the 2009 submission, emission factors for 2005 and 2006 have been updated on the basis of new information available regarding the amount of different coals imported.

t CO2 / TJ t CO2 / t t CO2 / tep

Sub bituminous coal, IPCC 96.234 2.557 4.026

Steam coal 1990 94.582 2.502 3.960

Steam coal 1995 94.007 2.519 3.936

Steam coal 1998 94.582 2.437 3.957

Steam coal 1999 93.844 2.400 3.926

Steam coal 2000 91.446 2.404 3.826

Steam coal 2001 93.398 2.434 3.908

Steam coal 2002 92.832 2.42 3 3.884

Steam coal 2003 93.478 2.435 3.911

Steam coal 2004 93.474 2.430 3.911

Steam coal 2005 94

. 623 2.475 3.959

Steam coal 2006 95.076 2.450 4.016

Steam coal 2007 95.041 2.465 3.977

Table A6.4

– Coal, average carbon emission factors

### 296



## ANNEX 7: A GRICULTURE SECTOR

Additional information used for estimating categories 4A and 4B from the agriculture sector are reported in this section.

Annex 7 .1 Enteric fermentation (4A) Following suggestions from the last centralized review 2 

### , the time series of th e parameters used for estimating the Dairy Ca ttle emission factor using the T ier 2 approach

is reported in Table A.7.1

. Information on the equations used for estimating the different net energy (NE

m 

### , NE g 

### , etc.) is

detailed in IPCC (2000).

Source: ISPRA, 2009

Table A.7.1 Parameters used for the Tier 2 approach

- dairy cattle

2 http://unfccc.int/resource/docs/2009/arr/ita.pdf

NE

m (MJ/day) NE

a (MJ/day) NE g (MJ/day) NE l (MJ/day) NE

w (MJ/day) NE p (MJ/day) NE

ma /DE NE

ga /DE GE

(MJ/day)

1990 40.75 0.35 0.10 33.52 0.00 3.97 0.51 0.31 235.77

1991 40.75 0.35 0.10 37.71 0.00 3.96 0.51 0.31 248.30

1992 40.75 0.35 0.10 40.42 0.00 3.91 0.51 0.31 256.30

1993 40.75 0.35 0.10 40.25 0.00 3.89 0.51 0.31 255.70

1994 40.75 0.35 0.10 42.53 0.00 3.92 0.51 0.31 262.63

1995 40.75 0.35 0.10 43.38 0.00 3.86 0.51 0.31 264.99

1996 40.75 0.35 0.10 44.66 0.00 3.86 0.51 0.31 268.84

1997 40.75 0.35 0.10 45.46 0.00 3.85 0.51 0.31 271.18

1998 40.75 0.35 0.10 45.25 0.00 3.79 0.51 0.31 270.40

1999 40.75 0.35 0.10 45.17 0.00 3.75 0.51 0.31 270.00

2000 40.75 0.35 0.10 44.31 0.00 3.78 0.51 0.31 267.52

2001 40.75 0.35 0.10 43.74 0.00 3.73 0.51 0.31 265.67

2002 40.75 0.35 0.10 47.60 0.00 3.72 0.51 0.31 277.19

2003 40.75 0.35 0.10 47.57 0.00 3.72 0.51 0.31 277.10

2004 40.75 0.35 0.10 49.68 0.00 3.66 0.51 0.31 283.26

2005 40.75 0.35 0.10 50.84 0.00 3.71 0.51 0.31 286.88

2006 40.75 0.35 0.10 51.17 0.00 3.67 0.51 0.31 287.76

2007 40.75 0.35 0.10 51.15 0.00 3.65 0.51 0.31 287.62

### 297

Annex 7 .2 Manure management (4B)

In this section the time series used to apply the methane emission reduc tion to the 4B Manure management category from the agriculture sector are reported . The source of information is the National Electrical Service Operator

- GSE (Gestore Servizi Elettrici) 3 

### . The total gross production

of biogas produced from animal manure i s used for the production of electricity and combine d (electricit y and heat

) production

. The conversion of this information (GWh) into metane (Gg) has assumed a 30% yield and a net caloric value of 50.038 Gg/TG. A representation of the time series is

prese nted in the following Table A.7.2 and Figure A.7.1

.

Source: TERNA, 2009

Table A.7.2 Time series of gross production of biogas from animal manure

3 http://www.gse.it BIOGAS

Year Only for electricity

production (GWh) Combined:

For electricity +heat production

(GWh) TOTAL Gross production (GWh) Methane (Gg)

1990 0 0 0 0.00

1991 0 1.3 1.3 0.31

1992 0 0.5 0.5 0.1 2

1993 0 0.4 0.4 0.10

1994 0 6.3 6.3 1.51

1995 0 8.1 8.1 1.94

1996 0 7.6 7.6 1.82

1997 0 6.9 6.9 1.65

1998 0 5.7 5.7 1.37

1999 0.8 5.6 6.4 1.53

2000 0.2 4.7 4.9 1.18

2001 0 8.7 8.7 2.09

2002 0 11.3 11.3 2.71

2003 3.5 9.7 13.2 3.17

2004 6.3 12.2 18.5 4.44

2005 8.8 16.9 25.7 6.16

2006 16.2 28.5 44.7 10.72

2007 20.9 32.4 53.3 12.78

### 298 0 4 8 12 16 20 24 28 32 36199019911992199319941995199619971998199920002001200220032004200520062007GWh

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14Gg only eletricity production combined= electricity + heat production methane (Gg)

Source: Cóndor et al. 2008[c] Figure A7

. 1 Time series of gross pro duction of biogas from animal manure

### 299



## ANNEX 8 : CRF TREND TABLES FOR GREENHOUSE GASES

This appendix shows a copy of Tables 10s1

- 10s5 from the Common Reporting Format 200 7

, submitted in 200 9 , in which time series of emission estimates for the foll owing gases are reported:

• CO 2



### • CH

4



### • N 2 

### O

• HFCs, PFCs, SF 6



### • All gases and sources categories

### 300

Table A 8 .1 CO 2 emissions trends, CRF year 200 7 (years 1990

– 1999)

TABLE 10 EMISSION

TRENDS Inventory

200 7

CO 2 Submission

200 9 v1. 3

(Part 1 of 2) ITALY

Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999 GREENHOUSE GAS

SOURCE AND SINK

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg)

1. Energy 405,362.41 404,891.70 403,948.05 400,610.70 394,537.77 418,078.67 414,043.11 418,123.50 429,405.09 434,558.59

A. Fuel Combustion
(Sectoral Approach) 402,021.44 401,626.94 400,736.43 397,230.81 391,311.70 414,904.60 411,007.89 414,880.10 426,286.57 432,154.14

1. Energy Industries 134,092.13 128,409.96 128,308.81 122,891.90 125,531.51 137,973.44 133,477.62 135,233.81 145,716.93 141,641.43
2. Manufacturing

Industries and Construction 88,937.35 85,985.66 84,303.50 84,766.43 85,764.73 87,954.97 85,740.04 88,806.50 83,048.96 86,753.59

3. Transport 101,268.76 103,786.58 108,03 3.89 109,632.51 109,241.76 111,445.87 112,671.21 114,360.34 118,143.79 119,688.84

4. Other Sectors 76,676.86 82,248.15 78,809.30 78,491.90 69,314.51 76,090.33 77,936.90 75,254.68 78,337.61 82,959.85

5. Other 1,046.34 1,196.59 1,280.93 1,448.07 1,459.19 1,439.99 1,182.11 1,224.77 1,039.27 1,110.43
B. Fugitive Emissions from

Fuels 3,340.96 3,264.77 3,211.62 3,379.89 3,226.07 3,174.07 3,035.22 3,243.41 3,118.52 2,404.46

1. Solid Fuels NA NA NA NA NA NA NA NA NA NA

2. Oil and Natural

Gas 3,340.96 3,264 .77 3,211.62 3,379.89 3,226.07 3,174.07 3,035.22 3,243.41 3,118.52 2,404.46

2. Industrial Processes 27,190.32 26,792.42 27,320.39 24,448.95 23,570.49 25,414.97 23,016.25 23,102.11 23,151.29 23,309.33

A. Mineral Products 21,099.66 21,051.69 21,863.21 1 9,407.30 18,913.76 20,768.08 19,075.78 19,320.39 19,575.62 20,383.81
B. Chemical Industry 2,198.88 2,101.70 2,064.25 1,473.98 1,207.27 1,229.99 962.27 1,034.92 1,040.80 958.46

C. Metal Production 3,891.78 3,639.03 3,392.93 3,567.68 3,449.47 3,416.89 2 ,978.20 2,746.80 2,534.86 1,967.06

D. Other Production NA NA NA NA NA NA NA NA NA NA

E. Production of

Halocarbons and SF 6 F. Consumption of

Halocarbons and SF 6 G. Other NA NA NA NA NA NA NA NA NA NA

3. So lvent and Other Product

Use 1,598.05 1,584.54 1,586.70 1,535.12 1,463.04 1,423.99 1,378.75 1,378.90 1,328.15 1,330.94

4. Agriculture

### 301

TABLE 10 EMISSION

TRENDS Inventory

200 7

CO 2 Submission

200 9 v1. 3

(Part 1 of 2) ITALY

Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999 GREENHOUSE GAS

SOURCE AND SINK

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg)

A. Enteric Fermentation

B. Manure Management

C. Rice C

ultivation
D. Agricultural Soils
E. Prescribed Burning of

Savannas
F. Field Burning of
Agricultural Residues

G. Other

5. Land Use, Land

- Use Chan

ge and Forestry

(2) - 67,650.69

- 85,599.15

- 83,249.16

- 65,542.83

- 81,187.16

- 85,816.00

- 92,121.65

- 80,990.35

- 76,533.85

- 81,380.38

A. Forest Land

- 53,548.90

- 75,038.50

- 71,040.61

- 55,830.62

- 72,326.81

- 77,554.80

- 80,119.83

- 71,947.20

- 69,434.80

- 77,121.98
B. Cropland

- 16,876.40

- 11,902.38

- 13,485.61

- 11,856.88

- 11,005.03

- 10,405.88

- 12,336.71

- 11,187.82

- 9,243.72

- 6,403.07

C. Grassland

- 385.17

- 1,821.00

- 1,888.60 NO NO NO

- 2,870.31 NO NO NO

D. Wetlands NO NO NO NO NO NO NO NO NO NO

E. Settlements 3,159. 78 3,162.74 3,165.66 2,144.67 2,144.67 2,144.67 3,205.21 2,144.67 2,144.67 2,144.67

F. Other Land NO NO NO NO NO NO NO NO NO NO

G. Other NA NA NA NA NA NA NA NA NA NA

6. Waste 536.90 562.22 562.44 521.18 524.10 483.02 472.13 507.76 504.42 393.47

A. Solid Waste Disposal on

Land NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

B. Waste

- water Handling

C. Waste Incineration 536.90 562.22 562.44 521.18 524.10 483.02 472.13 507.76 504.42 393.47

D. Other NA NA NA NA NA NA NA NA NA NA

7. Other (as specified in
Summary 1.A) NA NA NA NA NA NA NA NA NA NA

### 302

TABLE 10 EMISSION

TRENDS Inventory

200 7

CO 2 Submission

200 9 v1. 3

(Part 1 of 2) ITALY

Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999 GREENHOUSE GAS

SOURCE AND SINK

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg)

Total CO

2 emissions including

net CO 2 from LULUCF 367,036.98 348,231.74 350,168.42 361,573.12 338,908.25 359,584.64 346,788.60 362,121.93 37 7,855.10 378,211.96

Total CO

2 emissions excluding

net CO 2 from LULUCF 434,687.67 433,830.89 433,417.57 427,115.95 420,095.41 445,400.65 438,910.24 443,112.28 454,388.95 459,592.34

Memo Items:

International Bunk ers 8,549.97 8,576.11 8,392.37 8,762.20 8,992.41 9,708.35 8,936.90 9,260.17 9,930.35 10,691.95

Aviation 4,160.77 4,993.23 4,940.81 5,082.84 5,353.48 5,673.52 6,081.29 6,200.46 6,737.93 7,392.96

Marine 4,389.20 3,582.88 3,451.56 3,679.36 3,638.93 4,034.83 2,855.61 3,059.71 3,192.42 3,298.98
Multilateral Operations NE NE NE NE NE NE NE NE NE NE

CO 2 Emissions from Biomass 5,243.86 5,962.78 6,286.98 6,209.51 7,215.92 7,076.58 7,063.49 7,702.89 7,572.41 8,897.95

### 303

Table A 8 .1 CO 2 emissions trends, CRF year 200 7 (years 2000

– 200 7 )

TABLE 10 EMISSION TRENDS Inventory 2007

CO 2 Submission

2009 v1.3

(Part 2 of 2) ITALY

2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest reported year GREENHOUSE GAS SOURCE AND SINK

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) %

1. Energy 437,143.25 442,063.26 444,221.30 458,632.83 460,802.52 462,022.92 457,573.05 446,746.87 10.21

A. Fuel Combustion (Sectoral Approach) 434,558.53 439,623.18 441,960.77 455,798.73 458,650.37 459,910.88 455,384.37 444,571.12 10.58

1. Energy Industries 146,912.84 150,303.41 157,182.69 158,253.29 157,141.91 159,307.50 159,178.95 157,849.66 17.72
2. Manufacturing Industries and

Construction 88,134.43 85,411.61 81,539.62 86,418.00 86 ,243.55 81,731.73 82,106.25 78,866.83

- 11.32

3. Transport 120,109.01 122,181.08 124,142.62 125,105.60 127,090.52 125,830.22 127,151.03 127,212.06 25.62

4. Other Sectors 78,596.14 81,373.15 78,782.28 85,361.70 87,083.41 91,843.74 85,966.53 79,746.38 4.0 0

5. Other 806.10 353.94 313.56 660.15 1,090.98 1,197.69 981.61 896.19

- 14.35

B. Fugitive Emissions from Fuels 2,584.72 2,440.08 2,260.52 2,834.10 2,152.15 2,112.03 2,188.68 2,175.75

- 34.88

1. Solid Fuels NA NA NA NA NA NA NA NA 0.00

2. Oil and Natu ral Gas 2,584.72 2,440.08 2,260.52 2,834.10 2,152.15 2,112.03 2,188.68 2,175.75

- 34.88

2. Industrial Processes 24,096.81 24,858.46 24,817.98 25,855.77 26,653.41 26,457.34 26,559.08 26,924.41

- 0.98

A. Mineral Products 21,265.81 22,095.84 22,088.70 22,9 85.79 23,553.49 23,131.30 23,219.30 23,678.01 12.22

B. Chemical Industry 1,061.65 1,033.79 1,081.56 1,243.32 1,327.72 1,316.92 1,307.98 1,311.07

- 40.38

C. Metal Production 1,769.35 1,728.83 1,647.72 1,626.67 1,772.19 2,009.12 2,031.80 1,935.33

- 50.27

D. Other Production NA NA NA NA NA NA NA NA 0.00

E. Production of Halocarbons and SF 6 F. Consumption of Halocarbons and SF 6

G. Other NA NA NA NA NA NA NA NA 0.00

3. Solvent and Other Product Use 1,273.82 1,2 95.07 1,306.03 1,309.87 1,314.82 1,331.47 1,354.03 1,360.61

- 14.86

4. Agriculture

A. Enteric Fermentation

B. Manure Management

### 304

TABLE 10 EMISSION TRENDS Inventory 2007

CO 2 Submission

2009 v1.3

(Part 2 of 2) ITALY

2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest reported year GREENHOUSE GAS SOURCE AND SINK

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) %

C. Rice Cultivation

D. Agricultural Soils

E. Prescribed Burning of Savannas
F. Field Burning of Agricultural Residues

G. Other

5. Land Use, Land

- Use Change and Forestry

(2) - 79,326.04

- 92,671.78

- 95,683.41

- 126,869.62

- 91,87 8.49

- 95,374.01

- 90,136.26

- 71,126.53 5.14

A. Forest Land

- 70,452.09

- 79,009.29

- 85,423.00

- 74,789.16

- 80,933.35

- 83,523.40

- 84,194.42

- 55,588.35 3.81
B. Cropland

- 11,696.68

- 10,955.83

- 11,544.39

- 11,084.57

- 8,880.74

- 10,154.68

- 8,086.51

- 10,959.93

- 35.0 6

C. Grassland

- 386.82

- 5,910.99

- 1,918.25

- 44,160.58

- 5,223.97

- 4,849.13 NO

- 7,759.75 1,914.64

D. Wetlands NO NO NO NO NO NO NO NO 0.00

E. Settlements 3,209.54 3,204.33 3,202.23 3,164.68 3,159.56 3,153.20 2,144.67 3,181.49 0.69

F. Other Land NO NO NO NO NO NO NO NO 0.00

G. Other NA NA NA NA NA NA NA NA 0.00

6. Waste 201.57 222.26 244.97 215.76 199.23 244.69 267.49 270.17

- 49.68

A. Solid Waste Disposal on Land NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

B. Waste

- water Handling

C. Waste Incineration 201.57 222.26 244.97 215.76 199.23 244.69 267.49 270.17

- 49.68

D. Other NA NA NA NA NA NA NA NA 0.00

7. Other (as specified in Summary 1.A) NA NA NA NA NA NA NA NA 0.00

Total CO

2 emissions i ncluding net CO 2 from

LULUCF 383,389.41 375,767.27 374,906.87 359,144.61 397,091.49 394,682.39 395,617.40 404,175.53 10.12

Total CO

2 emissions excluding net CO 2 from

LULUCF 462,715.45 468,439.04 470,590.27 486,014.24 488,969.97 490,056.41 485,753.66 475,302.06 9.34

### 305

TABLE 10 EMISSION TRENDS Inventory 2007

CO 2 Submission

2009 v1.3

(Part 2 of 2) ITALY

2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest reported year GREENHOUSE GAS SOURCE AND SINK

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) %

Memo Items:

International Bunkers 12,196.09 12,824.92 12,862.42 14,809.34 15,426.56 16,029.88 17,274.95 18,185.82 112.70

Aviation 8,015.50 8,011.06 7,312.69 8,526.80 8,620.09 9,110.86 9,833.14 10,430.30 1 50.68

Marine 4,180.59 4,813.86 5,549.73 6,282.54 6,806.47 6,919.02 7,441.81 7,755.53 76.70

Multilateral Operations NE NE NE NE NE NE NE NE 0.00

CO 2 Emissions from Biomass 9,362.29 10,318.00 9,940.73 11,990.42 14,397.94 14,048.31 14,993.25 17,156.24 227. 17

### 306

Table A 8. 2 CH

4 emission trends, CRF year 200 7 (years 1990

– 1999)

TABLE 10 EMISSION TRENDS Inventory

200 7

CH 4 Submission

200 9 v1. 3

(Part 1 of 2) ITALY

Ba se year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999 GREENHOUSE GAS SOURCE AND SINK

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg)

1. Energy 427.06 428.68 434.14 428.93 420.03 408.72 401.36 399.65 402.51 391.33

A. Fuel Combustion (Sectoral Approach) 73.73 77.29 80.34 80.6 5 80.78 81.01 78.93 78.94 77.62 75.86
1. Energy Industries 9.27 8.93 8.59 8.14 8.39 8.63 8.41 8.60 8.52 8.26
2. Manufacturing Industries and

Construction 6.82 6.67 6.49 6.62 6.59 7.02 6.48 6.69 6.44 6.06

3. Transport 42.74 45.17 48.12 49.69 48.05 47 .13 46.03 43.92 42.78 39.33

4. Other Sectors 14.73 16.33 16.95 15.98 17.54 18.01 17.82 19.56 19.72 22.04

5. Other 0.17 0.19 0.20 0.22 0.21 0.22 0.19 0.17 0.16 0.18
B. Fugitive Emissions from Fuels 353.33 351.38 353.80 348.28 339.25 327.71 322.44 320.7 2 324.89 315.47

1. Solid Fuels 5.79 5.33 5.31 3.90 3.39 3.07 2.88 2.85 2.63 2.52

2. Oil and Natural Gas 347.54 346.06 348.48 344.38 335.86 324.64 319.56 317.87 322.26 312.95

2. Industrial Processes 5.16 4.95 4.83 4.87 5.07 5.36 2.99 3.23 3.10 3.05

A. Mineral Products NA NA NA NA NA NA NA NA NA NA
B. Chemical Industry 2.45 2.43 2.40 2.28 2.49 2.65 0.60 0.62 0.59 0.59

C. Metal Production 2.71 2.51 2.43 2.59 2.58 2.71 2.39 2.61 2.51 2.46

D. Other Production

E. Production o f Halocarbons and SF 6 F. Consumption of Halocarbons and SF 6

G. Other NA NA NA NA NA NA NA NA NA NA

3. Solvent and Other Product Use

4. Agriculture 819.80 829.39 807.99 805.18 807.07 82 0.15 821.62 823.14 816.91 823.22

A. Enteric Fermentation 579.93 592.81 574.81 568.74 573.87 584.15 586.80 589.39 585.33 591.84

### 307

TABLE 10 EMISSION TRENDS Inventory

200 7

CH 4 Submission

200 9 v1. 3

(Part 1 of 2) ITALY

Ba se year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999 GREENHOUSE GAS SOURCE AND SINK

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg)

B. Manure Management 164.86 164.82 158.67 158.32 153.34 156.48 156.90 156.26 157.94 159.48

C. Rice Cultivation 74.39 71.09 73.86 77.48 79.22 78.90 77.27 76.91 72.99 71.27

D. Agricultural Soils NA NA NA NA NA NA NA NA NA NA

E. Prescribed Burning of Savannas NO NO NO NO NO NO NO NO NO NO
F. Field Burning of Agricultural Residues 0.62 0.68 0.66 0.64 0.64 0.62 0.64 0.57 0.64 0.62

G. Other NA NA NA NA NA NA NA NA NA NA

5. Land Use, Land

- Use Change and Forestry 6.80 1.74 2.88 7.18 2.90 1.30 1.06 3.53 4.11 2.02

A. Forest Land 6.80 1.74 2.88 7.18 2.90 1.30 1.06 3.53 4.11 2.02

B. Cropland NO NO NO NO NO NO NO NO NO NO

C. G rassland NO NO NO NO NO NO NO NO NO NO

D. Wetlands NO NO NO NO NO NO NO NO NO NO

E. Settlements NO NO NO NO NO NO NO NO NO NO

F. Other Land NO NO NO NO NO NO NO NO NO NO

G. Other NA NA NA NA NA NA NA NA NA NA

6. Waste 735.55 787.21 773.85 796 .16 831.87 868.51 877.68 892.69 882.43 887.85

A. Solid Waste Disposal on Land 633.22 673.99 660.75 678.80 714.56 750.21 760.43 771.56 762.22 764.72

B. Waste

- water Handling 94.67 98.43 101.48 104.73 105.46 105.37 106.34 107.85 108.40 108.66

C. Waste I ncineration 7.65 14.78 11.61 12.61 11.81 12.91 10.89 13.24 11.76 14.38

D. Other 0.01 0.01 0.01 0.02 0.02 0.02 0.02 0.05 0.06 0.08

7. Other (as specified in Summary 1.A) NA NA NA NA NA NA NA NA NA NA

Total CH

4 emissions includin

g CH 4 from

LULUCF 1,994.37 2,051.97 2,023.69 2,042.32 2,066.93 2,104.04 2,104.72 2,122.24 2,109.06 2,107.46

Total CH

4 emissions excluding CH 4 from

LULUCF 1,987.57 2,050.23 2,020.82 2,035.14 2,064.03 2,102.74 2,103.66 2,118.71 2,104.95 2,105.44

### 308

TABLE 10 EMISSION TRENDS Inventory

200 7

CH 4 Submission

200 9 v1. 3

(Part 1 of 2) ITALY

Ba se year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999 GREENHOUSE GAS SOURCE AND SINK

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg)

Memo Items:

International Bunkers 0.47 0.39 0.38 0.41 0.41 0.45 0.34 0.37 0.39 0.41

Aviation 0.05 0.05 0.05 0.06 0.06 0.06 0.07 0.07 0.08 0.09

Marine 0.42 0.34 0.33 0.35 0.35 0.39 0.27 0.29 0.31 0.32
Multilateral Operat ions NE NE NE NE NE NE NE NE NE NE

CO 2 Emissions from Biomass

### 309

Table A8.2 CH

4 emission trends, CRF year 2007 (years 2000

– 2007 )

TABLE 10 EMISSION TRENDS Inventory 2007

CH 4 Submission

2009 v 1.3

(Part 2 of 2) ITALY

2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest
reported year GREENHOUSE GAS SOURCE AND SINK

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) %

1. Energy 377.01 358.32 351.73 344.74 336.78 334.27 3 10.02 308.70

- 27.71

A. Fuel Combustion (Sectoral Approach) 71.12 69.34 64.03 63.97 64.71 61.75 62.74 67.24

- 8.80
1. Energy Industries 6.85 5.95 5.92 6.14 6.21 6.34 6.43 6.32

- 31.80
2. Manufacturing Industries and

Construction 5.72 5.78 5.68 5.82 5.74 6.27 6.22 6.51

- 4.55

3. Transport 35.62 33.71 31.15 29.05 26.08 23.45 22.51 21.27

- 50.24

4. Other Sectors 22.81 23.82 21.21 22.86 26.53 25.53 27.45 33.03 124.24

5. Other 0.13 0.09 0.07 0.10 0.14 0.16 0.13 0.11

- 34.34
B. Fugitive Emissions from Fuel s 305.89 288.98 287.70 280.77 272.07 272.52 247.28 241.46

- 31.66

1. Solid Fuels 3.48 3.85 3.72 4.50 3.05 3.27 2.56 4.00

- 30.93

2. Oil and Natural Gas 302.41 285.13 283.98 276.27 269.03 269.25 244.72 237.46

- 31.67

2. Industrial Processes 3.01 2.83 2. 71 2.77 2.91 3.06 3.14 3.08

- 40.25

A. Mineral Products NA NA NA NA NA NA NA NA 0.00
B. Chemical Industry 0.40 0.33 0.33 0.31 0.33 0.33 0.32 0.34

- 86.32

C. Metal Production 2.61 2.50 2.38 2.46 2.58 2.72 2.81 2.75 1.43

D. Other Production

E. Production of Halocarbons and SF 6 F. Consumption of Halocarbons and SF 6

G. Other NA NA NA NA NA NA NA NA 0.00

3. Solvent and Other Product Use

4. Agriculture 801.77 765.51 748.8 6 751.55 739.99 737.16 721.39 743.77

- 9.27

A. Enteric Fermentation 579.30 539.99 525.24 526.47 516.01 516.37 506.13 525.07

- 9.46

### 310

TABLE 10 EMISSION TRENDS Inventory 2007

CH 4 Submission

2009 v 1.3

(Part 2 of 2) ITALY

2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest reported year GREENHOUSE GAS SOURCE AND SINK

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) %

B. Manure Management 156.10 159.18 155.39 154.84 150.26 150.06 144.34 145.57

- 11.70

C. Rice Cultivation 65.80 65.80 67.63 69.69 73.05 70.11 70.32 72.52

- 2.51

D. Agricultural Soils NA NA NA NA NA NA NA NA 0.00
E. Prescribed Burning of Savannas NO NO NO NO NO NO NO NO 0.00

F. Field Burning of Agricultural Residues 0.58 0.53 0.60 0.55 0.67 0.62 0.60 0.61

- 1.82

G. Other NA NA NA NA NA NA NA NA 0.00

5. Land Use, Land

- Use Change and Forestry 4.14 2.63 1.47 3.09 1.65 1.63 1.46 9.37 37.69

A. Forest Land 4.14 2.63 1.47 3.09 1.65 1.63 1.46 9.37 37.69
B. Cropland NO NO NO NO NO NO NO NO 0.00

C. Grassland NO NO NO NO NO NO NO NO 0.00

D. Wetlands NO NO NO NO NO NO NO NO 0.00

E. Settlements NO NO NO NO NO NO NO NO 0.00

F. Other Land NO NO NO NO NO NO NO NO 0.00

G. Other NA NA NA NA NA NA NA NA 0.00

6. Waste 922.81 917.27 889.05 857.06 817.38 813.34 777.08 764.32 3.91

A. Solid Waste Disposal on Land 801.16 793.42 765.11 733.44 690.02 687.46 649.42 635.27 0.32

B. Waste

- water Handling 109.62 110.74 111.19 110.60 110.98 111.55 113.97 115.95 22.48

C. Waste Incineration 11.94 12.98 12.59 12.85 16.20 14.14 13.47 12 .89 68.54

D. Other 0.10 0.12 0.16 0.18 0.18 0.20 0.21 0.22 1,961.04

7. Other (as specified in Summary 1.A) NA NA NA NA NA NA NA NA 0.00

Total CH

4 emissions including CH 4 from

LULUCF 2,108.75 2,046.55 1,993.81 1,959.21 1,898.71 1, 889.46 1,813.09 1,829.25

- 8.28

Total CH

4 emissions excluding CH 4 from

LULUCF 2,104.60 2,043.92 1,992.34 1,956.11 1,897.06 1,887.83 1,811.63 1,819.88

- 8.44

### 311

TABLE 10 EMISSION TRENDS Inventory 2007

CH 4 Submission

2009 v 1.3

(Part 2 of 2) ITALY

2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest reported year GREENHOUSE GAS SOURCE AND SINK

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) %

Memo Items:

International Bunkers 0.51 0.58 0.65 0.74 0.80 0. 83 0.88 0.87 86.52

Aviation 0.11 0.12 0.12 0.14 0.15 0.17 0.17 0.13 176.28

Marine 0.40 0.46 0.53 0.60 0.65 0.66 0.71 0.74 76.55

Multilateral Operations NE NE NE NE NE NE NE NE 0.00

CO 2 Emissions from Biomass

### 312

Table A 8 .3 N 2 O emission trends, CRF year 200 7 (years 1990

– 1999)

TABLE 10 EMISSION TRENDS Inventory

200 7

N 2 O Submission

200 9 v1. 3

(Part 1 of 2) ITALY

Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999 GREENHOUSE GAS SOURCE

AND SINK CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg)

1. Energy 14.89 14.88 15.19 15.33 15.89 17.09 17.47 17.77 17.86 18.15

A. Fuel Combustion (Sectoral Approach) 14.88 14.88 15.19 15.33 15.88 17.09 17.47 17.76 17.86 18.1 4

1. Energy Industries 1.63 1.55 1.51 1.44 1.46 1.64 1.59 1.59 1.61 1.52
2. Manufacturing

Industries and Construction 4.93 4.89 4.90 4.51 4.47 4.52 4.42 4.47 4.49 4.51

3. Transport 3.58 3.77 4.00 4.32 5.03 5.83 6.35 6.61 6.60 6.84

4. Other Sectors 4.52 4.44 4.53 4.78 4.66 4.88 4.94 4.89 4.99 5.13

5. Other 0.23 0.24 0.24 0.28 0.25 0.21 0.18 0.21 0.17 0.14
B. Fugitive Emissions from Fuels 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

1. Solid Fuels NA NA NA NA NA NA NA NA NA NA

2. Oil and Natural Gas 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

2. Industrial Processes 21.54 22.81 21.11 21.65 20.36 23.35 22.66 22.78 23.06 23.56

A. Mineral Products NA NA NA NA NA NA NA NA NA NA
B. Chemical Industry 21.54 22.81 21.11 21.65 20.36 2 3.35 22.66 22.78 23.06 23.56

C. Metal Production NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

D. Other Production

E. Production of Halocarbons

and SF 6 F. Consumption of Halocarbons

and SF 6

### 313

TABLE 10 EMISSION TRENDS Inventory

200 7

N 2 O Submission

200 9 v1. 3

(Part 1 of 2) ITALY

Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999 GREENHOUSE GAS SOURCE

AND SINK CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg)

G. Other NA NA NA NA NA NA NA NA NA NA

3. Solvent and Other Product Use 2.57 2.42 2.41 2.45 2.41 2.44 2.91 2.91 3.35 3.28

4. Agriculture 75.36 77.27 77.08 78.24 76.43 74.60 73.69 76.98 75.04 75.83

A. Enteric Fermentation

B. Manure Management 12.65 12.63 12.09 11.98 11.93 12.20 12.34 12.44 12.70 12.89

C. Rice Cultivation
D. Agricultural Soils 62.69 64.63 64.97 66.25 64.48 62.39 61.34 64.53 62.33 62.93
E. Prescribed Burning of

Savannas NO NO NO NO NO NO NO NO NO NO

F. Field Burning of Agricultural

Residues 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01

G. Other NA NA NA NA NA NA NA NA NA NA

5. Land Use, Land

- Use Change and Forestry 0.05 0.01 0.02 0.36 0.81 0.64 0.01 0.18 1.29 1.80

A. Forest Land 0.05 0.01 0.02 0.05 0.02 0.01 0.01 0.02 0.03 0.01

B. Cropland NO NO NO 0.31 0.79 0.63 NO 0.16 1.26 1.79

C. Grassland NO NO NO NO NO NO NO NO NO NO

D. Wetlands NO NO NO NO NO NO NO NO NO NO

E. Settlements NO NO NO NO NO NO NO NO NO NO

F. Other Land NO NO NO NO NO NO NO NO NO NO

G. Other NA NA NA NA NA NA NA NA NA NA

6. Waste 6.30 6.57 6.41 6.28 6.29 6.27 6.36 6.43 6.51 6.74

A. Solid Waste Disposal on

Land

B. Waste

- water Handling 6.01 6.08 6.01 5.86 5.89 5.85 6.01 6.00 6.12 6.28

C. Waste Incineration 0.28 0.49 0.40 0.42 0.40 0.42 0.36 0.43 0.39 0.45

D. Other NA NA NA NA NA NA NA NA NA NA

### 314

TABLE 10 EMISSION TRENDS Inventory

200 7

N 2 O Submission

200 9 v1. 3

(Part 1 of 2) ITALY

Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999 GREENHOUSE GAS SOURCE

AND SINK CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg)

7. Other (as specified in Summary
1.A) NA NA NA NA NA NA NA NA NA NA

Total N 2 O emis sions including N 2 O

from LULUCF 120.69 123.97 122.22 124.31 122.18 124.40 123.10 127.05 127.11 129.36

Total N 2 O emissions excluding N 2 O

from LULUCF 120.65 123.96 122.20 123.95 121.37 123.76 123.09 126.87 125.82 127.55

Memo Items:

International Bunkers 0.23 0.21 0.22 0.24 0.24 0.26 0.25 0.27 0.29 0.31

Aviation 0.12 0.12 0.13 0.14 0.15 0.16 0.18 0.19 0.21 0.23

Marine 0.11 0.09 0.09 0.09 0.09 0.10 0.07 0.08 0.08 0.08
Multilateral Operations NE NE NE NE NE NE NE NE NE NE

CO 2 Emissions from Biomass

### 315

Table A 8 .3 N 2 O emission trends, CRF year 200 7 (years 2000

– 200 7 )

TABLE 10 EMISSION TRENDS Inventory

2007

N 2 O Submission

2009 v1.3

(Part 2 of 2) ITALY

2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest reported year GREENHOUSE GAS SOURCE AND

SINK CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) %
1. Energy 18.26 18.39 18.25 18.55 18.97 17.62 17.75 17.56 17.95

A. Fuel Combustion (S ectoral Approach) 18.26 18.39 18.24 18.55 18.97 17.62 17.75 17.55 17.95
1. Energy Industries 1.60 1.69 1.77 1.80 1.88 1.89 1.84 1.82 12.09
2. Manufacturing Industries and

Construction 4.66 4.74 4.77 4.93 5.03 5.02 5.05 4.98 0.97

3. Transport 6.75 6. 62 6.53 6.28 6.19 4.78 5.02 4.94 37.84

4. Other Sectors 5.11 5.30 5.15 5.41 5.59 5.64 5.60 5.59 23.69

5. Other 0.14 0.03 0.02 0.13 0.28 0.29 0.24 0.23 0.71
B. Fugitive Emissions from Fuels 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 19.01

1. Solid Fuels NA NA NA NA NA NA NA NA 0.00

2. Oil and Natural Gas 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 19.01

2. Industrial Processes 25.54 26.55 25.49 24.38 27.24 25.03 8.54 6.10

- 71.68

A. Mineral Products NA NA NA NA NA NA NA NA 0.00
B. Chemical Industry 25.54 26.55 25.49 24.38 27.24 25.03 8.54 6.10

- 71.68

C. Metal Production NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA 0.00

D. Other Production

E. Production of Halocarbons and SF 6 F. Consumption of Halocarbons an d

SF 6 G. Other NA NA NA NA NA NA NA NA 0.00

### 316

TABLE 10 EMISSION TRENDS Inventory

2007

N 2 O Submission

2009 v1.3

(Part 2 of 2) ITALY

2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest
reported year GREENHOUSE GAS SOURCE AND

SINK CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) %

3. Solvent and Other Product Use 3.26 2.95 2.95 2.76 2.67 2.61 2.56 2.49

- 3.04
4. Agriculture 74.52 73.80 72.66 72.00 72.19 70.20 69.28 69.65

- 7.57

A. Enteric Fermentation

B. Manure Management 12.46 12.90 12.41 12.31 12.03 12.02 11.67 12.25

- 3.18

C. Rice Cultivation
D. Agricultural Soils 62.06 60.89 60.24 59.68 60.14 58.17 57.60 57.39

- 8.46
E. Prescribed Burning of Savannas NO NO NO NO NO NO NO NO 0.00
F. Field Burning of Agricultural

Residues 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.65

G. Other NA NA NA NA NA NA NA NA 0.00

5. Land Use, Land

- Use Change and Forestry 0.03 0.02 0.01 0.02 0.01 0.01 0.97 0.06 37.69

A. Forest Land 0.03 0.02 0.01 0.02 0.01 0.01 0.01 0.06 37.69
B. Cropland NO NO NO NO NO NO 0.96 NO 0.00

C. Grassland NO NO NO NO NO NO NO NO 0.00

D. Wetlands NO NO NO NO NO NO NO NO 0.00

E. Settlements NO NO NO NO NO NO NO NO 0.00

F. Other Land NO NO NO NO NO NO NO NO 0.00

G. Other NA NA NA NA NA NA NA NA 0.00

6. Waste 6.71 6.65 6.64 6.67 6.81 6.80 6.84 6.90 9.54

A. Solid Waste Disposal on Land

B. Waste

- water Handling 6.35 6.25 6.26 6.29 6.34 6.38 6.44 6.51 8.29

C. Waste Incineration 0.36 0. 39 0.38 0.38 0.47 0.42 0.40 0.39 35.96

D. Other NA NA NA NA NA NA NA NA 0.00

7. Other (as specified in Summary 1.A) NA NA NA NA NA NA NA NA 0.00

### 317

TABLE 10 EMISSION TRENDS Inventory

2007

N 2 O Submission

2009 v1.3

(Part 2 of 2) ITALY

2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest
reported year GREENHOUSE GAS SOURCE AND

SINK CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) %

Total N 2 O emissions including N 2 O from

LULUCF 128.33 128.37 125.99 124.38 127.89 122. 27 105.94 102.76

- 14.86

Total N 2 O emissions excluding N 2 O from

LULUCF 128.30 128.35 125.98 124.36 127.88 122.25 104.97 102.70

- 14.88

Memo Items:

International Bunkers 0.35 0.36 0.36 0.37 0.38 0.39 0.41 0.44 90.94

Av iation 0.25 0.24 0.22 0.21 0.21 0.21 0.22 0.24 104.38

Marine 0.11 0.12 0.14 0.16 0.17 0.18 0.19 0.20 76.55
Multilateral Operations NE NE NE NE NE NE NE NE 0.00

CO 2 Emissions from Biomass

### 318

Table A8 .4 HFC, PFC and SF 6 em ission trends, CRF year 200 7 (1990

– 1999)

TABLE 10 EMISSION TRENDS Inventory 200 7

HFCs, PFCs and SF 6 Submission

200 9 v1.3

(Part 1 of 2) ITALY
Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999 GREENHOUSE GAS SOURCE AND

SINK CATEGORIES (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg)

Emissions of HFCs (3)

- (Gg CO 2 equivalent) 351.00 355.43 358.78 355.42 481.90 671.29 450.33 755.74 1,181.72 1,523.65

HFC

- 23 0.03 0.03 0.03 0.03 0.03 0.03 0.00 0.00 0.00 0.00

HFC

- 32 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00 0.00 0.02 0.05

HFC

- 41 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

HFC

- 43

- 10mee NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

HFC

- 125 NA,NO 0.00 0.00 0.00 0.00 0.01 0.01 0.04 0.05 0.08

HFC

- 134 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

HFC

- 134a NA,NO 0.00 0.00 0.00 0.10 0.20 0.29 0.43 0.68 0.85

HFC

- 152a NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

HFC

- 143 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

HFC

- 143a NA,NO NA,NO NA,NO NA,NO NA,NO 0.01 0.01 0.02 0.03 0.03

HFC

- 227ea NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00 0.00 0.00 0.01

HFC

- 236fa NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

HFC

- 245ca NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO
Unspecified mix of listed HFCs (4)

- (Gg

CO 2 equivalent) NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

Emissions of PFCs (3)

- (Gg CO 2 equivalent) 1,807.65 1,451.54 849.56 707.47 476.84 490.80 243.39 252.08 270.43 258.00

CF 4 0.21 0.17 0.10 0.08 0.06 0.06 0.03 0.03 0.03 0.03

C 2 F 6 0.05 0.04 0.02 0.02 0.01 0.01 0.01 0.01 0.01 0.01

C 3 F 8 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

C 4 F 10 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

c

- C 4 F 8 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00 0.00

C 5 F 12 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

C 6 F 14 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

### 319

TABLE 10 EMISSION TRENDS Inventory 200 7

HFCs, PFCs and SF 6 Submission

200 9 v1.3

(Part 1 of 2) ITALY
Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999 GREENHOUSE GAS SOURCE AND

SINK CATEGORIES (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg)

Unspecified mix of liste d PFCs (4)

- (Gg

CO 2 equivalent) NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

Emissions of SF6 (3)

- (Gg CO 2 equivalent) 332.92 356.39 358.26 370.40 415.66 601.45 682.56 728.64 604.81 404.51

SF 6 0.01 0.01 0.01 0.02 0.02 0.03 0.03 0.03 0.03 0.02

### 320

Table A 8 .4 HFC, PFC and SF 6 emission trends, CRF year 200 7 (2000

– 2007 )

TABLE 10 EMISSION TRENDS Inventory 2007

HFCs, PFCs and SF 6 Submission

2009 v1.3

(Part 2 of 2) ITALY

2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest reported year GREENHOUSE GAS SOURCE AND SINK

CATEGORIES
(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) %

Emissions of HFCs (3)

- (Gg CO 2 equivalent) 1,985.67 2,549.75 3,099.90 3,795.82 4,514.91 5,267.03 5,956.20 6, 700.69 1,809.03

HFC

- 23 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

- 92.53

HFC

- 32 0.08 0.12 0.17 0.23 0.29 0.36 0.43 0.49 100.00

HFC

- 41 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

HFC

- 43

- 10mee NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

H FC

- 125 0.13 0.20 0.28 0.38 0.48 0.59 0.69 0.79 100.00

HFC

- 134 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

HFC

- 134a 1.01 1.19 1.31 1.50 1.67 1.83 1.96 2.15 100.00

HFC

- 152a NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

HFC

- 143 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

HFC

- 143a 0.06 0.08 0.11 0.15 0.19 0.24 0.28 0.32 100.00

HFC

- 227ea 0.01 0.01 0.01 0.02 0.02 0.03 0.03 0.04 100.00

HFC

- 236fa NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

HFC

- 245ca NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

Unspecified mix of listed HFCs (4)

- (Gg CO 2 equivalent) NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

Emissions of PFCs (3)

- (Gg CO 2 equivalent) 345.85 451.24 423.74 497.63 347.89 352.62 282.30 287.78

- 84.08

CF 4 0.04 0.05 0.04 0.05 0.04 0.04 0.03 0.04

- 82.52

C 2 F 6 0.01 0.01 0.02 0.02 0.01 0.01 0.01 0.00

- 90.34

C 3 F 8 NA,NO 0.00 0.00 0.00 0.00 0.00 0.00 0.00 100.00

C 4 F 10 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

c

- C 4 F 8 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 100.00

C 5 F 12 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

C 6 F 14 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

Unspecified mix of listed PFCs (4)

- (Gg CO 2 equivalent) NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA ,NO 0.00

### 321

TABLE 10 EMISSION TRENDS Inventory 2007

HFCs, PFCs and SF 6 Submission

2009 v1.3

(Part 2 of 2) ITALY

2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest reported year GREENHOUSE GAS SOURCE AND SINK

CATEGORIES
(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) %

Emissions of SF6 (3)

- (Gg CO 2 equivalent) 493.43 795.34 739.72 467.56 502.14 465.39 405.87 427.55 28.42

SF 6 0.02 0.03 0.03 0.02 0.02 0.02 0.02 0.02 28.42

### 322

Table A 8 .5 Total emission trends, CRF year 200 7 (years 1990

– 1999)

TABLE 10 EMISSION TRENDS Inventory

2007

SUMMARY Submission

2009 v1.3 (Part 1 of 2) ITALY

GREENHOUSE GAS EMISSIONS Base year ( 1990 ) 1991 1992 1993 1994 1995 1996 1997 1998 1999

CO 2 equivalent (Gg) CO 2 equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg)

CO 2 emissions including net CO 2 from

LULUCF 367,036.98 348,231.74 350,168.42 361,573.12 338, 908.25 359,584.64 346,788.60 362,121.93 377,855.10 378,211.96

CO 2 emissions excluding net CO 2 from

LULUCF 434,687.67 433,830.89 433,417.57 427,115.95 420,095.41 445,400.65 438,910.24 443,112.28 454,388.95 459,592.34

CH 4 emissions including CH 4 from

LULUC F 41,881.77 43,091.33 42,497.57 42,888.68 43,405.52 44,184.91 44,199.08 44,567.03 44,290.23 44,256.72

CH 4 emissions excluding CH 4 from

LULUCF 41,738.88 43,054.80 42,437.17 42,737.86 43,344.67 44,157.53 44,176.91 44,492.96 44,204.00 44,214.27

N 2 O emission s including N 2 O from

LULUCF 37,414.74 38,430.48 37,887.77 38,535.38 37,875.03 38,563.14 38,160.65 39,386.46 39,405.46 40,101.12

N 2 O emissions excluding N 2 O from

LULUCF 37,400.24 38,426.77 37,881.64 38,423.30 37,624.23 38,364.14 38,158.40 39,329.54 39,005. 59 39,541.79

HFCs 351.00 355.43 358.78 355.42 481.90 671.29 450.33 755.74 1,181.72 1,523.65

PFCs 1,807.65 1,451.54 849.56 707.47 476.84 490.80 243.39 252.08 270.43 258.00

SF 6 332.92 356.39 358.26 370.40 415.66 601.45 682.56 728.64 604.81 404.51

Total ( including LULUCF) 448,825.07 431,916.91 432,120.36 444,430.47 421,563.19 444,096.25 430,524.60 447,811.87 463,607.74 464,755.97
Total (excluding LULUCF) 516,318.37 517,475.83 515,302.99 509,710.39 502,438.71 529,685.87 522,621.82 528,671.23 539,655.49 545 ,534.56

GREENHOUSE GAS SOURCE AND

SINK CATEGORIES Base year
( 1990 ) 1991 1992 1993 1994 1995 1996 1997 1998 1999

CO 2 equivalent
(Gg) CO 2 equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg)

1. Energy 418,945.37 418,507.58 417,773.58 414,370.53 408,283.14 431,961.27 427,888.89 432,024.86 443,394.73 448,402.46

2. Industrial Processes 36,466.66 36,130.61 35,5 32.23 32,696.69 31,362.64 34,530.35 31,480.33 31,969.10 32,421.90 32,862.34

3. Solvent and Other Product Use 2,394.46 2,334.44 2,334.44 2,293.12 2,210.30 2,179.77 2,279.45 2,279.79 2,367.00 2,348.44
4. Agriculture 40,576.25 41,371.34 40,862.45 41,162. 90 40,640.82 40,348.92 40,096.87 41,150.14 40,418.37 40,795.03

5. Land Use, Land

- Use Change and

- 67,493.30

- 85,558.91

- 83,182.63

- 65,279.92

- 80,875.52

- 85,589.62

- 92,097.22

- 80,859.36

- 76,047.75

- 80,778.59

### 323

Forestry (5)

6. Waste 17,935.63 19,131.86 18,8 00.28 19,187.14 19,941.81 20,665.57 20,876.28 21,247.33 21,053.50 21,126.28

7. Other NA NA NA NA NA NA NA NA NA NA
Total (including LULUCF) (5) 448,825.07 431,916.91 432,120.36 444,430.47 421,563.19 444,096.25 430,524.60 447,811.87 463,607.74 464,755.97

### 324

Table A 8 .5 Total emission trends, CRF year 200 7 (years 20 00

– 200 7 )

TABLE 10 EMISSION TRENDS Inventory 2007

SUMMARY Submission

2009 v1.3 (Part 2 of 2) ITALY

GREENHOUSE GAS EMISSIONS 2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest reported year

CO 2 equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg) CO 2

equivalent
(Gg) (%)

CO 2 emissions includi

ng net CO 2 from LULUCF 383,389.41 375,767.27 374,906.87 359,144.61 397,091.49 394,682.39 395,617.40 404,175.53 10.12

CO 2 emissions excluding net CO 2 from LULUCF 462,715.45 468,439.04 470,590.27 486,014.24 488,969.97 490,056.41 485,753.66 475,302.06 9.34

CH 4 emissions including CH 4 from

LULUCF 44,283.69 42,977.57 41,870.01 41,143.38 39,872.85 39,678.68 38,074.79 38,414.21

- 8.28

CH 4 emissions excluding CH 4 from

LULUCF 44,196.69 42,922.38 41,839.08 41,078.41 39,838.23 39,644.52 38,044.18 38,217.46

- 8.44

N 2 O emissions including N 2 O from

LULUCF 39,781.10 39,793.53 39,056.12 38,558.95 39,645.33 37,902.46 32,841.82 31,855.78

- 14.86

N 2 O emissions excluding N 2 O from

LULUCF 39,772.27 39,787.93 39,052.98 38,552.36 39,641.82 37,898.99 32,540.21 31,835.81

- 14.88

HF Cs 1,985.67 2,549.75 3,099.90 3,795.82 4,514.91 5,267.03 5,956.20 6,700.69 1,809.03

PFCs 345.85 451.24 423.74 497.63 347.89 352.62 282.30 287.78

- 84.08

SF 6 493.43 795.34 739.72 467.56 502.14 465.39 405.87 427.55 28.42

Total (including LULUCF) 470,279.15 462,334.69 460,096.36 443,607.96 481,974.60 478,348.57 473,178.39 481,861.53 7.36

Total (excluding LULUCF) 549,509.36 554,945.68 555,745.69 570,406.02 573,814.96 573,684.95 562,982.42 552,771.35 7.06

GREENHOUSE GAS SOURCE

AND SINK CATEGORIES 2000 2001 2002 2003 2004 2005 2006 2007 Change from

base to latest
reported year

CO 2 equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg) CO 2

equivalent (Gg) (%)

1 . Energy 450,722.44 455,289.63 457,263.97 471,622.91 473,756.12 474,505.53 469,585.98 458,672.79 9.48

2. Industrial Processes 34,903.34 36,946.22 37,039.91 38,231.91 40,522.46 40,366.88 35,915.85 36,295.95

- 0.47

### 325

3. Solvent and Other Product Use 2,284 .53 2,210.51 2,219.20 2,166.67 2,143.88 2,139.11 2,146.55 2,132.81

- 10.93
4. Agriculture 39,939.85 38,953.95 38,250.04 38,101.53 37,917.46 37,241.73 36,627.42 37,210.50

- 8.29

5. Land Use, Land

- Use Change and
Forestry (5) - 79,230.21

- 92,610.99

- 95,649.3 4

- 126,798.06

- 91,840.36

- 95,336.38

- 89,804.03

- 70,909.82 5.06

6. Waste 21,659.21 21,545.38 20,972.57 20,283.00 19,475.03 19,431.70 18,706.62 18,459.31 2.92

7. Other NA NA NA NA NA NA NA NA 0.00

Total (including LULUCF) (5) 470,279.15 462,334.69 460,096.36 443,607.96 481,974.60 478,348.57 473,178.39 481,861.53 7.36

### 326



## ANNEX 9 : METHODOLOGIES, DATA SOURCES AND EMISSION

FACTORS

This appendix shows a copy of Tables I

- 1

- I

- 4 on methodologies, data sources and emission factors

used for the Italian invent ory communicated to the European Commission under the implementing provisions for the compilation of The European Community Inventory.

### 327

Table A 9 .1 Methods, activity data and emission factors used for the Italian Inventory

ANNEX I

Table for methodologies , data sources and emission factors used by Member States for EC key sources for the purpose of Article 4(1)(b). Information on methods used could be the tier method, the model or a country

- specific approach. Activity data could be from national statistics or plant

- specific. Emission factors could be the IPCC default emission factors as outlined in the revised 1996 IPCC guidelines for national greenhouse gas inventories and in the IPCC good practice guidance, country

- specific emission factors, plant

specifi c emission factors or CORINAIR emission factors developed under the 1979 Convention on Long

- Range Transboundary Air Pollution.

Table I

- 1: Community summary report for methods, activity data and emission factors used (Energy)

GREENHOUSE GAS

SOURCE AND S INK CO 2 CH 4 N 2 O

CATEGORIES Key

source (1) Method

applied (2) Activity

data (3) Emission

factor (4) Key

source (1) Method

applied (2) Activity

data (3) Emission

factor (4) Key

source (1) Method

applied (2) Activity

data (3) Emission

factor (4)

1. Energy

A. Fuel Combustion

1. Energy Industries
a. Public Electricity

and Heat Production

Liquid fuels Yes T3 NS, PS CS No No

Solid fuels Yes T3 NS, PS CS No Yes T3 NS, PS C, D

Gaseous fuels Yes T3 NS, PS CS No No

Other fuels Yes T3 NS, PS CS No No

b. Petroleum Refining

Liquid fuels Yes T3 NS, PS CS No No

Solid fuels Yes NA NA NA No No

Gaseous fuels Yes T3 NS, PS CS No No

c. Manufacture of

Solid Fuels and Other Energy Industries

Solid fuels Yes T3 NS CS No No

Gaseous fuels Yes T3 NS CS No No

2. Manufacturing

Industries and

### 328

GREENHOUSE GAS

SOURCE AND S INK CO 2 CH 4 N 2 O

CATEGORIES Key

source (1) Method

applied (2) Activity

data (3) Emission

factor (4) Key

source (1) Method

applied (2) Activity

data (3) Emission

factor (4) Key

source (1) Method

applied (2) Activity

data (3) Emission

factor (4)

Construction

a. Iron and Steel

Liquid fuels Yes T2 NS CS No No

Solid fuels Yes T2 NS CS No No

Gaseous fuels Yes T2 NS CS No No

b. Non

- Ferrous

Metals

Solid fuels Yes T2 NS CS No No

Gaseous fuels No T2 NS CS No No

c. Chemicals

Liquid fuels Yes T2 NS CS No No

Solid fuels Yes T2 NS CS No No

Gaseous fuels Yes T2 NS CS No No

Other fuels Yes T2 NS CS No No

d. Pulp, Paper and

Print

Liquid fuels Yes T2 NS CS No No

Gaseous fuels Yes T2 NS CS No No

e. Food Processing,
Beverages and Tobacco

Liquid fuels Yes T2 NS CS No No

Solid fuels Yes T2 NS CS No No

Gaseous fuels Yes T2 NS CS No No

f. Other (as specified
in table 1.A(a)s2)

Liquid fuels Yes T2 NS CS No No

Solid fuels Yes T2 NS CS No No

Gaseous fuels Yes T2 NS CS No No

Other fuels Yes T2 NS CS No No

3. Transport

a. Civil Aviation

### 329

GREENHOUSE GAS

SOURCE AND S INK CO 2 CH 4 N 2 O

CATEGORIES Key

source (1) Method

applied (2) Activity

data (3) Emission

factor (4) Key

source (1) Method

applied (2) Activity

data (3) Emission

factor (4) Key

source (1) Method

applied (2) Activity

data (3) Emission

factor (4)

Jet kerosene Yes T1, T2 NS CS No No

b. Road Transportation

Gasoline Yes COPERT IV NS, AS CS Yes COPERT

IV NS, AS CS Yes CO PERT IV NS, AS CS

Diesel oil Yes COPERT IV NS, AS CS No Yes COPERT IV NS, AS CS

LPG Yes COPERT IV NS, AS CS No No

Other fuels No No No

c. Railways

Liquid fuels Yes D NS CS No No

d . Navigation

Gas/Diesel oil Yes T1, T2 NS CS No No

Residual Oil Yes T1, T2 NS CS No No

e. Other Transportation (as specified in table
1.A(a)s3)

Gaseous Fuels Yes T2 NS CS No No

4. Other Sectors

a. Commercial/Institutional

Liquid fuels Yes T2 NS CS No No

Solid fuels Yes T2 NS CS No No

Gaseous fuels Yes T2 NS CS No No

b. Residential

Liquid fuels Yes T2 NS CS No No

Solid fuels Yes T2 NS CS No No

Gaseous fuels Yes T2 NS CS No No

c. Agriculture/Forestry

/Fisheries

### 330

GREENHOUSE GAS

SOURCE AND S INK CO 2 CH 4 N 2 O

CATEGORIES Key

source (1) Method

applied (2) Activity

data (3) Emission

factor (4) Key

source (1) Method

applied (2) Activity

data (3) Emission

factor (4) Key

source (1) Method

applied (2) Activity

data (3) Emission

factor (4)

Liquid fuels Yes T2 NS CS No No

Solid fuels Yes T2 NS CS No No

Gaseous fuels Yes T2 NS CS No No

5. Other

a. Stationary

Solid fuels Yes NA NA NA No No

b. Mobile

Liquid fuels Yes T2 NS CS No No

B. Fugitive Emissions

from Fuels

1. Solid Fuels

a. Coal Mining No Yes T1 NS D, CS No

b. Solid Fuel

Transformation No No No

c. Other

(as specified in table 1.B.1) No No No

2. Oil and Natural Gas

a. Oil Yes T1, T2 NS D, CS No No

b. Natural Gas No Yes T1, T2 NS D, CS No

c. Venting and Flaring Yes T2 NS CS No No

d. Other

(as specified in table 1.B.2) No No No

### 331

Table I

- 2: Community summary report for methods, activity data and emission factors used (Industrial Processes)

GREENHOUSE GAS SOURCE

AND SINK CO 2 CH 4 N 2 O HFCs PFCs SF 6

CATEGORIESKey source(1)Method applied(2)Activity data(3)Emission factor(4)Key source(1)Method applied(2)Activity data(3)Emission factor(4)Key source(1)Method applied(2)Activity data(3)Emission factor(4)Key source(1)Method applied(2)Activity data(3)Emission factor(4)Key source(1)Method applied(2)Activity data(3)Emission factor(4)Key source(1)Method applied(2)Activity data(3)Emission factor(4)

2. Industrial Processes

A. Mineral Products

1. Cement Production Yes T2 NS CS, PS No No

2. Lime Production Yes D NS CS,PS No No

3. Limesto ne and Dolomite Use Yes D NS D, CS,PS No No

4. Soda Ash Production and Use No No No

5. Asphalt Roofing No No No

6. Road Paving with Asphalt No No No

7. Other (as specified in table
2(I)A

- G) No No No

B. Chemical Industry

1. Ammonia Production Yes D NS,PS C, PS No No No No No

2. Nitric Acid Production No No Yes D PS D,

PS No No No

3. Adipic Acid Production No No Yes D PS PS No No No

4. Carbide Production No No No No No No

5. Other (as specified in table
2(I)A

- G) Yes D PS PS No Yes D NS,

AS C,
CS,

PS No No No

C. Metal Production

1. Iron and Steel Productio n Yes D NS C, CS,

PS No No No No

2. Ferroalloys Production No No No No No

3. Aluminium Production No No No Yes T1,

T2 PS PS No

4. SF 6 Used in Aluminium and Mag nesium Foundries No No No No No

### 332

GREENHOUSE GAS SOURCE

AND SINK CO 2 CH 4 N 2 O HFCs PFCs SF 6

CATEGORIESKey source(1)Method applied(2)Activity data(3)Emission factor(4)Key source(1)Method applied(2)Activity data(3)Emission factor(4)Key source(1)Method applied(2)Activity data(3)Emission factor(4)Key source(1)Method applied(2)Activity data(3)Emission factor(4)Key source(1)Method applied(2)Activity data(3)Emission factor(4)Key source(1)Method applied(2)Activity data(3)Emission factor(4)

5. Other (as specified in table
2(I)A

- G) No No No No No

D. Other Production

1. Pulp and Paper No

2. Food and Drink No

E. Production of Halocarbons and

SF 6 1. By

- product Emissions Yes CS PS PS No Yes CS PS PS

2. Fugi tive Emissions No No No

3. Other (as specified in table
2(II) Yes NA NA NA No No

F. Consumption of Halocarbons

and SF 6 1. R efrigeration and Air
Conditioning Equipment Yes T2 AS CS No No

2. Foam Blowing Yes T2 AS D No No

3. Fire Extinguishers No No No

4. Aeros ols/ Metered Dose

Inhalers Yes T2 AS CS No No

5. Solvents No No No

6. Other applications using ODS

substitutes No No No

7. Semic onductor Manufacture No No No

8. Electrical Equipment No No No

9. Other (as specified in table
2(II) No No Yes NA NA NA

G. Other

### 333

Table I

- 3: Community summary report for methods, activity data and emission factors used (Solvent and Other Product Use, Agriculture)

GREENHOUSE GAS SOURCE AND SINK CO 2 CH 4 N 2 O

CATEGORIES Key

source (1) Method
applied

(2) Activity

data (3) Emission

factor (4) Key

source (1) Method
applied

(2) Activity

data (3) Emission

factor (4) Key

source (1) Method
applied

(2) Activity

data (3) Emission

factor (4)

3. Solvent and Other Product Use

A. Paint Application No No

B. Degreasing and Dry Cleaning No No

C. Chemical Products, Manufacture and Processing No No

D. Other No No

4. Agriculture

A. Enteric Fermentation

1. Cattle Yes T2 NS CS

2. Buffalo No

3. Sheep Yes T1 NS D

4. Other No

B. Manure Management

1. Cattle Yes T2 NS CS No

2. Buffalo No No

3. Sheep No No

4. Other No No

8. Swine Yes T2 NS CS No

13. Solid Storage and Dry Lot No Yes T2 NS D, CS

C. Rice Cultivation

D. Agricultural Soils

1. Direct Soil Emissions No No Yes D NS D, CS

2. Pasture, range and paddock manure No No Yes D NS D, CS

3. Indirect Emissions No No Yes D NS D, CS

4. Other (as specified in table 4.D) No No N o

E. Prescribed Burning of Savannas No No

F. Field Burning of Agricultural Residues No No

G. Other No No

### 334

Table I

- 4: Community summary report for methods, activity data and emission factors use d (Land

- Use Change and Forestry, Waste, Other)

GREENHOUSE GAS SOURCE AND

SINK CO 2 CH 4 N 2 O

CATEGORIES Key

source (1) Method applied (2) Activity

data (3) Emission

factor (4) Key

source (1) Method applied

(2) Activity

data (3) Emission

factor (4) Key

source (1) Method applied

(2) Activity

data (3) Emission

factor (4)

5. Land

- Use, Land

- Use Change and
Forestry

A. Forest Land

1. Forest Land remaining Forest Lands Yes T1, T2 NS D, CS No No

2. Land converted to Forest Lands Yes T1, T2 NS D, CS No No

B. Cropland

1. Cropland remaining Cropland Yes T1 NS D, CS No No

2. Land converted to Cropland Yes T1 NS D, CS No No

C . Grassland

1. Grassland remaining Grassland Yes T1 NS D, CS No No

2. Land converted to Grassland Yes T1 NS D, CS No No

D. Wetlands

1. Wetlands remaining Wetlands No No No

2. Land converted to Wetlands No No No

E. Settlements

1. Settlements remaining Settlements No No No

2. Land converted to Settlements Yes T1 NS D, CS No No

F. Other Land

1. Other Land remaining Other Land No No

2. Land converted to Other Land No No No

G. Other (please specify)

Harvested W ood Products No No No

6. Waste

A. Solid Waste Disposal on Land

1. Managed Waste Disposal on Land No Yes T2 NS CS

2. Unmanaged Waste Disposal Sites No Yes T2 NS CS

3. Other (as specified in table 6.A) No No

B. Wastewater Handling

### 335

GREENHOUSE GAS SOURCE AND

SINK CO 2 CH 4 N 2 O

CATEGORIES Key

source (1) Method applied (2) Activity

data (3) Emission

factor (4) Key

source (1) Method applied

(2) Activity

data (3) Emission

factor (4) Key

source (1) Method applied

(2) Activity

data (3) Emission

factor (4)

1. Industrial Wastewater No No

2. Domestic and Commercial Wastewater Yes D NS D Yes D NS D

3. Other (as specified in table 6.B) No No

C. Waste Incineration

D. Other No No No

7. Other (as specified in Summary 1.A)

Memo Items: (8 )

International Bunkers

Aviation No No No

Marine No No No

CO 2 Emissions from Biomass No No No

Legend for tables I

- 1 to I

- 4

(1) Key sources of the Community. To be completed by Commission/EEA with results from key category analysis from previous inventory submission.

(2) Use the following notation keys to specify the method applied:

D (IPCC default), T1a, T1b, T1c (IPCC Tier 1a, Tier 1b and Tier 1c, respectively), C (CORINAIR), COPERT X (Copert Model X =
Version)

RA (Reference Approach), T2 (IPCC Tier
2), CS (Country Specific).

T1 (IPCC Tier 1), T3 (IPCC Tier 3), M (Model)
If using more than one method within one source category, enumerate the relevant methods. Explanations regarding country

- specific methods or any modifications to the default IPCC methods, as well as information regarding the use of

Different methods per source category where more than one m ethod is indicated, should be provided in the documentation box.

(3) Use the following notation keys to specify the sources of activity data used :

NS (national
statistics), IS (International
statistics), AS (associations, business organizatio ns)

RS (regional statistics), PS (Plant Specific data). Q (specific questionnaires, surveys)

If keys above are not appropriate for national circumstances, use additional keys and explain those in the documentation box.

Where a mix of AD sou rces has been used, use different notations in one and the same cells with further explanations in the documentation box.

(4) Use the following notation keys to specify the emission factor used:

### 336 D (IPCC default), CS (Country Specific),

C (CORINAIR), PS (Plant Specific).

Where a mix of emission factors has been used, use different notations in one and the same cells with further explanations in the documentation box.

Documentation box:
* The full information on methodological issues, such as methods, activity data and emission factors used, can be found in the relevant sector sections of chapter 5 of the NIR. If any additional

information is needed

To understand the content of this table, use this documentation box to provide references to the relevant section of the NIR where further details can be found.
* Where a mix of methods/ emission factors has been used within one source category, use this documentation box to spec ify those methods/emission factors for the various sub

- sources where they have been applied
(see also footnotes 2 to 4 to
this table).

### 337



## ANNEX 10 : THE NATIONAL REGISTRY FOR FOREST CARBON SINKS

The so

- called “National Registry for forest carbon sinks” is part of the Italian National System; it is the
instrument to estimate, in accordance with the COP/MOP decisions, the IPCC Good Practice Guidance on LULUCF and every relevant IPCC guidelines, the greenhouse gases emissions by source s and removals by sinks in forest land and related land

- use changes and to account for the net removals in order to allow the Italian Registry to issue the relevant amount of RMUs.

Italy has approved the National Plan for greenhouse gases reduction (P NR GHG 

### ) with the CIPE
( Interministerial Economic Planning Committee ) decision n. 123, of 19 December 2002. The PNR GHG 

### sets policies and measures to act in order to achieve the national target of the Kyoto Protocol; Italy has

committed to 6.5% reduction belo w 1990 greenhouse gases emission levels. The article 7.4 of CIPE decision (123/2002) states that Ministry for the Environment, Land and Sea (MATTM), in agreement with Ministry of Agriculture, Food and Forest Policies (MIPAAF) has to constitute, the Nationa l Registry for the forest carbon sinks to account for the net removals in the period 2008

– 2012, from Afforestation

, Reforestation and Deforestation activities (art. 3.3 KP) and from elected activities under article 3.4 of Kyoto Protocol ( Forest managemen t

). Italy, in the “

Report on the determination of Italy’s assigned amount under Article 7, paragraph 4, of the Kyoto Protocol

” (Decision 13/CMP.1), has reported:

- the election of Forest Management as an activity under Article 3.4 of Kyoto Protocol and has

a dopted the forest definition in agreement with Food and Agriculture Organization of the United

Nations definitions, with the following threshold values for tree crown cover, land area and tree height :

a. a minimum area of land of 0.5 hectares;

b. tree crown cov

er of 10 per cent;

c. minimum tree height of 5 meters. Italy’s forest area eligible under Forest management activity is the total forest area, since the entire Italian forest area has to be considered managed.



## Collecting data

Scientific advice

Scientific Committee 

## Implementation

National Registry Unit 

## Data submission

UNFCCC

Secretariat 

## National Registry for forest carbon sinks

### 338

Under SBSTA conclusion FCCC/SBSTA/2006/L.6 and re lated draft COP/MOP2 decision (FCCC/SBSTA/2006/L.6/Add.1), credits from forest management are capped, in the first commitment period, to 2,78 Mt C per year, times fives. Italy intends to account for Article 3.3 and 3.4 activities at the end of the commitm ent period. Considering that the entire Italian forest area is subject to the Forest management activity, Kyoto Protocol reporting has to account for carbon stocks changes (and the related non

- CO 2 

### emissions) on the
national forest area, and on deforested a reas, occurring in the first Commitments Period. The key elements of the accounting system in the National Registry for forest carbon sinks are:

National Land

- Use Inventory (IUTI) aimed at identifying and quantifying:

− forest land

areas;

− land in conversio n from forest land category since 31 December 1989;

− land in conversion to forest land category since 31 December 1989.

National Inventory of Carbon Stocks ( ISCI ) aimed at quantifying:

- carbon stocks and carbon stock changes in any land

- use category in the first Commitments

Period.

National Census of Forest Fires ( CIFI ) aimed at identifying and quantifying:

− forest land

areas affected by fires.

National Inventory of non

- CO 2 

### emissions from forest fires (IEIF) aimed at quantifying:

− non

- CO 2 

### emissions from

for est land areas affected by fires.

National Land

- Use Inventory (IUTI)

The National Land

- Use Inventory (IUTI) is aimed at identifying the land uses and land

- use changes over the national territory. IUTI will supply data concerning areas of forest land cate gory (art. 3.4 of KP) and of land in conversion to and from forest land categories (art. 3.3 of KP). IUTI will also supply estimates of the coverage percentage of the most important land

- cover elements (that are considered as

land

- use indicators).

Time:

I UTI will annually provide, from 01/01/2008 in experimental phase and from 01/01/2010 in operational phase, time

- series of the areas devoted to any land

- use category and any land

- use change subcategory

to and from forest land

use, in the KP reporting. For t he Kyoto Protocol first Commitment Period (I CP) accounting, the needed time series is related to the period 31/12/1989

- 1/1/2013; in particular the 31/12/1989 data are needed for identifying existing forest lands ( Forest Management , art. 3.4) and setting land reference scenario for Afforestation, Reforestation and Deforestation (art. 3.3);

Space: The sampling grid and the relative sample plots will homogenously cover the national territory and will supply data, at NUT2 level, of the investigated variable s (i.e. forest land category and each subcategory

in conversion to and from forest land ). The sampling grid will be dimensioned on the basis of the first

### 339

phase results of the National Forest Inventory (NFI). The analysis of sample plots will be carried out using remote sensed data and ground truth for present and future dates while for setting the 1990 only remote sensed data (satellite and aerial photographs) will be used since no ground truth is available for

that date.

Land

- use indicators:

Land

- use indicators are the different elements covering the investigated area (e.g. trees, buildings,
roads, rivers, grasses, etc.) and that indicated the potential land use. The land

- use indicators are used to

drive the land

- use classification of the area under ex amination and contribute to quantify the carbon
stock related to the same area. For instance, the presence of trees potentially higher than 5 meters can point out the potential forest land use, while the tree

- coverage percentage is an important driver for estimating carbon stocks.

Categories and subcategories:
Land use categories are defined according to IPCC Good Practice Guidance for LULUCF:

Settlements: prevalent urban use. Land

- use indicators: building, infrastructures insisting on an area of 0.5 ha, with a density at least equal to X%.

Cropland: prevalent agricultural use. Land

- use indicators: herbaceous cultures, woody crops insisting on an area of 0.5 ha, with a density at least equal to X%.

Forest land
prevalent forest use. Land

- use indicators: trees potentially higher more than 5 meter, crops insisting on an area of 0.5 ha, with a density at least equal to 10%.

Wetlands prevalent wetland use. Land

- use indicators: land covered or saturated by water for all or part of the year (e.g. peatland), i nsisting on an area of 0.5 ha, with a density at least equal to 10%.

Grassland : prevalent grazing use. Land

- use indicators: herbaceous cultures, shrubs crops insisting on an area of 0.5 ha, with a density at least equal to 10%.



## Land Unit = 0,5 ha

### 340

Other Lands : no prevale nt use. It corresponds to unproductive category.

Relation between activities under articles 3.3 and 3.4 of the Kyoto Protocol and the land

- use categories

Initial

Settlements Cropland Forest Land Wetlands Grassland Other lands

Settlements

------ D

Cropland

------ D

Forest Land AR AR

------ AR AR AR

Wetlands D

------

Grassland D

------Final



### Other Lands D

------



### Quality assurance: Data supplied by IUTI will be collected in the so

- called “ National Registry for the forest c arbon sinks ”
of Kyoto Protocol, and have to fulfil quality requirements as stated by the IPCC and UNFCCC guidelines.

Classification methodology The adopted classification methodology ensures that any unit of land could be classified univocally
(exclusion

of multiple classification of the same unit of land) under a category (exclusion of the null case), by means of

:

− a systematic sampling design to select classification points;

− a list of land

- use definitions as reported in the IPCC GPG land

- use classificati on;

− a list of land

- use indicators able to indicate the presence of a certain use on the land;

− a hierarchical order of prevalence of the land uses to assess the predominant land

- use. The

hierarchical order takes into account the socio

- economic value of use, following the FAO

FRA2000 forest definition.

Hierarchical

order Land

- use category Land

- cover indicators

1 Settlements building, infrastructures

2 Cropland herbaceous and woody cultures

3 Forest trees

4 Wetland land covered or saturated by water

5 Grassland grasses, shrubs

6 Other land none

### 341

To achieve land use classification, a 0.5 ha circular neighbourhood of the sample plot is investigated. In the first phase, this area

is processed, by the way of a contour mapping software: any sub

- area co vered by any land

- use indicator is contoured. In a second phase, a video

- operator codes each contoured sub

area, identifying the different land

- use indicators. Then, the processed area is archived and automatically classified under a land use and, at the s ame time, the surface of each sub

- area is

measured. The assignment of any unit of land to a land

- use category is done with a routine that test the prevalence of a land

- use category, following the hierarchical order and checking the exceeding of the

cover t hresholds set for the land indicators.
For instance, an area, where different land

- use indicators, e.g. farm, herbaceous cultures, coppices, are present, will be classified, testing:

− if the land

- use indicator “ farm ” reaches or exceeds settlements threshold , then the sample point

is classified as settlements land use and the coverage percentage of the land

- use indicators is
recorded;

− then if the land

- use indicator “ herbaceous culture ” reaches or exceeds cropland threshold, then the sample point is classifie d as cropland land use and the coverage percentage of the land

- use indicators is recorded;

− lastly, if the land

- use indicator “ coppices ” reaches or exceeds forest land threshold, then the sample point is classified as forest land land use and the coverage p ercentage of the land

- cover
indicators is recorded.

Once set the land

- use classification of the national land, the comparison of subsequent land

- use classifications produces land

- use change matrices which permits to figure out the activities under

which ev ery unit of land shall be accounted for, if any.

### 342

### 343 National Inventory of Carbon Stocks (ISCI)

The National Inventory of the Carbon Stocks is a sampling of carbon stocks related to the different

land

- use categories. The National Inventory of the Carb on Stocks includes:

- carbon stock changes in the land

- use category forest land, the dataset is derived by the IFN
data;

- carbon stock changes in the subcategories of the conversion to or from forest land to other predominant uses, the land in conversion to a nd from forest land

to other uses require data integration with studies and additional surveys in order to estimate, at regional level, the C

stock levels related to non

- forest land uses(i.e. settlements

, cropland

, grassland

, wetlands ).

Time:

ISCI will an

nually provide, from 01/01/2008 in experimental phase and from 01/01/2010 in operational phase, time series of carbon stock levels and carbon stock changes for the category forest land

and for the sub

- categories land in conversion to and from forest land to other uses. For the Kyoto Protocol first Commitment Period accounting, the needed time series is related to the period 31/12/2007

- 1/1/2013.

Space: Concerning the category forest land and any other category in conversion to and from forest land,

the N FIs will assure the spatial coverage, providing carbon stocks data, at NUT2 level.

Quality assurance: Data supplied by ISCI will be collected in the so

- called “ National Registry for the forest carbon

sinks ” of Kyoto Protocol, and have to fulfil quality re quirements as stated by the IPCC and UNFCCC guidelines

.

### 344 National Census of Forest Fires (CIFI)

The National Census of Forest Fires is a system aimed at detecting, locating and classifying the forest land

areas affected by fires; it will provide data on

- forest areas affected by fires;

- forest typology and stand features;

- proxy parameters in order to estimate the initial C stock and losses by fire (e.g. vegetation height, altitude, slope, exposure).

Time: CIFI will annually provide, from 01/01/2008, time series of forest areas affected by fires. For the Kyoto Protocol first Commitment Period accounting, the needed time series is related to the period

01/01/2008

- 31/12/2012 (because of the strong variability of the forest fires occurrence no interpolation of data is allowed).

Space: CIFI will cover all the national territory and will provide geographically referenced data on burned forest land remaining forest land areas (art. 3.4) and on land converted to forest land burned areas
(art. 3.3).

Key elements : The key elements are:

- ground surveys that have to detect fires and record boundaries of burned areas. Additional data will concern collection of attributes as damage evaluation (percentage of oxidised biomass), forest typology (following NFI classificati on);

- remote sensed data will integrate data from ground surveys, in order to cross

- check detected burned areas, at 0.5 ha spatial definition;

- digital terrain model;

- forest

- non forest Boolean mask.

Quality assurance: Data supplied by CIFI will be collected in the so

- called “ National Registry for the forest carbon

sinks ” of Kyoto Protocol, and have to fulfil quality requirements as stated by the IPCC and UNFCCC guidelines.

### 345 National Inventory of non

- CO 2 

### emissions from forest fires (IEIF)

The Forest fires GH G emissions National Inventory is aimed at estimating non

- CO 2 

### emissions from
forest fires (CO 2 

### emissions aren’t taken into account, being already computed by National Inventory Carbon Stocks as decreases in carbon stocks). It will provide:

- emission figures of the land

- use category forest land ;

- emission figures of the land

- use categories in conversion to or from forest land to other predominant uses.

Time: The Forest fires GHG emissions National Inventory will annually provide, from 01/01/2008 in experimen

tal phase and from 01/01/2010 in operational phase, time series of non

- CO 2 

### emissions

from forest fires. For the Kyoto Protocol first Commitment Period (CP) accounting, the needed time series is related to the period 01/01/2008

- 31/12/2012.

Space: IEIF wi

ll supply estimates of emissions released by fires detected by National Census of

Forest Fires.

Key elements: For any fire, once identified the prevalent forest typology and the damage of the stand (i.e. percentage of burned biomass) affected by fire, thr ough the National Forest Service surveys, related carbon stocks are estimated by National Inventory Carbon Stocks. Emissions are calculated applying the damage coefficients and the emissions factors referenced or elaborated by research projects to the esti

mated carbon stocks.

Quality assurance: Data supplied by IEIF will be collected in the so

- called “ National Registry for the forest carbon

sinks ” of Kyoto Protocol, and have to fulfil quality requirements as stated by the IPCC and UNFCCC guidelines.

### 346



## ANNE X 1 1 : THE NATIONAL REGISTRY

A1 1 .1 Introduction

In this annex it is reported a description of the Italian national Registry, in accordance with the guidelines set down in UNFCCC’s Decision 22/CP.8 (Additional sections to be incorporated in the guideline s for the preparation of the information required under Article 7, and in the guidelines for the review of information under Article 8, of the Kyoto Protocol).

All data referring to units holdings and transactions during the year 2008 are reported in the SEF submission; figures are included in tables A10.1, A10.2 and A10.3.

Italy carried out all required steps of the initialization process with the UNFCCC: in particular, Italy successfully performed and passed:

• SSL connectivity testing (Oct. 26 th 

### 2007);

• V PN connectivity testing (Oct. 15 th 

### 2007);

• Interoperability test according to Annex H of the UN Data Exchange Standards (DES) (Nov.

9 th 

### 2007), and submitted all required information through a complete Readiness questionnaire.

This implies that the Italian registry fulfilled all of its obligations regarding conformity with the UN DES. These obligations include having adequate transaction procedures, adequate security measures to prevent and resolve unauthorized manipulations and adequate measures for data st orage and registry recovery. The registry was therefore deemed fully compliant with the registry requirements

defined in decisions 13/CMP.1 and 5/CMP.1.

As a result, Italy could participate to the “ETS go

- live” event that took place in October 2008.

After successful completion of the go

- live process on 16 th 

### October 2008, the Italian registry commenced live operations with the ITL and it’s been operational ever since.

At present, Italy is also operating its registry under Article 19 of Directive 2003/87/CE establishing the EU Emission Trading Scheme and according to Regulation No. 2216/2004 of the European Commission, which require national registries to be compliant with the UN DES document.

The Italian registry is based on the GRETA registry software dev eloped by the UK Department for Environment, Food and Rural Affairs (DEFRA) and used by many other Member States. Currently, the development of this software adheres to the standards specified in Draft #7 of the UN DES document. Italy had the registry syst ems tested successfully with the EU Commission on February the 6th 2006; the connection between the registry’s production environment and the CITL was established on March the 13th 2006 and the Registry has since gone live, starting on 28 March

2006.

A1 1. 2 Registry administrator

The Italian Government modified the previous Legislative Decree 216/2006 which enforced the Directive 87/2003/ CE, by the new Legislative Decree 51 of March 7th 2008. Due to this new Decree, Italy’s Agency for the Protection of t he Environment and for Technical Services (APAT) is responsible for developing, operating and maintaining the national registry under Directive 2003/87/CE. In August 2008 APAT was merged into ISPRA ( Institute for Environmental Protection and Research) and therefore ISPRA , as Registry Administrator, becomes responsible for

### 347

the management and functioning of the Registry, including Kyoto protocol obligations. The reference person is Mr Mario Contaldi.

The Decree 51/2008 also establishes that the economic resou rces for the technical and administrative support of the Registry will be supplied to ISPRA by operators paying a fee for the use of the Registry. The amount of such a fee will be regulated by a future Decree.

Besides the one person designated as Registr y administrator, ISPRA set up an operational unit (“Settore del Registro nazionale dei crediti di emissione”) where five persons are working in order to manage, develop and maintain the Italian National Registry and, additionally, relays on the

structure o f the Agency for information, secretary and administrative services:

• one IT expert who is taking care of hardware and software on site, with the support of an external IT supplier giving remote consultancy;

• two persons are responsible for the registry app lication management, the resolution of problems with operators, the manual intervention in the database and they interface with the “Competent Authority”;

• one person is dedicated to the helpdesk for operators;

• one person is dedicated to archiving the docum entation.

A1 1 .3 Cooperation with other Parties

Italy’s National Registry is currently linked to the other EU member states’ National Registries and to the European Commission CITL (Community Independent Transaction Log) by way of the
UNFCCC ITL (Interna tional Transaction Log), in a consolidated system forming the European Emissions trading scheme (EU ETS).

A1 1 .4 Database structure and capacity of the national registry

The GRETA registry system is implemented using a Microsoft SQL Server 2000 Enterprise Edition relational database management system with a dedicated data model for supporting registry operations. The SQL license adopted has no access limitations of simultaneous transactions.

The actual production environment consists in: 1 Firewall server + 1 webserver + 2 DB server in cluster configuration with two controllers fibre channel towards storage unit; the data directory is on the data storage device + 1 Tape Autoloader.

The actual test environment is protected by 1 Firewall server. The test en vironment webserver has the same hardware and software configuration of the production web server. In this case the DB

server is on the same unit. It will be reinstalled on another server.

The disaster recovery environment is physically separated from the production environment (in a different building in a different part of the city of Rome) and has been implemented in the following

way:

• a firewall Cisco ASA is installed and configured and then connected through VPN with the firewall Cisco ASA of the pro duction environment;

• 2 servers S.O. Windows 2003 are installed and configured;

• Microsoft SQL Server 2000 Enterprise Edition is installed, synchronized with the production SQL through VPN;

• Microsoft Internet Information Server 6 and the GRETA software are i nstalled.

This synchronization system between the production environment and the disaster recovery

environment is carried out every 15 minutes. In case the primary system falls, the synchronization

### 348

platform will be served by a different connection to the internet with the immediate recovery of all functionalities; the time estimated is just the time needed to update the public DNS caches that will have to “memorize” the new path towards a different IP address. The ITL is requested to send the

last 15 minut es transaction logs files in order to upgrade the disaster recovery DB and start it again. In the meantime, the dedicated personnel will try to resolve as soon as possible the problem on the production platform. Once a week, the correct functioning of the disaster recovery platform is checked.

A1 1 .5 Conformity with data exchange standards (DES)

The GRETA registry system has been developed for the EU Emissions Trading Scheme. This scheme requires its Member States’ registries to be compliant with the UN D ata Exchange Standards specified for the Kyoto Protocol. Currently, the development adheres to the standards specified in Draft #7 of the UN DES document.
In addition, 24 Hour Clean

- up, Transaction Status enquiry, Time Synchronisation, Data Logging require ments (including Transaction Log, Reconciliation Log, Internal Audit Log and Message Archive) and the different identifier formats as specified in the UN DES document have been implemented. From February the 7th 2008, however, on both production and test s ites a new NTP software has been installed. This software is provided by “http://www.meinberg.de/english/sw/ntp.htm” and was obtained by compiling version 4.2.4p4 sources of the software supplied by ntp.org.

Formats for account numbers, serial numbers fo r ERUs, CERs, AAUs, and RMUs, including project identifiers and transaction numbers are as specified in the UN DES #7 Annex F

–Definition

of Identifiers. The display format is controlled via the registries web configuration file.

Electronical information when transferring ERUs, CERs, AAUs, and/or RMUs to other registries will be transmitted to other registries in the format of the messages specified in the UN DES #7 via

the ITL. Acknowledgement information when acquiring ERUs, CERs, AAUs, and/or RMUs from other national registries or the CDM registry will be transmitted to other registries in the format of the messages specified in the UN DES #7 via the ITL.

Electronical Information when issuing, transferring, acquiring, canceling and retiring ERUs, CERs,

A AUs, and/or RMUs. will be transmitted from the national registry to the ITL in the format of the messages specified in the UN DES #7.

A1 1 .6 Procedures for minimizing and handling of discrepancies

Communications between the National Registry and the ITL is via web

- services using XML

messages

–as specified in the UN DES document. These web

- services, XML message format and the processing sequence are as per that specified in the UN DES document. In the EU ETS, to prevent discrepancies between the Registry an d the Transaction Log, internal checks (as specified in the UN DES document) are implemented as far as possible. The same approach has been adopted for the development of the GRETA software for the remaining Kyoto

functionalities. Whenever a possible discr epancy is detected by the internal checks no transaction will be started. Moreover, unit blocks involved in a pending transaction are locked for use in any other transaction

and there will be an automatic termination of the transaction that has caused the discrepancy. In the event of a failure to terminate the transaction, an inconsistency with the ITL or STL will be detected during the subsequent reconciliation process. The ITL or STL will then block any transaction involving the related blocks. The status of the blocks will afterwards be corrected

### 349

manually by the registry administrator with the help of a manual intervention function. This intervention will be logged automatically in the registry. If no inconsistencies are detected during

the next reconcil iation process with the ITL or STL, the related unit blocks will be unblocked so

that further transactions with these blocks will be possible.

A1 1 .7 Prevention of unauthorized manipulations and operator error

The Agency emphasizes physical security of se rver premises in addition to normal logical access control methods. All servers and backup media are located in secure premises with electronic access control, allowed only to the system administrators. Personnel have duty of identification when entering t he building and a security channel allows monitoring inside the building. When moving servers or backup media between controlled premises, they are never left unattended. Computers are accessible through username and password and they are automatically loc ked after 15 minutes of idle time. Employees are required to lock the computers manually whenever leaving

the desk. Servers are protected by firewalls (Cisco ASA appliances).

To log

- in, every user of the registry software is obliged to use username and pa ssword. Passwords are of 8 to 15 digits including minimum 1 numbers and minimum 1 alphabet and to change their password every 60 days. The registry administrator disables unused user ids and passwords on a regular basis. Session security is ensured by usin g encryption both in management traffic and production network
traffic (SSL). All servers are protected with Anti

- Virus product (eTrust Inoculate) updated daily. Regular virus
scans are run on all nodes, workstations and servers within their network. Signi ficant attention is placed on verifying the identity of the operator’s or organization’s legal representative who is signing the nomination of the account primary and secondary authorized representatives.

For the operators’ accounts, such verification re quires a “visura camerale”, a document produced by the Italian Chamber of Commerce identifying the legal representatives of a specific commercial company. Non Italian Companies are requested to provide an equivalent document, identifying the Company’s repr

esentatives and their roles and responsibilities. The same document, “visura camerale” or an equivalent (e.g. statute), is requested for organizations applying for an account. For individual accounts, only a signed copy of an identity document is required (identity card or passport for non Italian persons). All persons involved those who delegate and the authorized representatives, need to send a signed copy of an identity document (identity card or passport for non Italians).

A1 1 .8 User interface of the n ational registry

The GRETA software makes available on the registry site publicly accessible information. These reports are described below in the following.

1. Open Internet Explorer (or similar) and browse to the following URL:

http://www.greta.sinanet.apat.it

2. Click on the link to the national registry

3. Select the public reports link at the bottom of the page. The user can choose from:

### 350

a. User details

–unchanged, updated, created

b. Account details

–unc hanged, updated, created

c. Operator holding account

–unchanged, updated, created

A1 1 .9 Integrity of data storage and recovery

In addition to disaster recovery in real time (see paragraph A10.4), a backup policy is implemented for the production environme nt, according to the following schedule:

• full backup of the database is taken everyday in the storage unit;

• differential backups of new logs are taken every hour in the storage unit;

• every week all daily backups are recorded on a tape that is retained for 2 weeks in a separate

location. We are using the internal backup scheduling system of SQL Server 2000 Enterprise Edition. Full database backup are taken everyday. Differential backups of new logs are taken every hour. Both storage (HP StorageWorks MSA20) a nd tapes (HP StorageWorks 1/8 Tape Autoloader Ultrium 230) are kept in secure location with controlled access. Currently APAT uses three backup tapes. After being in use for one week, the tape is stored for two

weeks. After two weeks it is erased and used again. This means that daily backups are available in 14 generations (two weeks). Backup software’s log is checked every weekday. Abnormalities are checked and necessary

corrections made. Reliability of the whole system is guaranteed by the following stabi lity features:

• power supply from the public power supply network through two separate feeding points;

• uninterruptible power supply on battery basis;

• guarantee of the supply through diesel emergency power aggregate in the event of prolonged

failure of the public power supply network;

• all essential hardware components of the server are implemented with redundancy (power supply, multiprocessor, hard

- disks RAID);

• the database servers are operated as a cluster (switchover).

A1 1 .10 Test results

The performa nce and security measures of the national registry have been successfully tested through the implementation of secure connection (digital certificates and VPN tunnel). As reported in paragraph A10.1, Italy carried out all required steps of the initializati on process with the UNFCCC. In particular, Italy successfully performed and passed SSL connectivity testing, VPN connectivity testing, interoperability test according to Annex H of the UN DES and submitted all required information through a complete Readin ess questionnaire. Currently, the GRETA registry system for the EU Emissions Trading Scheme uses the security mechanism as specified within the EU Regulation Annex XV; that is, it uses basic authentication

and SSL.

### 351

Table A1 1 .1 Annual external transactio ns of Kyoto Protocol units

Submission year 2009
Reported year 2008
Commitment period 1



### Table 2 (b). Annual external transactions

Additions Subtractions

Unit type Unit t ype

AAUs ERUs RMUs CERs tCERs lCERs AAUs ERUs RMUs CERs tCERs lCERs

Transfers and acquisitions

AT NO NO NO NO NO NO 212000 NO NO NO NO NO

BE 195000 NO NO NO NO NO NO NO NO NO NO NO

CDM NO NO NO 13379879 NO NO NO NO NO NO NO NO

CH NO NO NO 1230888 NO NO NO NO NO 50598 NO NO

DE 61101 NO NO 90133 NO NO 200001 NO NO NO NO NO

DK 168000 NO NO 100001 NO NO 100000 NO NO 900000 NO NO

ES 19500 NO NO NO NO NO 4500 NO NO 3000 NO NO

EU 579204 NO NO NO NO NO NO NO NO NO NO NO

FI 3400 NO NO NO NO NO 34000 NO NO NO NO NO

FR 5466500 NO NO 388159 NO NO 1331939 NO NO 2272401 NO NO

GB 12239997 NO NO 3957262 NO NO 1185263 NO NO 6689921 NO NO

NL 1558255 NO NO 130000 NO NO 735000 NO NO 58000 NO NO

PT 2000 NO NO NO NO NO 2000 NO NO NO NO NO

Sub

- total 20292957 NO NO 19276322 NO NO 3804703 NO NO 9973920 NO NO



### Additional information

Independently verified ERUs NO



### Table 2 (c). Total annual transactions

Total (Sum of tables 2a and 2b) 20292957 NO NO 19276322 NO NO 3804703 NO NO 9973920 NO NO

### 352

Table A 11

. 2 Total quantities of Kyoto Protocol units

Party Italy
Submission year 20 09
Reported year 2008
Commitment period 1



### Table 4. Total quantities of Kyoto Protocol units by account type at end of reported year

Unit type

Account type AAUs ERUs RMUs CERs tCERs lCERs

Party holding accounts 22320354 44 NO NO NO NO NO
Entity holding accounts 200730708 NO NO 9302402 NO NO

Article 3.3/3.4 net source cancellation accounts NO NO NO NO

Non

- compliance cancellation accounts NO NO NO NO

Other cancellation accounts NO NO NO NO NO NO

Retirement acco unt NO NO NO NO NO NO
tCER replacement account for expiry NO NO NO NO NO

lCER replacement account for expiry NO NO NO NO

lCER replacement account for reversal of storage NO NO NO NO NO

lCER replacement account for non

- submission of certificatio n report NO NO NO NO NO

Total 2432766152 NO NO 9302402 NO NO

### 353

Table A1 1 .3 Summary information on Kyoto Protocol units
Party Italy Submission year 2009 Reported year 2008

Commitment

pe ri od 1

Table 5 (a). Summary information on additions and subtractions

Additions Subtractions

Unit type Unit type

Starting values AAUs ERUs RMUs CERs tCERs lCERs AAUs ERUs RMUs CERs tCERs lCERs Issuance pursuant to Art icle 3.7 and

3.8 2416277898

Non

- compliance cancellation NO NO NO NO Carry

- over NO NO NO

Sub

- total 2416277898 NO NO NO NO NO NO

Annual transactions
Year 0 (2007) NO NO NO NO NO NO NO NO NO NO NO NO

Year 1 (2008) 20292957 NO NO 19276322 NO NO 3804703 NO NO 9973920 NO NO
Year 2 (2009) NO NO NO NO NO NO NO NO NO NO NO NO
Year 3 (2010) NO NO NO NO NO NO NO NO NO NO NO NO
Year 4 (2011) NO NO NO NO NO NO NO NO NO NO NO NO
Year 5 (2012) NO NO NO NO NO NO NO NO NO NO NO NO
Year 6 (2013) NO NO NO NO NO NO NO NO NO NO NO NO
Year 7 (2014) NO NO NO NO NO NO NO NO NO NO NO NO
Year 8 (2015) NO NO NO NO NO NO NO NO NO NO NO NO

Sub

- total 20292957 NO NO 19276322 NO NO 3804703 NO NO 9973920 NO NO

Total 2436570855 NO NO 19276322 NO NO 3804703 NO NO 9973920 NO NO

Table 5 (b). Summary information on replacement Table 5 (c). Summary informa tion on retirement

Retirement Requirement

for replacement Replacement Unit type Unit type Unit type Year AAUs ERUs RMUs CERs tCERs lCERs

tCERs lCERs AAUs ERUs RMUs CERs tCERs lCERs Year 1 (2008) NO NO NO NO NO NO

Previ ous CPs NO NO NO NO NO NO Year 2 (2009) NO NO NO NO NO NO
Year 1 (2008) NO NO NO NO NO NO NO Year 3 (2010) NO NO NO NO NO NO

Year 2 (2009) NO NO NO NO NO NO NO Year 4 (2011) NO NO NO NO NO NO
Year 3 (2010) NO NO NO NO NO NO NO Year 5 (2012 ) NO NO NO NO NO NO
Year 4 (2011) NO NO NO NO NO NO NO Year 6 (2013) NO NO NO NO NO NO
Year 5 (2012) NO NO NO NO NO NO NO NO Year 7 (2014) NO NO NO NO NO NO
Year 6 (2013) NO NO NO NO NO NO NO NO Year 8 (2015) NO NO NO NO NO NO Year 7 (2014) NO NO NO NO NO NO NO NO Total NO NO NO NO NO NO

Year 8 (2015) NO NO NO NO NO NO NO NO

Total NO NO NO NO NO NO NO NO