. 

Italian Greenhouse Gas Inventory

1990-2007 

National Inventory Report 2009 

Daniela Romano, Chiara Arcarese, Antonella Bernetti, Antonio Caputo, Rocío D. Cóndor, Mario 

Contaldi, Riccardo De Lauretis, Eleonora Di Cristofaro, Sandro 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 Environmental 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 

Services), 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 to 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 (industrial 

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 change and forestry)

Contact: Riccardo De Lauretis

Telephone +39 0650072543

Fax +39 0650072657

E-mail delauretis@apat.it

ISPRA- Institute for Environmental Protection and Research 

Environment Department 

Monitoring and Prevention of Atmospheric Impacts

Air Emission Inventory Unit

Via V. Brancati, 48 

00144 Rome 

ITALY

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 

Nazionale, 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 internazionale 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 limitazione delle emissioni.

In particolare, ogni 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 uno specifico documento, 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 sottoposte. 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 realtà, 

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 esclusa 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 progetti 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 serra dal 

1990 al 2007. 

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 cambiamenti 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 rapporto, le emissioni totali dei gas serra (espressi in termini di CO2 equivalente) sono 

aumentate, dal 1990 al 2007, del 7.1% a fronte di un impegno nazionale di riduzione pari al 6,5% 

entro il periodo 2008-2012. 

Contents

EXECUTIVE 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 

SOMMARIO (ITALIAN) 18

1. INTRODUCTION 19 

1.1 Background information on greenhouse gas inventories and climate change 19 

1.2 Description of the institutional arrangement for inventory preparation 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 evaluation, including data on the overall uncertainty for the

inventory totals 35 

1.8 General assessment of the completeness 36 

2. TRENDS IN GREENHOUSE GAS EMISSIONS 39 

2.1 Description and interpretation of emission trends for aggregate greenhouse

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 SO2 51 

3. ENERGY [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 construction 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 consistency 

 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-specific 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 energy balance 

3.10.2 National emission factors

3.11 Fugitive emissions from solid fuels, oil and natural gas 81 

4.INDUSTRIAL PROCESSES [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 Methodological 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 description 

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 category description

4.6 Production of halocarbons and SF6 (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 SF6 (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. SOLVENT 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-specific recalculations 110 

6. AGRICULTURE [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 planned improvements

7. LAND USE, LAND USE CHANGE AND FORESTRY [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-specific 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 Grassland (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 improvements 

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 Direct N2O emissions from N fertilization(5(I)) 183 

7.9 N2O emissions from drainage of soils(5(II)) 183 

7.10 N2O emissions from disturbance associated with land-use conversion to Cropland

(5(III)) 183 
7.10.1 Source category description

7.10.2 Methodological 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 improvements

7.12.4 Source-specific recalculations

8. WASTE [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-series 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 consistency 

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 Source-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-specific QA/QC and verification

8.5.5 Source-specific recalculations

8.5.6 Source-specific planned improvements

9. RECALCULATIONS AND IMPROVEMENTS 207 

9.1 Explanations and justifications for recalculations 207 

9.2 Implications for emission levels 207 

9.3 Implications 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., institutional arrangements, inventory

preparation) 

10. REFERENCES 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 

ANNEX 1: KEY CATEGORIES AND UNCERTAINTY 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 

ANNEX 2: DETAILED TABLES OF ENERGY CONSUMPTION FOR POWER GENERATION 256 

ANNEX 3: ESTIMATION OF CARBON CONTENT OF COALS USED IN INDUSTRY 259 

ANNEX 4: CO2 REFERENCE APPROACH 264 

A4.1 Introduction 264 

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

ANNEX 5: NATIONAL ENERGY BALANCE, YEAR 2007 267 

ANNEX 6: NATIONAL EMISSION FACTORS 292 

ANNEX 7: AGRICULTURE SECTOR 296 

ANNEX 8: CRF TREND TABLES FOR GREENHOUSE GASES 299 

ANNEX 9: METHODOLOGIES, DATA SOURCES AND EMISSION FACTORS 326 

ANNEX 10: THE NATIONAL REGISTRY FOR FOREST CARBON SINKS 337 

ANNEX 11: THE NATIONAL REGISTRY 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 period, 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, which was adopted by the Interministerial Committee for 

Economic Planning (CIPE) on 19th 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, Italy 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 commitments, 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 submission 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, an 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 Convention, 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. Adjustments 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 the revision of the entire time series 1990-2006. 

The assigned amount for Italy, pursuant to Article 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 (CPR), 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 CO2 eq. for the assigned 

amount and 2,174,650,108 tonnes of CO2 eq. for the CPR. The CRP is calculated on the basis of 

the assigned amount so it has not changed from the previous submission.
12 

Emission estimates comprise the six direct greenhouse gases 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 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/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.

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

Total greenhouse gas emissions, in CO2 equivalent, excluding emissions and removals of CO2

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

516 to 553 millions of CO2 equivalent tons), while the 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, CO2, which accounted for 86.0% of total emissions in CO2

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.

CH4 and N2O emissions were equal to 6.9% and 5.8%, respectively, of the total CO2 equivalent 

greenhouse gas emissions in 2007. Both gases showed a decrease from 1990 to 2007, equal to 

8.4% and 14.9% for CH4 and N2O, respectively. 

Other greenhouse gases, HFCs, PFCs and SF6, 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 CO2

equivalent terms, by substance and category.
13 

1990 

(base year) 1995 2000 2001 2002 2003 2004 2005 2006 2007 

GHG Emissions

CO2 equivalent (Gg)

CO2 emissions including net CO2 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

CO2 emissions excluding net CO2 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

CH4 emissions including CH4 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

CH4 emissions excluding CH4 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

N2O emissions including N2O 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

N2O emissions excluding N2O from 

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

SF6 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 LULUCF) 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) GREENHOUSE GAS SOURCE AND 1995 2000 2001 2002 2003 2004 2005 2006 2007 

SINK CATEGORIES

CO2 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 Other 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 and 

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 CO2 equivalent (Gg CO2 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 emissions 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 CO2, whose levels increased by 10.2% from 

1990 to 2007 and accounts for 97.4% of the total in the energy sector, and N2O which showed an 

increase of 18.0% but its share out of the sectoral total is only 1.2%; CH4, 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%. Specifically, in terms of total CO2 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, CO2 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. CH4 decreased by 40.3%, but it accounts 

only for 0.2%, while N2O, whose levels share 5.2% of total industrial emissions, decreased by 

71.7% due to the fully operational 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 CO2 and N2O 

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 CO2 emissions, which account for 

63.8% of the sector. As regards CO2, emission levels from paint application sector, which

accounts for 51.4% of total CO2 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, CO2 emissions from metal degreasing and dry cleaning activities, decreased by 

61.3% but they account for only 5.0% of the total. 

The level of N2O emissions, on the other hand, did not show a significant variation from 1990 to 

2007 (-3.0%).

 

For agriculture, emissions refer to CH4 and N2O 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 CH4 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-water handling, which increased of about 15.6% and accounts for 24.1% of the 

total. The most important greenhouse gas in this sector is CH4 which accounts for 87.0% of the 

sectoral emissions and shows an increase of 3.9% from 1990 to 2007. N2O levels increased by 

9.5%, whereas CO2 decreased by 49.7%; these gases account for 11.6% and 1.5%, respectively.

Table ES.2 provides an overview of the CO2 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 

CO2: 1. Energy Industries

 

134,092 

 

137,973 

 

146,913 

 

150,303 

 

157,183 

 

158,253 

 

157,142 

 

159,308 

 

159,179 

 

157,850 

CO2: 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 

CO2: 3. Transport 

 

101,269 

 

111,446 

 

120,109 

 

122,181 

 

124,143 

 

125,106 

 

127,091 

 

125,830 

 

127,151 

 

127,212 

CO2: 4. Other Sectors 

 

76,677 

 

76,090 

 

78,596 

 

81,373 

 

78,782 

 

85,362 

 

87,083 

 

91,844 

 

85,967 

 

79,746 

CO2: 5. Other

 

1,046 

 

1,440 

 

806 

 

354 

 

314 

 

660 

 

1,091 

 

1,198 

 

982 

 

896 

CH4

 

1,548 

 

1,701 

 

1,494 

 

1,456 

 

1,345 

 

1,343 

 

1,359 

 

1,297 

 

1,318 

 

1,412 

N2O

 

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 

CO2

 

3,341 

 

3,174 

 

2,585 

 

2,440 

 

2,261 

 

2,834 

 

2,152 

 

2,112 

 

2,189 

 

2,176 

CH4

 

7,420 

 

6,882 

 

6,424 

 

6,069 

 

6,042 

 

5,896 

 

5,713 

 

5,723 

 

5,193 

 

5,071 

N2O

 

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 

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 

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 

SF6

 

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 

CO2

 

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 

N2O

 

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 

CH4: Enteric fermentation

 

12,179 

 

12,267 

 

12,165 

 

11,340 

 

11,030 

 

11,056 

 

10,836 

 

10,844 

 

10,629 

 

11,027 

CH4: Manure management

 

3,462 

 

3,286 

 

3,278 

 

3,343 

 

3,263 

 

3,252 

 

3,156 

 

3,151 

 

3,031 

 

3,057 

CH4: Rice Cultivation

 

1,562 

 

1,657 

 

1,382 

 

1,382 

 

1,420 

 

1,463 

 

1,534 

 

1,472 

 

1,477 

 

1,523 

CH4: Field Burning of Agricultural 

Residues

 

13 

 

13 

 

12 

 

11 

 

13 

 

11 

 

14 

 

13 

 

13 

 

13 

N2O: Manure management

 

3,921 

 

3,782 

 

3,862 

 

4,000 

 

3,847 

 

3,816 

 

3,731 

 

3,725 

 

3,618 

 

3,797 

N2O: Agriculture soils

 

19,435 

 

19,340 

 

19,237 

 

18,875 

 

18,673 

 

18,500 

 

18,643 

 

18,032 

 

17,856 

 

17,791 

N2O: 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 

CO2 -67,651 -85,816 -79,326 -92,672 -95,683 -126,870 -91,878 -95,374 -90,136 -71,127 

CH4

 

143 

 

27 

 

87 

 

55 

 

31 

 

65 

 

35 

 

34 

 

31 

 

197 

N2O

 

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 

CO2

 

537 

 

483 

 

202 

 

222 

 

245 

 

216 

 

199 

 

245 

 

267 

 

270 

CH4

 

15,447 

 

18,239 

 

19,379 

 

19,263 

 

18,670 

 

17,998 

 

17,165 

 

17,080 

 

16,319 

 

16,051 

N2O

 

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 CO2 equivalent (Gg CO2 eq)
17

ES.4. Other information 

In Table ES.3 NOX, CO, NMVOC and SO2 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 SO2 (-81.1%), while CO and NOX emissions reduced by about 51.9% and 42.8% 

respectively, NMVOC levels showed a decrease by 38.4%. 

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

and SO2 ktons

NOX 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 

SO2 1,795 1,320 749 697 616 518 480 401 379 339 

Table ES.3. Total emissions of indirect greenhouse gases and SO2 (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 Cambiamenti 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 sistema 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 sottoposte 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 review, 

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 disponibile 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 CO2 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 periodo 2008-2012. 

In particolare, le emissioni complessive di CO2 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 SF6, hanno un peso complessivo 

sul 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 SF6 mostrano un minore

incremento. Sebbene al momento tali variazioni non risultino determinanti 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 and 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 recently, 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 warming 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 concentrations”. 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 Convention on Climate Change (UNFCC) which was approved in New York on 9th

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 inventories 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 Protocol, 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 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 

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 

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

19th December 2002 (deliberation n. 123 of 19/12/2002).

The Kyoto Protocol finally entered into force on 16th February 2005.

As a Party to the Convention and the Kyoto 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 and 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 emission 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 2007 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 Gas Monitoring Mechanism. 

The 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. The 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 

determined figures are reported in the document FCCC/IRR/2007/ITA and amount to

2,416,277,898 tonnes CO2 eq., for the assigned amount, and 2,174,650,108 tonnes of CO2 eq., for 

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

previous submissions. 

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 gases (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/items/

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 article 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 information 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 States 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 1st April 2008, 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 instrument 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 account 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 133/2008 and performs the functions of three former institutions: 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 which 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 Italian 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 help 

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, coordinates participation in reviews, publishes and archives the inventory results. 

Specifically, ISPRA is responsible for all aspects of national inventory preparation, 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 Inventory 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 ensures 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 Institute 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 6th 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 and 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 coordinating 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 2008-2010, was issued on 6

th August 2008. 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 of 

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 statistical 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 Statistical 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 generally 

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 Decree on 1st 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 

submission 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 Agriculture, 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 

activities 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 

height 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

FCCC/SBSTA/2006/L.6 and related COP/MOP2 decision1, 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 period.

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 responsible 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 established 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 51/2008 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.

Italy carried out all required steps of the initialization process with the UNFCCC: in particular, Italy 

successfully performed and passed:

• SSL connectivity testing (Oct. 26th 2007);

• VPN connectivity testing (Oct. 15th 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 storage 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 16th October 2008, the Italian 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. In 2008, 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 

Commission, 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 States. 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 production environment and the CITL was

established on March 13th 2006 and the Registry has since gone live, starting on March 28th 2006. 

Detailed information on the national registry is reported in Annex 11. 

1.3 Brief description of the process of inventory preparation

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 improvement 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 

estimates 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 with 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 experts, 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 transparency, 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

scientific 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 documentation 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 

inventory 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, 2007); national emission factors are used as well as default emission 

factors from international guidebooks, when national data are not available. The development 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 

inventory 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 SF6

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 SF6 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.

CO2 CH4 N2O

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 are 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 other 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 and 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 estimates 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, industries 

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 and 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 figures 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 Directive 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 provided 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 associations. 

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 by 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 data 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 data 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 Italian 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 defined 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, add 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 have 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, 19 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, 25 

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)

CO2 stationary combustion liquid fuels L

CO2 stationary combustion solid fuels L

CO2 stationary combustion gaseous fuels L

N2O stationary combustion L

CO2 Mobile combustion: Road Vehicles L

CO2 Fugitive emissions from Oil and Gas Operations L

CH4 Fugitive emissions from Oil and Gas Operations L

CO2 Cement production L

N2O Adipic Acid L

CH4 Enteric Fermentation in Domestic Livestock L

N2O Manure Management L

CH4 Manure Management L

Direct N2O Agricultural Soils L

Indirect N2O from Nitrogen used in agriculture L

CH4 from Solid waste Disposal Sites L

CO2 Iron and steel production L1 

CO2 Mobile combustion: Waterborne Navigation L1

CO2 Limestone and dolomite use L1

N2O Nitric Acid L1

N2O Mobile combustion: Road Vehicles L2

CO2 Emissions from solvent use L2

N2O Emissions from solvent use L2

N2O from animal production L2

CH4 Emissions from Wastewater Handling L2

N2O Emissions from Wastewater Handling L2

CH4 Mobile combustion: Road Vehicles L2

Table 1.3 Key categories (excluding LULUCF) by the IPCC Tier 1 and Tier 2 approaches (L=Level). Base year

Key categories (including the LULUCF sector)

CO2 stationary combustion liquid fuels L

CO2 stationary combustion solid fuels L

CO2 stationary combustion gaseous fuels L

N2O stationary combustion L

CO2 Mobile combustion: Road Vehicles L

CH4 Fugitive emissions from Oil and Gas Operations L

CO2 Cement production L

CH4 Enteric Fermentation in Domestic Livestock L

CH4 Manure Management L

N2O Manure Management L

Direct N2O Agricultural Soils L

Indirect N2O from Nitrogen used in agriculture L

CH4 from Solid waste Disposal Sites L

CO2 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

CO2 Cropland remaining Cropland L

CO2 Land converted to Forest Land L

CO2 Fugitive emissions from Oil and Gas Operations L

CO2 Mobile combustion: Waterborne Navigation L1

CO2 Iron and steel production L1

N2O Adipic Acid L1

CO2 Limestone and Dolomite Use L1

N2O from animal production L2

CH4 Emissions from Wastewater Handling L2

CO2 Emissions from solvent use L2

CO2 Land converted 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 2007 inventory, without considering the LULUCF sector, 29 

key categories were totally individuated, both at level and trend. Results are reported in Table 1.5. 

Key categories (excluding the LULUCF sector)

CO2 stationary combustion liquid fuels L, T

CO2 stationary combustion solid fuels L, T

CO2 stationary combustion gaseous fuels L, T

CO2 Mobile combustion: Road Vehicles L, T

N2O Mobile combustion: Road Vehicles L2 

CH4 Fugitive emissions from Oil and Gas Operations L, T

HFC, PFC substitutes for ODS L, T

CH4 Enteric Fermentation in Domestic Livestock L, T

Direct N2O Agricultural Soils L, T

Indirect N2O from Nitrogen used in agriculture L, T2 

CO2 Cement production L, T2

N2O Manure Management L, T2

CH4 Manure Management L, T2

CH4 from Solid waste Disposal Sites L, T2

CO2 Fugitive emissions from Oil and Gas Operations L2, T

N2O stationary combustion L

N2O Adipic Acid T

CO2 stationary combustion other fuels L1, T1 

CO2 Emissions from solvent use L2, T2

N2O from animal production L2, T2

CH4 Emissions from Wastewater Handling L2, T2

N2O Emissions from Wastewater Handling L2, T2

CO2 Mobile combustion: Waterborne Navigation L1, T2

CH4 stationary combustion L2

CO2 Limestone and Dolomite Use L1 

CO2 Iron and steel production T1 

CO2 Ammonia production T1 

PFC Aluminium production T1 

N2O 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 2007

If considering emissions and removals from the LULUCF sector, 28 key categories were

individuated as reported in Table 1.6. 

There are no additional categories as compared to the previous analysis expect for those referring to 

the LULUCF sector. 

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
31

Key categories (including the LULUCF sector)

CO2 stationary combustion liquid fuels L, T

CO2 stationary combustion solid fuels L, T

CO2 stationary combustion gaseous fuels L, T

CO2 Mobile combustion: Road Vehicles L, T

CH4 Fugitive emissions from Oil and Gas Operations L, T

HFC, PFC substitutes for ODS L, T

CH4 Enteric Fermentation in Domestic Livestock L, T

Direct N2O Agricultural Soils L, T

CO2 Forest land remaining Forest land L, T

CO2 Cropland remaining Cropland L, T

CO2 Land converted to Grassland L, T

Indirect N2O from Nitrogen used in agriculture L, T

N2O Manure Management L, T2

CH4 from Solid waste Disposal Sites L, T2

CO2 Cement production L, T2

CO2 Land converted to Settlements L, T2 

CH4 Manure Management L,T2

CO2 stationary combustion other fuels L1, T1

CH4 Emissions from Wastewater Handling L2, T2

CO2 Land converted to Forest Land L2, T2

N2O stationary combustion L

CO2 Mobile combustion: Waterborne Navigation L1 

CO2 Fugitive emissions from Oil and Gas Operations T1

N2O Adipic Acid T1

CO2 Iron and steel production T1

PFC Aluminium production T1

N2O from animal production L2

N2O 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 2007.

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 process, 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 procedures and verification activities to be followed during the inventory

compilation and helps in the inventory improvement. Furthermore, specific QA/QC procedures and 

different verification activities implemented thoroughly the current inventory compilation, 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 inventory 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 CO2 equivalent emissions and with a high 

uncertainty. 

In addition 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 are 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 inventory 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’ database. 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 submission 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 local 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 estimate 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 comments have been considered before 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, estimations 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 fact, 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 emissions 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 are 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.

The inventory is also presented to a Technical Committee on Emissions (CTE), coordinated by the 

Ministry for the Environment, Land and Sea, where all the relevant Ministries and local authorities 

are represented; within this task emission figures and results are shared and discussed. 

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 subjected by the UNFCC Secretariat to the incountry 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 review 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 on 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 contexts, 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 particular, 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, emissions from power generation per kWh of electricity 
34

produced, emissions 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 

European and international level by considering the annual reports compiled by the EC and the 

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

relevant workshops.

Additional comparisons between emission estimates from industrial sectors and those published by 

the industry itself in their 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 national 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 methodologies 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 International 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/past_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. More 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 was 

dedicated to the national emission inventory. In addition, a specific event was held on the results of 

the 2005 national GHG inventory. 

A specific procedure undertaken for improving the inventory regards the establishment of national 

expert panels (in particular, 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. 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 information 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. 

In addition to 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 statistical 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, these 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 collected 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 completed 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 activities are 

documented and archived. The archive is organised so that any skilled analyst could obtain relevant 

data sources and spreadsheets, reproduce the inventory and review all decisions about assumptions 

and methodologies undertaken. A master documentation catalogue is generated for each inventory 

year and it is possible to track changes in data and methodologies over time. Specifically, the 

documentation includes:

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

and final CRF tables; 

• electronic copies of all the final, linked source category spreadsheets for the inventory 

estimates (including all spreadsheets that feed the emission spreadsheets);

• results of the reviews and, in general, all documentation related to the corresponding 

inventory year submission.

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 consists 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 greenhouse 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 the 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 CO2

emissions from road transport and N2O 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 available and a high uncertainty was supposed. A combination of 

Montecarlo and Bootstrap simulation was applied to CO2 emissions, in consideration of the specific 

data availability assuming a normal distribution for activity data and for the emission factor of 

natural gas. The overall uncertainty of CO2 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 bootstrap analysis to the emission factor of diesel oil, 

all the other figures are very similar. For N2O 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 needs further study before a 

throughout application. The importance of these results is that in neither of the cases does the 

uncertainty estimation of the national 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, and 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 Annex 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 2007 the analysis assesses an uncertainty of 2.6%.

Including the LULUCF sector into the national figures, the uncertainty according to the Tier 1 

approach is equal to 6.4% for the year 2007, 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, excluding 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 documentation to duplicate the analysis. The 

assumptions on which uncertainty estimations are based are documented for each category. 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 European Emissions Trading Scheme, the European 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%; the 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 energy sector sources out of the total which estimates derive from accurate 

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

sectors. For the categories with a high uncertainty further improvements are planned whenever 

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; results 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 2007 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 N2O 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, CO2 and CH4 emissions from 

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

detailed information is available. CH4 emissions from other leakage emissions are included in

distribution emission estimates. N2O emissions from 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 use 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 2007 inventory
39

Chapter 2: TRENDS IN GREENHOUSE GAS EMISSIONS

2.1 Description and interpretation 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 A8.1- A8.5 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 CO2 equivalent, excluding emissions and removals from

LULUCF, have increased by 7.1% between 1990 and 2007, varying from 516 to 553 CO2

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, CO2, which accounts for 86.0% of total emissions in CO2

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.

CH4 and N2O emissions are equal, respectively, to 6.9% and 5.8% of the total CO2 equivalent 

greenhouse gas emissions. CH4 emissions have decreased by 8.4% from 1990 to 2007, while N2O 

has decreased by 14.9%. 

Other greenhouse gases, HFCs account for 1.2% of total emissions, PFCs and SF6 are equal to 0.1% 

of total emissions; HFC emissions show a strong increase, while PFC emissions show a decrease 

and SF6 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 more important in next years. 

Figure 2.1 illustrates the national trend of greenhouse gases for 1990-2007, expressed in CO2

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

199019911992199319941995199619971998199920002001200220032004200520062007

CO2 eq. (Mt) excluding LULUCF

CO2 CH4 N2O HFCs, PFCs, SF6 

Figure 2.1 National greenhouse gas emissions from 1990 to 2007 (without LULUCF) (Mt CO2 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% and 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 contributes with 11.4%.

Figure 2.2 shows total greenhouse gas emissions and removals subdivided by sector.

-140

-40

60

160

260

360

460

560

199019911992199319941995199619971998199920002001200220032004200520062007

 CO2 eq. (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 CO2 eq.)

2.2 Description and interpretation of emission trends by gas

2.2.1 Carbon dioxide emissions 

CO2 emissions, excluding CO2 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 (33.2%) 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 CO2 emissions by sector is shown in Figure 2.3.

0

100

200

300

400

500

199019911992199319941995199619971998199920002001200220032004200520062007

CO2 (Mt)

Energy Industries Manufacturing Industries and Construction

Transport Non industrial combustion

Industrial processes Other

Figure 2.3 National CO2 emissions by sector from 1990 to 2007 (Mt)
41

The main sectors responsible for the increase of CO2 emissions are transport and energy industries; 

in particular, emissions from transport have 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 construction 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;

• CO2 emissions, excluding emissions and removals from land-use change and forests;

• CO2 intensity, which represents CO2 emissions per unit of total energy consumption.

The figures of CO2 emissions per total energy unit show that CO2 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

199019911992199319941995199619971998199920002001200220032004200520062007

1990=100

GDP

Total energy consumption

CO2 emissions

CO2 Intensity

Figure 2.4 Energy-related and economic indicators and CO2 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 CO2 equivalent, and show a decrease of approximately 3.5 Mt as compared to 1990 

levels.

CH4 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 the 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 emissions equal to 9.3% as compared to 

1990. 
42

In terms of CH4 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 extraction 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 sector, 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

199019911992199319941995199619971998199920002001200220032004200520062007

C H 4 (Gg)

Energy Agriculture Waste Other 

Figure 2.5 National CH4 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 CO2 equivalent.

The major source of N2O 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% from 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 N2O emission factors of catalysed automobiles.

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 abatement 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

199019911992199319941995199619971998199920002001200220032004200520062007

N O (Gg) 2

Energy Agriculture

Industrial processes Waste

Solvent use

Figure 2.6 National N2O 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 SF6. Taken altogether, the emissions of fluorinated gases 

represent 1.3% of total greenhouse gases in CO2 equivalent in 2007, and they show an increase of 

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

gases.

HFCs, for instance, have increased considerably from 1990 to 2007, from 0.4 to 6.7 Mt in CO2

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 CO2 equivalent, and it it is due to the use of the gases in the production of 

aluminium (69.5%) and in the production of semiconductors (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 SF6 are equal to 0.4 Mt in CO2 equivalent in 2007, with an increase of 28.4% as 

compared to 1990 levels. 12.6% of SF6 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 semiconductors manufacture. From 2005 to 2006, emissions of SF6 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 cooperation 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

199019911992199319941995199619971998199920002001200220032004200520062007

CO2 eq. (Gg)

SF6

PFCs

HFCs 

Figure 2.7 National emissions of fluorinated gases by sector from 1990 to 2007 (Gg CO2 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 CO2 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 CO2 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

Manufacturing 

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 CO2 equivalent from the energy sector by source (1990-2007) (Gg CO2 eq.) 

An upward trend is noted from 1990 to 2005, total greenhouse gas emissions, in CO2 equivalent, 

show an increase 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 CO2, whose levels have increased by 10.2% from 1990 to 

2007 and account for 97.4% of the total, and N2O which shows an increase of 18.0% but its share 
45

out of the total is only 1.2%; CH4, 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 CO2

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

0.2 1.6

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 CO2 equivalent from the energy sector (1990-2007) (Mt CO2 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 CO2 equivalent, show a decrease of 0.5%, from the base year to 2007. 

Taking into account emissions by substance, CO2 level decreased by 1.0%, while N2O level 

decreased by 71.7%; these two substances account altogether for about 79.4% of the total emissions 

from industrial processes. The 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 production. 

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%. 

Details 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

SF6 333 601 493 795 740 468 502 465 406 428

Table 2.2 Total emissions in CO2 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 CO2 equivalent from industrial processes (1990-2007) (Mt CO2 eq.)

2.3.3 Solvent and other product use

Emissions from the solvent and other product use sector refer to CO2 and N2O, 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 CO2 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 different sources. As regards CO2, 

emission levels from paint application sector, which accounts for 51.4% of total CO2 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, CO2 emissions from metal degreasing 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 CO2 equivalent emissions (excluding 

LULUCF) and for 42.7% of the total NMVOC emissions, and represents the main source of

anthropogenic NMVOC national emissions. 

N2O emissions from this sector, in 2007, represent 2.4% of the total N2O national emissions.

Emissions from paint application and other use of solvents for NMVOC and CO2 are about equal to 

80.5% and 95.0%, respectively, of the total sector. 

From 1990 to 1995, a quite stable level of N2O emissions is observed, afterwards from 1995 to 

1998 emissions increased by 37.5%. From 1999, there appears to be a reduction in N2O emissions, 

due to a decrease in the anaesthetic use of N2O, 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 CO2 equivalent from the solvent and other product use sector (1990-2007) 

(Mt CO2 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 7,383 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 CO2 equivalent from the agricultural sector by source (1990-2007) (Gg CO2 eq.)

Emissions refer to CH4 and N2O 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 CH4 emissions from enteric fermentation (-9.5%) which account for 29.6% of the total 

emissions. Detailed 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 CO2 equivalent from agriculture (1990-2007) (Mt CO2 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 CO2 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 -55,372

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 CO2 equivalent from the LULUCF sector by source/sink (1990-2007) (Gg CO2 eq.) 

Total removals, in CO2 equivalent, show an increase of 5.1%, from the base year to 2007.

CO2 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 CO2 equivalent fr om LULUCF (1990-2007) (Mt CO2 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 CO2 equivalent 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%), which 

accounts for 24.1% of the total . 

Considering emissions by gas, the most important greenhouse gas is CH4 which accounts for 87.0% 

of the total and shows an increase of 3.9% from 1990 to 2007. N2O levels have increased by 9.5% 

while CO2 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 CO2 equivalent from the waste sector by source (1990-2007) (Gg CO2 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

3.6 0.025

6A

6B

6C

6D

Figure 2.13 Trend of total emissions in CO2 equivalent from waste (1990-2007) (Mt CO2 eq.)
51

2.4 Description and interpretation of emission trends for indirect greenhouse gases and SO2 

Emission trends of NOX, CO, NMVOC and SO2 from 1990 to 2007 are presented in Table 2.6 and 

Figure 2.14.

 

Indirect greenhouse 

gases and SO2

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

kt

NOX 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

SO2 1,795 1,320 749 697 616 518 480 401 379 339

Table 2.6 Total emissions for indirect greenhouse gases and SO2 (1990-2007) (kt)

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

observed for SO2 (-81.1%), CO levels have reduced by 51.9%, while NOX 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 SO2, NOX, NMVOC and NH3, 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 low sulphur content and natural gas. 

0

1000

2000

3000

4000

5000

6000

7000

8000

199019911992199319941995199619971998199920002001200220032004200520062007

kt

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 used 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 process 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 emissions 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. That 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 available 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 fuel 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 illustrate 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 they 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 sector tables 1.A.4a and 1.A.4b. Four out of six key categories refer 

to CO2 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 accurate 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 CO2, N2O and CH4, 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 CO2 from air transport and road transport, as can be seen in the 

Table 3.18 and 3.19, respectively. The trend of N2O and CH4 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 emissions 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

1CO2 stationary combustion liquid fuels L,T X 3.4, 3.5 and 3.7 Table 3.9

2CO2 stationary combustion solid fuels L,T X 3.4, 3.5 and 3.7 Table 3.9

3CO2 stationary combustion gaseous fuels L,T X 3.4, 3.5 and 3.7 Table 3.9

4CO2 mobile combustion: Road Vehicles L,T X 3.6 and 3.6.3 Tables 3.18, 3.19

5N2O stationary comb ustion L X 3.4, 3.5 and 3.7 Table 3.9

6CO2 mobile combustion: Waterborne Navigation L1,T2 X 3.6.4 Table 3.24

7CH4 fugitive emissions from Oil and Gas Operations L,T X 3.11 Table 3.28

8N2O mobile combustion: Road Vehicles L2 3.6 and 3.6.3 Tables 3.18, 3.19

9CO2 fugitive emissions from Oil and Gas Operations L2,T X 3.11 Table 3.28

1

0

CO2 stationary combustion other fuels

L1,T1

not key 

in 1990

3.4, 3.5 and 3.7 Table 3.9

1

1

CH4 stationary combustion

L2

not key 

in 1990

3.4, 3.5 and 3.7 Table 3.9

1

2

CH4 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 

fuel. 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) = Emission 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 (CO2);

NOx as nitrogen dioxide;

nitrous oxide (N2O);

methane (CH4);

non methane volatile organic compounds (NMVOC);

carbon monoxide (CO);

sulphur dioxide (SO2).

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;

Public 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 hydrocarbon 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 

fuel 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 Italy, 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, biodiesel 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 Guidelines (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 

agriculture.

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 estimated 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-categories, 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 stationary 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 IPCC 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 their 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 facilities 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, energy 

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 CO2 emissions, considering the total 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, industrial 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 emission factor is equal to 

112.9 kg CO2/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 agriculture 

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 2006 submission, there has been an overall revision of CO2 from the iron and steel industry. CO2

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, CO2 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 used 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 whole 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 sectoral 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, natural gas CO2 emission factors have been updated for 2006 because of 

additional information collected on the chemical composition of natural gas imported; coal CO2 

average emission factors have also been revised from 2005 based on updated amounts of fuel 

imported from different countries. Fuel oil CO2 average emission 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 refineries, 

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 distributor 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 energy 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 completely revised N2O 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 recalculations 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 “Statistical 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 voltage 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, either 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 content 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 that 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 for 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 publish 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, m3

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, m509 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, m3

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 m3 

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 the 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 energy 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;

- activity 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 differences 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 emissions.

To estimate CO2 emissions, and also N2O and CH4 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 process of the Initial report of the Kyoto Protocol and of the 2006 

submission under the Convention, N2O and CH4 stationary combustion emission factors have been 

revised for the whole time series taking into account default IPCC (IPCC, 1997; IPCC, 2000) and 

CORINAIR 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 industrial 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 industrial 

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 grid. 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 CO2

, 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/CO2 emissions in CRF format, year 2007

In Table 3.4, the time series of the total CO2 emissions deriving from electricity generation

activities is reported, including total electricity produced and specific CO2 emissions for the total 

production and for the thermoelectric production only.

The time series clearly 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 stable from the year 

2000 to 2002 because efficiency increases have been balanced by a growing coal share. From 2003 
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 CO2 emitted, Mt 128.5 135.7 140.5 138.3 145.4 148.1 146.0 146.4 148.7 144.2

g CO2 / kwh of gross thermo-electric production 720 693 645 640 641 624 609 596 578 556

 g CO2 / kwh of total gross production 592 562 508 496 511 504 481 482 474 459

Source: ISPRA elaborations

Table 3.4 Time series of CO2 emissions from electricity production

3.4.2 Refineries

The consumption data used come from BEN (MSE, 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 boilers 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 the 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 counting of the CO2 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 routinely 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. 

 CO2 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, CO2 emission calculation, year 2007

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO2 emissions, Mt 16.3 18.6 21.8 23.6 23.6 22.7 24.2 26.1 24.9 25.9

CH4 emissions, kt 0.46 0.53 0.59 0.67 0.68 0.64 0.64 0.67 0.67 0.70

N2O 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 in 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 production 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 CO2 / TJ t CO2 / t t CO2 / tep

Liquid fuels

Crude 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 (sm3

) 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

Refinery 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

Municipal 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, 2000-07 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 industry 

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 emission 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 electricity 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 emissions 

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

CO2 emissions, kt 88,937 87,955 88,134 85,412 81,540 86,418 86,244 81,732 82,106 78,867

CH4 emissions, t 6,819 7,021 5,717 5,778 5,676 5,817 5,742 6,267 6,225 6,508

N2O 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 emissions 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 CO2 emissions from combustion 

of liquid fuels and an increase of emissions from gaseous fuels.

1990 2007 

CO2 stationary combustion liquid fuels kt 153,467 86,306

CO2 stationary combustion solid fuels kt 59,395 66,727

CO2 stationary combustion gaseous fuels kt 85,066 159,220

CH4 stationary combustion t 1,779 4,210

N2O 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 increased in the period from 1990 to 2007.

The time series of CO2, CH4 and N2O 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 N2O 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

CO2 Mt 101.3 111.4 120.1 122.2 124.1 125.1 127.1 125.8 127.2 127.2

CH4 Mt 0.90 0.99 0.75 0.71 0.65 0.61 0.55 0.49 0.47 0.45

N2O Mt 1.11 1.81 2.09 2.05 2.02 1.95 1.92 1.48 1.55 1.53

Total, Mt CO2 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 aviation are reported as a memo item, and 

are not included in national totals.

Civil aviation gives mainly rise to CO2 emissions. CH4 and N2O emissions also occur and are 

estimated in this category but their contribution is insignificant. 

In 2007 total GHG emissions 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 CO2 only, 

the share is almost the same. 

From 1990 to 2007 GHG emissions from the sector increased 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 aviation is not a key category 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

developed 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 and 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 aviation 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 different 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 statistics 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 specificities 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 both 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 flights 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 from 

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 airports considering the information 

of whether the flight is international or domestic and the 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, estimates have been carried out 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 international, 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 international 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 available 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). Therefore, 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)

CO2

a

SO2

Aviation jet fuel 849 1.0

Aviation gasoline 839 1.0

a Emission factor as kg carbon/t.

Table 3.12 CO2 and SO2 emission factors for Aviation (kg/t) 1990-2007

 Units CH4 N2O NOx CO NMVOC Fuel

Domestic LTO kg/LTO 0.189 0.040 5.313 6.939 1.698 461.7

International 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 akg/t fuel 0.4 0.2 15.8 126 3.6 -

a EMEP/CORINAIR, 2007 

Tabl e 3.13 Non-CO2 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 387 385 464 502 546 629 642 588 590 587

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 -series consistency 

The combined uncertainty in CO2 emissions from aviation is estimated to be about 4% in annual 

emissions; a higher uncertainty is calculated for CH4 and N2O emissions on account of the 

uncertainty levels attributed to the related emission factors. 

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 more modern aircraft into the 

fleet slow down the tendency in the last years.

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO2 kt 1.613 1.709 2.649 2.424 2.425 2.415 2.231 2.204 2.291 2.428

CH4

t 32 33 63 69 78 96 102 112 98 72

N2O 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 2009 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 time 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 consumption; 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 NOX, 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 technological improvements and 

fleet composition for domestic flights.

Specifically, for greenhouse gases, CO2 emissions were recalculated from 1990 due to a different 

emission factor applied with respect to previous submissions. The emission factors used are 

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 and 70.0 kg/Gj for the avio 

gasoline. For these fuels, an oxidation factor equal to 1 has been considered. This recalculation 

resulted in an increase of CO2 emission by 1% with respect to previous submissions.

N2O and CH4 emissions were also recalculated but they are less important in terms of absolute 

values. N2O 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 kg/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 

CH4 emissions which have been calculated applying the default emission factor of 10% of total 

hydrocarbons (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 from 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 specific 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 N2O emissions are calculated on fuel based emission factors 

using fuel consumption data from BEN. Emissions of CO, NMVOC, NOx and methane are based 

on the EMEP/CORINAIR methodology (EMEP/CORINAIR, 2007). The emission factors shown in 

Table 3.16 are aggregate factors so that all factors are reported on the common basis of fuel 

consumption.

CO2 CH4 N2O NOx CO NMVOC SO2

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. 

CO2 for road transport is key category for 2007 with Tier 1 and Tier 2 methods at level and trend 

assessment, with and without LULUCF. N2O emissions are key category at level assessment only 

with Tier 2. CH4 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 

data 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 (EMEP/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, distinguishing 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 (LPG) 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 CO2, expressed as kg carbon per tonne of fuel, are based on the H/C ratio of the fuel; 

emissions of SO2 are based on the sulphur content of the fuel. Values of the fuel-based emission 

factors for CO2 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 SO2 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 European Directives on fuel quality; these figures are also published by the refineries industrial 

association (UP, several years).

National emission factors t CO2 / TJ t CO2 / t

Mtbe 73.121 -

Gasoline, 1990-'99, interpolated emission 

factor 71.034 3.121

Gasoline, test data, 2000-07b71.145 3.109

Gas oil, 1990-'99, IPCC OECDa73.274 3.127

Gas oil, engines, test data, 2000-07b73.153 3.138

LPG, 1990-'99, IPCCa Europe 64.350 3.000

LPG, test data, 2000-07b64.936 2.994

Natural gas (dry) 1990 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 Factors for Road Transport

Emissions of CO2 and SO2 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 used 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 used for the whole time series. As reported more in details in the following, the new 

model updates especially NOX and N2O emission factors; the application to Italian data resulted in a 

strong increase of NOX emissions and a strong decrease of N2O 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, NOX, CO, CH4 and N2O are calculated from emission factors 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 different 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/km) 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 35,857,521

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 at 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 registered. 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 are 

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 vehicles 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 operating 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 the 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

characteristics 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 emissions 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 Vehicles (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, several 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 produces 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 information 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, subdivided 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 duty (%)

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 network 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 surveys 

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 (109 veh-km/y) 295 352 389 426 426 426

Car fleet (106) 27 30 32 34 35 35

Moto, total mileage (109 vehkm/y) 31 39 45 49 50 51

Moto fleet (106) 7 7 9 10 10 10

Goods transport, total mileage 

(109 veh-km/y) 69 77 93 98 102 104

Truck fleet (106), 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 emits 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 until 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 transport. 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 CO2 emissions from road transport is estimated to be about 4% in 

annual emissions; a higher uncertainty is calculated for CH4 and N2O 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 CO2 equivalent from 

road transport, highlighting the evolution of this growing source.

An upward trend in CO2 emission levels is observed from 1990 to 2004, which is explained by the 

increasing of the fleet, total mileages and fuel consumptions. 

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

CO2 kt 93,387 103,553 110,385 113,064 115,209 116,321 118,395 117,035 118,268 118,721

CH4 kt 867 956 713 674 621 576 515 459 440 415

N2O 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 CO2 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 inventory 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 factors 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 possible 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. The 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 management 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 

emissions. 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 motorcycles, 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 series 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 updated 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 CO2 emission factors, IPCC values were considered 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 N2O and NOX for the whole time series, for all 

vehicles. The main update regarded heavy goods vehicles and passenger cars diesel fuelled. New 

estimates of N2O 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. Higher 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 for 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.

Mainly CO2 emissions derive from this category, whereas CH4 and N2O emissions are less 

important.

Emissions from navigation constituted 3.9 per cent of the total GHG in the transport sector in 2007 

and 0.9 per cent of the national total. If considering CO2 only, emissions from navigation are 1.1% 

out of the national CO2 emissions. GHG emissions decreased by 8.3 per cent from 1990 to 2007, 

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 CO2 emissions 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/CORINAIR 

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 cruise 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 for 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 shipping 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 and harbour activities and national cruise, taking 

into account national specificities. These specificities derive from the results of a national study 

which, taking into account detailed information on the Italian marine fleet and the origin-destination 

movement matrix for the year 1997, calculated national values (ANPA, 2001; Trozzi et al., 2002 

[b])) 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 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 2004, 2005 and 2006 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 harbour (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 each 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 number 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 90% 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 and 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 described above and emissions are therefore calculated. 
76

3.6.4.3 Uncertainty and time -series consistency 

The combined uncertainty in CO2 emissions from maritime is estimated to be about 4% in annual 

emissions; a higher uncertainty is calculated for CH4 and N2O 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 travels 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

Fuel in domestic travels (kt) 778 706 802 843 866 818 811 787 748 741 732 740 709 673

Fuel in harbours (dom+int ships) 

(kt) 748 693 794 824 853 814 818 800 767 766 763 759 727 690

Fuel 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

CO2 (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

CH4 (kt CO2 eq.) 29 32 33 33 33 32 32 32 31 31 30 30 29 29

N2O (kt CO2 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 CO2 eq.)

3.6.4.4 Source-specific QA/QC and verification 

Basic data to estimate emissions have been reconstructed starting from information 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 communicated 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 were applied for the all time series considering 

model results of the year 1997. 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 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 NOX, 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 gasoline 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 movements 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 underestimated.

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 

reported 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. 

The 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

Emissions 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 Industry, 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 diesel 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 portable 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)

• aircraft 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 Construction.

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. agriculture 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 used 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 was 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. Time 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 but 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 transport 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 are 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;

- quantities 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 possible 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 Table 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 quantities 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.

At national level, this methodology seems the most precise according to the available data. The 

European Project “Non Energy use-CO2 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 produced 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 National 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: BEN 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 excise 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 emissions 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 CO2 equivalent, account for 1.6% out of the total emissions in the 

energy sector. Both CH4 and CO2 emissions show a reduction from 1990 to 2007 by 32% and 35%, 

respectively.
82

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO2

Oil and 

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

CH4

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

N2O

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 CO2 eq.)

The decrease of CO2 fugitive emissions is driven by the reduction in crude oil losses in refineries. 

Emissions are balanced with the amount of crude oil losses reported in the national Energy Balance 

(MSE, several years [a]). 

The trend of CH4 fugitive emissions from solid fuels is related to the extraction of coal and lignite 

that in Italy is quite low while the decrease of CH4 fugitive 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 identification in the fugitive sector with the IPCC Tier1 and Tier2 approaches (without LULUCF)

1B2 CH4 Fugitive emissions from oil and gas operations Key (L, T)

1B2 CO2 Fugitive emissions from oil and gas operations Key (L2, T)

Specifically, methane emissions from 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 emissions and removals. CO2 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 emissions and removals. The uncertainty in CH4, N2O and CO2 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.

Fugitive emissions from solid fuels, reported in 1.B.1, are not relevant. In fact, CH4 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 surface, produces lignite. The surface mine 

stopped the activity in 2001. CH4 emissions from solid fuel transformation refer to the coke 

production in the iron and steel industry, which is also decreasing in the last years. 

CH4 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). CH4 emissions from coke production have been estimated on the basis of 

activity data published in the national statistical yearbooks (ISTAT, several years) and emission 

factors reported in the EMEP/CORINAIR Guidebook (EMEP/CORINAIR, 2005). CO2 and N2O 

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 CO2 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 (MSE, 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).

CH4 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. CH4 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). CH4 emissions from the transmission 

in pipelines and distribution of natural gas have been estimated on the basis of activity data 

published 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 reported 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 pressure 

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 collected 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, N2O 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 CO2 equivalent.

In the submission 2009, CH4 emissions from the transmission 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 CH4 emission 

equal to 0.5% and 3.4% in 2004 and 2005, respectively, and a reduction of 0.9% in 2006. Moreover 

CH4 emissions from the production of oil from 2005 were updated on the basis of new activity 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 explained below. 

CO2 and CH4 fugitive emissions from oil exploration are included in those from production because 

no detailed information is available. N2O 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. CO2 and CH4 emissions from gas exploration are also included in those from production 

while CH4 emissions from other leakage are included in distribution emission estimates. Further

investigation will be carried out with industry about these figures.
84

CO2 and CH4 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.

CO2 and CH4 emissions from gas flaring are also included in production under 1.B.2.b.

A summary of the completeness of CO2, CH4 and N2O fugitive emissions is shown in the following 

Table 3.29.

1.B. 2.a. Oil 

i. Exploration CO2,CH4Included in 1.B.2.a production

i. Exploration N2O Included in 1.B.2.c oil flaring

iv. Refining N2O Included in 1.B.2.c oil flaring

1.B.2.b. Natural Gas 

i. Exploration CO2,CH4Included in 1.B.2.b production

iii. Other leakage CH4 Included in 1.B.2.b distribution

1.B. 2.c. Venting and

flaring

 

i. Oil CO2,CH4Included in 1.B.2.a production

ii. Gas CO2,CH4Included in 1.B.2.b production

Table 3.29 Completeness of CO2 CH4 and N2O fugitive emissions 
85

Chapter 4: INDUSTRIAL PROCESSES [CRF sector 2]

4.1 Overview of sector

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 separately and included in category 1A2. 

All greenhouse gases as well as CO, NOx, NMVOC and SO2 emissions are estimated.

In 2007 industrial processes account for 5.7% of CO2 emissions, 0.2% of CH4, 5.9% of N2O, 100% 

of PFCs, HFCs and SF6. In term of CO2 equivalent, 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 CO2, CH4 and N2O and in Gg of CO2 equivalent for Fgases. An increase in HFC emissions is observed from 1990 to 2007, while CO2 emissions from 

chemical and metal industry reduced sharply.

GAS/SUBSOURCE 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO2 (Gg)

2A. Mineral Products 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

CH4 (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

N2O (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 CO2 eq.) 351 671 1,986 2,550 3,100 3,796 4,515 5,267 5,956 6,700

PFCs (Gg CO2 eq.) 1,808 491 346 451 424 498 348 353 282 288

SF6 (Gg CO2 eq.) 333 601 493 795 740 468 502 465 406 428

Table 4.1 Trend in greenhouse gas emissions from 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 identification in the industrial processes sector with the IPCC Tier1 and Tier2 approaches

2F HFC, PFC Emissions from substitutes for ODS Key (L, T)

2A CO2 Emissions from cement production Key (L, T2)

2B N2O Emissions from adipic acid Key (T)

2A CO2 Emissions from limestone and dolomite use Key (L1)

2C CO2 Emissions from iron and steel production Key (T1)

2B CO2 Emissions from ammonia production Key (T1)

2C PFC Emissions from aluminium production Key (T1) 

CO2 emissions from cement and limestone and dolomite use are included in category 2A; N2O 

emissions from adipic acid and CO2 emissions from ammonia refer both to 2B; PFCs from 

aluminium production are included in 2C as CO2 emissions from iron and steel production.

Methane emissions from the sector are not a key source.

All these categories, except CO2 emissions from limestone and dolomite use and ammonia, are also 

key category sources including the LULUCF estimates in the key category assessment. 

In addition CO2 emissions from limestone and dolomite use is a key category in the base year at 

level assessment with the Tier 1 approach including LULUCF and N2O 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 Source category description

In this sector CO2 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 contributes are also included in this sector but they contribute 

only with NMVOC emissions; CO2 emissions from decarbonising in glass production have been 

estimated and reported in “Other”.

Cement

Cement production (2A1) is the main source of CO2 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 changes 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 “semidry” 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 association, 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

CO2 emissions occur also from processes where lime is produced and account for 0.51% of the total 

national emissions. Lime production can also occur, beside 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 Italy 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 CO2 emissions 

according to the following reaction:

CaCO3 + MgCO3 + heat‡ CaO +MgO+2CO2

CO2 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. 

CO2 emissions estimation is related to lime production in mineral industry and it includes also the 

production of lime in iron and steel making facilities 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 and dolomite use (brick and tiles; fine ceramics)

CO2 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 steps 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 dolomite are also used 

in paper production process. CO2 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 types: 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 North. 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 released 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, NOx, SOx, CO2; occasionally and depending on the specific production process heavy 

metals, fluorides and chlorides gases could be released. CO2 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 Italy 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. CO2 is released to air and calcium chloride 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 production 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

CO2 emissions from cement production are estimated 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 combustion process and 

decarbonising process. For the years from 1990 up to 2003 the resulting emission factor for cement 

production was equal to 540 kg CO2/ton clinker, based on the average CaO content in the clinker 

and taking into account the contribute of carbonates 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 values: 532 kg CO2/ton 

clinker in 2004, 525 kg CO2/ton clinker in 2005, 526 kg CO2/ton clinker in 2006 and 531 kg 

CO2/ton clinker in 2007, based on the average CaO content in the clinker and taking into account 

the contribute of carbonates and additives.

Lime

CO2 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 estimated 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 706 kg CO2/ton lime production in 2005; 694 kg CO2/ton lime 

production in 2006 and 707 kg CO2/ton lime production in 2007.

Limestone and dolomite

CO2 emissions from limestone and dolomite use are related to the use of limestone and dolomite in 

bricks, tiles 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 CaCO3 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 associations (ANDIL, 2000; ANDIL, several years;

ASSOPIASTRELLE, several years; ASSOPIASTRELLE, 2004).

Soda ash

CO2 emissions from soda ash production have been estimated on account of information available 

on the Solvay process (Solvay, 2003), whereas those from soda ash use are included in glass 

production. 

Glass

CO2 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 

framework 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 factors 

(EMEP/CORINAIR, 2007).

4.2.3. Uncertainty and time -series consistency

The uncertainty in CO2 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% and 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 considered 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 CO2 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)

CO2 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 2,185 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 CO2 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

CO2 emissions have been checked with the relevant industrial 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 have been done as CO2 emission factors for cement and lime industries (2004-2006) 

have been changed on account of the complete information availability from emissions trading 

scheme. Consequently, as for CO2 emissions, recalculations for cement industries result 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 are planned.

4.3 Chemical industry (2B) 

4.3.1 Source category description

CO2, CH4 and N2O emissions from chemical productions are estimated and included in this sector.

In this submission, CO2 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: 

C6H11OH+2HNO3‡HOOC(CH2)4COOH+N2O+2H2O+energy

Adipic acid is then used to produce nylon or is fed to other production processes. Together with 

adipic acid, N2O is produced and CO2 is one of the by-products (Radici Chimica, 1993). 

Emissions data from adipic acid production are provided and referenced by one plant, which is the 

sole producer in Italy (Radici Chimica, several years). Specifically, for N2O, adipic acid is a key 

source at trend assessment, both with the Tier 1 and Tier 2 approach. These emissions accounted for 

16.0% of total N2O emissions in 2005 and 2.45% in 2007 because the technology to reduce N2O 

emissions started to be fully operative at the existing producing facility. 

N2O emissions have been relevantly decreasing thanks to the implementation of a catalytic

abatement system (pilot scale plant). The use of thermally stable catalysts in the pilot plant has 

allowed the treatment of highly N2O concentrated flue gas from the adipic acid production plant, 

thus reducing the volumes of treated gas and the size of the pilot plant itself. In 2004 this system 

was tested for one month resulting in complete decomposition of N2O, in 2005 because of technical 

changes in the system the catalytic process was started only at the end of 2005; in 2006 the 

abatement system had been operating continuously for 9 months (three months were needed for 

maintenance and technical changes) leading to the decomposition of 95% of N2O emissions; in 

2007 the operating time was 11 months (about one month was needed for maintenance operations). 

The abatement pilot scale plant is generally run together with the adipic acid production process; 

the abatement rate for N2O emissions was 90% in 2007.

Also CO2 emissions are estimated from this source.

Ammonia production

In Italy only 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. CO2 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.

CO2 emissions 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 facilities 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 NH3 to NO2 and subsequent reaction with water. Currently the reactions involved take place in 

low and medium pressure processes. 

N2O 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, H2, H2O, NOx, SOx and H2S; it is generally burn 

to reduce the emissions to air and to recover energy to be used in the production process.

CO2 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 manufacture 

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 processes 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 propylene, 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

CO2 emissions from dioxide titanium production have been estimated on the basis of information 

supplied directly by the Italian production plants. TiO2 is the most used white pigment especially 

for paint and plastic industries. In Italy there’s only one facility where 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 N2O.

N2O emissions from caprolactame production 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 is obtained according to the following reaction:

CaO+3C‡CaC2+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 because 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 for adipic acid have been provided by the process 

operator (Radici Chimica, several years); for the whole time series. N2O emissions from adipic acid 

production (2B3) have been estimated using the default IPCC emission factor equal to 0.30 kg 

N2O/kg adipic acid produced, from 1990 to 2003. In 2004, the N2O 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 N2O/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 N2O/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 CO2 emission factor, equal to 1.175 t CO2/t ammonia production, 

has been calculated on the basis of information reported by the production plants for 2002 and 2003 

in the framework 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 N2O average emission factors are calculated from 1990 on the 

basis of the emission factors provided by the existing production plants in the national EPER/EPRTR registry, applied for the whole time series, and default IPCC emission factors for low and 

medium 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 7.07 kg N2O/Mg nitric acid production, in 

1990 and in 2007 respectively. 

Caprolactame

N2O 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 (ISTAT, 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 N2O/Mg caprolactame production. The plant closed in 2003.

Carbon Black

CO2 and CH4 emissions from carbon black production process have been estimated on the basis of 

information supplied by the Italian production plants in the framework of the national EPER/EPRTR registry and the European emissions trading scheme. In 1996 a change in the production 

technology in the existing plants caused a reduction of CH4, NMVOC, NOx, SOx and PM10
93

emissions. In 2005, the CO2 implied emission factor is equal to 2.55 t CO2/t carbon black 

production, in 2007 it is 2.50 t CO2/t carbon black production. 

Calcium carbide

CO2 emissions 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) CO2 emission factor has been used to estimate the 

emissions. 

4.3.3. Uncertainty and time -series consistency

The uncertainty in N2O emissions from adipic and nitric acid and caprolactame production and in 

CO2 emissions from ammonia and for other chemical production is estimated 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, while 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 N2O emissions and 

for CO2 emissions from other industrial processes. 

In Tables 4.4 and 4.5, the production of chemical industry, including non-key sources, and CO2, 

CH4 and N2O 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 CO2 emissions from ammonia have decreased as a result of a relevant reduction in production 

while CO2 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

CO2 (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 7.09 - - - - - - - -

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

CH4 (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 oxide 0.42 0.37 0.09 0.03 NA NA NA NA NA NA

N2O (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 CO2, CH4 and N2O 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 process 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 CO2 emissions from calcium carbide

production process have been estimated and reported for the years from 1990 to 1995. So in terms 

of Gg CO2 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; CO2 emissions from iron and steel 

production and PFC emissions from aluminium production are key sources at Tier 1 trend

assessment.

The share of CO2 emissions from metal production accounts, in the year 2007, for 0.4% of the 

national total CO2 emissions, and 7.2% of the total CO2 from industrial processes.

The share of CH4 emissions is, in the year 2007, equal to 0.15% of the national total CH4 emissions 

while N2O 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 processes 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 fluxes 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) needed 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 electric 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 pipes.

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 furnace 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 steel 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).

CO2 emissions from steel production refer to carbonates used in basic oxygen furnaces and crude 

iron and electrodes in electric arc furnaces. CO2 emissions from pig iron production refer to 

carbonates used in sinter and pig iron production. CO2 emissions from iron and steel production due 

to the fuel consumption in combustion processes are estimated and reported in the energy sector 

(1A2a) to avoid double counting.

CH4 emissions from steel production refer to blast furnace charging, basic oxygen furnace, electric 

furnaces and rolling mills. CH4 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 CO2 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 produces mainly ferro-manganese

and silicon-manganese alloys.
96

Aluminium

From primary aluminium production CO2 and two PFCs (CF4 and C2F6) are emitted.

PFCs are formed during a phenomenon known as the ‘anode effect’, when alumina levels are low.

At present in Italy 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 technology; 

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, SF6 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, SF6 has been replaced by HFC 125, due to the enforcement of fluorinated 

gases regulation (EC, 2006).

4.4.2. Methodological issues

CO2 and CH4 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 framework 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/ACE, 2000) or 

supplied directly by industry (FEDERACCIAI, 2004) have been used.

Iron and steel

CO2 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; they 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 published 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 CO2 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 CO2 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 productions.

Time series of carbonates used in basic oxygen furnaces have been reconstructed 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 the amount of carbonates estimated in sinter plants, average emission factor was 

equal in 1990 to 0.15 t CO2/t pig iron production, while in 2007 it reduced to 0.071 t CO2/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 CO2 in the blast furnaces producing pig iron. 

CO2 average emission factor in basic oxygen furnaces results in 1990 equal to 0.079 t CO2/t steel 

production, while from 2003 is null.

CO2 average emission factor in electric arc furnaces, equal to 0.035 t CO2/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 emission factors for steel production reduced from 0.053 to 0.022 t CO2/t steel production, 

from 1990 to 2007, due to the reduction in the basic oxygen furnaces.

CO2 emissions due to the consumption of coke, coal or other reducing agents used in the iron and 

steel 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.

CH4 emissions 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/CORINAIR Guidebook (EMEP/CORINAIR, 2007) and refer to blast 

furnace, basic oxygen furnace, electric furnaces and rolling mills.

Ferroalloys

CO2 emissions from ferroalloys have been estimated on the basis of activity data published in the 

national statistical yearbooks (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 production 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 CO2/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 CO2 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 emissions, 

specifically CF4 and C2F6, 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 the 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 Tier 2 method has been followed, based on default technology 

specific slope and overvoltage coefficients.

Regarding the Tier 1 methodology, the emission factors for CF4 and C2F6 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 team.

Technology specific emissions (kg CF4 / 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 (CF4) 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

Horizontal Stud Søderberg 0.09

Table 4.7 Multiplier factor for calculation of Hexafluoroethane (C2F6) 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 content 

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 Coefficients used for estimation with the Tier 2 methodology by plant

CO2 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 

default 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 

CO2/t primary aluminium production for the whole time series.

Magnesium foundries

For SF6 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 SF6 used is emitted. In 2007, SF6 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 production is estimated to be 

about 11% in annual emissions, 5% and 10% concerning respectively activity data and emission 

factors; the uncertainty for SF6 emissions from magnesium foundries is estimated to be about 7%, 

5% for both activity data and emission factors. The uncertainty in CO2 emissions from the sector is 

estimated to be 10.4%, for each activity, while for CH4 emissions about 50%.

In Table 4.10 emission trends of CO2, CH4 and F-gas from metal production are reported. The 

decreasing of CO2 emissions 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 CO2 emissions from 

aluminium and ferroalloys are driven by the production levels. 

In Table 4.11 the emission trend 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 

SF6 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

CO2 (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

CH4 (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 CO2 eq.) 

Aluminium production 1,673 298 199 234 199 268 157 181 154 200

SF6 (Gg) 

Magnesium foundries - - 0.0072 0.0188 0.0167 0.0057 0.0039 0.0035 0.0026 0.0023

Table 4.10 CO2, CH4 and F-gas emissions from metal production, 1990 – 2007 (Gg)

COMPOUND 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Gg CO2 eq.

CF4 (PFC-14) 1,289.2 235.8 168.1 198.1 168.1 226.4 133.1 153.0 130.6 170.9

C2F6 (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 SF6 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 emissions 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 CO2 equivalent, 1990 – 2007

The consistency of the time series of PFC emissions from aluminium 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 other 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 

transparent, 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 C2F6 values calculated with Tier 1 rise up.

COMPOUND 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Tier 1

CF4 (t) 198.3 36.3 19.0 18.8 19.0 19.1 19.5 19.3 19.4 18.0

C2F6 (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 

CF4 (t) 198.3 36.3 25.9 30.5 25.9 34.8 20.5 23.5 20.1 26.3

C2F6 (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 and 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;

ASSOMET, 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 magnesium 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 2002 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 CO2 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 CO2 emission 

estimates for 2004 and to improve 2006 estimates. This review process has resulted in an increase 

of CO2 emissions in iron and steel equal to 7.83% for 2004 and in a decrease equal to 7.00% in 

2006. CH4 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 factor of CO2 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 SO2 emissions occur from these sources.
101

In this sector, non-energy emissions from pulp and paper as well as food and drink production, 

especially wine and bread, are reported. CO2 from food and drink production (e.g. CO2 added to 

water or beverages) can be of biogenic or non-biogenic origin but only information on CO2

emissions of non-biogenic origin should be reported in the CRF.

According to the information provided by industrial associations, CO2 emissions do not occur, but 

only NMVOC emissions originate from these activities. CO2 emissions from food 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, NOX and NMVOC emissions as well as SO2 are 

estimated.

4.6 Production of halocarbons and SF6 (2E)

4.6.1. Source category description

The sub-sector production of halocarbons and SF6 consists of two sources, “By-product emissions” 

and “Fugitive emissions”, identified as non-key sources. Only two production plants are present in 

Italy, located in Porto Marghera and Spinetta Marengo. Within by-product emissions, HFC-23 

emissions are released from HCFC-22 manufacture, whereas C2F6, CF4 and HFC 143a emissions 

are released from the production of CFC 115, SF6 and HFC 134a, respectively. Production of HFC 

125, HFC 134a, HFC 227ea and SF6 lead to fugitive emissions of the same gases. CFC115 and SF6

productions stopped in 1998 and in 2005, respectively.

The share of F-gas emissions from the production of halocarbons and SF6 in the national total of Fgases 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 emissions” 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 years).

4.6.3. Uncertainty and time -series consistency

The uncertainty in F-gas emissions from production of halocarbons and SF6 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, thus 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 SF6 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 SF6 production stopped 

from the 1st 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 production of HFC-134a has been recovered and commercialised.
102

In Table 4.13 an overview of the emissions from production of halocarbons and SF6 is given for the 

1990-2007 period, per compound.

COMPOUND 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Gg CO2 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

CF4 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

SF6 119.5 119.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Total F-gas fugitive 

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 SF6

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 halocarbons and SF6 in Gg CO2

equivalent, 1990 – 2007

4.6.4. Source-specific QA/QC and verification

Emissions from production of halocarbons and SF6 have been checked with data reported to the 

national EPER/E-PRTR registry.

4.6.5. Source-specific recalculations

No recalculations have been done.

4.6.6. Source-specific planned improvements

No further improvements are planned.

4.7 Consumption of halocarbons and SF6 (2F)

4.7.1. Source category description

The sub-sector consumption of halocarbons and SF6 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, SF6 emissions from semiconductor manufacturing”, “SF6 emissions from 

electrical equipment”, that are non-key categories. 

Potential emissions are also reported in this section. The share of F-gas emissions from the 

consumption of halocarbons and SF6 in the national total of F-gases was 8.6% in the base-year 1990 

and 96.3% in 2007; the share in the national total greenhouse gas emissions was 0.04% in the baseyear 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 SF6 are 

presented in the following box:

Sub-sources of F-gas 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 Tier 2a

Aerosols/metered dose inhalers (2F4) IPCC Tier 2a

PFC, HFC, SF6 emissions from 

semiconductor manufacturing (2F6) IPCC Tier 2a

SF6 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 other 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 

years; 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 equipment, 

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 generally 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.

SF6 emissions from electrical equipment have been estimated according to the IPCC Tier 2a 

approach from 1990 to 1994, and IPCC Tier 3c from 1995. SF6 leaks from installed equipment have 

been estimated on the basis of the total amount of sulphur hexafluoride accumulated and average 

leakage rates; leakage data published in environmental reports have also been used for major 

electricity producers (ANIE, several years). Additional data on SF6 used in high voltage gasinsulated transmission lines have been supplied by the main energy distribution companies (ACEA, 

2004; 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, import, 

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), producers, 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, that 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, SF6 emissions from semiconductor manufacturing is 

estimated to be about 58% in annual emissions, 30% and 50% concerning respectively activity data 

and emission factors; the uncertainty in SF6 emissions from electrical equipment is estimated to be 

about 11 % in annual emissions, 5% and 10% concerning respectively activity data and emission 

factors.

In Table 4.14 an overview of the emissions from consumption of halocarbons and SF6 is given for 

the 1990-2007 period, per compound.

HFC emissions from refrigeration and air conditioning equipment increased from 1994 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. Emissions from semiconductor manufactures are 

driven by the consumption data provided by the producers, one started in 1995 and the second one 

in 1998. SF6 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 CO2 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

HFC 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

CF4 0.0 24.4 64.8 107.8 106.2 117.1 127.3 96.8 87.0 71.5

C2F6 0.0 34.6 82.0 99.1 108.0 97.7 52.6 62.8 30.8 11.4

C3F8 0.0 0.0 0.0 9.0 10.2 13.2 9.6 3.5 3.5 0.1

C4F8 0.0 0.0 0.4 1.2 0.8 2.0 1.2 8.7 6.6 4.6

SF6 0.0 0.0 20.9 49.4 53.3 60.5 75.2 61.5 46.5 36.3

Total PFC, HFC, SF6

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

SF6 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 halocarbons 

and SF6

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 SF6 in Gg CO2

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 availability 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 CO2 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

CF4 0.0 0.0 55.8 158.6 167.4 183.9 186.1 148.9 159.9 141.3

C2F6 0.0 0.0 65.5 147.9 164.5 134.0 114.7 111.4 67.8 54.9

C3F8 0.0 0.0 0.0 33.9 36.8 47.0 40.3 17.9 17.9 1.5

C4F8 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

SF6 3,752.3 3,675.8 3,919.6 5,903.3 3,689.2 3,211.2 2,943.2 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 SF6, in Gg CO2

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 SF6 have been checked with data reported to the 

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 manufacturing 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 recalculations from the previous submission 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 

CF4 14.04% 14.04% 14.04%

C2F6 -22.69% -22.69% -22.69%

C3F8 -18.60% -18.60% -18.60%

C4F8 -13.00% -13.00% -13.00%

SF6 7.66% 7.66% 7.66%

Total PFC, HFC, SF6 emissions from 

semiconductor manufacturing 

SF6 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 SF6

0.01% 0.06% 0.07% 0.16% -0.06% 0.63%

Table 4.16 Comparison between recalculated and previous F-gas emissions from the consumption of halocarbons 

and SF6 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 CO2 emissions, related to Non-Methane Volatile Organic 

Compound (NMVOC) emissions from solvent use in paint application, degreasing and dry

cleaning, chemical products manufacturing or processing and other use, have been estimated.

N2O emissions from this sector have also been estimated. These emissions arise from the use of 

N2O in medical applications, such as anaesthesia, and in food industry, where N2O 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 CO2 emissions (excluding LULUCF) and 

42.68% of total NMVOC emissions, and represents the second source of anthropogenic NMVOC 

national emissions.

N2O emissions, in 2007, share 2.42% of the total N2O 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

CO2 (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

N2O (Gg)

3D. Other (use of N2O 

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, CO2 and N2O emissions from the solvent use sector, 1990 – 2007 (Gg)

CO2 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, N2O 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 the solvent and other product use sector with the IPCC Tier1 and Tier2 approaches 

(without LULUCF)

 3 CO2 Solvent and other product use Key (L2, T2)

 3D N2O Use of N2O in anaesthesia and aerosol cans Key (T2)
108

5.2 Source category description 

In accordance 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 CO2

emissions as final oxidation of NMVOC. Emissions from the following sub-sectors 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).

CO2 emissions have been estimated and included in this sector, as they are not already accounted 

for in the energy and industrial processes sectors.

N2O emissions from the use of N2O for anaesthesia and from aerosol cans (3D) have been

estimated. Emissions of N2O from fire extinguishers do not occur.

Emissions of N2O from other use of N2O (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 have 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 the 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 order 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, information 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 CO2 emissions has 

been carried out considering that carbon content is equal to 85% as indicated by the European 

Environmental Agency for the CORINAIR project (EEA, 1997), except for CO2 emissions from the 

3C sub-sector which are not calculated to avoid double-counting. These emissions are, in fact, 

already accounted for in sectors 1A2c and 2B.

Emissions of N2O have been estimated taking into account information available by industrial 

associations. Specifically, the manufacturers and distributors association of N2O products has 

supplied data on the use of N2O 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 Producers (AIA, several years [a] and [b]) has 

provided data on the annual production of aerosol cans. It is assumed that all N2O used will 

eventually be released to the atmosphere, therefore the emission factor for anaesthesia is 1 Mg 
109

N2O/Mg product use, while the emission factor used for aerosol cans is 0.025 Mg N2O/Mg product 

use, because the N2O content in aerosol cans is assumed to be 2.5% on average (Co.Da.P., 2005).

N2O emissions have been calculated multiplying activity data, total quantity of N2O used for 

anaesthesia and total aerosol cans, by the related emission factors.

5.4 Uncertainty and time -series consistency

The combined uncertainty in CO2 emissions from solvent use is estimated equal to 58% due to an 

uncertainty by 30% and 50% in activity data and emission factors, respectively. For N2O emissions, 

the uncertainty is estimated equal to 51% due to an uncertainty in activity data of N2O 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, establishing a reduction of the solvent content in products. Figure 

5.1 shows emission trends from 1991 to 2007 with respect to 1990 by sub-sector. 

From 2000, the reduction in N2O emissions is due to a decrease in the anaesthetic use of N2O 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 NMVOC 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 acquired 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, several years).
110

In the framework of the MeditAIRaneo project, ISPRA (ex APAT) commissioned to 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 fattori 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 emission factors for

polyurethane and polystyrene 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 N2O 

emissions. 

For NMVOC, the main modification occurred 3C category where emission factors for the

polyurethane and polystyrene foam processing activities have been modified. These recalculations

did not affect CO2 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 Format2

(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 (CH4) and nitrous oxide (N2O) emissions are estimated and reported. Savannas 

areas (4E) are not present in Italy. Emissions from other sources (4G) have not been estimated. CO2

and F-gas emissions do not occur.

To provide update information 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 hectares, +0.3% more 

than FSS 2005. Between 2000 (Agricultural Census) and 2007, agricultural holdings have decreased 

by 22% (474,000 units). Moreover, at national level, the average size of the agricultural holdings

varied from 7.4 hectare in 2005 to 7.6 hectares in 2007. With respect to 2000 Agricultural Census, 

holdings have gained 1.5 hectares of UAA. The distribution of agricultural holdings 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 holdings 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% of the Italian GHG emissions, 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 2007 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). CH4 and N2O emissions have decreased by 9.3% and 

7.6%, respectively (see Table 6.1). In 2007, the agriculture sector has been the dominant national 

source for CH4 and N2O emissions, sharing 40.9% and 67.8%, respectively. 

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Gg CO2 eq.

CH4 17,216 17,223 16,837 16,076 15,726 15,782 15,540 15,480 15,149 15,619

N2O 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 CO2 eq.)

 

2

 http://unfccc.int/national_reports/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

199019911992199319941995199619971998199920002001200220032004200520062007

CO2 eq. (Gg)

CH4 N20

Figure 6.1 Trend of GHG emissions for the Agriculture sector from 1990 to 2007 (Gg CO2 eq.)

Emission trends per sector

Total GHG emissions and trends by sub category from 1990 to 2007 are presented in Table 6.2

(expressed in Gg. CO2 eq.). CH4 emissions from enteric fermentation (4A) and N2O emissions from 

direct agriculture soils (4D) are the most relevant source categories. In 2007, their individual share

in national GHG emissions without LULUCF was 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 CO2 equivalent] 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, CH4 from enteric fermentation, N2O and CH4 from manure management, and N2O 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). N2O from agricultural soils, both 

direct and indirect emissions, and CH4 enteric fermentation are ranked among the top-10 trend key 

sources with the Tier 2 analysis, including the uncertainty (T2). In the following box, key and nonkey 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 CH4 Emissions from enteric fermentation Key (L, T)

4B CH4 Emissions from manure management Key (L, T2)

4B N2O Emissions from manure management Key (L, T2)

4D1 N2O Direct soil emissions Key (L, T)

4D2 N2O Emissions from animal production Key (L2, T2)

4D3 N2O Indirect soil emissions Key (L, T2)

4C CH4 Rice cultivation Non-key

4F CH4 Emissions from field burning of agriculture residues Non-key

4F N2O 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 characteristics 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 international 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, an internal report describes the procedure for preparing the 

agriculture UNFCCC/CLRTAP national emission inventory (Cóndor, 2009). 

In the last years, results from different research projects have improved the quality of the agriculture 

national inventory (MeditAIRaneo project and convention signed between ISPRA and the Ministry 

for the Environment, Land and Sea). Furthermore, suggestions from the inventory review processes

have been considered (ISPRA, 2009; UNFCCC, 2009). Methodologies 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. Synergies among international conventions and European directives while preparing the 

agriculture inventory 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 every 5 years to prepare a 

more disaggregated inventory by region and province 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 methodologies are used for estimating emission scenarios and 

projections for the years 2010, 2015 and 2020 (MINAMBIENTE, 2007).

6.1.4 Agricultural statistics 

The Italian National Statistical System (SISTAN3) 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 producers and users of agricultural 

statistics (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 through 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 surveys4 (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 – FSS6 (ISTAT, 2008[a]; ISTAT, 2007[a]; ISTAT, 2006[a]). Furthermore, the quality 

reports of the FSS 2005 and FSS 2007 have been obtained from ISTAT (ISTAT, 2008[b]; ISTAT, 

2007[e]). The main agricultural statistics sources, used in the agriculture emission inventory, are 

available 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 occur, and 

emissions from rabbits are estimated and included in “Other” as suggested by IPCC guidelines. In 

2007, CH4 emissions from this category were 525.07 Gg, which represent 70.6% of CH4 emissions 

for the agriculture sector (70.7% in 1990) and 28.9% for national CH4 emissions (29.2% in 1990). 

Methane emissions from this source mainly consist of cattle emissions: dairy cattle (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 1990), 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 same 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 number 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

Sheep 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 (CRPA, 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];OSSLATTE, 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 calculating 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 CH4 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 dairy cattle estimations with the Tier 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 CH4

dairy cattle EF was 113.19 kg CH4 head-1 year-1 with an average milk production of 6,320 kg head-1

year-1 (17.3 kg head-1 day-1). This value is close to the default EF of 109 kg CH4 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 CH4 emission factor for dairy cattle

Non-dairy cattle

For non-dairy cattle, CH4 emissions from enteric fermentation 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 weight (CRPA, 2000; INRA, 1988; NRC, 1984; NRC, 1988; Borgioli, 1981; 

Holter and Young, 1992; Sauvant, 1995). Dry matter intake is converted into 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 equation 4.14 from IPCC (2000). In Table 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 balance 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, CH4 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 head

-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 breeding 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-1day-1)

89.4 197.31 214.78 156.92 171.21 315.50 212.18 212.18 195.26

CH4 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 CH4 emissions, as they are milk fed. Therefore, the average weight for the 

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 CH4 emission factor estimations

National characteristics of Italian breeding are reflected in EFs and are also related to the age 

classification of animals and dry matter intake. In Table 6.6, implied emission factors (IEF) for nondairy cattle are shown. In 2007, the non dairy-cattle EF was 46.13 kg CH4 head-1

 year-1 while IPCC 

default EF is 48 kg CH4 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 others breeding

for 

slaughter breeding for slaughter all breeding

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 59,281 503,041 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 28,133 655,749 708,152 179,488 101,922 410,062 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 59,961 440,845 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 CH4 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 CH4 EF was 73.50 kg CH4 head-1 year-1 and for other buffaloes the value was 56.0 kg CH4 

head-1 year-1. The IEF in the CRF is an average EF for the buffalo category (67.08 kg CH4 head-1 

year-1). 

In the following boxes, parameters used for the Tier 2 approach are presented:

Parameters for the calculation of CH4 cow buffalo emission 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)

Average 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 

CH4 conversion (%) 6 6 

CH4 emission factor (kg head-1 year-1) 21.16 (*) 73.42 

(*) original CH4 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 CH4 head-1 year-1.

Rabbits

Methane 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 CH4 conversion rate has 

been assumed (CRPA, 2004[c]). 

Other livestock categories

A Tier 1 approach, with IPCC default EFs, has been used to estimate CH4 emissions from swine, 

sheep, goats, horses, mules and asses (IPCC, 1997). In Table 6.6, emission 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 CH4 emission factors for enteric fermentation (kg CH4 head-1 year-1)

Table 6.7 Ti me series of number of animals from 1990 to 2007

Year Dairy 

cattle

Nondairy 

cattle

Buffalo 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 10.0 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 66.2 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 7,444,937 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 8,138,309 987,844 277,819 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 7,954,167 945,895 278,471 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 CH4 emissions from enteric fermentation was 28% for annual emissions, 

resulting from the combination of 20% of uncertainty for both activity data and emission factors.

In 2007, livestock CH4 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 CH4 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 

CH4 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

Nondairy 

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 CH4 emissions from enteric fermentation (Gg) 

6.2.4. Source-specific QA/QC and verification

Since 2006 submission, results from the MeditAIRaneo project focusing 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 parameters 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 content 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 (ISTAT 

web site)

Table 6.9 Improvements for the enteric fermentation category according to the QA/QC plan

Table 6.10 Dairy cattle and buffalo CH4 emission factors for the enteric fermentation category (kg head -1year-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, CH4 emissions from manure management were 145.57 Gg, which represents 19.6% of CH4

emissions for the agriculture sector (20.1% in 1990) and 8.0% of national CH4 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 65.7

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). CH4 emissions from swine were 66.42 Gg and from cattle 56.33 Gg; these sub-categories 

represented 45.6% and 38.7% of total CH4 manure management emissions, respectively. 

In 2007, N2O emissions from manure management were 12.25 Gg, which represents 17.6% of total 

N2O emissions for the agriculture sector (16.8% in 1990) and 11.9% of national N2O emissions 

(10.5% in 1990). In 2007, N2O emissions from this source mainly consist of the solid storage source 

(10.79 Gg), which accounts for 88.1% of the N2O manure management source.

Since the 2006 submission, parameters related to the estimation of CH4 and N2O 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 Inter-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 CH4

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 CH4 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 estimating 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 manure 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 monthly 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 (CRPA, 

1993). 

For cattle and buffalo, the estimation of the EF begins with the calculation of the methane emission 

rate (g CH4 m

-3 day-1

), which is obtained from an equation presented for slurry (Husted, 1994) and 

solid manure (Husted, 1993). Then the methane emission rate is transformed to g m-3 month-1. The 

equations used are presented below (CRPA, 2006[a]; CRPA, 1997[a]):

For slurry: 

CH4 (g m-3 day-1) = e (0.68+0.12*average regional monthly temperature) Eq. 6.1

For solid manure:

CH4 (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 (m3 head-1) 

with the average production of slurry and solid manure per livestock category per day (m3 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 been 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 CH4 head-1 month-1) 

are calculated for each month, and 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 CH4 head-1 year-1). Then, to correlate CH4 emission 

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 CH4/kg VS and 4.80 g CH4/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 EFs (kg CH4 head-1 year-1) have been 

calculated 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-1day-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 gCH4/Kg VS • VS production slurry (kg VS head-1 day1) • 365 days Eq. 6.3

EF manure = 4.8 gCH4/Kg VS • VS production slurry (kg VS head-1 day1) • 365 days Eq. 6.4

Livestock category Slurry

(kg CH4 head-1 yr-1)

Solid manure

(kg CH4 head-1 yr-1)

CH4 manure management

EF

(kg CH4 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 cattle (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 CH4 head-1 yr-1)

Since the 2006 submission, the average production of slurry and solid manure per livestock 

category per day (m3 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 distribution 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 8.06 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 6.30

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 management emission factors for cattle and buffalo (kg CH4 head-1 yr-1)

Since the 2006 submission, a reduction of CH4 emissions has been considered for the manure 

management category on account of biogas production. A national census on biogas

production/technology can be found in CRPA (2008) and CRPA/AIEL (2008). Activity data are

collected every year from the National Electric Network - TERNA7 (2009). Further information on 

biogas activity data can be found in Annex 7. 

Reduction of CH4 emissions are assumed for 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 CH4 head-1 year-1 and 7.04 kg CH4 head-1 year-1, respectively. IPCC default 

emissions factors for cool temperature are 14 kg CH4 head-1year-1 and 6 kg CH4 head-1year-1, 

respectively (IPCC, 1997). 

The IEF for non-dairy cattle and buffalo represents 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, EFs and IEFs are presented.

Differences, as mentioned before, are related to the amount of CH4 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 CH4 head-1 yr-1)

IEF(*)

(kg CH4 head-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 from 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 have 

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-specific characteristics.

Livestock category VS country-specific (*)

(kg dm head-1 yr-1)

VS IPCC default

(kg DM head-1 yr-1)

Bo country-specific (*)

(CH4 m3/kg VS)

Bo IPCC default

(CH4 m3/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 CH4 emissions for swine, a country-specific methane emission rate has been 

experimentally determined 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 considered, such as the livestock population, average weight for 

fattening swine and sows, and methane emission rate. Methane emission rates used are 41 normal 

litre CH4/100 kg live weight/day for fattening swine and 47 normal litre CH4/100 kg live

weight/day for sows 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, parameters 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 (classified 

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 CH4 head-1year-1 and for the other swine category was 8.33 

kg CH4 head-1 year-1 (average EF swine of 7.91 kg CH4 head-1year-1). In Table 6.14 the time series

of EFs for the disaggregated swine category (sow and other swine) are shown. The IEF as reported 

in the CRF submission 2009 is 7.16 kg CH4 head-1 year-1. The difference between the EF and the 

IEF for the swine category is due to the reduction in CH4 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 excretion 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 CH4/100 kg live weight)

Emission factor

(kg CH4 head-1

yr-1)

Other swine 84 569,829 13,768 8.33

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 15,783 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 weight 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 considered 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 N2O 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 EFs for cattle, buffalo and swine categories are 

shown. For the other categories, the EFs are as follows:

• rabbits, 0.080 kg CH4 head-1 year-1

• sheep, 0.22 kg CH4 head-1 year-1

• goats, 0.145 kg CH4 head-1 year-1

• horses, 1.48 kg CH4 head-1 year-1 

• mules and asses, 0.84 kg CH4 head-1 year-1

• hen, 0.082 kg CH4 head-1 year-1

• broilers, 0.079 kg CH4 head-1 year-1

• other poultry, 0.079 kg CH4 head-1 year-1
127

(*) These are the EFs used for estimating methane emissions from manure management. They do not include CH4 reduction.

Table 6.14 Average methane EF for manure management (kg CH4 head-1 year-1)

Nitrous oxide emissions

Nitrous 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, the 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 N2O-N/kg N excreted, 0.02 kg 

N2O-N/kg N excreted and 0.02 kg N2O-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 manure 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 N2O are shown. The nitrogen

excretion rate 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 CH4 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 12.12 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 excretion 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 balance 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 rates8 and net nitrogen arriving to the field9 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 Italian 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 categories 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 head-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 national inter-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 swine 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 submission, 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 each breed were considered (CRPA, 

2006[a]; PROINCARNE, 2005). As mentioned before, slurry and solid manure production

parameters were updated since the 2006 submission. These parameters consider characteristics from 

Italian breeding, for slurry and solid manure 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 CH4 and N2O emissions from manure management 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 CH4 emissions from manure management were 11.7% (145.57 Gg CH4) lower 

than in 1990 (164.86 Gg CH4). 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 number of 

cattle. We have to consider that cattle CH4 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, 

CH4 emission trends from manure management are shown. These CH4 emissions considered the 

reduction of CH4 because of biogas recovery.

 

10 ASSONAPA, Associazio ne Nazionale della Pastorizia Ufficio Centrale dei Libri Genealogici e dei Registri Anagrafici.
130

Year Dairy 

cattle

Nondairy 

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 13.82 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 15.25 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 CH4 emissions from manure management (Gg)

In 2007, N2O emissions from manure management were 3.2% (12.25 Gg N2O) lower than in 1990 

(12.65 Gg N2O). The major contribution is given by the solid storage system with 88.1% (in 1990 

with 95.1%). In Table 6.18, N2O 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 N2O 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 agreement 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 Different 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 

CH4 and N2O emissions. A reduction of CH4 occurred because of an update of biogas recovered for 

cattle and swine categories (see section 6.3.2). 

For N2O emissions, the liquid and solid manure production parameters have been updated for the 

years 2004 and 2006.

6.3.6. Source-specific 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 query 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 that 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 by the review process (UNFCCC, 2009) have been 

taken into consideration. For this category, the same N excretion rate is actually applied to the

whole time series, but this figure is the result of a specific inter-regional project on nitrogen

balance, which is not possible to develop annually. Nevertheless, we 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 acquired. At present, 

initial results do not supply reliable information to make a correlation between these parameters but 

we continue on consulting 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 

(bovini maschi ingrasso), fattening heifer (manze ingrasso) and heifer for replacement (manze rimonta); 

(**) values are variable for the time series.

Livestock 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 66.8

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 (manze 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 rabbits (fattrici) 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 CH4 emissions are estimated, other GHGs do not occur; N2O 

from fertilisation during cultivation has been estimated and reported in “Agricultural soils” under 

direct soil emissions - synthetic fertilizers. In 2007, CH4 emissions from rice cultivation were 72.52 

Gg, which represents 9.8 % of CH4 emissions for the agriculture sector (9.1% in 1990) and 4.0% for 

national CH4 emissions (3.7% in 1990). 

In Italy, CH4 emissions from rice cultivation 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 CH4 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 CH4 emissions and rice cultivation (Wassmann, 2005), a detailed 

methodology has been implemented. New activity data and parameters have been used for the 

estimation of CH4 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. Different national experts from the rice

cultivation sector were also contacted11. 

The quality of the Italian rice emission inventory has been verified with the DNDC12 model. Initial 

results have found a high correspondence between the EFs used for the Italian inventory and those 

simulated with DNDC model (Leip and Bocchi, 2007). 

6.4.2. Methodological issues

For the estimation of CH4 emissions from rice cultivation a detailed methodology has been

implemented following the IPCC guidelines (IPCC, 2006). We have considered country-specific 

circumstances, therefore, we have used an adjusted integrated emission factor (kg CH4 m

-2

day-1), 

cultivation period of rice (days) and annual harvested area (ha) cultivated under specific conditions. 

Information of the cultivated 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 

these data are published in the ENR web site and also provided to ISTAT. In the following box, 

information related to the collection of data is shown. 

Parameters used for the calculation of CH4 emissions from rice cultivation 

Parameters Reference

Cultivated surface with “dry -seeded” technique (%) Centro Ricerche sul Riso, 2007

Cultivated 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 CH4 m-2 d-1) Leip et al., 2002; Schutz 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); Antonino 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; Tossato & 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 & Giardini, 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 wetseeded (*)

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

Wetseeded 

“classic

”

1oaeration -

AR

2o aerationAA3o final 

aeration

15 April

Flooding 

and wetseeded (*)

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 

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. In some 

cases, between April 

and May, even 3 

aeration periods are 

practised.

IPCC classification:

Intermittently 

flooded – multiple 

aeration 

Wetseeded

“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 

aeration

Dryseeded 

with 

delay 

floodin

g

1o aerationAA2o 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 for 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 order 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, 

2004; 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 processes (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 topdressed 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 others 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, but 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 been considered for understanding fertilizer and crop residues management

(Zavattaro et al., 2004).

Methane emission factor

An analysis on recent and past literature, for the CH4 daily emission factor (kg CH4 m-2 d-1), has 

been done. Different scientific publications related to the CH4 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 CH4 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 CH4 emissions 24-31% 

lower than fields planted with cultivar Roma. Marik et al. have published detailed information on 

agronomic practices (fertilized fields) related to measurements of CH4 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 CH4 emission factors 

for a particular agronomic practice, which has been presented in Table 6.21, the so called dryseeded with delay flooding (semina interrata a file). The dry–seeded technique could bring

interesting benefits in emission reduction, since experimentally it has been determined lower 

emission rates compared with a normal practice.

The estimation of CH4 emissions for the rice cultivation category considers an irrigated regime, 

which includes intermittently flooded with single aeration and multiple aeration regimes. The CH4

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 rice 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 CH4 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 CH4 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 CH4 m

-2

 d-1) 0.18 0.21 0.21

Days of cultivation (days) 138 156 1556

Seasonal EF (g CH4 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 CH4 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, CH4 emissions from rice cultivation were 2.5% (72.52 Gg CH4) lower than in 1990 (74.39 

Gg CH4). In Italy, the driving force of CH4 emissions from rice cultivation is the harvest area and 

the percentage of single aerated surface. Methane emissions 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, CH4 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 

cultivation 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 Sustainability - 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 plan
137

6.4.5. Source-specific recalculations

In Table 6.24, CH4 emission from 2007 and 2008 submissions are presented. Period of cultivation 

of rice varieties have been updated for the years 2003-2006. For the years 2004-2006 updated 

information on rice production has been provided (ENR, 2009).

Year Harvested area

(10 9m

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 CH4 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 uncertainty. 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 application 

(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; Lupotto 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, N2O emissions from agricultural soils were 57.39 Gg, representing 82.4% of emissions for 

the agriculture sector (83.2% in 1990) and 55.9% for national N2O emissions (52.0% in 1990). N2O 

emissions from this source mainly consist of direct soil emissions with 28.04 Gg and indirect soil 

emissions with 24.28 Gg. 

Direct N2O emissions from agricultural soils are key sources at level and trend assessment, both 

with Tier 1 and Tier 2 approaches. Indirect N2O 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 soil, 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 category 

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 UNFCCC inventory, specifically for the estimation of

FRACGASM and FRACGASF parameters, used for calculating FAM and FSN. 

6.5.2. Methodological issues

Methodologies used for estimating N2O emissions from “Agricultural soils” follow the IPCC

approach. Emission 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

Data 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 surface (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 type CESTAAT, 1988

Crop residue production (t dry matter ha-1yr-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 N2O direct soil emissions, the IPCC approach has been followed, and some

modifications have been included because of country-specific peculiarities (IPCC, 2000; IPCC, 

1997). N2O-N emissions have been estimated from the amount of synthetic fertilizers (FSN), animal 

waste applied to soil (FAM), crop residues (FCR), N-fixing crops (FBN) and cultivation of histosols 

(FOS). Then default IPCC emission factors (IPCC, 2000) have been applied. Afterwards N2O-N 

emissions were converted to N2O emissions, multiplying by the 44/28 coefficient. Animal 

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 FRACLEACH 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 fertilizers (FSN)

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 (FSN) has been obtained by 

multiplying the total use of fertilizer by (1- FRACGASF). FRACGASF parameter has been estimated 

for the whole time series, following the IPCC definition where the total N-NH3 and N-NOx 

emissions from fertilizers are divided by the total nitrogen content of fertilizers. N2O emissions for 

synthetic fertilizers have been obtained multiplying FSN by the emission factor 0.0125 kg N-N2O/kg 

N (IPCC, 1997). In 2007, the total use of synthetic fertilizers was 760,063 t N, while FSN parameter 

was 869,044 t N (see Table 6.27). In the 2007 submission, a specification 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. 

Table 6.25 Total use of synthetic fertilizer in 2007 (t N yr-1)

Animal waste applied to soil (FAM)

The manure nitrogen corrected for NH3 and NOx emissions, excluding manure produced during 

grazing (kg N yr-1), has been calculated with the IPCC methodology (IPCC, 1997), using countryspecific nitrogen excretion rates (CRPA, 2006[a]; GU, 2006; Xiccato et al., 2005). A countryspecific FRACGASM parameter has been estimated and used for the calculation of the animal waste 

applied to soil. In the 2009 submission FRACGASM(direct) and FRAC GASM(indirect) have been

reported (see Table 6.27). The estimation has followed the IPCC definition; therefore, the NH3 and 

NOx emissions from animal manure have been divided by the total nitrogen excreted. The FAM (t yr1

) value has been estimated by summing the FAM for each livestock category; then emissions have 

been calculated with emission factor 0.0125 kg N-N2O/kgN (IPCC, 1997). In 2007, FAM parameter 

was 447,969 t N. In the 2009 submission the time series of FAM has been updated due to a revision 

of CLRTAP-NH3 agriculture inventory (see recalculation section 6.5.5). 

Type 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 nitrate < 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 

ammoniacale)

- - 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 (FBN)

Nitrogen input from N-fixing crops (FBN, 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 forage. FBN 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 surface from N-fixing species 

(ha yr-1) and nitrogen fixed by each species (kg N ha-1 yr-1) are presented. In 2007, FBN parameter 

was 160,757 t N (time series Table 6.27).

Crop residues (FCR)

For the estimation of nitrogen input from crop residues (FCR), a country-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 of 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 and 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- FRACBURN, where FRACBURN is the fraction of crop residue that is 

burned rather than left on 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 FCR parameter has been obtained by adding the nitrogen content of cultivars crop 

residues. In 2007, FCR parameter was 124,377 t N (see Table 6.27). Emissions are calculated with 

emission factor 0.0125 kg N-N2O/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 ha1

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) 58 521,169 195,191 252,647 152,331 176,134 130,335

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 surface and nitrogen fixed by each variety
141

Cultivation of histosols (Fos) 

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-N2O ha-1 yr-1, as suggested 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 data for Emilia Romagna region, where this type of 

soil is most prevalent.

(*) FRACGASM(indirect) is reported in the Table4.Ds2 as “other fractions”

Table 6.27 Parameters used for the estimation of direct and indirect N2O emissions

Animal production

As mentioned in section 6.3.2, when estimating N2O emissions from manure 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-1yr-1) used for estimations 

are presented. Nitrous oxide emissions are estimated with the total nitrogen excreted from grazing 

(include all livestock categories), number of animals, and an EF of 0.02 kg N2O-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 FSN

(t N)

FAM

(t N)

FBN

(t N)

FCR

(t N)

Fos

(ha) FRACGASF

FRACGASM

(direct)

FRACGASM

(indirect) 

(*)

1990 691,723 473,804 254,654 147,541 9,000 0.087 0.319 0.328

1991 764,911 473,328 240,032 149,041 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 726,343 453,400 191,018 142,216 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 716,405 469,741 191,722 150,228 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 0.292 0.301
142

The estimation of N2O emissions due to atmospheric deposition of NH3 and NOx has followed the 

IPCC approach (IPCC, 1997). Parameters which have been used are: total use of synthetic fertilizer, 

t N yr-1, FRACGASF emission factor, total N excreted by livestock (kg head-1yr-1), FRAC GASM

emission factor (see Table 6.27) and emission factor 0.01 kg N2O-N per kg NH3-N + NOx-N 

emitted (IPCC, 2000; IPCC, 1997). 

The estimation of N2O 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), FRACLEACH emission factor 0.3 

N/kg nitrogen of fertilizer or manure and the emission factor 0.025 Kg N2O-N per kg nitrogen 

leaching/run-off (IPCC, 2000; IPCC, 1997). As mentioned above, the FRACLEACH IPCC default 

value has been compared with the country specific FRACLEACH (ADBPO, 2001; ADBPO, 1994).

In the 2009 submission the time series of for Atmospheric deposition has been updated due to a 

revision of CLRTAP-NH3 agriculture inventory (see recalculation section 6.5.5). 

6.5.3. Uncertainty and time -series consistency

Uncertainty for N2O 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 N2O emission are 

reported.

Table 6.28 Nitrous oxide emission trends from Agricultural soils (Gg)

In 2007, N2O emissions from agricultural soils were 8.5% (57.39 Gg N2O) lower than in 1990 

(62.69 Gg N2O). In 2007, major contributions come from direct soil emissions (28.04 Gg) and 

indirect soil emissions (24.28 Gg). Indirect N2O emissions from nitrogen leaching and run-off subcategory has the highest individual contribution with respect to total 4D N2O emissions (19.10 Gg 

N2O; 33%). N2O 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

2003 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 fertilizers and the 

trend of livestock number.

In 2007, the second individual source with respect to total N2O emissions was 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 N2O 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 N2O could be identified as outlier (see Table 6.30).

Direct N2O emissions Indirect N2O 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 with 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 could also 

derive from different products classification. In Table 6.31, activity data used for N2O estimations 

have been provided. In Table 6.32, the QA/QC plan for this category is presented. 

6.5.5. Source-specific recalculations

Updates of N2O emissions occurred due to the revision of NH3 estimates for the CLRTAP-NH3

agriculture inventory. Emission factors for cattle and buffalo for estimating N-NH3 emissions from 

the spreading phase have been revised. Consequently, the fraction of livestock nitrogen excretion 

that volatilizes as NH3 and NOx from the CRLTAP-NH3 inventory has changed. This update is 

linked to the UNFCCC inventory, then N2O emissions, 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 6.31 Cultivated surface, crop production and total residue production time series

Year of 

submission 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 1,945,347 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 

submission

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 project for the use of slow 

release fertilizers.

Table 6.32 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, CH4 emissions from this source were 0.61 Gg, which represents 

only 0.082% of emissions for the agriculture sector. N2O 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 residues. 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 summarised 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 (CH4, N20) 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 category (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” burnable residues13 (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 oxidized15 (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 from stubble burning release in air16 (t C), calculated with the amount of 

“fixed” dry residue oxidized and the fraction of carbon from the dry matter of residues.

e) C-CH4 from stubble burning17 (t C-CH4), calculated with the amount of carbon from stubble 

burning release in air and default emissions rate for C-CH4, equal to 0.005 (IPCC, 1997).

In 2007, final CH4 emissions from on field burning of agriculture residues (0.61 Gg CH4) have been 

estimated multiplying the C-CH4 value (0.459 Gg C-CH4) by the coefficient 16/12. In Table 6.34, 

parameters used for the estimation of CH4 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" (tonnellate 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 1,272,952 213,992

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 10,427,930 429,153 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 CH4 emissions from agriculture residues in 2007

For estimating N2O 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 air18 (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-N2O from stubble burning19 (t N-N2O), calculated with the amount of nitrogen from stubble 

burning release in air and the default emissions rate for N- N2O, equal to 0.007 (IPCC, 1997).

In 2007, final N2O emissions from on field burning of agriculture residues (0.013 Gg N2O) are 

estimated by multiplying the N-N2O value (0.008 Gg N) with the coefficient 44/28. Table 6.35 

shows parameters for the estimation of CH4 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 CH4 and N2O emissions from field burning of agriculture residues are estimated to 

be 54% as a result of 50% and 20% for activity data and emission factor, respectively. In 2007, CH4

 

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” residues

(t 1000 dry 

matter)

Amount of “fixed” 

dry residues 

oxidized 

(t 1000 dry 

matter)

Amount of 

carbon from 

stubble 

burning 

(t 1000 C)

C-CH4 from stubble 

burning 

(t C-CH4)

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-N2O from stubble 

burning

(t N-N2O)

Wheat (frumento) 92 0.030 0.005 0.443 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

TOTAL 208 1.188 8.3
148

emissions from field burning of agriculture residues were 0.61 Gg CH4 and N2O emissions were 

0.013 Gg N2O (see Table 6.36). Variation in emissions trend is related to cereal production trends. 

Table 6.36 CH4 and N2O 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 provided 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 years 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 CH4 (Gg) N2O (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: LAND USE, LAND USE CHANGE AND FORESTRY [CRF SECTOR 5]

7.1 Overview of sector

CO2 emissions and removals occur as a result of changes in land-use and from forests. The sector is 

responsible for 70.9 Mt of CO2 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.

CO2 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 Settlements 

Gg CO2 eq.

removals

emissions

Figure 7.1 Greenhouse gas removals and emissions in LULUCF sector in 2007 [Gg CO2 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

CO2 -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

CH4 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

N2O 14.50 199.00 8.83 5.60 3.14 6.59 3.51 3.47 301.62 19.97

A. Forest Land 14.50 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
151

CO2 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

199019911992199319941995199619971998199920002001200220032004200520062007

Gg CO2

removals

emissions

Figure 7.2 CO2 removals and emissions in LULUCF sector in the period 1990-2007 [Gg CO2]

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 Table 7.2. CO2 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 settlements have been 

identified as key sources or sinks. Concerning CH4 or N2O emissions, no categories have

resulted as a key source. 

gas categories 2007

5.A.1 CO2 Forest land remaining forest land key (L, T)

5.A.2 CO2 Land converted to forest land key (L2, T2)

5.B.1 CO2 Cropland remaining cropland key (L, T)

5.B.2 CO2 Land converted to cropland Non-key

5.C.1 CO2 Grassland remaining Grassland Non-key

5.C.2 CO2 Land converted to Grassland key (L, T)

5.D CO2 Wetlands Non-key

5.E CO2 Settlements remaining Settlements Non-key

5.E CO2 Land converted to Settlements key (L,T2)

5.A.1 CH4 Forest land remaining forest land Non-key

5.A.1 N2O Forest land remaining forest land Non-key

5.B.2 N2O Land converted to cropland Non-key

Table 7.2 Key categories identification 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 aboveground 

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 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). This loss could be 

attributed to the response of the 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, Post 

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 change 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 landuse change, and it is applied only once, for the year in which it is determined. 

In the following Table 7.3, the land use 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

1989

1990

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 30.134

1991

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 30.134

1992

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

1992

1993 Final

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

1993

1994 Final

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 30.134

1995

1994

Final

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 30.134

1996

1995
154

Final

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 30.134

1997

1996

Final

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 30.134

1998

1997

Final

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 30.134

1999

1998

Final

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 30.134

2000

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

2000

2001
155

Final

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

2001

2002 Final

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

2002

2003 Final

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 30.134

2004

2003

Final

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

2004

2005
156

Final

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

2005

2006 Final

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

2006

2007

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, CO2 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 organic 

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 CO2 2007 LULUCF emissions and removals, while the 

mean forest land removals for the years 1990-2007 is 81% of total mean CO2 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 2007 forest land 

CO2 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 Percentage contribution of carbon pools to forest land category, in 1990-2007

CO2 removals from forest land remaining forest land have identified as key category (sinks) in 

level and in trend assessment (Tier 1); CO2 emissions and removals from land converting to 

forest land have identified as key category in level and in trend assessment (Tier 2);

Concerning the CH4 or N2O emissions, neither forest land nor land converting to forest land 

have resulted as a key source.
157

7.2.2 Methodological issues

Forest Land 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 definition: 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 forestrelated statistical data: input data for the forest area, per region and inventory typologies20, 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 Experimental 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 hectares (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, was followed by a ground survey, in order to assess 

the forest use, and 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 National 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 stock volume is the 1985 growing stock data (MAF/ISAFA, 1988);

2. starting from 1985, for each year, the current increment per hectare [m3 ha-1] is 

computed with the derivative Richards function21, for each forest typology by the

Italian yield tables collection;

3. starting from 1986, for each year the growing stock per hectare [m3 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.

 

20The inventory typologies 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 oak, 

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 [m3

] and increment [m3 y

-1

] 

obtained by the data of the national 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.

1 0y

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 y0 is derived from the data of age and volume reported in the yield tables: more precisely y0 has the value of the 

volume for the age 1. After choosing the function, it is fitted to the measurements by non-linear regression. 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

V I H F M D

v

−−−−+

=

−1

where: 

( ) −− 11 = ⋅

i Aii

I f v

in which the current increment is estimated year by year applying the derivative Richards 

function and

 is the Richards function reported above

A is the total area referred to a specific forest typology for the previous year

 is the previous year growing stock volu me per hectare

A is the total area referred to a specific forest typology for the current year

D is the annual rate of drain and grazing for the protective forest 

Mi is the annual rate of mortality 

F is the total amount of burned growing stock for the current year

H is the total amount of harvested growing stock for the current year

I is the total current increment of growing stock for the current year

V is the total previous year growing stock volu me

 is the volume per hectare of growing stock for the current year

i-1

1

i

i

i

i

i-1

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, 2003). 

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 m3, are 

disaggregated at NUTS2 level, in sectoral statistics (ISTAT, several years [a]) or at NUTS1 

level for coppices and high forests in national statistics (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 fraction 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 been 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 and 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 CO2 released, for 

different categories (stands, coppices, plantations, protective forests) are shown.

Year burned growing stock

m

3

CO2 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 CO2 released for the years 1990-2007
160

Once estimated the growing stock, the amount of aboveground tree biomass (dry matter), 

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 the 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:

Aboveground tree biomass (d.m.) =GS ⋅ BEF ⋅WBD ⋅ A

where:

GS = volume of growing stock (MATT/ISAFA, 1988) [m3 ha1]

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

] (Giordano, 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 increment per hectare [m3 ha1 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 [m3 ha-1] is computed, from 

the previous year 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:

Aboveground tree biomass = GS ⋅ BEF ⋅WBD⋅ A

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 0.53

stands

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 0.43

coppices

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 0.48

plantations

partial total 1.36 0.40

rupicolous forest 1.44 0.52

riparian forest 1.39 0.41

shrublands 1.49 0.63

protective 

partial total 1.46 0.56

Total 1.38 0.53

Table 7.6 Biomass 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:

Belowground biomass (d.m.) = GS⋅WBD⋅R⋅ A

where:

GS = volume of growing stock [m3 ha-1]

R = Root/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 typology

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 oak 0.24 0.69

other oaks 0.20 0.67

other broadleaves 0.24 0.53

stands

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 0.43

coppices

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 0.48

plantations

partial total 0.25 0.40

rupicolous forest 0.42 0.52

riparian forest 0.23 0.41

Shrublands 0.62 0.63

protective

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 living biomass has been calculated according to the GPG for 

LULUCF (IPCC, 2003), from the aboveground tree biomass and belowground biomass:

ΔC Living biomass = ΔC Aboveground biomass+ ΔC Belowground biomass

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 (DCF10) 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 dead mass [t] is:

Deadmass (d.m.) =GS ⋅ BEF ⋅WBD⋅DCF ⋅ A

where:
163

GS = volume of growing stock [m3ha-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 which 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 CANIF22 (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 forestry 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 at stand level, the annual rate of accumulation of litter C is 0.0723 t C ha-1yr-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-processes/research/Schulze_Euro_CANIF.html

Inventory typology Relation litter – aboveground C per 

ha 

norway spruce y = . ⋅ x + .5045106590

silver fir y = . ⋅ x + .5045106590

larches y = . ⋅ x + .5045106590

mountain pines y = . ⋅ x + .5045106590

mediterranean pines y = . ⋅ x + .5045106590

other conifers y = . ⋅ x + .5045106590

european beech y −= . ⋅ x + .3665902990

turkey oak y −= . ⋅ x + .3665902990

other oaks y −= . ⋅ x + .3665902990

stands

other broadleaves y −= . ⋅ x + .3665902990

european beech y −= . ⋅ x + .3665902990

sweet chestnut y −= . ⋅ x + .3665902990

hornbeams y −= . ⋅ x + .3665902990

other oaks y −= . ⋅ x + .3665902990

turkey oak y −= . ⋅ x + .3665902990

evergreen oaks y −= . ⋅ x + .3665902990

other broadleaves y −= . ⋅ x + .3665902990

coppices

conifers y = . ⋅ x + .5045106590

eucalyptuses coppices y −= . ⋅ x + .3665902990

other broadleaves 

coppices

y −= . ⋅ x + .3665902990

poplars stands y −= . ⋅ x + .3665902990

other broadleaves stands y −= . ⋅ x + .3665902990

conifers stands y = . ⋅ x + .5045106590

plantations

others y −= . ⋅ x+ .3285701650

rupicolous forest y −= . ⋅ x+ .3285701650

riparian forest y −= . ⋅ x + .3665902990

protective

shrublands y −= . ⋅ x + .3665902990
164

The dead organic matter carbon pool is defined, in the GPG, as the sum of the dead wood and 

the litter. 

ΔC Dead OrganicMatter = ΔC dead mass+ ΔC litter

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. 

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 

aboveground 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 converting to forest 

land has been estimated and reported.

Inventory typology Relation soil – aboveground C per ha 

norway spruce y = 0.4041⋅ x + 57.874

silver fir y = 0.4041⋅ x + 57.874

larches y = 0.4041⋅ x + 57.874

mountain pines y = 0.4041⋅ x + 57.874

mediterranean pines y = 0.4041⋅ x + 57.874

other conifers y = 0.4041⋅ x + 57.874

european beech = . ⋅ xy + .0746598430

turkey oak = . ⋅ xy + .0746598430

other oaks = . ⋅ xy + .0746598430

stands

other broadleaves = . ⋅ xy + .0746598430

european beech y = 0.3922 ⋅ x + 65.356

sweet chestnut y = 0.3922 ⋅ x + 65.356

hornbeams y = 0.3922 ⋅ x + 65.356

other oaks y = 0.3922 ⋅ x + 65.356

turkey oak y = 0.3922 ⋅ x + 65.356

evergreen oaks y = 0.3922 ⋅ x + 65.356

other broadleaves y = 0.3922 ⋅ x + 65.356

coppices

conifers y = . ⋅ x + .8745740410

eucalyptuses coppices y = 0.3922 ⋅ x + 65.356

other broadleaves 

coppices

y = 0.3922 ⋅ x + 65.356

poplars stands = . ⋅ xy + .0746598430

other broadleaves stands = . ⋅ xy + .0746598430

conifers stands y = . ⋅ x + .8745740410

plantations

others y = . ⋅ x + .6383376470

rupicolous forest y = . ⋅ x + .6383376470

riparian forest = . ⋅ xy + .0746598430

protective

shrublands y = 0.3922 ⋅ x + 65.356
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 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, 

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 biomass, 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 -154.21 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 

CO2 emissions due to wildfires in forest land remaining forest land are included in Table 5.A.1, 

carbon stocks change in living biomass, decrease.

Values of burned growing stocks and respective CO2 released, for different categories (stands, 

coppices, plantations, protective forests), are reported in the previous Table 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 year 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 VAB V

S

V

S

E

L

V

L

E

D

V

D

E

BG VBG EAG VAG E

E

+ +++

















+ ⋅

















+ ⋅

















+ ⋅

















+ ⋅

















⋅

=

where the terms AG1985V , BG1985V , D1985V , L1985V e S1985V stand for the 1985 carbon stocks of the 

five pools, aboveground, belowground, dead mass, litter and soil, while, with the letter E, the 

related uncertainties have been indicated. In Table 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 associated to the growing stock data given by 

the first National Forest Inventory, BEF1

E points to uncertainty related to biomass expansion 

factors for the aboveground biomass, BD E is the basic density uncertainty and the 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 BEF2

E stands for the

uncertainty related to the expansion 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 (IPCC, 2003), 

while LS1985

E and SS1985E are the uncertainties related to the litter and soil carbon stock data 

deduced from the CANIF Project23 data and the CONECOFOR Programme (Corpo Forestale, 

2005) respectively. Finally the terms LR1985

E and SR1985E 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 the 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 EBEF E NFI EBG E = +++

Dead mass 2

1985

2

1985 1985 DEF E

AG ED

E = +

Litter 2

5

2

1985 1985 LR E

LS EL

E = +

Soil 2

5

2

1985 1985 SR E

SS ES

E = +
168

Aboveground biomass VAG 137.8

Belowground biomass VBG 31.5

Dead mass VD 20.8

Litter VL 27.4

Carbon stocks

t CO2 eq. ha

-1

Soil VS 264.7

Growing stock ENFI 3.2%

Current increment (Richards)24 ENFI 51.6%

Harvest25 EH 30%

Fire26 EF 30%

Drain and grazing ED 30%

Mortality EM 30%

BEF EBEF1 30%

R EBEF2 30%

DCF EDEF 30%

Litter (stock + regression) EL 161%

Soil (stock + regression) ES 152%

Basic Density EBD 30%

Uncertainty

C Conversion Factor ECF 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 EAG 42.59%

Belowground biomass EBG 42.59%

Dead mass ED 52.10%

Litter EL 161.22%

Soil ES 152.05%

Overall uncertainty E1985 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 years 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 EBEF E

V DVV HV

I

V NFI V

VEVEVE HV HE

I

V

I

E NFI V NFI E

AG E

F MOR

FF DD MM

+++

























−+−+−+−++

⋅ + ⋅ + ⋅ + ⋅ + ⋅ + ⋅

=

The uncertainties related to the carbon pools and the overall uncertainty for 1986 are shown in 

Table 7.14: 

Aboveground biomass EAG 42.67%

Belowground biomass EBG 42.67%

Dead mass ED 52.16%

Litter EL 161.22%

Soil ES 152.05%

Overall uncertainty E1986 84.75%

Table 7.14 Uncertainties 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 reported. 

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 with 

the following relation:

( ) ( )

1990 2006

2

2005 2006

2

1990 1990

20061990

VV

VE VE

E

+

⋅ + ⋅

=

−

where the terms V stands for the growing stock [m

3

 ha-1 CO2 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%. The 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 

methodology, 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 database27, ISTAT data28) has been made. Data 

entries have been checked several times during the compilation of the inventory; particular 

attention has been focussed 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 INEMAR29, 

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, in seven of the 20 Italian regions 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). The 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 Figure 

7.4. As well as soils carbon pools estimates, the different SOC reference level used 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 FAO, 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 Difference 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 the 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 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 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 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 indepth analysis on the information 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 georeferenced data should assure the 

estimates of burned areas in the different land uses. The fraction of CO2 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 expert panels, ISPRA participates 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 producers 

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 communication.
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 carbon stocks inventories, with a 

special focus on the Italian territory.

7.3 Cropland (5B)

7.3.1 Source category description

Under this category, CO2 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 CO2 LULUCF emissions and removals, in particular the 

living biomass removals represent 97%, while the emissions from soils stand for 3% of total 

cropland CO2 emissions and removals.

Removals are almost entirely due to cropland remaining cropland, while only land converting to 

cropland category is responsible for emissions.

CO2 emissions and removals from cropland remaining cropland have been identified as key

category in level and in trend assessment (Tier 1). Concerning N2O 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 change 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 cropland 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 in 

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, harvest/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 crops 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 basic 

assumption of Tier 1, since the croplands are abandoned or consociated with annual crops. The 

biomass clearing is relatively unusual. Biomass carbon losses have been estimated, taking into 

account the pruning of woody cropland, using the same country-specific 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.

According 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 wasn’t 

possible to point out different sets of relative stock change factors [FLU (land use), FMG

(management), FI (input 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.
173

No CO2 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 carbon 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 reported 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 LULUCF (2003).

CO2 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). 

N2O emissions arising from the conversion of land to cropland have been also estimated, and 

reported in Table 5(III) - N2O 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 planted 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 stocks 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 national expert 

judgement, it has been assumed that the 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 few 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 DC 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

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. Initial land use 

soil carbon stock [SOC(0-T)] and soil carbon stock in the inventory year [SOC0] 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 replaces the previous value (44.5 tC/ha) fixed for 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 

cultivations such as vineyards and olive orchards (Triberti et al 2008, Ceccanti et al 2008, 

Monaco et al 2008, Martiniello 2007, Lugato and Berti 2008, Francaviglia 2006, IPLA 2007, 

ERSAF 2008, Del Gardo et al 2003, Puglisi et al, 2008, Lagomarsino et al 2009, Perucci 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):

( ) ii i

K

i

Td = ∑ i P D ⋅⋅⋅ − S

=

1

1

r

where Tdis the overall soil carbon stock (gcm-2) and, for each K layer of the soil profile, riis the 

soil bulk density (gcm-3), Pi is the soil carbon content (gCg-1), Di is the layer thickness (cm), 

Siis 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, r0 average bulk 

density of organic matter (0.224 gcm-3) and rm 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 (FLU, FMG, FI) 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 proportional relevance of the indagated area (ha) over the entire 

Italian 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 conversion 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 CO2 emissions from organic 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 inventory 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 soils. Notable deviations 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 change 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 harvest/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, CO2 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 CO2 removals in 2007, with 1,243 Gg of CO2

emissions due to living biomass pool and 9,003 Gg of CO2 removals due the soils pool. In the 

period 1990-2007 mean grassland emissions share 3.8% of absolute CO2 LULUCF emissions 

and removals, in particular the living biomass emissions represent 12%, while the removals 

from soils stand for 88% of absolute total grassland CO2 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 setaside since 1970 have been considered as grasslands. To assess change in carbon in grassland 

biomass, 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 practice 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 [FLU (land use), FMG (management), FI (input 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 CO2 emissions from organic soils or from application of carbonate containing lime 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 organic 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 the 

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 carbon 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 transition, 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 assumed 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 Tier 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 to 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 DCgrowth DC

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 mineral 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 [SOC0] for the grassland 

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 replaces the previous value (44.5 tC/ha coming from an expert judgement 

reported also for cropland) and makes 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, Masciandaro 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):

( ) ii i

K

i

Td = ∑ i P D ⋅⋅⋅ − S

=

1

1

r

where Tdis the overall soil carbon stock (gcm-2) and, for each K layer of the soil profile, riis the 

soil bulk density (gcm-3), Pi is the soil carbon content (gCg-1), Di is the layer thickness (cm), 

Siis 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
179

where r soil bulk density (gcm-3), X, percent by weight of organic matter, r0 average bulk 

density of organic matter (0.224 gcm-3) and rm 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 (FLU, FMG, FI) 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 proportional relevance of the indagated area (ha) over the entire 

Italian territory.

With the stock change factors, the grassland soil carbon stock [t C] for the inventory year 

[SOC0] 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

LULUCF Good Practice Guidance (IPCC, 2003). Remarkable deviations 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 1990-2006. 
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 converting 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 Afforestation/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 data 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 Wetlands30 have been included in this category (MAMB, 1992). 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 CO2, CH4 and N2O 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; CO2 emissions, from living biomass and soil, from land converted in settlements have 

been also reported. In the period 1990-2007 mean settlements emissions share 3.1% of absolute 

CO2 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 living 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 Cover31 maps, 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 transition 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 equation 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 minus 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 zero. 

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 carbon 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 factors 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 settlements 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 -10.82 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

Changes 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 converted to 

settlements are reported.

annual crops to settlements perennial crops to settlements 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. Significant deviations from the precedent 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 planned 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 information, 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, CO2 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 N2O emissions from N fertilization (5(I))

N2O 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 N2O emissions from drainage of soils (5(II))

As regards to N2O 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 N2O emissions from disturbance associated with land-use conversion to Cropland

(5(III))

7.10.1 Source category description

Under this category, N2O emissions from disturbance of soils associated with land-use 

conversion to cropland are reported, according to the GPG (IPCC, 2003). N2O emissions from 

cropland remaining 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

N2O emissions from land use conversions are derived from mineralization 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 abovementioned, 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 N2O 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 N2O-N/kg N for the C/N ratio and for calculating N2O 

emissions from N in the soil respectively, N2O emissions have been estimated. 

In Table 7.24 N2O emissions resulting from the disturbance associated with land-use conversion 

to cropland are reported:

Year Conversion Area Carbon stock Nnet-min N2O net-min -N N2O emissions

k ha Gg C kt N kt N2O-N Gg N20 

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 N2O emissions from land-use conversion to cropland

7.10.4 Source-specific 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 converting 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, CH4 and N2O 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]). 

CO2 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.

7.12.2 Methodological issues 

In Italy, in consideration of national regulations, forest fires do not result in changes in land use; 

therefore conversion of forest and grassland does not take place. Anyway CO2 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 reduction due to forest 

fires, and subsequent emissions, have been estimated following the methodology reported in

paragraph 7.2.2.

IPCC method was followed for CH4 and N2O emissions, multiplying the amount of C released 

from 1990 to 2007, calculated on the basis of regional parameters (Bovio, 1996), by the

emission factors suggested in the IPCC guidelines (IPCC, 1997).

In Table 7.25 CH4 and N2O emissions resulting from biomass burning are reported:

CH4 emissions N2O 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 CH4 and N2O 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 overlapping 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 CO2 emissions. Activities planned in the framework of the

National 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 CH4 and N2O emissions from forest fires between the previous and the current 

submission 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 four 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 rank 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, CH4 and NMVOC emissions from compost production are reported.

Emissions from methane recovered, used for energy purposes, in landfills and wastewater

treatment plants are estimated and reported under category 1A4a.

GAS/SUBSOURCE 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CO2 (Gg) 

6C. Waste incineration 536.90 483.02 201.57 222.26 244.97 215.76 199.23 244.69 267.49 270.17

CH4 (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

N2O (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 incineration 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. Methane 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 emissions 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 CH4 Emissions from solid waste disposal sites Key (L, T2)

6B CH4 Emissions from wastewater handling Key (L2, T2)

6B N2O Emissions from wastewater handling Key (L2, T2)

6C CO2 Emissions from waste incineration Non-key

6C CH4 Emissions from waste incineration Non-key

6C N2O Emissions from waste incineration Non-key

6D CH4 Emissions from other waste (compost production) 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 CH4, both in terms of 

level and trend. The share of CH4 emissions in the national methane total 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 nonmethane 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 

amount 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 waste 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 municipal 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 last 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 recyclable 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 

(Decree 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 waste 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 the 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 waste 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 forced 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 disposal 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 Carbon (DOC);

3) fraction of DOC dissimilated (DOCF);

4) fraction of methane in landfill gas (F);

5) oxidation factor (OX);

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 gradually 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.

Municipal 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 represented by the 

data reported through the Uniform Statement Format (MUD), complemented by that provided 

by regional permits, provincial communications and by registrations in the national register of 

companies involved in waste management activities.

These figures are elaborated and published by ISPRA yearly since 1999: the yearbooks report

waste production data, as well as data concerning landfilling, incineration, composting and 

generally waste life-cycle data (ANPA-ONR, several years; APAT-ONR, several 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 1975 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 reconstructed 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 policies 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 incineration 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

100.0

19731974197519761977197819791980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007

Figure 8.2 Percentage of MSW disposal 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 Disposed 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 Disposed 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 incineration plants. 

The percentage of each treatment (landfilling, soil spreading, composting, incinerating and

stocking), has been reconstructed within the years starting from 1993: for that year, data on 

tonnes of sludge treated in a given way are available 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 been 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 percentages 

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), the 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 equal 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 reported.
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 4,610 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, 1972; 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 refers to waste production 

and not to waste 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

Moderately

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 potential (L0)

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 = Σi (DOCi * Wi)

Where:

DOC = fraction of degradable organic carbon in bulk waste, kg C/kg of wet waste

DOCi = fraction of degradable organic carbon in waste type i, 

Wi = fraction of waste type i by waste category

Degradable organic carbon in waste type i can be caluculated as following:

DOCi = Ci * (1-ui) * Wi

Where:

Ci = organic carbon content in dry waste type i, kg C/ kg of waste type i

ui= moisture content in waste type i

Wi = fraction of waste type i by waste category
194

In Tables 8.8, 8.9 and 8.10, only 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 by 

weight

(wet waste)

Moisture 

content

Organic carbon 

content

(dry matter)

DOCi

(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 Organic Carbon calculation, 1950-1970

WASTE COMPONENT

Composition by 

weight

(wet waste)

Moisture 

content

Organic carbon 

content

(dry matter)

DOCi

(kg C/t MSW)

Food 33.3% 60% 48% 63.95

Garden and park 3.7% 50% 48% 8.88

Paper, paperboard, textile and 

wood

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)

DOCi

(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 degradable organic carbon, the methane generation potential value (L0) is 

calculated as following:

L0 = MCF * DOC * DOCF * F * 16/12

Where:

MCF = methane correction factor

DOCF = fraction of DOC dissimilated

F = fraction of methane in landfill gas

Fraction of degradable organic carbon (DOCF) 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.

DOCF value is dependent on many factors like temperature, moisture, pH, composition of waste: 

the default value 0.5 has been used.

The methane correction factor (MCF) accounts for that unmanaged SWDS produce less CH4

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 factor’, 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 mostly

shallow, because 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 dioxide and 50% methane.

The following Table 8.11 summarize the methane generation potential values (L0) generated, 

distinguished for managed and unmanaged landfills.

L0 (m3CH4 tMSW-1) 1950 - 1970 1971 - 1990 1991 - 2007 

Rapidly biodegradable 

- Managed 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 landfill 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 waste 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 conditions and slowly degradable waste such as wood or paper. Thus, for each rapidly, 

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

Rapidly 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 reconstructed 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 the methane extracted can be used for 

energy or can be flared. 

In Figure 8.3 methane 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

450,000

199019911992199319941995199619971998199920002001200220032004200520062007

tons

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 consistency

The combined uncertainty in CH4 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 CH4 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 produced (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

CH4 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

Methane recovered (Gg) 0 0 0 0 0 0 0 0 0 0

CH4 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 CH4 and NMVOC net emissions, 1990 – 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 led 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 knowledge 

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 emissions 

from landfills, have been presented and discussed at the 10th 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 estimation 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% separate 

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, CH4 and N2O are estimated both from domestic-commercial and 

industrial wastewaters.

In Table 8.14 an 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 N2O emissions are reported in 6.B.2.2 Human sewage

 Sludge N2O 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, CH4 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 treatment process used to stabilised wastewater sludge.

Actually, in Italy 84% of population is served by sewer systems, whereas 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 wastewater 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 using 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 cases where, notwithstanding aerobic treatments, CH4 emissions can occur due to 

a bad management.

For high strength organic waste, such as some industrial wastewater, anaerobic process is

recommended 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 estimated 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 disposal do occur.

8.3.2. Methodological issues

Regarding N2O 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 been followed. Fraction of nitrogen protein (Frac NPR) 0.16 kg N kg-1

protein and emission factor (EF6) 0.01 kg N-N2O 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 Chemical Oxygen

Demand (COD) are available so the default value of 0.25 kg CH4 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 (m3 t-1) and 

by the degradable organic component (kg COD (m3)

-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

(FEDERCHIMICA, 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 detailed references for 2007 are reported: for the se national data, slightly

differences within the years can occur.
199

Wastewater 

generation

(m3/t)

References COD (g/l) References

Coke 1.5 IPCC, 2000 0.1 IPCC, 2000

Petroleum Refineries UNIONE PETROLIFERA supplies 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, Fruits 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

Beer 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.

CH4 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 investigation 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]).

CH4 emissions have been calculated on the basis of the equivalent inhabitants treated in Imhoff 

tanks, the organic loading in biochemical oxygen demand per person equal to 60 g BOD5 capita1

 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 BOD5 that readily settles equal 

to 0.3 (ANPA, 2001; Masotti, 1996), and the IPCC emission factor default value of 0.6 g CH4 g1

 BOD5. 

8.3.3. Uncertainty and time -series consistency

The combined uncertainty in CH4 emissions from wastewater 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 N2O 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).

CH4 emission trend for industrial wastewater handling for different sectors is shown in Table 

8.17, whereas the emission trend for N2O emissions both from industrial wastewater handling 

and human sewage is shown in Table 8.18.
200

Concerning CH4 emissions from industrial wastewater, neither wastewater flow nor average 

COD value change much over time, therefore emissions are stable and mainly related to the 

production data. 

The CH4 emission trend from wastewater and sludge generated by domestic and commercial 

wastewater 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 documentation 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 calculation of the emissions 

from wastewater handling, has been presented and discussed at the 10th International Trade Fair 

on Material and Energy Recovery and Sustainable Development, Ecomondo 2006 (Ecomondo, 

2006).

Wastewater production 

(1000 m3)

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 production by sector, 1990 – 2007 (1000 m3)

CH4 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 1.005

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 CH4 emissions from anaerobic industrial wastewater treatment, 1990 – 2007 (Gg)

N2O 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 6.042 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 N2O 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

CH4 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

(103 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

CH4 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 CH4 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 in 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 for 

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 facilities 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 published by ISPRA (APATONR, 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 detailed methodology is reported in Chapter 6 (6.6.2).

CH4 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

Practice 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 calculated for each type of waste: municipal, industrial, hospital, sewage 

sludge and waste oils.

A complete database 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; APATONR, several years; AUSITRA-Assoambiente, 1995; Morselli, 1998; FEDERAMBIENTE,

1998; FEDERAMBIENTE, 2001; AMA-Comune di Roma, 1996; ENI S.p.A., 2001; 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 CH4 emission factor that is derived from EMEP Corinair 

(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 levels 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 sludge, 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 waste treated, for municipal, 

industrial, hospital waste, waste oils and sewage sludge.

NMVOC

(kg/t)

CO

(kg/t)

CO2 fossil

(kg/t)

N2O

(kg/t)

NOx

(kg/t)

SO2

(kg/t)

CH4

(kg/t)

Municipal waste 0.46 0.07 289.26 0.1 1.15 0.39 0.06

Hospital waste 7.4 0.075 1200 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), detail 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 CO2 emission factor for municipal waste, it has been calculated 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 CO2 from fossil fuels (generally plastics) and CO2 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

CO2 emission factor for industrial, oils and hospital waste has been derived as the average of 

values of investigated industrial plants. On the other hand, CO2 emissions from the incineration 

of sewage sludge were not included at all, while all emissions relating to the incineration of 

hospital and industrial waste were considered.

Municipal waste Average concentration 

values (mg/Nm3)

Standard specific flue 

gas volume 

(Nm3/KgMSW)

E.F. (g/t)

SO2 78.00 5 390

NOx 230.00 1,150

CO 14.00 70

N2O 100

CH4 59.80

NMVOC 460.46

C content, % weight 23

CO2 826.5 (kg/t)

Table 8.21 Municipal waste emission factors

Industrial and oil waste Average concentration 

values (mg/Nm3)

Standard specific flue 

gas volume 

(Nm3/KgMSW)

E.F. (g/t)

SO2 160.00 8 1,280

NOx 250.00 2,000

CO 70.00 560

N2O 100

CH4 59.80

NMVOC 7,400

CO2 1,200 (kg/t)

Table 8.22 Industrial waste and oils emission factors

Hospital waste Average concentration 

values (mg/Nm3)

Standard specific flue 

gas volume 

(Nm3/KgMSW)

E.F. (g/t)

SO2 3.24 8 26

NOx 75.45 604

CO 9.43 75

N2O 100

CH4 59.80

NMVOC 7,400

CO2 1,200 (kg/t)

Table 8.23 Hospital waste emission factors

Sewage sludge Average concentration 

values (mg/Nm3)

Standard specific flue 

gas volume 

(Nm3/KgMSW)

E.F. (g/t)

SO2 300 6 1,800

NOx 500 3,000

CO 100 600

N2O 100

CH4 59.80

NMVOC 7,400

CO2 1,200 (kg/t)

Table 8.24 Sewage sludge emission factors

CH4 and N2O 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, the 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 the 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 residues 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 the 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, CH4 and N2O emissions have been 

calculated, both accounting nearly for 100% of the whole emissions from waste incineration. 

CO2 emissions have been calculated but not included in the inventory as biomass. All these 

parameters refer both to the IPCC Guidelines (IPCC, 1997) and country-specific values

(CESTAAT, 1988; Borgioli, 1981).

8.4.3. Uncertainty and time -series consistency

The combined uncertainty in CO2 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 N2O and CH4 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; CO2 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 N2O and CH4 emissions are summarized, including those 

from open burning.

In the period 1990-2007, total CO2 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%. While CO2 emission trend reported in 6C is influenced by 

the amount of waste incinerated in plant without energy recovery, CH4 and N2O 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 47.30 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 CO2 emissions from waste incineration (without and with energy recovery), 1990 – 2007 (Gg)

GAS/SUBSOURCE 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

N2O (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

CH4 (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 N2O and CH4 emissions from waste incineration, 1990 – 2007 (Gg)

8.4.4. Source-specific QA/QC and verification

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 10th 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 CO2 emissions and account for 14.3%.

In 2005, data has been update for one incineration plant 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 CO2 emission factor on the basis of carbon content.

8.5 Other waste (6D)

8.5.1. Source category description

Under this source category CH4 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; AUSITRAAssoambiente, 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 sludge 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 incinerating 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 compost 

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 CH4 and NMVOC emissions are reported.

GAS 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

CH4 (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 CH4 and NMVOC emissions from compost production, 1990 – 2007 (Gg)

8.5.3. Uncertainty and time -series consistency

The uncertainty in CH4 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

The methodology, as well as the parameters used in the calculation of the emissions from 

compost production, have been presented and discussed at the 10th 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-specific 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

accuracy 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 

submissions, changes due to error corrections and in consideration of new available information. 

The complete revised CRFs from 1990 to 2006 have been submitted as well as the CRF for the 

year 2007 and recalculation tables of the CRF have been filled in. Explanatory information on 

the major recalculations between the 2008 and 2009 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 following section 9.4.1.

9.2 Implications for emission levels

The time series reported in the 2008 submission and the series reported this year (2009 

submission) are shown in Table 9.2 by gas and sector. Specifically, by gas, the comparison and 

differences 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 the last year 

submission (-0.11%) whereas emissions for the year 2006 showed a decrease equal to 0.87%. 

Considering the national total with the LULUCF sector, the base year has increased by 2.53, and 

the 2006 emission levels increased 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 from 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 

industrial 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 2006, changes affected the energy sector, due to the same methodological revision for road 

transport and civil aviation, as for 1990, and a reconsideration 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 Explanations of the main recalculations in the 2009 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 2008 and 2009 submitted time series by gas and sector
211

Base 

year 

1990

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Net CO2

emissions/removals 

(Gg CO2-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 367,037 359,585 346,789 362,122 377,855 378,212 383,389 375,767 374,907 359,145 397,091 394,682 395,617

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%

CO2 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%

CH4 emissions

(Gg CO2-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%

CH4 emissions

(without LULUCF)

(Gg CO2-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%

N2O emissions

(Gg CO2-eq.)

2007 

subm 38,024 38,814 38,547 39,824 39,970 40,741 40,891 41,080 40,702 40,409 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%

N2O emissions

(without LULUCF)

(Gg CO2-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 CO2-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 5,956

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 CO2-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%

SF6 (Gg CO2-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

516,898 530,457 523,426 529,617 540,956 546,914 552,274 557,980 559,191 574,084 578,039 577,945 567,922

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 2009 and 2008 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 2008, emission levels of the base year, total 

emissions in CO2 equivalent without LULUCF, slightly changed (-0.11%) due to a revision in the 

energy and industrial sectors as previously described. 

If considering emission levels with LULUCF, an increase by 2.53% is observed between the 2008 

and 2009 total figures in CO2 equivalent, mainly due to the update of land use areas. 

For the year 2006, changes affected negatively CO2, CH4 and N2O emissions (-0.47%, -0.30%, -

7.35%, respectively). 

The trend ‘base year- year 2006’ does not show a significant change from the previous to this year 

submission.

Improvements in methodologies used to compile the inventory guarantee 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 inventory 

since the 2008 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 2006, 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 recalculations 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, CO2

emission factors for natural gas, coal and fuel oil were revised 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 minor 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 production 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 revisions concerned the update of activity data in wastewater handling and

incineration sectors.
213

9.4.2 Response to the UNFCCC review process 

In 2008, the Italian GHG inventory was subject to the centralised review of the 2007 and 2008 

Inventory submissions. 

Following the recommendations of the review processes different improvements have been carried 

out. 

The main improvements regarded 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 revise 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 emissions 

have been actually presented different institutions, 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, 

activity 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 Protocol 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 sector specific improvements are identified in the relevant chapters and specified in the 2009 

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 information 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 sectors, 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 and 

availability of information on waste composition and other parameters following the entering into 

force of the European landfill directive. 

For the LULUCF; activities planned in the framework of the National Registry for Forest Carbon 

Sinks should provide 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. 

Finally, 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 Tier 2 approach of the IPCC Good Practice 

Guidance. 

TABLE 8(a) RECALCULATION - RECALCULATED DATA Recalculated year: Inventory 2006

Submission 2009 v1.3

ITALY

Previous 

submission

Latest 

submission

Difference Difference excluding 

LULUCF

including 

LULUCF

Previous 

submission

Latest 

submission

Difference Difference excluding 

LULUCF

including 

LULUCF

Previous 

submission

Latest 

submission

Difference Difference excluding 

LULUCF

including 

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

CO2 Emissions from Biomass 14,994.38 14,993.25 -1.13 -0.01 0.00 0.00

Previous 

submission

Latest 

submission Difference Difference

 excluding 

LULUCF

including 

LULUCF

Previous 

submission

Latest 

submission Difference Difference

 excluding 

LULUCF

including 

LULUCF

Previous 

submission

Latest 

submission Difference Difference

 excluding 

LULUCF

including 

LULUCF

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 SF6 20.83 20.83 NA,NO NA,NO NA,NO NA,NO

2.F. Consumption of Halocarbons and SF6 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 CO2 Equivalent Emissions with Land Use, Land-Use Change and Forestry 17,465.19 3.83

Total CO2 Equivalent Emissions without Land Use, Land-Use Change and Forestry -4,939.78 -0.87

CO2 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

CO2 equivalent (Gg) (%) CO2 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

CO2 CH4 N2O

CO2 equivalent (Gg) (%) CO 2 equivalent (Gg) (%) CO 2 equivalent (Gg) (%)

Table 9.4 Recalculated data of the year 2006
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, 2005. 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 Assurance/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 2007. 

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]. Carbon 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 implementing 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, 2007. Atmospheric Emission Inventory Guidebook. Technical report No 

16/2007. 

ENEA/MAP/APAT, 2004. Energy data harmonization for CO2 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 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.
216

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 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 inventory 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 greenhouse gas inventories of Italy

submitted in 2007 and 2008. FCCC/ARR/2008/ITA. UNFCCC, 16 January 2009.

10.2 ENERGY [CRF sector 1]

ACI, several years. Annuario statistico. Automobile Club d’Italia, Roma.

http://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/sintesi_cont_gas/sintesi_datigas. 

AISCAT, several years. Aiscat in cifre. Data and reports available on website at:

http://www.aiscat.it/pubb_cifre.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 inventari 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 del sistema energetico nazionale nel breve e medio periodo. Tricarico A., Rapporto 

Tecnico N° 01/2003.

APAT, 2003 [b]. Analisi dei fattori di emissione di CO2 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.

EC, 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 activities. Commission of the European Communities, 2009 (draft).

EDISON, several years. Rendiconto ambientale e della sicurezza.

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.

EEA, 2007. COPERT 4, Computer programme to calculate emissions from road transport.

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. ENI.

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 sviluppi 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 Inventories 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 industrie di base.

http://dgerm.sviluppoeconomico.gov.it/dgerm/ben.asp. 

MSE, several years [b]. Bollettino Petrolifero Trimestrale (BPT). Ministero delle Attività

Produttive.

MINT, several years. 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 Petrolifera.

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 

industriali 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.

Boehringer 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, del 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 informazioni 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. Technical 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.

ENIRISORSE, 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 Italiane.

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 WBCSD/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, 

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, 

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.

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. Annuario 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 Communication. 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 years. 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 Sostenibilità 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 di 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 review 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. Personal 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 

Carolina. 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. Associazione 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 1999 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 emissions 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. Official 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 secco.

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 Centre, 

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.

Regione 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 Adriatico. 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, Studio 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 campionaria 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. Database 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 Patron, 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 Livestock 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. Impact 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’Agricoltura, l’Ambiente e il Territorio, p. 311. 

Cóndor G. R., Vitullo, M., De Lauretis, 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 “Cambiamenti 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. Monteny, 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 sector 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 del 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 Journal 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=contributiscientifici.htm

Cóndor, R.D., Cristofaro, E. De Lauretis, R. 2008[c]. Agricoltura: inventario nazionale delle

emissioni e disaggregazione provinciale. Istituto superiore per la protezione e la ricerca ambientale, 

ISPRA Rapporto tecnico 85/2008. Roma, Italia. 

http://www.apat.gov.it/site/it-IT/APAT/Pubblicazioni/Rapporti/Documento/rapporto_85_2008.html

Cóndor, R.D., 2009. Procedura per la preparazione, 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 Journal 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 bufala 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 dei 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]. Piani 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 in 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.

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241

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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 Guidance 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 CO2 dal settore energetico, metodo di riferimento IPCC. 

Contaldi M., La Motta S.

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MSE, several years [b]. Bollettino Petrolifero Trimestrale (BPT). Ministero dello Sviluppo

Economico.

10.10 ANNEX 6

APAT, 2003. Analisi dei fattori di emissione di CO2 dal settore dei trasporti. Ilacqua M., Contaldi 

M., Rapporti n° 28/2003.

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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.
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 

that 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 expanded 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 terms 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: the 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 establishing 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 detailed 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 practice 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 has been carried out.

Summary of the results of the key category analysis, for the base year and 2007, 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, according to Tier 1, Tier 2 or both the methods.

For the base year, 19 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, 25 

categories were selected jointly by the Tier 1 and the Tier 2. 

For the year 2007, 17 sources were individuated by the Tier 1 approach accounting for 95% of the 

total emissions, without LULUCF; for the trend 13 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 2007, and, 
245

in trend assessment, 17 key categories are observed. Jointly for both the Tier 1 level and trend, 22 

key categories were totally individuated. 

The application of the Tier 2 to the 2007 emission levels gives as a result 21 key categories 

accounting for the 95% of the total levels uncertainty; when applying the trend analysis the key 

categories decreased to 20 with differences with respect to the previous list.

The application of the Tier 2 including the LULUCF categories results in 21 key categories, for the 

year 2007, accounting 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 assessment

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 should 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:

TotalContribution

Source or Sink Category Estimate

Key Category Level Assessment =

Therefore, key categories are those which, 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:

( Source or Sink Category Level Assessment ) Source or Sink CategoryTrend - TotalTrend

Source or Sink Category Trend Assessment 

⋅

=

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 trend 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 significantly 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 2007 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 reported. 

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 the 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 
246

inventory this occurs only for N2O from other production in the chemical industry and SF6 from the 

production of SF6. 

CATEGORIES

2007 Gg 

CO2eq

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 

CO2eq

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 LULUCF 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 14 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 17 key categories outcome from the 

trend analysis, with LULUCF categories, presenting some differences 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 inventory.

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 2007 inventory.

The results of the approach are reported in Table A1.3, for the year 2007, 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 CO2 emissions and removals, are 

reported whereas in Table A1.5, the results include CO2, CH4, N2O 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-HFC0 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: CO2

IPCC Gas Base year Year t Type A Type B 

Sorce category emissions emissions sensitivity sensitivity

1990 2007

Gg CO2 eq Gg CO 2 eq % % % % % % % % %

A. Forest Land CO2 -53,549 -55,588 30% 54% 61% 48% -1% 82% -1% 35% 35%

B. Cropland CO2 -16,876 -10,960 75% 75% 106% 16% -10% 16% -8% 17% 19%

- living biomass CO2 -17,206 -11,290 75% 75% 106% 17% -10% 17% -8% 18% 19%

- soils CO2 330 330 75% 75% 106% 0% 0% 0 % 0 % 1% 1 %

C. Grassland CO2 -385 -7,760 75% 75% 106% 12% 11% 11% 8 % 12% 15%

- living biomass CO2 62 0 75% 75% 106% 0% 0% 0 % 0 % 0% 0 %

- soils CO2 -447 0 75% 75% 106% 0% -1% 0 % -1% 0% 1 %

D. Wetlands CO2 0 0 0 % 0% 0% 0 % 0 % 0% 0 %

E. Settlements CO2 3,160 3,181 75% 75% 106% 5% 0% 5 % 0 % 5% 5 %

F. Other Land CO2 0 0 0 % 0% 0% 0 % 0 % 0% 0 %

G. Other CO2 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 Chapter 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 have been assigned by expert judgment, taking into account the final combined uncertainty

Table A1.4 Results of the uncertainty analysis for the LULUCF sector – CO2 (Tier1)

Tier 1 Uncertainty calculation and reporting: CO2+CH4+N2O

 

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 

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

Gg CO2 eq Gg CO2 eq % % % % % % % % %

A. Forest Land CO2 -53,392 -53,392 30% 54% 61% 49% 0% 79% 0% 34% 34%

B. Cropland CO2 -16,876 -16,876 75% 75% 106% 27% 0% 25% 0% 27% 27%

- living biomass CO2

-17,206 -17,206 75% 75% 106% 27% 0% 25% 0% 27% 27%

- soils CO2

330 330 75% 75% 106% 1% 0% 0% 0% 1% 1%

C. Grassland CO2 -385 -385 75% 75% 106% 1% 0% 1% 0% 1% 1%

- living biomass CO2

62 62 75% 75% 106% 0% 0% 0% 0% 0% 0%

- soils CO2

-447 -447 75% 75% 106% 1% 0% 1% 0% 1% 1%

D. Wetlands CO2 0 0 0% 0% 0% 0% 0% 0% 0%

E. Settlements CO2 3,160 3,160 75% 75% 106% 5% 0% 5% 0% 5% 5%

F. Other Land CO2 0 0 0% 0% 0% 0% 0% 0% 0%

G. Other CO2 0 0 0% 0% 0% 0% 0% 0% 0%

TOTAL 

-67,493 -67,493 56% 43%

Table A1.5 Results of the uncertainty analysis for the LULUCF sector – CO2, CH4, N2O (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-HFC0 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, 57 sources, 

according to the IPCC list in 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 66 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. 

The 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 Guidance (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 low 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 when 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 uncertainty increases to 7.0%.

In 2007, 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 2007. 

Specifically, for the LULUCF sector, the uncertainty value resulting from Tier 1 approach is 55% in 

the combined GWP total emissions for the year 2007, whereas the uncertainty in the trend is 43%. 

Similar values result from Tier 1 approach in uncertainty related to CO2 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 year 2007, whereas the

uncertainty in the trend between 1990 and 2007 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 following 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 the base and the current year submission; in this 

section detailed results are reported for the 2007 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 22 key categories accounting for the 

95% of the total levels uncertainty. The application of the Tier 2 to the inventory including the 

LULUCF categories results in 21 key categories accounting for the 95% of the total levels

uncertainty.

For the year 2007, the application of the Tier 2 gives as a result 21 key categories accounting for the 

95% of the total levels uncertainty; when applying 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 21 key 

categories accounting for the 95% of the total levels 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 Results 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) without LULUCF categories. 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 ENERGY CONSUMPTION FOR 

POWER GENERATION

 The detailed breakdown of total fuels consumed for electricity generation 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 CO2 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 consumption 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 can 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 the 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 errors 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 

improved (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 reference 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 different 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 connected 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 this 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 Terna 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, gross 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 6.35 292,050.00 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 

Petroleum 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 18,172.04 404,246,405.56 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 170.00 206.38 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 482,770,231.84 482,791,760.00 499,981,543.39 

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 factors 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 coal 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 concentration 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 

processes 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 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.

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 the 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 gases 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 energy 

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 –output 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 furnace 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, they seem to be 

produced using very low EFs for coal produced CO2, 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 blast 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 balance, coke 

ovens

Carbon balance, 

blast furnace

1.2 -1.2 Difference in physical emissions

8% -14% Unbalance in %

Emissions Efs 

(t CO2/Tcal)

14.68 400.4 Carbon in produced coke 

2.83 400.4 Transformation losses

0.67 400.4 non energy 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 CO2

The flowchart of carbon cycle for the year 2007 is reported below. CO2 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 consumptions 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

CO2 emission calculation

Year 2007

 

INPUT

Clinker 

production/Construction 

industries

Thermoelectric power 

plants

Anthracite 

used in steel 

plant 

185 kt CO2

Steam coal 

47,221 kt 

CO2

2,049 kt CO2

41,043 kt 

CO2

4,130 kt CO2

Blast furnace / Electric 

Arc Furnace

Sub 

bituminous 

coal and 

lignite

278 kt CO2

185 kt CO2

278 kt CO2
263

 

 * It results from the carbon balance: 

= 11,858 kt CO2 – 3,428 kt CO2

Coke 

Imports/Stock 

change 

839 kt CO2

Coking coal 

18,362 kt 

CO2

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 CO2

37 kt CO2 590 kt CO2 133 kt CO2 16 kt CO2 9,518 kt CO2302 kt CO2

175 kt CO2

Energy 

transformation losses
264

ANNEX 4: CO2 REFERENCE APPROACH

A4.1 Introduction

The IPCC Reference Approach is a ‘top down’ inventory 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 emissions 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 - CO2 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 time 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 entering 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 all 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 estimated 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 of 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 reference 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 kerosene, 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

From 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-export 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, fiscal 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 electricity 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, quantities 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 following 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 reported 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 energy 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 further 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 CO2 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 

from 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 fuel 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 inputs 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 ENEL/TERNA than the figure reported in the energy balance and higher quantities of petcoke 

calculated from cement production data than those reported in the energy balance.

Differences between emissions estimated by the reference and sectoral approach are reported 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 396.06 406.64 426.15 429.98 432.63 447.16 452.23 453.80 450.33 438.06

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 CO2 emission estimates 1990-2007 (Mt) and percentage differences

There are a number of reasons why the totals differ and these 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 producers 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 – production 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 includes 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 approach 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 changes 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.sviluppoeconomico.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 independent 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 energy 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 of 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 average 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 transactions 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 customers 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 natural 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 conventional 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 and transport sectors.
268

Table A5.1 – National Energy Balance, year 2007, Primary fuels, 109 kcal

PRIMARY SOURCES

BALANCE

 Coking 

coal

 Steam 

coal

Coal other 

uses

Lignite Subproduct

s (a)

Natural 

Gas

Crude oil Refinery 

feedstocks

Hydraulic 

Energy (e)

Geotherma

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)

Geotherma

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 thermic 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 regeneration 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, 109kcal

SECONDARY SOURCES

BALANCE

Electric 

Energy

CharcoalCoke 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

CharcoalCoke 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 transformation industries, "Enclosure 1/a", 109kcal 

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 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) 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 / Photovoltaic 

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 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

 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 

plants 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 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

(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", 109kcal 

SECONDARY SOURCES

TRANSFORMATIO

NS

 

Electric 

Energy

CharcoalCoke 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

CharcoalCoke 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

CharcoalCoke 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 

Workshop 

 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

CharcoalCoke 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) Petroleum 

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, Primary fuels losses, "Enclosure 2/a", 109kcal

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 

Photovoltai

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 

Photovoltai

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) Thermoelectric 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 Energy Balance, year 2007, Secondary fuels losses, "Enclosure 2/a", 109kcal

SECONDARY SOURCES

CONSUMPTIO

NS AND 

LOSSES

Electric 

Energy

CharcoalCoke 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

CharcoalCoke 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 

transport and 

distribution 20,647 20,647

 4) Differences : 

 - Statistics 1 -1

 - of 

conversion -2 4 5 -1 1 3 4 2 1 17

TOTAL 

(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", 109kcal

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 factor (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 industry 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 
283

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 factor (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-Total 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 

COMMERCIAL 

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", 109kcal

SECONDARY SOURCES

FINAL 

CONSUMPTIONS

Electric 

Energy

CharcoalCoke 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 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

CharcoalCoke 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 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

CharcoalCoke 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 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) 490 109 kcal of diesel and 22 109 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", quantity

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, paper 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

CharcoalCoke 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 

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 

industry 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

CharcoalCoke 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 

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

CharcoalCoke 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 

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 to 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

IPCC 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 users. 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 1990 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, thank to updated pipeline connection. Sizeable additional NGL facilities are under construction.

Each of those natural gases 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 the 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 the 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 emission factors 

 t CO2 / TJ t CO2 / 103 std cubic mt t CO2 / 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 1.965 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 2.329

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 year 2000 and to collect the available 

information on previous years fuels. The aim of this work is the verification of CO2 emission factors 

of the Italian energy system and specifically of the transportation sector. The results of analysis of 

fuel samples performed 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 programme 

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 been 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 

for 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 

experimental 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 refer 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 reach 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 extensive series of samples (more than 400) 

analysed by ENEL and made available to APAT.

 t CO2 / TJ t CO2 / t t CO2 / tep

Petrol, IPCC / 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 73.274 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 62.392 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 type. 

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 years 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.

Table 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 from 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 data 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 data, 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, 2007);

- for each inventory year it is possible to calculate the 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.

Using 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 CO2 / TJ T CO2 / T T CO2 / 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 3.124 3.203

Fuel oil, average 2000 75.898 3.124 3.176

Fuel oil, average 2001 75.889 3.122 3.175

Fuel 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 impressive 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 of 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 2.423 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: AGRICULTURE 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 review2, the time series of the parameters used for 

estimating the Dairy Cattle emission factor using the Tier 2 approach is reported in Table A.7.1. 

Information on the equations used for estimating the different net energy (NEm, NEg, 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

NEm

(MJ/day)

NEa

(MJ/day)

NEg

(MJ/day)

NEl

(MJ/day)

NEw

(MJ/day)

NEp

(MJ/day) NEma /DE NEga/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 reduction 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 is used for the production of electricity and combined 

(electricity 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 

presented 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 0.12

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

36

199019911992199319941995199619971998199920002001200220032004200520062007

GWh

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

Gg

 only eletricity production combined= electricity + heat production methane (Gg)

Source: Cóndor et al. 2008[c]

Figure A7.1 Time series of gross production 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 2007, 

submitted in 2009, in which time series of emission estimates for the following gases are reported:

• CO2

• CH4

• N2O

• HFCs, PFCs, SF6

• All gases and sources categories
300

Table A8.1 CO2 emissions trends, CRF year 2007 (years 1990 – 1999)

TABLE 10 EMISSION 

TRENDS

Inventory 

2007

CO2

Submission 

2009 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 101,268.76 103,786.58 108,033.89 109,632.51 109,241.76 111,445.87 112,671.21 114,360.34 118,143.79 119,688.84

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 19,407.30 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 SF6

 

F. Consumption of 

Halocarbons and SF6 

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

3. Solvent 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 

2007

CO2

Submission 

2009 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 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) -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 

2007

CO2

Submission 

2009 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 CO2 emissions including 

net CO2 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

Total CO2 emissions excluding 

net CO2 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 Bunkers 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

CO2 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 A8.1 CO2 emissions trends, CRF year 2007 (years 2000 – 2007)

TABLE 10 EMISSION TRENDS Inventory 2007

CO2

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 4.00

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 Natural 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 22,985.79 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 SF6 

F. Consumption of Halocarbons and SF6 

G. Other NA NA NA NA NA NA NA NA 0.00

3. Solvent and Other Product Use 1,273.82 1,295.07 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

CO2

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 -91,878.49 -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 -35.06

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 CO2 emissions including net CO2 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 CO2 emissions excluding net CO2 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

CO2

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 10,430.30 150.68

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

CO2 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 A8.2 CH4 emission trends, CRF year 2007 (years 1990 – 1999)

TABLE 10 EMISSION TRENDS

 

Inventory 

2007

CH4

 

Submission 

2009 v1.3

(Part 1 of 2) ITALY

GREENHOUSE GAS SOURCE AND SINK Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999

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 80.65 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 353.33 351.38 353.80 348.28 339.25 327.71 322.44 320.72 324.89 315.47

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 of Halocarbons and SF6 

F. Consumption of Halocarbons and SF6 

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

3. Solvent and Other Product Use 

4. Agriculture 819.80 829.39 807.99 805.18 807.07 820.15 821.62 823.14 816.91 823.22

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 

2007

CH4

 

Submission 

2009 v1.3

(Part 1 of 2) ITALY

GREENHOUSE GAS SOURCE AND SINK Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999

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. 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 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 Incineration 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 CH4 emissions including CH4 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 CH4 emissions excluding CH4 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 

2007

CH4

 

Submission 

2009 v1.3

(Part 1 of 2) ITALY

GREENHOUSE GAS SOURCE AND SINK Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999

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 Operations NE NE NE NE NE NE NE NE NE NE

CO2 Emissions from Biomass 
309

Table A8.2 CH4 emission trends, CRF year 2007 (years 2000 – 2007)

TABLE 10 EMISSION TRENDS Inventory 2007

CH4

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 377.01 358.32 351.73 344.74 336.78 334.27 310.02 308.70 -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 Fuels 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 SF6 

F. Consumption of Halocarbons and SF6 

G. Other NA NA NA NA NA NA NA NA 0.00

3. Solvent and Other Product Use 

4. Agriculture 801.77 765.51 748.86 751.55 739.99 737.16 721.39 743.77 -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

CH4

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) %

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 CH4 emissions including CH4 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 CH4 emissions excluding CH4 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

CH4

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 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

CO2 Emissions from Biomass 
312

Table A8.3 N2O emission trends, CRF year 2007 (years 1990 – 1999)

TABLE 10 EMISSION TRENDS

 

Inventory 

2007

N2O 

Submission 

2009 v1.3

(Part 1 of 2) ITALY

GREENHOUSE GAS SOURCE Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999

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 18.14

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 23.35 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 SF6 

F. Consumption of Halocarbons 

and SF6

 
313

TABLE 10 EMISSION TRENDS

 

Inventory 

2007

N2O 

Submission 

2009 v1.3

(Part 1 of 2) ITALY

GREENHOUSE GAS SOURCE Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999

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 

2007

N2O 

Submission 

2009 v1.3

(Part 1 of 2) ITALY

GREENHOUSE GAS SOURCE Base year (1990) 1991 1992 1993 1994 1995 1996 1997 1998 1999

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 N2O emissions including N2O 

from LULUCF 120.69 123.97 122.22 124.31 122.18 124.40 123.10 127.05 127.11 129.36

Total N2O emissions excluding N2O 

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

CO2 Emissions from Biomass 
315

Table A8.3 N2O emission trends, CRF year 2007 (years 2000 – 2007)

TABLE 10 EMISSION TRENDS Inventory 

2007

N2O

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 (Sectoral 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 SF6 

F. Consumption of Halocarbons and 

SF6 

G. Other NA NA NA NA NA NA NA NA 0.00
316

TABLE 10 EMISSION TRENDS Inventory 

2007

N2O

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

N2O

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 N2O emissions including N2O from 

LULUCF 128.33 128.37 125.99 124.38 127.89 122.27 105.94 102.76 -14.86

Total N2O emissions excluding N2O 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

Aviation 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

CO2 Emissions from Biomass 
318

Table A8.4 HFC, PFC and SF6 emission trends, CRF year 2007 (1990 – 1999)

TABLE 10 EMISSION TRENDS Inventory 2007

HFCs, PFCs and SF6

 

Submission 

2009 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 CO2

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 

CO2 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 CO2

equivalent) 1,807.65 1,451.54 849.56 707.47 476.84 490.80 243.39 252.08 270.43 258.00

CF4 0.21 0.17 0.10 0.08 0.06 0.06 0.03 0.03 0.03 0.03

C2F6 0.05 0.04 0.02 0.02 0.01 0.01 0.01 0.01 0.01 0.01

C 3F8 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

C4F10 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

c-C4F8 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00 0.00

C5F12 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO

C6F14 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 2007

HFCs, PFCs and SF6

 

Submission 

2009 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 listed PFCs(4)- (Gg 

CO2 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 CO2

equivalent) 332.92 356.39 358.26 370.40 415.66 601.45 682.56 728.64 604.81 404.51

SF6 0.01 0.01 0.01 0.02 0.02 0.03 0.03 0.03 0.03 0.02
320

Table A8.4 HFC, PFC and SF6 emission trends, CRF year 2007 (2000 – 2007)

TABLE 10 EMISSION TRENDS Inventory 2007

HFCs, PFCs and SF6

 

Submission 

2009 v1.3

(Part 2 of 2) ITALY

2000 2001 2002 2003 2004 2005 2006 2007

Change from 

base to latest 

GREENHOUSE GAS SOURCE reported year AND SINK 

CATEGORIES

(Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) (Gg) %

Emissions of HFCs(3)- (Gg CO2 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

HFC-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 CO2 equivalent) NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

 

Emissions of PFCs(3) - (Gg CO2 equivalent) 345.85 451.24 423.74 497.63 347.89 352.62 282.30 287.78 -84.08

CF4 0.04 0.05 0.04 0.05 0.04 0.04 0.03 0.04 -82.52

C2F6 0.01 0.01 0.02 0.02 0.01 0.01 0.01 0.00 -90.34

C 3F8 NA,NO 0.00 0.00 0.00 0.00 0.00 0.00 0.00 100.00

C4F10 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

c-C4F8 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 100.00

C5F12 NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO NA,NO 0.00

C6F14 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 CO2 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 SF6

 

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 CO2 equivalent) 493.43 795.34 739.72 467.56 502.14 465.39 405.87 427.55 28.42

SF6 0.02 0.03 0.03 0.02 0.02 0.02 0.02 0.02 28.42
322

Table A8.5 Total emission trends, CRF year 2007 (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

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

CO2 emissions including net CO2 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

CO2 emissions excluding net CO2 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

CH4 emissions including CH4 from 

LULUCF

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

CH4 emissions excluding CH4 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

N2O emissions including N2O 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

N2O emissions excluding N2O 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

SF6 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

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

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 35,532.23 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 18,800.28 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 A8.5 Total emission trends, CRF year 2007 (years 2000 – 2007)

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

CO2

equivalent 

(Gg)

CO2

equivalent 

(Gg)

CO2

equivalent 

(Gg)

CO2

equivalent 

(Gg)

CO2

equivalent 

(Gg)

CO2

equivalent 

(Gg)

CO2

equivalent 

(Gg)

CO2

equivalent 

(Gg)

(%)

CO2 emissions including net CO2

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

CO2 emissions excluding net CO2

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

CH4 emissions including CH4 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

CH4 emissions excluding CH4 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

N2O emissions including N2O 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

N2O emissions excluding N2O 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

HFCs 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

SF6 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

CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

 CO2

equivalent 

(Gg)

CO2

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 -95,649.34 -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 inventory communicated to the European Commission under the implementing 

provisions for the compilation of The European Community Inventory.
327

Table A9.1 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, plantspecific 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 CO2 CH4 N2O

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 CO2 CH4 N2O

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 CO2 CH4 N2O

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 COPERT 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 CO2 CH4 N2O

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 CO2 CH4 N2O HFCs PFCs SF6

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)

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. Limestone 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 Production

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. SF6 Used in Aluminium and 

Magnesium Foundries

No No No No No 
332

GREENHOUSE GAS SOURCE 

AND SINK CO

2 CH4

N

2

O HFCs PFCs SF6

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)

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. Fugitive 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. Refrigeration 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. Aerosols/ Metered Dose 

Inhalers

 Yes T2 AS CS No No 

5. Solvents No No No 

6. Other applications using ODS 

substitutes

 No No No 

7. Semiconductor 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 CO2 CH4 N2O

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 No 

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 used (Land-Use Change and Forestry, Waste, Other)

GREENHOUSE GAS SOURCE AND 

SINK

CO2 CH4 N2O

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 Wood 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

CO2 CH4 N2O

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 

CO2 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 method 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 organizations) 

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 sources 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 specify 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 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.

Italy has approved the National Plan for greenhouse gases reduction (PNRGHG) with the CIPE

(Interministerial Economic Planning Committee) decision n. 123, of 19 December 2002. The PNRGHG

sets policies and measures to act in order to achieve the national target of the Kyoto Protocol; Italy has 

committed to 6.5% reduction below 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 management).

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 

adopted 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 cover 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 related 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 commitment 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-CO2 emissions) on the 

national forest area, and on deforested areas, 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 conversion 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-CO2 emissions from forest fires (IEIF)

aimed at quantifying:

− non-CO2 emissions from forest 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 category (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:

IUTI 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 the 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 variables (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 examination 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

prevalentwetland use. Land-use indicators: land covered or saturated by water for all or part of the year 

(e.g. peatland), insisting 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 prevalent 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 carbon 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 classification;

− 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 FAOFRA2000 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 covered 

by any land-use indicator is contoured. In a second phase, a video-operator codes each contoured subarea, identifying the different land-use indicators. Then, the processed area is archived and

automatically classified under a land use and, at the same 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 thresholds 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 classified 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 percentage 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 every 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 Carbon 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 and 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 annually 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 NFIs 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 requirements 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 classification);

- 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-CO2 emissions from forest fires (IEIF)

The Forest fires GHG emissions National Inventory is aimed at estimating non-CO2 emissions from 

forest fires (CO2 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 

experimental phase and from 01/01/2010 in operational phase, time series of non-CO2 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 will 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, through 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 estimated 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

ANNEX 11: THE NATIONAL REGISTRY 

A11.1 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 

guidelines 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. 26th 2007);

• VPN connectivity testing (Oct. 15th 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 storage 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 16th 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 developed 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 systems 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. 

A11.2 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 the 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 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. 

Besides the one person designated as Registry 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 of 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 application 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 documentation.

A11.3 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 (International Transaction Log), in a consolidated system forming the European 

Emissions trading scheme (EU ETS).

A11.4 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 environment 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 production 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 installed.

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 minutes 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.

A11.5 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 Data 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 

requirements (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 sites 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 for 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, 

AAUs, 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.

A11.6 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 and 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 discrepancy 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 reconciliation process with the ITL or STL, the related unit blocks will be unblocked so 

that further transactions with these blocks will be possible.

A11.7 Prevention of unauthorized manipulations and operator error

The Agency emphasizes physical security of server 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 the 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 locked 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 password. 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 using 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.

Significant 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 requires 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 representatives 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).

A11.8 User interface of the national 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:
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a. User details – unchanged, updated, created

b. Account details – unchanged, updated, created

c. Operator holding account – unchanged, updated, created

A11.9 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 environment, 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) and 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 stability 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).

A11.10 Test results 

The performance 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 initialization 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 Readiness 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. 
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Table A11.1 Annual external transactions of Kyoto Protocol units

 Submission year 2009 

 Reported year 2008 

 Commitment period 1 

 

 Table 2 (b). Annual external transactions

Additions Subtractions

Unit type Unit type 

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
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Table A11.2 Total quantities of Kyoto Protocol units

Party Italy 

Submission year 2009 

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 2232035444 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 account 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 certification report NO NO NO NO NO

Total 2432766152 NO NO 9302402 NO NO
353

Table A11.3 Summary information on Kyoto Protocol units 

 Party Italy 

 Submission year 2009 

 Reported year 2008 

 

Commitment 

period 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 information on retirement

 Requirement Retirement

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