World Meteorological Organization

Global Ozone Research and Monitoring Project—Report No. 55

SCIENTIFIC ASSESSMENT OF

OZONE DEPLETION: 2014

National Oceanic and Atmospheric Administration

National Aeronautics and Space Administration

United Nations Environment Programme

World Meteorological Organization

European Commission
World Meteorological Organization

7bis, avenue de la Paix

Case postale 2300

CH-1211, Geneva 2

Switzerland

United Nations Environment Programme

Ozone Secretariat

P.O. Box 30552

Nairobi, 00100

Kenya

U.S. Department of Commerce

National Oceanic and Atmospheric Administration

14th Street and Constitution Avenue NW

Herbert C. Hoover Building, Room 5128

Washington, D.C. 20230

National Aeronautics and Space Administration

Earth Science Division

NASA Headquarters

300 E Street SW

Washington, D.C. 20546-0001

European Commission

Directorate-General for Research and Innovation

B-1049 Bruxelles

Belgium

Published online December 2014

ISBN: 978-9966-076-01-4

Note: Figures from this report are in the public domain and may be used with proper attribution to source.

This report and other components of the 2014 Ozone Assessment are available at the following locations:

http://www.wmo.int/pages/prog/arep/gaw/ozone_2014/ozone_asst_report.html

http://ozone.unep.org/en/assessment_panels_bodies.php?committee_id=7

http://ozone.unep.org/Assessment_Panels/SAP/SAP2014_Assessment_for_Decision-Makers.pdf

http://esrl.noaa.gov/csd/assessments/ozone/

This document should be cited as:

World Meteorological Organization (WMO), Scientific Assessment of Ozone Depletion: 2014, World 

Meteorological Organization, Global Ozone Research and Monitoring Project—Report No. 55, 416 pp., Geneva, 

Switzerland, 2014.

Example chapter citation:

L.J. Carpenter and S. Reimann (Lead Authors), J.B. Burkholder, C. Clerbaux, B.D. Hall, R. Hossaini, J.C. Laube, 

and S.A. Yvon-Lewis, Ozone-Depleting Substances (ODSs) and Other Gases of Interest to the Montreal Protocol, 

Chapter 1 in Scientific Assessment of Ozone Depletion: 2014, Global Ozone Research and Monitoring Project –

Report No. 55, World Meteorological Organization, Geneva, Switzerland, 2014.
World Meteorological Organization

Global Ozone Research and Monitoring Project—Report No. 55

SCIENTIFIC ASSESSMENT OF

OZONE DEPLETION: 2014

Pursuant to Article 6 of the Montreal Protocol

on Substances that Deplete the Ozone Layer

National Oceanic and Atmospheric Administration

National Aeronautics and Space Administration

United Nations Environment Programme

World Meteorological Organization

European Commission

iii

LIST OF INTERNATIONAL AUTHORS,

CONTRIBUTORS, AND REVIEWERS

Assessment Cochairs

Ayité-Lô Nohende Ajavon

Paul A. Newman

John A. Pyle

A.R. Ravishankara

Scientific Steering Committee

Ayité-Lô Nohende Ajavon

David J. Karoly

Malcolm K. Ko

Paul A. Newman

John A. Pyle

A.R. Ravishankara

Theodore G. Shepherd

Susan Solomon

Chapters, Lead Authors, and Chapter Editors

Chapter 1: Update on Ozone-Depleting Substances (ODSs) and 

Other Gases of Interest to the Montreal Protocol

Lucy J. Carpenter and Stefan Reimann [Lead Authors]

Andreas Engel and Stephen A. Montzka [Chapter Editors]

Chapter 2: Update on Global Ozone: Past, Present, and Future

Steven Pawson and Wolfgang Steinbrecht [Lead Authors]

Vitali E. Fioletov and Ulrike Langematz [Chaper Editors]

Chapter 3: Update on Polar Ozone: Past, Present, and Future

Martin Dameris and Sophie Godin-Beekmann [Lead Authors]

Slimane Bekki and Judith Perlwitz [Chapter Editors]

Chapter 4: Stratospheric Ozone Changes and Climate

Julie M. Arblaster and Nathan P.Gillett [Lead Authors]

Lesley J. Gray and David W.J. Thompson [Chapter Editors]

Chapter 5: Scenarios and Information for Policymakers

Neil R.P. Harris and Donald J. Wuebbles [Lead Authors]

Mack McFarland and Guus J.M. Velders [Chapter Editors]

Twenty Questions and Answers About the Ozone Layer: 2014 Update

Michaela I. Hegglin [Lead Authors]

Coordinating Editor

Christine A. Ennis
iv

Authors, Contributors, and Reviewers

Jon Abbatt Canada

Ayité-Lô Nohende Ajavon Togo

Hideharu Akiyoshi Japan

Joan M. Alexander USA

Simon Alexander Australia

Stephen O. Andersen USA

Valentina Aquila USA

Julie M. Arblaster Australia/USA

Matthew Ashfold Malaysia

Ghassem Asrar USA

Pieter J. Aucamp South Africa

Alkiviadis F. Bais Greece

Mark P. Baldwin UK

Elizabeth A. Barnes USA

Steven L. Baughcum USA

Gufran Beig India

Slimane Bekki France

Peter Bernath USA

Tina Birmpili UNEP

Thomas Birner USA

Donald R. Blake USA

Greg Bodeker New Zealand

Rumen D. Bojkov Germany

Geir O. Braathen WMO

Peter Braesicke Germany

Stefan Brönnimann Switzerland

Dominik Brunner Switzerland

James B. Burkholder USA

John P. Burrows Germany

Neal Butchart UK

Amy H. Butler USA

Wenju Cai Australia

Francesco Cairo Italy

Natalia Calvo Spain

Pablo O. Canziani Argentina

Lucy Carpenter UK

Kenneth S. Carslaw UK

Andrew J. Charlton-Perez UK

Wissam Chehade Germany

Martyn P. Chipperfield UK

Bo Christiansen Denmark

Irene Cionni Italy

Cathy Clerbaux France

Melanie Coldewey-Egbers Germany

Martin Dameris Germany

John S. Daniel USA

Jos de Laat The Netherlands

Andy Delcloo Belgium

Sandip Dhomse UK

Susana B. Diaz Argentina

Marcel Dorf Germany

Anne R. Douglass USA

Geoffrey S. Dutton USA

Richard S. Eckman USA

Nawo Eguchi Japan

James William Elkins USA

Andreas Engel Germany

Ines Engel Germany

Christine A. Ennis USA

Veronika Eyring Germany

David W. Fahey USA

Vitali Fioletov Canada

Eric L. Fleming USA

Piers M. Forster UK

Paul Fraser Australia

Stacey M. Frith USA

Lucien Froidevaux USA

Jan Fuglestvedt Norway

Masatomo Fujiwara Japan

John C. Fyfe Canada

Annie Gabriel Australia

Lenah Gaoetswe Botswana

Chaim I. Garfinkel Israel

Hella Garny Germany

Marvin A. Geller USA

Edwin P. Gerber USA

Andrew Gettelman USA

Tomasz Gierczak Poland

Manuel Gil-Ojeda Spain

Nathan P. Gillett Canada

Sophie Godin-Beekmann France

Marco González Kenya

Lesley J. Gray UK

Kevin M. Grise USA

Jens-Uwe Grooß Germany

Serge Guillas UK

Joanna D. Haigh UK

Bradley D. Hall USA

Steven C. Hardiman UK

Neil R.P. Harris UK

Birgit Hassler USA

Alain Hauchecorne France

Peter Haynes UK

Michaela I. Hegglin UK

François Hendrick Belgium

Peter Hitchcock UK
Authors, Contributors, and Reviewers

v

Øivind Hodnebrog Norway

Larry Horowitz USA

Ryan Hossaini UK

Jianxin Hu China

Nathalie Huret France

Dale F. Hurst USA

Iolanda Ialongo Finland

Mohammad Ilyas Malaysia

Franz Immler Belgium

Ivar S.A. Isaksen Norway

Charles H. Jackman USA

Michal Janouch Czech Republic

Julie M. Jones UK

Ashley Jones Canada

Kenneth W. Jucks USA

David J. Karoly Australia

Alexey Yu. Karpechko Finland

Yasuko Kasai Japan

Philippe Keckhut France

Sergey Khaykin Russia

Doug Kinnison USA

Andrew R. Klekociuk Australia

Jeff R. Knight UK

Malcolm K. Ko USA

Yutaka Kondo Japan

Karin Kreher New Zealand

Kirstin Krüger Norway

Paul B. Krummel Australia

Lambert J.M. Kuijpers The Netherlands

Markus Kunze Germany

Michael J. Kurylo USA

Paul J. Kushner Canada

Erkki Kyrölä Finland

Gabriela Lakkis Argentina

Shyam Lal India

Jean-François Lamarque USA

Tom Land USA

Ulrike Langematz Germany

Johannes Laube UK

Katharine Law France

Franck Lefèvre France

Bernard Legras France

Jos Lelieveld Germany

Qing Liang USA

Eun-Pa Lim Australia

Jintai Lin China

Nathaniel Livesey USA

Diego Loyola Germany

Emmanuel Mahieu Belgium

Desmond Manatsa Zimbabwe

Gloria L. Manney USA

Martin R. Manning New Zealand

Elisa Manzini Germany

Bella Maranion USA

Daniel R. Marsh USA

Amanda C. Maycock UK

Mack McFarland USA

Charles McLandress Canada

Chris McLinden Canada

Johan Mellqvist Sweden

Michael P. Meredith UK

Pauline M. Midgley Switzerland

Daniel M. Mitchell UK

Mario J. Molina USA

Stephen Montzka USA

Olaf Morgenstern New Zealand

Jens Mühle USA

Rolf Müller Germany

Hiroaki Naoe Japan

Thando Ndarana South Africa

Paul A. Newman USA

Ole John Nielsen Denmark

Simon O’Doherty UK

Keiichi Ohnishi Japan

Luke D. Oman USA

Vladimir L. Orkin USA

Andrew Orr UK

Yvan Orsolini Norway

Steven Pawson USA

Juan Carlos Peláez Cuba

Stuart A. Penkett UK

Judith Perlwitz USA

Thomas Peter Switzerland

Irina Petropavlovskikh USA

Klaus Pfeilsticker Germany

Daniel Phoenix USA

Damaris K. Pinheiro Brazil

Giovanni Pitari Italy

Michael Pitts USA

David Plummer Canada

Lorenzo M. Polvani USA

Jean-Pierre Pommereau France

Lamont Poole USA

Robert W. Portmann USA

Michael J. Prather USA

Michael Previdi USA

Ronald G. Prinn USA

John A. Pyle UK

Birgit Quack Germany

B. Rajakumar India

S. Ramachandran India

V. Ramaswamy USA
Authors, Contributors, and Reviewers

vi

Cora Randall USA

William Randel USA

Marilyn Raphael USA

A.R. Ravishankara USA

Stefan Reimann Switzerland

James Renwick New Zealand

Laura Revell Switzerland

Markus Rex Germany

Robert C. Rhew USA

Harald E. Rieder Austria

Martin Riese Germany

Matt Rigby UK

Vincenzo Rizi Italy

Alan Robock USA

Jose M. Rodriguez USA

Eugene Rozanov Switzerland

Vladimir Ryabinin Switzerland

Alfonso Saiz-Lopez Spain

Takatoshi Sakazaki Japan

Ross J. Salawitch USA

Michelle L. Santee USA

Robert Sausen Germany

Sue Schauffler USA

Robyn Schofield Australia

Dian J. Seidel USA

Megumi Seki UNEP

William Seviour UK

Jonathan Shanklin UK

Tiffany A. Shaw USA

Rajendra Shende India

Theodore G. Shepherd UK

Kiyotaka Shibata Japan

Keith Shine UK

Masato Shiotani Japan

Michael Sigmond Canada

Peter Simmonds UK

Isla R. Simpson USA

Isobel J. Simpson USA

Rajiv R. Singh USA

Björn-Martin Sinnhuber Germany

Karen L. Smith USA

Susan Solomon USA

Seok-Woo Son Korea

Johannes Staehelin Switzerland

Wolfgang Steinbrecht Germany

Gabriele P. Stiller Germany

Richard S. Stolarski USA

William T. Sturges UK

Tove M. Svendby Norway

Neil C. Swart Canada

David W. Tarasick Canada

Susann Tegtmeier Germany

Said Ali Thauobane Comoros

Larry W. Thomason USA

Owen Brian Toon USA

Matthew B. Tully Australia

David W.J. Thompson USA

Simone Tilmes USA

John Turner UK

Joachim Urban Sweden

Ronald van der A The Netherlands

Guus J.M. Velders The Netherlands

Daniel P. Verdonik USA

Jean-Paul Vernier USA

Martin K. Vollmer Switzerland

Peter von der Gathen Germany

Christian von Savigny Germany

Timothy J. Wallington USA

Darryn W. Waugh USA

Ann R. Webb UK

Mark Weber Germany

Debra K. Weisenstein USA

Ray F. Weiss USA

Laura J. Wilcox UK

Jeannette Wild USA

Elian Augusto Wolfram Argentina

Yutian Wu USA

Donald J. Wuebbles USA

Shi-Keng Yang USA

Shigeo Yoden Japan

Yoko Yokouchi Japan

Paul J. Young UK

Shari A. Yvon-Lewis USA

Durwood Zaelke USA

Christos S. Zerefos Greece

Lingxi Zhou China

Jerry Ziemke USA

Chapter Editorial Contributors

Chapter 1:

Nada Derek Australia

Jenny Hudson UK
vii

Remembrances

It is with sadness that we note the passing of the following scientists who have played leading roles in the 

science and international assessments of the ozone layer.

F. Sherwood “Sherry” Rowland (1927–2012) (Donald Bren research professor of 

chemistry in Earth system science at University of California, Irvine) passed away on 10 

March 2012. Sherry was born on 28 June 1927 in Delaware, Ohio. He earned a B.A. in 

1948 from Ohio Wesleyan University, his M.S. in 1951, and his Ph.D. in 1952 from the 

University of Chicago. In 1974, Mario Molina and Sherry warned that chlorofluorocarbons 

(CFCs) were increasing in the atmosphere, and were releasing chlorine in the stratosphere 

and thus depleting the ozone layer. Acting on this science spawned by Mario and Sherry, 

the nations of the world agreed in the 1985 Vienna Convention that ozone depletion was a 

real and serious problem. In 1987, the nations negotiated the Montreal Protocol on 

Substances that Deplete the Ozone Layer. The Montreal Protocol has now been 

strengthened to fully control the production and consumption of ozone depleting 

substances (ODSs), and has now been signed by every nation on Earth. In 1995, Sherry, 

Mario and Paul J. Crutzen shared the Nobel Prize for Chemistry “for their work in atmospheric chemistry, particularly 

concerning the formation and decomposition of ozone.” Sherry’s many other awards include the Tolman Award in 

1976, the Tyler Prize for Environmental Achievement in 1983, the Japan Prize in 1989, the Peter Debye Award in 1993, 

the Albert Einstein World Award of Science in 1994, and the AGU Roger Revelle Medal in 1994. Sherry contributed in 

numerous ways to the WMO/UNEP assessments, in fact, it can be easily stated that he started the whole process with 

his seminal 1974 paper.

Harold “Hal” Johnston (1920–2012) died 20 October 2012 at the age of 

92. He was born on 11 October 1920 in Woodstock, Georgia. He received 

his degree in chemistry from Emory University in 1941 and his Ph.D. from 

California Institute of Technology in 1948. After a few years at Stanford 

University, he was at UC Berkeley for his long and illustrious career. He 

was one of the pioneers of stratospheric research, having recognized the role 

of nitrogen oxides in destroying the ozone layer (simultaneously with Prof. 

Crutzen) and thus showing the potential impact of supersonic aircraft flying 

in the stratosphere. He was a major contributor to the Climatic Impact 

Assessment Program (CIAP) reports, an integrated assessment of the 

potential atmospheric impacts of the proposed American supersonic transport aircraft (SST) in the early 1970s. These 

reports predated the ozone layer assessments under the Montreal Protocol and laid the groundwork for stratospheric 

research. Hal received a number of awards and prizes, including the National Medal of Science, the Tyler World Prize 

for Environmental Achievement, the National Academy of Sciences Award for Chemistry in the Service to Society, and 

American Geophysical Union’s Roger Revelle Medal.

Joseph C. Farman (1930–2013) died in Cambridge on 11 May 2013 at the 

age of 82. Joe led the British Antarctic Survey (BAS) team that made one of 

the major geophysical discoveries of the 20th century when it reported a very 

large decline in springtime stratospheric ozone, a phenomenon that became 

known as the Antarctic Ozone Hole. Joe was born on 7 August 1930 in 

Norwich, England. He received his M.A. in Natural Sciences from Corpus 

Christi College, Cambridge, where he was later a Fellow and Honorary 

Fellow. In 1956 he joined the Falkland Island Dependencies Survey (later 

British Antarctic Survey) with responsibility for establishing their 

geophysical measurements during the International Geophysical Year. He stayed at BAS until his retirement in 1990, 

then joining the European Ozone Research Coordinating Unit. He assisted directly and indirectly with a number of 

WMO/UNEP Ozone Assessments and played a key role in the development of the Montreal Protocol, well beyond his 

initial scientific input. His scientific life was characterized by a painstaking attention to detail, to the primacy of data,

and for the need in geophysics for long data records. 
viii
ix

CONTENTS

SCIENTIFIC ASSESSMENT OF OZONE DEPLETION: 2014

PREFACE .......................................................................................................................................................... xi

EXECUTIVE SUMMARY: Assessment for Decision-Makers.................................................................. ES.1

CHAPTER 1: UPDATE ON OZONE-DEPLETING SUBSTANCES (ODSs) AND OTHER GASES 

OF INTEREST TO THE MONTREAL PROTOCOL

Lucy J. Carpenter and Stefan Reimann [Lead Authors]

Andreas Engel and Stephen A. Montzka [Chapter Editors]

Scientific Summary ................................................................................................................................. 1.1

1.1 Summary of the Previous Ozone Assessment .................................................................................. 1.5

1.2 Longer-Lived Halogenated Source Gases ........................................................................................ 1.5

1.3 Very Short-Lived Halogenated Substances (VSLS) ....................................................................... 1.31

1.4 Changes in Atmospheric Halogens ................................................................................................. 1.53

1.5 Changes in Other Trace Gases that Influence Stratospheric Ozone and Climate ........................... 1.63

1.6 Policy-Relevant Information Highlights ......................................................................................... 1.74

References ............................................................................................................................................. 1.79

CHAPTER 2: UPDATE ON GLOBAL OZONE: PAST, PRESENT, AND FUTURE

Steven Pawson and Wolfgang Steinbrecht [Lead Authors]

Vitali E. Fioletov and Ulrike Langematz [Chapter Editors]

Scientific Summary ................................................................................................................................. 2.1

2.1 Introduction ..................................................................................................................................... 2.5

2.2 Past Ozone in Observations and Model Simulations ....................................................................... 2.6

2.3 Updates on Natural Ozone Variations ............................................................................................ 2.28

2.4 Update on Future Ozone Changes .................................................................................................. 2.39

2.5 Highlights for Policymakers ........................................................................................................... 2.49

References ............................................................................................................................................. 2.51

Appendix 2A: Ozone Data Sets ............................................................................................................ 2.64

CHAPTER 3: UPDATE ON POLAR OZONE: PAST, PRESENT, AND FUTURE

Martin Dameris and Sophie Godin-Beekmann [Lead Authors]

Slimane Bekki and Judith Perlwitz [Chapter Editors]

Scientific Summary ................................................................................................................................. 3.1

3.1 Introduction ...................................................................................................................................... 3.3

3.2 Recent Polar Ozone Changes ........................................................................................................... 3.6

3.3 Understanding of Polar Ozone Processes ....................................................................................... 3.16

3.4 Recovery of Polar Ozone ................................................................................................................ 3.27

3.5 Future Changes in Polar Ozone ...................................................................................................... 3.31

3.6 Key Messages of Chapter 3 for the Decision-Making Community ............................................... 3.39

References ............................................................................................................................................. 3.43

Appendix 3A: Satellite Measurements Useful for Polar Ozone Studies .............................................. 3.60
x

CHAPTER 4: STRATOSPHERIC OZONE CHANGES AND CLIMATE

Julie M. Arblaster and Nathan P. Gillett [Lead Authors]

Lesley J. Gray and David W.J. Thompson [Chapter Editors]

Scientific Summary ................................................................................................................................. 4.1

4.1 Introduction and Scope ..................................................................................................................... 4.3

4.2 Observed Changes in Stratospheric Constituents that Relate to Climate ......................................... 4.4

4.3 Observed and Simulated Changes in Stratospheric Climate ............................................................ 4.6

4.4 Effects of Past Changes in Stratospheric Ozone on the Troposphere and Surface ........................ 4.19

4.5 Policy-Relevant Information .......................................................................................................... 4.43

References ............................................................................................................................................. 4.45

CHAPTER 5: SCENARIOS AND INFORMATION FOR POLICYMAKERS

Neil R.P. Harris and Donald J. Wuebbles [Lead Authors]

Mack McFarland and Guus J.M. Velders [Chapter Editors]

Scientific Summary ................................................................................................................................. 5.1

5.1 Introduction ....................................................................................................................................... 5.5

5.2 Issues of Potential Importance to Stratospheric Ozone and Climate ................................................ 5.7

5.3 Metrics for Changes in Ozone and Climate .................................................................................... 5.15

5.4 Scenarios and Sensitivity Analyses ................................................................................................ 5.28

References ............................................................................................................................................. 5.41

Appendix 5A ......................................................................................................................................... 5.49

Table 5A-1: Analyses of GWPs and GTPs

Table 5A-2: Baseline Scenario Mixing Ratios

APPENDICES

A LIST OF INTERNATIONAL AUTHORS, CONTRIBUTORS, AND REVIEWERS .................. A.1

B MAJOR ACRONYMS AND ABBREVIATIONS ......................................................................... B.1

C MAJOR CHEMICAL FORMULAE AND NOMENCLATURE FROM THIS ASSESSMENT... C.1
xi

PREFACE

This document is part of the information upon which the Parties to the United Nations Montreal Protocol 

will base their future decisions regarding ozone-depleting substances, their alternatives, and protection of 

the ozone layer. It is the latest in a long series of scientific assessments that have informed the Parties.

The Charge to the Assessment Panels

Specifically, the Montreal Protocol on Substances that Deplete the Ozone Layer 1 states (Article 6): “...the 

Parties shall assess the control measures...on the basis of available scientific, environmental, technical, 

and economic information.” To provide the mechanisms whereby these assessments are conducted, the 

Protocol further states: “...the Parties shall convene appropriate panels of experts” and “the panels will 

report their conclusions...to the Parties.”

To meet this request, the Scientific Assessment Panel (SAP), the Environmental Effects Assessment 

Panel (EEAP), and the Technology and Economic Assessment Panel (TEAP) have each prepared, about 

every 3–4 years, major assessment reports that updated the state of understanding in their purviews. These 

reports have been scheduled so as to be available to the Parties in advance of their meetings at which they 

consider the need to amend or adjust the Protocol.

The Sequence of Scientific Assessments

The present 2014 report is the latest in a series of 12 scientific Assessments prepared by the world's leading 

experts in the atmospheric sciences and under the international auspices of the World Meteorological 

Organization (WMO) and/or the United Nations Environment Programme (UNEP). This report is the eighth 

in the set of major Assessments that have been prepared by the Scientific Assessment Panel directly as input 

to the Montreal Protocol process. The chronology of all the scientific Assessments on the understanding of 

ozone depletion and their relation to the international policy process is summarized as follows:

Year Policy Process Scientific Assessment

1981 The Stratosphere 1981 Theory and Measurements. WMO No. 11

1985 Vienna Convention Atmospheric Ozone 1985. WMO No. 16

1987 Montreal Protocol

1988 International Ozone Trends Panel Report 1988. WMO No. 18

1989 Scientific Assessment of Stratospheric Ozone: 1989. WMO No. 20

1990 London Amendment and 

adjustments

1991 Scientific Assessment of Ozone Depletion: 1991. WMO No. 25

1992 Methyl Bromide: Its Atmospheric Science, Technology, and 

Economics (Assessment Supplement). UNEP (1992).

1992 Copenhagen Amendment 

and adjustments

1994 Scientific Assessment of Ozone Depletion: 1994. WMO No. 37

1995 Vienna adjustments

1997 Montreal Amendment 

and adjustments

1998 Scientific Assessment of Ozone Depletion: 1998. WMO No. 44

1999 Beijing Amendment and 

adjustments

2002 Scientific Assessment of Ozone Depletion: 2002. WMO No. 47

2006 Scientific Assessment of Ozone Depletion: 2006. WMO No. 50

2007 Montreal adjustments

2010 Scientific Assessment of Ozone Depletion: 2010. WMO No. 52

2014 Scientific Assessment of Ozone Depletion: 2014. WMO No. 55

																																																												 1 In this report, ozone-depleting substances (ODSs) refer to the gases listed in the Annexes to the Montreal Protocol. In 

addition to these gases, other chemicals also influence the ozone layer, and they are referred to as ozone-relevant gases.
Preface

xii

The Current Information Needs of the Parties

The genesis of Scientific Assessment of Ozone Depletion: 2014 was the 23rd Meeting of the Parties to the 

Montreal Protocol held during 21–25 November 2011 in Bali, Indonesia, at which the scope of the 

scientific needs of the Parties was defined in their Decision XXIII/13 (4), which stated that:

“...for the 2014 report, the Scientific Assessment Panel should consider issues including:

o Assessment of the state of the ozone layer and its future evolution, including in respect of 

atmospheric changes from, for example, sudden stratospheric warming or accelerated BrewerDobson circulation;

o Evaluation of the Antarctic ozone hole and Arctic winter/spring ozone depletion and the predicted 

changes in these phenomena, with a particular focus on temperatures in the polar stratosphere;

o Evaluation of trends in the concentration in the atmosphere of ozone-depleting substances and their 

consistency with reported production and consumption of those substances and the likely 

implications for the state of the ozone layer and the atmosphere;

o Assessment of the interaction between the ozone layer and the atmosphere; including: (i) The effect 

of polar ozone depletion on tropospheric climate and (ii) The effects of atmosphere-ocean coupling;

o Description and interpretation of observed ozone changes and ultraviolet radiation, along with 

future projections and scenarios for those variables, taking into account among other things the 

expected impacts to the atmosphere;

o Assessment of the effects of ozone-depleting substances and other ozone-relevant substances, if any, 

with stratospheric influences, and their degradation products, the identification of such substances, 

their ozone-depletion potential and other properties;

o Identification of any other threats to the ozone layer.”

The 2014 SAP Assessment has addressed all the issues that were feasible to address to the best possible 

extent. Further, given the change in the structure of the report and the evolution of science, the UV 

changes are addressed by the Environmental Effects Assessment Panel (EEAP) of the Montreal Protocol. 

The SAP has provided the necessary information on ozone levels, now and in the future, to EEAP as 

input to their assessments.

The 2014 Assessment Process

The formal planning of the current Assessment was started early in 2013. The Cochairs considered 

suggestions from the Parties regarding experts from their countries who could participate in the process. 

Two key changes were incorporated for the 2014 Assessment: (1) creation of a Scientific Steering 

Committee consisting of the Cochairs and four other prominent scientists; and (2) instituting Chapter 

Editors for each chapter to ensure that the reviews were adequately and appropriately handled by the 

authors and key messages were clearly enunciated to take them to the next level. For this reason, the 

Chapter Editors are also Coauthors of the Assessment for Decision Makers (ADM) of the Scientific 

Assessment of Ozone Depletion: 2014. The plan for this Assessment was vetted by an ad hoc international 

scientific advisory group. This group also suggested participants from the world scientific community to 

serve as authors of the science chapters, reviewers, and other roles. In addition, this advisory group 

contributed to crafting the outline of this Assessment report. As in previous Assessments, the participants 

represented experts from the developed and developing world. The developing country experts bring a 

special perspective to the process, and their involvement in the process has also contributed to capacity 

building in those regions and countries.

The 2014 Scientific Assessment Panel (SAP) Report

The 2014 report of the Scientific Assessment Panel differs from the past seven reports in its structure and 

mode of publication. However, as in the past, it is a thorough examination and assessment of the science. 

The process by which this report was generated, as in the past, was also thorough; the documents 

underwent multiple reviews by international experts.

The Structure of the 2014 Report

The previous SAP reports have served well the Parties to the Montreal Protocol, the scientific community, 

and the managers who deal with the research activities. However, the Montreal Protocol process has 
rPreface

xiii

matured significantly and its needs have evolved. It was clear from the discussions between the Cochairs 

and both the Party representatives and the people involved in decision making that the previous very 

lengthy assessment reports would not meet the current needs of the Parties for a short, pithy, document 

that is written for them and not for the scientific community. Yet, it was also clear that the integrity of 

and the trust in the SAP reports come from the very thorough assessment of the science. Therefore, this 

2014 Assessment was restructured to serve both purposes. The new structure is shown schematically 

below.

First, as in the past, a major scientific assessment process was carried out and the findings from these 

discussions and reviews constitute the five major chapters of the assessment foundation from the 

scientific community. This is shown on the left hand side of the diagram. The five scientific chapters are 

published only on the web but are an integral part of the 2014 SAP report to the Parties. Also, as 

discussed earlier, the assessment of the surface UV changes due to past ozone depletion or to projected 

future ozone levels are not included in this document. Readers are referred to the 2014 Environmental 

Effects Assessment Panel report for the UV discussion.

Second, the findings from the SAP’s five scientific chapters were then synthesized and written in a 

language that is accessible to the Parties to the Protocol. The contents of the Assessment for DecisionMakers document—an Executive Summary and three sections—are shown on the right hand side. This 

short document, which contains all the major scientific summary points written in a clear and accessible 

language, is available in print and on the web. It is hoped that this new document will be useful to and 

usable by the Parties to the Protocol, countries, and high-level policymakers and managers. If more 

scientific details are needed, the complete document can be accessed via the web.

Third, for this Assessment, the Twenty Questions and Answers About the Ozone Layer has been only 

updated. This is because the overarching scientific understanding has not changed significantly from the 

previous Assessment. The update will ensure that the answers include the most current data and are 

consistent with the 2014 Assessment. These updated questions and answers are published separately 

(both in print and on the web) in a companion booklet to this report.

It is hoped that these steps will enhance the usefulness of the document to the Parties, meet the needs of 

the multiple user communities for the information, minimize the workload of the scientific community, 

and reduce costs.

Chapters 

(Web-published) 

“ODSs” 

Science Update 

“Strat O3 Changes 

& Climate” 

Science Update 

“Polar Ozone” 

Science Update 

“Global Ozone” 

Science Update 

Policy-Relevant Highlights from the Chapter 

1 

2 

3 

4 

5 “Scenarios and Info 

for Policymakers” 

Science Update 

2014 Chapter Scientific Summary (bullets)

What We Know from Previous Assessments 

Synthesis of the 

Policy-Relevant 

Highlights of the 2014 

Ozone Assessment 

Additional Information 

of Interest to 

Decision-Makers 

(metrics, scenarios) 

Appendices: 

• Chapter Summaries 

• Other Supporting Detail 

(e.g., tables of ODPs, lifetimes, 

scenario details) 

~50 

pages 

~30 

pages 

Assessment Foundation 

from the Scientific Community 

Assessment for the DecisionMaking Community 

Decision-Relevant Information 

(Web and print publication) 

Executive Summary 
Preface

xiv

The Process of Preparing the 2014 Assessment

The initial plans for the scientific chapters of the 2014 Scientific Assessment Panel's report were

examined at a meeting that occurred on 10–11 June 2013 in Cambridge, UK. The Lead Authors, the 

Scientific Steering Committee, and Chapter Editors—along with a few representatives of other 

assessment panels and organizations—focused on the planned content of the chapters and on the need for 

coordination among the chapters.

The first drafts of the scientific chapters were mailed to 213 experts for written reviews. The chapters 

were revised to take into account the comments of the reviewers. The revised drafts were subsequently 

sent to 65 reviewers who either attended a review meeting in Boulder or communicated their comments 

back to the group. These second drafts were reviewed by 63 experts in person in Boulder, CO, USA 

during 8–10 April 2014. Final changes to the chapters were decided upon at this meeting, and the final 

chapter summary points were agreed. Subsequently, the chapters were revised for clarity and to address 

specific points that were agreed to at the Boulder meeting. Final drafts of the scientific chapters were 

completed in May 2014.

Subsequent to the finalization of the five chapters, an author team consisting of the Scientific Steering 

Committee, Chapter Lead Authors, and Chapter Editors wrote a draft of the Assessment for DecisionMakers. This document was based on the science findings of the five chapters. The draft ADM was made 

available on June 13 to the attendees of a Panel Review Meeting that took place in Les Diablerets, 

Switzerland, on 23–27 June 2014. The overall ADM was reviewed, discussed, and agreed to by the 59 

participants. The Executive Summary of the ADM, contained herein (and posted on the UNEP and WMO 

websites on 10 September 2014), was prepared and completed by the attendees of the Les Diablerets 

meeting.

The final result of this two-year endeavor is the present assessment report. As the accompanying list 

indicates (Appendix A), the Scientific Assessment of Ozone Depletion: 2014 is the product of 285

scientists from 36 countries 2 of the developed and developing world who contributed to its preparation 

and review (133 scientists prepared the report and 220 scientists participated in the peer review process).

																																																												 2 Argentina, Australia, Austria, Belgium, Botswana, Brazil, Canada, People’s Republic of China, Comoros, Costa 

Rica, Cuba, Czech Republic, Denmark, Finland, France, Germany, Greece, India, Israel, Italy, Japan, Korea, 

Malaysia, New Zealand, Norway, Poland, Russia, South Africa, Spain, Sweden, Switzerland, The Netherlands, Togo, 

United Kingdom, United States of America, Zimbabwe.
ES-1

EXECUTIVE SUMMARY

ASSESSMENT FOR DECISION-MAKERS

[This is the Executive Summary of the Assessment for Decision-Makers of the 2014 Ozone Assessment. 

It contains the policy-relevant major findings of the Assessment’s five scientific chapters, which follow.]

Actions taken under the Montreal Protocol have led to decreases in the atmospheric 

abundance of controlled ozone-depleting substances (ODSs), and are enabling the return 

of the ozone layer toward 1980 levels.

• The sum of the measured tropospheric abundances of substances controlled under the Montreal 

Protocol continues to decrease. Most of the major controlled ODSs are decreasing largely as 

projected, and hydrochlorofluorocarbons (HCFCs) and halon-1301 are still increasing. Unknown or 

unreported sources of carbon tetrachloride are needed to explain its abundance.

• Measured stratospheric abundances of chlorine- and bromine-containing substances 

originating from the degradation of ODSs are decreasing. By 2012, combined chlorine and 

bromine levels (as estimated by Equivalent Effective Stratospheric Chlorine, EESC) had declined by 

about 10–15% from the peak values of ten to fifteen years ago. Decreases in atmospheric abundances 

of methyl chloroform (CH3CCl3), methyl bromide (CH3Br), and chlorofluorocarbons (CFCs) 

contributed approximately equally to these reductions.

• Total column ozone declined over most of the globe during the 1980s and early 1990s (by about 

2.5% averaged over 60°S to 60°N). It has remained relatively unchanged since 2000, with 

indications of a small increase in total column ozone in recent years, as expected. In the upper 

stratosphere there is a clear recent ozone increase, which climate models suggest can be explained by 

comparable contributions from declining ODS abundances and upper stratospheric cooling caused by 

carbon dioxide increases.

• The Antarctic ozone hole continues to occur each spring, as expected for the current ODS 

abundances. The Arctic stratosphere in winter/spring 2011 was particularly cold, which led to large 

ozone depletion as expected under these conditions.

• Total column ozone will recover toward the 1980 benchmark levels over most of the globe under 

full compliance with the Montreal Protocol. This recovery is expected to occur before midcentury in 

midlatitudes and the Arctic, and somewhat later for the Antarctic ozone hole. 

The Antarctic ozone hole has caused significant changes in Southern Hemisphere 

surface climate in the summer.

• Antarctic lower stratospheric cooling due to ozone depletion is very likely the dominant cause of 

observed changes in Southern Hemisphere tropospheric summertime circulation over recent 

decades, with associated impacts on surface temperature, precipitation, and the oceans. In the 

Northern Hemisphere, no robust link has been found between stratospheric ozone depletion and 

tropospheric climate.
Executive Summary—Assessment for Decision-Makers

ES-2

Changes in CO2, N2O, and CH4 will have an increasing influence on the ozone layer as 

ODSs decline.

• As controlled ozone-depleting substances decline, the evolution of the ozone layer in the second 

half of the 21st century will largely depend on the atmospheric abundances of CO2, N2O, and

CH4. Overall, increasing carbon dioxide (CO2) and methane (CH4) elevate global ozone, while 

increasing nitrous oxide (N2O) further depletes global ozone. The Antarctic ozone hole is less 

sensitive to CO2, N2O, and CH4 abundances.

• In the tropics, significant decreases in column ozone are projected during the 21st century.

Tropical ozone levels are only weakly affected by ODS decline; they are sensitive to circulation 

changes driven by CO2, N2O, and CH4 increases.

The climate benefits of the Montreal Protocol could be significantly offset by projected 

emissions of HFCs used to replace ODSs.

The Montreal Protocol and its Amendments and adjustments have made large contributions toward 

reducing global greenhouse gas emissions. In 2010, the decrease of annual ODS emissions under the 

Montreal Protocol is estimated to be about 10 gigatonnes of avoided CO2-equivalent emissions per year, 

which is about five times larger than the annual emissions reduction target for the first commitment 

period (2008–2012) of the Kyoto Protocol (from the Executive Summary of the Scientific Assessment of 

Ozone Depletion: 2010).3

• The sum of the hydrofluorocarbons (HFCs) currently used as ODS replacements makes a small 

contribution of about 0.5 gigatonnes CO2-equivalent emissions per year. These emissions are 

currently growing at a rate of about 7% per year and are projected to continue to grow.

• If the current mix of these substances is unchanged, increasing demand could result in HFC emissions 

of up to 8.8 gigatonnes CO2-equivalent per year by 2050, nearly as high as the peak emission of CFCs 

of about 9.5 gigatonnes CO2-equivalent per year in the late 1980s.4

• Replacements of the current mix of high-Global Warming Potential (GWP) HFCs with low-GWP 

compounds or not-in-kind technologies would essentially avoid these CO2-equivalent emissions.

• Some of these candidate low-GWP compounds are hydrofluoro-olefins (HFOs), one of which (HFO1234yf) yields the persistent degradation product trifluoroacetic acid (TFA) upon atmospheric 

oxidation. While the environmental effects of TFA are considered to be negligible over the next few 

decades, potential longer-term impacts could require future evaluations due to the environmental 

persistence of TFA and uncertainty in future uses of HFOs.

• By 2050, HFC banks are estimated to grow to as much as 65 gigatonnes CO2-equivalent. The climate 

change impact of the HFC banks could be reduced by limiting future use of high-GWP HFCs to avoid 

the accumulation of the bank, or by destruction of the banks.

Additional important issues relevant to the Parties to the Montreal Protocol and other 

decision-makers have been assessed.

• Derived emissions of carbon tetrachloride (CCl4), based on its estimated lifetime and its accurately 

measured atmospheric abundances, have become much larger than those from reported production 

and usage over the last decade.

																																																												 3 GWP-weighted emissions, also known as CO2-equivalent emissions, are defined as the amount of gas emitted 

multiplied by its 100-year Global Warming Potential (GWP). Part of the effect of ODSs as greenhouse gases is 

offset by the cooling due to changes in ozone. 

4 This is equivalent to about 45% of the fossil fuel and cement emissions of CO2 in the late 1980s. 
Executive Summary—Assessment for Decision-Makers

ES-3

• As of 2009, the controlled consumption of methyl bromide declined below the reported consumption 

for quarantine and pre-shipment (QPS) uses, which are not controlled by the Montreal Protocol.

• Increased anthropogenic emissions of very short-lived substances (VSLS) containing chlorine and 

bromine, particularly from tropical sources, are an emerging issue for stratospheric ozone. The 

relative contribution of these emissions could become important as levels of ODSs controlled under 

the Montreal Protocol decline.

• As the atmospheric abundances of ODSs continue to decrease over the coming decades, N2O, as the 

primary source of nitrogen oxides in the stratosphere, will become more important in future ozone 

depletion.

• Emissions of HFC-23, a by-product of HCFC-22 production, have continued despite mitigation 

efforts.

• While ODS levels remain high, a large stratospheric sulfuric aerosol enhancement due to a major 

volcanic eruption or geoengineering activities would result in a substantial chemical depletion of 

ozone over much of the globe.

While past actions taken under the Montreal Protocol have substantially reduced ODS 

production and consumption, additional, but limited, options are available to reduce 

future ozone depletion.

Emissions from the current banks are projected to contribute more to future ozone depletion than those 

caused by future ODS production, assuming compliance with the Protocol.

• Possible options to advance the return of the ozone layer to the 1980 level (analyses based on 

midlatitude EESC) are shown graphically. The cumulative effect of elimination of emissions from all 

banks and production advances this return by 11 years.

CHAPTER 1

Update on Ozone-Depleting Substances (ODSs) and 

Other Gases of Interest to the Montreal Protocol

Lead Authors:

L.J. Carpenter

S. Reimann

Coauthors:

J.B. Burkholder

C. Clerbaux

B.D. Hall

R. Hossaini

J.C. Laube

S.A. Yvon-Lewis

Contributors:

D.R. Blake

M. Dorf

G.S. Dutton

P.J. Fraser

L. Froidevaux

F. Hendrick

J. Hu

A. Jones

P.B. Krummel

L.J.M. Kuijpers

M.J. Kurylo 

Q. Liang 

E. Mahieu

J. Mühle

S. O'Doherty

K. Ohnishi

V.L. Orkin

K. Pfeilsticker 

M. Rigby

I.J. Simpson

Y. Yokouchi

Chapter Editors:

A.	Engel

S.A.	Montzka
[Formatted for double-sided printing.]

From: 

WMO (World Meteorological Organization), Scientific Assessment of Ozone Depletion: 2014, Global 

Ozone Research and Monitoring Project – Report No. 55, 416 pp., Geneva, Switzerland, 2014.

This chapter should be cited as: 

L.J. Carpenter and S. Reimann (Lead Authors), J.B. Burkholder, C. Clerbaux, B.D. Hall, R. Hossaini, J.C. 

Laube, and S.A. Yvon-Lewis, Ozone-Depleting Substances (ODSs) and Other Gases of Interest to the 

Montreal Protocol, Chapter 1 in Scientific Assessment of Ozone Depletion: 2014, Global Ozone Research 

and Monitoring Project – Report No. 55, World Meteorological Organization, Geneva, Switzerland, 2014.
CHAPTER 1

UPDATE ON OZONE-DEPLETING SUBSTANCES (ODSs) 

AND OTHER GASES OF INTEREST TO THE MONTREAL PROTOCOL

Contents

SCIENTIFIC SUMMARY .......................................................................................................................... 1

1.1 SUMMARY OF THE PREVIOUS OZONE ASSESSMENT ........................................................... 5

1.2 LONGER-LIVED HALOGENATED SOURCE GASES ................................................................. 5

1.2.1 Updated Observations, Lifetimes, and Emissions ................................................................. 5

1.2.1.1 Chlorofluorocarbons (CFCs) .................................................................................. 6

1.2.1.2 Halons ................................................................................................................... 21

1.2.1.3 Carbon Tetrachloride (CCl4) ................................................................................ 22

1.2.1.4 Methyl Chloroform (CH3CCl3) ............................................................................ 24

1.2.1.5 Hydrochlorofluorocarbons (HCFCs) .................................................................... 24

1.2.1.6 Methyl Chloride (CH3Cl) ..................................................................................... 27

1.2.1.7 Methyl Bromide (CH3Br) ..................................................................................... 28

1.3 VERY SHORT-LIVED HALOGENATED SUBSTANCES (VSLS) ............................................. 31

1.3.1 Abundance, Trends, and Emissions of Very Short-Lived Source Gases ............................ 37

1.3.1.1 Chlorine-Containing Very Short-Lived Source Gases ......................................... 37

1.3.1.2 Bromine-Containing Very Short-Lived Source Gases ......................................... 38

1.3.1.3 Iodine-Containing Very Short-Lived Source Gases ............................................. 41

1.3.2 Dynamics and Transport of VSLS ...................................................................................... 42

1.3.2.1 Source Gas Injection (SGI) .................................................................................. 43

1.3.2.2 Product Gas Injection (PGI) ................................................................................. 46

1.3.2.3 Total VSLS Halogen Input into the Stratosphere ................................................. 47

1.3.3 Potential Influence of VSLS on Ozone ............................................................................... 50

1.3.4 New Anthropogenic VSLS ................................................................................................. 50

1.4 CHANGES IN ATMOSPHERIC HALOGENS .............................................................................. 53

1.4.1 Tropospheric and Stratospheric Chlorine Changes ............................................................. 53

1.4.1.1 Tropospheric Chlorine Changes ........................................................................... 53

1.4.1.2 Stratospheric Chlorine Changes ........................................................................... 55

1.4.2 Tropospheric and Stratospheric Bromine Changes ............................................................. 57

1.4.2.1 Tropospheric Bromine Changes ........................................................................... 57

1.4.2.2 Stratospheric Bromine Changes ........................................................................... 58

1.4.3 Tropospheric and Stratospheric Iodine Changes ................................................................. 60

1.4.3.1 Tropospheric Iodine Changes ............................................................................... 60

1.4.3.2 Stratospheric Iodine Changes ............................................................................... 60

1.4.4 Changes in Ozone-Depleting Halogen Abundance in the Stratosphere Based Upon 

Long-Lived Source Gas Measurements: Equivalent Chlorine (ECl) and Equivalent 

Effective Stratospheric Chlorine (EESC) ............................................................................ 60

1.4.5 Fluorine in the Troposphere and Stratosphere .................................................................... 62

1.5 CHANGES IN OTHER TRACE GASES THAT INFLUENCE STRATOSPHERIC OZONE 

AND CLIMATE .............................................................................................................................. 63

1.5.1 Updates to Mole Fractions, Budgets, Lifetimes, and Observations .................................... 63

1.5.1.1 F-gases .................................................................................................................. 64
1.5.1.2 Nitrous Oxide (N2O) ............................................................................................. 72

1.5.1.3 Methane (CH4) ...................................................................................................... 73

1.5.1.4 COS, SO2 .............................................................................................................. 73

1.6 POLICY-RELEVANT INFORMATION HIGHLIGHTS ............................................................... 74

1.6.1 HCFCs Becoming a Larger Fraction of Tropospheric Chlorine; Bromine from Halons 

Now Decreasing .................................................................................................................. 74

1.6.2 VSLS Chlorinated Compounds Become More Relevant for Stratospheric Ozone ............. 75

1.6.3 Radiative Forcing of ODSs and ODS Replacement Compounds ....................................... 75

1.6.4 GWP-Weighted Emissions of ODS and ODS Replacement Compounds .......................... 76

1.6.5 Ongoing Mismatch between Estimated Sources of CCl4 from Measurements and from 

Inventories ........................................................................................................................... 77

1.6.6 Quarantine and Pre-Shipment (QPS) Consumption of CH3Br Has Exceeded Non-QPS 

Consumption ....................................................................................................................... 78

REFERENCES ........................................................................................................................................... 79
ODSs and Other Gases of Interest

1.1

SCIENTIFIC SUMMARY

Changes in the global atmospheric abundance of a substance are determined by the balance between its 

emissions and removal. Declines observed for ozone-depleting substances (ODSs) controlled under the 

Montreal Protocol are due to global emission reductions that have made emissions smaller than removals. 

Most ODSs are potent greenhouse gases. As the majority of ODSs have been phased out, demand for 

hydrochlorofluorocarbon (HCFC) and hydrofluorocarbon (HFC) substitutes for the substances controlled 

under the Montreal Protocol has increased; these are also greenhouse gases. HCFCs deplete much less 

ozone per kilogram emitted than chlorofluorocarbons (CFCs), while HFCs essentially deplete no ozone.

The amended and adjusted Montreal Protocol has continued to reduce emissions and atmospheric 

abundances of most controlled ozone-depleting substances. By 2012, the total combined abundance 

of anthropogenic ODSs in the troposphere (measured as Equivalent Chlorine) had decreased by 

nearly 10% from its peak value in 1994.

The contributions to the overall decline in tropospheric chlorine (Cl) and bromine (Br) from 

substances and groups of substances controlled and not controlled under the Montreal Protocol

have changed since the previous Assessment. The observed declines in total tropospheric Cl and Br 

from controlled substances during the 5-year period 2008–2012 were 13.4 ± 0.9 parts per trillion (ppt) yr-1

and 0.14 ± 0.02 ppt yr-1, respectively.1

Substances controlled under the Montreal Protocol

• −13.5 ± 0.5 ppt Cl yr-1 from chlorofluorocarbons (CFCs) 

• −4.1 ± 0.2 ppt Cl yr-1 from methyl chloroform (CH3CCl3)

• −4.9 ± 0.7 ppt Cl yr-1 from carbon tetrachloride (CCl4)

• −0.07 ± 0.01 ppt Cl yr-1 from halon-1211

• +9.2 ± 0.3 ppt Cl yr-1 from hydrochlorofluorocarbons (HCFCs)

• −0.06 ± 0.02 ppt Br yr-1 from halons

• −0.08 ± 0.02 ppt Br yr-1 from methyl bromide (CH3Br)

Substances not controlled under the Montreal Protocol

• −1.7 ± 1.3 ppt Cl yr-1 from methyl chloride (CH3Cl)

• +1.3 ± 0.2 ppt Cl yr-1 from very short-lived chlorine compounds (predominantly dichloromethane, CH2Cl2)

Tropospheric Chlorine

Total tropospheric chlorine from ODSs continued to decrease between 2009 and 2012 to 3300 parts 

per trillion (ppt) in 2012. The observed decline in controlled substances of 13.4 ± 0.9 ppt Cl yr-1 during 

2008–2012 was in line with the A1 (baseline) scenario of the 2010 Assessment.

Of total tropospheric Cl in 2012:

• CFCs, consisting primarily of CFC-11, -12, and -113, accounted for 2024 ± 5 ppt (about 61%) 

and are declining. Their relative contribution is essentially unchanged from the 2010 Assessment 

(62% in 2008).

• CCl4 accounted for 339 ± 5 ppt (about 10%). While our current understanding of the budget of 

CCl4 is incomplete, mole fractions of CCl4 declined largely as projected based on prior observations 

and the A1 scenario of the 2010 Assessment during 2009–2012.

• HCFCs accounted for 286 ± 4 ppt (8.7%). In total, the rate of increase for the sum of HCFCs has 

slowed by 25% since 2008 and has been lower than projected in the 2010 Assessment.

 1

 All uncertainties are one standard deviation unless otherwise specified.
Chapter 1

1.2

• CH3CCl3, the largest contributor to the decrease in total tropospheric chlorine until around 

2005, accounted for only 16 ± 1 ppt (0.5%). This is 50% less than in 2008 (32 ppt) and a 95% 

reduction from its mean contribution to the total Cl decline during the 1980s. The fraction is 

declining in line with the A1 scenario of the 2010 Assessment.

• CH3Cl accounted for 540 ± 5 ppt (about 16%) and has remained essentially constant since 

2008. This gas is emitted predominantly from natural sources.

• Very short-lived compounds (VSLS) contribute approximately 3%.

Global emissions of HCFCs remain substantial, but relative emissions of individual constituents 

have changed notably since the last Assessment. Emissions of HCFC-22 have stabilized since 2008 at 

around 370 gigagrams per year (Gg yr-1). HCFC-142b emissions decreased in the same period. In contrast 

emissions of HCFC-141b have increased since the last Assessment, in parallel with reported production 

and consumption in Article 5 Parties.

Estimated sources and sinks of CCl4 remain inconsistent with observations of its abundance. The 

estimate of the total global lifetime (26 years) combined with the observed CCl4 trend in the atmosphere 

(−1.1 to −1.4 ppt yr-1 in 2011–2012) implies emissions of 57 (40–74) Gg yr-1, which cannot be reconciled 

with estimated emissions from net reported production. New evidence indicates that other poorly quantified 

sources, unrelated to reported production, could contribute to the currently unaccounted emissions.

Three CFCs (CFC-112, -112a, -113a) and one HCFC (HCFC-133a) have recently been detected in 

the atmosphere. These four chlorine-containing compounds are listed in the Montreal Protocol and 

contribute about 4 ppt or ~ 0.1% toward current levels of total chlorine, currently adding less than 0.5 ppt 

Cl yr-1. Abundances of CFC-112 and CFC-112a are declining and those of CFC-113a and HCFC-133a are 

increasing. The sources of these chemicals are not known.

Stratospheric Inorganic Chlorine and Fluorine

Hydrogen chloride (HCl) is the major reservoir of inorganic chlorine (Cly) in the mid- to upper stratosphere. Satellite-derived measurements of HCl (50°N–50°S) in the mid- to upper stratosphere show a 

mean decline of 0.6% ± 0.1% yr-1 between 1997 and 2012. This is consistent with the measured 

changes in controlled chlorinated source gases. Variability in this decline is observed over shorter time 

periods based on column measurements above some ground-based sites, likely due to dynamic variability.

Measured abundances of stratospheric fluorine product gases (HF, COF2, COClF) increased by 

about 1% yr-1 between 2008 and 2012. This is consistent with increases in measured abundances of 

fluorinated compounds and their degradation products. The increase was smaller than in the beginning of 

the 1990s, when the concentrations of fluorine-containing ODSs were increasing more rapidly.

Tropospheric Bromine

Total organic bromine from controlled ODSs continued to decrease in the troposphere and by 2012 

was 15.2 ± 0.2 ppt, approximately 2 ppt below peak levels observed in 1998. This decrease was close to 

that expected in the A1 scenario of the 2010 Assessment and was primarily driven by declines in methyl 

bromide (CH3Br), with some recent contribution from an overall decrease in halons. Total bromine from 

halons had stopped increasing at the time of the last Assessment, and a decrease is now observable.

CH3Br mole fractions continued to decline during 2008–2012, and by 2012 had decreased to 7.0 ±

0.1 ppt, a reduction of 2.2 ppt from peak levels measured during 1996–1998. These atmospheric 

declines are driven primarily by continued decreases in total reported consumption of CH3Br from 

fumigation. As of 2009, reported consumption for quarantine and pre-shipment (QPS) uses, which are 

exempted uses (not controlled) under the Montreal Protocol, surpassed consumption for controlled (non-
ODSs and Other Gases of Interest

1.3

QPS) uses. As a result of the decrease in atmospheric CH3Br, the natural oceanic source is now 

comparable to the oceanic sink.

Stratospheric Inorganic Bromine

Total inorganic stratospheric bromine (Bry), derived from observations of bromine monoxide 

(BrO), was 20 (16–23) ppt in 2011, and had decreased at ~0.6 ± 0.1% yr-1 between peak levels 

observed in 2000–2001 and 2012. This decline is consistent with the decrease in total tropospheric 

organic Br based on measurements of CH3Br and the halons.

Equivalent Effective Stratospheric Chlorine (EESC)

EESC is a sum of chlorine and bromine derived from ODS tropospheric abundances weighted to reflect 

their expected depletion of stratospheric ozone. The growth and decline in EESC depends on a given 

tropospheric abundance propagating to the stratosphere with varying time lags (on the order of years) 

associated with transport. Therefore the EESC abundance, its peak timing, and its rate of decline, are 

different in different regions of the stratosphere.

By 2012, EESC had declined by about 10% in polar regions and about 15% in midlatitudes from their 

peak values, with CH3CCl3, CH3Br, and CFCs contributing approximately equally to these declines. 

This drop is about 40% of the decrease required for EESC in midlatitudes to return to the 1980 benchmark 

level, and about 20% of the decrease required for EESC in polar regions to return to the 1980 benchmark level.

Very Short-Lived Halogenated Substances (VSLS)

VSLS are defined as trace gases whose local lifetimes are comparable to, or shorter than, 

interhemispheric transport timescales and that have non-uniform tropospheric abundances. These local 

lifetimes typically vary substantially over time and space. As in prior Assessments, we consider species 

with annual mean lifetimes less than approximately 6 months to be VSLS. Of the VSLS identified in the 

current atmosphere, brominated and iodinated species are predominantly of oceanic origin, while the 

chlorinated species have significant industrial sources. These compounds will release their halogen 

atoms nearly immediately once they enter the stratosphere. The current contribution of chlorinated VSLS 

to Equivalent Chlorine (ECl) is about one-third as large as the contribution of VSLS brominated gases. 

Iodine from VSLS likely makes a minor contribution to ECl.

Total chlorinated VSLS source gases increased from 84 (70–117) ppt in 2008 to 91 (76–125) ppt in 

2012 in the lower troposphere. Dichloromethane (CH2Cl2), a VSLS that has predominantly anthropogenic sources, accounted for the majority of this change, with an increase of ~60% over the last decade.

The estimated contribution of chlorinated VSLS to total stratospheric chlorine remains small. A 

lack of data on their concentrations in the tropical tropopause layer (TTL) limits our ability to quantify 

their contribution to the inorganic chlorine loading in the lower stratosphere. Current tropospheric 

concentrations of chlorinated VSLS imply a source gas injection of 72 (50–95) ppt, with 64 ppt from 

anthropogenic emissions (e.g., CH2Cl2, CHCl3, 1,2 dichloroethane (CH2ClCH2Cl), tetrachloroethene 

(CCl2CCl2)). The product gases are estimated to contribute 0–50 ppt giving a total of ~ 95 ppt (50–145 

ppt) against a total of 3300 ppt of chlorine from long-lived ODSs entering the stratosphere.

There is further evidence that VSLS contribute ~5 (2–8) ppt to a total of ~20 ppt of stratospheric 

bromine. Estimates of this contribution from two independent approaches are in agreement. New data 

suggest that previous estimates of stratospheric Bry derived from BrO observations may in some cases 

have been overestimated, and imply a contribution of ~5 (2–8) ppt of bromine from VSLS. The second 

approach sums the quantities of observed, very short-lived source gases around the tropical tropopause 

with improved modeled estimates of VSLS product gas injection into the stratosphere, also giving a total 

contribution of VSLS to stratospheric bromine of ~5 (2–8) ppt.
Chapter 1

1.4

Updated Lifetime Estimates

The uncertainties of estimated lifetimes for key long-lived ozone-depleting and related substances 

are better quantified following the SPARC Lifetimes Assessment (Stratosphere-troposphere 

Processes And their Role in Climate, 2013). Of note is the change in the estimated lifetime of CFC-11 

(revised from 45 yr to 52 yr). The estimate of the total global lifetime of CCl4 (26 yr) remains unchanged 

from the previous Assessment, although estimates of the relative importance of the multiple loss 

processes have been revised.

Other Trace Gases That Directly Affect Ozone and Climate 

The emissions of CFCs, HCFCs, and HFCs in terms of their influence on climate (as measured by 

gigatonnes of carbon dioxide (CO2)-equivalent emissions) were roughly equal in 2012. However, the

emissions of HFCs are increasing rapidly, while the emissions of CFCs are going down and those of 

HCFCs are essentially unchanged. The 100-year GWP-weighted emissions for the sum of CFC, HCFC, 

and HFC emissions was 2.2 Gt CO2-equivalent in 2012. The sum of GWP-weighted emissions of CFCs 

was 0.73 ± 0.25 Gt CO2-equivalent yr-1 in 2012 and has decreased on average by 11.0 ± 1.2% yr-1 from 

2008 to 2012. The sum of HCFC emissions was 0.76 ± 0.12 Gt CO2-equivalent yr-1 in 2012 and has been 

essentially unchanged between 2008 and 2012. Finally, the sum of HFC emissions was 0.69 ± 0.12 Gt 

CO2-equivalent yr-1 in 2012 and has increased on average by 6.8 ± 0.9% yr-1 from 2008 to 2012. The HFC 

increase partially offsets the decrease by CFCs. Current emissions of HFCs are, however, are less than 

10% of peak CFC emissions in the early 1990s (>8 Gt CO2-equivalent yr-1).

From 2008 to 2012 the global mean mole fraction of nitrous oxide (N2O), which leads to ozone 

depletion in the stratosphere, increased by 3.4 parts per billion (ppb), to 325 ppb. With the 

atmospheric burden of CFC-12 decreasing, N2O is currently the third most important long-lived 

greenhouse gas contributing to radiative forcing (after CO2 and methane (CH4)).

Methane (CH4) is an important greenhouse gas and influences stratospheric ozone. In 2012 the average 

background global mole fraction of CH4 was 1808 ppb, with a growth rate of 5–6 ppb yr-1 from 2008 to 

2012. This is comparable to the 2006–2008 period when the CH4 growth rate began increasing again after 

several years of near-zero growth. The renewed increase is thought to result from a combination of 

increased CH4 emissions from tropical and high-latitude wetlands together with increasing anthropogenic 

(fossil fuel) emissions, though the relative contribution of the wetlands and fossil fuel sources is uncertain.

Hydrofluorocarbons (HFCs) used as ODS substitutes are increasing in the global atmosphere. The 

most abundant HFC, HFC-134a, reached a mole fraction of nearly 68 ppt in 2012 with an increase of 5 

ppt yr-1 (7.6%) in 2011–2012. HFC-125, -143a, and -32 have similar or even higher relative growth rates 

than HFC-134a, but their current abundances are considerably lower.

Worldwide emissions of HFC-23, a potent greenhouse gas and by-product of HCFC-22 production, 

reached a maximum of ~15 Gg in 2006, decreased to ~9 Gg in 2009, and then increased again to reach 

~13 Gg yr-1 in 2012. While efforts in non-Article 5 Parties mitigated an increasing portion of HFC-23 emissions through 2004, the temporary decrease in emissions after 2006 is consistent with destruction of HFC-23 

in Article 5 Parties owing to the Clean Development Mechanism (CDM) of the Kyoto Protocol. The average 

global mole fraction of HFC-23 reached 25 ppt in 2012, with an increase of nearly 1 ppt yr-1 in recent years.

Mole fractions of sulfur hexafluoride (SF6), nitrogen trifluoride (NF3), and sulfuryl fluoride (SO2F2) 

increased in recent years. Global averaged mole fractions of SF6 reached 7.6 ppt in 2012, with an annual 

increase of 0.3 ppt yr-1 (4% yr-1). Global averaged mole fractions of NF3 reached 0.86 ppt in 2011, with an 

annual increase of 0.1 ppt yr-1 (12% yr-1). Global averaged mole fractions of SO2F2 reached 1.8 ppt in 

2012, with an annual increase of 0.1 ppt yr-1 (5% yr-1). The considerable increases for these entirely 

anthropogenic, long-lived substances are caused by ongoing emissions.
ODSs and Other Gases of Interest

1.5

1.1 SUMMARY OF THE PREVIOUS OZONE ASSESSMENT

Chapter 1 of the 2010 Assessment report (Montzka and Reimann et al., 2011) provided evidence 

of continued reductions of the atmospheric abundance of most ozone-depleting substances (ODSs), 

resulting from phase-out of controlled ODS production and consumption under the Montreal Protocol. 

Total tropospheric chlorine and bromine from long-lived chemicals continued to decrease between 2005 

and 2008. The atmospheric reservoir for methyl chloroform (CH3CCl3) had reduced to the point that its 

contribution to the chlorine decline was surpassed by the chlorofluorocarbons (CFCs). Mole fractions of 

CFC-12, the single largest contributor to the atmospheric chlorine loading, declined for the first time in 

this period. The total tropospheric chlorine decline was however slower than expected because the sum of 

the CFC mole fractions did not drop as rapidly as projected and increases in hydrochlorofluorocarbons 

(HCFCs) were larger than anticipated. The stratospheric chlorine burden declined in accordance with the 

tropospheric decrease, within expected uncertainties. Chlorine-containing very short-lived substances 

(VSLS) and their degradation products contributed approximately 80 ppt (parts per trillion) of chlorine to

the stratosphere, which was about 2% of the contribution from the longer-lived ODSs.

Chapter 1 of the 2010 Assessment documented the continued discrepancy between emissions of carbon tetrachloride (CCl4) inferred from observed global trends with the much lower and more variable emissions 

derived from data reported to the United Nations Environment Programme (UNEP). These differences could 

not solely be explained by scaling the atmospheric lifetime. For other important ODSs (e.g., CFC-11), there 

was evidence that atmospheric lifetimes might be longer than reported in previous Assessments.

Tropospheric mole fractions of hydrofluorocarbons (HFCs), used as non-ozone-depleting ODS 

substitutes, continued to increase, which was reflected by an increase in column abundances of hydrogen 

fluoride (HF), one of their major degradation products. In total the sum of HFC emissions used as ODS 

replacements, weighted by direct, 100-year Global Warming Potentials (GWPs), increased by nearly 10%

yr-1 from 2004 to 2008. In addition, emissions of the very potent greenhouse gas HFC-23 (CHF3), which 

was mainly released from the production of HCFC-22 and therefore not labeled as an ODS replacement, 

had increased despite efforts to curb HFC-23 emissions.

The only regulated bromine compound still not decreasing in 2008 was halon-1301. The total 

tropospheric bromine levels from long-lived ODSs, however, continued to decrease because of the declining 

abundance of methyl bromide (CH3Br) and because the sum of halons had stopped increasing. For the first 

time, measurements of stratospheric bromine showed a slight decrease over this period. Slightly more than 

50% of the atmospheric bromine stemmed from sources not controlled by the Montreal Protocol (i.e., from 

natural sources and from quarantine and pre-shipment (QPS) uses of CH3Br). The contribution from mostly 

natural short-lived compounds such as dibromomethane (CH2Br2) and tribromomethane (CHBr3) and their 

degradation products to stratospheric bromine was estimated to be 1–8 ppt, which contributed substantially 

to the estimated total of 22.5 ppt of bromine in the stratosphere in 2008.

Equivalent Effective Stratospheric Chlorine (EESC) represents the overall influence on stratospheric 

ozone levels from the sum of the tropospheric abundances of chlorine and bromine ODSs. A discussion of the 

EESC concept can be found in Box 8-1 of the 2006 Assessment (Daniel and Velders, 2007). By the end of 

2008, the EESC abundance in the midlatitude stratosphere had decreased by about 11% from its peak value in 

1997. This represented 28% of the decrease required for EESC in the midlatitude stratosphere to return to the 

1980 benchmark level. In the polar stratosphere, EESC had decreased by about 5% from its peak value in 

2002, which is 10% of the decrease required for EESC in polar regions to return to the 1980 benchmark level.

1.2 LONGER-LIVED HALOGENATED SOURCE GASES

1.2.1 Updated Observations, Lifetimes, and Emissions

Global tropospheric observations of ODSs have been performed and updated by independent 

groups using both in situ and flask measurements as early as the late 1970s (Figure 1-1, Table 1-1). Data 
Chapter 1

1.6

from networks with global coverage (AGAGE: Advanced Global Atmospheric Gases Experiment; 

NOAA: National Oceanic and Atmospheric Administration; UCI: University of California, Irvine) are 

discussed primarily, except for substances where data from only one global network are available. For 

some ODSs, surface observations have been complemented with trends of total column measurements 

using satellite- and ground-based remote sensing techniques (Table 1-2).

Global steady-state lifetime estimates of the main ODSs and related substances appear in Table 1-

3. Most are taken directly from SPARC (2013) and were derived from a weighted average of the lifetimes 

using different methods. Global steady-state lifetimes are derived from a combination of partial lifetimes 

for tropospheric hydroxyl radical (OH) reactive loss, stratospheric loss, and ocean and soil loss. 

Furthermore, updates to atmospheric budgets (emissions and sinks) of ODSs are discussed. Global mean 

mole fractions, trends, and emissions were calculated by combining the global network data with a twodimensional model (Rigby et al., 2013, 2014).

1.2.1.1 CHLOROFLUOROCARBONS (CFCS)

Observations

The global surface mean dry air mole fractions of the three most abundant chlorofluorocarbons 

(CFC-12 (CCl2F2), CFC-11 (CCl3F), and CFC-113 (CCl2FCClF2)) continued to decline since the last 

Assessment (Figure 1-1 and Table 1-1). Between 2008 and 2012 the trends observed for these three ODSs 

are consistent (within uncertainties) with those anticipated in the A1-2010 scenario (Daniel and Velders et 

al., 2011). For these three ODSs, differences in global abundances estimated by the three global networks 

in Table 1-1 were less than 1% in 2011–2012. This is comparable to differences of 1–2% for the 

measurement of these substances evaluated within the International Halocarbons in Air Comparison 

Experiment (IHALACE) (Hall et al., 2014). Differences between the global networks are used not only 

for estimating the uncertainty of the measurement data themselves, but also for assessing the accuracy and 

reliability of global emission estimates, which make use of these data.

Recent changes in the Northern Hemisphere abundances of CFC-11, CFC-12, and CFC-113 

measured by ground-based infrared solar absorption spectroscopy (e.g., Zander et al., 2008) and spacebased instruments (Brown et al., 2011; Kellmann et al., 2012) are largely consistent (within uncertainties) 

with those measured at the surface between 2004 and 2010 (Figure 1-2 and Table 1-2). Only CFC-113 

from Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS) (Brown et al., 

2011) shows a faster decrease than the ground-based measurements, which could be caused by 

measurement issues in the space-based instrument for this compound.

Global mole fractions of both CFC-114 (CClF2CClF2) and CFC-115 (CClF2CF3) have remained 

nearly constant since 2008 (Table 1-1). Measurements of CFC-114 include a fraction due to CFC-114a 

(CCl2FCF3), which is estimated to be around 10%, based on measurements in the 1990s (Oram, 1999). 

Furthermore, CFC-112 (CCl2FCCl2F), -112a (CClF2CCl3), -113a (CCl3CF3), and HCFC-133a (CH2ClCF3) 

(Section 1.2.1.5) were recently determined to be present in the atmosphere, with mole fractions of less 

than 1 ppt in 2010 (Laube et al., 2014). Abundances of CFC-112 and CFC-112a are declining but those of 

CFC-113a (and HCFC-133a) are increasing. These newly detected ODSs are listed in the Montreal 

Protocol and contribute about 4 ppt or ~ 0.1% toward current levels of total chlorine, currently adding less 

than 0.5 ppt Cl yr-1.

Lifetimes and emissions

For CFC-11, a longer steady-state lifetime of 52 (43–67) years was recommended by SPARC 

(2013) compared with the 45-year lifetime used in the previous Assessments. Since the SPARC (2013) 

evaluation, a new CFC-11 UV absorption spectrum data set was reported by McGillen et al. (2013) that

significantly reduced the overall estimated uncertainty in the CFC-11 spectrum from ~20%, as reported in 

SPARC (2013), to ~4%. This leads to a substantially reduced contribution to the CFC-11 lifetime 

uncertainty due to uncertainties in CFC-11 photolysis. The recommended CFC-11 steady-state lifetime of 

SPARC (2013) and its estimated uncertainty range, however, do not change significantly as a result. In 
ODSs and Other Gases of Interest

1.7

SPARC (2013) the lifetime and its range were primarily determined by the differences between 

observational data and various 3-D model calculations.

Another notable change discussed in SPARC (2013) was for CFC-115, for which the total 

lifetime was revised from 1020 to 540 years based on new O(1D) + CFC-115 reaction rate data from 

Baasandorj et al. (2013).

Results since SPARC (2013) include a suggested revision of the CFC-113a lifetime from ~45 to 59 

(31–305) years by Laube et al. (2014), although uncertainties of the new estimate include the old number.

Global top-down emissions of CFC-11 derived from atmospheric observations, considering its 

new lifetime of 52 years, have been declining slowly over the past decade and are estimated to have been 

57 (46–68) Gg in 2012 (Figure 1-3). Bottom-up estimated emissions are only available until 2003 and 

averaged 73 Gg yr-1 in the period 2000–2003 (UNEP, 2006). This was 19 Gg yr-1 smaller than estimated 

emissions using measurement-based top-down methods and a 52-year lifetime (Figure 1-3). The increase 

of the lifetime estimate from 45 years to 52 years considerably reduces the gap for CFC-11 emission 

estimates by the two methods from the previous Assessment (Montzka and Reimann et al., 2011).

Global CFC-12 emissions have been declining more rapidly than those of CFC-11. Top-down 

estimates (Figure 1-3) indicate emissions of CFC-12 were decreasing at a rate of ~7 Gg yr-1 in recent 

years to 40 (26–54) Gg in 2012. Global CFC-113 emissions have been consistently lower than 5 Gg yr-1

over recent years.

Emissions of the newly detected CFC-113a were estimated at 2 Gg in 2012 (Figure 1-3) and they 

could be caused by its usage as an intermediate in agrochemical production (Laube et al., 2014) or as a 

feedstock for HFC-125 (CHF2CF3) and HFC-134a (CH2FCF3) production (UNEP, 2013a). Although 

global production numbers for these HFCs are not available, the rapid increases in mole fractions and 

global emissions of HFC-125 and HFC-134a in the atmosphere (Figures 1-24, 1-25, and Table 1-14) 

indicate the potential for increasing releases of CFC-113a.

Measurements within specific regions and meteorological models are used to estimate emissions 

of ODSs and other halocarbons on regional scales. These regional source estimates are prone to 

considerable uncertainties due to inaccuracies in meteorological data, transport models, and in some 

instances, seasonal variations of emission. The summed effect of the errors in these parameters and their 

extrapolations can lead to large uncertainties for estimated regional emissions (see, e.g., Figure 1-4). When 

studied regions are substantially different from national scales, additional errors can be introduced by 

extrapolation of the regional estimates to national scales, which are often compared to national inventorybased estimates. Regional emissions of CFC-11, -12, and -113 were predominantly estimated to be from 

East Asia in recent years, due to the phase-out of these compounds in important Article 5 countries in 

2010. In Figure 1-4 historical and projected bottom-up emissions in China (Wan et al., 2009) are compared 

with top-down regional emissions derived from atmospheric measurements (Palmer et al., 2003; Vollmer 

et al., 2009; Kim et al., 2010; An et al., 2012; Fang et al., 2012). The concurrent decline of emissions seen 

by both independent methods (top-down and bottom-up) shows the success of the Montreal Protocol in 

substantially decreasing CFC emissions in China. In 2000 CFC-12 top-down emission estimates were more 

than a factor of two higher than inventory-based estimates, but both estimates compare better in most 

recent years. Whereas CFC-11 emissions are still substantial but also declining, both top-down and 

bottom-up emissions of CFC-113, which was mostly used as a solvent, were found to be consistently small 

in recent years. However, measurements of these CFCs in urban environments in China, for example in the 

Pearl River Delta (Shao et al., 2011; Wu et al., 2014), still show mole fraction enhancements above 

background levels, indicating ongoing emissions from in-use equipment.

Recent estimates of emissions of CFC-11 and CFC-12 in the U.S. and Europe (Millet et al., 2009; 

Miller et al., 2012; Keller et al., 2012) were still comparable to those in China, although new production 

of CFCs for use was restricted in the U.S. and Europe in 1996/1995 (i.e., 14/15 years ahead of restrictions 

in China). For CFC-113, enhancements above background levels were not detected in the U.S. by Gentner 

et al. (2010) or Millet et al. (2009), suggesting very low emissions in this region of the world. In a sourcespecific study, Hodson et al. (2010) found that landfills were only small sources of CFC-11, CFC-12, and 

CFC-113 in the U.S. and in the United Kingdom.
Chapter 1

1.8

Figure 1-1. Mean global surface mole fractions (expressed as dry air mole fractions in parts per trillion or 

ppt) of ozone-depleting substances from independent sampling networks and from scenario A1 of the 

previous Ozone Assessments (Daniel and Velders et al., 2007, 2011) over the past 22 years (1990–2012). 

Measured global surface annual means are shown as red lines (NOAA data), black lines (AGAGE data), 

and blue lines (University of East Anglia (UEA) Southern Hemisphere (S.H.) data, (continued next page)
ODSs and Other Gases of Interest

1.9

(Figure 1-1, continued) using Cape Grim archived air). Mole fractions from scenario A1 from the previous 

assessment (green lines) were derived to match observations in years before 2009 (Daniel and Velders et 

al., 2011). The scenario A1-2010 results shown in years after 2008 are projections made for 2009. Mole 

fractions from scenario A1 from the 2006 Assessment (green-dashed lines) were derived to match 

observations in years before 2005 (Daniel and Velders et al., 2007). The scenario A1-2006 results shown in 

years after 2004 are projections made in 2005.
Chapter 1

1.10

Table 1-1. Measured mole fractions and changes of ozone-depleting gases from ground-based 

sampling networks.

Chemical 

Formula

Common or 

Industrial Name

Annual Mean

Mole Fraction (ppt)

2008 2011 2012

 Change

 (2011–2012)

(ppt yr-1) (% yr-1)

Network, Method

CFCs

CCl3F CFC-11 243.4 237.6 235.5 −2.1 −0.9 AGAGE, in situ 1

244.8 238.6 236.3 −2.3 −1.0 NOAA, flask & in situ

244.2 237.9 235.3 −2.6 −1.1 UCI, flask

CCl2F2 CFC-12 537.5 530.4 527.5 −2.9 −0.5 AGAGE, in situ

535.3 527.2 524.4 −2.9 −0.5 NOAA, flask & in situ

532.6 525.3 522.5 −2.8 −0.5 UCI, flask

CCl2FCCl2F CFC-112 0.45 0.45 0.44 −0.01 −2 UEA, flask (Cape Grim)

CCl3CClF2 CFC-112a 0.065 0.066 0.064 −0.002 −3 UEA, flask (Cape Grim)

CCl2FCClF2 CFC-113 76.7 74.4 73.6 −0.8 −1.1 AGAGE, in situ

76.5 74.5 73.8 −0.6 −0.8 NOAA, flask & in situ

77.1 74.9 74.2 −0.7 −0.9 UCI, flask

CCl3CF3 CFC-113a 0.39 0.44 0.48 0.04 10 UEA, flask (Cape Grim)

CClF2CClF2 CFC-114 2 16.46 16.37 16.33 −0.04 −0.2 AGAGE, in situ

15.95 15.77 15.75 −0.02 −0.1 NIES, in situ (Japan)

CClF2CF3 CFC-115 8.38 8.39 8.40 0.01 0.2 AGAGE, in situ

8.32 8.44 8.48 0.04 0.5 NIES, in situ (Japan)

HCFCs

CHClF2 HCFC-22 191.8 214.2 219.8 5.6 2.6 AGAGE, in situ

190.9 212.7 218.0 5.3 2.5 NOAA, flask

188.3 209.0 214.5 5.5 2.6 UCI, flask

CHClFCF3 HCFC-124 1.48 1.34 1.30 −0.04 −3 AGAGE, in situ

CH2ClCF3 HCFC-133a 0.275 0.313 0.365 0.052 17 UEA, flask (Cape Grim)

CH3CCl2F HCFC-141b 19.5 21.4 22.5 1.1 5.1 AGAGE, in situ

19.3 21.3 22.3 1.0 4.4 NOAA, flask

18.8 20.8 21.8 1.0 4.8 UCI, flask

CH3CClF2 HCFC-142b 19.0 21.5 22.0 0.5 2.4 AGAGE, in situ

18.5 20.9 21.3 0.4 2.0 NOAA, flask

18.0 21.0 21.8 0.8 3.8 UCI, flask

Halons

CBr2F2 halon-1202 0.026 0.020 0.019 −0.001 −5 UEA, flask (Cape Grim)

(continued next page)
ODSs and Other Gases of Interest

1.11

Chemical 

Formula

Common or 

Industrial Name

Annual Mean

Mole Fraction (ppt)

2008 2011 2012

 Change

 (2011–2012)

(ppt yr-1) (% yr-1)

Network, Method

Table 1-1, continued.

CBrClF2 halon-1211 4.29 4.09 4.01 −0.08 −2.0 AGAGE, in situ

4.20 4.00 3.92 −0.08 −2.0 NOAA, flask 3

4.25 4.03 3.96 −0.07 −1.7 NOAA, in situ

4.24 4.18 4.14 −0.04 −1.0 UCI, flask

CBrF3 halon-1301 3.20 3.27 3.30 0.03 0.9 AGAGE, in situ

3.12 3.18 3.22 0.04 1.1 NOAA, flask

CBrF2CBrF2 halon-2402 0.47 0.45 0.44 −0.01 −1.3 AGAGE, in situ 4

0.47 0.45 0.44 −0.01 −1.4 NOAA, flask

0.41 0.394 0.387 −0.007 −2 UEA, flask (Cape Grim)

Chlorocarbons

CH3Cl methyl chloride 544.2 530.3 537.1 6.8 1.3 AGAGE, in situ

546.6 537.1 542.2 5.0 0.9 NOAA, flask 

546 - - - - NOAA, in situ

CCl4 carbon 

tetrachloride

88.6 85.2 84.2 −1.1 −1.2 AGAGE, in situ

90.5 86.4 85.1 −1.4 −1.6 NOAA, flask & in situ

91.5 87.8 86.7 −1.1 −1.3 UCI, flask

CH3CCl3 methyl 

chloroform

10.6 6.26 5.20 −1.06 −17 AGAGE, in situ

10.8 6.31 5.25 −1.06 −17 NOAA, flask

11.5 6.8 5.7 −1.1 −16 UCI, flask 

Bromocarbons

CH3Br methyl bromide 7.47 7.14 7.07 −0.11 −1.0 AGAGE, in situ

7.33 7.07 6.95 −0.12 −1.7 NOAA, flask

Mole fractions in this table represent independent estimates measured by different groups for the years indicated. Results in bold 

text are estimates of global surface mean mole fractions. Regional data from relatively unpolluted sites are shown (in italics) 

where global estimates are not available, where global estimates are available from only one network, or where data from global 

networks do not represent independent calibration scales (e.g., halon-2402). Absolute changes (ppt yr-1) are calculated as the 

difference in annual means; relative changes (% yr-1) are the same difference relative to the 2011 value. Small differences 

between values from previous Assessments are due to changes in calibration scale and methods for estimating global mean mole 

fractions from a limited number of sampling sites.

These observations are updated from the following sources: Rowland et al. (1982); Butler et al. (1998); Fraser et al. (1999); 

Montzka et al. (1999); Oram (1999); Montzka et al. (2000); Prinn et al. (2000); Montzka et al. (2003); O’Doherty et al. (2004); 

Yokouchi et al. (2006); Simpson et al. (2007); Miller et al. (2008); Montzka et al. (2009); Newland et al. (2013); Laube et al. 

(2014). AGAGE, Advanced Global Atmospheric Gases Experiment (http://agage.eas.gatech.edu/); NOAA, National Oceanic and 

Atmospheric Administration, U.S. (http://www.esrl.noaa.gov/gmd/dv/site/); UEA, University of East Anglia, United Kingdom 

(http://www.uea.ac.uk/environmental-sciences/research/marine-and-atmospheric-sciences-group); UCI, University of California, 

Irvine, U.S. (http://ps.uci.edu/~rowlandblake/research_atmos.html); NIES, National Institute for Environmental Studies, Japan

(http://db.cger.nies.go.jp/gem/moni-e/warm/Ground/st01.html). Cape Grim: Cape Grim Baseline Air Pollution Station, Australia.

Notes: 1Global mean estimates from AGAGE are calculated using atmospheric data and a 12-box model (Cunnold et al., 1983; 

Rigby et al., 2013). AGAGE calibrations as specified in CDIAC (2014) and related primary publications. 2Measurements of 

CFC-114 are a combination of CFC-114 and the CFC-114a isomer, with an assumed relative contribution of 10% CFC-114a 

(Oram, 1999). 3The NOAA halon-1211 data have been updated following an instrument change in 2009. 4AGAGE halon-2402 

data are on the NOAA scale.
Chapter 1

1.12

Table 1-2. Comparison of annual trends of ODSs, HFC-23, CF4, and SF6 from in-situ measurements vs. remote sensing measurements. Relative trends in ODSs and halogenated greenhouse 

gases for the common 2004–2010 time period (except when specified) derived from in-situ surface 

measurements and remote sensing observations from the ground and from space. Surface trends were 

derived from monthly mean mole fractions, weighted by surface area in the region 30°N–90°N. Shown are 

the average and standard deviation of trends derived independently from NOAA and AGAGE data (% yr-1

relative to 2007 annual mean). For CF4 and HFC-23, only AGAGE data were used, and the uncertainty 

was derived from uncertainties (one standard deviation) in the slope and 2007 annual mean. For HFC-23, 

global mean data were used from 2007 through 2010, supplemented with data from Miller et al. (2010) for 

2004–2007. Ground-based remote sensing trends were derived from daily mean total column measurements performed at Jungfraujoch (46.5oN). The ACE-FTS trends were determined using tropical occultations (30oN–30oS), after averaging the mixing ratios in molecule-dependent altitude ranges (Brown et al., 

2011). For HFC-23, the 40oN–40oS occultations were considered in the 10–25 km altitude range. For 

MIPAS CFC-11 and -12, mean rates of change for the 20oN–20oS and 10–15 km altitude range are provided, including observations between 2002 and 2011 (Kellmann et al., 2012). For SF6, the trend characterizes the 2006–2009 time period between 17.5oN–17.5oS latitude and 9–15 km altitude (Stiller et al., 2012).

Substance Annual Trend 2004–2010

(% yr-1 relative to 2007)

Data Sources

In-situ

30°N–90°N

Remote sensing 

ground 

(total columns)

Remote sensing

satellite

CFC-11 −0.84 ± 0.09 −0.99 ± 0.10 MIPAS:

−1.03±0.09

ACE-FTS:

−0.9 ± 0.1

NOAA, AGAGE

Zander et al., 2008 

Kellmann et al., 

2012

Brown et al., 2011

CFC-12 −0.39 ± 0.05 −0.38 ± 0.07 MIPAS:

−0.51± 0.09

ACE-FTS:

−0.4 ± 0.1

NOAA, AGAGE

Zander et al., 2008 

Kellmann et al., 

2012

Brown et al., 2011

CFC-113 −0.93 ± 0.02 ACE-FTS:

−1.2 ± 0.1

NOAA, AGAGE

Brown et al., 2011

CCl4 −1.35 ± 0.08 −1.31 ± 0.15 ACE-FTS

−1.2 ± 0.1

NOAA, AGAGE

Rinsland et al., 2012

Brown et al., 2011

HCFC-22 3.97 ± 0.06 3.52 ± 0.08 ACE-FTS

3.7 ± 0.1

NOAA, AGAGE

Zander et al., 2008

Brown et al., 2011

HCFC-141b 2.57 ± 0.07 ACE-FTS

0.74 ± 0.5

NOAA, AGAGE

Brown et al., 2011

HCFC-142b 5.44 ± 0.03 ACE-FTS

7.0 ± 0.4

NOAA, AGAGE

Brown et al., 2011

HFC-23 4.2 ± 0.2 ACE-FTS

3.9 ± 1.2

AGAGE

Harrison et al., 2012

CF4 0.86 ± 0.01 1.02 ± 0.05 ACE-FTS

0.74 ± 0.04

AGAGE

Mahieu et al., 2014

Brown et al., 2011

SF6 4.27 ± 0.07 4.14 ± 0.32 MIPAS

4.3 

ACE-FTS:

4.2 ± 0.1

NOAA, AGAGE

Zander et al., 2008

Stiller et al., 2012

Brown et al., 2011
ODSs and Other Gases of Interest

1.13

Table 1-3. Steady-state lifetimes for selected long-lived halocarbons (total lifetimes greater than 0.5 years). 

Total and partial lifetimes are defined in Box 1-1. Compounds included in the SPARC (2013) lifetime report are given in 

bold with the total lifetimes calculated using the SPARC (2013) atmospheric partial lifetime recommendation and the 

ocean and soil partial lifetimes reported here; stratospheric partial lifetimes for these compounds were taken from the 

SPARC (2013) model-mean unless noted otherwise. The footnotes contain specific details for each compound in the 

table. See Table 1-5 in Section 1.3 for local lifetime estimates for very short-lived substances (VSLS) and Table 1-11 in 

Section 1.3 for lifetimes of potential ODS replacement compounds.

Industrial 

Designation

or 

Common Name

Chemical 

Formula

WMO 

(2011)

Total 

Lifetime

 (years)

New 

Total

Lifetime a

 (years)

SPARC (2013)

Atmospheric Partial

Lifetime & Estimated 

Uncertainty Range b

(years)

Tropospheric 

OH Partial

Lifetime c

 (years)

Stratospheric 

Partial

Lifetime

 (years)

Ocean

Partial

Lifetime

 (years) d

Notes

Halogenated Methanes

HFC-41 CH3F 2.8 2.8 2.9 ~65 1340 1, 2

HFC-32 CH2F2 5.2 5.4 5.4 [4.0–8.2] 5.5 124 1

HFC-23 CHF3 222 228 228 [160–394] 243 4420 1

PFC-14 (Carbon 

tetrafluoride)

CF4 >50,000 >50,000 3

Methyl chloride CH3Cl 1.0 0.9 1.3 [0.9–2.0] 1.57 30.4 e 12 4–7

Carbon 

tetrachloride

CCl4 26 26 44 (36-58) [33-67] 44 f 94 7

HCFC-31 CH2ClF 1.3 1.2 1.3 ~35 1, 2, 8

HCFC-22 CHClF2 11.9 11.9 12 [9.3–18] 13.0 161 1174 4

HCFC-21 CHCl2F 1.7 1.7 1.8 ~35 673 1, 2, 8

CFC-11 CCl3F 45 52 52 (43–67) [35–89] 55 9

CFC-12 CCl2F2 100 102 102 (88–122) [78–151] 95.5 9

CFC-13 CClF3 640 640 3

Methyl bromide CH3Br 0.8 0.8 1.5 [1.1–2.3] 1.8 26.3e 3.1 4, 7, 10

Halon-1201 CHBrF2 5.2 5.1 6.0 ~35 1, 2, 8

Halon-1301 CBrF3 65 72 72 (61–89) [58–97] 73.5 9

Halon-1211 CBrClF2 16 16 16 [10–39] 41 11

Halon-1202 CBr2F2 2.9 2.5 2.5 [1.5–7.3] 36 11

Halogenated Ethanes

HFC-152a CH3CHF2 1.5 1.6 1.6 [1.2–2.2] 1.55 39 1958 1

HFC-143 CH2FCHF2 3.5 3.5 3.70 ~75 1, 2

HFC-143a CH3CF3 47.1 51 51 [38–81] 57 612 1

HFC-134 CHF2CHF2 9.7 9.7 10.5 ~135 1, 2

HFC-134a CH2FCF3 13.4 14 14 [10–21] 14.1 267 5909 4

HFC-125 CHF2CF3 28.2 31 31 [22–48] 32 351 10650 1

PFC-116 

(Perfluoroethane)

CF3CF3 >10,000 >10,000 3

Methyl chloroform CH3CCl3 5.0 5.0 g 6.1 [4.7–5.4] 6.1 f 38 94 12

HCFC-141b CH3CCl2F 9.2 9.4 9.4 [7.2–18] 10.7 72.3 9190 1

HCFC-142b CH3CClF2 17.2 18 18 [14–25] 19.3 212 122200 1

HCFC-133a CH2ClCF3 4.3 4.0 4.5 41 1, 2, 13

HCFC-123 CHCl2CF3 1.3 1.3 1.35 36 1, 14

HCFC-123a CHClFCF2Cl 4.0 4.0 4.3 ~65 1, 2, 8

HCFC-123b CHF2CCl2F 6.2 ~6 ~7 ~50 2, 8, 15

HCFC-124 CHClFCF3 5.9 5.9 6.3 111 1855 1, 14

(continued next page)
Chapter 1

1.14

Industrial 

Designation

or 

Common Name

Chemical 

Formula

WMO 

(2011)

Total 

Lifetime

 (years)

New 

Total

Lifetime a

 (years)

SPARC (2013)

Atmospheric Partial

Lifetime & Estimated 

Uncertainty Range b

(years)

Tropospheric 

OH Partial

Lifetime c

 (years)

Stratospheric 

Partial

Lifetime

 (years)

Ocean

Partial

Lifetime

 (years) d

Notes

HCFC-124a CHF2CClF2 9.1 ~9.2 ~10 ~120 2, 16

CFC-112 CCl2FCCl2F 59 59 13

CFC-112a CClF2CCl3 51 51 13

CFC-113 CCl2FCClF2 85 93 93 (82–109) [69–138] 88.4 9, 17

CFC-113a CCl3CF3 ~45 59 59 13

CFC-114 CClF2CClF2 190 189 189 [153–247] 191 9, 17

CFC-114a CCl2FCF3 ~100 ~100 ~100 18

CFC-115 CClF2CF3 1020 540 540 [404–813] 664 19

Halon-2311 

(Halothane)

CHBrClCF3 1.0 1.0 1.1 ~16 1, 2, 8

Halon-2402 CBrF2CBrF2 20 28 28 [20–45] 41 11

Halogenated Propanes

HFC-263fb CH3CH2CF3 1.2 1.1 1.16 ~40 1, 2

HFC-245ca CH2FCF2CHF2 6.5 6.5 6.9 ~105 1, 2

HFC-245ea CHF2CHFCHF2 3.2 3.2 3.4 ~70 1, 2

HFC-245eb CH2FCHFCF3 3.1 3.2 3.3 ~70 1, 2

HFC-245fa CHF2CH2CF3 7.7 7.9 7.9 [5.5–14] 8.2 149 1

HFC-236cb CH2FCF2CF3 13.1 ~13 ~14 ~240 20

HFC-236ea CHF2CHFCF3 11.0 11.0 11.9 ~145 1, 2

HFC-236fa CF3CH2CF3 242 222 253 ~1800 1, 21

HFC-227ea CF3CHFCF3 38.9 36 36 [25–61] 37.5 673 4, 22

PFC-218 

(Perfluoropropane)

CF3CF2CF3 2,600 ~7,000 23

PFC-c216 

(Perfluorocyclopropane)

c-C3F6 ~3,000 ~4,000 23

HCFC-243cc CH3CF2CCl2F 19.5 19.5 27.1 ~70 1, 2, 8

HCFC-234fb CF3CH2CCl2F 49 ~45 98 ~85 1, 2, 8

HCFC-225ca CHCl2CF2CF3 1.9 1.9 2.0 44 1, 14

HCFC-225cb CHClFCF2CClF2 5.9 5.9 6.3 101 1, 14

Halogenated Higher Alkanes

HFC-365mfc CH3CF2CH2CF3 8.7 8.7 9.3 ~125 1, 2

HFC-356mcf CH2FCH2CF2CF3 1.3 1.2 1.26 ~40 1, 2

HFC-356mff CF3CH2CH2CF3 8.3 8.3 8.9 ~120 1, 2

HFC-338pcc CHF2CF2CF2CHF2 12.9 12.9 14.0 ~160 1, 2

HFC-329p CHF2CF2CF2CF3 28.4 ~30 ~34 ~260 2, 24

PFC-C318 

(Perfluorocyclobutane)

c-C4F8 3,200 3,200 3

PFC-31-10 

(Perfluorobutane)

C4F10 2,600 ~5,000 23

(E)-R316c ((E)-1,2-

dichlorohexafluorocyclobutane)

(E)-1,2-c-C4F6Cl2 75 76 9, 25

(Z)-R316c ((Z)-1,2-

dichlorohexafluorocyclobutane)

(Z)-1,2-c-C4F6Cl2 114 115 9, 25

(continued next page)
ODSs and Other Gases of Interest

1.15

Industrial 

Designation

or 

Common Name

Chemical 

Formula

WMO 

(2011)

Total 

Lifetime

 (years)

New 

Total

Lifetime a

 (years)

SPARC (2013)

Atmospheric Partial

Lifetime & Estimated 

Uncertainty Range b

(years)

Tropospheric 

OH Partial

Lifetime c

 (years)

Stratospheric 

Partial

Lifetime

 (years)

Ocean

Partial

Lifetime

 (years) d

Notes

HFC-43-10mee CF3CHFCHFCF2CF3 16.1 16.1 17.9 157 1, 14

HFC-458mfcf CF3CH2CF2CH2CF3 22.9 22.9 25.5 ~225 1, 2

PFC-41-12 

(Perfluoropentane)

C5F12 4,100 4,100 3

HFC-55-10mcff CF3CF2CH2CH2CF2CF3 7.5 7.5 8.0 ~115 1, 2

HFC-52-13p CHF2CF2CF2CF2CF2CF3 32.2 32.7 37.0 ~280 2, 26

PFC-51-14 

(Perfluorohexane)

C6F14 3,100 3,100 3

PFC-61-16 

(Perfluoroheptane)

C7F16 ~3,000 ~3,000 23

PFC-71-18 

(Perfluorooctane) C8F18

~3,000 23

Perfluorodecalin C10F18, (E)- and (Z)-isomers ~2,000 ~2,000 23

Fluorinated Alcohols

1,1,1,3,3,3-hexafluoroisopropanol(CF3)2CHOH 1.9 1.9 2.0 ~50 1, 2

Halogenated Ethers

HFE-143a CH3OCF3 4.8 4.8 5.1 ~90 1, 2

HFE-134 CHF2OCHF2 24.4 25.4 28.4 ~240 1, 2

HFE-125 CHF2OCF3 119 119 147 ~620 1, 2

HFE-227ea CF3OCHFCF3 51.6 46.7 54 ~345 1, 2

HCFE-235da2 

(Isoflurane)

CHF2OCHClCF3 3.5 3.5 3.7 ~55 1, 2, 27

HFE-236ea2 

(Desflurane)

CHF2OCHFCF3 10.8 10.8 11.7 ~145 1, 2

HFE-236fa CF3OCH2CF3 7.5 ~7.5 ~8 ~115 2, 28

HFE-245fa1 CF3OCH2CHF2 6.6 ~6.6 ~7 ~105 2, 29

HFE-245fa2 CHF2OCH2CF3 5.5 5.5 5.8 ~95 1, 2

HFE-245cb2 CH3OCF2CF3 4.9 5.0 5.24 ~90 1, 2

HFE-254cb2 CH3OCF2CHF2 2.5 2.5 2.62 ~60 1, 2

HFE-236ca CHF2OCF2CHF2 20.8 20.8 23.1 ~210 1, 2

HFE-235ca2 

(Enflurane)

CHF2OCF2CHFCl 4.3 4.3 4.62 ~70 2, 8, 30

HFE–329mcc2 CF3CF2OCF2CHF2 22.5 ~25 23–34 ~220 2, 31

HFE–338mcf2 CF3CF2OCH2CF3 7.5 ~7.5 ~8 ~130 2, 32

HFE–347mcc3 CH3OCF2CF2CF3 5.0 5.0 5.3 ~90 1, 2

HFE–347mcf2 CF3CF2OCH2CHF2 6.6 ~6.6 ~7 ~105 2, 33

HFC-347mcf CHF2OCH2CF2CF3 5.7 5.6 6.0 ~95 1, 2

HFE-347pcf2 CF3CH2OCF2CHF2 6.0 5.9 6.3 ~100 1, 2

HFE–356mec3 CH3OCF2CHFCF3 ~3 ~3 ~3 ~65 2, 34

HFE–356pcc3 CH3OCF2CF2CHF2 ~3 ~3 ~3 ~65 2, 34

HFE–356pcf2 CHF2CH2OCF2CHF2 5.7 ~6 ~6 ~95 2, 35

HFE–356pcf3 CHF2OCH2CF2CHF2 3.5 3.5 3.7 ~75 1, 2

HFE-347mmz1

(Sevoflurane)

(CF3)2CHOCH2F 2.2 ~2 ~2 ~50 2, 36

HFE-338mmz1 (CF3)2CHOCHF2 21.2 21.2 23.5 ~215 1, 2

(continued next page)
Chapter 1

1.16

Industrial 

Designation

or 

Common Name

Chemical 

Formula

WMO 

(2011)

Total 

Lifetime

 (years)

New 

Total

Lifetime a

 (years)

SPARC (2013)

Atmospheric Partial

Lifetime & Estimated 

Uncertainty Range b

(years)

Tropospheric 

OH Partial

Lifetime c

 (years)

Stratospheric 

Partial

Lifetime

 (years)

Ocean

Partial

Lifetime

 (years) d

Notes

Perfluoroisopropyl 

methyl ether

(CF3)2CFOCH3 3.7 3.6 3.8 ~75 1, 2

HFE-7100 CH3O(CF2)3CF3 4.7 4.7 5.0 ~85 1, 2

HFE-54-11mecf CF3CHFCF2OCH2CF2CF3 8.8 8.8 9.5 ~125 2, 37

HFE-569sf2 CH3CH2O(CF2)3CF3 0.8 ~0.8 ~0.8 ~30 2, 38

HFE–236ca12 CHF2OCF2OCHF2 25.0 25.0 28.0 235 1, 2

HFE–338pcc13 CHF2OCF2CF2OCHF2 12.9 12.9 14.0 ~160 1, 2

HFE–43–10pccc CHF2OCF2OCF2CF2OCHF2 13.5 13.5 14.7 ~165 1, 2

Trifluoromethyl 

formate

CF3OC(O)H <3.5 <3.5 3.7 ~75 2, 39, 

40

Perfluoroethyl 

formate

C2F5OC(O)H <3.5 <3.5 3.7 ~75 2, 40, 

41

Perfluoro-n-propyl 

formate

n-C3F7OC(O)H <2.6 <2.6 2.7 ~60 2, 40, 

41

Other Fluorinated Compounds

TrifluoromethylsulfurpentafluorideSF5CF3 650–950 650–950 42

Sulfur hexafluoride SF6 3,200 3,200 3

Nitrogen 

trifluoride

NF3 500 569 740 43

Sulfuryl fluoride SO2F2 36 36 >300 630 40 44

a

 Total lifetime includes tropospheric OH and Cl atom reaction and photolysis loss, stratospheric loss due to reaction (OH and O(1D)) and photolysis, and ocean and 

soil uptake as noted in the table. b

 The lifetimes given in parenthesis () represent the “most likely” lifetime range, while the lifetimes given in brackets [] represent the “possible” lifetime range, see 

SPARC (2013). c

 Lifetime for tropospheric loss due to reaction with OH calculated relative to the lifetime for CH3CCl3, (6.1 years) and a temperature of 272 K (see Box 1-1). d

 Ocean lifetimes were taken from Yvon-Lewis and Butler (2002) unless noted otherwise. e

 Stratospheric lifetime from Chapter 5 of SPARC (2013). f

 Stratospheric lifetime from SPARC (2013) was based on both tracer (40 years) and model-mean (49 years) derived lifetimes. g

 The value of τOH of 6.1 years for methyl chloroform was derived from its measured overall lifetime of 5.0 years (Prinn et al., 2005; Clerbaux and Cunnold et al., 

2007), taking into account an ocean partial lifetime of 94 years and stratospheric partial lifetime of 38 years.

Notes

1. OH rate coefficient data taken from Sander et al. (2011).

2. Stratospheric reactive loss (O(1D) and OH) partial lifetime estimate was based on an empirical correlation derived from data reported in Naik et al. (2000); 

log(Stratospheric reactive partial lifetime) = 1.537 + 0.5788*log(Tropospheric OH partial lifetime). This correlation was used in WMO (2011).

3. Total lifetime is a best estimate taken from Ravishankara et al. (1993) that includes mesospheric loss due to Lyman-α (121.567 nm) photolysis.

4. OH rate coefficient data taken from SPARC (2013) Chapter 3.

5. Lifetime due to reaction with Cl atom of 259 years taken from the SPARC (2013) Chapter 5 model-mean.

6. Ocean lifetime taken from Hu et al. (2013).

7. Total lifetime also includes soil uptake partial lifetimes: 4.2 years for CH3Cl (Hu, 2012), 195 years for CCl4 (Montzka and Reimann et al., 2011), and 3.35 years 

for CH3Br (Montzka and Reimann et al., 2011).

8. Stratospheric photolysis lifetime was estimated using the empirical relationship given in Orkin et al. (2013a).

9. Tropospheric UV photolysis partial lifetime: 1870 years for CFC-11, 11600 years for CFC-12, 4490 years for halon-1301, 7620 years for CFC-113, 19600 years 

for CFC-114, 3600 years for (E)-R316c, and 10570 years for (Z)-R316c.

10. Ocean lifetime taken from Hu et al. (2012).

11. Lifetimes from 2-D model calculations using cross section data from Papanastasiou et al. (2013). The total lifetime includes a tropospheric photolysis partial 

lifetimes: 27.2 years for halon-1211, 2.74 years for halon-1202, and 85.5 years for halon-2402.

12. Tropospheric OH partial lifetime calculated from an overall lifetime of 5.0 years derived from the AGAGE and NOAA networks using a stratospheric partial 

lifetime of 38 years and an ocean partial lifetime of 94 years (Prinn et al., 2005).

13. Stratospheric partial lifetime of 51 (27–264) years taken from Laube et al. (2014) and scaled to a CFC-11 lifetime of 52 years.

14. Stratospheric partial lifetime taken from Naik et al. (2000).

15. Tropospheric OH partial lifetime estimated from that for CHF2CF3 taking into account the effects of chlorine substitution on the rate coefficients for CH3CF3 and 

CH3CFCl2.

16. Tropospheric OH partial lifetime estimated from that for CHF2CF3 taking into account the effects of chlorine substitution on the rate coefficients for CH3CF3 and 

CH3CF2Cl; stratospheric photolysis estimated to be the same as for CF3CF2Cl of 1590 years from SPARC (2013) Chapter 5 model mean.

17. The revised O(1D) rate coefficient recommended in SPARC (2013) Chapter 3 would decrease the model calculated stratospheric partial lifetime slightly.

18. UV photolysis is the expected predominant stratospheric loss process, however, no UV absorption spectrum data are available. Lifetimes assumed to be similar to 

CFC-12.
ODSs and Other Gases of Interest

1.17

19. Stratospheric partial lifetime from 2-D model calculations using O(1D) rate coefficient data from Baasandorj et al. (2013). The total lifetime includes mesospheric 

loss due to Lyman-α (121.567 nm) photolysis.

20. Lifetimes estimated to be similar to that of HFC-134a (CH2FCF3).

21. Stratospheric partial lifetime estimated based on a reactivity comparison with CH2F2 and CF3CHFCF3.

22. Stratospheric partial lifetime calculated using 2-D model with OH and O(1D) rate coefficients recommended in SPARC (2013) Chapter 3.

23. Total lifetime estimated based on the increase in Lyman-α (121.567 nm) cross section with increasing number of –CF2– groups in the perfluorocarbon.

24. OH rate coefficient from Young et al. (2009) and an assumed temperature dependence the same as for CHF2CF3.

25. Lifetimes taken from the 2-D model calculations in Papadimitriou et al. (2013b).

26. OH rate coefficient data taken from Atkinson et al. (2008).

27. Stratospheric partial lifetime assumed to be the same as for HCFC-133a (CH2ClCF3).

28. Tropospheric OH partial lifetime estimated from that for CF3CH2OCF2CHF2 by adjusting for the reactivity contribution of –CF2CHF2 determined from the 

reactivity of CF3CF2OCF2CHF2.

29. Tropospheric OH partial lifetime estimated from those for CF3OCH3 and CHF2CH2CF3.

30. OH rate coefficient taken from Tokuhashi et al. (1999).

31. Tropospheric OH partial lifetime estimated as being greater than that of CHF2CF2OCHF2 and less than that of CHF2CF2CF2CF3.

32. Tropospheric OH partial lifetime assumed to be the same as that of CF3OCH2CF3.

33. Tropospheric OH partial lifetime assumed to be the same as for CHF2CH2OCF3.

34. Tropospheric OH partial lifetime assumed to be approximately that of CH3OCF2CHF2.

35. Tropospheric OH partial lifetime estimated from the sum of the OH reaction loss of CF3CF2OCF2CHF2 and CF3CF2OCH2CHF2.

36. OH rate coefficient from the 298 K studies of Langbein et al. (1999) and Sulbaek Andersen et al. (2012) and an assumed E/R of 1500 K.

37. OH rate coefficient from Chen et al. (2005a).

38. OH rate coefficient from the 295 K study of Christensen et al. (1998) and an assumed E/R of 1000 K.

39. OH rate coefficient taken from Chen et al. (2004b).

40. Ocean loss for perfluoro esters has been estimated from hydrolysis and solubility data for non-fluorinated and partially fluorinated esters by Kutsuna et al. (2005). 

These authors suggest that the ocean sink can be comparable to the tropospheric reaction sink for perfluoro esters, thereby reducing the total lifetimes given in this 

table by as much as a factor of 2.

41. OH rate coefficient from Chen et al. (2004a).

42. Total lifetime taken from Table 1-4 in Clerbaux and Cunnold et al. (2007).

43. Lifetimes calculated based on 2-D model from Papadimitriou et al. (2013a); total lifetime includes tropospheric (84150 years) and mesospheric (2531 years) 

partial lifetimes.

44. From Papadimitriou et al. (2008) and Mühle et al. (2009).

Figure 1-2. Time evolution of monthly-mean total vertical column abundances (in molecules per square 

centimeter) for CFC-12, CFC-11, CCl4, and HCFC-22 above the Jungfraujoch station, Switzerland, 

through 2012 (updated from Zander et al. (2008), using the bootstrap resampling tool described by 

Gardiner et al. (2008) for the trend evaluations and Rinsland et al. (2012)). Note the discontinuity in the 

vertical scale. Solid blue lines show polynomial fits to the columns measured in June to November only so 

as to mitigate the influence of variability caused by atmospheric transport and tropopause subsidence 

during winter and spring (open circles) on derived trends. Dashed green lines show nonparametric leastsquares fits (NPLS) to the June to November data.
Chapter 1

1.18

Figure 1-3. Top-down and bottom-up global emissions estimates (Gg yr-1) for ozone-depleting 

substances. Top-down emissions from AGAGE (black) and NOAA (red) atmospheric data were calculated 

using a global 12-box model (Cunnold et al., 1983; Rigby et al., 2013). (continued next page)
ODSs and Other Gases of Interest

1.19

(Figure 1-3, continued) Additionally, for CFC-112, CFC-113a, HCFC-133a, and halons the emissions 

were calculated using UEA data from the Southern Hemisphere (S.H.) (Cape Grim archived air (blue); 

Laube et al., 2014). Lifetimes and ranges were taken from Newland et al. (2013), Laube et al. (2014), and 

SPARC (2013). Shaded bands indicate overall uncertainties derived from uncertainties in measurement, 

lifetimes, and prior emissions estimates. Mean values given in the text, and shown in figures for 2012, 

were calculated as the mean of AGAGE and NOAA estimates (when available). Ranges were taken from 

AGAGE data as shown in this figure unless AGAGE and NOAA ranges differed by more than 10%, in 

which case an average range was reported (e.g., CFC-113). CFC-11 emissions were also calculated 

using an older lifetime estimate of 45 years instead of 52 years (dashed violet line). Bottom-up estimates 

include UNEP (2006) (green) and UNEP (2011b) (violet). Note the x-axis ranges are not the same for all 

panels.

Figure 1-4. Regional emission 

estimates of CFC-11, CFC-12, and 

CFC-113 from China. Top-down 

estimates in years indicated were 

taken from 1Palmer et al. (2003), 2

Vollmer et al. (2009), 3Kim et al. 

(2010), 4An et al. (2012), and 5Fang 

et al. (2012). Bottom-up estimates 

(solid and dashed lines) are from 

Wan et al. (2009).
Chapter 1

1.20

Box 1-1. Lifetimes and Removal Processes

The total lifetime (τTotal) of a trace species is defined as the ratio of its global atmospheric burden (CGlobal) 

to its total global loss rate (LTotal)

where LTotal is the sum of the loss rates for various removal processes

LAtm represents the loss rate for processes occurring in the atmosphere (gas-phase reaction and photolysis), LSoil

is the loss rate due to soil uptake, and LOcean is the rate for loss to the oceans (additional loss rates are 

represented by LX). Lifetimes are not constant values because they depend on the abundance of a chemical 

relative to the distribution of its sinks (and hence can vary with emission magnitude and location). Steady-state 

lifetimes refer to a lifetime when the emission and removal rates of a species are equal. A discussion of 

lifetimes and methods for defining their uncertainties is given in SPARC (2013).

Loss rates are associated with partial lifetimes such that

where 

The atmospheric lifetime can also be separated into partial troposphere, stratosphere, and mesosphere 

lifetimes using the total global atmospheric burden and the loss rate integrated over the different atmospheric 

regions such that

Species with total lifetimes greater than ~0.5 years are well-mixed in the troposphere and, for the 

purposes of this Assessment, are considered long-lived. In this case, τTotal is considered to be independent of 

the location of emission, and is considered to be a global lifetime that represents the compound’s persistence in 

the Earth’s atmosphere. The lifetime of a long-lived species due to reaction with tropospheric OH radicals is 

estimated relative to the corresponding tropospheric OH partial lifetime of methyl chloroform (CH3CCl3, 

MCF) such that

where is the OH partial lifetime for compound RH, kRH(272 K) and kMCF(272 K) are the rate coefficients 

for the reactions of OH with RH and MCF at 272 K, respectively, and = 6.1 years (see Table 1-3).

Very short-lived substances (VSLS) (i.e., compounds with atmospheric lifetimes less than ~0.5 years) 

typically have non-uniform tropospheric distributions, because this time period is comparable to or shorter 

than the characteristic time of mixing processes in the troposphere. Local atmospheric lifetimes of VSLS, 

therefore, depend on where and when the compound is emitted, as well as local atmospheric conditions (Table 

1-5, page 1.35). The concept of a single global lifetime, an Ozone Depletion Potential (ODP), or a Global 

Warming Potential (GWP) is inappropriate for VSLS, as discussed in Chapter 5.

Since the last Assessment, SPARC (Stratosphere-Troposphere Processes And their Role in Climate)—a 

core project of the World Climate Research Programme (WCRP)—initiated a study of the “Lifetimes of 

Stratospheric Ozone-Depleting Substances, Their Replacements, and Related Species” (SPARC, 2013). The 

study included 27 long-lived key ozone-depleting substances (ODSs), replacement compounds, and greenhouse gases (see Table 1-3). Including CFC-11 was of particular importance since it is the reference species 

used in defining the ODPs of other ODSs. The lifetime evaluation was warranted because of advancements in
ODSs and Other Gases of Interest

1.21

(Box 1-1, continued) 

the ability of models to simulate atmospheric circulation (leading to better estimates of age of air) and new 

measurement data from ground-based networks, high-altitude sampling, and satellite observations. The 

recommended steady-state atmospheric lifetimes were derived using results from state-of-the art models and 

measurement-based estimates. The report also provides an in-depth analysis of the uncertainties in these 

lifetimes. The SPARC-recommended atmospheric steady-state lifetimes and estimated range of lifetimes given 

in Table 1-3 were obtained from a weighted average of the lifetimes derived from different methods, as 

described in SPARC (2013).

1.2.1.2 HALONS

Observations

Halon-1211 (CBrClF2), halon-2402 (CBrF2CBrF2), and halon-1202 (CBr2F2) mole fractions 

continued to decline from peak values observed in the early and mid-2000s (Table 1-1; Figure 1-1; 

Newland et al., 2013). Recent trends in halon-1211, halon-1301, and halon-2402 agree with those 

anticipated in the A1-2010 scenario (Daniel and Velders et al., 2011). Although globally averaged mole 

fractions of halon-1301 (CF3Br) continued to increase (reaching 3.26 ppt in 2012), the summed 

contribution of halons to total atmospheric bromine peaked around 2007. A decrease in global total 

bromine from halons was not evident at the time of the last Assessment, but is now significant, with an 

average rate of decline of −0.06 ppt yr-1 between 2008 and 2012.

Over the 2008–2012 period, estimates of the global abundances of halon-1301 and -1211 varied 

by 1–2% among global networks (Table 1-1). For halon-2402, Southern Hemispheric mole fractions from 

the University of East Anglia (UEA; Newland et al., 2013) were 7.5% lower than the NOAA scale.

Lifetimes and emissions

The new recommended steady-state lifetime of halon-1301 is 72 years (increased from 65 years) 

(SPARC, 2013). Revised lifetimes for halon-1202, halon-1211, and halon-2402, obtained using a 2-D 

model, are reported in this Assessment based on UV absorption cross section measurements made since 

the SPARC (2013) assessment (Papanastasiou et al., 2013). These halons are removed exclusively by 

photolysis in the troposphere and stratosphere. The lifetime uncertainty due solely to the uncertainty in 

the new cross section data for these substances (Table 1-3) is considerably smaller than reported in 

SPARC (2013), where the uncertainties were derived by averaging various 3-D approaches and 

observational data.

Global emission estimations derived from measured global mole fractions peaked around 1988 

for halon-1301, 1993 for halon-2402, and 1995–1998 for halon-1211 (Figure 1-3). Emissions of halon1211 and halon-2402 have been decreasing in recent years, while those of halon-1301 have remained 

approximately constant (Figure 1-3). This is broadly consistent with emission estimates from inventories 

(UNEP, 2011b). Continued emissions of halons are expected from banks (Box 5-1), since the primary use 

for these chemicals is in fire extinguishers. Therefore any impact of the 2010 global phase-out of halon 

production will likely not be observed in the atmosphere immediately. Top-down and bottom-up 

emissions estimates agree reasonably well for halon-1211 and halon-1301, but a large discrepancy 

continues to exist for halon-2402, which was predominantly produced and used in the former Soviet 

Union (McCulloch, 1992).

In 2010 halon banks were estimated by the Halons Technical Options Committee (HTOC); 

(UNEP, 2011b) as 43 Gg for halon-1301 and as 65 Gg for halon-1211. For the same year Newland et al. 

(2013) estimated an identical bank size for halon-1301, but only 37 Gg for halon-1211. The difference for 

halon-1211 may be partially explained by the relatively large uncertainty in the halon-1211 lifetime range 

(10–39 years), which translates into large uncertainties in emissions and bank sizes. With banks likely 

much larger than current emissions, it may take decades before halon-1211 and halon-1301 banks are 

depleted.
Chapter 1

1.22

1.2.1.3 CARBON TETRACHLORIDE (CCl4)

Observations

The global surface mean mole fraction of carbon tetrachloride (CCl4) continued to decline from 

2008 to 2012 (Table 1-1). The AGAGE and UCI networks report rates of decline of 1.2–1.3% from 

2011–2012, whereas the rate of decline reported by the NOAA network was 1.6%. These relative declines 

in mole fractions at Earth’s surface are comparable to declines in column abundances from remote 

sensing instruments of 1.2–1.3% yr-1 (Table 1-2).

Lifetimes and emissions

Historically, CCl4 was used as a solvent and as a feedstock for production of CFCs and their 

replacements. Current production is limited to feedstock, process agent use (e.g., in chlor-alkali 

production plants), and minor other essential uses (UNEP, 2013b; Fraser et al., 2014). Sinks for CCl4

include loss in the stratosphere (Sander, 2011; SPARC, 2013), degradation in the oceans (Krysell et al., 

1994; Yvon-Lewis and Butler, 2002; Lee et al., 2012), and degradation in soils (Happell and Roche, 

2003; Liu, 2006; Rhew et al., 2008; Mendoza et al., 2011). A revised best estimate of the partial lifetime 

with respect to stratospheric loss, including the results of Laube et al. (2013) and Volk et al. (1997), is 44 

years (SPARC, 2013), updated from 35 years. The partial lifetime with respect to oceanic uptake is still 

94 (82–191) years (Yvon-Lewis and Butler, 2002). The soil sink partial lifetime is estimated to be 

approximately 195 (108–907) years (Montzka and Reimann et al., 2011). The sum of these three updated 

partial loss rates results in a total lifetime estimate of 26 years, which is unchanged from the previous 

Assessment (Montzka and Reimann et al., 2011). If the soil sink was negligible this would result in total 

lifetime of ~30 years.

Since the last Assessment, the discrepancy between bottom-up and top-down CCl4 emission 

estimates has not been resolved. Global emissions determined from AGAGE and NOAA atmospheric 

data, using a total lifetime of 26 years, averaged 57 (40–74) Gg in 2012. After 2005 these top-down 

emission estimates are considerably higher than bottom-up emissions (derived from reported production 

minus feedstock use and destruction) (Figure 1-6).

A further indication of ongoing CCl4 emissions (mostly in the Northern Hemisphere) is provided 

by the difference in mean mole fraction between hemispheres (Northern Hemisphere minus Southern 

Hemisphere, or NH−SH), which has been virtually stable at about 1.3 ppt since 2006. This is between the 

NH-SH difference of CFC-11 (~2 ppt), with annual emissions of 57 (46–68) Gg (410 (330–490) Mmol)

in 2012, and CFC-113, with virtually no interhemispheric gradient and only small annual emissions of 1.5 

(0–7) Gg (9 (0–40) Mmol) in 2012 (Figure 1-5). This suggests that significant sources of CCl4 remain in 

the NH, although the higher oceanic sink in the SH, caused by the larger ocean area, may also account for 

some of this difference (Montzka and Reimann et al., 2011).

Emissions of CCl4 could potentially arise from old industrial sites and from feedstock usage. The 

magnitude of emissions from CCl4 feedstock uses are highly uncertain (UNEP, 2012) but have been 

estimated to be approximately 0.5%–2% of the feedstock production (1–4 Gg yr-1 in 2012, Figure 1-6). 

Emissions from CCl4 used as a process agent have also been suggested (UNEP, 2013b; Fraser et al., 

2014). Fraser et al. (2014) detected enhanced abundances of CCl4 downwind of industrial waste sites in 

Melbourne (Australia) and provided evidence that significant amounts of CCl4 could be emitted from 

contaminated soils, toxic waste treatment facilities, and possibly chlor-alkali production plants. This 

finding is also supported by de Blas et al. (2013), who observed similar enhancements at an industrial site 

in Spain. On the other hand, UNEP (2013b) reported that CCl4 emissions from process agent use are 

small and declining (<1 Gg yr-1). Although it is possible that unreported fugitive emissions (e.g., in the 

manufacture of polymers) exist (UNEP, 2013b), it is unlikely that these sources can explain the 30–70 Gg 

yr-1 discrepancy between the top-down and bottom-up emission estimates.

The contributions of regional CCl4 sources to global emissions are not well known. This is particularly true for developing countries, since the density of long-term surface measurements in these 

countries is still low. For North America, CCl4 emissions between 0 and 0.4 Gg yr-1were derived from regional
ODSs and Other Gases of Interest

1.23

Figure 1-5. Trends in mean hemispheric mole fraction differences (NH minus SH ppt) for CFC-11 and 

CFC-113 (upper panel, NOAA data) and CCl4 (lower panel; AGAGE data: blue symbols and blue line; 

NOAA data: gray symbols and black line). The red line is a fit to the AGAGE data.

Figure 1-6. CCl4 emissions derived from 

atmospheric measurements (red line and 

shading) and potential emissions estimated 

from production data (green lines). The 

lower potential emissions estimate (lower 

green line) was derived from the difference 

between total CCl4 production reported to 

UNEP (solid black line labeled “P”) and the 

sum of feedstock and amounts destroyed 

(dotted blue line labeled “F&D”), and also 

includes estimates of underreported 

feedstock production. The upper potential 

emissions estimate (upper green line) was 

derived similarly, but was augmented by 

fugitive emissions of 2% of reported CCl4

feedstock use, and assuming an efficiency 

of only 75% for reported destruction. Production magnitudes related to feedstock 

alone are indicated with the dashed blue line labeled “F”. Top-down estimates (red line) were derived 

using AGAGE data and a 12-box model as in Figure 1-2. The shaded region represents the uncertainty in 

the top-down emissions resulting from measurement uncertainty, prior emissions, and a range of 

lifetimes. A range of partial lifetimes with respect to stratospheric loss, loss to soils, and loss to the oceans, 

was considered. The mean total lifetime for CCl4 was 26 years and the range was 22–32 years.
Chapter 1

1.24

campaigns and extrapolated to the entire U.S. by Hurst et al. (2006), Millet et al. (2009), and Miller et al. 

(2012) between 2003 and 2009. Xiao et al. (2010a) used monthly means and their uncertainties from 

globally distributed sites and a global transport model to estimate emissions for several regions, 

constrained by the global total. They estimated CCl4 emissions of 4.9 ± 1.4 Gg yr-1 for North America 

during 1995–2004. More significantly, their study indicated that S.E. Asia was responsible for ~53% (37–

42 Gg yr-1) of the average global CCl4 emissions from 1996–2004. Palmer et al. (2003) (with a campaign 

downwind of China) and Vollmer et al. (2009) (with high-frequency observations at a site near Beijing) 

found that emissions from China in the early to mid-2000s were in the range of 15.0–17.6 Gg yr-1, which 

is 20–25% of the global emissions estimated by top-down methods during that period. Furthermore, based 

on measurements at Cape Grim (Tasmania), Xiao et al. (2010a) and Fraser et al. (2014) estimated 

Australian CCl4 emissions of 0.3–0.4 Gg in the late 1990s, declining to 0.1–0.2 Gg in the early 2010s.

In summary, the mismatch between bottom-up inventories and global top-down estimates of CCl4

is still unresolved. There are, however, indications that some of the discrepancy could be explained by 

additional sources unrelated to reported production, such as contaminated soils and industrial waste 

(Fraser et al., 2014), although their global significance is highly uncertain. Additional explanations could 

include underreported emissions and incorrect partial lifetimes (stratosphere, ocean, or soil).

1.2.1.4 METHYL CHLOROFORM (CH3CCl3)

Observations

The global mole fraction of methyl chloroform (1,1,1-trichloroethane, CH3CCl3) has been 

declining steadily since reaching a maximum in the early 1990s (Figure 1-1). At ~5.4 ± 0.3 ppt in 2012, 

the global mean mole fraction is only 4% of its maximum. Thus, the contribution of CH3CCl3 to future 

changes in total Cl will likely be small. Atmospheric CH3CCl3 continues to be used to study the 

variability of the OH radical (Prinn et al., 2005; Montzka et al., 2011).

Lifetimes and emissions

Using atmospheric data and a global lifetime of 5.0 years (SPARC, 2013), global emissions of 

CH3CCl3 are estimated to have been < 10 Gg yr-1 since 2005 and decreased to ~2 Gg in 2012 (Figure 1-3). 

This behavior is consistent with the historical uses of this controlled chemical as a solvent, with generally 

rapid release to the atmosphere. However, small remaining banks and potential emissions from its 

feedstock usage could lead to ongoing emissions. Small but non-zero emissions have been reported for 

different years during the last decade for the U.S. (2.4–2.8 Gg yr-1) by Millet et al. (2009) and Miller et al. 

(2012) as well as for China (1.7–3.3 Gg yr-1) by Vollmer et al. (2009) and Li et al. (2011).

1.2.1.5 HYDROCHLOROFLUOROCARBONS (HCFCS)

Observations

The global surface mean mole fractions of the three most abundant hydrochlorofluorocarbons 

(HCFC-22, CHClF2; HCFC-141b, CH3CCl2F; HCFC-142b, CH3CClF2) continue to increase (Table 1-1). 

However, the growth rates in 2012 differed significantly from those in 2008 (Figures 1-1, 1-7). Between 

2008 and 2012 the growth rate declined by ~30% for HCFC-22 and by nearly 60% for HCFC-142b. In 

contrast, recent trends in HCFC-141b show a substantial increase (~70%) in the growth rate since 2008. 

Whereas the increase in HCFC-141b was anticipated under the A1-2010 scenario (Figure 1-1), the slower 

increases of HCFC-22 and HCFC-142b were not.

Trends in total column HCFC-22 are also available from remote sensing instruments (updated 

from Gardiner et al., 2008; Zander et al., 2008; Brown et al., 2011) and are similar to those derived from 

surface data (Table 1-2). On the other hand, trends for HCFC-142b and HCFC-141b derived from satellite 

observations (ACE-FTS) do not agree with those measured at the surface (Table 1-2). For HCFC-141b, 

the ACE-FTS column measurements are subject to interference from other trace gases, such as CFC-114 
ODSs and Other Gases of Interest

1.25

and HFC-23, particularly at lower altitudes (Brown et al., 2011), which may explain some of the 

discrepancy.

For HCFC-124 (CHClFCF3) AGAGE measurements indicate a 9% decline in the global mole 

fraction between 2009 and 2012 (update of Prinn et al., 2000 and Miller et al., 2008). Laube et al. (2014) 

reported first measurements of HCFC-133a (CH2ClCF3), which is used in the production of 

pharmaceuticals and is an intermediate in HFC-134a production (Miller and Batchelor, 2012; UNEP, 

2012). Mole fractions of HCFC-133a in the Southern Hemisphere increased slowly from the 1970s to 

2003, then increased more rapidly from 2004 to 2008, and after a period of little change from 2008–2010, 

increased rapidly again to 0.365 ppt in 2012 (Laube et al., 2014; Figure 1-1 and Table 1-1).

Figure 1-7. Recent trends for 

HCFC-22, HCFC-141b, and 

HCFC-142b estimated from 

AGAGE and NOAA global 

network data and the A1-2010 

scenario: global mean mole 

fraction estimates (solid lines, 

left axis) and growth rates 

(dashed lines, right axis).
Chapter 1

1.26

Lifetimes and emissions

With a large bank of HCFC-22 thought to exist in refrigeration systems, emissions are expected 

to continue, but should decline as new refrigerants are being adopted as a consequence of the freeze of 

HCFC production and consumption for dispersive uses in 2013 in developing (Article 5) countries. 

Global emissions of HCFC-22, calculated using surface measurements of HCFC-22, peaked in 2010 at 

381 (331–431) Gg and were 366 (316–416) Gg in 2012 (Figure 1-3) (i.e., stable within the uncertainties).

The estimated lifetime of HCFC-142b was revised from 17.2 to 18.0 years (+5%) since the 

previous Assessment (SPARC, 2013). Global HCFC-142b emissions peaked at 39 (34–44) Gg yr-1 in 

2008 and have since declined by 27% to 29 (23–34) Gg in 2012. This decline in emissions follows 

reduced production and consumption in non-Article 5 (non-A5) countries and a leveling off of production 

and consumption in Article 5 (A5) countries (Figure 1-8) (UNEP, 2014). Total global production in 2011 

was only half that of 2009. On the other hand, feedstock use of HCFC-142b has increased markedly in 

recent years in both A5 and non-A5 countries. Emissions estimated from feedstock use vary, but are 

generally thought to be low (UNEP, 2013b).

Figure 1-8. 

History of production, 

consumption, and feedstock use of HCFC22, -142b, and -141b in 

Article 5 countries (red) 

and non-Article 5 countries 

(black) (UNEP, 2014). 

Total production (nonA5+A5) (blue) does not 

include feedstock production. Feedstock data for 

HCFC-141b are not shown 

because HCFC-141b feedstock use (15 Gg in 2010; 

UNEP, 2012) is thought to 

be small compared to that 

of HCFC-22 and HCFC142b.

Gg / yr Gg / yr Gg / yr
ODSs and Other Gases of Interest

1.27

Current global HCFC-141b emissions are approaching the same level they were during peak 

production in the early 2000s (Figure 1-8). While production has decreased in non-A5 countries over the 

last decade, it has increased substantially in A5 countries since 2005 (UNEP, 2014). Regional studies 

indicate that China was responsible for about 15–30% of global HCFC-141b emissions in 2008–2009 

(Wan et al., 2009; Stohl et al., 2010; Li et al., 2011; Fang et al., 2012).

Global and regional studies suggest a shift of HCFC emissions from midlatitudes to lower 

latitudes. Montzka et al. (2009) found a trend toward smaller intrahemispheric gradients as global 

emissions increased for HCFC-22, -141b, and -142b from 1996 to 2007. An updated gradient analysis 

using data through 2012 shows similar patterns to those described by Montzka et al. (2009), suggesting 

that recent shifts of production and consumption from non-A5 countries to A5 countries (Figure 1-8), 

which mostly are at lower latitudes, continue to be mirrored by higher emissions in these regions.

Recently, Saikawa et al. (2012) estimated regional HCFC-22 emissions between 1995 and 2009 

using globally distributed surface data. They found a distinctive increase in emissions from Article 5 

countries in Asia in recent years. A number of regional studies, along with bottom-up emission estimates 

and consideration of total HCFC production trends, suggest an increase in HCFC-22 emissions 

particularly from China in recent years (Figure 1-9) (Yokouchi et al., 2006; Stohl et al., 2010; Vollmer et 

al., 2009; Li et al., 2011; An et al., 2012; Fang et al., 2012). Apart from Vollmer et al. (2009) the temporal 

increase of the Chinese bottom-up emissions estimate from Wan et al. (2009) is consistent with several 

measurement-based studies (Figure 1-9). An et al. (2012) used an extension of the data set used by 

Vollmer et al. (2009) and found emissions that were comparable to those from Wan et al. (2009) (Figure 

1-9). The reason for the difference between 

these two studies could be due to improvements in the regional transport simulation and 

in the inversion method used by An et al. 

(2012).

Figure 1-9. HCFC-22 emissions from China 

estimated by bottom-up (solid line; Wan et al., 

2009) and top-down methods (filled squares): 1

Stohl et al. (2009); 2Yokouchi et al. (2006); 3

Stohl et al. (2010); 4Vollmer et al. (2009); 5Li 

et al. (2011); 6An et al. (2012); 7Fang et al. 

(2012).

1.2.1.6 METHYL CHLORIDE (CH3Cl)

Observations

The global surface mean mole fraction of methyl chloride (CH3Cl) determined by the NOAA and 

AGAGE global networks was 540 ppt with a range from 537.1 to 542.2 ppt in 2012 (Table 1-1) and 

contributed ~16% to the total tropospheric chlorine. Only small changes were observed since the last 

Assessment, showing an enhanced interannual variability from 2011 to 2012 but an overall decline from 

2008 to 2012 (Table 1-1, Figure 1-1).

Spatial and temporal variations in the distribution of CH3Cl in the upper troposphere and 

stratosphere were assessed by Santee et al. (2013) using 8 years of Microwave Limb Sounder (MLS) 

satellite data. They found a correlation of enhanced CH3Cl levels with regional biomass burning events, 

giving additional evidence for the importance of this highly fluctuating anthropogenically influenced 

source on the CH3Cl budget.
Chapter 1

1.28

Sources and sinks

While production and consumption of this primarily natural compound are not controlled by the 

Montreal Protocol, CH3Cl shares many natural sources and sinks with CH3Br, which is controlled. 

Sources of CH3Cl include the ocean, biomass burning, fungi, salt marshes, wetlands, rice paddies, 

mangroves, and tropical forests (Table 1-4). As with CH3Br, the budget for CH3Cl remains unbalanced, 

with sinks outweighing sources (Table 1-4).

Since the last Assessment, the magnitude of the tropical source has been better defined. 

Individual studies have shown that tropical sources of CH3Cl are significant. Saito et al. (2013) used an 

isotope tracer technique to separate the production of CH3Cl from the degradation associated with tropical 

plants. They confirmed earlier studies (Yokouchi et al., 2002, 2007; Blei et al., 2010; Saito et al., 2008; 

Gebhardt et al., 2008) suggesting that tropical plants are a substantial net source of CH3Cl. The modeling 

results of Xiao et al. (2010b) also suggest a substantial CH3Cl source from the tropics. These studies 

together suggest an average tropical terrestrial flux of 2040 ± 610 Gg yr-1 (Table 1-4).

Sinks of CH3Cl include reaction with hydroxyl radicals, uptake by soils, degradation in oceans, 

and photolysis in the stratosphere (Tables 1-3 and 1-4). Recently, Hu (2012) estimated a global soil 

uptake rate for CH3Cl of 1058 (664–1482) Gg yr-1. This rate was determined by scaling with the soil 

uptake rate for CH3Br, as suggested by Rhew et al. (2011). The oceanic uptake and emission of CH3Cl 

were recently revised by Hu et al. (2013) (Table 1-4), where the coastal ocean uptake and emissions were 

explicitly considered along with the open ocean fluxes and more degradation rate constant measurements.

1.2.1.7 METHYL BROMIDE (CH3Br)

Observations

The global surface mean mole fraction of methyl bromide (CH3Br) continued to decline since the 

last Assessment. The surface global mean mole fractions determined by NOAA and AGAGE networks 

was 7.0 ± 0.1 ppt in 2012 (Table 1-1). This represents a decline of around 25% from the 9.2 ppt observed 

in the mid-1990s (Yvon-Lewis et al., 2009). When data from ice core measurements from Butler et al. 

(1999), Saltzman et al. (2004), Trudinger et al. (2004), and Saltzman et al. (2008) are averaged, a natural 

background in the Southern Hemisphere of 5.5 ± 0.2 ppt results, which is consistent with the previous 

Assessment. Under the assumption that no natural interhemispheric gradient existed, this would signify 

that mole fractions of around 7 ppt in 2012 are still 27% above the natural background.

Sources and sinks

CH3Br has both natural and anthropogenic sources. Our estimate of global sinks and sources for 

CH3Br is not balanced, with known sinks outweighing known sources (Table 1-4). This imbalance 

persists from pre-phase-out (1995–1998) through the most recent years (Hu et al., 2012).

The primary anthropogenic source of CH3Br has been from its use as a fumigant. Non-quarantine 

and pre-shipment (non-QPS) fumigation uses (mainly in agriculture) were the dominating anthropogenic 

source of atmospheric CH3Br in the past, but are subject to phase-out and currently only limited amounts 

are still allowed for applications in critical-use exemptions. Quarantine and pre-shipment (QPS) uses, 

which are mainly related to pest control during transport and storage, are exempted from the phase-out

and consumption from QPS uses was approximately stable in the last two decades (UNEP, 2014). 

Therefore, the declining atmospheric abundance of CH3Br is the result of reductions in consumption for 

non-QPS uses (Figure 1-10). Accordingly, the non-QPS consumption became lower than the QPS 

consumption in 2009 and by 2012 it was only 43% of the QPS consumption, or 30% of the total 

fumigation use (Figure 1-10). Estimated emissions from non-QPS uses became lower than QPS uses after 

2006, as emission factors are higher for QPS uses (84%) than for non-QPS uses (65%) (UNEP, 2007). 

These QPS/non-QPS uses do not include consumption as a chemical feedstock (Montzka and Reimann et 

al., 2011) or the application of CH3Br as a transient in the conversion of methane to fuel (Ding et al., 

2013), as CH3Br is assumed to be released only in minor quantities from these processes.
ODSs and Other Gases of Interest

1.29

Table 1-4. Sources and sinks for atmospheric CH3Cl and CH3Br in Gg yr-1 (adapted from Hu, 2012). 

The best values are shown with their possible ranges in parentheses. n.q. = not quantified. QPS = 

quarantine and pre-shipment. For CH3Cl, figures represent the current knowledge. For CH3Br changes in 

anthropogenic sources between 1995–1998 and 2012 are derived from reported information. 

Source / Sink CH3Cl (Gg yr-1) CH3Br (Gg yr-1) 

1995 – 1998 2012 

SOURCES 

Anthropogenic Sources 

Leaded Gasoline n.q. 3 (0.6–6)18-21 0–3 

Coal Combustion; 

Waste Incineration; 

Industrial Activity 

162 (29–295)1n.q. n.q. 

Fumigation – QPS a n.q. 8.1 (7.5–8.7) 7.4 (6.9–7.8)

Fumigation – non-QPS b n.q. 39.9 (28.2–55.9) 2.5 (1.7–3.5)

Biomass Burning – 

Indoor Biofuel Use c

113 (56–169) 6 (3–9) 6 (3–9) 

Biomass Burning –

Open Field Burning e

355 (142–569) 17 (7–27) d 17 (7–27) 

Ocean 700 (510–910)2 32 (22–44)22 32 (22–44)22

Terrestrial sources 

Tropical and 

Subtropical Plants; 

Tropical Leaf Litter f

2040 (1430–2650)3-9 n.q. n.q.

Mangroves 12 (11–12)10 1.3 (1.2–1.3)10 1.3 (1.2–1.3)10

Rapeseed n.q. 4.9 (3.8–5.8)23 5.1 (4.0–6.1)23

Fungus 145 (128–162)7,11 2.2 (1–5.7)7,24 2.2 (1–5.7)7,24

Salt Marshes 85 (1.1–170)12,13 7 (0.6–14)26 7 (0.6–14)26

Wetland 27 (5.5–48)14,15 0.6 (−0.1–1.3)24 0.6 (−0.1–1.3)24

Rice Paddies 3.7 (2.7–4.9)16 0.7 (0.1–1.7)24 0.7 (0.1–1.7)24

Shrublands 15 (9–21)17 0.7 (0.5–0.9)17 0.7 (0.5–0.9)17

Subtotal (Sources) 3658 123 84 

SINKS g

Reaction with OH h 2832 (2470–3420) 74 (63–83) 56 (48–63)

Loss in Soil 1058 (664–1482) 40 (25–54) 30 (19–41)

Loss in Ocean 370 (296–445)2 43 (27–58)22 33 (20–44) 22

Loss in Stratosphere 146 5 4

Subtotal (Sinks) 4406 162 123 

Net (Sources – Sinks) −748 −39 −39

a. Data for fumigation — QPS consumptions of CH3Br were downloaded from UNEP

(http://ozone.unep.org/Data_Reporting/Data_Access) and the emission ratio is 84% (78%–90%) from UNEP 

(2007).

b. Data for fumigation — non-QPS consumptions of CH3Br were downloaded from UNEP

(http://ozone.unep.org/Data_Reporting/Data_Access) and the emission ratio is 65% (46%–91%) from UNEP 

(2007) and UNEP (2011c). (continued next page)
Chapter 1

1.30

Table 1-4, continued. 

c. Emissions of indoor biofuel use were estimated based on the total dry matter burned for indoor biofuel use in 

1995 (Yevich and Logan, 2003) and emission factors from Andreae and Merlet (2001).

d. Average biomass burning emissions were determined using the dry matter burned (van der Werf et al., 2010)

and emission factors from Andreae and Merlet (2001).

e. Mean of observations with range of ±1σ.

f. Average value from Hu (2012).

g. For sinks, partial lifetimes from Table 1-3 were used. For the calculation of the atmospheric burden (Ba) the 

following equation was used: Ba= χa ntr/r, where χa is the sea-level mole fraction (CH3Cl 540 ppt in 2012; 

CH3Br 9.2 ppt in 1995-1998 and 7.0 ppt in 2012), ntr is the number of moles in the troposphere (1.446 × 1020

moles), and r is the fraction of the total amount of the substance that resides in the troposphere (r = 0.95 for 

CH3Br and 0.887 for CH3Cl; Lal et al., 1994).

h. The sink due to the reaction with Cl-radicals is not included.

1

McCulloch et al. (1999), 2Hu et al. (2013), 3Yokouchi et al. (2007), 4Blei et al. (2010), 5Saito et al. (2008), 6

Gebhardt et al. (2008), 7Lee-Taylor et al. (2001), 8Xiao et al. (2010b), 9Yoshida et al. (2004), 10Manley et al. (2007), 11Watling and Harper (1998), 12Rhew et al. (2000), 13Cox et al. (2004), 14

Varner et al. (1999), 15Dimmer et al. 

(2001), 16Lee-Taylor and Redeker (2005), 17Rhew et al. (2001), 18Thomas et al. (1997), 19Chen et al. (1999), 20Baker 

et al. (1998), 21Bertram and Kolowich (2000), 22 adapted from Hu et al. (2012) according to footnote g, 23Mead et al. 

(2008), 24 Lee-Taylor and Holland (2000), 26Montzka and Reimann et al. (2011).

Figure 1-10. Upper panel: Trends since 1995 in methyl 

bromide (upper) mole fractions with NH (!) SH (") and 

global (!) NOAA data (Montzka et al., 2003, updated). 

Middle panel: Interhemispheric differences (NH−SH) as 

monthly means (•) and as a running average (▬). Lower 

panel: consumption (dashed lines) as reported in the 

UNEP database (UNEP, 2014) for non-QPS uses (- - -),

QPS uses (- - -) and total (- - -)., and emission (solid lines) 

from non-QPS uses (▬), QPS uses (▬) and total (▬). 

Soil fumigation emission rates estimated as 65% (46–

91%) of reported consumption rates (UNEP 2007). QPS 

emission rates estimated as 84% (78–90%) of reported 

consumption rates (UNEP 2007).
ODSs and Other Gases of Interest

1.31

The total controlled and non-controlled fumigation emission is estimated to have accounted for 30 

(22–40)% of the total global CH3Br emissions during 1996–1998, before industrial production and consumption were reduced. By 2012, the total fumigation-related emissions, from controlled and non-controlled 

uses of CH3Br, is estimated to have been reduced to 8 (7–10)% of the total global CH3Br emissions.

Other anthropogenic sources of CH3Br include the combustion of leaded gasoline, biomass burning,

and emissions from certain crop species (e.g., canola/rapeseed, rice, mustard and cabbage) (references in 

Table 1-4). Biomass burning emissions are separated into open field burning, which can be anthropogenic or 

natural and indoor biofuel combustion (Yvon-Lewis et al., 2009; Hu, 2012). The combined burning 

emissions from these sources are comparable to the estimates in the previous Assessment (Table 1-4).

Natural sources of CH3Br include the ocean, freshwater wetlands, fungus, tropical plants and leaf 

litter, and coastal saltmarshes (Table 1-4). Individual studies have shown that tropical sources are small or 

not significant (Gebhart et al., 2008; Blei et al., 2010). These studies were confirmed recently by Saito et al. 

(2013), who showed that the uptake of CH3Br associated with tropical plants was nearly equal to its 

emission, resulting in only a small net source for CH3Br from tropical plants. The variability in the 

magnitude of these tropical plant emissions has made them difficult to quantify over the global tropical 

region and they are therefore not included in the Table 1-4. An updated distribution of net fluxes from open

and coastal oceans and of degradation rate constants has resulted in ocean emissions being revised 

downward from 42 Gg yr-1 (Montzka and Reimann et al., 2011) to 33 (20–44) Gg yr-1 (Table 1-4).

Since sink rates scale with the atmospheric burden, the rates of uptake by oceans, reaction with OH, 

photolysis, and soil microbial degradation continue to decline as the atmospheric concentrations have 

decreased (Table 1-4). In a recent study, Nilsson et al. (2013) proposed a significantly (~60%) faster 

reaction rate of CH3Br with OH radicals than was recommended in SPARC (2013). However, due to the 

significant difference between the new reaction rate constant and the consistent values in the existing 

literature, no major change in the recommended rate constant could be justified. The rate constant 

recommended in SPARC (2013) is only slightly different from that used in previous Assessments. The 

partial CH3Br lifetime with respect to reaction with OH and photolysis is 1.8 years, vs. 1.7 years in the 

previous Assessment. The partial lifetime for soil uptake, estimated at 3.35 years in the last Assessment, has 

been substantiated by results of Rhew et al. (2010) and Rhew (2011). The partial lifetime with respect to 

oceanic uptake has been revised upward to 3.1 (2.3–5.0) years (Hu et al., 2012) from the 2.2–2.4 years 

reported in the last Assessment based on Yvon-Lewis et al. (2009). However, when combined with the 

small reduction in the partial lifetime with respect to reaction with OH (discussed above) and the unchanged 

soil sink from the last Assessment, the overall lifetime remains unchanged at 0.8 years.

The reduction in the atmospheric abundance of CH3Br since the time that the oceanic uptake rate 

was re-examined results in a lower uptake rate in Table 1-4 than that reported above by Hu et al. (2012). 

As a result of the decrease in atmospheric CH3Br, the natural oceanic source is now comparable to the 

oceanic sink; this is consistent with the model prediction reported by Butler (1994) and Yvon-Lewis et 

al. (2009) and the near-equilibrium conditions observed in 2010 and reported by Hu et al. (2012).

1.3 VERY SHORT-LIVED HALOGENATED SUBSTANCES (VSLS)

As in previous Assessments, we consider VSLS to include very short-lived halogenated source 

gases (SGs), halogenated organic and inorganic product gases (PGs) arising from SG degradation, and 

other sources of tropospheric inorganic halogens.

Various lines of evidence suggest that VSLS may be transported from the boundary layer into the 

stratosphere, where they contribute to stratospheric halogen loading (Gettelman et al., 2009; Brioude et al., 

2010; Montzka and Reimann et al., 2011; Marecal et al., 2012). Evaluating this contribution requires 

knowledge of VSLS tropospheric degradation and removal (Box 1-2), and the spatial and temporal variability 

of emissions, loss processes (Table 1-5), and transport processes (Box 1-3). These factors have consequences 

for the calculation of Ozone Depletion Potentials (ODPs) for VSLS, as the traditional concept of a single, 

geographically independent and time-independent value does not apply (Chapter 5: Section 5.3, Table 5-4).
Chapter 1

1.32

Box 1-2. Atmospheric Chemistry of Very Short-Lived Ozone-Depleting Substances

For very short-lived (VSL) source gases (SGs), sinks include radical oxidation and 

photochemistry, resulting in typical mean local lifetimes of <6 months near Earth’s surface (see Table 1-

5). Photolysis of chlorinated SGs is slow and OH oxidation dominates tropospheric loss. Brominated SGs 

are removed by both OH oxidation and photolysis, with the latter more important for SGs containing 

multiple Br atoms (e.g., CHBr3). Oxidation of SGs by Cl atoms is also possible but given the relatively 

low tropospheric abundance of Cl atoms (~103–104 molecules cm-3) (Lawler et al., 2009), it is likely to be 

a relatively minor loss process for most SGs. Ultimately, the actual mean lifetime of a VSLS emission 

varies due to emission location/season, the distribution of tropospheric oxidants (e.g., Rex et al., 2014),

and background conditions (e.g., temperature and solar flux). As SG lifetimes can be comparable to 

tropospheric transport timescales, the seasonal/spatial variability of transport processes (e.g., Aschmann 

et al., 2009) is also a key factor controlling stratospheric source gas injection (SGI).

Degradation of VSL SGs leads to a range of product gases (PGs), which may themselves be 

transported to the stratosphere via product gas injection (PGI). The breakdown of brominated and 

chlorinated SGs can lead to carbonyl compounds (e.g., CX2O, CHXO) and minor products such as 

halogenated hydroperoxides (e.g., CHX2OOH) or peroxynitrates (e.g., CHX2O2NO2), where X=Br or Cl, 

the relative yield of which depends on background HOx and NOx loading (Krysztofiak et al., 2012). Once 

inorganic halogens are released, both gas-phase and heterogeneous reactions partition species among 

reactive (e.g., XO) and reservoir (e.g., HX) forms, controlling the fraction available for ozone destruction 

cycles or subject to tropospheric (dry/wet) deposition processes. Figure 1 highlights the principal 

reactions involved in the degradation of a typical tri-halogen SG, such as bromoform (CHBr3). In global 

models, organic PG chemistry is generally bypassed as many of these species are short lived with respect 

to their parent SG. For example, CBr2O and CHBrO have tropospheric lifetimes of ~7 and 2 days in the 

tropics, respectively (Hossaini et al., 2010). Therefore, instantaneous production of inorganic products is a 

reasonable approximation in the case of bromine (Sinnhuber and Folkins, 2006; Warwick et al., 2006a; 

Hossaini et al., 2010). PGI due to inorganic halogens may be enhanced by both multi-phase and 

heterogeneous reactions in/on liquid and frozen substrates (Crowley et al., 2010) that speciate halogens 

into radical form and thereby extend their lifetime against deposition processes (Aschmann and 

Sinnhuber, 2013).

Box 1-2, Figure 1.

The principal reactions 

involved in the degradation of a typical trihalogen very shortlived source gas (blue 

shaded). The most 

stable organic intermediates are shaded 

gray. Orange arrows 

denote reactions that 

liberate halogen atoms. 

The approximation used 

in global models, that all 

three halogen atoms are 

released instantaneously on SG degradation, is 

denoted. Also shown 

are the primary gasphase and heterogeneous reactions (green arrows) that cycle inorganic halogen species between active and 

reservoir forms. See also discussion in Ko and Poulet et al. (2003).
ODSs and Other Gases of Interest

1.33

Box 1-3. Transport of Ozone-Depleting Substances to the Stratosphere in the Tropics

Ozone-depleting substances (ODSs) are transported to the stratosphere primarily in tropical 

regions where ascent through the troposphere is dominated by convection (Figure 1). Outflow from 

convective clouds, typically between 12–14 km (Folkins and Martin, 2005), can inject boundary layer air 

that may be rich in ODSs into the tropical tropopause layer (TTL) (e.g., Gettelman and Forster, 2002;

Fueglistaler et al., 2009; Randel and Jensen, 2013). Here, over several kilometers, a transition occurs from 

the well-mixed, convectively dominated troposphere to a region of slow ascent controlled by the 

ascending branch of the stratospheric Brewer-Dobson circulation. The TTL is here defined as the layer 

between the level of maximum convective outflow (~12 km altitude, 345K potential temperature) and the 

cold-point tropopause (CPT, ~17 km, 380K). The level of zero radiative heating (LZRH) marks the 

transition from clear-sky radiative cooling to clear-sky radiative heating (Qclear, ~15 km, 360K), and above 

which (in the “upper TTL”) air masses may cross the CPT to enter the “tropical stratosphere” or 

“stratospheric overworld.” For long lived and thus well-mixed halogenated source gases (see Section 1.2), 

the details of their troposphere-to-stratosphere transport are of minor importance. However, for very 

short-lived substances (VSLS), whose lifetimes may be comparable to tropospheric transport timescales, 

transport processes—along with physical and chemical processes that occur in the TTL—may strongly 

impact their stratospheric source gas and product gas injections.

The convective transport of air masses to the TTL is zonally asymmetric and exhibits significant 

seasonal and also interannual variability (e.g., Fueglistaler et al., 2004; Ashfold et al., 2012). Preferential 

transport into the TTL takes place in strong convective source regions. Examples include boreal winter 

over the Maritime Continent (e.g., Hosking et al., 2010; Bergman et al., 2012)—located within the 

tropical warm pool, between the Indian and Pacific Oceans—and also boreal summer within Indian 

monsoon regions (e.g., Devasthale and Grassl, 2009; Devasthale and Fueglistaler, 2010) and Southeast 

Asia (e.g., Wright et al., 2011; Chen et al., 2012). Air detrained into the lower TTL enters a region of 

large-scale subsidence and will mostly descend into the mid-troposphere. Air detrained above the LZRH 

can ascend through the upper TTL, where vertical velocities and residence times vary in both space and 

time. As zonal variation in these transport timescales can be large, the location at which air enters the 

TTL, along with its horizontal transport through regions of upwelling/downwelling in relation to the 

fluctuating LZRH, strongly impact transport into the stratosphere (e.g., Gettelman et al., 2004; Tzella and 

Legras, 2011; Bergman et al., 2012). In addition to these circulations, the TTL is also characterized by 

two-way exchange with the extratropics, which may strongly impact the abundance and seasonality of 

trace gases in the TTL, including ozone (e.g., Ploeger et al., 2012).

For particularly short-lived VSLS (i.e., those with a local lifetime of several days or less at the 

surface), significant transport to the upper TTL is unlikely unless emitted close to deep convection 

(Hossaini et al., 2012a). Residence times in this layer are estimated to be in the range of 24–45 days 

(Montzka and Reimann et al., 2011). For VSLS with comparable or shorter local lifetimes, significant 

source gas (SG) to product gas (PG) conversion could take place. If product gases are subsequently 

removed from this layer, for example due to adsorption onto cirrus ice followed by sedimentation, the net 

stratospheric input of halogen from VSLS will be reduced. Particularly deep overshooting convection can 

transport air masses directly up to or above the tropopause (e.g., Pommereau, 2010), providing rapid 

transport through the upper TTL. These events could allow even the shortest-lived VSLS to be 

transported to the stratospheric overworld, though they are relatively rare (Liu and Zipser, 2005;

Takahashi and Luo, 2014) and at present their global-scale impact on stratospheric composition is 

uncertain. In addition to transport into the overworld, quasi-horizontal transport from the base of the TTL 

may provide a rapid transport route for VSLS to enter the extratropical lowermost stratosphere (i.e., above 

the tropopause but below the 380 K isentrope) (Levine et al., 2007). (continued next page)
Chapter 1

1.34

Box 1-3, Figure 1. Schematic of the convective boundary layer (CBL), tropical deep convection, and its 

interaction with the tropical tropopause layer (TTL). The temperature lapse rate minimum (typically 

between 10–12 km) is used to define the base of the TTL (taken here as 12 km) and the cold point 

tropopause (CPT) as the top (Gettelman and Forster, 2002). The level of zero radiative heating (LZRH, 

zo) marks the transition from clear-sky radiative cooling to clear-sky radiative heating. The melting level 

indicates the altitude at which ice begins to melt. Red lines denote the redistribution of mass. Pink lines 

denote typical routes for tracer (e.g., VSLS) advection. A typical temperature profile is shown in green. 

Note, the arrow sizes are not representative of the relative importance of the various transport 

components. Figure courtesy of Diane Pendlebury (University of Toronto) and Thomas Birner (Colorado 

State University).

180K 300K 220K 260K

Temperature

clear sky

radiative cooling

ubiquitous

shallow convection

overshooting

convection

TTL

lapse rate minimum

LZRH (z )0

CPT

stratospheric circulation

CBL

17 km

15 km

1 km 1

2 km

5 km melting level

Tropical Tropopause Layer and Deep Convection

deep

convective

heating

shallow outflow layer

deep outflow layer
ODSs and Other Gases of Interest

1.35

Table 1-5. Lifetime estimates for halogenated very short-lived (VSL) source gases. Local lifetimes for the tropospheric tropical and midlatitude 

regions were calculated using the OH and temperature climatology from Spivakovsky et al. (2000) and Prather and Remsberg (1993), respectively. 

Photolysis lifetimes were calculated using solar fluxes taken from the TOMCAT chemical transport model (e.g., Hossaini et al., 2012a). For the 

tropics, annually averaged values are reported along with the seasonal range of lifetimes given in parentheses. For midlatitudes, seasonally 

averaged local lifetimes (summer, fall, winter, spring) are reported. VSLS with new kinetic or photolysis laboratory studies available since the last 

Assessment are highlighted in bold, with local lifetimes calculated using the WMO (2011) method given in the footnotes.

Compound WMO (2011) 

Local 

Lifetime

(days) 1

Loss 

Process

Local Lifetime 2

Tropics (25°S–25°N)

(days)

Local Lifetime 

Midlatitude (25°N–65°N)

(days)

Notes

Boundary Layer 10 km Boundary Layer 10 km

Su F W Sp Su F W Sp

Chlorocarbons

CH2Cl2 144 OH 109 (98–133) 179 (171–185) 95 235 725 155 180 480 1070 430 3, 7

CHCl3 149 OH 112 (100–136) 190 (182–197) 97 240 750 160 190 515 1145 460 4, 7

CH3CH2Cl 39 OH 30 (27–37) 47 (45–49) 26 65 200 43 47 125 280 111 5, 7

CH2ClCH2Cl 65 OH 47 (42–58) 90 (86–93) 41 103 320 69 90 250 555 225 4, 7

CH3CH2CH2Cl 14 OH 11 (10–14) 14 (14–15) 10 24 70 15 14 37 80 32 5, 7

CHClCCl2 4.9 OH 5 (4–6) 3 (3–4) 4 9 27 6 3 8 16 6 3, 7

CCl2CCl2 90 OH 67 (60–81) 119 (114–123) 58 145 450 96 120 325 725 290 3, 7

CH3CHClCH3 18 OH 15 (14–19) 17 (17–18) 13 32 95 21 17 44 95 38 5, 7

Bromocarbons

CH2Br2 123

5000

OH

J

94 (84–114)

–

150 (144–155)

–

80

–

200

–

620

–

135

–

150

–

405

–

890

–

360

–

3

123 Total 94 (84–114) 150 (144–155) 80 200 620 135 150 405 890 360

CHBr3 76

36

OH

J

40 (36–48)

23 (21–26)

46 (44–48)

27 (25–30)

34

25

84

59

250

130

54

33

45

28

117

70

250

135

101

40

6, 9

24 Total 15 (13–17) 17 (16–18) 14 35 86 20 17 44 88 29

CH2BrCl 137 OH 103 (92–125) 174 (167–180) 89 220 685 147 175 470 1050 420 3, 7

CHBrCl2 121

222

78

OH

J

Total

65 (58–79)

108 (104–111)

41 (37–46)

82 (79–85)

114 (111–117)

48 (46–49)

56

120

38

137

305

94

410

610

245

89

160

57

81

130

50

210

300

124

460

550

250

185

165

87

6, 7

(continued next page)
Chapter 1

1.36

Compound WMO (2011) 

Local 

Lifetime

(days) 1

Loss 

Process

Local Lifetime 2

Tropics (25°S–25°N)

(days)

Local Lifetime 

Midlatitude (25°N–65°N)

(days)

Notes

Boundary Layer 10 km Boundary Layer 10 km

Su F W Sp Su F W Sp

CHBr2Cl 94

161

59

OH

J

Total

50 (45–61)

91 (87–94)

32 (30–37)

59 (57–61)

55 (54–57)

28 (28–29)

43

120

32

105

360

81

310

820

225

67

170

48

58

72

32

150

195

85

325

415

182

130

97

56

6, 7

CH3CH2Br 41 OH 32 (29–40) 45 (43–47) 28 69 210 45 45 118 260 103 3, 7

CH2BrCH2Br 70 OH 51 (46–62) 95 (91–99) 44 111 350 74 97 265 590 235 4, 7

n-C3H7Br 12.8 OH 11 (10–13) 12 (12–13) 9 23 67 15 12 30 65 26 3, 7

Iso-C3H7Br 16.7 OH 14 (13–17) 15 (15–16) 12 30 88 19 15 38 81 33 3, 7

Iodocarbons

CH3I 158

7

OH

J

114 (102–139)

4.2 (4.0–4.5)

223 (213–231)

3.6 (3.5–3.7)

99

4.3

250

9.6

780

19

165

5.6

230

3.5

620

7.5

1395

13

560

4.6

4

7 Total 4.0 (3.8–4.3) 3.5 (3.4–3.6) 4.1 9.2 19 5.4 3.4 7.4 13 4.6

CF3I 4 J 0.97 (0.9–1.0) 0.85 (0.84–0.9) 0.9 2 4 1.1 0.7 1.6 2.9 1 3, 8

CH3CH2I 17.5

5

OH

J

16 (14–19)

3.6 (3.3–3.8) 

14 (13–14)

2.9 (2.8–2.9) 

14

3.7

33

8.2

94

16.4

21

4.8

13

2.9

34

6.0

71

9.9

28

3.7

4

4 Total 2.9 (2.7–3.2) 2.4 (2.3–2.4) 2.9 6.6 13.9 3.9 2.4 5.1 8.7 3.3

Notes:

1. Instantaneous local lifetimes for OH reactive loss were calculated with [OH] = 1 × 106 molecule cm-3 and T = 275 K; photolysis lifetimes taken from WMO 

(2011).

2. Annually averaged local lifetimes with the range in seasonal lifetimes given in parentheses.

3. OH reaction rate coefficient taken from JPL 10-6.

4. OH reaction rate coefficient taken from Atkinson et al. (2008).

5. OH reaction rate coefficient taken from Yujing and Mellouki (2001).

6. OH reaction rate coefficient taken from Orkin et al. (2013b); the instantaneous local lifetimes calculated as in WMO (2011) (see footnote 1) are 21 days (48 

day OH reaction partial lifetime and 36 day partial lifetime for photolysis) for CHBr3, 60 days for CHBrCl2, and 80 days for CHBr2Cl.

7. Photolysis is a negligible loss process; total local lifetime = local partial lifetime for OH reaction.

8. OH reaction is a negligible loss process; total local lifetime = local partial lifetime for photolysis.

9. Photolysis rates calculated using UV absorption cross sections from Papanastasiou et al. (2014); photolysis rates calculated using recommendations in Sander 

et al. (2011) are ~15% greater, see Papanastasiou et al. (2014).
ODSs and Other Gases of Interest

1.37

1.3.1 Abundance, Trends, and Emissions of Very Short-Lived Source Gases

1.3.1.1 CHLORINE-CONTAINING VERY SHORT-LIVED SOURCE GASES

This section focuses on the chlorinated VSLS most widely reported in the background atmosphere, i.e., dichloromethane (CH2Cl2), trichloromethane (CHCl3), tetrachloroethene (CCl2CCl2, shortened 

to C2Cl4), trichloroethene (C2HCl3), and 1,2-dichloroethane (CH2ClCH2Cl). Long-term global 

observations are available from the AGAGE (updated from O’Doherty et al., 2001, and Simmonds et al., 

2006) and NOAA networks for CH2Cl2 and C2Cl4, and from AGAGE only for CHCl3. Annual weighted 

sums of these globally distributed measurements are given in Table 1-6 and long-term trends are shown in 

Figure 1-11. It is notable that considerable differences exist between CH2Cl2 mole fractions reported by 

the two networks. These equate to an 11.2 ppt difference in tropospheric chlorine in 2012 (Table 1-6). 

Possible causes include differences in calibration scales and in measurement locations; the relatively short 

atmospheric lifetime of this compound (3–6 months in the tropics, Table 1-5) means that it shows large 

hemispheric and regional variability. However the observed relative growth in CH2Cl2 between 2001 and 

2012 is comparable between the AGAGE (62%) and NOAA (67%) networks (i.e., during the period of 

onset of CH2Cl2 increases). In contrast, C2Cl4 abundances have decreased by 63% since the beginning of 

observations in 1994. AGAGE observations of C2Cl4 are only available from 2004 onward but both 

relative (−35%) and absolute (−0.6 ppt) changes compare well to NOAA trends in this period (−35%, 

−0.6 ppt).). For CHCl3, no significant trends are apparent since the beginning of the record in 1994. Over 

the 5-year period between 2008 and 2012, we estimate that changes in the abundances of the three VSLS 

discussed above equate to an increase of 1.3 ± 0.2 ppt Cl yr-1, and that total tropospheric chlorine from 

CH2Cl2, CHCl3, CCl2CCl2, C2HCl3, and CH2ClCH2Cl increased from 84 (70–117) ppt to 91 (76–125) ppt, 

as shown in Table 1-7.

Other chlorinated VSLS such as vinyl chloride, 1,1-dichloroethane, 1,1-dichloroethene, 1,2-dichloropropane, 1,1,2-trichloroethane, 1,1,2,2-tetrachloroethane, hexachlorobutadiene, and chlorobenzene 

have been detected in urban air (e.g., Logue et al., 2010), but there is no observational evidence for these 

compounds in background air, the upper troposphere, or stratosphere.

Estimated global emissions for CH2Cl2, CHCl3, and C2Cl4, calculated using a global 12-box 

model and using the observed mole fractions discussed above, are shown in Table 1-6. Emissions derived 

using either the NOAA or AGAGE observations (which have different station locations) are within the 

uncertainties of each other.

Table 1-6. Annual global mean mole fractions of chlorinated VSLS, and estimated emissions. 

Emissions from AGAGE and NOAA atmospheric data were calculated using a global 12-box model 

(Cunnold et al., 1983; Rigby et al., 2013, 2014), identical to the global emissions shown in Figure 1-3 for 

longer-lived ODSs.

Formula

Annual Mean Mole 

Fraction (ppt)

Growth

 (2011–2012)

Annual Global Emissions 

(Gg yr-1)

Laboratory

2008 2011 2012 (ppt yr-1) (% yr-1) 2008 2011 2012

CH2Cl2 21.7 23.9 25.1 1.2 5.0 633 ± 142 681 ± 167 752 ± 177 AGAGE, in situ1

24.8 28.4 30.7 2.3 8.1 709 ± 135 791 ± 182 841 ± 183 NOAA

CHCl3 7.21 7.39 7.53 0.14 1.9 272 ± 51 277 ± 51 285 ± 53 AGAGE, in situ

C2Cl4 1.55 1.24 1.16 −0.08 −6.5 213 ± 40 167 ± 31 160 ± 30 AGAGE, in situ

1.66 1.26 1.18 −0.08 −6.6 230 ± 50 164 ± 38 157 ± 33 NOAA

1 AGAGE calibrations as specified in CDIAC (2014) and related primary publications.
Chapter 1

1.38

Figure 1-11. Global abundances of CH2Cl2, CHCl3, and C2Cl4 as measured by the ground-based AGAGE 

(Simmonds et al., 2006, updated) and NOAA (Montzka et al., 2011, updated) networks. Global annual 

mean estimates were derived as weighted averages of monthly mean surface data from globally 

distributed observing sites (NOAA) and from the AGAGE 12-box model (AGAGE).

The atmospheric sources of chlorinated VSLS have been discussed in detail in Montzka and 

Reimann et al. (2011). In summary, anthropogenic emissions dominate strongly over natural sources with 

the exception of CHCl3 and C2H5Cl. The anthropogenic emissions of CHCl3 have been found to show a 

strong seasonality possibly affecting emission estimates (Gentner et al., 2010). Since the last Assessment 

various regional studies have confirmed anthropogenic and natural sources for chlorinated VSLS. For 

CH2Cl2, CHCl3, C2HCl3, C2Cl4, and CH2ClCH2Cl, observation-based studies have reported emissions 

most likely related to industrial and commercial processes in North America (e.g., Millet et al., 2009; 

Russo et al., 2010; Miller et al., 2012) as well as East Asia (e.g., Shao et al., 2011; Xue et al., 2011; Bian 

et al., 2013). Natural sources including biomass burning (CHCl3, C2H5Cl, and CH2ClCH2Cl), phytoplankton production (CH2Cl2), and soils (CHCl3) such as drained peat land pasture soils or blanket peat 

bogs have also been reported (Simmonds et al., 2010; Ooki and Yokouchi, 2011; Simpson et al., 2011; 

Khan et al., 2012; Fraser et al., 2014). For CHCl3 up to ~50% can be accounted for by anthropogenic 

sources (Trudinger et al., 2004; Worton et al., 2006). For C2H5Cl there are indications for both industrial 

and natural sources (e.g., Low et al., 2003; Simpson et al., 2011), but similar to C2HCl3 and CH2ClCH2Cl, 

no reliable global emission estimate is available to date.

1.3.1.2 BROMINE-CONTAINING VERY SHORT-LIVED SOURCE GASES

Very short-lived brominated trihalomethanes (e.g., CHBr3, CHBrCl2, and CHBr2Cl) and 

dibromomethane (CH2Br2) have primarily natural oceanic sources (Law and Sturges et al., 2007), with a 

small anthropogenic source from drinking water and cooling water chlorination for the trihalomethanes 

(Worton et al., 2006). There are also small anthropogenic sources of the VSLS 1-bromopropane (n-propyl 

bromide) and 1,2-dibromoethane (Montzka and Reimann et al., 2011); no new observations of these 

compounds have been reported since the last Assessment.

The atmospheric local lifetimes for CHBr3, CHBrCl2, and CHBr2Cl are revised from the previous 

Assessment (Table 1-5). This is due to new rate coefficient data for the OH reaction with CHBr3, CHBrCl2,
ODSs and Other Gases of Interest

1.39

Table 1-7. Summary of observations of VSLS source gases from the marine boundary layer (MBL) to the 

tropical tropopause layer (TTL). All table entries are mole fractions, with units of parts per trillion (ppt). Note 

that many of the upper troposphere measurements were made at least one decade ago. For those gases that 

show trends (notably CH2Cl2 and CCl2CCl2), these data may no longer be appropriate for the present-day 

atmosphere. The mole fractions in the LZRH (used to derive the stratospheric input of VSLS chlorine source 

gases, see Table 1-9) have therefore been scaled to reflect their measured trends in the MBL; the new values

are shown in bold. The scaling factor is the ratio of the current MBL mole fraction to that reported in the last 

Assessment (shown in italics in the MBL column), which are considered concurrent with the higher-altitude data.

Marine Boundary 

Layer (MBL)

Lower TTL LZRH (z0)

a Upper TTL Tropical 

Tropopause

Height range 12–14 km 14.5–15.5 km 15.5–16.5 km 16.5–17.5 km

Potential Temperature Range 340–355 K 355–365 K 365–375 K 375–385 K

Medianb Rangec Mean b Rangec Mean b Rangec Mean b Rangec Mean b Rangec

CH2Cl2 28.4

(17.5)

21.8–34.4 17.1 7.8–38.1 14.3

(23.2)

10.8–27.8

(17.5–27.8)

13.2 9.8–28.6 12.6 7.2–30.4

CHCl3 7.5 7.3–7.8 6.8 5.3–8.2 5.7 3.5–7.9 4.8 3.5–6.6 4.9 3.3–6.4

CH2ClCH2Cl 3.7 0.7–14.5 3.6 0.8–7.0 2.7 1.6–4.9 2.2 1.2–4.0 2.0 0.6–4.3

CHClCCl2 0.5 0.05–2 0.08 0.0–0.7 0.03 0.00–0.17 0.02 0.00–0.05 0.03 0.00–0.17

CCl2CCl2 1.3

(1.8)

0.8–1.7 1.1 0.7–1.3 0.9

(0.7)

0.4–1.3

(0.3–1.3)

0.6 0.3–0.9 0.5 0.1–1.0

CH2Br2 0.9 0.6–1.7 0.89 0.6–1.2 0.74 0.59–0.99 0.66 0.43–0.83 0.52 0.3–0.86

CHBr3 1.2 0.4–4.0 0.56 0.2–1.1 0.22 0.00–0.63 0.14 0.01–0.29 0.08 0.00–0.31

CH2BrCl 0.10 0.07–0.12 0.12 0.13–0.16 0.10 0.06–0.13 0.11 0.1–0.12 0.07 0.05–0.11

CHBr2Cl 0.3 0.1–0.8 0.11 0.04–0.26 0.06 0.03–0.11 0.05 0.01–0.11 0.02 0.00–0.14

CHBrCl2 0.3 0.1–0.9 0.21 0.14–0.30 0.09 0.06–0.18 0.12 0.11–0.14 0.06 0.03–0.12

other brominated SGd <0.2 <0.2 <0.2

CH3I 0.8 0.3–2.1 0.16 0.00–0.38 0.04 0.00–0.10 0.00 0.00–0.01 0.01 0.00–0.06

Total Cl 93.4e

91f

70–134e

76–125f

67 36–103 55

(72)

38–95

(50–95)

48 38–89 46 26–93

Anthrop. Clg 76 55–115 48 22–96 39

(64)

27–72

(34–85)

34 24–68 32 17–73

Total Br 7.3 2.8–18.0 4.1 2.2–6.7 2.7 1.4–4.6 2.0 1.1–3.2 1.4 0.7–3.4

Total I 0.8 0.3–2.1 0.16 0.00–0.38 0.04 0.00–0.10 0.00 0.00–0.01 0.01 0.00–0.06

a LZRH(z0) corresponds to the level of zero clear-sky radiative heating (see Box 1-3, Figure 1). As in the previous Assessment, this 

level is at about 15 km or 360 K, where there is a transition from clear-sky radiative cooling to clear-sky radiative heating. In general, 

air masses above this level are expected to enter the stratosphere. b Note that calibration scales for VSLS differ among different research groups (see C.E. Jones et al., 2011; Hall et al., 2014). 

Abundances in the MBL are calculated from AGAGE and NOAA global 2012 data for CH2Cl2, CHCl3, and CCl2CCl2, from the 

compilation of Ziska et al. (2013) for CHBr3, CH2Br2, and CH3I (20°N to 20°S), from Brinckmann et al. (2012) for CH2BrCl, and 

from the last Assessment (Montzka and Reimann et al., 2011) for all other MBL data. Data in and above the upper troposphere have 

been compiled from observations during the PEM-Tropics A and B, TC4, Pre-AVE, and CR-AVE aircraft campaigns (Schauffler et 

al., 1999), from the SHIVA, HIPPO, and ATTREX aircraft campaigns (Tegtmeier et al., 2013), and from balloon observations (Laube 

et al., 2008, Brinckmann et al., 2012). See below for definition of field mission acronyms. c The stated observed range represents the smallest mean minus 1 standard deviation and the largest mean plus 1 standard deviation. d Estimated maximum contribution from species like C2H5Br, C2H4Br, and C3H7Br (Montzka and Reimann et al., 2011). e Average median value and range. f Mean value and range. g The anthropogenic fraction of VSLS (Anthrop. Cl) has been calculated from the sum of 90% of CH2Cl2, 50% of CHCl3, and 100% of 

CH2ClCH2Cl.

PEM-Tropics = Pacific Exploratory Missions-Tropics A (1996) and B (1999); TC4 = Tropical Composition, Cloud and Climate 

Coupling missions (2007); Pre-AVE = Pre-Aura Validation Experiment (2004); CR-AVE = Costa Rica-Aura Validation Experiment 

(2006); SHIVA = Stratospheric Ozone: Halogen Impacts in a Varying Atmosphere (SHIVA); HIPPO = HIAPER (High-Performance 

Instrumented Airborne Platform for Environmental Research) Pole-to-Pole Observations (2009–2011); ATTREX = Airborne Tropical 

Tropopause Experiment (2011).
Chapter 1

1.40

and CHBr2Cl reported by Orkin et al. (2013b), measured over a more applicable temperature range than 

previous studies, and improved temperature-dependent UV absorption spectrum data for CHBr3 reported 

by Papanastasiou et al. (2014). The new data result in a decrease of the calculated partial lifetime due to 

OH reaction for CHBr3, CHBrCl2, and CHBr2Cl by ~35% from those given in the previous Assessment, 

and an overall decrease in the atmospheric photolysis rate of CHBr3 of the order of ~15% in the tropical 

troposphere, the region most critical for transport to the stratosphere. The combination of these new 

laboratory data implies that photolysis accounts for 50 to 70% of the CHBr3 removal in the tropical 

troposphere (see Papanastasiou et al., 2014), which is less than obtained using the JPL10-6 recommendations used in the previous Assessment.

The relatively short local lifetimes of brominated VSLS, combined with spatially and temporally 

varying sources, means that determining global budgets for these gases requires extensive global-scale 

observations. For example, Ashfold et al. (2014) found that around two thirds of the measured CHBr3 at a 

site in Borneo may be due to emissions in a region covering less than 1% of the tropics.

A number of emission estimates for brominated halocarbons have been reported since the last 

Assessment. Ziska et al. (2013) derived the first global climatology for CHBr3 and CH2Br2 from a global 

database of measured halocarbon mole fractions, and determined a lower global flux of bromine from the 

oceans to the atmosphere than other estimates (Table 1-8). However the authors acknowledged that coastal 

(e.g., Carpenter et al., 2009; Liu et al., 2011) and other elevated emissions were likely underestimated 

in their climatology. Coastal VSLS emissions exhibit significant variability due to differing types and

Table 1-8. Fluxes of total bromine from bromoform (CHBr3) and dibromomethane (CH2Br2) in Gg 

(Br) yr-1, and iodine from methyl iodide (CH3I) in Gg (I) yr-1. Values in italics originate from regional 

studies while all other values are global studies.

Reference CHBr3 Flux (Gg Br yr-1) CH2Br2 Flux (Gg Br yr-1 ) CH3I Flux (Gg I yr-1 )

Global Open 

Ocean

Coastal Global Open 

Ocean

Coastal Global Open 

Ocean

Coastal

Bell et al. (2002) 272

Yokouchi et al. (2005) 820 a

Warwick et al. (2006a)d,e 560 d 280 d 280 d 100

Butler et al. (2007) 800 150 650 280 50 230 550 270 280

Carpenter et al. (2009) 200

O’Brien et al. (2009) 820 a

1400 b Palmer and Reason (2009) 120 c

Liang et al. (2010) e 430 260 170 57 34 23

Jones et al. (2010) f 300 240 60

Youn et al. (2010)g 236

Pyle et al. (2011)

h 362

Ordóñez et al. (2012) e 506 62 270

Ziska et al. (2013) i 120–200 62–78 157–184

Ashfold et al. (2014) 213 (tropics only)

Liu et al. (2013) j 19–304 9–62

a Scaled to CH2Br2 emissions from Ko and Poulet et al. (2003) based on global loss rates and an estimated global burden. b Scaled to CH2Br2 emissions from Warwick et al. (2006b). c

 Tropical ocean only. d Modeling study: “Scenario 5”: 70% of 

emissions in the tropics; August/September. e Top-down estimates based on modeling of airborne measurements primarily in 

the Pacific and North American troposphere and lower stratosphere. CH3I estimate based upon Bell et al. (2002) inventory. f Bottom-up estimate from north and tropical Atlantic data only. “Coastal” CH3I emissions include shelf and upwelling fluxes. g Based upon Bell et al. (2002) global inventory. h Update of “Scenario 5” from Warwick et al. (2006b). South East Asian 

emissions scaled to give better agreement with ground-based observations. i Net flux (source – sink) reported in Ziska et al. 

(2013) based on compiled sea-air flux data from the Halocat database (https://halocat.geomar.de/ ). Range represents global 

extrapolation of data using the robust fit (lower) or ordinary least squares (upper) technique. j Extrapolated global open ocean 

fluxes reported by (Liu et al., 2013) are based on 5 cruises in the Atlantic.
ODSs and Other Gases of Interest

1.41

,

Figure 1-12. Latitudinal dependence of zonally averaged (a) CHBr3 and (b) CH2Br2 emissions (10-13 kg 

m-2 s

-1

) between 30°N and 30°S from recent top-down emission inventories (Warwick et al., 2006a

[updated in Pyle et al., 2011]; Liang et al., 2010; Ordoñez et al., 2012) and bottom-up derived emission 

inventories (Ziska et al., 2013). The figure is modified from Hossaini et al. (2013).

amounts of macroalgae (Leedham et al., 2013), thus global extrapolation of coastal emissions is subject to 

high uncertainty. Liu et al. (2013) suggested that the Atlantic Ocean has comparable or possibly higher Br 

VSLS seawater concentrations than the Pacific Ocean, in contrast to an earlier study (Butler et al., 2007). 

These differing results may be due to differences in the locations of the observations and amount of data from 

each region. Several authors (e.g., Mattsson et al., 2013; Ziska et al., 2013) have also noted the existence of 

negative saturation anomalies (i.e., net flux from the atmosphere to the ocean) for CHBr3 and CH2Br2, mostly 

in polar seas. Sparse data in these regions means that they may not be properly accounted for in global 

emission estimates. Although studies have attempted to map VSLS emissions by linking them to chlorophyll a (Ordoñez et al., 2012), brominated VSLS in seawater do not exhibit robust relationships with oceanic 

pigments (Roy, 2010; Roy et al., 2011; He et al., 2013), likely due to complex production mechanisms and 

interconversion processes (Lin and Manley, 2012; Hughes et al., 2013; Wever and van der Horst, 2013).

Ordoñez et al. (2012) assessed the ocean fluxes of CHBr3 and CH2Br2 using a global chemistryclimate model combined with surface and aircraft observations. Global estimates were in the range of 

previous top-down emission estimates (e.g., Warwick et al., 2006a; Liang et al., 2010; Ordoñez et al., 

2012) (Table 1-8). Hossaini et al. (2013) evaluated four global emission estimates, and found that no 

single inventory provided a satisfactory match between model and observations in all locations. For the 

tropics, the relatively low emissions of Ziska et al. (2013) provided the best fit with the limited available 

data. Discrepancies between top-down and bottom-up emission inventories (Figure 1-12 and Table 1-8) 

indicate that there are still insufficient data to constrain VSLS budgets to within a factor of 2–3.

1.3.1.3 IODINE-CONTAINING VERY SHORT-LIVED SOURCE GASES

Methyl iodide (CH3I)

The ocean contributes over 80% of global CH3I emissions with small contributions from rice 

production and other land sources (Redeker et al., 2000; Bell et al., 2002, Youn et al., 2010). Known 

oceanic production processes include photochemical degradation of organic matter in seawater (e.g., 

(Richter and Wallace, 2004) and phytoplankton production (e.g., Brownell et al., 2010). Observed surface 

seawater concentrations of CH3I show best agreement with global model simulations that include a 

photochemical production pathway or both a photochemical and biological production pathway 

(Stemmler et al., 2013). CH3I has potential anthropogenic sources since it is registered as a pesticide (as a 

replacement for CH3Br) in a number of countries including the U.S., Japan, and Mexico. However the 

manufacturer has withdrawn it from the U.S. market.
Chapter 1

1.42

Long-term time-series from the late 1990s of atmospheric CH3I from several remote marine sites 

are now available (Yokouchi et al., 2012) and show a decreasing trend before 2003, but increases in CH3I 

from 2003/2004 to 2009/2010 by several tens of percent. The interannual variation was linked with the 

Pacific Decadal Oscillation (PDO), suggesting that CH3I emissions are affected by global-scale sea 

surface temperature oscillations (Yokouchi et al., 2012). Seasonally, CH3I atmospheric mole fractions at 

remote marine locations outside of the polar regions tend to maximize in summer (Archer et al., 2007; 

Yokouchi et al., 2011, 2012), whereas winter maxima are observed in the Arctic due to long-range 

transport and slower atmospheric photooxidation (Yokouchi et al., 2012).

Globally, CH3I emissions are not well constrained (Table 1-8). Recent top-down model estimates 

(Youn et al., 2010; Ordoñez et al., 2012), based on the CH3I emission distribution of Bell et al. (2002), are 

about a factor of two lower than the global bottom-up estimate of Butler et al. (2007). While these model 

studies showed good agreement between simulated and observed marine boundary layer (MBL) mole 

fractions in some locations, there were regional discrepancies, indicating uncertain sources or sinks and/or 

model meteorology. A new global climatology (Ziska et al., 2013) has been calculated by interpolating 

available data onto a 1° × 1° grid, and results in even lower emissions of 158–184 Gg I yr-1, depending on 

the fit used. The approach used may underrepresent locally elevated emissions. Quantifying emissions is 

challenging because oceanic and atmospheric abundances vary significantly in space and time, and there 

are also differences between measurement calibrations (up to about a factor of 2) (C.E. Jones et al., 2011) 

used by different research groups, although these are not as large as discrepancies in emission estimates.

Other iodine-containing VSLS

Recent observations indicate that the combined ocean-to-atmosphere flux of iodine-containing 

dihalomethanes (CH2ICl, CH2IBr, and CH2I2) provides a global iodine source of ~330 ± 190 Gg I yr-1, 

comparable to that of CH3I (Table 1-8), and a surface iodine atom source 3–4 times higher than CH3I due 

to the rapid photolysis rates of these compounds (Jones et al., 2010). A number of studies have shown 

however that total organic iodine—including CH3I, CH2ICl, CH2IBr, and CH2I2—cannot account for 

observations of IO in the MBL (Jones et al., 2010; Mahajan et al., 2010; Mahajan et al., 2012; Großmann 

et al., 2013), as they contribute only about 20% of the necessary reactive iodine flux. Laboratory 

measurements suggest that instead, inorganic emissions, namely I2 and HOI (Carpenter et al., 2013), are 

the dominant contributors to MBL reactive iodine chemistry. These compounds are too reactive to be 

transported out of the MBL, though will be important contributors to particulate iodine, which has been 

observed in the upper troposphere and lower stratosphere (Murphy and Thomson, 2000).

1.3.2 Dynamics and Transport of VSLS

The last Assessment contained a comprehensive discussion of relevant dynamical processes 

controlling the transport of VSLS from the boundary layer (BL) to the tropical tropopause layer (TTL) 

and from the TTL into the stratosphere. Since then, theoretical and modeling studies have been performed 

that additionally constrain our understanding of the location and magnitude of the tropospherestratosphere transport of VSLS, the relative importance of source gas injection (SGI) versus product gas 

injection (PGI), and the total contribution of VSLS to stratospheric bromine, chlorine, and iodine; also,

new observations of both very short-lived source gases (SGs) and product gases (PGs) have been made.

Models continue to implicate the Maritime Continent as a strong convective source region where 

VSLS may be transported to the stratosphere rapidly (Levine et al., 2007; Aschmann et al., 2009; Pisso et 

al., 2010; Ashfold et al., 2012). However, uncertainties in parameterization of the boundary layer and 

convective transport (Hoyle et al., 2011; Schofield et al., 2011; Liang et al., 2014) limit the ability of 

models to calculate absolute amounts of VSLS reaching the stratosphere. The representation of very deep 

convection that penetrates the tropical tropopause (Liu and Zipser, 2005) is limited in global models 

(Hosking et al., 2010; Feng et al., 2011). A key constraint on the stratospheric SGI of VSLS is whether 

regions with particularly high surface mixing ratios are also preferred source regions for stratospheric air, 
ODSs and Other Gases of Interest

1.43

or whether a VSLS is sufficiently long-lived to be transported into these regions. Because transport 

processes also vary seasonally, the ODP (Ozone Depletion Potential; see Chapter 5) of a VSLS is 

dependent on both emission location and season (Pisso et al., 2010; Brioude et al., 2010).

Lagrangian transport calculations, combined with observed sea-to-air fluxes of VSLS in the 

Maritime Continent, have been used to infer the magnitudes of stratospheric SGI and PGI from CHBr3, 

CH2Br2, and CH3I (Tegtmeier et al., 2012, 2013). These results suggest sporadic injections of halogens 

from VSLS above the tropopause that are an order of magnitude larger than the global mean. These rare 

enhancements are highly localized in space and time and thus not representative of the global scale. 

However, they highlight a large variance that is not captured by coarse global-scale models. The “snapshot” nature of observations during individual field campaigns makes an assessment of the relative 

importance of various geographical regions challenging. For VSLS, this is exacerbated by uncertainties in 

the magnitude of tropical emissions and how they are distributed with respect to convectively active 

regions. Based on global model simulations, Liang et al. (2014) found that the largest stratospheric input 

of bromine from VSLS occurred over the tropical Indian Ocean, where the modeled surface mixing ratio 

of CHBr3 and CH2Br2 was large. Critically, these results depend on the validity of assumed surface 

emissions which, in sparsely sampled regions such as the Indian Ocean, are difficult to verify.

Interannual variability of VSLS troposphere-stratosphere transport is likely related to phases of the 

El Niño-Southern Oscillation (ENSO), through its impact on sea surface temperature (SST) (Aschmann et 

al., 2011; Ashfold et al., 2012). Using a model driven by offline meteorological analyses, Aschmann et al. 

(2011) reported 20% more CHBr3 and 6% more CH2Br2 reaching the stratosphere during a strong El Niño 

event (relative to an ENSO-neutral year). While enhanced SGI is expected to be positively correlated with 

convective activity, PGI may be anticorrelated because inorganic PGs (e.g., HBr) are highly soluble and 

can be physically removed from the troposphere in convective rainfall. Liang et al. (2014) suggest that the 

net transport of bromine from VSLS into the stratosphere is largest under low convective conditions, 

because the associated increase in PGI (2–3 ppt) greatly exceeds the minor reduction in SGI.

1.3.2.1 SOURCE GAS INJECTION (SGI)

Source gases deliver halogens to the stratosphere in the same form as they were emitted at the 

surface. For a given SG, the efficiency of SGI is determined by its tropospheric loss rate versus timescales 

for troposphere-to-stratosphere transport. New aircraft observations of VSL SGs, especially the 

brominated gases, have been reported in tropical regions. These include observations from five aircraft 

missions spanning the global troposphere over different seasons and multiple years: HIAPER (Highperformance Instrumented Airborne Platform for Environmental Research) Pole-to-Pole Observations 

(HIPPO 1–5) campaigns, 2009–2011; the Stratospheric Ozone: Halogen Impacts in a Varying 

Atmosphere (SHIVA) campaign in 2011, located in the previously poorly-sampled Maritime Continent 

region; and CARIBIC flights over the West Atlantic, Africa, and Southeast Asia. Aircraft observations 

during these campaigns were made at altitudes up to the lower TTL. Higher-altitude observations around 

the tropical tropopause have been made during the ongoing NASA Airborne Tropical Tropopause 

Experiment (ATTREX) campaign. These compiled data are reported in Table 1-7.

SGI from chlorinated VSLS

The majority of upper tropospheric data for the chlorinated VSLS shown in Table 1-7 were 

measured around a decade ago. Taken together with the surface data, the measurements apparently 

indicate a strong vertical gradient of CH2Cl2 within the troposphere, which is inconsistent with its 

relatively long lifetime compared to the analogous brominated SGs (see Table 1-5). The reason for this is 

most likely the temporal disparity between the (current) surface data and the higher-altitude data. Recent 

data from the HIPPO 1–5 campaign (Wofsy et al., 2011) show mean CH2Cl2 mixing ratios in the lower 

TTL of 23.5 (14.8–49.8) ppt, larger than the range of 14.9 (11.7–18.4) ppt reported in the last 

Assessment. The CHCl3 mean mixing ratio in the lower TTL was 6.0 (4.7–8.2) ppt, within the range of 
Chapter 1

1.44

7.1 (5.9–9.2) ppt reported previously. No new observations of chlorinated VSLS have been reported 

above the level of zero radiative heating (LZRH), where previous measurements suggested a SGI of 55 

(38–80) ppt of chlorine from VSLS (Montzka and Reimann et al., 2011). For CH2Cl2 and C2Cl4, gases 

that show observable trends in the boundary layer (Figure 1-11), we therefore scale mole fractions around

the LZRH by the ratio of current MBL abundances to those reported in the last Assessment, which were

concurrent with the compiled upper tropospheric data. We therefore suggest an increase in the VSLS 

chlorine SGI from 55 ppt to 72 (50–95) ppt, to take into account likely increases in CH2Cl2 abundances 

near the tropopause.

SGI from brominated VSLS

The estimated stratospheric SGI of bromine from VSLS, based on available observations around 

the tropical tropopause, is unchanged since the last Assessment (Table 1-7). Observations of the major 

brominated VSLS, CHBr3 and CH2Br2, during HIPPO 1–5 show tropical mean mole fractions of 0.47 

(0.14–1.13) ppt and 0.84 (0.58–1.09) ppt in the lower TTL, respectively. These values are generally in 

close agreement with the compiled mean and range reported in the last Assessment. Over Borneo, aircraft 

observations made during the SHIVA campaign show a total of 4.35 (±0.6) ppt of organic bromine from 

CHBr3, CH2Br2, CH2BrCl, CHBr2Cl, and CHBrCl2 at approximately 12 km (Sala et al., 2014). Similarly, 

a total of 4.2 ppt was obtained at 10–13 km from observations of the same suite of VSLS made during 

CARIBIC flights over Southeast Asia (Wisher et al., 2014). These estimates are in close agreement with 

the 4.3 (2.8–6.5) ppt of organic bromine reported in the last Assessment. At higher altitudes, in 2008 

Brinckmann et al. (2012) reported balloon-borne observations of these five VSLS over Teresina, Brazil,

up to the tropical tropopause. Around the LZRH, total organic bromine from VSLS was observed to be 

2.25 ppt, in reasonable agreement with the 2.7 (1.4–4.6) ppt reported in the last Assessment. At 17.5 km, 

total organic bromine from VSLS was observed to be 1.35 ppt and thus within the previously reported 

range of 0.7–3.4 ppt.

Global model simulations suggest SGI contributes on average ~50% and ~90% of the total 

bromine reaching the stratosphere from CHBr3 and CH2Br2, respectively (Aschmann et al., 2011; 

Hossaini et al., 2012a). Somewhat lower estimates of 21% (CHBr3) and 74% (CH2Br2) were derived from 

a single set of balloon-borne observations (Brinckmann et al., 2012). For global models, explicit 

representation of SGI requires a sound treatment of VSLS emissions. The modeled contribution of VSLS 

to stratospheric bromine has been shown to vary by a factor of ~2 (Hossaini et al., 2013) when using the 

different available emission inventories (Liang et al., 2010; Pyle et al., 2011; Ordoñez et al., 2012; Ziska 

et al., 2013).

The proximity of emissions to convective source regions likely leads to geographical variation in 

SGI efficiency (Aschmann et al., 2009; Tegtmeier et al., 2012, 2013). The spatial distribution and 

seasonality of the primary tropospheric oxidant, the hydroxyl radical (OH), also leads to a significant 

variation in the lifetimes of less photolabile VSLS (Table 1-5). Over the West Pacific warm pool, an [OH] 

minimum has been inferred (Rex et al., 2014) based on reported low levels of tropospheric ozone from 

sonde, satellite, and aircraft data, in qualitative agreement with earlier observations (e.g., Kley et al., 

1996). The lifetime of CH2Br2 was calculated to be up to a factor of 3 longer within this “OH hole” 

relative to typical Atlantic conditions (Figure 1-13), suggesting that regionally, a larger fraction of 

CH2Br2 may escape tropospheric oxidation to reach the TTL over the warm pool. Once in the TTL, the 

local lifetime of CH2Br2 can be long (~500 days) due to the strong temperature dependence of the CH2Br2

+ OH reaction, meaning stratospheric SGI is likely (Hossaini et al., 2010). Future changes to tropospheric 

[OH], for example due to a projected methane increase/decrease, could alter the local lifetime and SGI of 

CH2Br2 substantially (Hossaini et al., 2012b) (Figure 1-14).

SGI from iodinated VSLS

Available high-altitude CH3I observations in the last Assessment showed that mixing ratios in the 

TTL at 15 km were generally below 0.1 ppt, leading to the conclusion that no more than 0.05 ppt of iodine
ODSs and Other Gases of Interest

1.45

Figure 1-13. Top: Observed [OH] 

(106 molecules cm-3) and O3 mixing 

ratio (ppb) as a function of solar 

zenith angle (SZA) from the NASA 

Stratospheric Tracers of Atmospheric Transport (STRAT) aircraft 

mission (1995–1996) near Hawaii. 

Observations are taken above 11 

km altitude. Analysis of back 

trajectories revealed an air mass

originating from the West Pacific 

region containing relatively low O3

and [OH]. The black line denotes 

the compact relation described in 

Hanisco et al. (2001). Bottom:

Observed O3 columns from satellite 

and sonde data, along with the 

modeled OH column from GEOS 

CHEM. This analysis indicates an 

“OH hole” region in the maritime 

continent, where the lifetime of 

CH2Br2 is significantly enhanced. 

Modified from Rex et al. (2014).

Figure 1-14. Modeled 2100 change in (a) OH abundance (molecules cm-3) and (b) CH2Br2 lifetime due to 

OH oxidation, τOH, (%) under projected IPCC RCP 4.5 and 8.5 climate scenarios (relative to 2000). The 

dashed lines denote cold-point tropopause under each scenario. Modified from Hossaini et al. (2012a).

SZA (deg)

Air mass from

West Pacific

0 20 40 60 80

OH concentration [106 cm-3] 3

2

1

0

(b) O3: GEOS Chem

(c) OH: GEOS Chem

(a) O3: TES & Sondes

eg)

60 80

(b) O3: GEOS Chem

(c) OH: GEOS Chem

(f) CH2Br2

188

55

(g) SO2

18

5

Lifetimes [days]

(a) O3: TES & Sondes
Chapter 1

1.46

enters the stratosphere as CH3I at the CPT. New high-altitude observations in the East Pacific region, 

along with associated modeling (Tegtmeier et al., 2013) are consistent with this conclusion, showing 

0.01–0.02 ppt of CH3I around the tropical CPT. The authors inferred considerably larger mixing ratios in 

the tropical West Pacific with 0.08 ppt CH3I at the tropical CPT, calculated using a Lagrangian transport 

model and observed sea-air fluxes of CH3I. The annual modeled mean over the inner tropical latitude 

bands between ~20°S and 20°N was ~0.05 ppt. Based on observed correlations between large oceanic 

CH3I emissions and strong vertical uplift, however, a small amount of air was projected to carry larger 

amounts of CH3I, with 5.5% of air at the tropical CPT calculated to have mixing ratios larger than 0.2 ppt.

Shorter-lived iodinated VSLS (e.g., CH2ICl) with lifetimes of hours to a few days are unlikely to 

reach the stratosphere in significant amounts. Hossaini et al. (2012a) estimated with a global model that 

on average <1% of the surface mixing ratio of an idealized 6-hour lifetime tracer in the MBL was able to 

reach the CPT over the tropical West Pacific. However, such compounds contribute to longer-lived 

inorganic iodine product gases (Box 1-2; Saiz-Lopez et al., 2012), which could release reactive iodine at 

higher altitude.

1.3.2.2 PRODUCT GAS INJECTION (PGI)

The degradation of VSL SGs in the troposphere is expected to produce a range of organic and 

inorganic PGs. If these PGs evade tropospheric removal processes, such as dry/wet deposition, they may 

be transported to the stratosphere via PGI. Observational evidence for PGI is limited, and in general 

global models have limited representation of the multi-phase and microphysical processes that, coupled 

with sub-grid scale transport processes, determine the efficiency of PGI. Since the last Assessment, 

observations of inorganic PGs have been made in tropical regions, though observations in the TTL remain 

sparse. A number of recent modeling studies have also attempted to further constrain estimates of PGI 

from brominated VSLS.

PGI from chlorinated VSLS

The estimate of total stratospheric PGI from chlorinated VSLS is essentially unchanged since the 

last Assessment, at 25 (0–50) ppt Cl. This estimate is derived from observations of hydrogen chloride 

(HCl) and phosgene (COCl2) observed around the LZRH (Marcy et al., 2007; Mebarki et al., 2010; 

Brown et al., 2011) of up to 20 and 32 ppt Cl, respectively. As noted in previous Assessments, chlorinated 

PGs are also produced following the breakdown of long-lived SGs in the stratosphere, and thus the 

possibility of “double counting” exists if they are recirculated into the troposphere (Montzka and 

Reimann et al., 2011). Thus, between 0 and 100% of the observed COCl2 and HCl could originate from 

VSLS. Recent aircraft observations report evidence for episodic enhancements of ClO in the TTL (up to 

40 ppt) in air of tropospheric origin (von Hobe et al., 2011). Heterogeneous chlorine activation, also 

observed around the tropopause at midlatitudes (Thornton et al., 2007), may occur on ice and/or liquid 

aerosol particles (von Hobe et al., 2011) at cold TTL temperatures.

PGI from brominated VSLS

Although there is now evidence for free tropospheric BrO originating from surface sources of 

VSLS, with tropospheric BrO columns of around 1–3 × 1013 molecules cm-2 (Fitzenberger et al., 2000; 

Richter et al., 2002; Van Roozendael et al., 2002; Sinnhuber et al., 2005; Theys et al., 2007, 2011; 

Parrella et al., 2013), observational evidence for PG as BrO in the TTL is sparse (Dorf et al., 2008), and 

likely around the limit of detection (~1 ppt) for remote sensing instruments at the LZRH. Estimates of 

PGI from VSLS bromine are therefore derived from modeling studies. Such calculations of PGI are 

particularly sensitive to assumptions regarding partitioning of Bry, wet scavenging, and heterogeneous 

recycling. Soluble inorganic bromine (Bry) species, particularly HBr, are subject to wet deposition 

processes (Liang et al., 2010; Marecal et al., 2012) and have high uptake coefficients on ice (Crowley et 

al., 2010). HBr and HCl adsorbed to ice can be converted via heterogeneous reactions with hypohalous 
ODSs and Other Gases of Interest

1.47

acids (HOX) or halogen nitrates (XONO2) to gas phase Br2, BrCl, and/or Cl2, which are readily 

photolyzed to halogen atoms (see Box 1-2).

Previous global modeling studies simplified tropospheric removal of Bry by assuming a fixed and 

uniform loss rate (Sinnhuber and Folkins, 2006; Warwick et al., 2006a; Hossaini et al., 2010). In the last 

Assessment, PGI from CHBr3 and CH2Br2 was estimated at 0.4–3.9 ppt Br based on a model sensitivity 

study (Hossaini et al., 2010) in which the prescribed “washout lifetime” of Bry varied between 10 days 

and infinity (i.e., no tropospheric removal of Bry). More recent models speciate Bry in an explicit or semiimplicit manner and/or use a more complex representation of the dehydration processes (e.g., Aschmann 

et al., 2011; Hossaini et al., 2012a), and show that scavenging of Bry from VSLS (Bry

VSLS) is a minor loss 

process in the TTL, removing <10% (Aschmann et al., 2011; Aschmann and Sinnhuber, 2013; Liang et 

al., 2014). Models also indicate that organic PGs, such as CBr2O and CHBrO, for which no observations 

exist, may also reach the TTL, although their contribution to the total bromine PGI is expected to be 

minor (Hossaini et al., 2010; Marecal et al., 2012). The tropospheric chemistry and speciation of organic 

PGs, which are likely sensitive to background NOx and HOx loading (Krysztofiak et al., 2012), was 

discussed in Ko and Poulet et al. (2003).

Based on the modeling work discussed above, PGI makes a non-negligible contribution to 

stratospheric bromine loading from VSLS but critically depends on how rapidly SGs can ascend through 

the troposphere, where the likelihood of Bry washout decreases with altitude and may be minor once in 

the TTL (e.g., Aschmann et al., 2011). Independent model estimates of total PGI of bromine from CHBr3

and CH2Br2 are 2.5 ppt Br (Liang et al., 2010), ~1.1 ppt Br (Hossaini et al., 2012b), 1.5 ppt Br (Aschmann 

and Sinnhuber, 2013), and ≥4 ppt Br (Liang et al., 2014). These models contain a more comprehensive 

treatment of Bry than the calculations that formed the basis of the previous Assessment. However, care 

should be taken when making a direct comparison of these estimates due to variation in the modeling 

approaches. For example, only Aschmann and Sinnhuber (2013) considered the adsorption of HBr onto 

ice within the TTL, and the assumed VSLS emissions varied between these studies.

As in Montzka and Reimann et al. (2011), we estimate that PGI from minor brominated VSLS 

not considered in the studies mentioned above, such as CHBr2Cl, CHBrCl2, and CH2BrCl, could 

contribute around 0 to 0.3 ppt Br. Therefore, overall we conclude that total PGI could range from 1.1 to 

4.3 ppt Br, compared to the 0.4 to 4.2 ppt Br reported in the last Assessment.

PGI from iodinated VSLS or other iodine sources

There are no new observations of inorganic iodine (Iy) in the TTL since the last Assessment, when 

available Differential Optical Absorption Spectroscopy (DOAS) measurements (Bösch et al., 2003; Butz et 

al., 2009) suggested upper limits of 0.1 ppt IO and 0.1 ppt OIO and a total Iy level of <0.15 ppt. New 

observations of IO in the free troposphere suggest that similar levels are present (Puentedura et al., 2012; Dix 

et al., 2013). Such low levels of IO are challenging to retrieve accurately but indicate that most of the IO 

vertical column is above the MBL. This is surprising since the majority of sources are very short lived 

(Section 1.3.1.3), and could have implications for our understanding of iodine sources and/or the Ix (I + IO) 

lifetime with respect to irreversible uptake of reactive iodine to aerosol surfaces. Combined with uncertainties 

in transport and in iodine chemistry (Saiz-Lopez et al., 2012), the quantity of iodinated PGI is not known, up 

to the upper limits previously reported for IO and OIO in the TTL of 0.1 ppt (Butz et al., 2009).

1.3.2.3 TOTAL VSLS HALOGEN INPUT INTO THE STRATOSPHERE

As discussed above, VSLS contribute to stratospheric halogen loading by both SGI and PGI. 

Observations of SGs around the tropopause provide some constraint on the magnitude of SGI. 

Observational evidence for PGI is, however, still rather limited and as such its contribution remains a 

significant uncertainty. An updated estimate of SGI, PGI, and the total (SGI + PGI) contribution of VSLS 

to stratospheric halogen loading is given in Table 1-9 and is based on available SG/PG observations in the 

tropics and recent model studies.
Chapter 1

1.48

TABLE 1-9. Summary of estimated VSLS source gas (SG) and product gas (PG) contributions to 

stratospheric halogens, based on observations and model results.

Halogen or Compound Best Estimate (ppt Cl, Br, or I)

Chlorine

VSL SGs 72 (50–95)

HCl PG 10 (0–20)

COCl2 PG 15 (0–30)

Total chlorine 95 (50–145)

Bromine

VSL SGs 0.7–3.4

PG sum 1.1–4.3

Total bromine 5 (2–8)

Iodine

CH3I SG < 0.05

PG sum < 0.1

Total iodine < 0.15

Total input from chlorinated VSLS

As in the previous Assessment, “the best estimate” of total chlorine from VSLS reaching the 

stratosphere is obtained by summing the observed contribution from SGs (Table 1-7) at the tropopause 

and adding the estimated PG contribution from COCl2 and HCl. This gives a best estimate and range of 

95 (50–145) ppt. The anthropogenic fraction of VSLS chlorinated SG to the total SG at the tropopause is 

estimated to be around 70% (Table 1-7). Assuming this applies also to PGs, then we estimate ~70% of the 

total chlorine from VSLS entering the stratosphere is from anthropogenic sources.

Total input from brominated VSLS

The best estimate of bromine from VSLS that reaches the stratosphere, Bry

VSLS, is based on SG 

observations around the tropical tropopause, two BrO profiles measurements in the TTL (Dorf et al., 

2008), and an estimated PGI contribution from recent global modeling. A range is derived by summing 

the lower limits of SGI and PGI estimates as well as the upper limits (Table 1-9). This leads to a total 

estimated range of 2–8 ppt Bry

VSLS, which is slightly narrower than the reported range of 1–8 ppt in the 

last Assessment, due to constraints on recent model estimates of PGI (Liang et al., 2010; Hossaini et al., 

2012a; Aschmann and Sinnhuber, 2013; Liang et al., 2014).

An alternative approach to estimating Bry

VSLS is to use observations of stratospheric BrO 

combined with model estimates of the BrO/Bry ratio to calculate total stratospheric Bry, and subtract the 

contribution of long-lived SGs. Uncertainties in the absolute mole fractions of long-lived source gases—

CH3Br and the halons—are small (< 5%) (see Section 1.2). The overall uncertainty in the BrO/Bry ratio is 

dominated by uncertainties in chemical kinetics, which are estimated to be 10 to 30% (Hendrick et al.,

2008; McLinden et al., 2010; Salawitch et al., 2010; Parrella et al., 2012). Based on balloon-borne 

observations over Kiruna (68°N) and photochemical modeling, Kreycy et al. (2013) inferred that the

j(BrONO2)/k(BrO+NO2) ratio (i.e., the ratio of bromine nitrate photolysis to production), could be larger 

by a factor of 1.7 (+0.4, −0.2) than that obtained using JPL recommendations. This result changes 

modeled BrO/Bry ratios such that the total Bry derived from BrO observations is reduced by about 1–2 ppt 

under conditions of high stratospheric NOx levels (for which most Bry assessments are made), although 

the impact could be near zero in regions where BrONO2 is not important. While not affecting the trend in 
ODSs and Other Gases of Interest

1.49

Bry (see Section 1.4.2.2), this study implies that Bry

VSLS estimated from BrO observations could be smaller 

than considered previously.

Table 1-10 is an update from the previous Assessment and contains compiled Bry

VSLS estimates 

from ground-, balloon-, aircraft- and satellite-based measurements of BrO, with associated uncertainties. 

Resolution of the measured total BrO columns from satellite UV-visible instruments into their 

stratospheric and tropospheric contributions depends upon assumptions regarding the presence of BrO in 

the troposphere and the spatial inhomogeneity of stratospheric BrO. Theys et al. (2011), Choi et al. 

(2012), and Sihler et al. (2012) have recently addressed many of the issues associated with retrieval of 

tropospheric BrO from the satellite sensors Ozone Monitoring Instrument (OMI), Global Ozone 

Monitoring Experiment (GOME-2), and Scanning Imaging Absorption Spectrometer for Atmospheric 

Chartography (SCIAMACHY), with results that support realistic separation of tropospheric fractions of 

the measured total BrO columns.

The three new estimates of Bry

VSLS in Table 1-10 are based on measurements of BrO from the 

Aura Microwave Limb Sounder (MLS) instrument (Millán et al., 2012), SCIAMACHY (Parrella et al., 

2013), and from a balloon-borne Submillimeterwave Heterodyne Limb Sounder (SLS) (Stachnik et al., 

2013). These estimates of 5 (0.5–9.5) ppt, 7 (1–13) ppt, and 6 (3–9) ppt, respectively, fall within the 

previously reported range and support the “ensemble” value of 6 (3–8) ppt from the last Assessment 

(Montzka and Reimann, 2011). However, the discussion above regarding the j(BrONO2)/k(BrO+NO2) 

ratio suggests that the lower bound of this estimate should be revised downward, giving a higher uncertainty

Table 1-10. Estimates of inorganic bromine from very short-lived substances (Bry

VSLS) 

contribution to stratospheric bromine derived from BrO measurements. Update of Table 1-14 

from the previous Assessment (Montzka and Reimann et al., 2011), extended with new results.

Data Source

Bry

VSLS

Central Value (ppt)

Bry

VSLS

Range (ppt) References

Compilation of ground-based 

column BrO, aircraft & balloon 

BrO profiles, satellite BrO 

profiles from SCIAMACHY, 

MLS, and OSIRIS, and GOME 

and OMI satellite column BrO

6 3–8 Montzka and 

Reimann et al. (2011)

MLS satellite BrO profiles

55°S–55°N, 10–4.6 hPa

5 0.5–9.5 Millán et al. (2012)

SCIAMACHY satellite BrO 

profiles, 80°S–80°N, 15–30 km

7 1–13 Parrella et al. (2013)

SLS balloon BrO profiles

Ft. Sumner, New Mexico (34°N)

6 3–9 Stachnik et al. (2013)

Ensemble 6 (3–8) a

New, adjusted ensemble 5 (2–8) b

SCIAMACHY, Scanning Imaging Absorption Spectrometer for Atmospheric Cartography; MLS, Microwave 

Limb Sounder; OSIRIS, Optical Spectrograph and InfraRed Imager System; GOME, Global Ozone Monitoring Experiment; OMI, Ozone Monitoring Instrument; SLS, Submillimeterwave Heterodyne Limb Sounder.

a Average and range of the central values of the 15 published estimates of BryVSLS. b Ensemble values, with mean and lower bound adjusted downwards by ~1 ppt to account for larger 

j(BrONO2)/k(BrO+NO2) ratio (Kreycy et al., 2013).
Chapter 1

1.50

range, since it is not yet clear how the new results of Kreycy et al. (2013) affect individual measurements. 

We therefore suggest a new ensemble value for Bry

VSLS from BrO of 5 (2–8) ppt. This new ensemble 

range is the same as that based on SG observations and model PGI estimates (see above). Based on the 

similarity between these estimates from two different approaches, and the increased confidence in PGI 

estimates from models, we merge them to a best estimate of 5 (2–8) ppt Bry

VSLS. This inferred quantity of 

Bry

VSLS comprises a significant fraction of total stratospheric Bry and is large enough to significantly 

affect the balance of ozone in the lower stratosphere, particularly at high latitudes (e.g., Feng et al., 2007)

(see Section 1.3.3).

Total input from iodinated VSLS

The best estimate of iodine from VSLS that reaches the stratosphere, based on observed CH3I around the 

tropopause and observed upper limits of stratospheric IO and OIO (Butz et al., 2009), is <0.15 ppt, which 

is unchanged from the last Assessment.

1.3.3 Potential Influence of VSLS on Ozone

A number of modeling studies have shown that inclusion of Bry

VSLS in the stratosphere improves 

agreement between modeled and observed O3 trends (Salawitch et al., 2005; Feng et al., 2007; Sinnhuber 

et al., 2009). These models show that the influence of Bry

VSLS is largest during periods of elevated 

stratospheric aerosol, such as following large volcanic eruptions (e.g., Mt. Pinatubo in 1991), when 

heterogeneous halogen activation is enhanced. Therefore, proposed geoengineering strategies to combat 

climate change, such as stratospheric sulfate injections, may enhance the impact of VSLS on O3 (Tilmes 

et al., 2012). In a volcanic quiescent year (2000) and relative to a model run with no VSLS, Feng et al. 

(2007) reported a column O3 decrease of ~10 Dobson units (DU) at midlatitudes due to 6 ppt of Bry

VSLS in 

the lower stratosphere during 2000.

Recent chemistry-climate model (CCM) studies have also included brominated VSLS (e.g., 

Ordoñez et al., 2012). Braesicke et al. (2013) reported up to a ~20% reduction in O3 in the lower 

stratosphere in polar regions between a model run with and without Bry

VSLS under 2000 stratospheric 

conditions.

The impact of chlorinated VSLS on O3 trends has not been assessed, though relative to bromine it 

is likely to be small at present. Globally and annually averaged, the chemical effectiveness of bromine 

relative to chlorine for global O3 destruction, the alpha factor, is estimated to be ~60 (Sinnhuber et al., 

2009). The alpha factor for iodine is expected to be significantly larger, with an estimated range of 150–

300 (Ko and Poulet et al., 2003). However, at the low levels of stratospheric iodine inferred from 

observed CH3I around the tropopause and observed IO/OIO (Butz et al., 2009), models suggest that 

iodine is a very minor sink for O3 (Bösch et al., 2003).

1.3.4 New Anthropogenic VSLS

A number of short-lived compounds have been proposed as replacements for long-lived ozonedepleting substances (ODSs) and radiatively active hydrofluorocarbons (HFCs). Several of these 

substances are halogenated VSLS (i.e., lifetimes <0.5 years) and were chosen due to their low Ozone 

Depletion Potentials (ODPs) and Global Warming Potentials (GWPs). An updated summary of the 

lifetimes of the proposed replacement substances is given in Table 1-11. These compounds are discussed 

further in Chapter 5.
ODSs and Other Gases of Interest

1.51

Table 1-11. Local lifetimes of in-use and potential short-lived replacement compounds for longlived ODSs. Local lifetimes were calculated for OH reactive loss with the OH and temperature 

climatology from Spivakovsky et al. (2000) and Prather and Remsberg (1993), respectively, unless noted 

otherwise. Note that local lifetimes are estimates because the actual lifetimes of short-lived gases are 

dependent on their emission location and season as well as local atmospheric conditions (e.g., OH 

concentration and temperature).

Compound WMO 

(2011) a

Local

Lifetime

(days)

Tropics

(25°S–25°N)

Annually Averaged 

Local Lifetime (days)

Midlatitude

(25°N–65°N)

Annually Averaged 

Local Lifetime (days)

Notes

BL 10 km BL 10 km

Hydrocarbons

CH2=CHCH3 (propene) 0.35 0.31 0.27 0.47 0.50 1

(CH3)2C=CH2 (isobutene) 0.20 0.18 0.15 0.27 0.29 1

CH3CH2CH3 (propane, R-600) 12.5 9.9 13.6 16 27 2

(CH3)2CHCH3 (isobutane, R-600a) 6.0 5.2 5.6 8.1 10.7 1

CH3CH2CH2CH2CH3 (n-pentane) 3.4 2.7 3.3 4.3 6.5 3

c-CH2CH2CH2CH2CH2 (cyclopentane) 2.7 2.2 2.7 3.5 5.3 3

(CH3)2CHCH2CH3 (isopentane) 3.4 2.9 3.1 4.5 6.0 3

CH3OCHO (methyl formate) 72 60 73 95 143 4

(CH3)2CHOH (isopropanol) 2.0 1.9 1.5 2.9 2.7 2

CH3OCH2OCH3 (methylal) 2.2 1.7 1.5 2.6 2.8 5

Hydrofluorocarbons

CH3CH2F (HFC-161) 66 51 76 83 154 2

CH2FCH2F (HFC-152) 146 114 165 183 335 2

CH3CHFCH3 (HFC-281ea) 23 19 23 30 46 2

Unsaturated Fluorocarbons

CH2=CHF 2.1 2.0 1.4 3.1 2.6 2

CH2=CF2 4.0 3.7 3.0 5.7 5.4 2

CF2=CF2 1.1 1.0 0.7 1.6 1.3 2

CH2=CHCH2F 0.7 0.6 0.5 1.0 0.8 2

CH2=CHCF3 7.6 7.2 5.5 11 10 2

CH2=CFCF3 (HFC-1234yf) 10.5 9.6 8.4 15 16 2

CF2=CFCH2F ~2 ~2 ~2 ~2 6

CF2=CHCHF2 <5 <5 <5 <5 6

CHF=CFCHF2 <5 <5 <5 <5 6

CF2=CHCF3 ~2 ~2 ~2 ~2 6

(E)-CHF=CHCF3 (HFC-1234ze(E)) 16.4 15.0 12.8 23 24 2

(E)-CHF=CFCF3 4.9 4.5 3.7 6.9 6.8 2

(Z)-CHF=CFCF3 8.5 8.0 6.2 12 11 2

CF2=CFCF3 4.9 4.7 3.3 7.1 6.0 2

CH2=CHCF2CF3 7.9 7.5 5.8 11.4 10.5 2

CH2=CHCF2CF2CF3 ~8 ~6 ~10 ~10 7

(E)-CF3CH=CHCF3 ~22 ~16 ~30 ~30 8

(Z)-CF3CH=CHCF3 21.2 16.3 32 30 9

CF2=CFCF=CF2 1.1 1.0 0.8 1.5 1.6 10

(E)-CF3CH=CHCF2CF3 ~22 ~16 ~30 ~30 11

Unsaturated Chlorocarbons

CH2=CHCl 1.5 1.5 0.9 2.2 1.6 2

(continued next page)
Chapter 1

1.52

Compound WMO 

(2011) a

Local

Lifetime

(days)

Tropics

(25°S–25°N)

Annually Averaged 

Local Lifetime (days)

Midlatitude

(25°N–65°N)

Annually Averaged 

Local Lifetime (days)

Notes

BL 10 km BL 10 km

CH2=CCl2 0.9 0.9 0.5 1.3 0.9 2 

CClH=CClH 4.4 3.2 6.7 5.9 12

CHCl=CCl2 4.9 4.7 3.3 7.1 6.0 2, 13

CCl2=CCl2 90 66 119 109 245 2

CF2=CFCl 1.4 1.4 0.8 2.1 1.4 14

(E)-CF3CH=CHCl 26 24 21 37 39 15

(Z)-CF3CH=CHCl ~25 ~20 ~40 ~40 16

CF3CCl=CH2 ~25 ~20 ~40 ~40 16

CF2=CFCF2Cl ~5 ~5 ~3 ~7 ~6 17

CF2=CFCF2CFCl2 ~5 ~5 ~3 ~7 ~6 17

Unsaturated Bromocarbons

CFBr=CF2 1.4 1.3 0.9 2.0 1.6 18

CHBr=CF2 2.3 2.3 1.5 3.4 2.7 18

CH2=CBrCF3 2.7 2.6 1.8 3.9 3.3 18

CH2=CBrCF2CF3 3.1 3.0 2.0 4.6 3.6 18

CH2=CHCF2CF2Br 6.5 6.2 4.7 9.5 8.6 18

Fluorinated Ethers, HFE

CH3OCH2CF3 (HFE-263fb2) 23 19 24 30 47 19, 20

CH3OCHFCF3 (HFE-254eb2) 88 69 99 111 200 2

CH3OCH2CF2CF3 (HFE–365mcf3) 21 17 21 27 42 20, 21

CH3CH2OCF2CHF2 (HFE–374pc2) 64 50 71 80 142 2

CF3CH2OCH2CF3 (HFE-356mff) 105 79 132 129 270 2

CH3OCH(CF3)2 (HFE–356mm1) 61 49 64 79 128 22

Fluorinated Ketones

CF3CF2C(O)CF(CF3)2 (FK 5-1-12) 7–14 23

(CF3)2CFC(O)CF(CF3)2 24

CF3CF2CF2C(O)CF(CF3)2 24

Fluorinated Alcohols

CH2FCH2OH 12.9 11 11 18 22 2

CHF2CH2OH 51 42 53 66 103 2

CF3CH2OH 142 111 161 180 325 2

C2F5CH2OH 143 111 165 180 335 2

C4F9CH2OH 142 111 164 178 330 2

CF3CHFCF2CH2OH 112 85 137 138 280 1

Special Compounds

CF3CF2CF2I (1-iodo-heptafluoropropane) <2 25

CH3I (methyl iodide) 7 4.0 3.5 9.6 7.1 26

COF2 (carbonyl fluoride) 5–10 27

PBr3 <0.01 28

NH3 Few days 2, 29

CH3CH2Br (bromoethane) 41 32 45 52 90 30

 (continued next page)
ODSs and Other Gases of Interest

1.53

Notes:

a OH reactive loss partial lifetime was estimated with an OH abundance of 1 × 106 molecule cm-3 and a temperature of 275 K.

1. OH reaction rate coefficient taken from Atkinson et al. (2008).

2. OH reaction rate coefficient taken from JPL 10-6 (Sander et al., 2011).

3. OH reaction rate coefficient taken from Calvert et al. (2008).

4. OH reaction rate coefficient taken from Le Calvé et al. (1997).

5. OH reaction rate coefficient taken from Porter et al. (1997).

6. No experimental data available for the OH reaction; lifetime estimate was based on reactivity trends of fluorinated ethenes.

7. No experimental data available for the OH reaction; lifetime estimated to be similar to that of CH2=CHCF2CF3.

8. No experimental data available for the OH reaction; lifetime estimated to be similar to that of (Z)-CF3CH=CHCF3.

9. OH reaction rate coefficient taken from Baasandorj et al. (2011).

10. OH reaction rate coefficient taken from Acerboni et al. (2001).

11. Lifetime estimated to be similar to that of (E)-CF3CH=CHCF3.

12. OH reaction rate coefficient from Zhang et al. (1991).

13. Photolysis lifetime taken from Table 2-4 in Ko and Poulet et al. (2003).

14. OH reaction rate coefficient taken from Abbatt and Anderson (1991).

15. Room temperature OH reaction rate coefficient taken from Sulbaek Andersen et al. (2008).

16. Local lifetime estimated as similar to that of (E)-CF3CH=CHCl.

17. Local lifetime estimated as similar to that of CF3CF=CF2.

18. OH reaction rate coefficient taken from Orkin et al. (2002).

19. OH reaction rate coefficient taken from Oyaro et al. (2005).

20. Only room temperature rate coefficient data available; OH reaction lifetime calculated assuming E/R = 500 K.

21. OH reaction rate coefficient taken from Oyaro et al. (2004).

22. OH reaction rate coefficient from Chen et al. (2005b).

23. Estimated local lifetime range due to UV photolysis taken from Taniguchi et al. (2003).

24. Lifetime estimated to be similar to that of CF3CF2C(O)CF(CF3)2.

25. Estimated local lifetime taken from WMO (2011).

26. Losses due to OH reaction and UV photolysis, see Table 1-5.

27. Estimated local lifetime range due to heterogeneous uptake taken from Wallington et al. (1994).

28. Local lifetime taken from Table 2-1 in Law and Sturges et al. (2007); OH reaction rate coefficient taken from Jourdain et 

al. (1982); the local lifetime is probably determined by UV photolysis.

29. Local lifetime taken from IPCC/TEAP (2005); determined by washout rate.

30. See Table 1-5.

1.4 CHANGES IN ATMOSPHERIC HALOGENS

1.4.1 Tropospheric and Stratospheric Chlorine Changes

1.4.1.1 TROPOSPHERIC CHLORINE CHANGES

Total organic chlorine (CCly) in the troposphere peaked in 1993–1994 at 3660 ± 23 ppt and has 

then continuously declined for 20 years, initially at a rate of around 1% per year, reducing to a rate of 

around 0.5% yr-1 in recent years (Figure 1-15). By mid-2012, tropospheric organic Cl from anthropogenic 

(CFCs, HCFCs, and chlorinated solvents, including methyl chloroform) and natural (mainly CH3Cl) 

sources had declined to 3300 ppt (Figure 1-15 and Table 1-12). This is a decrease of 1.5% since the 2010 

Assessment report and of almost 10% when compared to the 1993 peak value, due to decreases in the 

anthropogenic Cl gases. In 2012, the CFCs and HCFCs accounted for 61% and 9%, respectively, of CCly

in long-lived gases in the lower atmosphere. Table 1-12, updated from the 2010 Assessment, shows the 

contribution of halocarbons to the total chlorine budget for three milestones: 2004, 2008 and 2012.
Chapter 1

1.54

Figure 1-15. Total organic chlorine (CCly) from the 

NOAA (gray) and AGAGE (black) global measurement networks. Quantities are based on global mean 

mole fractions of CFC-11, CFC-12, CFC-113, 

CH3CCl3, CCl4, CH3Cl, HCFC-22, HCFC-141b, 

HCFC-142b, and halon-1211 determined by the 

respective networks. CFC-114, CFC-115, CFC-112, 

and CFC-113a were estimated from measurements of 

Cape Grim archive air samples (Prinn et al., 2000; 

Laube et al., 2014) and included in records from both 

networks. NOAA HCFC and halon-1211 data were 

included in the AGAGE record for years 1992–1993 to 

provide a more complete total chlorine record. An 

additional 75–91 ppt was added to NOAA and 

AGAGE records to account for the sum of CHCl3, 

CH2Cl2, C2Cl4, and COCl2 (see Table 1-12).

Table 1-12. Contributions of long-lived halocarbons to total chlorine in the troposphere.

Total Cl (ppt) *

2004 2008 2012

Contribution to Total 

(%)

2004 2008 2012

Average Rate of Change of Total Cl **

(ppt yr-1)

 2000–2004 2004–2008 2008–2012

All CFCs 2126 2078 2024 62.6 62.0 61.34 −7.7 (1.3) –12.0 (1.0) –13.5 (0.5)

CCl4 376 358 339 11.1 10.7 10.3 –4.0 (0.6) –4.4 (0.5) –4.9 (0.7)

HCFCs 212 249 286 6.3 7.4 8.7 8.3 (0.4) 9.2 (0.2) 9.2 (0.3)

CH3CCl3 66 32 16 1.9 1.0 0.5 –17.6 (1.1) –8.4 (0.5) –4.1 (0.2)

CH3Cl 535 545 540 15.8 16.3 16.4 –0.3 (2.8) 2.5 (0.9) –1.7 (1.3)

halon-1211 4.33 4.24 3.96 0.13 0.13 0.12 0.05 (0.01) –0.02 (0.01) –0.07 (0.02)

Total Cl 3397 3352 3300 –21.0 (1.8)

–0.60%

–15.6 (1.3)

–0.46%

–13.4 (0.9)

–0.40%

* Chlorine mid-year mole fractions were derived using AGAGE, NOAA, and archive data (see Figures 1-1, 1-15).

** Total and relative Cl changes over 5-year periods, as indicated. Uncertainties (in parentheses) are one standard 

deviation based on trends determined from different global networks. Relative changes in total chlorine (in percent) 

were calculated relative to values at the beginning of each period (3484 ppt in 2000).

Values for past years differ slightly from previous Assessments because of updated calibration information, different

methods for determining global mean mole fractions, rounding errors, and the inclusion of CFC-112 and CFC-113a 

(Laube et al., 2014). Total Cl also includes 77, 84, and 91 ppt as VSLS in 2004, 2008, and 2012, respectively. 

Average trends in total Cl are based only on controlled species (not CH3Cl and VSLS).
ODSs and Other Gases of Interest

1.55

1.4.1.2 STRATOSPHERIC CHLORINE CHANGES 

Most chlorine enters the stratosphere as organic chlorine (CCly) in long-lived source gases and 

undergoes photochemical oxidation to inorganic forms (Cly) as air is transported to higher altitudes within 

the stratosphere. In the upper stratosphere, total chlorine, i.e., the sum of CCly and Cly, lags the 

tropospheric CCly time series by up to 6 years owing to timescales for air to be transported to higher 

altitudes after crossing the tropopause, depicted in Figure 1-16. It is expected that total chlorine will 

continue to decrease in the stratosphere, with a time-delay as compared to tropospheric observations. The 

leveling off of inorganic chlorine occurred in 1996–1997 in the stratosphere (Rinsland et al., 2003).

The most abundant chlorine-containing gases in the stratosphere are the “reservoirs” HCl and 

ClONO2, which can generate chlorine-containing radicals including ClO. Peak stratospheric abundances 

of ClONO2, HCl, and ClO occur near 25–30 km, 50–60 km, and 25–45 km (daytime)/38–45km (nighttime), respectively (Froidevaux et al., 2006; Sato et al., 2012; Kreyling et al., 2013).

Table 1-13 summarizes observed trends of HCl, ClONO2, and ClO derived from ground-based 

and satellite measurements of partial and total columns. Over a broad latitudinal range, observed upper 

stratospheric HCl, which is the dominant Cly compound in this region, shows trends of −0.5 to −0.8% yr-1

for various time periods between 1997 and 2010. Between 1997 to 2013 and averaged over 50oN to 50oS, 

HCl trends of −0.5 to −0.6% yr-1 are derived from HALOE (Halogen Occultation Experiment) data from 

January 1997 to November 2005 and ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform 

Spectrometer) data from February 2004 to February 2013 (A. Jones et al., 2011) (Figure 1-17). These 

measurements are made between 35 to 45 km, an altitude range particularly suitable for analysis due to 

the sensitivity of both instruments and because most source gases have been converted to inorganic 

species, primarily HCl. HALOE and ACE-FTS measurements are biased with respect to each other, due 

to non-uniform (time-dependent in the case of HALOE) sampling, and different time periods used. 

However the data shown in Figure 1-17 indicate a trend in HCl similar in magnitude to other observations 

over different time periods and locations (Table 1-13) and with the observed decrease in tropospheric 

CCly of 0.5 to 1% per year on average since 1993–1994 (Figure 1-15).

Figure 1-16. Midlatitude total chlorine evolution in the stratosphere, calculated using the vertical 

distribution of mean age (derived from observations of the age tracers SF6 and CO2) and assumptions on 

the width of the age spectrum. Tropospheric data from NOAA (using the data shown in Figure 1-15) are 

used exclusively as the basis of the calculation (updated from Engel et al., 2002).

30

25

20

15

1980 1990 2000 2010

Year

3500

3000

2500

2000

1500

Total chlorine in ppt
Chapter 1

1.56

Table 1-13. Observed inorganic chlorine changes in the upper atmosphere. 

Data Source/ 

Location

Cly Species Altitude 

Region

Rate of Change 

(yr-1)

Time 

Period

Reference

Ground-based microwave 

instrument (reanalysis)

Mauna Kea, Hawaii

(19.8°N, 204.5°E)

ClO 33 – 37 km −0.64 ± 0.15% 1995–2012 Connor et al. 

(2013)

Aura MLS + Odin SMR

20°S–20°N 

ClO 35 – 45 km −0.71 ± 0.78% Dec 2001–Nov 2008 A. Jones et al. 

(2011)

Aura MLS

60°S–60°N

HCl 50 – 65 km −0.78 ± 0.08% Aug 2004–Jan 2006 Froidevaux 

et al. (2006) 

ACE-FTS (v3.0) 

30°S–30°N

HCl 50 – 54 km −0.7 ± 0.1% 2004–2010 Brown et al. 

(2011)

HALOE and ACE-FTS

30°N–50°N, 30°S–50°S,

and 20°N–20°S

HCl 35 – 45 km −0.51% (NH), 

−0.52% (SH), 

−0.58% (tropics)

1997–2008 A. Jones et al. 

(2011)

17 FTIR NDACC stations

(80.1°N–77.8°S)

HCl Total column Between −0.36 ± 

0.67% and −1.56 ± 

0.64%

2000–2009, 

station dependent

Kohlhepp 

et al. (2012)

17 FTIR NDACC stations

(80.1°N–77.8°S)

ClONO2 Total column Between −0.07 ± 

0.52% and −4.56 ± 

0.78%

2000–2009, 

station dependent, 

without Ny Alesund

Kohlhepp 

et al. (2012)

MLS = Microwave Limb Sounder; SMR = Sub-millimetre Radiometer; ACE-FTS = Atmospheric Chemistry Experiment Fourier

Transform Spectrometer; HALOE = Halogen Occultation Experiment; FTIR = Fourier Transform Infrared; NDACC = Network 

for the Detection of Atmospheric Composition Change.

Figure 1-17. Time series of HCl anomalies at 35–45 km, averaged over 50°S–50°N. The anomalies 

represent de-seasonalized monthly averaged data for the all-instrument average (green) produced from 

HALOE v19 data from January 1997 to November 2005 and ACE-FTS v3.0/3.5 data from February 2004 

to February 2013 (Ashley Jones, University of Toronto, extended from A. Jones et al., 2011). The 

anomalies are calculated by subtracting the climatological average value for each of the 12 months 

(calculated over the time span of each instrument) from each individual month (as in A. Jones et al., 

2011). The vertical black dot-dash line at 1997 indicates the turnaround date. The solid black lines 

indicate the fitted trend to the all-instrument average before and after 1997. Trend values are given in 

percent per decade and uncertainties are 2 standard deviations. 
ODSs and Other Gases of Interest

1.57

Ground-based column data are more sensitive to HCl in the lower stratosphere, and are therefore 

potentially susceptible to short-term variability. At some ground-based stations, the total-column trends of 

HCl and ClONO2 show significant differences, with much faster ClONO2 decreases than HCl at low and 

high latitudes (Kohlhepp et al., 2012). However the mean annual cycles of HCl and ClONO2 and the 

overall trend in the stratospheric chlorine content reported by Kohlhepp et al. (2012) were in agreement 

with five model calculations, also reported in the study, which were driven by baseline scenarios from 

WMO (2003) and WMO (2007).

Recently, Mahieu et al. (2013) updated the long-term Jungfraujoch HCl column measurement time 

series (Figure 1-18), and this update significantly impacts the derived trend (−0.7% yr-1 for 1997–2011 

instead of –1.1% yr-1 for 1997–2007). Surprisingly, a flattening or even a positive trend (at the 2-σ

uncertainty level) is found for the 2007–2011 time period, although these changes are relatively small in 

relation to the atmospheric variability. A change in atmospheric circulation over this period, with more 

frequent sampling of northerly air masses at the Jungfraujoch, is a possible explanation (Mahieu et al.,

2013). Previous Assessments have also noted abrupt unexplained variations in HCl trends, i.e., which 

differ over short time periods from lagged tropospheric chlorine trends (Montzka and Fraser et al., 2003). 

The overall changes reported here for HCl, in Figure 1-17 and Table 1-13, and in previous Assessments are 

however generally consistent with expectations based on trends in tropospheric long-lived chlorine gases.

1.4.2 Tropospheric and Stratospheric Bromine Changes

1.4.2.1 TROPOSPHERIC BROMINE CHANGES

Total organic bromine in the troposphere has declined by about 2 ppt since it peaked in 1998 

(Figure 1-19), at an average rate of −0.86 ± 0.05% Br yr-1 from 1998–2012, and at −0.95 ± 0.13% Br yr-1

from 2008–2012. The majority of this decline results from reduced industrial production and emission of 

CH3Br, although the rate of CH3Br decline has slowed from ~0.14 ppt yr-1 during the last Assessment to 

0.08 ± 0.02 ppt yr-1 since 2008. During 2008–2012 total bromine from CH3Br and the halons decreased 

from 15.8 ± 0.2 ppt to 15.2 ± 0.2 ppt at an average rate of 0.14 ± 0.02 ppt yr-1, based on two independent 

networks of surface observations (see Table 1-1). In the last Assessment, there were tentative signs of a 

decline in total Br from halons, from a peak around 2007; this decline is now larger and more robustly 

determined, decreasing at an average rate of 0.06 ± 0.02 ppt Br yr-1 since 2008 (see Table 1-1). Halon-1301 

is the only anthropogenic 

bromocarbon that is still 

increasing, although the growth 

has slowed in recent years to 

0.03 ± 0.01 ppt yr-1.

Figure 1-18. Time series 

(1983–2012) of monthly-mean 

total column HCl (red circles) 

and ClONO2 (green triangles), 

as measured above the 

Jungfraujoch station (46.5°N). 

Cly total columns (blue triangles) were obtained by 

summing the corresponding 

HCl and ClONO2 data points. 

To avoid the significant variability affecting measurements in winter and spring, the time series were derived from June to November 

data. Least-square fits were applied to these data sets (black curves) to provide trends estimates. 

Updated from Montzka and Reimann et al. (2011).



	
 
 
 

 
 
 

 

 

 

 
	



 


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Chapter 1

1.58

Figure 1-19. Tropospheric 

bromine expressed as bromine 

from halons, bromine from 

halons plus CH3Br, and as 

Equivalent Chlorine (ECl, using 

α= 65) (upper panel) and 

annual changes in Br-halons 

and Br-halons+CH3Br (lower 

panel). Sums are derived from 

the NOAA/AGAGE/UEA averaged data set.

1.4.2.2 STRATOSPHERIC BROMINE CHANGES

Total stratospheric inorganic bromine (Bry, which includes Br, BrO, BrONO2, HOBr, BrCl, HBr, 

BrONO, and Br2) can be determined through modeled estimates of the inorganic product gases arising 

from bromine source gases (see Section 1.3.2.2). Another method, as discussed in 1.3.2.3, is to use 

measurements of BrO in the stratosphere and estimate the concentrations of Bry based on the calculated 

BrO/Bry concentration ratios (e.g., Dorf et al., 2006; Millán et al., 2012). Figure 1-20 shows the updated 

stratospheric Bry time series inferred from ground-based DOAS (Differential Optical Absorption 

Spectroscopy) BrO measurements at Lauder (45°S) and Harestua (60°N), and balloon-borne measurements (Dorf et al., 2006). The long- term time series of stratospheric BrO vertical column density 

measured at Harestua is shown in Figure 1-21 (update of Hendrick et al., 2008). The newly inferred trend 

values based on Harestua data alone, of +2.2 ± 0.3% yr-1 between 1995 and 2001 and of −0.6 ± 0.1% yr-1

between 2001 and 2012, are consistent with the previous estimates of Hendrick et al. (2008) of +2.5 ± 

0.5% yr-1 and −0.9 ± 0.4% yr-1, respectively, who identified a negative trend of stratospheric BrO of about 

1% yr-1 from 2001 from observations in both hemispheres. The stratospheric Bry decline is consistent with 

the observed temporal changes in total tropospheric bromine discussed above.

Recent BrO measurements imply a mean stratospheric Bry burden of 20 (16–23) ppt in 2011 

(Figure 1-20, Kreycy et al. (2013)). The estimated relative contribution to this burden from controlled 

uses of halons (~8.4 ppt in 2007, accounting for the mean age of stratospheric air) and CH3Br (~0.3 ppt in 

2007 from regulated agricultural use (non-QPS)) is within the range of the last Assessment’s estimate of 

40–45%, although it is declining slowly. Without accounting for the age of air, the estimated relative 

contributions to Bry entering the stratosphere in 2012 from controlled uses are ~8.1 ppt for halons and 

~0.15 ppt from regulated agricultural use (non-QPS) of CH3Br. Thus, VSLS bromocarbons, natural 

sources of CH3Br, and QPS uses of CH3Br (which are not controlled by the Montreal Protocol) contribute 

more than half of the stratospheric Bry burden.
ODSs and Other Gases of Interest

1.59

Figure 1-20. Changes in total 

stratospheric Bry (ppt) derived 

from balloon-borne BrO observations (squares) (update of 

Dorf et al. (2006)) and annual 

mean mixing ratios calculated 

from ground-based UV-visible 

measurements of stratospheric 

BrO made at Harestua (60°N) 

and Lauder (45°S) (filled and 

open orange triangles, respecttively) (adapted from Hendrick 

et al. (2007) and Hendrick et 

al. (2008)), using a common 

BrO absorption cross section. 

These stratospheric trends are 

compared to trends in measured bromine (ppt) at Earth’s 

surface with additional constant amounts of Bry added 

(thin lines). Dark blue line 

shows global tropospheric 

bromine from methyl bromide as measured in firn air (pre-1995, including consideration of a changing 

interhemispheric gradient; Butler et al., 1999) and ambient air (after 1995, Montzka et al., 2003) with no 

correction for tropospheric CH3Br loss. Purple line shows global tropospheric bromine from the sum of 

methyl bromide plus halons (Butler et al. (1999) and Fraser et al. (1999) through 1995; Montzka et al. 

(2003) thereafter). Thin blue lines show bromine from CH3Br, halons, plus additional constant amounts of 

3, 5, and 7 ppt Br. Total inorganic bromine is derived from (i) stratospheric measurements of BrO and 

photochemical modeling that accounts for BrO/Bry partitioning from slopes of Langley BrO observations 

above balloon float altitude (filled squares); and (ii) lowermost stratospheric BrO measurements (open 

squares and circles). For the balloon-borne observations, bold/faint error bars correspond to the 

precision/accuracy of the estimates, respectively. For the ground-based measurements (triangles), the 

error bars correspond to the total uncertainties in the Bry estimates. For stratospheric data, the date 

corresponds to the time when the air was last in the troposphere, i.e., sampling date minus estimated 

mean age of the stratospheric air parcel. For tropospheric data, the date corresponds to the sampling time, 

i.e., no corrections are applied for the time required to transport air. This figure updates Figure 1-21 from the 

previous Assessment (Montzka and Reimann et al., 2011).

Figure 1-21. Times series of 

monthly averaged ground-based 

UV-visible BrO vertical column 

densities (VCDs) at Harestua 

(60°N) (update of Hendrick et al., 

2008). The gray error bars correspond to the standard error of the 

monthly mean. The black and 

green thick solid lines represent 

the trend analyses for the 1995–

2001 and 2001–2012 periods, 

respectively. The thick straight 

lines correspond to the linear trend 

for both periods. The full data set has been optimized using improved DOAS settings (mainly: new fitting 

window (342–357 nm), O3 cross sections at 218K and 243K from Brion, Daumont, and Malicet (Brion et al., 

1998; Daumont et al., 1992; Malicet et al., 1995), Taylor expansion of O3 slant column densities in wavelength and vertical optical depth as in Pukite et al. (2010), and O4 cross sections from Greenblatt et al. (1990)).
Chapter 1

1.60

1.4.3 Tropospheric and Stratospheric Iodine Changes 

1.4.3.1 TROPOSPHERIC IODINE CHANGES 

More than a decade of atmospheric CH3I observations at several remote sites, ranging in location 

from 82.5°N to 40.4°S, have revealed an increase from 2003–2004 to 2009–2010 by several tens of 

percent, with a decreasing trend before 2003 (Yokouchi et al., 2012). The interannual variability of the 

observations corresponded with the Pacific Decadal Oscillation (PDO), suggesting that CH3I emissions 

are affected by SST-related processes on a global- and decadal scale.

1.4.3.2 STRATOSPHERIC IODINE CHANGES 

There are no new observations of inorganic iodine in the upper troposphere/lower stratosphere 

(UTLS) since the last Assessment, when available measurements (Bösch et al., 2003; Butz et al., 2009) 

suggested upper limits of 0.1 ppt IO and 0.1 ppt OIO in the UTLS and a total inorganic stratospheric 

iodine (Iy) level of <0.15 ppt.

1.4.4 Changes in Ozone-Depleting Halogen Abundance in the Stratosphere Based Upon 

Long-Lived Source Gas Measurements: Equivalent Chlorine (ECl) and Equivalent 

Effective Stratospheric Chlorine (EESC)

Changes in the stratospheric burden of total inorganic halogens (Cl and Br) can be estimated from 

changes in the calculated abundance of Equivalent Effective Stratospheric Chlorine (EESC) (Daniel and 

Velders, 2007); changes in total tropospheric halogen (Cl and Br) abundance can be addressed with the 

Equivalent Chlorine (ECl) metric (WMO, 1992). At its peak in 1994–1995, the total abundance of ECl 

was ~4450 ppt. By 2012 ECl had decreased by nearly 10%, to ~4030 ppt.

EESC is a sum of chlorine and bromine derived from ODS tropospheric abundances weighted to 

reflect their potential influence on ozone. The EESC abundance and temporal behavior is derived for 

specific regions of the stratosphere (here, as in previous Assessments, for polar and midlatitude regions), 

because it is dependent on transport timescales and respective trace gas decomposition rates (see Montzka 

and Reimann et al. (2011) for further details). We continue to use the formulation of EESC introduced by 

Newman et al. (2007), which includes a variety of parameters such as transport times (expressed as mean 

ages of air), the efficiency of different halogens to deplete ozone (expressed as alpha factors), mixing 

processes, and age-of-air-dependent ODS decomposition rates (i.e., fractional release factors, FRFs), to 

predict inorganic halogen abundances and changes in the stratosphere based on tropospheric measurements of chlorinated and brominated source gases.

EESC has continued to decrease in both the midlatitude and polar stratosphere (Figure 1-22, 

upper panel), by 16.2 ± 0.4% and 8.9 ± 1.2%, respectively, between the times of its peak values through 

to 2012. Midlatitude EESC is calculated at a mean age of 3 years and polar EESC at 5.5 years, with the 

latter being generally larger due to enhanced ODS decomposition with increasing mean age. Using the 

average of model-derived fractional release factors from Newman et al. (2007), as used in the last 

Assessment, and from a new observation-based study by Laube et al. (2013), we find that between 2008 

and 2012, EESC declined by 4.15% in midlatitudes and 3.2% in polar latitudes. As in the previous 

Assessment, we find that no single chemical class dominated these declines in EESC. In the polar 

stratosphere, CH3CCl3 was still the main contributor to this change (−1.3%), with similar contributions 

from CH3Br (−1.1%) and long-lived CFCs (−0.9%). CCl4 was a more minor contributor to the decline 

(change of −0.4%), whereas both HCFCs (+0.3%) and halons (+0.2%) were counteracting as they were 

still increasing. In the midlatitude stratosphere, the CH3CCl3 change (−1.25%) was less pronounced 

relative to the total, reflecting its decreasing contribution to total tropospheric Cl, with the EESC changes 
ODSs and Other Gases of Interest

1.61

mostly influenced by CH3Br (−1.4%). CFCs contributed −1.0%, CCl4 −0.55%, halons were contributors 

to an EESC decrease for the first time (change of −0.25%), and increases in HCFCs contributed +0.2%.

EESC calculations displayed in the lower panel of Figure 1-22 show changes in EESC relative to 

peak levels observed in the mid-1990s and amounts inferred for 1980 (Hofmann and Montzka, 2009), and 

are calculated separately using the FRFs from Newman et al. (2007) and Laube et al. (2013). The new 

FRFs do not appreciably change our understanding of the relative decline in EESC over time. We find 

38–41% recovery to 1980 levels in midlatitudes (2008: 28%) and 16–21% recovery in polar latitudes 

(2008: 10%) by 2012. We note that ozone depletion is likely to have already been significant before the 

benchmark recovery date (1980).

Figure 1-22. The Equivalent Effective Stratospheric Chlorine (EESC) was calculated for the midlatitude 

and polar stratosphere based on global mean mole fractions measured at the surface. Mean ages of 3

years (midlatitude) and 5.5 years (polar) were used along with spectral widths equal to one-half of the 

mean age. Surface data included CFC-11, CFC-12, CFC-113, CFC-114, CFC-115, CFC-112, CFC-113a, 

CH3CCl3, CCl4, HCFC-22, HCFC-141b, HCFC-142b, halon-1211, halon-1301, halon-1202, halon-2402, 

CH3Br, and CH3Cl. Surface data were derived from NOAA and AGAGE global networks and from global 

means estimated from Cape Grim archive air samples (see Figure 1-1). Calibration scale adjustments 

were made as necessary. The lower panel shows EESC relative to peak levels. Percentages on the right 

indicate the observed changes in EESC relative to the changes needed for EESC to return to 1980 levels 

(note that in 1980, more than half the EESC abundance was already from anthropogenic origin). Here, 

two EESC cases are shown: (1) using age-of-air-dependent fractional release factors (FRF) from 

Newman et al. (2007) (black lines), and (2) using age-of-air-dependent FRF from Laube et al. (2013) (red 

lines). FRFs for CFC-112 and CFC-113a were derived as in Laube et al. (2014) for both cases. EESC 

returned 38–41% (midlatitude) and 16–21% (polar) of the way toward 1980 levels by the end of 2012.
Chapter 1

1.62

Using the different FRFs (Newman et al., 2007; Laube et al., 2013), however, results in fairly 

significant differences in the absolute magnitude of reactive halogens as EESC, and different relative 

contributions of different gases to the EESC decline. The dominating limitations and uncertainties in 

EESC estimates are related to the methods used to derive inorganic halogen abundances in the 

stratosphere, which in turn relate to a limited understanding of ODS decomposition rates (expressed as 

FRFs), and mixing processes (Newman et al., 2007). Calculations of FRFs are dependent upon the 

methods used to calculate stratospheric mean ages of air (including assumptions on age spectra), 

interannual variability (especially in the Arctic winter), and long-term changes in stratospheric circulation 

(Engel et al., 2009; Stiller et al., 2012). Further, the relationship between a trace gas and the EESC 

derived from it could change with time if the tropospheric trends of the respective ODSs change (Laube et 

al., 2013); for trends changing by a few percent per year, the impact on the FRF is expected to be a few 

percent.

The study by Laube et al. (2013), who derived FRFs for 10 major ODSs (CFC-11, CFC-12, CFC113, HCFC-22, HCFC-141b, HCFC-142b, CCl4, CH3CCl3, halon-1211, and halon-1301), translates into a 

22% reduction of the total abundance of EESC from these compounds in midlatitudes and 24% in polar 

latitudes in 2008, compared to WMO (2011). In terms of the relative importance of different ODS groups, 

using the Laube et al. (2013) fractional release leads to an increased relative contribution to total EESC 

from halons and solvents, and a decrease for CFCs and HCFCs, compared to WMO (2011). This would 

affect future projections depending on the temporal evolution of the individual ODSs; note that in Figure 

1-22 the curves derived from the two fractional release data sets diverge most in recent years. In addition 

it should be noted that no VSLS are included in the EESC. This compound group quickly releases a large 

portion of its halogen in the lower stratosphere with fractional release factors close to one at relatively 

low mean ages (Pfeilsticker et al., 2000; Schauffler et al., 2003; Laube et al., 2008). The relative impact 

of VSLS on stratospheric Equivalent Chlorine is likely to be larger when using the Laube et al. (2013) 

fractional release.

1.4.5 Fluorine in the Troposphere and Stratosphere

Although the sum of fluorine from ODSs is declining, the tropospheric abundance of fluorine (F) 

(derived from CFCs -11, -12, -113, -114, -115; HCFCs -22, -141b, -142b, -124; halons -1211, -1301, -2402; 

HFCs -23, -32, -125, -134a, -143a, -152a, -227ea, -236fa, -245fa, -365mfc, -4310mee; C1-C8

perfluorocarbons (PFCs); SF6; SF5CF3; SO2F2, and NF3) was still increasing between 2009 and 2012 at a 

mean annual rate of 1.2% yr-1 or 33 ppt yr-1 and reached 2801 ppt in 2012. This recent growth in F, which 

is caused by the rising abundances of fluorine-containing replacement compounds (such as HFCs), is 

higher than that observed from 1995–2005 (29 ppt yr-1), but lower than that of the 1980s (81 ppt yr-1) 

during the period of unrestricted production and use of ODSs.

In the stratosphere, the reservoir species or product gases HF (hydrogen fluoride), COF2

(carbonyl fluoride), and COClF (carbonyl chlorofluoride) are currently produced by major ODSs and 

other source gases. In order to estimate recent changes in stratospheric fluorine product gases, only source 

gases with stratospheric lifetimes of <100 years were considered (Table 1-3). This subset of fluorinated 

source gases decreased in the troposphere with a change of around −0.5% yr-1 during 2009–2012. 

Therefore, the recent stratospheric fluorine changes are likely to be between these two ranges (−0.5% to 

+1.2% yr-1).

The stratospheric fluorine reservoir species HF, COF2, and COClF are monitored by ACE-FTS 

(Brown et al., 2011; 2014), while the ground-based Network for the Detection of Atmospheric 

Composition Change (NDACC) Fourier Transform Infrared (FTIR) network (Kohlhepp et al., 2012) 

provides time series of the more abundant HF and COF2 only. Using ACE-FTS occultation 

measurements, trends of total stratospheric fluorine were determined by Brown et al. (2014). Total 

stratospheric fluorine mole fractions increased from 2004 to 2009 by 24.3 ± 3.1 and 28.3 ± 2.7 ppt yr-1 (or 

0.96 ± 0.12 and 1.12 ± 0.11% yr-1), for the 30–70°S and 30–70°N latitude bands, respectively.
ODSs and Other Gases of Interest

1.63

Figure 1-23. Time series of monthly-mean total column HF (red circles) and 2 x COF2 (green triangles) 

(molecules per square centimeter), as derived from the Jungfraujoch station (46.5°N) for the June to 

November months, updated from Montzka and Reimann et al. (2011). The blue triangles correspond to 

the weighted sum of the HF and COF2 total columns, i.e., a very good proxy of the total inorganic fluorine 

at northern midlatitudes (COClF is the only fluorine reservoir missing, with a contribution to the Fy budget

estimated to be about 2%).

Kohlhepp et al. (2012) investigated the trend of HF at 16 NDACC stations covering the 80°N to 

77.8°S latitude range through 2009. For the vast majority of sites, positive linear trends are reported, 

generally consistent with an increase of HF at rates close to 1% yr-1 when considering the 2000 loadings 

as reference. The Jungfraujoch time series for HF (Duchatelet et al., 2010) and COF2 (Duchatelet et al., 

2009) have been updated to include all observations up to the end of 2012 (Figure 1-23). The long-term 

trends for HF, COF2, and their combination (Fy* = HF + 2×COF2) above the Jungfraujoch are all positive 

and remain in line with values reported in Kohlhepp et al. (2012) as well as in Montzka and Reimann et 

al. (2011). Overall, the remote-sensing measurements of stratospheric F indicate global trends close to a 

1% yr-1 increase between 2008 and 2012. This is smaller than trends observed during the late 1980s–early 

1990s, but within the expected changes for fluorine based on tropospheric trends in ODSs, their 

substitutes, and other fluorinated gases in recent years.

1.5 CHANGES IN OTHER TRACE GASES THAT INFLUENCE STRATOSPHERIC OZONE 

AND CLIMATE

1.5.1 Updates to Mole Fractions, Budgets, Lifetimes, and Observations

In this section, anthropogenically emitted substances that are not covered by the Montreal 

Protocol but that indirectly affect stratospheric ozone are discussed. These include long-lived greenhouse 

gases such as CH4, N2O, hydrofluorocarbons (HFCs), other fluorinated chemicals (e.g., perfluorocarbons 

(PFCs), SF6, NF3), and some other sulfur-containing gases. HFCs are a focal point because they are potent 



	
 
 
 

 
 
 

 

 

 

 
	


 
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Chapter 1

1.64

greenhouse gases and their increasing abundance in the atmosphere is a direct consequence of the 

restrictions on ODS production and consumption under the Montreal Protocol. Note that CO2 is not 

discussed because it was thoroughly discussed in the recent Intergovernmental Panel on Climate Change 

(IPCC) 5th Assessment Report (IPCC, 2013).

1.5.1.1 F-GASES

F-gases define a class of source gases with fluorine as the only halogen attached either to carbon, 

sulfur, or nitrogen. F-gases are also called Kyoto Protocol synthetics are almost solely emitted from 

anthropogenic activities. Stratospheric reservoir species such as HF (hydrogen fluoride) or COF2 (carbonyl 

fluoride) are not included here but in Section 1.4.5. F-gases do not deplete ozone but are potent greenhouse 

gases and therefore have an indirect effect on the ozone budget. They include the HFCs, the PFCs, sulfur 

hexafluoride (SF6), sulfuryl fluoride (SO2F2), and nitrogen trifluoride (NF3). Whereas HFCs have been 

introduced as replacements for ODSs under the Montreal Protocol for applications such as refrigeration 

and foam blowing, PFCs are by-products of the aluminum industry or are used in the semiconductor 

industry (IPCC/TEAP, 2005). Most HFCs and all PFCs are long-lived and have high Global Warming 

Potentials (GWPs). HFCs, in particular, were the subject of studies that forecasted that they could 

contribute considerably to climate change in the future (Velders et al., 2012, Rigby et al., 2014). In order to 

ease this environmental pressure, they are increasingly being replaced by shorter-lived alternatives such as

unsaturated HFCs (also named hydrofluoro-olefins, HFOs), or by the non-halogenated gases such as 

hydrocarbons, CO2, or not-in-kind alternatives (UNEP, 2011a, 2013a). In the group of sulfur-containing Fgases, SF6 is used as insulator gas in electrical switchgear and to a minor extent in various industrial 

applications (Maiss and Brenninkmeijer, 1998), and SO2F2 is used as a replacement for CH3Br in soil and 

grain fumigation (Mühle et al., 2009). Finally, NF3 is increasingly used in the semiconductor industry as a 

replacement for PFCs (Prather and Hsu, 2008, 2010; Fthenakis et al., 2010).

Update on observations and on atmospheric budget

Updates of the global mean abundances of F-gases measured by global networks and from archived 

unpolluted air collected at Cape Grim, Tasmania (Langenfelds et al., 1996) are given in Table 1-14 and 

Figure 1-24. Global emissions were derived from these observations, their trends, and their loss rates (i.e.,

lifetimes) as in Section 1.2 for ODSs (Figure 1-25). Regional emissions can be assessed by either extracting 

information from globally distributed measurements (e.g., Stohl et al., 2009; Rigby et al., 2010) or by using 

measurements from the source regions (e.g., Miller et al., 2012; Kim et al., 2010; Keller et al., 2012).

HFC-134a (CH2FCF3 )

Since the mid-1990s, HFC-134a has been used as replacement refrigerant for CFC-12 in mobile 

air conditioners, stationary refrigeration, as well as in foam-blowing applications, in aerosol inhalers, and 

for dry etching (Montzka et al., 1996; O’Doherty et al., 2004). In 2012 HFC-134a was the most abundant 

HFC and the two independent sampling networks (NOAA, AGAGE) show good agreement in its global 

mean mole fraction of 67.7 (67.5–67.8) ppt and also in the average annual trend of +5.0 ppt yr-1 (or 7.6% 

yr-1) in 2011–2012 (Table 1-14). Furthermore, with a radiative forcing of 11 mW m-2, HFC-134a was the 

F-gas with the largest radiative forcing in 2012. As HFC-134a has a high 100-year GWP of 1360 

(Chapter 5), low-GWP refrigerants (e.g., HFC-1234yf) are being considered as alternatives for its use in 

mobile air conditioning and other applications.

Estimated global emissions of 176 ± 39 Gg in 2012 represent an increase of 4% yr-1over 

emissions derived in 2008 (148 ± 24 Gg). Stohl et al. (2009) estimated that regional emissions were

highest in Asia and the U.S., followed by Europe, with 29%, 28%, and 17% of the global emissions, 

respectively. Despite the extrapolations involved with most of these regional studies, results from more 

recent regional studies are largely in accordance with these findings for the U.S. (Barletta et al., 2011; 

Miller et al., 2012), Europe (Keller et al., 2012), and Asia (Kim et al., 2010; Stohl et al., 2010; Fang et al., 

2012; Yao et al., 2012).
ODSs and Other Gases of Interest

1.65

Table 1-14. Measured mole fractions of selected fluorinated compounds (HFCs, PFCs, SF6, NF3, SO2F2, 

SF5CF3) and CH4, N2O, and COS.

Chemical 

Formula 

Common or 

Industrial 

Name

Annual Mean

Mole Fraction (ppt)

2008 2011 2012 

 Change

 (2011–2012)

ppt yr-1 % yr-1

Network, Method

Hydrofluorocarbons (HFCs)

CHF3 HFC-23 21.9 24.1 25.0 0.9 3.6 AGAGE, in situ (Global)

CH2F2 HFC-32 2.7 5.2 6.3 1.1 19 AGAGE, in situ (Global)

CHF2CF3 HFC-125 6.1 9.7 11.2 1.5 7.1 AGAGE, in situ (Global)

CH2FCF3 HFC-134a 48.1 62.7 67.8 5.1 7.8 AGAGE, in situ (Global)

47.6 62.7 67.5 4.9 7.5 NOAA, flask & in situ (Global)

48.4 64.3 68.9 4.6 8.3 UCI, flask (Global)

CH3CF3 HFC-143a 8.6 12.1 13.4 1.3 11 AGAGE, in situ (Global)

CH3CHF2 HFC-152a 5.8 6.7 6.9 0.2 2.9 AGAGE, in situ (Global)

5.6 6.5 6.7 0.2 3.0 NOAA, flask & in situ (Global) 

CHF2CH2CF3 HFC-245fa 0.86 1.28 1.44 0.16 12 AGAGE, in situ (Global)

CH3CF2CH2CF3 HFC-365mfc 0.44 0.59 0.65 0.06 9.7 AGAGE, in situ (Global)

CHF3CHCF3

CF3CF2(CHF)2CF3

HFC-227ea

HFC-43-10mee

0.44

0.15

0.66

0.20

0.74

0.21

0.08

0.01

11

7.9

AGAGE, in situ (Global)

AGAGE, in situ (Global)

Perfluorocarbons (PFCs)

CF4 PFC-14 77.1 79.0 79.7 0.8 1.0 AGAGE, in situ (Global)

C2F6 PFC-116 3.9 4.2 4.2 0.1 1.9 AGAGE, in situ (Global)

C3F8 PFC-218 0.50 0.56 0.57 0.01 2.1 AGAGE, in situ (Global)

c-C4F8 PFC-318c 1.11 1.20 1.24 0.04 3.2 UEA, Cape Grim

C4F10 PFC-31-10 0.17 0.17 AGAGE, flask (Global)

0.174 0.178 0.177 0.00 n.s. UEA, Cape Grim

C5F12 PFC-41-12 0.12 0.13 AGAGE, flask (Global)

0.133 0.136 0.134 0.00 n.s. UEA, Cape Grim

C6F14 PFC-51-14 0.26 0.27 AGAGE, flask (Global)

0.245 0.252 0.252 0.00 n.s. UEA, Cape Grim

C7F16 PFC-61-16 0.11 0.12 AGAGE, flask (Global)

0.095 0.108 0.107 0.00 n.s. UEA, Cape Grim

C8F18 PFC-71-18 0.09 0.09 AGAGE, flask (Global)

Other fluorinated compounds

SF6 Sulfur 

hexafluoride

6.42 7.28 7.58 0.30 4.1 AGAGE, in situ (Global)

6.46 7.30 7.59 0.29 4.0 NOAA, flask & in situ (Global)

(continued next page)
Chapter 1

1.66

Chemical 

Formula 

Common or 

Industrial 

Name

Annual Mean

Mole Fraction (ppt)

2008 2011 2012 

 Change

 (2011–2012)

ppt yr-1 % yr-1

Network, Method

NF3 Nitrogen

trifluoride

0.59 0.86 AGAGE, flask (Global)

SO2F2 Sulfuryl

fluoride

1.5 1.7 1.8 0.1 5.4 AGAGE, in situ (Global)

SF5CF3 0.149 0.152 0.153 0.001 n.s. UEA, Cape Grim

Other compounds

CH4 (ppb) Methane1 1787.9 1803.8 1808.9 5.1 0.28 AGAGE, in situ (Global)

1787.4

1785.3

1803.1

1798.1

1808.3

1807.5

5.2

9.4

0.29

0.52

NOAA, flask & in situ (Global)

UCI, flask (Global)

1785.2 1802.9 1806.5 3.6 0.20 CSIRO, flask (Global)

N2O (ppb) Nitrous oxide 321.6 324.1 325.0 0.85 0.26 AGAGE, in situ (Global)

321.6 324.2 325.0 0.84 0.26 NOAA, flask & in situ (Global)

321.4 324.0 324.9 0.93 0.29 CSIRO, flask (Global)

321.7 324.2 325.1 0.9 0.28 WMO/GAW (Global)

COS (ppt) Carbonyl 

sulfide

491 491 493 2 0.4 NOAA, flask & in situ (Global)

Mole fractions in this table represent independent estimates measured by different groups for the years indicated. 

Results indicated as “Global” are estimates of global surface mean mole fractions. Numbers in italics are from single 

sites that do not provide a global estimate.

Absolute changes (ppt yr-1) are calculated as the difference in annual means; relative changes (% yr-1) are the same 

difference relative to the average between 2011 and 2012 values. Small differences between values from previous 

Assessments are due to changes in calibration scale and methods for estimating global mean mole fractions from a 

limited number of sampling sites. n.s.: not significant.

These observations are updated from the following sources: Prinn et al. (2000); O’Doherty et al. (2004); Simpson et al. 

(2004); Montzka et al. (2007); Simpson et al. (2007); Miller et al. (2008); Montzka et al. (2009); Chevallier et al. 

(2010); Dlugokencky et al. (2011); Hall et al. (2011); Ivy et al. (2012a); Laube et al. (2012); Oram et al. (2012); 

Simpson et al. (2012); Sturges et al. (2012); Arnold et al. (2013); Thompson (2014).

AGAGE, Advanced Global Atmospheric Gases Experiment (http://agage.eas.gatech.edu/) with AGAGE calibrations as 

specified in CDIAC (2014) and related primary publications; NOAA, National Oceanic and Atmospheric 

Administration, U.S. (http://www.esrl.noaa.gov/gmd/dv/site/); UEA, University of East Anglia, United Kingdom 

(http://www.uea.ac.uk/environmental-sciences/research/marine-and-atmospheric-sciences-group); UCI, University of 

California, Irvine, U.S. (http://ps.uci.edu/~rowlandblake/research_atmos.html); Cape Grim: Cape Grim Baseline Air 

Pollution Station, Australia; WMO/GAW, World Meteorological Organization, Global Atmosphere Watch, World Data 

Center for Greenhouse Gases, http://ds.data.jma.go.jp/gmd/wdcgg.

1

Global mean estimates for CH4 from the WMO/GAW network are not included here because the criteria used for data 

selection in the WMO/GAW global mean mole fraction calculation are inconsistent with other global mean estimates 

shown. While NOAA, AGAGE, and CSIRO contribute data to the WMO/GAW network, the addition of inland and 

high-altitude sites in the WMO/GAW global mean leads to estimates for CH4 that are ~11 ppb larger than those shown 

here.
ODSs and Other Gases of Interest

1.67

Figure 1-24. Global mole fractions of F-gases. Continuous measurements by the AGAGE network are 

shown as solid lines; NOAA data are shown by blue diamonds. Global mole fractions that have been 

compiled from grab samples or air archive measurements (e.g., from Cape Grim, Australia) are shown 

using additional symbols.

HFC-23 (CHF3 )

The mean global mole fraction of HFC-23 reached 25 ppt in 2012, and has increased at a rate of 

~1 ppt yr-1 or 3.6% yr-1 in recent years (Table 1-14). At this global abundance, HFC-23 contributed 4.5 

mW m-2 to the atmospheric radiative forcing in 2012. Trends of HFC-23 from ground-based measurements are similar to increases derived from remote sensing instruments (Harrison et al., 2012) (Table 1-

2). However, calculated absolute mole fractions are around 30% higher from remote sensing data than 

from ground-based measurements.

HFC-23 is emitted into the atmosphere nearly exclusively as a by-product from over-fluorination 

during the production of HCFC-22, with only minor emissions from fire extinguishers, semiconductor 

industry, refrigeration, and as a feedstock for halon-1301 (Oram et al., 1998; Miller et al., 2010). Many 

HCFC-22 production facilities have destroyed the co-produced HFC-23 before it was emitted into the 

atmosphere or optimized the chemical process to minimize its formation (Miller et al., 2010; Han et al.,
Chapter 1

1.68

Figure 1-25. Global emissions of F-gases estimated by a global 12-box model (as described in Rigby et 

al. (2013)) using data shown in Figure 1-24 and lifetimes from SPARC (2013).

2012). For developing countries, this capability was facilitated by funding from the Clean Development 

Mechanism (CDM) under the Kyoto Protocol of the United Nations Framework Convention on Climate 

Change (UNFCCC).

Global emissions of HFC-23 estimated from measured and derived atmospheric trends reached a 

maximum of 15 Gg yr-1 in 2006, fell back to 8.6 Gg in 2009, and subsequently increased again to 12.8 Gg 

in 2012 (Figure 1-25, update of Miller et al., 2010 and Montzka et al., 2010). Whereas efforts in nonArticle 5 countries mitigated an increasing portion of HFC-23 emissions through 2004, the temporal 

decrease from 2007 to 2009 was likely caused by destruction facilitated by the CDM, even though HCFC22 production was highest around this time (Figure 1-8). The recent resurgence in emissions since 2009 

could be the result of an increase in production of HCFC-22 (see Figure 1-8) with no subsequent 

incineration of HFC-23 (reference case in Miller and Kujipers, 2011), or less CDM-aided destruction of 

existing production in developing countries. Indeed, Miller and Kuijpers (2011) warned that HFC-23 

emissions could surpass the historic peak values from 2006 if CDM projects ceased to be supported and 

feedstock production of HCFC-22 grows unabated.
ODSs and Other Gases of Interest

1.69

Current emissions of HFC-23 occur foremost in East Asia. Studies from Yokouchi et al. (2006), 

Stohl et al. (2010), and Kim et al. (2010) estimate emissions in China to be in the range of 6 to 12 Gg yr-1

between 2004 and 2008. In contrast, Yao et al. (2012) estimated lower emissions of only 2.8 Gg yr-1 for 

China in 2010–2011, based on measurements at one site and a limited catchment area. In Europe,

underreported emissions of HFC-23 from some HCFC-22 production facilities were found by Keller et al. 

(2011), but the difference of around 0.2 Gg yr-1 was small in comparison to global sources.

HFC-152a (CH3CHF2)

HFC-152a is used as a foam-blowing agent and as an aerosol propellant (Greally et al., 2007). Its 

growing average global mole fraction reached 6.8 ppt in 2012. The global mole fraction of HFC-152a 

grew at an average rate of 0.69 ± 0.04 ppt yr-1 from 2005–2008, but has slowed since 2008 to around 0.28 

ppt yr-1 (Figure 1-24, Table 1-14). Global emissions derived from measured global mole fractions and 

trends appear to have stabilized at ~50 Gg yr-1 since 2010 (Figure 1-25). HFC-152a has a relatively small 

GWP100 (of 133; Chapter 5) and its direct radiative forcing is small compared to other HFCs.

Currently the U.S. is the world’s most important source region for HFC-152a. Estimated U.S. 

emissions range from 25 (11–50) Gg yr-1 between 2004–2009 (Miller et al., 2012), to 12.3–15.1 Gg yr-1 in 

2006 (Stohl et al., 2009), to 32 Gg yr-1 in 2008 (Barletta et al., 2011). European emissions were estimated 

to be 2.9 Gg in 2009 (Keller et al., 2012). Emissions from China were estimated to be 2.0–2.9 Gg yr-1 in 

2010–2011 by Yao et al. (2012), which was lower than 3.4–5.7 Gg yr-1 estimated by Yokouchi et al. 

(2006), Kim et al. (2010), and Stohl et al. (2010) in former years.

HFC-32 (CH2F2 ), HFC-125 (CHF2CF3 ), HFC-143a (CH3CF3 ) 

These three HFCs are mostly used as refrigerants. They are blended in various combinations, for 

stationary air conditioners as well as for various minor applications (e.g., for fire suppression) replacing 

HCFC-22 and CFC-115 (IPCC/TEAP, 2005; O’Doherty et al., 2009). Global background mole fractions 

of HFC-32, HFC-125, and HFC-143a are steadily growing (Table 1-14, Figure 1-24). Current annual 

growth rates of more than 1 ppt yr-1 are among the highest for all F-gases, showing the importance of 

these refrigeration blends in connection with the phase-out of ozone-depleting HCFCs and CFCs. Global 

estimates of their emissions in 2012 were 19 Gg yr-1, 40 Gg yr-1, and 24 Gg yr-1 for HFC-32, HFC-125, 

and HFC-143a, respectively. During 2009–2012 the emissions approximately doubled for HFC-32 and 

HFC-125, and increased by ~50% for HFC-143a. The combined radiative forcing of these three 

substances was 5.4 mW m-2 in 2012, with highest impact from HFC-125 (2.6 mW m-2).

Regional emissions of these three gases have been estimated by several studies in recent years 

(2004–2011). However, differing time periods and the rapid increase of emissions hinder the direct 

comparison with total global emission estimates. Estimated emissions from the last decade from East Asia 

as estimated by Li et al. (2011) and Yao et al. (2012) were of the same order of magnitude as estimated 

emissions from Europe (O’Doherty et al., 2009; Keller et al., 2012) and from the U.S. (Miller et al., 2012)

for different years during this same period.

HFC-245fa (CF3CH2CHF2 ) and HFC-365mfc (CF3CH2CF2CH3 )

HFC-245fa and HFC-365mfc are replacements for HCFC-141b in foam-blowing applications 

(Vollmer et al., 2006; Stemmler et al., 2007; Vollmer et al., 2011). In 2012 global average mole fractions 

reached 1.44 and 0.65 ppt for HFC-245fa and HFC-365mfc (Table 1-14), respectively, and were 

increasing between 2011–2012 at similar rates of 12% and 10% (Table 1-14). The approximately factorof-two difference in the global mean mole fractions for these two compounds is also reflected in the 

2011–2012 growth rates of 0.17 ppt and 0.07 ppt for HFC-245a and HFC-365mfc, respectively. Global 

atmospheric-derived emissions of HFC-245fa and HFC-365mfc leveled off after 2006 but showed a

renewed increase since 2010 and reached 8.2 Gg yr-1 for HFC-245fa and 3.1 Gg yr-1 for HFC-365mfc by 

2012 (Figure 1-25).
Chapter 1

1.70

HFC-227ea (CF3CHFCF3 )

HFC-227ea is used in fire suppression, metered dose inhalers, refrigeration, and foam blowing. 

Vollmer et al. (2011) recently used archived air from both hemispheres to reconstruct the atmospheric 

history of HFC-227ea. They inferred that the global background mole fraction of HFC-227ea has grown 

from less than 0.1 ppt in the 1990s to 0.58 ppt in 2010 and that the annual growth rate of HFC-227ea 

increased from 0.026 ppt yr-1 in 2000 to 0.069 ppt yr-1 in 2010 (Vollmer et al., 2011). Global emissions 

were estimated to be 2.5 Gg yr-1 in 2010. These results were confirmed by firn air samples from 

Greenland (Laube et al., 2010), which showed similarly low mole fractions in the 1990s and increasing 

global emissions of nearly 2 Gg yr-1 in 2007. In 2012 the global background mole fraction was 0.74 ppt 

(Table 1-14) and global emissions were estimated at 3.3 Gg yr-1 (Figure 1-25).

HFC-43-10mee (CF3CF2CHFCHFCF3 )

HFC-43-10mee is used as a cleaning solvent in the electronics industry. First published 

measurements by Arnold et al. (2014) show a rising global mean mole fraction between 2000 and 2012 

(0.04 ± 0.03 ppt to 0.21 ±0.05 ppt). Based on these measurements, global emissions were estimated as 

1.13 ± 0.31 Gg yr-1 in 2012.

HFC-1234yf (CH2=CFCF3 ) and HFC-1234ze(E) (E-CHF=CHCF3 )

HFC-1234yf and HFC-1234ze(E) are unsaturated hydrofluorocarbons (also referred to as 

hydrofluoro-olefins, HFOs) with estimated tropospheric OH-lifetimes of 8–16 days and 13–24 days, 

respectively (Table 1-11). These substances have small Global Warming Potentials (GWPs) and are 

therefore considered as replacement compounds for long-lived HFCs with high GWPs. Whereas HFC1234ze(E) is already used for foam blowing, HFC-1234yf has only recently been accepted as a 

replacement for HFC-134a in mobile air conditioners and other refrigeration uses (UNEP, 2011a)

(Chapter 5).

Although these unsaturated HFCs degrade within days to weeks in the troposphere, there are 

concerns regarding the impact of their degradation products on the environment. Whereas HFC1234ze(E) degrades to short-lived intermediates, the atmospheric degradation of HFC-1234yf almost 

exclusively yields trifluoroacetic acid (CF3C(O)OH, TFA) (Hurley et al., 2008). TFA is resistant to 

further degradation in the environment and exhibits some herbicidal properties (Boutonnet et al., 1999). 

Under an upper-limit scenario of full replacement of HFC-134a by HFC-1234yf, Henne et al. (2012) and 

Papasavva et al. (2009) estimate that European and U.S. emissions of HFC-1234yf could reach ~20 Gg 

yr-1 and 11–25 Gg yr-1, respectively. There is currently no imminent danger connected to this potential 

input of TFA into the environment (Chapter 5). Accumulation of TFA in specific biomes from the longterm usage of HFC-1234yf is discussed in Cahill et al. (2001) and Russell et al. (2012).

Perfluorocarbons (PFCs)

Perfluorocarbons (PFCs) exclusively consist of carbon and fluorine. They are not substitutes for

ODSs, and they have very long atmospheric lifetimes of up to several thousand years (Table 1-3). In 

combination with their very large radiative efficiencies, they will have a long-lasting influence on the 

radiative balance of the atmosphere (Ravishankara et al., 1993; Myrhe et al., 2013). The combined 

radiative forcing of the PFCs was 6.0 mW m-2 in 2012, with CF4 as the main contributor.

Four PFCs were reported in the last Assessment (PFC-14 or CF4, PFC-116 or C2F6, PFC-218 or 

C3F8, and PFC-c-318 or c-C4F8). Ground-based mole fractions and growth rates for CF4, C2F6, and C3F8

were updated from Mühle et al. (2010) and are shown in Table 1-14 and Figure 1-24. CF4 observations 

based on remote-sensing techniques (Mahieu et al., 2014) find a comparable trend in the atmospheric 

abundance as for the ground-based measurements (Table 1-2). Furthermore, mole fractions and trends of 

c-C4F8 have been updated by Saito et al. (2010) and Oram et al. (2012), with a global mole fraction in 

2012 estimated at 1.24 ppt (Table 1-14) and estimated global emissions of 1.1 Gg yr-1 in 2007 (Oram et 

al., 2012). PFC-218 was shown to be a minor PFC emission from aluminium smelting, the major PFCs 

being PFC-14 and PFC-116 (Fraser et al., 2013).
ODSs and Other Gases of Interest

1.71

Since the previous Assessment, atmospheric mole fractions and emissions have been newly 

reported for n-C4F10, n-C5F12, n-C6F14, n-C7F16, and n-C8F18 in three recent publications (Ivy et al., 2012a,

2012b; Laube et al., 2012). As shown in Table 1-14, the mole fractions of all five long-chain PFCs are 

currently below 0.3 ppt. Their current growth rates are small and have continued to decrease in recent 

years, which could be due to the introduction of emission reduction techniques in industrial applications 

(Tsai et al., 2002). With nearly 1.5 Gg yr-1 in the 1990s highest emissions from these group of compounds 

was reached by n-C6F14 (Figure 1-25). In recent years emissions of all these PFCs were stable and smaller 

than 0.5 Gg yr-1.

Lifetime estimates for the perfluorocarbons (PFCs) C3F8, c-C3F6, and C4F10 were revised in this 

Assessment (Table 1-3). PFCs are persistent greenhouse gases removed primarily in the upperstratosphere and mesosphere (>65 km) mainly by Lyman-α (121.6 nm) photolysis. Lifetime estimates for 

PFCs (>2000 yr) are typically obtained from model calculations and are highly dependent on transport 

from the lower atmosphere. The revised lifetime estimates of these three PFCs shown in Table 1-3 are 

based on a correlation of an increase in Lyman-α absorption cross section with an increase in the –CF2-

sub-units within the molecule. Baasandorj et al. (2012) reported improved upper-limits for O(1D) reactive 

rate coefficients for C2F6, c-C4F8, n-C5F12, and n-C6F14, which reduces the calculated contribution of 

O(1D) reaction to their atmospheric loss further from the rate coefficient studies of Zhao et al. (2010) and 

Ravishankara et al. (1993). Furthermore, the lifetime for C8F18 was estimated to be ~3000 years by (Ivy et 

al., 2012a), which was adopted in this Assessment.

Sulfur hexafluoride (SF6 )

The global average mole fraction of sulfur hexafluoride (SF6) continues to increase, and reached 

7.6 ppt in 2012 (Table 1-14). The global average mole fraction at the surface was increasing at ~0.22 ppt 

yr-1 in the early 2000s, but has averaged ~0.28 ppt yr-1 since 2007 (Rigby et al., 2010; Hall et al., 2011). 

Due to its long lifetime (3200 years; Table 1-3) combined with a high radiative efficiency, the 

contribution of SF6 to radiative forcing is increasing accordingly. The resulting radiative forcing in 2012 

was 4.3 mW m-2.

Remote sensing techniques have also contributed to the monitoring of SF6 over the recent years. 

Brown et al. (2011) using ACE-FTS data, Stiller et al. (2012) using MIPAS global data, and Zander et al. 

(2008) using ground-based solar spectroscopy at Jungfraujoch all found growth rates which were 

comparable with the in-situ measurements (Table 1-2).

Global atmospheric-based emissions of SF6 were estimated by Levin et al. (2010) and Rigby et al. 

(2010) at 7.2–7.5 Gg yr-1 in 2008. Emissions since then have increased and were at their highest historic 

levels in 2012 at almost 8 Gg yr-1 in 2012 (Figure 1-25). Rigby et al. (2010) found that the rise in global 

emissions from 2004–2008 was likely mostly due to emissions from Asian developing countries. 

Consistent with this, Fang et al. (2013) estimated the contribution from East Asia to SF6 emissions to be 

3.8 ± 0.5 Gg yr−1 in 2009, or a contribution of about 50% to global SF6 emissions. In addition, based on 

an extrapolation of results from the northeastern U.S. only, Miller et al. (2012) reported U.S. emissions of 

1.4 (0.7–3.0) Gg yr-1 from 2004–2009, which is equivalent to about 20% of global emissions in 2008.

Trifluoromethylsulfurpentafluoride (SF5CF3 )

This substance was discovered in the atmosphere by Sturges et al. (2000), with a global 

background mole fraction of 0.12 ppt in 1999 and 0.15 ppt in 2010 (Sturges et al., 2012). SF5CF3 is very 

long lived, with an estimated lifetime of 650–950 years (Table 1-3). SF5CF3 levels have been stable in 

recent years and therefore Sturges et al. (2012) concluded that emission sources have ceased. They 

provide strong indications that SF5CF3 was released as a by-product of the production of perfluorooctanyl 

sulfonate (PFOS) and similar compounds. Furthermore, they used firn air measurements to place the 

onset of SF5CF3 emissions in the early 1960s. Baasandorj et al. (2012) reported improved upper limits for 

the O(1D) reactive rate coefficient of SF5CF3, thereby enhancing knowledge of its atmospheric loss 

processes from previous studies but not changing its lifetime estimate (Ravishankara et al., 1993; Zhao et 

al., 2010).
Chapter 1

1.72

Nitrogen trifluoride (NF3 )

NF3 is used in the production of flat panel displays, in plasma etching, and in the semiconductor 

industry as a replacement for PFCs (Weiss et al., 2008; Fthenakis et al., 2010). It was first measured in 

the atmosphere by Weiss et al. (2008). The measured record was recently extended and revised with a 

new calibration (Arnold et al., 2012, 2013). Its global tropospheric mole fraction was 0.86 ± 0.04 ppt in 

2011 (Table 1-14) with a yearly rate of increase of 0.10 ± 0.01 ppt (11%) between 2010 and 2011.

Global emissions of NF3 increased continuously from 0.21 Gg yr-1 in 1998 to 1.18 Gg yr-1 in 2011 

(Arnold et al., 2013; Figure 1-25). With a radiative forcing of just 0.2 mW m-2, the effect of NF3 on 

climate was still very small in 2011. However, its large atmospheric growth rate and its application in the 

growing semiconductor industry have a high potential to increase its importance in the future. Therefore, 

NF3 was added to the basket of greenhouse gases in the Doha Amendment to the Kyoto Protocol, which 

covers emissions in a second commitment period of 2013–2020 (UNFCCC, 2014).

The NF3 lifetime estimate was revised in SPARC (2013) to 569 (454–764) years based on 2-D 

model calculations that included the NF3 UV absorption spectrum temperature dependence reported by 

Papadimitriou et al. (2013a). SPARC (2013) also recommended a revision of the O(1D) + NF3 reaction 

rate coefficient, although the impact of the revision on the NF3 lifetime is minor.

Sulfuryl fluoride (SO2F2 ) 

Sulfuryl fluoride (SO2F2) replaced the ozone-depleting CH3Br as a fumigant against animal pests 

in buildings and other places susceptible to infestation (e.g., flour mills, grain silos, transport containers). 

The average global mole fraction of SO2F2 has increased to 1.8 ppt in 2012, with a yearly increase (2011–

2012) of 0.1 ppt (5%) (update of Mühle et al., 2009; Table 1-14). The total atmospheric lifetime of SO2F2

is 36 ± 11 yr (Mühle et al., 2009), with a partial lifetime for the oceanic uptake of 40 ± 13 yr as its most 

important contributor. Global emissions calculated from atmospheric observations and the estimated 

lifetime were 3.1 Gg in 2012. This is an increase of nearly a factor of two in comparison with 2008.

1.5.1.2 NITROUS OXIDE (N2O)

Nitrous oxide (N2O) has both natural and anthropogenic sources and unlike most other chemicals 

discussed in this section, it has a direct chemical influence on ozone (Ravishankara et al., 2009). The

influence of N2O on stratospheric ozone and on climate has been the focus of a recent review (UNEP, 

2013c). Photochemical degradation of N2O in the stratosphere leads predominately to N2 and O2, but about 

10% is converted to nitrogen oxides (NO, NO2) (UNEP, 2013c), which contribute to stratospheric ozone 

depletion. Current ODP-weighted emissions of N2O from anthropogenic activities are larger than those of 

any other ozone-depleting species (Ravishankara et al., 2009). Nitrous oxide is also a greenhouse gas, and 

with the atmospheric burden of CFC-12 decreasing, both of these gases contribute about equally to radiative 

forcing (Myhre et al., 2013) and are after CO2 and CH4 the most important anthropogenic greenhouse gases.

Atmospheric N2O has increased from a pre-industrial mole fraction of 271 ppb (Ciais et al., 2013)

to 325 ppb in 2012 (Table 1-14) with a fairly constant growth rate of 0.8 ppb yr-1 over the last decade (3.4 

ppb between 2008 and 2012). According to UNEP (2013c), current natural emissions (e.g., from 

terrestrial, marine, and atmospheric sources) are roughly 11 Tg N2O-N yr-1. Total gross anthropogenic 

emissions are estimated to contribute another 6.2 Tg N2O-N yr-1. Anthropogenic sources include 

agriculture, biomass burning, and industry (including combustion, production of nitric acid and adipic 

acid), as well as indirect emissions from reactive nitrogen leaching, runoff, and atmospheric deposition. 

The observed increase in atmospheric N2O over preindustrial levels is largely the result of nitrogen-based 

fertilizer use (Park et al., 2012). Ciais et al. (2013) have estimated that food production was likely 

responsible for 80% of the increase in atmospheric N2O in recent decades.

The IPCC AR5 report lists total global N2O emissions of 17.8 Tg-N yr-1 in 2006 (Ciais et al., 

2013). This value is consistent with global emissions of 17.5 to 20.1 Tg-N yr−1 estimated between 1999 

and 2009 (calculated from atmospheric observations and the estimated lifetime (Thompson et al., 2014)), 

and also with bottom-up estimates of 17.6 Tg-N yr-1 from UNEP (2013c). There are, however, substantial 
ODSs and Other Gases of Interest

1.73

uncertainties associated with both bottom-up and top-down emissions estimates due to uncertain emission 

factors (bottom-up) and uncertainties in the stratospheric sink (top-down). Revision of emissions factors 

between AR4 and AR5 resulted in reapportionment of global emissions among anthropogenic sources, 

but did not significantly affect the global total (Ciais et al., 2013). The global lifetime of N2O has also 

recently been updated from 114 yr to 123 yr with a range of 104–152 yr (SPARC, 2013).

1.5.1.3 METHANE (CH4)

In addition to its influence on radiative forcing, methane affects the efficiency for ODSs to deplete 

stratospheric ozone by acting as a sink for reactive chlorine (producing HCl as a reservoir species) and as a 

source of stratospheric water vapor. In the upper stratosphere, enhanced CH4 concentrations lead to ozone 

loss through the HOx catalytic cycle, but also reduce ozone loss by sequestering reactive chlorine. In the 

lower stratosphere and troposphere, additional CH4 leads to more ozone through photochemical smog 

chemistry and CH4 also reacts with OH radicals, which leads to an influence on the lifetimes of ODSs that 

also react with OH (such as HCFCs and VSLS). In general, an increase in global CH4 results in an increase 

in column ozone (Portmann et al., 2012; Revell et al., 2012; Shindell et al., 2013).

Wetlands are the primary natural source of CH4, with smaller contributions from sources such as 

geological seeps and freshwater (Ciais et al., 2013). Anthropogenic sources include agriculture (e.g., rice 

production, ruminants), landfills, biomass burning, and the extraction and processing of fossil fuels (Kirschke 

et al., 2013). The global mean mole fraction of CH4 was 1803 ppb in 2011 (Hartmann et al., 2013) and 1808 

ppb in 2012 (Table 1-14). Mole fractions today are more than 2 times greater than those in preindustrial times 

(1750) (Hartmann et al., 2013). After increasing from ~1750 to the 1980s, global CH4 mole fractions 

increased more slowly in the late 1990s and started to stabilize in the early 2000s, but increased again from 

1781 ppb in 2007 to 1808 ppb in 2012. Reasons for the growth rate slow-down in the 1990s and renewed 

increase beginning in 2007 are debated (Rigby et al., 2008; Dlugokencky et al., 2009; Aydin et al., 2011; 

Bousquet et al., 2011; Kai et al., 2011; Levin et al., 2012; Simpson et al., 2012; Kirschke et al., 2013). The 

subsequent increase of global CH4 levels since 2006 is likely due to increased emissions from natural

wetlands and fossil fuels, although their relative contributions remain uncertain (Kirschke et al., 2013).

1.5.1.4 COS, SO2

Carbonyl sulfide (COS) and other sulfur-containing gases such as sulfur dioxide (SO2) contribute 

to stratospheric sulfate aerosols (SSA) (SPARC, 2006).

Sources of SO2 include fossil fuel combustion, volcanoes, and oxidation of precursors. Fossil fuel combustion accounts for the largest part of the total flux of sulfur gases to the atmosphere, mainly from sources in the 

Northern Hemisphere (SPARC, 2006). While SO2 emissions were reduced in the U.S. and Europe in the 1980s and 

1990s as part of efforts to reduce acid rain, emissions from East Asia have increased in recent years (Lu et al., 2010).

Sources of COS include the oxidation of dimethyl sulfide (DMS) and carbon disulfide (CS2), and oceanatmosphere gas exchange (SPARC, 2006). Sinks of COS include uptake by terrestrial plants and soils, and 

oxidation by OH radicals. Current tropospheric mole fractions of COS (~490 ppt, Table 1-14) are substantially 

higher than preindustrial values of 300–400 ppt (Montzka et al., 2004). Total column COS measurements above 

Jungfraujoch indicate a decrease in the total column from 1990–2002 followed by an increase from 2002–2008 

(update from Zander et al., 2005). A relatively small trend in global COS derived from surface observations (1.8 

ppt yr-1) was reported in the last Assessment for the period 2000–2008 (Montzka and Reimann et al., 2011). 

Recent observations from the NOAA surface network updated through 2012 suggest that any systematic changes 

in global COS since 2000 have been small (<3%), with an increase of 0.4% from 2011–2012 (Table 1-14).

The fraction of COS contributing to SSA is uncertain, but could be about 30% (SPARC, 2006). 

This is supported by recent work by Hattori et al. (2011), Brühl et al. (2012), and Schmidt et al. (2013). 

However, it is not yet possible to reconcile these studies with an earlier study from Leung et al. (2002),

who concluded that COS is only a minor contributor to SSA.
Chapter 1

1.74

1.6 POLICY-RELEVANT INFORMATION HIGHLIGHTS 

1.6.1 HCFCs Becoming a Larger Fraction of Tropospheric Chlorine; Bromine from Halons

Now Decreasing 

As a result of the Montreal Protocol, the overall abundance of controlled ozone-depleting 

substances (ODSs) in the atmosphere has been decreasing for over 15 years. The reduction in the 

atmospheric abundance of an ODS in response to controls on production depends principally on two 

factors: (1) how rapidly an ODS is used and released to the atmosphere after being produced and (2) the 

lifetime for the removal of the ODS from the atmosphere. Much of the decline in tropospheric chlorine 

since the peak in the 1990s was due to decreases in methyl chloroform (CH3CCl3), which has a relatively 

short atmospheric lifetime of about 5 years. This substance still continues to make a significant 

contribution to declines in total chlorine, although decreases in chlorofluorocarbons (CFCs) are now the 

largest contributor. Hydrochlorofluorocarbon (HCFC) mixing ratios continue to increase, although at a 

declining rate.

CFCs still represent the largest fraction of tropospheric chlorine, but their contribution has been 

decreasing since 2005. The rapid decrease of CH3CCl3 in the atmosphere means that its relative 

contribution to the tropospheric ODS abundance is now approaching zero. Since the peak in total 

tropospheric chlorine, the relative contribution of carbon tetrachloride (CCl4) has not changed 

significantly, due to its relatively slow decline. The abundance of methyl chloride (CH3Cl), the largest 

natural contributor to chlorine, has remained fairly constant over the last decades, currently contributing 

around 17% of tropospheric chlorine. A large proportional change to the total chlorine-containing ODS 

abundance however comes from HCFCs; their contribution has more than doubled since the mid 1990s.

The largest contributor to the decline in tropospheric bromine is methyl bromide (CH3Br), which 

has both natural and anthropogenic sources. The rate of CH3Br decline has slowed as phase out of controlled emissions is now almost complete, and the balance of emissions is now overwhelmingly of natural 

origin, with the remainder mostly from non-controlled emissions. While the contribution of halons to total 

tropospheric bromine has increased since the mid-1990s, bromine from halons is now showing robust signs 

of decline. Natural sources contribute over half of the abundance of total tropospheric bromine.

Figure 1-6-1. Relative contribution to total tropospheric chlorine and total tropospheric bromine from 

individual and groups of compounds in 1996 and 2012. The sum of very short-lived species (CH2Cl2, 

CHCl3, C2Cl4, COCl2) is shown as “other gases” for chlorine, while halon-1202 and halon-2402 are 

included as “other gases” for bromine.
ODSs and Other Gases of Interest

1.75

1.6.2 VSLS Chlorinated Compounds Become More Relevant for Stratospheric Ozone

The current (2008–2012) increase in tropospheric very short-lived substance (VSLS) chlorine 

source gases is ~1.3 ± 0.3 ppt Cl yr-1, compared to the decline in long-lived controlled chlorinated 

substances of 13.4 ± 0.9 ppt Cl yr-1. Averaged over the longer time period of 2004–2013, the combined 

trend of the three major VSLS chlorine source gases CH2Cl2, C2Cl4, and CHCl3 is 1.8 ± 0.2 ppt Cl yr-1

(Figure 1-6-2). Increased levels of dichloromethane (CH2Cl2), which has predominantly anthropogenic 

sources, account for the majority of this change. The globally averaged surface abundance of CH2Cl2 has 

increased by ~60% over the last decade. The majority (>80%) of VSLS chlorinated gases and associated 

product gases are expected to reach the stratosphere, based upon observed vertical profiles of CH2Cl2 and 

and model calculations of CH2Br2, a gas with a similar atmospheric lifetime.

Figure 1-6-2. Average global, monthly mean values of total tropospheric chlorine from three VSLS gases 

(CH2Cl2, C2Cl4, and CHCl3) derived from 12-box model output using NOAA and AGAGE data (Simmonds 

et al., 2006; Montzka et al., 2011). Linear fits are shown as the thicker lines, starting 2004. The trend from

AGAGE: 1.6 ± 0.2 ppt Cl yr-1; from NOAA: 2.0 ± 0.2 ppt Cl yr-1; average trend: 1.8 ppt Cl yr-1. A constant 

21 ppt, derived from AGAGE data, was used to represent the contribution of CHCl3.

1.6.3 Radiative Forcing of ODSs and ODS Replacement Compounds

Update on the effect on the radiative budget of F-gases

In Figure 1-6-3 the radiative forcing values for ODSs and F-gases (source gases with fluorine as 

the only halogen attached either to carbon, sulfur, or nitrogen; also called Kyoto Protocol synthetics) are 

compared against those of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). In 2012 the 

total contribution from the F-gases was 33 mW m-2, with 22 mW m-2 from hydrofluorocarbons (HFCs), 6

mW m-2 from perfluorocarbons (PFCs), and 5mW m-2 from SF6, SO2F2, and NF3. The most important 

single HFC in terms of climate forcing in 2012 was the cooling agent HFC-134a. However, other HFCs 

used in cooling applications, such as HFC-125, HFC-32, and HFC-143a, are increasing and the sum of 

their radiative forcing surpassed that of HFC-23 (a by-product of HCFC-22 production) and is now equal 

to the sum of the PFCs. Radiative forcing from SF6 has continued its growth at a stable rate of 0.16–0.17 

mW yr-1 in recent years. SO2F2 and NF3 currently contribute very little to climate forcing.

In 2012 the total contribution of the F-gases was still small in comparison to the total 

anthropogenic-induced climate forcing due to the major greenhouse gases (1850 mW m-2 for CO2, 490 

mW m-2 for CH4, and 170 mW m-2 for N2O) and also compared to the total ODS contribution (330 mW

m-2), which has remained virtually stable since the last Assessment.

90

80

70

60

50

Chlorine (ppt)

2000 2002 2004 2006 2008 2010 2012

 NOAA

 AGAGE
Chapter 1

1.76

Figure 1-6-3. Left panels: The evolution of radiative forcing in W m-2 from the sum of the major 

greenhouse gases (CO2, CH4, N2O), the ODSs (CFCs, HCFCs, halons, solvents (CH3CCl3, CCl4)), and 

the Kyoto Protocol synthetic gases (F-gases (HFCs, PFCs, SF6). Right panels: The evolution of radiative 

forcing from Kyoto Protocol synthetic gases (and their sums) as well as specified F-gases. Other HFCs 

combine all measured HFCs from Table 1-14, except HFC-134a and HFC-23. Data are from Table 1-1 

and Table 1-14; radiative efficiencies are from Chapter 5. Radiative forcings are calculated according to 

Myhre et al. (2013). This figure represents an update of Figure 1-25 from the last Assessment (Montzka 

and Reimann et al., 2011).

1.6.4 GWP-Weighted Emissions of ODS and ODS Replacement Compounds

The emissions of CFCs, HCFCs, and HFCs in terms of their influence on climate (as 

measured by GtCO2-equivalent yr-1 emissions) were roughly equal in 2012. However, the emissions 

of HFCs are increasing rapidly, while the emissions of CFCs are going down and those of HCFCs 

are essentially unchanged. The 100-year GWP weighted emissions for the sum of CFC, HCFC, HFC, 

halons, and chlorinated solvents emissions was 2.3 GtCO2-eq in 2012. The sum of GWP-weighted 

emissions of CFCs was 0.73 ± 0.25 GtCO2-eq yr-1 in 2012 and has decreased on average by 11.0 ± 1.2%

yr-1 from 2008 to 2012. The sum of HCFC emissions was 0.76 ± 0.12 GtCO2-eq yr-1 in 2012 and has been 

essentially unchanged between 2008 and 2012. Finally, the sum of HFC emissions was 0.69 ± 0.12 

SF6

SO2F2

NF3

1985 1990 1995 2000 2005 2010

0.001

0.002

0.003

0.004

total PFCs

total HFCs

HFC-23

HFC-134a

other HFCs

0.005

0.010

0.015

0.020

Kyoto Protocol synthetics

total HCFCs

HCFC-22

HCFC-141b

HCFC-142b

0.01

0.02

0.03

0.04

0.05

1985 1990 1995 2000 2005 2010

0.1

0.2

0.3

0.4

0.5

1.2

1.4

1.6

1.8

Radiative Forcing (W m-2) 2.0

2.2

2.4

2.6

2.8

total

CO2

CH4

ODSs (CFCs, solvents, HCFCs, halons)

N2O

Kyoto Protocol synthetics (HFCs, PFCs, SF6)
ODSs and Other Gases of Interest

1.77

GtCO2-eq yr-1 in 2012 and has increased on average by 6.8 ± 0.9% yr-1 from 2008 to 2012. The HFC 

increase partially offsets the decrease by CFCs. Current emissions of HFCs are, however, less than 10% 

of peak CFC emissions in the early 1990s (>8 Gt CO2-eq yr-1).

Figure 1-6-4. Emissions of ODSs and 

ODS replacements weighted by 100-yr 

Global Warming Potential. The lower 

figure is an expanded version of the 

upper figure. In 2012, CO2-equivalent

emissions of CFCs, HCFCs, and HFCs 

were nearly equal. In this figure, “other” 

includes CCl4, CH3CCl3, and CH3Cl.

1.6.5 Ongoing Mismatch between Estimated Sources of CCl4 from Measurements and 

from Inventories

Carbon tetrachloride (CCl4) accounted for about 10% of total tropospheric Cl in 2012, and during 

2009–2012 declined largely as projected in the A1 scenario of the 2010 Assessment. However, estimated 

sources and sinks remain inconsistent with observations of CCl4, so the budget of this key gas remains 

unclear. When combined with the current estimate of the total atmospheric lifetime of CCl4 (26 years), the 

observed CCl4 trend in the atmosphere (−1.1 to −1.4 ppt yr-1 in 2012, right panel of Figure 1-6-5) implies 

sources of 57 (40–74) Gg yr-1 (red line in left panel of Figure 1-6-5), which cannot be reconciled by 

estimated emissions from feedstock and other uses (green lines). These industry-based estimates together 

with a global atmospheric CCl4 lifetime of 26 years result in calculated CCl4 mole fractions (dotted black 

line, right panel) much lower than measured abundances in the past decade, with an increasing 

divergence. The stable and significant interhemispheric CCl4 difference of 1.3 ppt in recent years could be 

an indicator for ongoing anthropogenic emissions in the Northern Hemisphere, although the distribution 

of CCl4 sources is not well understood.
Chapter 1

1.78

Figure 1-6-5. Left panel: Global top-down emissions of CCl4 and global potential emissions of CCl4, 

derived from raw production, feedstock, and destruction. For further explanation see caption of Figure 1-

6. Right panel: Global mole fractions from NOAA and AGAGE measurements along with the theoretical 

mole fraction (black dotted line) derived from potential emissions and a global lifetime of 26 years using a 

1-box model and observed concentrations in 1994, from 1994 through 2012.

1.6.6 Quarantine and Pre-Shipment (QPS) Consumption of CH3Br Has Exceeded NonQPS Consumption 

Quarantine and pre-shipment (QPS) consumption of methyl bromide (CH3Br) exceeded non-QPS 

consumption in 2009 (Figure 1-6-6). Article 5 and non-Article 5 countries consume similar amounts of 

CH3Br for QPS uses. There was a slight increase in QPS consumption by Article 5 countries in the mid2000s, with fairly steady consumption since then. QPS consumption by non-Article 5 countries was 34% 

of the total QPS consumption in 2012. With non-QPS emissions totaling just 30% of the 2012 total 

fumigation emissions, increases in QPS consumption/emissions will begin to reverse the reductions in 

tropospheric bromine gained from the reductions in non-QPS production, consumption, and emission.

Figure 1-6-6. Left panel: Trends in methyl bromide consumption (dashed lines) as reported in the UNEP 

database for non-QPS uses (- - -), QPS uses (- - -), and total (- - -); and trends in methyl bromide 

emission (solid lines) from non-QPS uses (▬), QPS uses (▬), and total (▬). Right panel: Quarantine 

and pre-shipment (QPS) consumption for Article 5 and non-Article 5 Parties to the Montreal Protocol

(UNEP, 2014).
ODSs and Other Gases of Interest

1.79

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CHAPTER 2

Update on Global Ozone: Past, Present, and Future

Lead Authors:

S. Pawson

W. Steinbrecht

Coauthors:

A.J. Charlton-Perez

M. Fujiwara

A.Yu. Karpechko

I. Petropavlovskikh

J. Urban

M. Weber

Contributors:

V. Aquila

W. Chehade

I. Cionni

M. Coldewey-Egbers

A. Delcloo

S.S. Dhomse

V. Eyring

E. Fleming

S.M. Frith

L. Froidevaux

N.P. Gillett

B. Hassler

M.I. Hegglin

D.E. Kinnison

D. Loyola

C.A. McLinden

L.D. Oman

D.A. Plummer

L.E. Revell

T. Sakazaki

W. Seviour

S. Tegtmeier

R.J. van der A

J. Wild

Chapter Editors:

V.E. Fioletov

U. Langematz
[Formatted for double-sided printing.]

From: 

WMO (World Meteorological Organization), Scientific Assessment of Ozone Depletion: 2014, Global 

Ozone Research and Monitoring Project – Report No. 55, 416 pp., Geneva, Switzerland, 2014.

This chapter should be cited as: 

Pawson, S., and W. Steinbrecht (Lead Authors), A.J. Charlton-Perez, M. Fujiwara, A.Yu. Karpechko, I. 

Petropavlovskikh, J. Urban, and M. Weber, Update on global ozone: Past, present, and future, Chapter 2 

in Scientific Assessment of Ozone Depletion: 2014, Global Ozone Research and Monitoring Project –

Report No. 55, World Meteorological Organization, Geneva, Switzerland, 2014.
CHAPTER 2

UPDATE ON GLOBAL OZONE: PAST, PRESENT, AND FUTURE

Contents

SCIENTIFIC SUMMARY ..........................................................................................................................1

2.1 INTRODUCTION ................................................................................................................................5

2.1.1 Main Findings of WMO-UNEP 2010 .........................................................................................5

2.1.2 Major New Developments Since 2010 .......................................................................................5

2.2 PAST OZONE IN OBSERVATIONS AND MODEL SIMULATIONS .............................................6

2.2.1 Data Sources ...............................................................................................................................6

2.2.2 Data Quality ...............................................................................................................................10

2.2.3 Changes in Total Column Ozone...............................................................................................11

2.2.3.1 Time Series ............................................................................................................................ 11

2.2.3.2 Interannual Variations ..................................................................................................14

2.2.3.3 Total Ozone Trends .....................................................................................................15

2.2.4 Trends in Ozone Profiles ..........................................................................................................18

2.2.4.1 Time Series ............................................................................................................................ 18

2.2.4.2 Ozone Trends up to 1997..............................................................................................22

2.2.4.3 Ozone Trends Since 2000 .............................................................................................24

2.2.4.4 Trend Profiles ..............................................................................................................25

2.2.4.5 Consistency Between Total Column Trends and Integrated Profile Trends ...............27

2.3 UPDATES ON NATURAL OZONE VARIATIONS ........................................................................28

2.3.1 Diurnal Ozone Variations and Their Impacts on Evaluating Long-Term Trends ....................29

2.3.2 Solar Variability.........................................................................................................................31

2.3.3 Variations Associated with El Niño-Southern Oscillation .......................................................33

2.3.4 Effects of Increased Stratospheric Aerosol Loading .................................................................34

2.3.5 Impacts of Ozone-Depleting Substances and Greenhouse Gas Changes 

on Ozone Trends........................................................................................................................36

2.3.5.1 Changes in Total and Lower Stratospheric Ozone and ODS and 

GHG Change.................................................................................................................36

2.3.5.2 Changes in Upper Stratospheric Ozone and ODS and GHG Changes.........................37

2.3.5.3 Tropical Ozone Changes...............................................................................................39

2.4 UPDATE ON FUTURE OZONE CHANGES....................................................................................39

2.4.1 Expected Return to 1960 or 1980 Levels and Ozone Recovery ...............................................39

2.4.2 Effects of Future Stratospheric Temperature and Circulation Changes ...................................42

2.4.3 Sensitivity to the Specification of Different Future Scenarios .................................................44

2.4.3.1 Effects of Different Representative Concentration Pathways (RCP) 

Scenarios.......................................................................................................................44

2.4.3.2 Influences of Nitrous Oxide and Methane ....................................................................46

2.5 HIGHLIGHTS FOR POLICYMAKERS ...........................................................................................49

REFERENCES...........................................................................................................................................51

APPENDIX 2A: OZONE DATA SETS ...................................................................................................64

Global Ozone

2.1

SCIENTIFIC SUMMARY

Past Changes in Total Column Ozone

This chapter deals with the evolution of global ozone outside of the polar regions. The increase of ozonedepleting substance (ODS) concentrations caused the large ozone decline observed from 1980 to the mid1990s. Since the late 1990s, concentrations of ODSs have been declining due to the successful 

implementation of the Montreal Protocol. As reported in the last Assessment, global ozone levels have 

remained stable since 2000. Ozone columns observed in the last four years have largely remained in the 

range observed since 2000.

Over the next decades we expect increasing global-mean stratospheric ozone columns, as ODSs decline 

further. Climate change and emissions of greenhouse gases, especially carbon dioxide (CO2), methane 

(CH4), and nitrous oxide (N2O), also affect the evolution of global stratospheric ozone, particularly in the 

second half of the 21st century, when ODS concentrations are expected to be low. 

• Compared to 1964–1980 total column ozone, ground-based and space-based observations show that 

present-day (circa 2008–2013) ozone columns are: 

• lower by about 2% for the near-global average (60°S–60°N), compared to 2.5% reported in 

the last Assessment; 

• lower by about 3.5% in the Northern Hemisphere (35°N–60°N), as reported in the last 

Assessment;

• lower by about 6% in the Southern Hemisphere (35°S–60°S), as reported in the last 

Assessment. The larger depletion in the Southern Hemisphere is linked to the Antarctic ozone 

hole; and 

• almost unchanged in the tropics (20°S–20°N), as in the last Assessment.

• Ground- and space-based observations indicate that near-global (60°S–60°N) column ozone has 

increased by around 1% ± 1.7% (2 sigma) between 2000 and 2013. However, there is substantial 

disagreement among the data sets about the magnitude and statistical significance of this increase. 

Two out of three independent data sets show increases at the upper end; one recently updated data set 

shows an increase at the lower end. The CCMVal-2 multi-model mean predicts a 1% increase 

between 2000 and 2013 for the near-global (60°S–60°N) column ozone.

• Total column ozone (dominated by lower stratospheric ozone) displays large, dynamically 

forced year-to-year variability in the middle and high latitudes, exemplified by unusually high 

ozone in 2010 and low ozone in 2011 in the Northern Hemisphere, and low ozone in 2006 in the 

Southern Hemisphere. The recent decline (15% since 1997) in concentrations of ODSs, as described 

by Equivalent Effective Stratospheric Chlorine (EESC), is expected to have had only a small impact 

on total ozone recovery (approximately 3 Dobson units (DU), or 1%, since 2000). Separation of the 

small recent ODS-related ozone increase from the large natural variability (up to 15 DU or 5% change 

from one year to the next) can currently not be made with a high level of confidence. 

Past Changes in Ozone Profiles

Additional and improved data sets have strengthened our ability to assess ozone profile changes over the 

last 10 to 15 years. Data from the upper stratosphere now confirm the significance of ozone increases that 

were already suggested in the last Assessment. Large ozone variability in the lower stratosphere 

complicates the identification of long-term ozone changes in this region. Chemistry-climate model (CCM) 

simulations that include realistic time variations of greenhouse gas (GHG) and ODS concentrations 
Chapter 2

2.2

capture changes in the ozone profile that agree quite well with those observed. These CCM simulations 

provide a means of attributing changes in ozone to different processes.

• Measurements show a statistically significant increase in upper stratospheric ozone (35–45 km 

altitude) in middle latitudes and the tropics since around 2000. Following a large observed decline 

of 5–8% per decade through the 1980s and middle 1990s, ozone has increased by 2.5–5% per decade 

over the 2000 to 2013 period.

• About half of the upper stratospheric ozone increase after 2000 can be attributed to the decline 

of ODS since the late 1990s. Increasing CO2 concentrations have led to a cooling of the upper 

stratosphere. CCM simulations reveal that, between the 1980s and the present this has contributed to 

an increase in ozone concentrations. Before the middle 1990s, this ozone increase was substantially 

smaller than the ozone decrease caused by ODS increases. From 2000 to 2013, the ozone increase 

arising from the decline in ODS concentrations is of comparable magnitude to that caused by upper 

stratospheric cooling.

• As reported in the last Assessment (WMO, 2011), CCMs consistently show a long-term decline 

of ozone in the lowermost tropical stratosphere by up to 20% between 1960 and 2060. This 

modeled ozone decline is caused by an increase in the strength of upwelling in the tropical lower 

stratosphere. This increased upwelling is associated with a strengthening Brewer-Dobson circulation 

caused by GHG-induced climate change. 

• In-situ and space-based observations reveal that ozone concentrations in the lowermost tropical 

stratosphere have declined by as much as 10% between 1984 and 2005. There are several 

additional data sets available since 2002. Continued ozone decreases are not detected in the presence 

of large natural variability during 2002–2013. This observed behavior is consistent with that 

computed in CCMs, which also show periods of strong interannual and decadal variability.

Future Ozone Changes

The chemistry-climate model simulations used in the last Assessment are still the main source for 

projection of future ozone levels and the dates of return of ozone to 1980 levels. Declining ODS 

concentrations, upper stratospheric cooling because of increased CO2, and the possible strengthening of 

the Brewer-Dobson circulation from climate change are all likely to affect recovery of global column 

ozone, with different relative contributions in various latitude regions. 

• Estimates of the likely return dates of total column ozone concentrations to their 1980 values have not 

changed since the last Assessment. The best estimates are:

• by midcentury for global mean annually averaged ozone;

• between 2015 and 2030 for annually averaged Northern Hemisphere midlatitude ozone;

• between 2030 and 2040 for annually averaged Southern Hemisphere midlatitude ozone; and

• for annual average tropical column ozone, slowly increasing until the middle of the 21st

century, before leveling off at values about 0–3% below 1980s columns.

• The updated lifetimes estimated for ODSs in the SPARC lifetimes report have no significant 

impact on model projections of future ozone evolution.

• Projections of future ozone levels depend substantially on the assumed scenario of greenhouse 

gas (GHG) emissions, especially in the later half of the 21st century. Six chemistry-climate model 

simulations show that projected total ozone columns in 2100 differ by up to 20 DU or 7% in the 

global average, by up to 40 DU or 12% in midlatitudes, and by up to 10 DU or 4% in the tropics 

between minimum and maximum radiative forcing Representative Concentration Pathway scenarios 

for future CO2, N2O, and CH4 emissions. These new estimates of scenario uncertainty are broadly 

consistent with previous estimates from different models and scenarios reported in the last 
Global Ozone

2.3

Assessment. Our confidence in the magnitude of this scenario uncertainty remains low because of the 

small number of models and scenarios assessed.

• Part of the scenario uncertainty in future column ozone is due to differences in emissions of N2O 

and CH4 between different scenarios. Increases of stratospheric N2O and CH4 impact the chemical 

cycles relevant for ozone. Higher N2O emissions tend to reduce column ozone, whereas higher CH4

tends to increase column ozone, each by a few percent from 2020 to 2100. The magnitude of these 

effects on ozone is comparable to what is expected from stratospheric cooling by CO2 increases. The 

influence of each individual trace gas on ozone also depends on emissions of the others, meaning that 

their impacts on ozone are strongly scenario dependent.

• Given that ODS levels remain high, a large enhancement of stratospheric sulfate aerosol in the 

next decade, e.g., due to a volcanic eruption of the same size as Mt. Pinatubo, could result in 

chemical losses of at least 2% in total ozone columns over much of the globe. Confidence in this 

conclusion is strengthened because the long-standing puzzle about the midlatitude hemispheric 

asymmetry in the midlatitude ozone response to Mt. Pinatubo aerosols is now much better 

understood. Studies have shown that enhanced ozone transport in the Brewer-Dobson circulation 

more than compensated the enhanced chemical loss in the Southern Hemisphere.
Chapter 2

2.4
Global Ozone

2.5

2.1 INTRODUCTION 

2.1.1 Main Findings of WMO-UNEP 2010

The 2010 Assessment (WMO, 2011) provided strong evidence that the limitations imposed by the 

Montreal Protocol on ozone-depleting substance (ODS) emissions were leading to a slowdown in 

chemical ozone destruction after 1997. Observations showed a leveling off of ozone values at almost all 

latitudes and altitudes, with a distinct change in the trend: A strong negative ozone trend between the 

1970s and the late 1990s was superseded by a period of almost no significant change in ozone until the 

end of the record in 2009. A broad range of numerical modeling studies, using chemical transport models 

(CTMs) and chemistry-climate models (CCMs), demonstrated that we have a robust scientific 

understanding of the mechanisms of ozone depletion. Further, the CCMs demonstrated at least three 

important connections between climate change and ozone depletion. First, observations and models 

demonstrated that the ozone hole impacts atmospheric heating rates, leading to a dynamical response of 

the springtime polar vortex that couples to the summertime dynamics of the Antarctic troposphere. 

Second, model simulations indicated that increasing greenhouse gases (GHGs) would further cool the 

stratosphere, thus slowing gas-phase reactions that destroy ozone in the upper stratosphere, and generally 

increase ozone and accelerate ozone increases. Third, the model simulations consistently predicted an 

increase in the strength of the Brewer-Dobson circulation (BDC), leading to lower ozone concentrations 

in the tropical lower stratosphere and higher values in the extratropics than might be otherwise expected. 

In WMO (2011) the observational evidence for this latter change was weak. 

These changes in stratospheric temperatures and tropical upwelling contribute substantially to 

projections of ozone change through the 21st century. CCM projections showed that, in the extratropics, 

ozone would recover to 1980 levels as ODSs were flushed from the atmosphere, with “return dates” 

occurring in the 2030s to 2060s. As GHG-induced climate change continued to increase the tropical 

upwelling, many CCMs indicated that ozone concentrations in the tropical lower stratosphere would 

continue to decrease through the 21st century. In the tropics, this dynamically induced decline in ozone 

would offset the impacts of chemical recovery. Likewise, CCMs predicted that, in the upper stratosphere, 

the lower temperature resulting from increasing GHGs and declining ODSs would lead to ozone increases 

through the 21st century. 

2.1.2 Major New Developments Since 2010

With the decline in emissions of ODSs and the consequent decrease in stratospheric chlorine- and 

bromine-containing compounds, a major component of the present Assessment concerns the detectability 

of any positive ozone trends over the past decade. The four additional years of observations available for 

analysis facilitate a new look at the potential recovery of ozone concentrations, with evidence that the 

positive trend associated with ODS reductions is becoming significant in some regions. Global ozone has 

been observed by spaceborne sensors for about 35 years. A continuous ozone profile data set based on one 

type of observations with global coverage is, however, not available. Since WMO (2011) the records of 

several instruments have been extended. These contribute substantially to the database of ozone profiles 

that supplements the sparse ground-based data sets. Long-term ozone profile data sets have been 

constructed by merging data from different instruments. New observations available since WMO (2011) 

have facilitated the investigation of the diurnal cycle of stratospheric ozone. This positions the research 

community to improve estimates of data set biases induced by diurnal effects (e.g., due to orbits that drift 

in local time), which can be particularly important in the upper stratosphere. The 2006 and 2010 Ozone 

Assessments drew heavily on model comparisons conducted by the SPARC (Stratosphere-troposphere 

Processes and their Role in Climate) Chemistry-Climate Model Validation (CCMVal) activity (Eyring et 
Chapter 2

2.6

al., 2010), with a consequent focus on differences among model predictions of ozone and some emphasis 

on the robustness of model simulations. Because the models used in CCMVal have not been substantially 

updated, no new multi-model comparison has been performed. New CCM simulations focus on different 

aspects of ozone change resulting from ODSs and GHGs, with a particular focus on the possible ozone 

distributions in the late 21st century, when chemical ozone destruction by halogens will have almost 

disappeared, and the main changes in ozone are driven by the assumed scenarios in greenhouse gas 

growth rates. 

A main focus of this Assessment thus relies on better detection of ozone change, its attribution, 

and the robustness of recent changes detected in observations. The second main focus is on how ozone is 

expected to evolve in the presence of ODS reductions and how assumptions about greenhouse gas 

pathways impact future ozone change. 

2.2 PAST OZONE IN OBSERVATIONS AND MODEL SIMULATIONS

2.2.1 Data Sources

As in the previous Assessments, carefully assessed, long-term ozone data sets have been used for 

trend analysis. Several new data sets have now become sufficiently long to examine ozone changes since 

2000, particularly from instruments on the Odin, Envisat, and Aura satellite platforms, available since 

2001, 2002, and 2004, respectively. Information about the ozone data sets used for this Assessment is 

summarized in Tables 2-1 (total ozone column) and 2-2 (ozone profiles). Detailed information about 

spatial and temporal coverage, vertical resolution, and systematic uncertainties is available from previous 

Assessments (WMO, 2007, 2011), and from recent SPARC initiatives on the evaluation of trace gas and 

aerosol climatologies (SPARC Data Initiative; Tegtmeier et al., 2013), and on past changes in the vertical 

distribution of ozone (SPARC/IO3C/IGACO-O3/NDACC = SI2N; Hassler et al., 2014). 

Because trend detection requires time series of observations that are longer than the lifetime of 

most satellite instruments, several new merged ozone time series are used in this Assessment. Challenges 

for such long-term records come from inter-instrument biases, drifts, differing local measurement times, 

different coordinate systems (e.g., ozone mixing ratio in a pressure-based coordinate system, or number 

density in an altitude-based system), different vertical and temporal resolution, and different sampling 

patterns. Box 2-1, for example, discusses differences in ozone profile trends that can arise from the 

coordinate system used. Section 2.3.1 discusses possible effects of diurnal variations, which are, however, 

presently not corrected for in any merged data set. This Assessment draws heavily on recent activities to 

combine and homogenize ozone data sets for trend studies. The following data sets are used here:

• The most recent update of the monthly-mean zonal mean data set combining Brewer spectrometer, 

Dobson spectrometer, filter, and SAOZ (Système d’Analyse par Observation Zénithale) total ozone 

data from the ground covering the period from 1964 to present (Fioletov et al., 2002; WMO, 2011).

• Merged total ozone data sets from the Global Ozone Monitoring Experiments (GOME, GOME-2) 

and the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography 

(SCIAMACHY): The Global Total Ozone data set (GTO: Chiou et al., 2014; Lerot et al., 2014) is 

based on the GODFIT (GOME Direct-FITting) retrieval (Loyola et al., 2009). An alternative data 

set is the weighting function differential optical absorption (WFDOAS) GOME/SCIAMACHY/

GOME-2 data set (GSG: Kiesewetter et al., 2010; Weber et al., 2011, 2013).

• The Multi Sensor Reanalysis (MSR), an assimilated total ozone data set using various satellite data 

(SBUVs, GOME, SCIAMACHY, GOME-2) and variants of retrieval algorithms as input (van der A 

et al., 2010). All satellite data sets have been bias corrected with respect to colocated ground 

Brewer and Dobson data.
Global Ozone

2.7

Table 2-1. Merged total ozone column data sets used in this report (zonal monthly-mean data).

Data Set Instruments Record Length Reference URL

Ground-Based Dobson, Brewer, SAOZ 01/1964 to 12/2013 Fioletov et al., 

2002, 2008; 

Hendrick et al., 

2011

http://www.woudc.org

ftp://ftp.tor.ec.gc.ca/pub/wou

dc/Projects-Campaigns/Zonal

Means

SBUV 

MOD V8

BUV Nimbus-4,

SBUV/TOMS Nimbus-7, 

SBUV/2 NOAA 9 to 19, OMI, 

TOMS EP

11/1978 to 12/2012 Stolarski and 

Frith, 2006

http://acd-ext.gsfc.nasa.gov/ 

Data_ services/merged/

SBUV V8.6 

NASA

(MOD V8.6)

BUV Nimbus-4, SBUV 

Nimbus-7, SBUV/2 NOAA 9 

to 19

BUV: 01/1970 to 

05/1976 SBUV: 

11/1978 to 12/2013

Chiou et al., 2014;

Labow et al., 

2013; McPeters et 

al., 2013

http://acd-ext.gsfc.nasa.gov/ 

Data_ services/merged/

SBUV V8.6 

NOAA

SBUV Nimbus-7, SBUV/2 

NOAA 9 to 19

11/1978 to 12/2013 ftp://ftp.cpc.ncep.noaa.gov/

SBUV_CDR/

GSG - Bremen GOME, SCIAMACHY, 

GOME2

07/1995 to 12/2013 Weber et al., 2013 http://www.iup.unibremen.de/gome/wfdoas/

GTO -

ESA/DLR

GOME, SCIAMACHY, 

GOME2

07/1995 to 12/2013 Chiou et al., 2014; 

Lerot et al., 2014

http://www.esa-ozone-cci.org

Multiple 

Satellite 

Reanalysis

assimilated TOMS, SBUV, 

GOME, SCIAMACHY, OMI

11/1978 to 12/2013 van der A et al., 

2010

http://www.temis.nl/protocols

/O3global.html

• Merged total ozone and ozone profile data sets from the V8.6 retrievals of the Solar Backscatter 

Ultraviolet (SBUV) instruments from NASA (MOD V8.6: DeLand et al., 2012; McPeters et al., 

2013; Chiou et al., 2014), which supersede the SBUV/Total Ozone Mapping Spectrometer 

(TOMS)/Ozone Monitoring Instrument (OMI) MOD V8 data set (Stolarski and Frith, 2006; WMO, 

2011). Another merged SBUV V8.6 data set from NOAA (MA-NOAA) uses inter-satellite 

adjustments similar to the previous SBUV/TOMS/OMI MOD V8 data set. It provides ozone time 

series very similar to MOD V8. Within the uncertainty margins discussed by Stolarski and Frith 

(2006), the new NASA and MA-NOAA SBUV V8.6 merged data sets agree over most of their 40-

year time series (i.e., total ozone columns are usually within 1% or better; profile ozone data are 

within 5% or better). Trend results from both data sets are similar. The NOAA SBUV V8.6 merged 

data set is not used in this Assessment, because currently no validation has been published for this 

recently merged data set.

• Stratospheric Aerosol and Gas Experiment II (SAGE II) data, updated from Version 6.2 to 7.0 

(Damadeo et al., 2013). For ozone, the new data version has not resulted in significant changes of 

SAGE II derived trends or long-term variability (Remsberg, 2014).

• The NASA “Making Earth System Data Records for Use in Research Environments” (MEaSUREs) 

Global OZone Chemistry And Related trace gas Data records for the Stratosphere (GOZCARDS) 

project (R. Wang et al., 2013), combining satellite ozone records primarily from Stratospheric 

Aerosol and Gas Experiments I and II (SAGE I, II, V6.20), Halogen Occultation Experiment 

(HALOE), Microwave Limb Sounders (Upper Atmosphere Research Satellite MLS, Aura MLS), and 

Atmospheric Chemistry Experiment (ACE-Fourier Transform Spectrometer). The quality of these 

data sets contributing to GOZCARDS was recently assessed in the SPARC Data Initiative 
Chapter 2

2.8

(Tegtmeier et al., 2013), which also considered results from the limb sounding instruments presented 

in the next bullet. 

• The HARMonized data set of OZone profiles (HARMOZ: Sofieva et al., 2013) produced by the 

European Space Agency Ozone Climate Change Initiative (ESA O3-CCI). HARMOZ consists of 

quality-screened European individual limb sounder data sets that are provided in common ozone 

units and altitude grid. HARMOZ consists of ozone data from the Optical Spectrograph and Infrared 

Imaging System (OSIRIS), the Sub-Millimetre Radiometer (SMR), both on the Odin satellite since 

2001, and from the Global Ozone Monitoring by Occultation of Stars (GOMOS), the Michelson 

Interferometer for Passive Atmospheric Sounding (MIPAS), and the Scanning Imaging Absorption 

Spectrometer for Atmospheric Chartography (SCIAMACHY), all on the Envisat platform from 2002 

to 2012. Tegtmeier et al. (2013) and Sofieva et al. (2013) discuss these individual data sets and their 

differences. In the Assessment, only ozone anomalies averaged over all available HARMOZ 

instruments are used. This removes the average bias of individual instruments, and reduces effects 

from spurious anomalies and drifts of individual instruments (see also Steinbrecht et al., 2006; Jones

et al., 2009; Nair et al., 2012). Results for individual instruments from the HARMOZ data set have 

been reported by Kyrölä et al. (2013), Eckert et al. (2014), and Gebhardt et al. (2014).

Table 2-2. Main ozone profile data sets used in this report.

Data Set Instruments Most 

Relevant for Trend

Record Length References URL

SBUV V8.6 

NASA

(MOD V8.6)

BUV Nimbus-4, SBUV 

Nimbus-7, SBUV/2 

NOAA 9 to 19

BUV: 01/1970 to 

05/1976 

SBUV: 11/1978 to 

07/2013

Kramarova et al., 

2013a; McPeters et al., 

2013

http://acd-ext.gsfc.nasa.gov/ 

Data_ services/merged/

SBUV V8.6 

NOAA

SBUV Nimbus-7, 

SBUV/2 NOAA 9 to 19

11/1978 to 12/2012 ftp://ftp.cpc.ncep.noaa.gov/

SBUV_CDR/

GOZCARDS SAGE I, SAGE II, 

HALOE, MLS-Aura

02/1979 to 12/2013 

Gap: 11/1981 to 

10/1984

R. Wang et al., 2013 https://gozcards.jpl.nasa.gov/

SAGE II, 

V7.0

SAGE II 10/1984 to 08/2005 Damadeo et al., 2013 https://eosweb.larc.nasa.gov/proje

ct/ sage2/sage2_table

HARMOZ ODIN: OSIRIS, SMR 

ACE-FTS; Envisat: 

GOMOS, MIPAS, 

SCIAMACHY

10/2001 to 12/2012 

08/2002 to 12/2011

Sofieva et al., 2013 http://www.esa-ozone-cci.org

NDACC 

ground-based

lidars, microwave 

radiometers, FTIRs 

about 5 stations

late 1980s/early 

1990s to 2012/2013, 

depending on station

Steinbrecht et al., 

2009; Vigoroux et al., 

2008

http://www.ndacc.org

see also Table 2-3

Umkehr about 5 stations 1956 (Arosa) 1984 

(Lauder) to 2012

Petropavlovskikh et 

al., 2005 ; Tourpali et 

al., 2007

http://www.esrl.noaa.gov/gmd/oz

wv/ umkehr/

Ozonesondes about 50 stations Late 1960s / mid1990s to 2012/2013 

depending on station

Smit et al., 2007; 

Deshler et al., 2008; 

Thompson et al., 2012

http://www.woudc.org 

http://www.ndacc.org

http://nadir.nilu.no

http://croc.gsfc.nasa.gov/shadoz/
Global Ozone

2.9

Box 2-1. Ozone Trends in Different Coordinates

Different instruments retrieve ozone in different fundamental units. SAGE and lidars, for 

example, provide ozone number density as a function of altitude. MLS provides ozone mixing ratio as a 

function of pressure. SBUV retrieves partial column ozone between two pressure levels, equivalent to 

mixing ratio versus pressure. All these quantities are linked through the background stratosphere (pressure 

and temperature), which is changing due to ozone and climate changes. Changing temperature and 

pressure profiles affect the different ozone coordinate systems. Since most ozone data sets come without 

corresponding temperature measurements, background atmospheres from operational meteorological 

analyses, or reanalyses (all with uncertainties; see Chapter 4), have to be used for unit conversion. This 

adds uncertainty to the comparison of ozone trends in different units.

McLinden and Fioletov (2011) assessed these differences using observed decadal temperature 

trends (see Chapter 4) to determine changes in the standard atmosphere. Stratospheric cooling leads to a 

contraction of the stratosphere, so pressure and ozone mixing ratio are shifted to lower geometric 

altitudes. As a result, above the mixing ratio peak (5 hPa, 35 km), lower ozone from higher altitudes 

replaces higher values at constant height surfaces. This makes ozone trends in mixing ratio versus altitude 

more negative than in mixing ratio versus pressure. The effect is enhanced for number density versus 

altitude trends by smaller pressures at the same altitude. Below the ozone maximum, atmospheric 

“shrinking” due to cooling is less pronounced and the contraction brings down higher ozone mixing ratios 

from above. Lower temperatures enhance number densities. As a consequence, below ~10 hPa or 30 km, 

number density versus altitude trends are slightly more positive than mixing ratio versus pressure trends.

The figure panel shows the result of McLinden and Fioletov (2011) applied to trends in mixing 

ratio versus pressure, VMR(p), and in number density vs. altitude, nd(z). Trends are shown for the two 

periods: 1979–1997, when both 

stratospheric ozone and temperature 

declined; and 2000–2013, when 

ozone increased and the temperature 

decreased. The biggest effects of 

cooling and the largest differences in 

ozone trends occur above 35 km. The 

clear 1–2% per decade effect near 2 

hPa before 1997 is consistent with 

differences between upper stratospheric trends from SAGE (nd(z)) 

and SBUV (VMR(p)). After 2000, the 

trend differences are smaller (1% per 

decade or less), because the 

temperature decline was 60% less 

than that before 1997 (see Chapter 4). 

The substantial uncertainty of ozone 

trends derived from any given 

instrument means that the smaller 

coordinate-related differences after 

2000 are hard to resolve.

100

10

1

pre

s

s

ure [h

P

a]

20

30

40

50

altitu

d

e [k

m]

-10 -5 0 5

ozone trend [%/dec]

trends up

to 1997

VMR(p)

nd(z)

trends

after 2000

VMR(p)

nd(z)
Chapter 2

2.10

2.2.2 Data Quality

Since the WMO (2011) Assessment there have been small improvements, but no major changes in 

data quality and uncertainty estimates for ground- and space-based ozone observing systems. Uncertainties 

for total ozone columns, monthly or annual means, are typically below 1%. Biases of individual systems 

are typically also 1% or less. Recent studies confirm this: UV total ozone data sets created from GOME, 

SCIAMACHY, and GOME-2 ozone records (Table 2-1), for example, show very good agreement with 

ground data and other satellites, within 1% in monthly zonal means, and with drifts generally well below 

1%/decade (Weber et al., 2005; Koukouli et al., 2012; Chiou et al., 2014; Lerot et al., 2014). Comparisons 

of column ozone from SBUV V8.6 with Dobson- and Brewer-spectrometer data also show agreement, 1% 

or better, over a thirty-year time span (Labow et al., 2013; McPeters et al., 2013). 

For ozone profiles, uncertainties are generally larger, of the order of 2 to 5% for the best 

instruments. Since the last Assessment (WMO, 2011), the SPARC Data Initiative (Tegtmeier et al., 2013), 

and the SI2N initiative on Past changes in the Vertical Distribution of Ozone (Hassler et al., 2014) have 

provided platforms to assess accuracy, precision, and stability of existing ozone profile records. Final 

results from SI2N are not yet available, but nearly all recent studies confirm the general picture that ozone 

profile uncertainties are smallest between 20 and 40 km altitude (pressures between 50 and 2 hPa), and 

are usually better than 10% for most instruments, and better than 2 to 5% for some instruments, including 

SAGE II, MLS, OSIRIS, and GOMOS (Tegtmeier et al., 2013; Adams et al., 2013, 2014; Eckert et al., 

2014; Damadeo et al., 2013; Kramarova et al., 2013a; Remsberg, 2014). Above this region, ozone 

decreases rapidly and uncertainties increase, for many instruments to 20% and more. Diurnal variations 

also play an increasing role above 30 to 40 km (10 to 2 hPa pressure), see Section 2.3.1. Below 20 km 

(pressure higher than 50 hPa), transport-driven ozone variability increases considerably. Sharp vertical 

ozone gradients occur and, especially near the tropopause, ozone concentrations are very low. In this 

region uncertainties increase substantially, to values larger than 20 to 30%, also due to limitations in 

sampling and altitude resolution. Limb sounding instruments, for example, have typical altitude 

resolutions of only 2–3 km in this region (Tegtmeier et al., 2013; Sofieva et al., 2013; Hassler et al., 

2014). SBUV ozone retrievals cannot separate contributions from lower stratospheric and tropospheric 

ozone (McPeters et al., 2013; Kramarova et al., 2013b). 

Time series of monthly-mean inter-instrument differences evaluated, e.g., in the SPARC Data 

Initiative (Tegtmeier et al., 2013; see Figure 2-1) confirm that monthly, zonal-mean ozone values from 

several limb-sounding satellites usually differ by less than 10–15% near 16 km (100 hPa), and less than 2 

–5% near 33 km (7 hPa). Some instruments, however, show substantial drifts and larger biases. A striking 

example is given in the left panel of Figure 2-1. At this particular pressure and latitude band, one data set

(GOMOS) exhibits a clear drift and should probably not be used. Near 7 hPa (see Figure 2-1) 

SCIAMACHY shows a large time-varying bias against the other instruments, about ±5% in phase with

the QBO. For SBUV, a QBO related bias is attributed to SBUV’s very coarse altitude resolution 

(Kramarova et al., 2013b). Good long-term stability and drifts of less than 2% per decade over the altitude 

range from 20 to 40 km are reported for SAGE, HALOE, UARS MLS, and Aura MLS ozone records 

against ground-based lidars (Nair et al., 2011, 2012; Kirgis et al., 2013). More details on the various 

systems can be found in Appendix 2A. Overall, drift uncertainties in the best individual ozone profile 

records are usually smaller than 2 to 5% per decade, but larger in the lowermost stratosphere. Only 

multiple independent records allow identification of bad records (like GOMOS in Figure 2-1). Averaging 

over several records removes noise and improves the precision. In this Assessment, averaging is done (on 

the basis of anomalies where the average annual cycle and bias of each instrument has been removed) for 

the HARMOZ record, which combines six European satellite limb sounders. The ozone profile time series 

in Section 2.2.4 indicate that for the best data sets drifts, and trend uncertainties, better than 1 to 2% can 

be achieved over the last 10 to 15 years, where many ozone profile records exist. Before 1990, however, 

only few records exist and profile trend uncertainties are larger. 
Global Ozone

2.11

Figure 2-1. Time series showing zonal-, monthly-mean ozone differences between different instruments 

for 2002–2010. Differences are expressed as a percentage from the reference. The left-hand panel shows 

differences at northern middle latitudes near 100 hPa, using OSIRIS V5.0 data as the reference data set. 

Differences are shown for SMR (green), MIPAS (blue), SCIAMACHY (cyan), and Aura-MLS (red). 

Differences for GOMOS (V5.0) data are also shown (black) but these are scaled by 0.33 as they are 

much larger than those for the other data sets. Similarly, the right-hand panel shows differences relative 

to SCIAMACHY (V2.5) near 7 hPa in the tropics. Colors are the same as in the previous panel and the 

OSIRIS curve is shown in pink. Adapted from Tegtmeier et al. (2013).

2.2.3 Changes in Total Column Ozone 

2.2.3.1 TIME SERIES

For the total ozone data sets in Table 2-1, Figure 2-2 shows time-series of annual-mean total 

ozone anomalies since 1964 for four regions: global (60°S–60°N), midlatitudes in both hemispheres (35°–

60°), and tropics (20°S–20°N). Anomalies were computed from monthly zonal mean total ozone data by 

subtracting the annual cycle over the period 1998–2008, individually for all data sets. This reference 

period was chosen because: (1) levels of ozone and ODSs were fairly constant from 1998 to 2008; (2) 

nearly all total column and profile ozone data sets provide data for a large part of this period; (3) it is long 

enough to cover one solar cycle and provide a stable baseline; and (4) it is not influenced by major 

volcanic eruptions.

In addition to the observations, the gray range in Figure 2-2 shows the range of simulated total 

ozone anomalies from the Chemistry-Climate Model Validation 2 activity (CCMVal-2, see Box 2-2: 

Eyring et al., 2010; SPARC, 2010). This ensemble of simulations from 17 CCMs was used in the WMO 

(2011) Assessment. Four of the same models have recently simulated ozone time series on the basis of 

recently updated ODS lifetimes, as described in Chapter 1 and SPARC (2013), but the long-term changes 

in ozone are virtually the same as those in CCMVal-2 (see Section 2.4.1). Thus the CCMVal-2 ozone 

results used in WMO (2011) remain viable for use in this Assessment. 

The gray range of CCMVal-2 simulations in Figure 2-2 gives the multi-model mean anomaly 

(from the 1998 to 2008 baseline) and 2 standard deviations of individual annual mean anomalies. The 

multi-model mean (and standard deviation) comes from 15 CCMs. Two models (MRI and CNRM-CMM) 

with known deficiencies were omitted (see Oman et al., 2010b; Michou, 2011). This approach to 

presenting the CCMVal-2 results differs from the last Assessment, where the complex Time Series 

Adaptive Method (Scinocca et al., 2010; WMO, 2011) was used to define the range of simulated ozone 

values. Because the TSAM method cannot readily be applied to observed time series, the simpler 

approach of computing means and standard deviation over sliding five-year windows and multiple models 

defines the range of simulated interannual, and, to a lesser degree, intermodel variability. The use of a

 Jan04 Jan06 Jan08 Jan10

−100

−50

0

50

[%]

O3 deviations with respect to OSIRIS, 35N−60N, 100 hPa

GOMOS deviations scaled by 1/3

SMR OSIRIS MIPAS(2) GOMOS SCIAMACHY Aura−MLS

 Jan04 Jan06 Jan08 Jan10

−10

−5

0

5

10

O3 deviations with respect to SCIAMACHY, 20S−20N, 7 hPa
Chapter 2

2.12

Figure 2-2. Total column ozone annual mean anomalies for different data sets. Anomalies are with 

respect to the 1998 to 2008 mean of each individual data set. Top left: 60°S–60°N (global), top right: 

35°N–60°N (Northern Hemisphere), bottom left: 20°S–20°N (tropics), bottom right: 35°S–60°S (Southern 

Hemisphere). Colored lines give observed results for the data sets from Table 2-1. Gray line and gray 

range give multi-model mean and ±2 standard deviation range of annual mean anomalies simulated by 

CCMVal-2 models (Eyring et al., 2010; WMO, 2011). The model simulations account for changing ODSs, 

GHGs, and a QBO. Up to about 2000, all simulations also account for the 11-year solar cycle, volcanic 

aerosol, observed sea surface temperatures, and sea ice coverage. After about 2000, sea surface 

temperature and sea ice are prescribed from other model simulations, and no solar cycle is included for 

most models. See text for details.

1998–2008 baseline spreads systematic differences to the beginning and end of the time series. The nearly 

identical treatment of simulations and observations in Figure 2-2 (and later Figures 2-5 to 2-8) allows 

direct comparison of observed ozone variations with the range of simulated interannual variations. Note 

that reducing the number of models used (e.g., from 15 to 9 or 7) barely changes the width of the gray

range in Figure 2-2 and later figures (see also Eyring et al., 2010; WMO, 2011). While recent studies 

discuss reducing the uncertainty range of multi-model simulations (Charlton-Perez et al., 2010; Strahan et 

al., 2011; Douglass et al., 2012; Karpechko et al., 2013), by selecting only a few (say, better-performing) 

models, this has not been done for the present Assessment. One motivation is that scenario uncertainty is 

not covered by the current CCMVal-2 simulations (all use the same scenario, see next paragraph), but will 

increase the range of simulated ozone, especially in the second half of the 21st century (Eyring et al., 

2013; see also Section 2.4.3).

1970 1980 1990 2000 2010

-5

0

5

10

total ozone deviations [%]

1998-2008

60°S-60°N

WOUDC (groundbased)

MSR

SBUV V8.6 NASA

GOME/SCIA GSG

GOME/SCIA GTO

MOD V8 (dotted)

CCMVal-2±2m

1970 1980 1990 2000 2010

-5

0

5

10

total ozone deviations [%]

1998-2008

35°N-60°N

WOUDC (groundbased)

MSR

SBUV V8.6 NASA

GOME/SCIA GSG

GOME/SCIA GTO

MOD V8 (dotted)

CCMVal-2±2m

1970 1980 1990 2000 2010

-5

0

5

10

total ozone deviations [%]

1998-2008

20°S-20°N

WOUDC (groundbased)

MSR

SBUV V8.6 NASA

GOME/SCIA GSG

GOME/SCIA GTO

MOD V8 (dotted)

CCMVal-2±2m

1970 1980 1990 2000 2010

-5

0

5

10

total ozone deviations [%]

1998-2008

35°S-60°S

WOUDC (groundbased)

MSR

SBUV V8.6 NASA

GOME/SCIA GSG

GOME/SCIA GTO

MOD V8 (dotted)

CCMVal-2±2m
Global Ozone

2.13

Box 2-2. Model Simulations

This Assessment uses simulations from a range of atmospheric models that have been used in previous Ozone 

Assessments and in recent international multi-model intercomparisons. These models can be divided into several general types:

• Chemical Transport Models (CTMs): CTMs are used for detailed calculations of chemical processes, using wind and 

temperature fields specified from meteorological analyses or from another model. There is no coupling between 

chemical species and radiation and transport in CTMs. They are often used for investigations of chemical processes. 

• Chemistry-Climate Models (CCMs): These models explicitly couple chemical processes to radiation and transport in 

the model, but generally do not couple to ocean models. The chemistry mechanism can be appropriate for the 

stratosphere only, the troposphere only, or coupled troposphere-stratosphere investigations.

• Atmosphere-ocean general circulation models (AOGCMs): These models include a dynamic ocean and coupled 

atmosphere-land-ocean-sea ice interactions and are primarily developed to understand surface and tropospheric climate 

variability and change. They generally do not include interactive chemistry processes, and rely on prescribed data sets 

for ozone and other radiatively important species. Until recently, these models typically had coarse resolution in the 

stratosphere and lower model upper boundaries than CCMs. 

While CCMs and AOGCMs have traditionally been used for different purposes, some AOGCMs now include some 

interactive chemistry and higher upper boundaries. Similarly, some CCMs now include a dynamical ocean and sea ice. 

CCMs and AOGCMs have been used in three recent multi-model intercomparisons that are drawn on in this Assessment:

• The second Chemistry-Climate Model Validation (CCMVal-2) activity (SPARC CCMVal, 2010) is a comparison of 

CCMs with stratospheric chemistry and a resolved stratosphere. This activity focused on understanding and projecting 

the evolution of stratospheric ozone and ozone-climate interactions. In these experiments, ozone-depleting substances 

(ODSs) followed the adjusted halogen scenario of WMO (2007). Greenhouse gases followed the Special Report on 

Emissions Scenarios (SRES) A1B scenario from the Intergovernmental Panel on Climate Change (IPCC) (2007). See 

Table 1 (below) for scenarios used. Many results from CCMVal-2 were discussed in the last Ozone Assessment 

(WMO, 2011).

• The Coupled Model Intercomparison Project, Phase 5 (CMIP5) (Taylor et al., 2012) is a comparison of AOGCMs that 

contributed significantly to the IPCC Assessment Report 5 (IPCC, 2013). Most (80%) of these models do not include 

interactive chemistry, and only one-third of them resolve the full stratosphere (model tops above 1 hPa). Both historical 

(1850–2005) and future scenario experiments (2006–2100) are included. See Table 1 for scenarios used. 

• The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) (Lamarque et al., 2013) is a 

comparison of CCMs with troposphere or troposphere-stratosphere chemistry. ACCMIP supplemented the CMIP5 

simulations, focusing on tropospheric chemistry-climate interactions.

Box 2-2, Table 1: Summary of chemistry-climate model experiments used for this report.

Activity Scenario Model 

Type

Years Stratospheric 

Ozone Forcing 

(ODS and precursor 

changes)

Other 

Forcings

Stratospheric 

Chemistry

Interactive 

Ocean

CCMVal-2 1 REF-B1 CCM 1960–

~2004

Observed Observed GHGs, solar variability, 

volcanic aerosols, SST x

Yes 1 of 17 

models

CCMVal-2 1 REF-B2 CCM 1960–

2100

A1 scenario 

WMO (2007)

SRES A1B GHGs (IPCC, 2007), 

model SST, fixed solar x, y

Yes 1 of 17 

models

CMIP5 2 Historical AOGCM 1850–

2005

Observed Observed GHGs, volcanic and 

anthropogenic aerosols, solar 

variability x

18 out of 

45 models

Yes

CMIP5 2 RCP 2.6, 

4.5, 6.0, 

8.5

AOGCM 2006–

2100

A1 scenario 

WMO (2003)

Four RCP scenarios, aerosols, 

land-use, tropospheric ozone, 

repeating solar cycle x

18 out of 

45 models

Yes

CMIP3 3 SRES 

A1B

AOGCM 2000–

2099

A1 scenario 

WMO (2003)

Mid-range GHG emissions, aerosols, 

tropospheric ozone, fixed solar 

No Yes

1 WMO (2011); Eyring et al. (2010). 2 Taylor et al. (2012); Eyring et al. (2013). 3 Meehl et al. (2007). x Most CCMVal-2 simulations include a nudged or model-generated quasi-biennial oscillation (QBO), whereas most CMIP5 model simulations 

do not include a QBO. y Several CCMVal-2 models include variable solar cycle forcing in their REF-B2 simulations.
Chapter 2

2.14

For Figure 2-2, (and Figures 2-5 to 2-8) up to 2004 (1999 for some models), the simulations 

account for changing ODSs (adjusted A1 scenario, WMO, 2007), changing GHGs (SRES A1B scenario, 

IPCC, 2007), solar cycle and volcanic forcings, observed sea surface temperatures and sea ice coverage, 

and the quasi-biennial oscillation (QBO) (REF-B1 scenario, see Table 1 in Box 2-2). After 2004 (or 1999 

for some models), the simulations include changing ODSs and GHGs (same scenarios as above), modeled 

sea surface temperatures and sea ice, and an internally generated QBO (for models that have one), but no 

volcanic forcing and usually no solar cycle forcing (REF-B2 scenario). Three of the CCMs apply solar 

cycle forcing. The common 1998 to 2008 baseline and the sliding five-year window allow these REF-B1 

and REF-B2 simulations to be combined, but the absence of volcanic and solar forcing substantially 

reduced the variability range after 2000 in Figure 2-2. 

Figure 2-2 extends results from previous Assessments. At midlatitudes, and in the 60°S to 60°N 

near-global mean, total ozone columns show a clear decline from the late 1970s to the mid-1990s. This 

decline has stopped. Since about 2000, observed ozone columns have been fluctuating around a more or 

less constant level (compare with the 1998 to 2008 baseline in Figure 2-2). This long-term behavior is in 

good agreement with previous Assessments. Agreement between different data sets is also good, typically 

better than 1% (see also Section 2.2.2).

CCMVal-2 model simulations attribute most of the long-term ozone decrease before the mid1990s to increasing ODSs and the subsequent leveling off to the small decline of ODSs, by about 15% 

since 2000 (WMO, 2003, 2007, 2011). The pronounced minimum in the Northern Hemispheric ozone in 

the 1990s arose from additional loss associated with the Mt. Pinatubo eruption in 1991 and several cold 

Arctic stratospheric winters (WMO, 2003, 2007, 2011). A clear minimum related to the Mt. Pinatubo 

eruption was not observed in the Southern Hemisphere (see also Section 2.3.4).

In the tropics, observed total ozone has remained nearly unchanged, with substantial interannual 

variability due to the QBO, tropical El Niño and La Niña events (El Niño-Southern Oscillation (ENSO)), 

and the 11-year solar cycle (see previous Assessments and Sections 2.3.2 and 2.3.3). Tropical ozone 

columns in recent years show a slight increase, as expected, at least in part, from the maximum of solar 

cycle 24 in 2012 to 2014. In contrast to the observations, which show little long-term column-ozone 

change from the 1960s/1970s to the 1990s, the CCMVal-2 simulations show a decline (Figure 2-2, lower 

left). However, this difference is less obvious in Figure 2-2 than reported in WMO (2011). Note that the 

difference relies on ground-based observations in the early years only, and is roughly twice the 1% 

systematic uncertainty of total ozone columns from Dobson spectrometers (Fioletov et al., 2008; Labow et 

al., 2013; Appendix 2A). 

Between 60°S and 60°N current ozone levels are on average 2% below the 1964–1980 mean. At 

northern midlatitudes, ozone levels are on average 3.5% below the pre-1980 values. In the Southern 

Hemisphere, current levels are on average 6% below pre-1980 values. These numbers are essentially the 

same as reported in WMO (2011). Figure 2-2 shows superimposed substantial year-to-year variations by 

several percent, also in the last decade, which clearly complicate the identification of small trends, like the 

small increase expected since about 2000 from the turnaround of ODS and from model simulations. 

2.2.3.2 INTERANNUAL VARIATIONS

Figure 2-3 focuses on ozone variations since the year 2000, a period with little overall change in 

total ozone levels (see Figure 2-2 and previous Assessments for variations before 2000). Most obvious are 

the QBO-related variations in the tropics and (usually of opposite sign) in the extratropics (Baldwin et al., 

2001). Sometimes the tropical anomalies seem to be exported to the extratropics, delayed by about a year 

(Tegtmeier et al., 2010). The largest interannual variations occur in winter and at high latitudes, for 

example the high total ozone at northern midlatitudes in 2002/2003, 2009/2010, and 2013, or in the 

Southern Hemisphere in late 2002 (polar vortex split) and 2012/2013. Examples for large ozone deficits in 

the Northern Hemisphere (NH) are 2008 and 2011 (large polar ozone loss: see Chapter 3; Manney et al., 

2011), or 2006 in the Southern Hemisphere (SH, largest ozone hole on record: see Chapter 3).
Global Ozone

2.15

Figure 2-3. Observed monthly 

zonal mean total ozone 

anomalies as a function of 

time and latitude. Results are 

from the GOME/SCIAMACHY/

GOME-2 (GSG) merged data 

set (see Table 2-1). 

Anomalies are with respect to 

the mean annual cycle 

obtained for the period 1998 

to 2008. For clarity, data are 

smoothed over three months 

and three 5° latitude bands. 

It is well known that these interannual variations are due to year-to-year variations in the strength 

of the polar winter vortices, (random) stratospheric warmings, and variation of the Brewer-Dobson 

circulation (BDC), which transports ozone from low latitudes to the winter pole (WMO, 1999, 2003, 

2007, 2011). Recent studies have confirmed this and have quantified some of the very large variations 

observed since the last Assessment. The unusually high total ozone columns in the NH in 2010, for 

example, are related to the negative phase of the AO (Arctic Oscillation) or NAO (North Atlantic 

Oscillation) (Rieder et al., 2010a, 2010b; Ossó et al., 2011; Steinbrecht et al., 2011; Weber et al., 2011).

Both oscillations are related to the BDC, and both describe nearly the same atmospheric anomalies. In the 

SH, the Antarctic Oscillation (AAO) plays a role for the high ozone columns in 2012 (Kramarova et al., 

2014). Progress has been made on influences from ENSO (Brönnimann et al., 2013; Oman et al., 2013; 

Rieder et al., 2013; see also Section 2.3.3). Long-term variations in these large meteorological influences, 

which easily exceed 5% or 15 DU (see Figure 2-3; or Frossard et al., 2013), and uncertainty on the 11-

year solar cycle variation (around 2% or 5 DU peak-to-peak, Brönniman et al., 2013; see also Section 

2.3.2), complicate detection of the expected small total ozone increase due to declining ODSs, which is 

only about 1% or 3 DU since 2000; see the CCMVal-2 mean in Figure 2-2. 

2.2.3.3 TOTAL OZONE TRENDS

As in previous Assessments (WMO, 1995, 2003, 2007, 2011), multiple linear regression (MLR) 

is used to estimate ozone trends and to account for the just-mentioned ozone variations due to natural 

factors (QBO, ENSO, volcanic aerosol, solar cycle). Here we use MLR on the basis of annual means for 

total ozone and monthly means for profile data (Section 2.2.4). ODS values reached their maximum 

around 1997 (Chapter 1) and there are different approaches to express ODS changes in the regression: 

(a) Two simple linear trends that are not necessarily joined at the ODS inflection time. 

(b) Piecewise linear trends (PWLT), with two linear trends connected at the ODS inflection time, or, 

alternatively, a continuous linear trend plus a trend-change term. Mathematically, both yield the 

same regressed time series (Newchurch et al., 2003; Reinsel et al., 2005; Jones et al., 2009; Nair et 

al., 2013; Chehade et al., 2014).

(c) Fitting Equivalent Effective Stratospheric Chlorine (EESC; Newman et al., 2007), as in Yang et al. 

(2006), Mäder et al. (2010), Steinbrecht et al. (2011), Nair et al. (2013), Frossard et al. (2013), and

Chehade et al. (2014).

A disadvantage of fitting EESC is that the ratio of ozone “trend before” to “trend after” (the ODS 

inflection time) is prescribed by the shape of the EESC curve. While the goodness of EESC fits does 

indicate overall agreement of ozone and ODS changes, the prescribed shape of the EESC curve precludes 

the independent estimation of an ozone increase after the ODS maximum. This is possible with PWLT, 

2000 2004 2006 2008 2010 2012 2014

-50

0

50

latitude

total ozone anomaly (reference period 1998-2008) 10

10

10

10

10

10

10

10

10

10

10

10

10

10

10

10

25

25

-25

25

-25

-10

-10

-10

-10

-10

-10

-10

-10

-10

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0 0

0

0

0

0

2004 2006 2008 2010 2012 2014

-50

0

50

-200-100 -50 -25 -15 -10 -5 5 10 15 25 50 100 200 DU
Chapter 2

2.16

and most studies use 1997 as the inflection time (Harris et al., 2008; WMO, 2011), although the exact 

year is not very critical (Mäder et al., 2010). Low ozone values around the inflection time (e.g., due to Mt. 

Pinatubo aerosol after 1991) can result in a larger decline before 1997, and a larger increase after 1997 

(see Figure 2-2). Therefore, in this Assessment a three-step process corresponding to regression approach 

(a) is used, similar to Newchurch et al. (2003). (1) A full MLR including PWLT (or EESC) contribution is 

applied to the time series, mainly to estimate QBO, ENSO, solar-cycle, and aerosol related ozone 

variations. (2) Ozone “residuals” are obtained by subtracting the QBO, ENSO, solar-cycle, and aerosol 

variations from step (1). These ozone “residuals” will then be rid of all contributions but still contain the 

long-term trends. (3) Two simple linear trends, from the beginning of each record up to 1997 and from 

2000 to the end of each record, are fitted separately to the ozone “residuals.” The year 2000 was selected 

as starting point for the second trend because: (1) it is after the peak of stratospheric chlorine loading; (2) 

the period between 2000 and the end of most data records (2011 to 2013) covers one full solar cycle, so 

this should minimize uncertainties in accounting for the solar cycle; and (3) 2000 is close to the beginning 

of the Odin- and Envisat-based HARMOZ ozone profile data sets starting in 2001/2002, allowing better 

comparison with results from this ozone profile data set. 

Uncertainties for the derived trends are estimated from the standard deviation of the fit residual, 

as in Newchurch et al. (2003), Kyrolä et al. (2013), or Gebhardt et al. (2014), and are corrected for firstorder autocorrelation in the fit residuals (Weatherhead et al., 2000). Note that this is not enough to 

account for longer-range correlations, so uncertainty bars may still be underestimated by a factor up to 1.5 

(Vyushin et al., 2007, 2010). For the CCMVal-2 simulations, trends are estimated by linear regression, 

similar to the trend estimation for the observations. Trends are estimated individually for each model from 

the REF-B2 runs, which do not include forcing by solar cycle and volcanic aerosol. Individual model 

trends are then averaged over all models. Mean and standard deviation are used as CCMVal-2 multimodel trend and uncertainty (see also Figure 2-25 of WMO, 2011). 

Figure 2-4 shows the resulting total ozone trends from 1979 to 1997, and from 2000 to 2013, as a 

function of latitude. Observed trends, derived by the three-step method, are given by the colored bars, 

which also give their uncertainty range. Dashed lines show the range of ozone trends obtained from fitting 

EESC to the observations (Approach c). The gray background gives the range of trends obtained from the 

CCMVal-2 simulations (see also Figure 2-2). Before 1997, the observed linear trends are negative 

everywhere, except for the inner tropics, and in good agreement with EESC trends, within uncertainty. 

Except for the tropics, observed trends before 1997 are also in good agreement with the simulations. 

These have a larger uncertainty range (Figure 2-2) due to differing sensitivity of models to ODS and other 

influences (Charlton-Perez et al., 2010; Strahan et al., 2011; Douglass et al., 2012). The negative ozone 

trends before 1997 are consistent with previous Assessments. Outside of the tropics they are largely due 

to increasing ODS (WMO, 1999, 2003, 2007, 2011).

After 2000, the computed linear trends are positive, around 1 to 2% per decade, at most latitudes. 

As expected due to the shorter period, uncertainty bars, ±1 to 2% per decade (2σ), are larger than for 1979 

to 1997. Poleward of 40°N, the post-2000 trends are not significant for most of the data sets. SBUV V8.6 

trends are not significantly different from zero in the entire NH. Poleward of 30° latitude in both 

hemispheres, the observed linear trends agree between data sets. There, they also agree with the range of 

trends obtained by fitting EESC (over the entire 40-year period) and with the range of CCMVal-2 

simulated trends. Especially in the NH, transport variations play a significant role (e.g., Kiesewetter et al., 

2010; Steinbrecht et al., 2011; Weber et al., 2011; Frossard et al., 2013; Rieder et al., 2013), but are not 

accounted for in the present regression (as in WMO, 2007, 2011). This contributes to the uncertainties. 

Between 30°S and 30°N, however, the large observed 2000 to 2013 trends from ground-based, 

GOME-SCIAMACHY-GOME-2, and Multi-Satellite-Reanalysis (MSR) data are often outside of the 

ranges expected from EESC (dashed lines) and simulations (gray range). Trends from SBUV V8.6 (and 

V8.0) are smaller, and are compatible with EESC and with simulations. The reason for the fairly large 

positive trends of some data sets in the tropics is currently not clear. Changing the initial year for the trend 

computation (e.g., from 2000 to 1997) does not change the trends significantly. Figure 2-2 (lower left
Global Ozone

2.17

total ozone trends (1979-1997)

-60 -40 -20 0 20 40 60

latitude [°]

-10

-8

-6

-4

-2

0

trends [%/decade]

WOUDC (groundbased)

MSR

SBUV V8.6 NASA

MOD V8.0

bars: linear trends ± 2m, black dash: min/max EESC± 2m

CCMVAL2 mean trend ± 2m

total ozone trends (2000-2013)

-60 -40 -20 0 20 40 60

latitude [°]

-2

0

2

4

6

8

trends [%/decade]

WOUDC (groundbased)

MSR

SBUV V8.6 NASA

GOME/SCIA GSG

GOME/SCIA GTO

MOD V8.0

CCMVAL2 mean trend ± 2m

bars: linear trends ± 2m, black dash: min/max EESC± 2m

Figure 2-4. Ozone trends for different merged total ozone data sets, as a function of latitude. Top: Trends 

from 1979 to 1997. Bottom: Trends from 2000 to 2013. Observed trends are derived using multiple linear 

regression (MLR) to account for solar cycle, QBO, volcanic aerosols, and ENSO. See text for details. The 

white dots give the linear trend in % per decade, the colored vertical bars indicate the ±2σ uncertainty 

range from the regression. Gray areas give average trend and ±2 standard deviation range of individual 

model trends from CCMVal-2 simulations (Eyring et al., 2010; WMO, 2011). Model trends were derived 

from REF-B2 simulations accounting for ODS and GHG changes, and including an internal QBO, but 

using only modeled sea surface temperatures and sea ice. Different from Figure 2-2, forcings from 

volcanic aerosol and 11-year solar cycle were not included in these simulations (except for three models 

that did include the solar cycle). The black dashed lines give the range of linear trends arising from MLR 

fits to the observations that include Equivalent Effective Stratospheric Chlorine (EESC) as a proxy for 

ODS changes. The fitted EESC coefficients usually give a negative ozone trend while EESC increases 

from 1979 to 1997, and a positive ozone trend while EESC declines from 2000 to 2013. For the EESC, a 

mean age-of-air of three years and width of 1.5 years were assumed (Newman et al., 2007).
Chapter 2

2.18

panel) indicates that instrumental uncertainties may play a role, since the different data sets diverge by about 

1% in the last years. Also, due to the different lengths of the data sets (50 years ground-based, >30 years 

SBUV, <20 years GSG), accounting for the solar cycle in the regression may make some difference (see also 

Section 2.3.2). Uncertainties may also be underestimated (Vyushin et al., 2007, 2010). Discrepancies 

between simulated and observed total ozone column trends in the tropics, therefore, remain. Before 1997, the 

decline detected from observations was smaller than in the CCMs (WMO, 1999, 2003, 2007, 2011). Since 

2000, the total-ozone increases in some data sets are larger than those simulated. 

Figure 2-4 shows that the total ozone column at most latitudes has a positive trend since 2000, but in 

many regions this trend is not statistically different from zero. This is consistent with WMO (2011) and with 

more recent studies using station data (e.g., Steinbrecht et al., 2011; Nair et al., 2013; Tully et al., 2013) and 

global data (e.g., Ziemke and Chandra, 2012; Krzyścin, 2012). As indicated by the black dashed lines for 

EESC trends in the lower panel of Figure 2-4, ODS-related total ozone increases since 1997 to 2000 should 

be small, <1% per decade at most latitudes, and not yet be detectable with the large current uncertainty 

margins of observed trends (mostly > ±1%/decade). Figure 2-4, thus, shows that total ozone has not been 

decreasing further after the mid-1990s, confirming the effectiveness of the Montreal Protocol. However, a 

clear attribution of total ozone increases to declining ODSs is not yet possible. This is essentially the same 

conclusion as reached in the last Assessment (WMO, 2011). 

2.2.4 Trends in Ozone Profiles

2.2.4.1 TIME SERIES

Like Figure 2-2 for total ozone, Figures 2-5 to 2-8 show time series of ozone profile annual mean 

anomalies at selected altitude or pressure levels. Section 2.2.1 and Table 2-2 summarize the profile data sets

that were used. Data sets using altitude coordinates are for the altitudes given in the figures; data sets using 

pressure coordinates are at the given pressures. Ground-based station data are also included, although the 

number of stations in the tropical and southern midlatitude bands is very limited (see Figure 2A-1 of 

Appendix 2A). All data sets are normalized to their 1998 to 2008 average annual cycles (same as for total 

ozone in Section 2.2.3).

These updates and additions give a comprehensive picture of ozone profile variations, but they have 

not resulted in major changes of our understanding from the last Assessment (WMO, 2011). For the upper 

stratosphere near 42 km/2 hPa, Figure 2-5 shows the well known ozone decline due to increasing ODS from 

the 1970s to the mid-1990s (WMO, 1999, 2003). Since 1995 to 2000, the decline is followed by a leveling 

off, as expected from the turnaround of ODSs after 1997 (WMO, 2007, 2011). In the last years, in most 

panels, the ozone values are usually above the zero line (=1998 to 2008 climatology), and indicate an ozone 

increase from around 2000 to 2012 or 2013. This increase is most visible in the 35°N to 60°N and 60°S to

35°S latitude bands. In the tropical band, data in recent years indicate little or no increase, only elevated 

ozone around the solar-cycle maxima, near 2001 and 2012. For the 60°S to 60°N mean, data points since 

2009 also lie above the zero line. 

Ozone time series at lower levels (Figures 2-6 to 2-8) also show the ODS-related long-term decline 

until the mid-1990s, and are generally leveling off since around 2000. However, long-term changes at these 

lower levels are less pronounced than at 2 hPa. Several aspects of Figures 2-6 to 2-8 are worth mentioning: 

• At 31 km/10 hPa and at 26 km/20 hPa (Figures 2-6 and 2-7), QBO-related variations are pronounced, 

especially in the tropics (Baldwin, 2001; Kirgis et al., 2013; Kramarova et al., 2013b; Gebhardt et al., 2014). 

• Near 31 km/10 hPa in the tropics (Figure 2-6), fairly high ozone values are recorded by several 

instruments between 2000 and 2003, whereas ozone has often been low after 2005. Thus, trend analyses 

over this period, e.g., of ozone records from instruments on the Odin and Envisat satellites, tend to 

indicate a decadal decline in the tropics around 31 to 35 km/10 to 5 hPa (Kyrölä et al., 2013; Eckert et al., 

2014; Gebhardt et al., 2014). 
Global Ozone

2.19

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

-5

0

5

10

15

20

-5

0

5

10

15

20

-5

0

5

10

15

20

ozone anomaly [%]

-5

0

5

10

15

20

ozone anomalies

42 km / 2 h3a

35°N to 60°N

20°S to 20°N

SBUV-NASA, SAGE V7.0, 

GOZCARDS, HARMOZ

Umkehr, Lidar, mWave

CCMVal-2 ±2V

60°S to 60°N

60°S to 35°S

Figure 2-5. Annual mean ozone anomaly time series for different latitude bands, at 42 km altitude (for 

data sets using altitude coordinates) or at 2 hPa pressure (for data sets using pressure coordinates). 

Satellite data (see Table 2-2) are based on zonal means. NASA SBUV V8.6 (MOD V8.6) is given in blue, 

SAGE II V7.0 in pink, GOZCARDS in green, HARMOZ in red. Ground-based station data (Umkehr, lidar, 

microwave; see Table 2-3, and also Figure 2A-1 of Appendix 2A) are averaged over the zonal bands. 

Umkehr data in purple, lidar in cyan, microwave data in orange. The gray background gives the CCMVal2 multi-model mean, and ±2 standard-deviation range of individual annual means, same as in Figure 2-2 

for total ozone. All anomalies are with respect to the average annual cycle during 1998 to 2008, 

determined individually for each data set/instrument/model.
Chapter 2

2.20

Table 2-3. Remote sensing stations used for ozone profile data sets in this report.

Station Latitude / 

Longitude

FTIR Lidar Microwave Umkehr

Lauder 45.0°S / 169.7°E 01/2001 to 12/2012 12/1994 to 06/2012 10/1992 to 10/2013 02/1987 to12/2011

Wollongong 34.4°S / 150.9°E 05/1996 to 12/2012

Mauna Loa 19.5°N / 155.6°W 07/1993 to 08/2013 07/1995 to 10/2013 01/1984 to 12/2011

Izana 28.3°N / 16.5°W 03/1999 to 10/2012

Table Mountain 34.4°N / 117.7°W 02/1988 to 08/2013

Tateno 

Rikubetsu

36.0°N / 140.1°W 

43.5°N / 143.8°E

 

05/1995 to 12/2009

08/1957 to 12/2011

Boulder 40.0°N / 105.3°W 05/1979 to 12/2011

Haute Provence 43.9°N / 5.7°E 07/1985 to 05/2013 01/1984 to 12/2011

Arosa 

Jungfraujoch

46.8°N / 9.7°E 

46.6°N / 8.0°E

 

03/1995 to 12/2012

01/1956 to 12/2011

Bern 

Payerne

47.0°N / 7.5°E 

46.8°N / 7.0°E

01/1994 to 12/2012 

01/2004 to 12/2013

Hohenpeissenberg 47.8°N / 11.0°E 09/1987 to 12/2013 

• Near 31 km/10 hPa and 26 km/20 hPa in the Southern Hemisphere (Figures 2-6 and 2-7), recent 

years indicate an ozone decrease from 2002 to 2005, and an increase from about 2005 to 2011, 

whereas in the Northern Hemisphere, ozone values were more or less constant over the last 

decade.

• Consistent with the high total column ozone observed in 2010 in the Northern Hemisphere (see 

Figures 2-2 and 2-3, and Section 2.2.3; Steinbrecht et al., 2011), the Northern Hemisphere profile 

data also report high ozone in 2010 from 19 to 31 km/70 to 10 hPa.

• In the tropical lower stratosphere (19 km/70 hPa, Figure 2-8), SAGE II data (V7.0), and the 

GOZCARDS record, which is based on SAGE II (V6.20), indicate a long-term decline from 1985 

to about 2005 (Randel and Thompson, 2011; Sioris et al., 2014). However, also from Figure 2-8 it 

appears that this decline has not continued over the last decade (Gebhardt et al., 2014). Note 

further the importance of El Niño in the tropical lower stratosphere, i.e., low ozone values 

associated with El Niño events (e.g., 1998, 2010), and high values associated with La Niña events 

(e.g., 1985, 1989, 1999/2000, 2011). See Section 2.3.3 for further discussion.

Unlike the largely ODS-related ozone changes at most altitudes and latitudes, the ozone decline in 

the tropical lowermost stratosphere (19 km/70 hPa, Figure 2-8) has been attributed to a long-term increase 

of the mean meridional upwelling of the Brewer-Dobson circulation (BDC) (Randel and Thompson, 

2011; Randel and Jensen, 2013), which enhances vertical transport of ozone-poor air in the tropics. CCMs 

predict such an increase and simulate a continuing ozone decline in the tropical lowermost stratosphere 

(Eyring et al., 2010; WMO, 2011). However, model simulations (black line and gray range in Figure 2-8) 

and observations also indicate substantial interannual and decadal variability, and no clear decline since 

1997. Observational evidence for the long-term decline before 1997 relies substantially on the high ozone 

values reported by SAGE II from 1985 to 1990. SAGE II has only sparse sampling in the tropics, but is
Global Ozone

2.21

Figure 2-6. Same as Figure 2-5, but for the 31.

km/10 hPa level. 

Figure 2-7. Same as Figures 2-5 and 2-6, but for 

the 26 km/20 hPa level. In addition, data from 

about 50 ozonesondes stations, averaged over the 

respective latitude bands are shown (see Figure 2-

25). Note that SBUV NASA has only very coarse 

altitude resolution (10 to 15 km), and reports only 

one layer from the ground to ≈20 hPa/26 km for the 

20°S to 20°N latitude belt.

the only credible observational data set for the tropical lowermost stratosphere before 1991. This, 

together with the leveling off of ozone in the tropical lowermost stratosphere since about 2000, suggested 

by multiple data sets in Figure 2-8, means that observational evidence for the modeled long-term ozone 

decline due to a strengthening BDC remains weak (see also Solomon et al., 2012). For further discussion 

see Section 2.4.2 and the more comprehensive discussion of the BDC in Chapter 4. 

Figures 2-5 to 2-8 also contain information about uncertainty of the available ozone records and 

about possible drifts. Nearly all data sets show very similar ozone evolution, especially over the last 10–

15 years (also due to normalization to the 1998 to 2008 period). The relative differences are larger in the 

early years (e.g., up to 15% between SBUV, Umkehr, and ozonesondes in the 1970s: Figures 2-6 and 2-

7). Before 1985, and before 2000 at 19 km/70 hPa, there are not enough observations to determine ozone 

levels with a high level of confidence in the tropics and the SH. After 2000, the availability of multiple 

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

-5

0

5

10

-5

0

5

10

-5

0

5

10

ozone anomaly [%]

-5

0

5

10

ozone anomalies

26 km / 20 h3a

35°N to 60°N

20°S to 20°N

SBUV-NASA, SAGE V7.0

GOZCARDS, HARMOZ

Umkehr, Lidar, mWave, Sondes

CCMVal-2 ±2V

60°S to 60°N

60°S to 35°S

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

-5

0

5

10

-5

0

5

10

-5

0

5

10

ozone anomaly [%]

-5

0

5

10

ozone anomalies

31 km / 10 h3a

35°N to 60°N

20°S to 20°N

SBUV-NASA, SAGE V7.0

GOZCARDS, HARMOZ

Umkehr, Lidar, mWave

CCMVal-2 ±2V

60°S to 60°N

60°S to 35°S
Chapter 2

2.22

and redundant data sets generally provides a higher level of confidence. Sampling issues also play a role, 

particularly when single station data are compared to zonal means (Gabriel et al., 2011a). This can be 

seen in the sometimes larger deviations of ground-based station data, such as lidars and microwave 

radiometers near 2 hPa in the 35°N to 60°N latitude band in 1986 and in 2010–2012 (Figure 2-5), or near 

20 hPa from 1994 to 1996 for Umkehr and lidar data at Mauna Loa, which is located at 20°N near the 

edge of the tropics (Figure 2-8). Generally, however, Figures 2-5 to 2-8 confirm statements about data 

quality and drifts from Section 2.2.2.

Figure 2-8. Same as Figure 2-7, but for 

the 19 km/70 hPa level. SBUV NASA data 

are not included because they have only 

very coarse altitude resolution, 10 to 15 

km, in the lowermost stratosphere. The 

dashed line for the sonde data in the 

tropical belt indicates that before 1998 

only data from the sonde station at Hilo, 

Hawaii (20°N), were used here. Umkehr, 

microwave and lidar data are also only 

from a few stations, e.g., Hawaii only in 

the tropical belt.

2.2.4.2 OZONE TRENDS UP TO 1997

Previous Assessments have established the latitude-altitude pattern of ozone decline due to 

increasing ODSs (WMO, 1999, 2003, 2007, 2011). The largest negative trends, −6 to −8% per decade,

were found around 42 km/2 hPa (e.g., Figure 2-4 of WMO, 2011). This section briefly revisits the 

latitude-pressure pattern of ozone trends before the turnaround of stratospheric chlorine loading, i.e.,

before 1997, based on the new data sets, and based on the regression described in Section 2.2.3.3. 

Figure 2-9 shows resulting linear ozone trends for the declining period up to 1997, for the 

GOZCARDS data set (in pressure coordinates), which is largely based on SAGE I and SAGE II (V6.20) 

over this trend period from 1978 to 1997, for the SBUV-NASA data set (trend period 1970 to 1997, in 

pressure coordinates), and for the SAGE II V7.0 data set (trend period 1984 to 1997, in altitude 

coordinates). The corresponding pattern from the CCMVal-2 model simulations (trend period 1970 to 

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

-10

0

10

20

-10

0

10

20

-10

0

10

20

ozone anomaly [%]

-10

0

10

20

ozone anomalies

19 km / 70 h3a

35°N to 60°N

20°S to 20°N

SAGE V7.0, GOZCARDS, HARMOZ

Umkehr, Lidar, mWave, Sonde

 CCMVal-2 ±2V

60°S to 60°N

60°S to 35°S
Global Ozone

2.23

1997) is shown as well. Note that small differences between trends can arise from the use of pressure or 

altitude in different observing systems (Box 2-1).

The observations all show the largest ozone decline near 42 km/2 hPa, between 30° and 70°, in 

both hemispheres. This highly significant (>3σ) decline is also simulated by the CCMVal-2 models, 

which show the largest loss near the poles, where SBUV and SAGE cannot observe during polar night. 

The trends from Figure 2-9 are consistent with previous Assessments (e.g., WMO, 2011), and with 

recent trend studies based on SAGE II V7.0 data (Remsberg, 2014), as well as the combined SAGE II –

GOMOS (Kyrolä et al., 2013) data set. Below 22 km/50 hPa, all observational data sets also report 

significant ozone decline in both hemispheres. This decline is also largely due to ozone depletion through 

ODSs, especially near the poles (WMO, 2003, 2007, 2011). 

In the tropical lowermost stratosphere below 22 km/50 hPa, the CCMVal-2 simulations indicate a 

long-term decline that is very pronounced in SAGE-II observations and captured in GOZCARDS, but is 

absent in the SBUV record. However, SBUV data have only very coarse altitude resolution below 25 km, 

where the retrieval mixes contributions from stratospheric and tropospheric ozone (Kramarova et al., 2013b). 

GOZCARDS 1979 to 1997

-90 -60 -30 0 30 60 90

latitude

1000

500

200

100

50

20

10

5

2

1

0.5

pressure [hPa]

0

0

0

2

2

2

2

2

2

2

2

3

3

3

3

3

3

3

-5

0

5

O3 trend

[%/dec]

 CCMVal-2 1970 to 1997

-90 -60 -30 0 30 60 90

latitude

0

10

20

30

40

50

altitude [km]

0

0

2

2

2

2

2

3 2

3

3

SAGE II V7.0 1984 to 1997

-90 -60 -30 0 30 60 90

latitude

1000

500

200

100

50

20

10

5

2

1

0.5

pressure [hPa]

0

0

0

2

2 2

2

2

3

3

3

3

3

3

3

-5

0

5

O3 trend

[%/dec]

 SBUV NASA V8.6 1970 to 1997

-90 -60 -30 0 30 60 90

latitude

0

10

20

30

40

50

altitude [km]

0

0

0

2

2

2

2 2

3

3

3

3

3

Figure 2-9. Ozone trends (in % per decade) before 1997 as a function of latitude and pressure. SAGE II altitude 

coordinates are converted to approximate pressure. Results are from multi-linear regression accounting for 

QBO, solar cycle, volcanic aerosol and ENSO related variations. See text for details. Top left: GOZCARDS 

record from 1979 to 1997. Top right: CCMVal-2 multi-model mean from 1970 to 1997 (REF-B1 runs, including 

volcanos and solar cycle, see text). Bottom left: SAGE II V7.0 from 1984 to 1997. Bottom right: BUV/SBUV/2 

V8.6 NASA MOD data set from 1970 to 1997. See Table 2-2 for data sources. Trend magnitude is given by the 

color scale. The black contour lines give the ratio of trend to uncertainty, i.e., the statistical significance of the 

trends. The line labeled 3 corresponds to 3σ, 2 corresponds to 2σ. Gray shading indicates regions where the 

trends are not significant at the 2σ level. See text for details on the uncertainties.
Chapter 2

2.24

2.2.4.3 OZONE TRENDS SINCE 2000

Upper stratospheric chlorine has been decreasing at a rate of 5–6%/decade since about 1997, 

following a strong increase in the early 1990s (Jones et al., 2011; see also Chapter 1). Despite the clear 

decline of upper stratospheric chlorine after 1997, a corresponding significant increase of upper 

stratospheric ozone had not been identified at the time of the last Assessment (WMO, 2011). There was, 

however, broad consensus that a significant change in the trend of midlatitude, upper stratospheric ozone 

had occurred in the second half of the 1990s (Reinsel et al., 2002; Newchurch et al., 2003; Miller et al., 

2006; Steinbrecht et al., 2009; Jones et al., 2009), and that the negative trend of ozone had slowed down 

and eventually ended (WMO, 2007, 2011). Ozone time series are now longer and more data sets are 

available. Several studies have reported statistically significant increases of ozone in the upper 

stratosphere since 2001 (Kyrölä et al., 2013; Gebhardt et al., 2014; Eckert et al., 2014).

Confirming these studies, Figure 2-10 gives ozone trends since 2000 for three independent 

observational data sets and for the CCMVal-2 simulations. In the upper stratosphere, between 36 and 48

GOZCARDS 2000 to 2013

-90 -60 -30 0 30 60 90

latitude

1000

500

200

100

50

20

10

5

2

1

0.5

pressure [hPa]

0

0

0

0

0

2

2

2

2

2

3

3

3

-5

0

5

O3 trend

[%/dec]

 CCMVal-2 2000 to 2013

-90 -60 -30 0 30 60 90

latitude

0

10

20

30

40

50

0

altitude [km]

2

2

2

2

3

3

3

HARMOZ 2000 to 2012

-90 -60 -30 0 30 60 90

latitude

1000

500

200

100

50

20

10

5

2

1

0.5

pressure [hPa]

0

0

0

0

0

0

0

2

2

2

2

2

2

2

2

2

3 3

3

3

3

-5

0

5

O3 trend

[%/dec]

 SBUV NASA V8.6 2000 to 2013

-90 -60 -30 0 30 60 90

latitude

0

10

20

30

40

50

altitude [km]

0

0

0

0

2

2

2

3

3

3

Figure 2-10. Same as Figure 2-9, but for ozone trends (in % per decade) since 2000. In the lower left 

panel, the trend derived from average ozone anomalies of the HARMOZ data set is given instead of 

SAGE II V7.0 trends. See Table 2-2 for details on the data sources. CCMVal-2 trend is for the REF-B2 

simulations (not including volcanos and solar cycle, see text).
Global Ozone

2.25

km/5 hPa and 1 hPa, all observations show significant ozone increases, up to 5% per decade, at most 

latitudes north of 60°S. Very similar increases are reported for individual instruments (Kyrölä et al., 

2013; Gebhardt et al., 2014; Eckert et al., 2014). Here, ozone anomalies from these instruments have 

been averaged to obtain the HARMOZ trend in Figure 2-10. Upper stratospheric ozone increases since 

2000, which have a peak near 2 hPa, are generally reproduced by the CCMVal-2 simulations (top right 

panel of Figure 2-10), although the simulated pattern is much smoother than the noisy observed pattern. 

Ozone increases in the upper stratosphere were mentioned in Figures 2-7 and 2-25 of WMO (2011). Four 

additional years of data, the new SBUV V8.6 data, and the additional GOZCARDS and HARMOZ data 

sets, now confirm these increases. In particular, the statistical significance of the increases is now higher 

(>2σ) than in WMO (2011).

In the mid- and lower stratosphere, ozone trends since 2000 are generally not significant. In the 

SH middle stratosphere (around 30 km/15 hPa), HARMOZ and SBUV show significant ozone increases, 

which are also evident, but not significant, in GOZCARDS. This increase was also reported for 

GOMOS, SCIAMACHY, and MIPAS by the studies mentioned above. In the NH, the observations show 

small ozone decreases between 30°N and 80°N at most levels below 32 km/10 hPa. These decreases are 

not statistically significant. At this point, the interhemispheric difference in Figure 2-10 is interesting, but 

not statistically significant. 

In the tropical stratosphere, 20°S to 20°N, observations agree on decreases between 32 and 36 

km/10 hPa and 5 hPa, largely due to high ozone values in the years 2000 to 2003 (see discussion of 

Figure 2-6; also Gebhardt et al., 2014; Eckert et al., 2014). In the lowermost tropical stratosphere, 

between 100 hPa and 50 hPa, 16 and 21 km, HARMOZ data indicate an increase, while GOZCARDS 

(and simulations) indicate a decrease: none of these are significant. There are substantial differences in 

trends since 2000 computed from individual instruments. Sioris et al. (2014) report a decline for OSIRIS 

data and Gebhardt et al. (2014) report an increase for SCIAMACHY and Aura MLS data. At this point, 

differences among trends computed from different data sets in the tropical lowermost stratosphere 

remain an open question.

2.2.4.4 TREND PROFILES

Trend profiles for the three latitude bands 60°S–35°S, 20°S–20°N, and 35°N–60°N are given in 

Figure 2-11. Results from the ground-based stations are averaged over available stations in each latitude 

belt, and are shown along with the satellite zonal mean data. CCMVal-2 model trends are given as gray

background. In all three zonal bands, and at most pressure/altitude levels, the observed trends computed 

for the different observational data sets agree to within uncertainty bars, and for both periods (before 

1997 and after 2000). The simulated trends also agree, within the uncertainty limits, with the observed 

trends. Some uncertainty bars are quite large, especially for the sparse ground-based data. There is only 

one station providing lidar, microwave, and Umkehr data in each of the tropical (Mauna Loa) and SH 

(Lauder) belts.

In addition to the individual trend estimates, the average trend of satellite and ground-based data 

sets is also plotted in Figure 2-11 (thick black line). This average trend is calculated as the weighted 

mean of the trends from all individual data sets, weighted by their inverse squared uncertainty. In order 

to account for possible instrumental drifts, a 2% per decade uncorrelated systematic uncertainty has been 

added to the individual trend uncertainties before building the weighted average. This results in more 

similar weights, and a larger and more conservative uncertainty estimate for the average trend. Table 2-4

summarizes these observed profile trends and compares them with the observed total column ozone 

trends from Figure 2-4.

Consistent with Figure 2-9 and previous Assessments (WMO, 1999, 2003, 2007, 2011), the left 

panel of Figure 2-11 shows significant ozone decline before 1997 at most levels. This decline peaks 

around 42 km/2 hPa at about −7% per decade in the Northern Hemisphere, at −4% per decade in the

tropics, and at −8% per decade in the Southern Hemisphere. Near 26 km/20 hPa, the ozone decline
Chapter 2

2.26

Figure 2-11. Ozone trends for the 

periods up to 1997 and after 2000 

from various observed data sets 

and CCMVal-2 model simulations 

and for selected latitude bands. 

Length of period depends on length 

of data record for each system. See 

Tables 2-1 and 2-2. For CCMVal-2 

simulations, the trend periods are 

1979 to 1997 and 2000 to 2013. 

Data sets using pressure coordinates are plotted on the 

pressure axis, data sets using 

altitude coordinates are plotted on 

the altitude axis. Observed trends 

are from multi-linear regression 

accounting for QBO, solar cycle, 

volcanic aerosol and ENSO, same 

as in Figures 2-4, 2-9, and 2-10. 

Gray areas give multi-model 

average trend and ±2 standard 

deviation range of individual model 

trends from CCMVal-2 REF-B2 

simulations (not including volcanos 

and solar cycle, see text).

before 1997 is small and barely 

significant. A second region with 

large declines before 1997, but also 

with large interannual variability 

and large uncertainty, occurs in the 

lower stratosphere, where trends 

peak around 100 hPa, and around 

−5% per decade. As in previous 

Assessments, trend uncertainties in 

the lowermost stratosphere are 

large, especially around the 

tropopause (10 km/200 hPa in the 

extratropics, 17 km/100 hPa in the 

tropics). This is due both to large natural variability and large gradients in this region (see also the large 

width of the gray range of model results), and due to less reliable observations at these altitudes.

The right-hand panels of Figure 2-11 indicate significant ozone increases since 2000 near 

42 km/2 hPa, by about +3% per decade in Southern and Northern midlatitudes, and by about +2% per 

decade in the tropics. The CCMVal-2 simulations reproduce these observed increases (gray range in 

Figure 2-11). Between 16 and 31 km (100 to 10 hPa), ozone trends since 2000 are not significantly 

different from zero in the Northern Hemisphere, and in the tropics. In the Southern Hemisphere, they are 

significantly positive above 27 km/20 hPa. This hemispheric asymmetry has already been mentioned (see 

previous section, and Figure 2-10).

-5 0 5 10 15

ozone trend after 2000 [%/dec]

0

10

20

30

40

50

altitude [km]

-15 -10 -5 0 5

ozone trend until 1997 [%/dec]

1000

100

10

1

pressure [hPa]

60°S to 35°S

-5 0 5 10 15

ozone trend after 2000 [%/dec]

1000

100

10

1

pressure [hPa]

0

10

20

30

40

50

altitude [km]

-15 -10 -5 0 5

ozone trend until 1997 [%/dec]

20°S to 20°N

-5 0 5 10 15

ozone trend after 2000 [%/dec]

1000

100

10

1

pressure [hPa]

0

10

20

30

40

50

altitude [km]

-15 -10 -5 0 5

ozone trend until 1997 [%/dec]

35°N to 60°N

2V error bars

SBUV-NASA, GOZCARDS, SAGE II V7.0, HARMOZ

NDACC lidar, mwave, FTIR, Umkehr, Sondes,

average, CCMVal-2

2V error bars

2V error bars
Global Ozone

2.27

Table 2-4. Summary of ozone trends. Given uncertainty margins are ±2σ. Statistically significant trends are 

printed in bold. Trends are derived for 1979 to 1997 and 2000 to 2013, as described in Section 2.2.3 for total 

column ozone and in Section 2.2.4 for ozone profile trends.

Ozone Trends

(% per decade)

60°S to 60°N 60°S to 35°S 20°S to 20°N 35°N to 60°N

up to 1997 since 2000 up to 1997 since 2000 up to 1997 since 2000 up to 1997 since 2000

Total column -2.0±0.7 +1.1±1.7 -3.8±1.2 +1.6±1.7 -0.6±0.7 +1.1±2.1 -3.3±1.4 +0.8±2.3

70 hPa / 20 km -3.8±2.0 -0.2±1.4 -1.5±2.9 -0.1±1.6 -0.8±4.0 -0.7±1.8 -4.6±2.2 +0.2±1.8

10 hPa / 30 km -2.9±1.4 +0.1±1.1 -2.6±1.9 +2.7±1.2 -1.7±1.9 -1.2±1.3 -3.0±1.5 +0.5±1.2

2 hPa / 40 km -6.1±1.7 +3.6±1.2 -7.8±2.0 +2.6±1.3 -4.0±1.8 +1.9±1.2 -6.8±1.8 +3.9±1.3

Positive ozone trends of about +3% per decade near 2 hPa since 1997 (or 2000) were already noted 

in Figures 2-7 and 2-25 of WMO (2011). Since then, these positive trends have now become clearer and 

statistically more significant. As discussed later (Section 2.4.2), the CCMVal-2 model simulations attribute 

this upper stratospheric ozone increase to declining ODSs and to stratospheric cooling by increasing GHGs.

2.2.4.5 CONSISTENCY BETWEEN TOTAL COLUMN TRENDS AND INTEGRATED PROFILE TRENDS

Although the long-term evolution of tropospheric ozone columns is only measured at a few 

sonde stations, and the vertical resolution and sampling of many instruments are limited in the lowermost 

stratosphere, it is useful and good practice from past Assessments to compare observed total ozone 

column trends with integrated profile trends. Generally, the profile ozone trends reported here (Figures 2-

9 to 2-11) are consistent within uncertainty bars with the total column ozone trends reported in Figure 2-

4. There are, however, two points worth noting:

Previous Assessments (WMO, 2003, 2007, 2011) have discussed that the large ozone decline 

reported in the tropical lowermost stratosphere from 1984 to 1997 by SAGE II (see Figure 2-8) is not 

consistent with the observed near constant total column ozone in the tropics. The observed, near-constant 

total ozone columns in the tropics were also not consistent with the long-term decline simulated by the 

CCMVal-2 models at these latitudes. New model results presented in Figure 2-12 now indicate that a 

long-term increase in tropospheric column ozone may resolve this long-standing discrepancy (Shepherd 

et al., 2014). The model simulation in Figure 2-12 shows good agreement between observed and 

simulated total ozone columns in the tropics, with little or no long-term decline (top panel). The middle 

panel shows good agreement also between observed stratospheric ozone columns from limb-sounding 

satellites and simulated stratospheric columns, both giving significant long-term decline. The new model 

simulations include a better simulation of tropospheric ozone changes. Figure 2-12 (bottom panel) 

indicates that a long-term increase of tropospheric ozone columns may have occurred. This could resolve 

the long-standing discrepancy mentioned above. Unfortunately, reliable long-term observations of 

tropospheric column ozone in the tropics are not available before 1998, precluding direct observational 

confirmation of this new model result. 

Total ozone column increases of 2% per decade reported from 2000 to 2013 by several data sets 

(Figure 2-4) are larger than the vertically integrated ozone profile changes between 20°S and 30°N (from 

Figures 2-10 and 2-11). There, the vertically integrated trends give only small and insignificant column 

increases of 0–1% per decade, with error bars of about 1% per decade. These vertically integrated 

changes are, however, consistent with the small total column changes reported by SBUV V8.6 (and 

TOMS/SBUV V8.0) between 30°S and 30°N (see Figure 2-4). Reasons for the larger total column trends
Chapter 2

2.28

Figure 2-12. Total ozone columns 

in the tropical belt (top panel), and 

partial ozone columns for the 

stratosphere (middle panel) and 

troposphere (bottom panel). For 

total column and stratospheric 

column ozone, results from 

observations (colored lines) are 

compared to simulations by one 

chemistry-climate model (CCM), 

driven by observed meteorology 

(gray lines). For the troposphere, a 

consistent long-term observational 

record is not available. CCM 

simulations are from the Canadian 

Middle Atmosphere Model (CMAM) 

and are driven by meteorological 

conditions from the ERA-40 and 

ERA-Interim reanalyses. Figure 

adapted from Shepherd et al. 

(2014).

from some data sets are currently not known. However, as mentioned in the discussion of Figure 2-4, 

systematic uncertainties in the total column data of the order of 1% have to be considered as well. 

2.3 UPDATES ON NATURAL OZONE VARIATIONS

This section discusses recent advances in understanding of ozone variability in the upper 

troposphere and stratosphere. An assessment of recent advances in diurnal ozone variations (Section 

2.3.1) is included to demonstrate the importance of time-of-day sampling in sun-synchronous (and other) 

satellite observations. This is followed by discussions of recent advances in understanding of lowfrequency ozone variability caused by the solar cycle and ENSO. It is well known that these two factors 

impact stratospheric composition, through their effects on chemistry and transport. As reported again by 

Kirgis et al. (2013) and Nair et al. (2013), the QBO is also an important contributor to interannual 

variability, both in the tropics and at higher latitudes (see also Figure 2-3). Dynamical feedbacks in the 

Earth System lead to effects of originally tropical phenomena, such as the QBO and ENSO, on 

midlatitude wave structures and wave propagation. This affects the Brewer-Dobson circulation and 

ozone transport in the stratosphere. Many variations thus impact detection and attribution of long-term 

changes. Finally, effects of volcanic and other aerosols are discussed in Section 2.3.4, since variations of 

such aerosols and their impacts on ozone chemistry must also be quantified.

1960 1970 1980 1990 2000 2010

I

II

Tropics 25°S - 25°N

Total column ozone

Stratospheric column ozone

Tropospheric column ozone

CMAM

CMAM

CMAM

Ground-based obs.
Global Ozone

2.29

2.3.1 Diurnal Ozone Variations and Their Impacts on Evaluating Long-Term Trends 

The diurnal variation of ozone is large and well established in the mesosphere and lower 

thermosphere, i.e., above 50 km (e.g., Huang et al., 1997; Schneider et al., 2005; Dikty et al., 2010a; 

Huang et al., 2008, 2010). Since WMO (2011), several studies have improved our understanding of 

diurnal ozone variations, demonstrating in particular that substantial diurnal variations occur also 

between 20 km and 50 km and even in the total column (e.g., Sakazaki et al., 2013; Studer et al., 2014).

Diurnal variations of ozone in the tropics and midlatitudes can be obtained from measurements 

by satellites with non-sun-synchronous orbit. Figure 2-13 shows tropical (10°S–10°N) diurnal ozone 

variations derived from data from the Superconducting Submillimeter-Wave Limb-Emission Sounder 

(SMILES) during Northern Hemisphere winter from October 2009 to April 2010 (Sakazaki et al., 2013). 

At 20–30 km, ozone levels have a maximum in the morning and a minimum in the late afternoon with 

typical variations of 1% above and below the daily mean. At 30–40 km, ozone levels are smallest after 

dawn and highest in the afternoon with variations of 2–3% above and below the daily mean. At 40–50 

km, ozone concentrations are minimum during daytime and maximum in the late afternoon with 

variations of 4% above and below the daily mean. UARS MLS and Sounding of the Atmosphere using 

Broadband Emission Radiometry (SABER) data show a similar altitude and local time dependence in the 

tropics (Huang et al., 1997, 2010) but there is disagreement about the size of the diurnal variation 

between the three instruments, particularly in the lower stratosphere.

Measurements of the diurnal cycle in ozone from ground-based microwave radiometers located 

in the extratropics are consistent with the results from satellites in the middle and upper stratosphere 

(Haefele et al., 2008; Studer et al., 2014). The vertical resolution of these radiometers is reported to be 6–

20 km. The diurnal cycle of ozone levels above two stations in Switzerland (Payerne (47°N, 7°E) and 

Bern (48°N, 7°E)) and a station at Mauna Loa (20°N, 116°E) shows an afternoon maximum at 30–40 km 

(approximately 2–4% larger than the nighttime value) and daytime depletion above 40 km. Haefele et al. 

(2008) and Studer et al. (2013) also noted a seasonal dependence of the diurnal cycle, with the largest 

amplitude in summer. Figure 2-14 shows their seasonal variations of the diurnal ozone cycle at 5.8 hPa 

(~35 km in altitude) at 48°N. The peak-to-peak difference is 6% in summer and 3% in winter. 

Generally, there is good agreement between the diurnal cycle of ozone in measurements and in 

CCMs and CTMs (Haefele et al., 2008; Sakazaki et al., 2013; Studer et al., 2014). Figure 2-13, for 

example, indicates good agreement between SMILES observations and model results for the whole 

tropical stratosphere. CTMs and CCMs show seasonal variations in the amplitude of the diurnal cycle 

that are, at least qualitatively, in agreement with space- and ground-based measurements.

The CTM simulations by Sakazaki et al. (2013) show that diurnal ozone variations in the 

stratosphere can be explained by a combination of photochemical processes (in the altitude region above 

30 km) and dynamical processes in association with vertical ozone transport by atmospheric tides. 

Figure 2-13. Diurnal ozone variations, 

relative to the daily mean, and averaged 

over 10°S–10°N, as a function of local time 

and altitude. Left panel: SMILES observations. Right panel: Specified DynamicsWhole-Atmosphere Community Climate 

Model (SD-WACCM) simulation. A lowpass filter (three-point running mean in both 

time and vertical domains) was applied to 

the SMILES observations. The WACCM 

simulation is given for the full grid, not 

subsampled to the SMILES observation 

points. Adapted from Sakazaki et al. (2013).
Chapter 2

2.30

Dynamical processes are important at 20–30 km and at 40–50 km where the vertical ozone gradient is 

large. Photochemical contributions are important at all latitudes, while the dynamical contributions are 

important only in the tropics. The latter means that the diurnal variations are enhanced in the tropics, at 

20–30 km and at 40–50 km. The combined effect of these dynamical/photochemical changes results in a 

peak-to-peak difference of up to 1% in the total ozone column in the tropics (Sakazaki et al., 2013). 

Semidiurnal variations are seen with maxima at 01:00 local time (LT) and 15:00 LT. The former 

maximum is caused by the variations at 20–30 km due to dynamics, while the latter is caused by the 

variations at 30–40 km due to photochemistry. In CTM simulations, the diurnal cycle in total ozone is 

large at high latitudes in the summer hemisphere (e.g., the peak-to-peak difference is up to 6 DU (1.5%) 

at 70°S and <1 DU (<0.2%) at 70°N in January). 

Diurnal variations are important for ozone trend analyses because data from satellite 

measurements have biases due to the difference in local time of measurements. It is well known that data 

from solar occultation satellite sensors show a sunset-sunrise bias. The SAGE II sunset profiles exhibit, 

for example, up to 10% more ozone than the sunrise profiles between 35 km and 55 km in the tropics

(McLinden et al., 2009; Kyrölä et al., 2013). The results presented here suggest that at least half of the 

sunset-sunrise bias in SAGE II can be attributed to diurnal variations. Second, the diurnal variation of 

ozone should be considered when creating merged ozone time series that combine data from different 

satellites measuring at different local solar times. Furthermore, the local solar time of satellite 

measurements may change as their orbits drift. For example, the local time of measurements by Solar 

Backscatter Ultraviolet (SBUV) instruments on several NOAA satellites changed from early afternoon to 

late afternoon over a few years (e.g., McPeters et al., 2013). None of the (merged) data sets at this time 

tries to correct for such diurnal effects. The results presented here indicate that, in severe cases, 

systematic differences due to changing local times could reach 5% even below 45 km altitude, and more 

at higher altitudes. Depending on the timescale of satellite changes or local time drifts, trend 

uncertainties of several percent per decade could result. For instruments with nearly fixed local time 

sampling, the effects should be substantially smaller, but the need to combine data from several 

instruments with different sampling complicates the issues.

Figure 2-14. (a) Seasonal variation of diurnal ozone cycle with respect to the mean nighttime value 

(22:30–01:30) at 5.76 hPa/35 km as derived from the Ground-Based Millimeter-Wave Ozone 

Spectrometer (GROMOS) radiometer measurements at Berne (48°N, 7°E) during 1994–2011. (b) As for 

(a) but from WACCM free-running simulation. Color bar is shown at the right. Contour interval is 1%. The 

thick lines near 4 to 8 local time and near 16 to 19 local time give the sunrise and sunset times for Berne, 

Switzerland. Adapted from Studer et al. (2014). 
Global Ozone

2.31

2.3.2 Solar Variability 

WMO (2011) reported a solar cycle effect on upper and lower stratospheric ozone of 2% to 4% 

between solar minimum and solar maximum. In the tropical middle stratosphere the observed solar cycle 

response is weaker and statistically insignificant (Soukharev and Hood, 2006; Randel and Wu, 2007). 

The solar cycle effect on upper stratospheric ozone is a direct radiative effect of heating and 

photochemistry. The lower stratospheric response in ozone (and also in total column ozone), however, 

occurs predominantly through a dynamical response to solar ultraviolet variations (e.g., Sitnov, 2009; 

Hood and Soukharev, 2012). The exact mechanism of the dynamical response to solar cycle variations is

not fully understood and cannot be reproduced fully by CCMs (Gray et al., 2010). Ozone changes in the 

middle and upper stratosphere are also in phase with 27-day sun-rotation UV variation (Fioletov, 2009; 

Gruzdev et al., 2009; Dikty et al., 2010b; Kubin et al., 2012). 

Remsberg and Lingenfelser (2010) and Remsberg (2014) found a stratospheric 11-year solar 

ozone response of around 2% for HALOE data and a response of up to 4% for SAGE II data. The 

differences between HALOE and SAGE II in the upper stratosphere solar response can be in part 

explained by the conversion between pressure and height coordinates that are used by the two data sets 

(see also Box 2-1). A minimum ozone response to the solar cycle in the middle stratosphere reported by 

Randel and Wu (2007) was not confirmed by Remsberg and Lingenfelser (2010). From a combined 

SAGE II/GOMOS data set, a solar cycle-induced stratospheric ozone response of 1–3% was derived 

(Kyrölä et al., 2013). These values are all in accord with WMO (2011).

Regarding total column ozone, in line with earlier studies (e.g., WMO, 2007, 2011), Hood and 

Soukharev (2012) confirmed a solar-induced 3% change in total column ozone from the SBUV/TOMS 

data set. This solar total ozone response is visible in the time-series of Figure 2-2, particularly in the 

tropics. The solar modulation of total ozone is likely driven by decadal variations of the Brewer-Dobson 

circulation (BDC) (Hood and Soukharev, 2012). Model simulations show that zonal asymmetries in the 

ozone, water vapor, and temperature fields are modulated by the 11-year solar cycle (Gabriel et al., 

2011b). This provides a direct link between the solar cycle, zonal asymmetries, planetary waves, and the 

BDC, all of which affect stratospheric ozone.

Based on a CTM driven by analyzed meteorological fields, a double-peak profile with a 

minimum in the middle stratosphere was found in the tropical solar cycle (Dhomse et al., 2011), in 

agreement with Randel and Wu (2007). This modeled solar response was in better agreement with 

HALOE than with SAGE-corrected SBUV (McLinden et al., 2009) or SAGE II. However, uncertainties 

in analyzed upper stratospheric temperatures and in the various ozone data sets still complicate the 

assessment of solar responses in models and observations (Dhomse et al., 2011). 

Since solar irradiance variations over the 11-year solar cycle are the main driver of the 

corresponding ozone variation, data from the Solar Radiation and Climate Experiment (SORCE)

satellite, suggesting a significantly stronger variability by a factor of 4–6 in the ultraviolet (UV) spectral 

range compared to other solar data (Harder et al., 2009; Haigh et al., 2010; Figure 2-15), have received a 

lot of attention. Most spectral solar irradiance (SSI) observations and solar models, with the exception of 

SORCE, had so far provided a qualitatively consistent picture of SSI variability over the 11-year solar 

cycle. 

In order to preserve total solar irradiance (TSI or solar constant), which is SSI integrated over the 

entire wavelength range, the large UV variability reported for SORCE data by Harder et al. (2009) 

requires that the visible SSI from SORCE has to decrease from solar minimum to solar maximum. Most 

solar models and other observations, however, indicate a positive (but weak) change in the visible 

(Ermolli et al., 2013; Figure 2-15). A careful analysis of the green spectral channel of VIRGO 

(Variability of solar IRradiance and Gravity Oscillations) confirmed a positive SSI change in the visible 

toward solar maximum (Wehrli et al., 2013). DeLand and Cebula (2012) and Lean and DeLand (2012) 

provide arguments that the SORCE data may be affected by optical degradation during the first years of 

the mission, near solar maximum. An additional investigation on the SORCE SSI variability closer to 
Chapter 2

2.32

solar minimum came to the conclusion that the SORCE UV SSI variability is about halved from the 

original studies but still higher than other observations and solar models (Ermolli et al., 2013; see Figure

2-15).

The large UV variation from SORCE has triggered several reinvestigations, comparing CCM 

runs using both the SORCE SSI and Naval Research Laboratory Solar Spectral Irradiance Model 

(NRLSSI) reconstructions. NRLSSI is representative for typical SSI variations assumed before SORCE 

data become available, and is commonly used in CCM simulations (e.g., Morgenstern et al., 2010). The 

CCMs generally showed a larger in-phase solar ozone response in the lower and middle stratosphere and 

out-of-phase (opposite) response above 37 to 45 km for simulations using SORCE SSI compared to 

simulations using NRLSSI (Haigh et al., 2010; Merkel et al., 2011; Swartz et al., 2012; Ermolli et al., 

2013; see Figure 2-16a). SABER (2002–2010) and Aura MLS (2004–2007) daytime ozone observations 

seem to confirm the anti-cyclic ozone behavior in the mesosphere (Haigh et al., 2010; Merkel et al., 

2011). Other results remain inconclusive as to which CCM simulations fit the observations better 

(Swartz et al., 2012; Shapiro et al., 2013; see Figure 2-15a). CTM simulations with different SSI 

implementations, including SORCE SSI, also provide very similar ozone responses in the middle 

atmosphere (Dhomse et al., 2013). 

In the upper stratosphere and mesosphere, ozone is influenced substantially by odd-hydrogen 

(HOx) chemistry. The observed decadal variability of hydroxyl (OH) total columns above 21 hPa, on the 

order of 7%, matches CCM results using SORCE SSI better than using NRLSSI (S. Wang et al., 2013). 

Many CCMs and general circulation models (GCMs) also show larger stratospheric temperature and 

shortwave heating rate responses for the SORCE SSI (Cahalan et al., 2010; Oberländer et al., 2012; 

Swartz et al., 2012; Ermolli et al., 2013). The modeled solar response of total ozone using SORCE SSI 

agrees better with SBUV/TOMS satellite data, but the run with NRLSSI agrees better with ground-based 

data (Swartz et al., 2012; Figure 2-16b). 

In summary, recent studies have confirmed a 2–4% variation of stratospheric ozone (3% in total 

ozone) in phase with the 11-year solar cycle. However, the exact shape of the solar response profile 

depends on the type of data and/or analysis, the length of data records, and the time periods under 

investigation. There is evidence that SORCE SSI strongly overestimates UV solar cycle variability. 

However, a clear conclusion on which SSI fits ozone observations best can currently not be drawn, 

because (1) available ozone records are too short (only a few solar cycles), and have limited accuracy, 

(2) spectral resolution of the radiation schemes in global models is not sufficient (Oberländer et al., 2012; 

Swartz et al., 2012), and (3) solar cycle induced changes in atmospheric transport compete with the 

direct radiative effects (Shapiro et al., 2013; Dhomse et al., 2013).

Figure 2-15. Spectral solar irradiance 

(SSI) changes over a solar cycle and 

in various spectral regions. SSI 

changes are normalized to total solar 

irradiance changes (TSI, solar 

constant), and are given for several 

data sets. WR-2002 (Woods and 

Rottman, 2002), SORCE, Solar 

Ultraviolet Spectral Irradiance Monitor 

(SUSIM), and SCIAMACHY are 

derived from observations. SATIRE, 

COSI, and OAR are solar models. 

NRLSSI is a solar reconstruction from 

Lean (2000). Except for SORCE 

(2004–2008) all values were derived from solar maximum to minimum conditions. As reported in Ermolli 

et al. (2013) a reanalysis of SORCE data close to solar minimum in 2009 revealed a weaker sensitivity in 

the UV, shown as SORCE reanalysis here. Adapted from Ermolli et al. (2013).
Global Ozone

2.33

Figure 2-16. Solar cycle response of ozone from Goddard Earth Observing System Chemistry-Climate 

Model (GEOSCCM) simulations using SORCE SSI (red line) and NRLSSI (black, Lean and DeLand,

2012). a.) Comparison to profile response in SAGE II data from Randel and Wu (2007). b.) Comparison 

to response in zonal mean total ozone from SBUV/TOMS data and from ground-based Dobson and 

Brewer data. Both panels from Swartz et al. (2012).

2.3.3 Variations Associated with El Niño-Southern Oscillation 

The El Niño-Southern Oscillation (ENSO) is an important mode of interannual variability in the 

tropical ocean and atmosphere. ENSO-forced variations in tropical upwelling lead to temperature and 

water vapor variations in the tropical lower stratosphere and have impacts on the chemistry and transport 

of ozone (e.g., Randel et al., 2009). Atmospheric teleconnections lead to ENSO-related impacts on the 

strength of planetary waves and the Brewer-Dobson circulation. Both affect stratospheric ozone 

distributions in middle and high latitudes. 

Since WMO (2011), several studies have refined our understanding of ozone variations 

associated with ENSO. Randel and Thompson (2011) describe ENSO-related variations of tropical ozone 

found in the SAGE II and Southern Hemisphere Additional Ozonesondes (SHADOZ) data sets. In the 

tropical lower stratosphere (17–21 km), ENSO warm events lead to enhanced tropical upwelling that 

results in a reduction of zonal-mean ozone concentrations. A similar analysis using combined SAGE II 

and OSIRIS ozone data (Sioris et al., 2014) demonstrates that ENSO cold events (La Niña) in 1988–1989 

and 1999–2000 led to positive anomalies in lower stratospheric ozone, see also Figure 2-8. Oman et al. 

(2013) used the spatially dense MLS and Tropospheric Emission Spectrometer (TES) observations to 

demonstrate the zonal symmetry of the ENSO signal in stratospheric ozone. ENSO-related signals 

(Figure 2-17) are strongest just above the tropical tropopause; at higher levels they appear with a one- to

two-month delay and are weaker than QBO-related signals in ozone. 

In contrast to the zonal-mean response in the lower stratosphere, these studies (Randel and 

Thompson, 2011; Oman et al., 2013) isolate a strong longitudinal dependence of the ENSO influence on 

tropical tropospheric ozone, which peaks in the upper troposphere (11–16km). It is also detected in total 

column ozone (Ziemke et al., 2010). This spatial structure is defined by an out-of-phase relationship 

between the Indonesian/western Pacific (high upper tropospheric ozone during ENSO warm events) and 

eastern Pacific regions (low ozone during ENSO warm events). Simulations using GEOSCCM (Oman 

et al., 2011, 2013), which include no year-to-year variations in biomass-burning emissions of ozone

a.) b.) 
Chapter 2

2.34

Figure 2-17. Sensitivity coefficient 

of ozone over the eastern Pacific 

(longitudinal average from 180°W 

to 110°W) to sea surface

temperature anomalies in the Niño 

3.4 region of the tropical Pacific 

(parts per billion by volume (ppbv)

per Kelvin). Results of multiple 

linear regression analysis by Oman 

et al. (2013). Top panel: 

Observation results from 

Microwave Limb Sounder (MLS) 

and Tropospheric Emission Spectrometer (TES). The thick black line 

at 260 hPa separates MLS data 

used above from TES data used 

below. Bottom panel: Same for 

model simulations by the GEOSCCM 

model. Only regions that are 

significant at the 2σ level are colored. 

The dashed black line gives the 

mean model tropopause. From 

Oman et al. (2013).

precursors, demonstrate that the ENSO-related longitudinal structure is mainly caused by changes in 

atmospheric circulation that impact transport and photochemistry. Impacts of ENSO-related variations of 

biomass-burning emissions might have additional effects (e.g., Ott et al., 2010). 

Several studies have examined the sensitivity of midlatitude ozone columns to the occurrence of 

ENSO through changes in planetary waves and their propagation and damping in the middle atmosphere 

(e.g., Hood et al., 2010; Gabriel et al., 2011b). Extratropical ozone variations due to ENSO are opposite 

to the tropical effects (Figure 2-17). There is also some evidence for hemispheric asymmetry, especially 

in the West Pacific (70°E–140°E). Smaller or negative sensitivity of ozone to ENSO is found in the SH 

midlatitude lower stratosphere, at least in these short records since 2004. Rieder et al. (2013) show a 

spatially complex relationship between midlatitude ozone column and ENSO index in both hemispheres 

during December-January-February and March-April-May between 30° and 50°N. Brönnimann et al. 

(2013) showed a similar zonal mean response to ENSO using an assimilated ozone data set covering 

much of the 20th century.

2.3.4 Effects of Increased Stratospheric Aerosol Loading 

Previous Assessments have described how stratospheric sulfate aerosols impact ozone 

concentrations through both direct impacts on heterogeneous chemical processes and indirect impacts on 

temperature and transport. Figure 2-18 (Trickl et al., 2013) shows the well-documented, rapid increases 

in sulfate aerosol loading associated with the El Chichón (1982) and Mt. Pinatubo (1991) volcanic eruptions
Global Ozone

2.35

Figure 2-18. Aerosol backscatter coefficient measured since 1976 by lidar at Garmisch-Partenkirchen 

(47.5°N, 11.0°E) as a measure of stratospheric aerosol loading. Backscatter coefficient is integrated over 

the stratospheric aerosol layer, from 1 km above the tropopause to above 30 km altitude. Arrows mark 

the eruption of volcanoes that have, most likely, resulted in the observed aerosol enhancements. Note 

the recent aerosol enhancement after 2008. From Trickl et al. (2013).

followed by several years of gradual reductions. The figure also reveals an increase in the stratospheric 

aerosol burden after 2006 to 2008. 

The recent aerosol increases are likely to impact stratospheric ozone. The 4–10% increase in the 

stratospheric aerosol burden is about twice as large in the tropics as in the middle latitudes (Vernier et al., 

2011; Trickl et al., 2013). While Hofmann et al. (2009) hypothesized that this aerosol increase could 

come from increasing Asian fossil-fuel emissions, other studies (Nagai et al., 2010; Vernier et al., 2011; 

Neely et al., 2013; Trickl et al., 2013) show that volcanic sulfate aerosols are the likely cause. Most 

volcanic sulfates are injected directly into the lowermost stratosphere, but some may also be transported 

there via monsoonal circulations from the upper troposphere (Bourassa et al., 2012; 2013). The exact 

path of aerosols and precursors is not always clear (Vernier et al., 2013; Fromm et al., 2013; Bourassa et 

al., 2013). Quantitative assessments of the impact on ozone of this observed stratospheric aerosol 

increase are needed, especially in the context of other changes in the tropical lower stratosphere. Most 

likely, given the current (high) stratospheric chlorine and bromine burden, heterogeneous reactions on 

the increased aerosol surface area will result in some lower-stratospheric ozone destruction. Using a total 

column depletion of typically 2%, maximum 5%, after Mt. Pinatubo as a reference (Telford et al., 2009; 

see also Figure 2-2, WMO, 1999), the current effect on the total column should be below 0.2 to 0.5%, 

since aerosol loading is about a factor of 10 smaller, and chlorine levels are comparable. Major 

stratospheric aerosol perturbations, however, are likely to lead to substantial ozone loss until 

stratospheric halogen loading falls to values expected in about 2030–2050 (Pitari et al., 2014). Note that 

bromine released from very short-lived halocarbons that are transported into the lowermost stratosphere 

contributes substantially, up to 50%, to the aerosol-related ozone destruction (Salawitch et al., 2005; 

Sinnhuber et al., 2009). These very short-lived halocarbon sources are not expected to decrease in the 

future, providing potential for ozone loss due to enhanced stratospheric aerosol even when controlled 

ODSs have largely disappeared from the stratosphere. 

Mt. Pinatubo was the most recent major volcanic eruption to increase global stratospheric 

aerosol levels by an order of magnitude or more, injecting about 17 teragrams (Tg) of sulfur dioxide into 

the stratosphere, which oxidized into about 30 Tg of sulfate aerosol (WMO, 1995, 1999). This aerosol 
Chapter 2

2.36

remained in the stratosphere for several years (see Figure 2-18) and was transported in approximately 

equal amounts to both hemispheres. The observed sudden depletion of stratospheric nitrogen dioxide 

(NO2) in both hemispheres (WMO, 1995, 1999) provided evidence that the volcanic aerosol had 

enhanced heterogeneous chemistry at all latitudes. However, while observations showed enhanced ozone 

depletion in the NH, a small increase of the ozone column was detected, surprisingly, in the SH during 

the year following the eruption (see Figure 2-2). This remained unexplained in WMO (2011). Recent 

studies have now provided explanations. Poberaj et al. (2011) suggested that in the SH, enhanced ozone 

transport in late 1991 and early 1992 more than compensated the aerosol-induced chemical ozone loss. 

The enhanced transport was related to enhanced wave forcing of the SH stratosphere. A set of CCM 

simulations by Aquila et al. (2013) demonstrated that aerosol-induced longwave heating in the lower 

stratosphere would increase tropical upwelling, leading in turn to an enhanced BDC. This also increases 

ozone in the southern midlatitudes. Both mechanisms have likely acted together, and can explain the lack 

of a clear ozone decline in the SH after the Mt. Pinatubo eruption. 

2.3.5 Impacts of Ozone-Depleting Substances and Greenhouse Gas Changes on Ozone 

Trends

Although the concentrations of ozone-depleting substances (ODSs) in the stratosphere continue 

to decrease, the detection of ozone recovery from ODSs remains a challenging scientific task. Essentially 

it is a statistical problem, complicated by the fact that influences other than ODSs, such as greenhouse 

gas (GHG) concentration increases, atmospheric dynamical variability, solar irradiance variations, and 

volcanic aerosol all affect stratospheric ozone (see previous sections). In the lower stratosphere and for 

total ozone, dynamical variability influences ozone directly, via changes in transport. Ozone is also 

affected indirectly by dynamical temperature changes, which affect rates of chemical production and 

destruction of ozone. 

In the following we report how our capability to connect observed changes in total column 

ozone, and ozone in the upper stratosphere, to changes in ODSs and GHGs has improved. We also report 

on recent studies that examine observational evidence, from ozone in the lowermost tropical 

stratosphere, for an acceleration of the mean meridional Brewer-Dobson circulation (BDC). This 

acceleration has been simulated by most chemistry-climate model (CCM) simulations. These remain the 

major tool for estimating contributions from different processes, which usually cannot be separated on 

the basis of observations alone. 

2.3.5.1 CHANGES IN TOTAL AND LOWER STRATOSPHERIC OZONE AND ODS AND GHG CHANGES

To detect the influence of ODSs on ozone changes, WMO (2011) relied on multiple-linear 

regression analysis. Equivalent Effective Stratospheric Chlorine (EESC) or piecewise linear trends 

(PWLT), both closely resembling the increase and the beginning of the decline of ODSs, were used as 

proxies describing the effect of ODSs (see also Section 2.2.3.3). In addition chemical transport models 

(CTMs) forced with winds and temperatures from meteorological analyses have been used to separate 

the influences of ODSs and dynamical variability. WMO (2007) attributed about 30% of the observed

negative total ozone column trend from 1979 to the mid-1990s to changes in the lower stratospheric 

circulation. WMO (2011) also found that total ozone column increases observed since mid-1990 were 

significantly larger than expected from ODS decreases, and that dynamical variability contributed to 

these increases. Several new studies, reviewed below, follow the same approach.

Kiesewetter et al. (2010), for example, used a CTM and attributed at least 50% of the linear 

negative trend in total ozone from 1979 to 1999 to gas-phase chemistry. They found that insignificant 

ozone increases over the period 2000–2009 were dominated by changes in transport (see also Section 

2.2.3.3). This is expected since stratospheric halogen loading has not yet decreased substantially over the 

last decade (compare EESC lines in Figure 2-4, or see Chapter 1). Kobayashi and Shibata (2011) also 
Global Ozone

2.37

used a CTM driven with observed meteorological conditions and pointed out that, in the northern 

midlatitudes, meteorological changes drive ozone changes on interannual to decadal timescales in the 

lower stratosphere, whereas upper stratospheric ozone decreases until the mid-1990s were dominated by 

changes in halogen loading, in agreement with previous studies.

Several studies assessed by WMO (2011) (e.g., Li et al., 2009; Waugh et al., 2009) used CCM 

model simulations driven by individual forcings to separately detect the influence of ODSs and GHGs on 

the past ozone trends. These results, corroborated by Plummer et al. (2010) and Fleming et al. (2011), 

have shown that ODS-induced changes dominated ozone during recent decades everywhere except for 

the lower tropical stratosphere (where little change has been observed; see Figure 2-8). However, none of 

these studies tested specifically whether observed ozone changes are consistent with responses to each of 

the forcings taking into account both the temporal evolution and spatial distribution of the changes. Such 

a test was performed by Gillett et al. (2011), who applied detection and attribution techniques common in 

other branches of climate science (e.g., Hegerl et al., 1996) to simulations from the CCMVal-2 ensemble, 

including simulations driven by all forcing, anthropogenic-only forcing, and GHG and ODS changes 

only over the period 1979–2005. Figure 2-19 (adapted from Gillett et al., 2011) shows a good agreement 

between observed total ozone trends and those simulated in response to the combined natural and 

anthropogenic forcing as well as to ODS changes alone. This suggests that the ODS changes are the 

dominant cause of the global ozone trends from 1979 to 2005, as concluded in WMO (2011). By 

applying optimal regression, Gillett et al. (2011) showed that the response of total column ozone to 

ODSs as well as to natural forcing (i.e., volcanoes and solar cycle) is detectable in observations. 

Furthermore, the observed and simulated responses to these forcings are of comparable magnitude. They 

also showed that the response of total ozone to GHG forcing is not yet detectable using this method. 

Note, however, that Gillett et al. (2011) attributed overall ozone changes over the entire 1979 to 2005 

period to ODS and GHG changes, without considering a possible change in the trend since around 2000.

Figure 2-19. Comparison of observed 

(black line, OBS) and simulated linear 

trends in zonal mean total column ozone in 

Dobson units (DU) over the 27-year period 

1979–2005. Observed total column ozone 

is taken from the merged TOMS/SBUV 

V8.0 data set. Simulated trends are from 

CCMVal-2 simulations and are shown for 

separate responses to ODS, GHG, and 

natural forcing, and all forcings combined 

(all, purple line). Gray band shows the 

estimated 5 to 95 percentile ranges of 

internal variability. Adapted from Gillett et 

al. (2011).

2.3.5.2 CHANGES IN UPPER STRATOSPHERIC OZONE AND ODS AND GHG CHANGES

As shown in previous Assessments (WMO, 1999, 2003, 2007, 2011), and reaffirmed by recent 

studies (e.g., Gillett et al., 2011), the large increase of ODSs from the 1970s to the late 1990s has been 

the main driver of the negative trend in upper stratospheric ozone until the late 1990s (see also Section 

2.2, Figures 2-5, 2-9, 2-11). Model simulations have indicated that stratospheric cooling due to 

increasing GHGs is another important driver of the ozone evolution in the upper stratosphere (WMO,

1999; Jonsson et al., 2009; Eyring et al., 2010; Oman et al., 2010b; Gillett et al., 2011; Fleming et al., 

2011; WMO, 2011; Stolarski et al., 2012). 

-90 -60 -30 0 30 60 90

Latitude [°]

-100

-80

-60

-40

-20

0

20

40

ozone column trend [DU]

OBS

all

ODS

GHG

natural

variability
Chapter 2

2.38

Figure 2-20. Observed and 

modeled ozone trend profiles. Left 

panel: For the period 1979 to 

1997. Right panel: For the period 

2000 to 2013. Black line: Average 

of all available observations in the 

35°N to 60°N latitude band (same 

as in Figure 2-11). Gray line with 

shading: Corresponding mean 

trends from CCMVal-2 model 

simulations (same as Figure 2-11, 

but only for the subset of 7 models 

that did simulations with fixed 

GHGs), with uncertainty range 

given by ±2 standard deviations of 

individual model trends. Red line: 

Trend attributed to ODS changes 

alone, from CCMVal-2 simulations 

with fixed GHG concentrations (7 

models). Blue line: Trend attributed to increasing GHGs alone, from CCMVal-2 simulations with fixed ODS 

concentrations (9 models). See Tables 1 and 2 of Eyring et al. (2010) or Tables 3-1 and 3-2 of WMO (2011) for 

details on CCMVal-2 fixed GHG and fixed ODS simulations.

The left panel of Figure 2-20 illustrates the influences of ODS and GHG changes on midlatitude 

ozone amounts during the period of ozone decline. The figure compares the observed ozone trend 

profiles (already shown in Figure 2-11; see also Figure 2-25 of WMO, 2011) to simulations from models 

in the CCMVal-2 ensemble forced by ODSs (red) and GHGs (blue) concentrations alone, in addition to 

simulations with all forcings (gray line and shading). Consistent with Oman et al. (2010a), simulations

forced with ODS changes alone and with all forcings produce a large decline (−7% per decade) in ozone 

at 2 hPa until the mid-1990s. Within observational and model uncertainty these changes are consistent 

with the observed decline. Ozone increases due to GHG-driven cooling are smaller at around 1% per 

decade and also peak around 2 hPa.

The more recent impacts of declining ODSs and increasing GHGs in the early 21st century are 

illustrated in the right panel of Figure 2-20. Since 2000, declining chlorine and the continued slowing of 

gas-phase ozone destruction cycles due to declining temperatures both act to increase upper stratospheric 

ozone. Each factor contributes about one-half to the simulated upper stratospheric ozone increases 

(Eyring et al., 2010; Oman et al., 2010b; Fleming et al., 2011; Shepherd and Jonsson, 2011; WMO, 

2011). The simulations also indicate that the contributions from ODSs and GHGs add linearly to produce 

the overall ozone change over this period (WMO, 2011).

Figure 2-20 indicates that this combined effect of GHG and ODS on upper stratospheric ozone 

can already be observed in the NH midlatitude upper stratosphere. Around 42 km (2 hPa), both ODS and 

GHG forced simulations each indicate a trend of 1–2% per decade in ozone concentration, compared to a 

mean observed trend of 2.5–5% per decade. Only when models are forced with both ODS and GHG 

changes are they able to capture trends as large as observed at these levels. 

Since WMO (2011), four years of additional observations and the availability of more data sets 

have decreased the uncertainty margins for the observed trends. There are now stronger indications that a 

significant ozone increase is detectable in the upper stratosphere since 2000, and that about half of this 

increase is due to declining ODSs, with another half coming from the photochemical response to the 

cooling of the upper stratosphere by increasing GHGs. 

-4 -2 0 2 4 6

ozone trend 2000 to 2013 [%/dec]

100

10

1

pressure [hPa]

-10 -8 -6 -4 -2 0

ozone trend 1979 to 1997 [%/dec]

20

30

40

50

altitude [km]

Ozone Trend 35°N to 60°N 

Observed (±2V)

CCMVal2 (±2V), ODS, GHG (±2V)
Global Ozone

2.39

2.3.5.3 TROPICAL OZONE CHANGES 

WMO (2011) reported negative ozone trends in the tropical lower stratosphere (about 18–19 km) 

for 1985–2005, based on SAGE II data. While the uncertainty in this trend was large, the ozone decrease 

was consistent with that simulated by CCMs. These simulations indicate a long-term increase in tropical 

upwelling and an increased Brewer-Dobson circulation (BDC), resulting in declining ozone in the 

tropical lowermost stratosphere. New studies that merge SAGE II data for 1984 to 2005 with either 

SHADOZ ozonesonde data for 1998–2009 (Randel and Thompson, 2011) or OSIRIS satellite data for 

2001–2012 (Sioris et al., 2014) seem to confirm a negative long-term ozone trend in the lowermost 

tropical stratosphere, −2% to −4% per decade for the 17 to 21 km altitude range, see also Figure 2-8. The 

magnitude and vertical profile of this ozone decline from 1984 to around 2000 are similar to the results 

from twelve different CCMVal-2 simulations (Eyring et al., 2010; WMO, 2011; Randel and Thompson, 

2011). 

However, as discussed in Section 2.2, recent analyses of shorter satellite data sets, between 2002 

and 2012, do not show significant lower stratospheric ozone trends. This is the case for both 

SCIAMACHY (Gebhardt et al., 2014) and MIPAS data (Eckert et al., 2014). Analysis of a combined 

SAGE II-GOMOS data set for 1984–2011 (Kyrölä et al., 2013) shows a significant negative trend 

between 20-22 km for the period 1984–1997 but an insignificant trend for 1997–2011. Examination of 

the tropical ozone time series near 70 hPa in Figure 2-8 reveals the large year-to-year variations of ozone 

in this region, and variations around a relatively constant level since 1997. The CCMVal-2 simulations in 

Figure 2-8 also do not indicate a clear decline over the last 10–15 years in the tropical belt. The absence 

of a significant trend in the most recent observations is therefore not unexpected. 

Overall these new results indicate substantial decadal variability of ozone in the tropical 

lowermost stratosphere. Based on existing tropical ozone records, there is little evidence for a continuing 

ozone decline in the tropical lowermost stratosphere since around 2000 that would be driven by a 

strengthening BDC. In agreement with WMO (2011), ozone values appear to have declined between 

1984 and about 2000. Chapter 4 of this Assessment examines the BDC and its possible long-term change 

in more detail. The general expectation from model simulations is that, in the long term, ozone in the 

tropical lowermost stratosphere will continue to decrease due to enhanced upwelling and increases of the 

BDC driven by increasing GHGs (WMO, 2011). 

2.4 UPDATE ON FUTURE OZONE CHANGES 

2.4.1 Expected Return to 1960 or 1980 Levels and Ozone Recovery 

The past two Ozone Assessments (WMO, 2007; 2011) have used chemistry-climate models 

(CCMs) as the primary tool for future ozone projections. WMO (2011) based their future projections on 

the simulations of 17 models, all of which participated in CCMVal-2 (Eyring et al., 2010). This ensemble 

remains the most comprehensive set of coordinated simulations of past and future stratospheric ozone 

changes. It is therefore the basis of future projections in the current Assessment. These CCMs have been 

extensively evaluated by CCMVal and the results are documented in the SPARC CCMVal Report 

(2010). Recent new simulations by four CCMVal-2 models using the revised estimates of ODS lifetimes 

(SPARC, 2013; also Chapter 1) are shown in Figure 2-21. These simulations indicate that the expected 

future evolution of near-global total ozone columns changes very little when using the revised ODS 

lifetimes. Changes in expected recovery dates to 1980 levels, for example, are typically less than a few 

years and are usually not significant given the large interannual variability and the intermodel 

differences. The estimates of return dates in different regions (Table 2-5) are not updated from WMO 

(2011). At this point there is not enough new evidence to motivate a revision of the estimates of ozone 

recovery presented in the previous Assessment.
Chapter 2

2.40

1960 2000 2040 2080

300

310

320

330

340

total ozone column [DU]

0

1

2

3

4

chlorine [ppbv]

1960 2000 2040 2080

284

288

292

296

total ozone column [DU]

0

1

2

3

4

chlorine [ppbv]

1960 2000 2040 2080

275

280

285

290

295

300

total ozone column [DU]

0

1

2

3

4

chlorine [ppbv]

1960 2000 2040 2080

265

270

275

280

285

290

295

total ozone column [DU]

0

1

2

3

4

chlorine [ppbv]

UMSLIMCAT, 60°S-60°N, RCP4.5 CMAM, 60°S-60°N, RCP6.0

GEOSCCM, 60°S-60°N, RCP6.0

O3 old lifetimes

O3 new lifetimes

Cltot(850hPa) old lifetimes, new lifetimes

Cly(1hPa) old lifetimes

 new lifetimes

O3 old lifetimes

O3 new lifetimes

Cltot(850hPa) old lifetimes, new lifetimes

Cly(1hPa) old lifetimes

 new lifetimes

O3 old lifetimes

O3 new lifetimes

Cltot(850hPa) old lifetimes, new lifetimes

Cly(1hPa) old lifetimes

 new lifetimes

WACCM, 60°S-60°N, RCP6.0

O3 old lifetimes

O3 new lifetimes

Cltot(850hPa) old lifetimes, new lifetimes

Cly(1hPa) old lifetimes

 new lifetimes

Figure 2-21. Comparison of total ozone column evolutions simulated using “old” ODS lifetimes from 

WMO (2010), black lines, and simulations using updated “new” ODS lifetimes from SPARC (2013), red 

lines. Also shown, on the axes on the right, are total organic chlorine at 850 hPa in the troposphere (Cltot, 

blue and cyan lines) and chlorine in the upper stratosphere at 1 hPa (Cly, dark green and light green 

lines). Annual means, averaged from 60°S to 60°N, are used. Results are from simulations with the 

chemistry-climate models UMSLIMCAT (Unified Model Single-Layer Isentropic Model of Chemistry and 

Transport; top left), CMAM (top right), GEOSCCM (bottom left, Oman and Douglass, 2014), and 

WACCM (bottom right). All models are described in Eyring et al. (2010) and WMO (2011). For 

greenhouse gases (GHGs) the simulations use the Representative Concentration Pathway (RCP) 6.0 

scenario, except for UMSLIMCAT, which uses the RCP4.5 scenario. WACCM is coupled to an 

interactive ocean; the other simulations use prescribed sea surface temperatures. For total ozone, sliding 

11-year averages are also plotted (thick lines).

WMO (2011) constructed its ozone projections by combining all available simulations from 

chemistry-climate model ensembles. WMO (2011) also gave equal weights to all simulations, and used 

multi-model means as the best estimate of future ozone and intermodel spread as a measure of 

uncertainty. This mean estimate of the CCMVal-2 ensemble can be seen in the black line in Figure 2-23, 

which will be discussed later in Section 2.4.3.1. 

Table 2-5 shows that the simulations predict a later return date for SH midlatitudes than for the 

NH. This is the opposite of the currently observed total column trends in Figure 2-4, or profile trends in 

Figures 2-10 and 2-11, which tend to indicate slightly more increase since 2000 in the SH. The 

differences are not very significant though. As mentioned (e.g., in Sections 2.2.3 and 2.2.4) decadal 

changes in transport play an important role. WMO (2011) assumes that long-term changes in transport, 

i.e., in the Brewer-Dobson circulation (BDC), cause the earlier NH return dates. Garny et al. (2013) 
Global Ozone

2.41

suggest other possible reasons for the asymmetry in return dates between NH and SH midlatitudes. They 

hypothesize that transport effects play only a small role in this asymmetry and that differences in column 

return dates are related to less efficient destruction of ozone by nitrogen-oxides (NOx) cycles in the NH 

and more efficient destruction of ozone by total inorganic chlorine (Cly) in the SH due to the larger polar 

vortex. These results should be interpreted cautiously because they rely on attribution of ozone changes 

in a single CCM and use a relatively novel and complex attribution method.

Since WMO (2011) there has been discussion about the possibility of using prior physical 

constraints to weight ozone projections from different models in order to reduce the significant 

uncertainty in current multi-model ozone projections. Challenges associated with combining projections 

from multi-model ensembles are common in all areas of climate science. Several weighting methods 

have been proposed. An overview of strategies for analyzing model ensembles and recommendations for 

good practice in applying multi-model ensembles is given in Knutti et al. (2010). Moreover, for CCMs 

the SPARC CCMVal Report (2010) presented a comprehensive set of diagnostics of model performance 

that are useful for model discrimination. 

Several recent studies demonstrate that, at least for some regions, the performance-based 

weighting may give a more realistic ozone projection than the multi-model mean approach used by 

WMO (2011). Strahan et al. (2011) argued that in the tropical lower stratosphere the spread of ozone 

projections from the full set of models is unrealistically large. They evaluated CCM performance based 

on several transport diagnostics and found that tropical ozone agreed best with observations in the 

models whose transport was the most realistic. They further demonstrated that models with the most 

realistic transport in the tropical stratosphere produced a smaller spread of ozone projections compared to 

the full set of models. Douglass et al. (2014) demonstrate that selecting models based on their realistic

performance can reduce the intermodel spread in the ensemble of projected ozone changes, although this 

comes at the expense of severely reducing the sample size. 

Douglass et al. (2012) showed that, in agreement with expectation based on photochemical 

theory of upper stratospheric ozone, models with cold biases in upper stratospheric temperatures have 

higher ozone levels and stronger ozone sensitivity to chlorine changes. Thus, intermodel spread is not 

always an appropriate measure of uncertainty in future upper stratospheric ozone projections, but is also 

indicative of systematic errors that depend on model biases in simulated temperature, ozone, and reactive 

nitrogen climatologies. 

Table 2-5. Expected return years when ozone columns will return to 1960 or 1980 values. Results 

from multi-model projections from the entire CCMVal-2 model simulation ensemble are repeated here 

from WMO (2011). Four new simulations using the recently updated longer ODS lifetimes from SPARC 

(2013; see also Chapter 1) indicate insignificant delays, about 2 years, in these return years (see Figure 

2-21). Interannual variability of ozone columns, systematic differences between models, and uncertainty 

about future emissions (see Figure 2-23) cause larger uncertainty in the estimated return years.

Region Date of 

Return

Mean Estimate Lower Bound Upper Bound

Global annual mean 1960 2053 2046 2064

1980 2032 2027 2038

Tropics annual mean 1960 --- --- ---

1980 2042 2028 ---

Northern midlatitude annual 

mean

1960 2029 2024 2036

1980 2021 2017 2026

Southern midlatitude annual 

mean

1960 2055 2049 2064

1980 2035 2030 2040
Chapter 2

2.42

Karpechko et al. (2013) used the dependence of Antarctic ozone projections on simulated biases 

in present-day transport to constrain future projections. They showed that constraining projections 

resulted in a slightly delayed ozone recovery compared to the multi-model mean; however the difference 

between the two estimates was within the uncertainty limits. Waugh and Eyring (2008) and WMO 

(2011) also reported little difference between weighted and unweighted ozone projections, providing 

some support for using multi-model mean projections, as done in Section 2.2. The agreement between 

weighted and unweighted projections can be expected if models have opposite biases that nearly 

compensate each other within the ensemble. However when the models tend to have common biases, 

weighted projections can differ considerably from the multi-model mean.

These studies suggest that physically based model weighting approaches may help to reduce 

uncertainty in future ozone projections for regions where ozone is dominated by a small number of well 

understood processes, which are poorly simulated by some models. For consistency with the last 

Assessment, however, this chapter uses unweighted multi-model mean and intermodel spread from all 

relevant CCMVal-2 models, as in Eyring et al. (2010) and WMO (2011), as discussed in Section 2.2.3.1. 

Further, as shown in Douglass et al. (2014), performance metrics based on observations of meteorology 

and transport do not currently reduce the ensemble spread of the impacts of climate change on ozone in 

the late 21st century because the response of any model to climate change is not closely related to its 

transport skill.

2.4.2 Effects of Future Stratospheric Temperature and Circulation Changes

Future increases in greenhouse gases (GHGs), especially carbon dioxide (CO2) are important for 

global ozone because they result in stratospheric cooling, slowing some chemical ozone destruction rates 

in the middle and upper stratosphere (e.g., Stolarski et al., 2012). According to model simulations, GHGforced climate change leads to increased upwelling in the tropics and to changes in planetary waves that 

drive an increase in the strength of the BDC, which in turn affects the distribution of ozone in the 

stratosphere and the transport of ODSs, nitrous oxide (N2O), methane (CH4), and water vapor (H2O) 

between the stratosphere and troposphere. For a mid-range GHG emission scenario, such as SRES A1B

used in CCMVal-2, the dominant impact on stratospheric temperatures is from CO2 changes. Future 

changes in transport due to the BDC, however, depend more on the amount of tropospheric warming, 

which will reflect the radiative forcing of the total mixture of future GHGs. Projecting future changes in 

the BDC is more difficult since the processes involved span the troposphere and stratosphere and are not 

well constrained in climate models. Observational evidence for changes in stratospheric temperatures 

and circulation is discussed in Chapter 4 of this Assessment.

Figure 2-22 shows a simple, illustrative experiment using the Solar-Climate-Ozone Links 

(SOCOL) CCM (Zubov et al., 2013) that separates the direct effects of GHG-induced temperature 

change on ozone from those resulting from stratospheric circulation change. This is achieved by 

performing timeslice experiments in which GHG and sea surface temperature and sea ice are varied 

independently. In the lower tropical stratosphere, large negative percentage changes of ozone below 20

hPa (Figure 2-22d) are driven almost completely by increased sea surface temperatures driven by 

tropospheric warming due to GHG increases (Figure 2-22c). As described in detail in WMO (2011), or 

Oberländer et al. (2013), the increased surface temperatures result in enhanced upward transport, 

especially in the tropics, and planetary wave driven increases in the mean meridional BDC. In 

midlatitudes, the same process is responsible for the enhancement of ozone in the lower stratosphere as 

ozone-rich air is transported from above. WMO (2011) concluded that CCMs consistently predict a 

strengthening of the BDC of around 2% per decade between 1960 and 2100, but that this strengthening 

had not been confirmed in observations (see also Section 2.3.5.3 and Figure 2-8). Recent work (see 

Chapter 4) separately considers changes in the shallow and deep branches of the BDC. Lin and Fu (2013) 

show that for the CCMVal-2 models, less than one-quarter of the predicted increase in tropical mass flux 

can be attributed to changes in the deep branch. CCM projections of changes to the shallow branch of the 
Global Ozone

2.43

BDC are sensitive to changes in the strength of the tropospheric subtropical jets and warming in the 

tropical upper troposphere (Lin and Fu, 2013), following the mechanism described by Shepherd and 

McLandress (2011). As well as the transport-induced impacts on lower stratospheric ozone 

concentrations, Meul et al. (2014) demonstrate using a CCM that the increased upwelling also leads to 

changes in chemical production and loss of tropical stratospheric ozone. The projected changes in lower 

stratospheric ozone concentrations in the late 21st century are thus caused by a combination of direct 

transport-induced changes and various chemical impacts that vary considerably with altitude in the low 

stratosphere. 

In the upper stratosphere, above 10 hPa, the local cooling effect of CO2 on ozone amounts 

(Figure 2-22b) is dominant, with little contribution from changes in transport. It is of comparable size to 

the increases in ozone driven by ODS reduction (Figure 2-22a; see also Figure 2-20 and Section 2.3.5.2). 

In midlatitudes, the upper stratospheric ozone increase from CO2 cooling is roughly similar to that in the 

tropics, whereas the ODS-driven ozone increases are larger at midlatitudes. These upper stratospheric 

increases, combined with enhanced transport, drive an increase in ozone also in the lower stratosphere, 

resulting in increases in total column amounts (with a stronger signal expected in the NH; see also 

Shepherd, 2008; Li et al., 2009). 

Figure 2-22. Zonal, 

annual and ensemble 

mean percentage changes 

of the ozone mixing ratio 

between different timeslice 

integrations of the SOCOL 

CCM for 2100 and for 

2000 conditions. 

(a) Ozone changes from 

2000 to 2100 when only 

ODSs are changed. 

(b) Ozone changes from 

2000 to 2100 due to GHG 

changes only. 

(c) Ozone changes due to 

changes in sea surface 

temperature and sea ice, 

driven by tropospheric 

warming. 

(d) Ozone changes when 

ODS, GHG, sea surface 

temperature, and sea ice 

are all changed together. 

White regions indicate 

nonsignificant changes at 

the 5% confidence level. 

Adapted from Zubov et al. 

(2013).
Chapter 2

2.44

2.4.3 Sensitivity to the Specification of Different Future Scenarios

As recognized in WMO (2011), numerous factors other than ODSs, including concentrations of 

CO2, N2O, and CH4, will affect the future evolution of ozone in the stratosphere. In addition, changes in 

stratospheric water vapor are important for HOx and NOx chemistry, as reviewed by WMO (2011). Apart 

from methane oxidation, stratospheric water vapor concentrations are strongly influenced by 

stratospheric and tropospheric temperature and circulation changes. All are reviewed in detail in Chapter 

4, Section 4.2.2 of this Assessment. Both natural and anthropogenic influences on the stratospheric 

aerosol layer also have the potential to influence ozone in the next decades, while ODS levels remain 

high. Since WMO (2011) our understanding of the influence of the 1991 Mt. Pinatubo eruption on ozone 

has increased, enhancing confidence in predictions of the future effects of these changes (Section 2.3.4).

Assessing the impact on ozone of future changes in CO2, N2O, and CH4 is complicated by the 

significant, nonlinear interactions between them (Portmann et al., 2012). The following subsections 

address impacts on ozone of various future scenarios, and the complex effects of changes in N2O and 

CH4. 

2.4.3.1 EFFECTS OF DIFFERENT REPRESENTATIVE CONCENTRATION PATHWAYS (RCP) SCENARIOS

Quantifying the combined influence of CO2, CH4, and N2O increases on ozone over the 21st

century requires an estimate of the potential range of future anthropogenic emissions of these gases and 

subsequent calculations of the effect of these changes on ozone abundance using CCMs. Given the 

computational complexity and cost of CCMs, the number of simulations available for these calculations 

is limited. 

As introduced in WMO (2011) the scenarios used for the latest Climate Model Intercomparison 

Project experiment (CMIP5) are the so-called Representative Concentration Pathways (RCPs, van 

Vuuren et al., 2011). These scenarios will also be the basis for most future runs of the next generation of 

CCMs, so they are reviewed here. It is important to note that the RCPs are chosen to represent some of 

the many different potential future emissions pathways and are produced using a complex chain of 

different Integrated Assessment Models (IAMs). RCPs are named to reflect their total radiative forcing 

in 2100. The evolution of emissions of CO2, CH4, N2O, and other GHGs in each scenario is complex and 

the ordering of emissions of each gas as a function of scenario changes with respect to time over the 21st

century. Key points to note are that CH4 emissions are much larger (by a factor of more than 2) in the 

RCP8.5 scenario than the other three scenarios and that N2O emissions in the RCP6.0 and 8.5 scenarios 

are much larger than those of the RCP2.6 and 4.5 scenarios by midcentury. Since the emissions 

trajectories for GHGs in the RCP scenarios are complex and have differing rates of change over time, 

this will lead to differing rates of change for key processes in CCMs, both in the stratosphere and in the 

troposphere. 

WMO (2011) reported early calculations of the sensitivity of future ozone to the GHG scenario 

and concluded that the GHG scenarios had a measurable impact on future ozone concentrations in the 

stratosphere and troposphere, particularly during the latter half of the 21st century, but that model 

uncertainty was at least as large as scenario uncertainty for all regions.

More recently, Eyring et al. (2013) considered the sensitivity of ozone projections to GHG 

scenario for those models submitted to CMIP5 that had a representation of stratospheric ozone 

chemistry. The results of Eyring et al. (2013) are qualitatively consistent with WMO (2011), increasing 

confidence in our understanding of the scenario uncertainty associated with future ozone projections. 

However, the CMIP5 results from Eyring et al. (2013) deviate quantitatively from the projections made 

by the CCMVal-2 models (WMO, 2011). As shown in Figure 2-23, the multi-model mean of the 

CCMVal-2 models assessed by WMO (2011), and used in this Assessment, differs in timing of minimum 

total ozone columns and in other aspects from the CMIP5 model projections. Most noteworthy are the 

differences between CCMVal-2 simulations using the SRES A1B intermediate radiative forcing (6 W 
Global Ozone

2.45

m-2) scenario from IPCC (2007), and CMIP5 simulations using the similar RCP6.0 scenario. These 

deviations may be due to differences in the models used in each ensemble, in the ensemble sizes, and 

differences in the scenarios themselves. It should also be noted that the RCP scenarios do not sample all 

possible future emission changes relevant to ozone, for example different ODS scenarios. As noted in 

WMO (2011), it will only be possible to refine estimates of scenario uncertainty by comparing a large 

number of CCM integrations forced with different emissions scenarios.

Given these caveats, all simulations in Figure 2-23 project substantial changes in total ozone 

columns in the future. Outside of the tropics, simulations for the scenarios with higher radiative forcing 

project a recovery of total ozone columns to 1980 values or even larger columns, with contributions from 

declining ODS, continued stratospheric cooling, and strengthening of the BDC (see previous sections). 

Future increases in tropospheric column ozone also contribute to the expected larger columns. In the 

tropics, projected future increases of tropospheric ozone column are particularly large in the RCP8.5 

scenario, where they more than compensate the projected decline of tropical stratospheric column ozone. 

Depending on the assumed scenario, total ozone columns in 2100 could vary by up to 10 DU or 4% in 

the tropics, by up to 20 DU or 7% in the global mean, and by up to 40 DU or 12% at midlatitudes. This 

large variation shows that, apart from the expected decline of ODS, future emissions of GHGs will have 

a substantial influence on ozone levels. 

Figure 2-23. 1980-baseline adjusted total column (tropospheric plus stratospheric) ozone time series for 

CMIP5 runs of models that follow four RCP scenarios for GHGs, and the A1 scenario from WMO (2003) 

for ODS. The RCP2.6 scenario is shown in the solid blue line with the 95% confidence interval for the 

mean of 5 models shown in blue stippling. The RCP4.5 scenario is shown in the light blue line and 

averages 6 models. The RCP6.0 scenario is shown in the orange line and averages 5 models. The 

RCP8.5 scenario is shown in the red line and averages 6 models. Five models are common to all 

scenarios. Also included is the CCMVal-2 multi-model mean (black line), which is based on different 

models, the SRES A1B scenario for GHGs, and the adjusted A1 scenario from WMO (2007) for ODS 

(see Section 2.2.3). Adapted from Eyring et al. (2013).
Chapter 2

2.46

2.4.3.2 INFLUENCES OF NITROUS OXIDE AND METHANE 

As well as being important GHGs, N2O and CH4 are key source gases for the NOx and HOx

chemical cycles, which directly impact ozone amounts. About 90% of stratospheric NOx arises from N2O 

oxidation (Vitt and Jackman, 1996). At low halogen levels, chemical ozone destruction is dominated by 

the NOx loss cycle in the middle stratosphere and by the HOx loss cycle below 20 km and above ~50 km 

(in the mesosphere). As the ODS burden declines over the 21st century, ozone changes will depend 

strongly on the N2O and CH4 burdens, which are assumed to change in very different ways in the RCP 

scenarios. These impacts are considered in this section. 

In the global mean, for a mid-range N2O emissions scenario, simulations compute a total ozone 

reduction by around ~5 DU by 2050, compared to preindustrial values. Similar changes are computed by 

both 2-D (Fleming et al., 2011; Portmann et al., 2012) and 3-D (Revell et al., 2012a, b) models. This 

reduction, shown by the green line in Figure 2-24, is about one-quarter of the isolated maximum effect of 

the ODS changes in 2000 (blue line in Figure 2-24), and comparable to the increases in total column 

ozone due to the isolated effects of CO2 and of CH4 through the 21st century (red and yellow lines in 

Figure 2-24). These studies found that the depletion of the total column due to the isolated effect of N2O 

does not exceed that due to ODSs until ~2080. The efficiency of N2O in destroying ozone can be 

compared to ODSs by computing the Ozone Depletion Potential for these gases (Ravishankara et al., 

2009; Daniel et al., 2010). This is discussed further in Chapter 5 (Sections 5.3–5.4), along with policyrelevant information about future N2O increases.

Figure 2-24. Global and annual average 

total ozone time series relative to 1860 

values from model simulations (lines) and 

ground-based data (pink crosses, updated 

from from Fioletov et al., 2002). The black 

dotted line shows a base simulation of the 

3-D chemistry-climate model GEOSCCM 

with the A1 scenario of WMO (2007) for 

ODS concentrations and the SRES A1B 

scenario for GHG concentrations (same as 

for the CCMVal-2 simulations). The black 

solid line shows the simulation of a 2-D 

chemical transport model that uses the 

same forcings. The other colored lines 

show additional scenarios of the 2-D model 

in which only selected forcings are varied in 

time (while keeping the others at 1850 

levels). The experiments are as follows: 

Red-line: Only CO2 varies. Green line: Only 

N2O varies. Yellow solid line: Only CH4

varies. Blue solid line: Only ODSs vary. 

Also shown are experiments in which both 

ODSs and CH4 are varied. The orange dot dashed line shows the effects of CH4 in the presence of timedependent ODS changes (difference between simulation with CH4 and ODSs changing and simulation 

with only ODSs changing). The blue dot dashed line shows the effects of ODSs in the presence of timedependent CH4 changes (difference between simulation with CH4 and ODSs changing and simulation 

with only CH4 changing). Finally, the orange dashed line shows the impact of CH4 on ozone when its 

effects are confined to impacts on the radiation budget only. Adapted from Fleming et al. (2011).
Global Ozone

2.47

Revell et al. (2012a) provided a study of the sensitivity to N2O/NOx by comparing three RCP 

scenarios, bounded by RCP2.6 (lower N2O growth) and RCP8.5 (higher N2O growth). They performed a 

suite of CCM simulations in which each of the gases is varied in isolation along four different future N2O 

and CH4 pathways. Their results demonstrate clear links between the assumed GHG scenario and 

stratospheric ozone. Increased N2O emissions lead to higher NOx concentrations and faster chemical 

ozone destruction in the middle stratosphere. Middle stratospheric ozone concentrations in the late 21st

century are thus substantially lower for the RCP8.5 N2O scenario than for the RCP2.6 scenario (Figure 2-

25a, b). In the lower tropical stratosphere the differences are of opposite sign because of enhanced ozone 

production following CH4 oxidation caused in the troposphere by the higher NOx concentrations in the 

RCP8.5 scenario (this mechanism is discussed below). Some of this lower stratospheric ozone increase 

could also be due to “self-healing” wherein the ozone decreases in the middle and upper stratosphere 

allow more solar UV radiation to penetrate to lower altitudes, leading to ozone enhancements in the 

lower stratosphere (Mills et al., 2008). 

Figure 2-25. Ozone changes in 

the 2090s due to different N2O 

and CH4 scenarios, computed with 

the National Institute of Water and 

Atmospheric Research (NIWA)-

SOCOL chemistry-climate model. 

(a) Difference between ozone in 

the 2090s under the N2O-RCP8.5 

scenario and ozone under the 

N2O-RCP2.6 scenario, calculated 

as a per-centage of N2O-RCP2.6 

ozone, as a function of latitude 

and pressure. In 2100, N2O mixing 

ratio is 340 parts per billion by 

volume (ppbv) for the RCP2.6 

scenario, and 430 ppbV for the 

RCP8.5 scenario, com-pared to 

320 ppbv in 2010. (b) Same but 

for the change in total column 

ozone (in Dobson units). Both 

simulations use the same 

scenario for CH4 and CO2 (IPCC 

SRES A1B), and the adjusted A1 

scenario from WMO (2007) for the 

halocarbons. (c, d) same but for 

CH4-RCP8.5 ozone minus CH4-

RCP2.6 ozone in the 2090s 

decade, otherwise using the same 

scenario for N2O and CO2 (IPCC 

SRES A1B), and the adjusted A1 

scenario from WMO (2007) for the 

halocarbons. In 2100, the CH4

mixing ratio is 1.25 parts per 

million by volume (ppmv) for the 

RCP2.6 scenario, and 3.75 ppmv 

for the RCP8.5 scenario; compared to 1.8 ppmv in 2010. 

Adapted from Revell et al. (2012a).

Ozone difference between different N O scenarios 2

Pressure (hPa)

(a) 1

2

5

10

20

50

100

−10

−5

0

5

−90 −60 −30 0 30 60 90

−15

−10

−5

0

Latitude (°)

Column ozone difference (DU)

(b)

%

Ozone difference between different CH scenarios 4

Pressure (hPa)

(c)

1

2

5

10

20

50

100

−5

0

5

10

15

−90 −60 −30 0 30 60 90

8

12

16

20

24

28

Latitude (°)

Column ozone difference (DU)

(d)

%
Chapter 2

2.48

Various feedbacks are also important. The recovering ozone layer will reduce the penetration of 

UV radiation to the middle stratosphere and reduce the photolytic production of O(1D) (Rosenfield and 

Douglass, 1998; Fleming et al., 2011; Chipperfield et al., 2014), thereby reducing the production of NOy

via N2O oxidation. Upper stratospheric cooling caused by GHG increases leads to enhanced conversion 

of NOy to N2 and less ozone destruction (Rosenfield and Douglass, 1998; Plummer et al., 2010). 

Portmann et al. (2012) computed that in 2100, the ozone destruction caused by increased N2O was 

reduced by roughly 20% when the CO2-induced stratospheric cooling effects on NOy were included in 

the model simulations. Oman et al. (2010a) showed that the upper stratospheric cooling was greater 

when CCM simulations used the SRES A2 scenario than when they used the SRES A1b scenario. This 

enhanced cooling moderated the NOy increase relative to the N2O growth in the A2 scenario. Climate

change-induced changes to the circulation, including an enhancement of the BDC, also modify the 

photochemical breakdown of N2O (Rosenfield and Douglass, 1998; Plummer et al., 2010). A stronger 

Brewer-Dobson circulation will increase the loss of NOy by increasing the rate of NOy transport to the 

extratropical troposphere, where it is removed via nitric acid (HNO3) washout. By comparing CCM 

simulations of N2O increases, with and without the radiative and dynamical impacts of GHGs, Plummer 

et al. (2010) showed that GHG-induced cooling and circulation changes reduced the N2O-induced 

increase of stratospheric NOy by more than 50% by the end of the century. 

The sensitivity of ozone to CH4 is also complex, arising from a combination of direct and 

indirect effects (e.g., Brasseur and Solomon, 2005). Ozone is decreased through the direct impact of 

enhanced HOx–ozone loss cycles as CH4 is oxidized to H2O. This mechanism dominates above ~45 km, 

so that the net impact of CH4 is to reduce ozone in the very upper stratosphere and mesosphere. Figure 2-

25c, d show the sensitivity of ozone in the late 21st century to the choice of high (RCP8.5) or low 

(RCP2.6) CH4 scenarios. Below 45 km, and in the total column, increased CH4 loading leads to increases 

in ozone via several mechanisms: 

1) CH4 converts active chlorine to the reservoir HCl via the reaction:

CH4 + Cl → HCl + CH3. This reduces the chlorine-catalyzed ozone loss, as long as chlorine levels 

are high (red areas around 20 hPa near the poles in Figure 2-25c).

2) CH4 oxidation (mainly CH4 + OH) leads to enhanced NOx-induced ozone production in the 

troposphere and lowermost stratosphere (“photochemical smog chemistry,” red area below 50 hPa 

in Figure 2-25c).

3) Increased H2O, from methane oxidation, enhances stratospheric cooling and reduces chemical 

ozone loss rates (shown by the red area in Figure 2-25c around 10 to 20 hPa in the tropics and 

midlatitudes, and around 20 hPa near the poles).

For present-day chlorine loading, roughly two-thirds of the total column increase due to methane 

loading can be attributed to mechanism (1), but this will be much less important by the late 21st century. 

The process also reduces the effectiveness of present-day chlorine in depleting ozone by 15–20% 

(Fleming et al., 2011; Portmann et al., 2012). Mechanism (3) is most important in the middle 

stratosphere to lower mesosphere (30–60 km); it contributes about 20% to the total projected CH4-

induced increase in total column ozone during the 21st century (Figure 2-25d). By 2100, mechanism (2) 

will likely have the greatest impact. Methane oxidation (mechanism 2) is also affected by lower 

stratospheric NOx produced by N2O oxidation (e.g., Portmann and Solomon, 2007), as seen in Figure 2-

25a. Also, CH4 loading will increase stratospheric HOx, which can (a) sequester NOx in the reservoir 

HNO3 (Nevison et al., 1999; Randeniya et al., 2002), and (b) enhance the HOx-ozone loss, thereby 

reducing atomic oxygen abundance which in turn will reduce the NOx-ozone loss cycles (Revell et al., 

2012b).

Based on the SRES A1B GHG scenario, 2-D model calculations show that the total column 

response of ozone to CH4 is around half to two-thirds that of N2O at the end of the 21st century, with a 

CH4-induced increase in the global ozone column of between 3 DU (Portmann et al., 2012) and 5 DU 

(Fleming et al., 2011) by 2100 (see Figure 2-24). However, quantifying the impact of CH4 on ozone 

amounts toward the end of the century will have a large uncertainty due to the wide variation among the 
Global Ozone

2.49

RCP CH4 scenarios, especially RCP8.5 (Section 2.4.3.1). Finally, uncertainties in the kinetic and 

photolytic loss rate parameters of both CH4 and N2O will have significant impacts on future ozone 

amounts (SPARC, 2013).

2.5 HIGHLIGHTS FOR POLICYMAKERS

This Assessment confirms the success of the international Montreal Protocol for the protection 

of the ozone layer.

As reported in previous Assessments, the decline of stratospheric ozone has been stopped in the late 

1990s. Since about 2000, ozone levels in most parts of the stratosphere have remained approximately 

constant, or have been increasing slightly. Assessment of the most recent ozone observations since 2010 

confirms these overall trends.

In the upper stratosphere, around 40 km altitude, ozone levels have been increasing in the last 10 years, 

and at a statistically significant rate. This increase is expected and is consistent with scientific 

understanding. About half of the ozone increase is due to declining ozone-depleting substances (ODSs, 

declining due to the Montreal Protocol). The other half is due to cooling of the stratosphere due to carbon 

dioxide (CO2) increases, which slows chemical ozone destruction cycles in the upper stratosphere.

Not only ozone-depleting substances, but also increasing greenhouse gases affect the ozone 

layer.

Radiatively active greenhouse gases (GHGs) absorb thermal infrared radiation in the troposphere (global 

warming). Less thermal radiation reaches the stratosphere. In addition, GHGs, especially CO2, emit 

radiation from the stratosphere to space. Both effects result in cooling of the stratosphere with increasing 

GHG levels. It is expected that GHG levels will increase throughout this century, and that the cooling of 

the stratosphere will continue.

A small acceleration of the global stratospheric Brewer-Dobson circulation (BDC) over the next century 

is expected from model simulations. This change is caused by GHG-induced warming of the troposphere 

and cooling of the stratosphere. Acceleration of the BDC will reduce ozone in the tropics and enhance 

ozone at higher latitudes.

As shown in previous Assessments, the continuing slow decline of ODSs, and the expected further 

increase of CO2, will contribute to a recovery of stratospheric ozone. Model simulations indicate that 

total column ozone outside of the tropics will recover to 1980s values by 2020 to 2050 and to 1960s 

values by 2025 to 2060, later in the Antarctic. The recovery dates will depend on future GHG emissions 

but are expected to remain in this range for different plausible emission scenarios. In the second half of 

the century, ozone columns may even exceed historical levels. Figure 2-26 shows the expected range of 

near global (60°S to 60°N) annual mean total column ozone anomalies. In the tropics, ozone columns 

will probably not recover to 1960 values, but past ozone decline in the tropics has also been small.

Importance of future nitrous oxide and methane emissions

Since the last Assessment, model simulations have confirmed that not only ODSs and CO2, but also 

future levels of nitrous oxide (N2O) and methane (CH4) will play a significant role in the recovery of 

stratospheric ozone over this century. By itself, increasing N2O will increase ozone loss. This would 

delay and negate part of the expected ozone recovery (due to declining ODSs and stratospheric cooling).
Chapter 2

2.50

Increasing methane, on the other hand, will generally increase ozone levels by tying up chlorine and by 

enhancing ozone production in the lower stratosphere. In the second half of the century, lower chlorine 

levels, stratospheric cooling, and other factors will reduce the efficiency by which CH4 and N2O 

emissions affect ozone.

Continued monitoring

Apart from future ODS levels, future levels of GHGs, especially carbon dioxide (CO2), nitrous oxide 

(N2O), methane (CH4), and water vapor (H2O) are expected to have important effects on the evolution of 

stratospheric ozone. Although most scenarios predict a recovery of stratospheric ozone, only continued 

measurements of ozone and these trace gases, and the combination of observations and model 

simulations, can verify that the ozone layer is recovering.

1960 2000 2040 2080

-4

0

4

8

ozone anomaly [%]

CCMVal-2 ±2V

observations

total ozone column 60°S to 60°N

Figure 2-26. Simulated and observed evolution of the near global total ozone column. Observations are 

annual mean anomalies averaged over all available ground- and satellite-based measurements (blue 

line). Black line and gray range give multi-model mean and ±2 standard deviations of simulated 

individual model annual mean anomalies for the CCMVal-2 simulations already used in WMO (2011). 

Only the subset of 9 models performing runs for fixed ODS and for all forcings is used. All data are 

referenced to the 1998 to 2008 period. Up to 2000, the simulations account for changing ODSs, GHGs, 

observed sea surface temperatures and sea ice, volcanic aerosol, the 11-year solar-cycle, and the QBO 

(REF-B1 scenario, Eyring et al., 2010; WMO, 2011). After 2000 the adjusted A1 scenario of WMO (2007) 

is used for ODSs, the SRES A1B scenario is used for GHGs, sea surface temperatures and sea ice are 

from other models, the QBO is generated internally, there is no volcanic aerosol, and most models, 

except for 3, do not include the solar cycle (REF-B2 scenario, Eyring et al., 2010; WMO, 2011).
Global Ozone

2.51

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Global Ozone

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Chapter 2

2.64

APPENDIX 2A

Ozone Data Sets

1) Ground-Based Measurement Systems

The World Ozone and Ultraviolet Data Centre (WOUDC) archives a record of ground-based 

total column ozone observations (http://www.woudc.org). This includes Dobson spectrophotometers 

(since the 1920s), automated Brewer spectrometers (since the 1980s), and filter instruments (Bojkov et 

al., 1994; Fioletov et al., 2008). At many ground stations, the Brewer instruments have supplemented or 

replaced the Dobsons (Scarnato et al., 2010). Dobson Umkehr ozone profiles provide a long historical 

record, with regular measurements beginning in 1957 at several stations around the world (Figure 2A-1). 

In addition to Dobson spectrometers, Brewer instruments in principle also provide Umkehr 

measurements since the 1990s (Petropavlovskikh et al., 2005).

Zenith-sky visible spectral measurements from SAOZ (Système d’Analyse par Observation 

Zénithale) instruments (Hendrick et al., 2011) are another source of total column ozone data, as are 

Fourier-Transform Infrared spectrometers (FTIRs). Both SAOZ and FTIR instruments are part of the 

NDACC network (Network for Detection of Atmospheric Composition Change, http://www.

ndsc.ncep.noaa.gov/) and the GAW (Global Atmosphere Watch) network (Table 2-3). Selected time 

series extend back to the early 1990s (SAOZ) and 1995 (FTIR). In addition to the total ozone column, 

the FTIR instruments also provide low vertical resolution ozone profiles.

Ozonesondes have been used since the middle 1960s for routine monitoring of ozone profiles at 

a number of stations around the world. Figure 2A-1 shows the network of ozonesonde stations, and other 

ground-based ozone profiling stations used in this Assessment. Most networks are biased toward 

populated Northern Hemisphere areas (Figure 2A-1), with additional capabilities over Antarctica (Liu et 

al., 2013). The Southern Hemisphere Additional Ozonesondes project (SHADOZ: Thompson et al., 

2012) has added substantially to the global coverage since 1998. Ozonesonde observations are also the 

backbone of the MATCH network of measurements (see Chapter 3), which are made in unpopulated 

regions of the NH and are crucial for monitoring ozone depletion in Arctic winter and spring.

Ozone measurements by lidar systems have been in operation since the late 1980s (Steinbrecht et 

al., 2009; Nair et al., 2012; Kirgis et al., 2013). Currently they are available at 12 stations, mostly in the 

NH, but fewer stations have long records that are used in this Assessment (Table 2-3; Figure 2A-1).

Ground-based microwave radiometers have been used for stratospheric ozone monitoring since 

the 1990s (Boyd et al., 2007; Studer et al., 2014). Stations are mostly in the Northern Hemisphere, with 

one station operating in the Southern Hemisphere (Lauder, New Zealand, see Figure 2A-1). 

Sondes

Lidar

mWave

FTIR

Umkehr -60

-40

-20

0

20

40

60

-135 -90 -45 0 45 90 135 180

Figure 2A-1. Ground-based ozone profiling stations used in this Assessment. See Table 2-3 for details 

on the few stations running lidars, microwave radiometers, Fourier-Transform Infrared spectrometers 

(FTIRs), or Umkehr measurements.
Global Ozone

2.65

2) Nadir-Viewing Satellite Instruments

The longest available satellite ozone record comes from Solar Backscatter Ultraviolet (SBUV) 

measurements. The Nimbus-4 BUV instrument collected ozone profiles between 1970 and 1976 from a 

sun-synchronous polar orbit. Routine measurements of profiles and total ozone from polar-orbiting 

satellites began in the late 1970s with the Nimbus-7 SBUV, followed by SBUV/2 instruments on several 

NOAA satellites. At least one SBUV instrument has been operational at all times since 1978. SBUV 

retrievals provide coarse-resolution vertical profiles. Partial column data are integrated to produce a total 

column ozone record. A series of similar instruments (i.e., Ozone Monitoring Instrument (OMI) and 

Ozone Mapping and Profiler Suite (OMPS)) have also flown on more recent research satellites (e.g., 

Kroon et al., 2011; Kramarova et al., 2014), with sensors designed to detect total ozone with smaller 

spatial footprints than the SBUV instruments. WMO (2011) used total ozone obtained using the V8 

retrieval algorithm, which included a homogenization of the time series (Stolarski and Frith, 2006). 

SBUV data based on the more recent retrieval algorithm (V8.6: Bhartia et al., 2013; McPeters et al., 

2013) are used in this Assessment.

Several European instruments have collected global data from the satellite polar orbiting 

platforms since 1995. These are: the Global Ozone Monitoring Experiment (GOME: 1995–2011); the 

Scanning Imaging Spectrometer for Atmospheric Chartography (SCIAMACHY: 2002–2012), Ozone 

Monitoring Instrument (OMI: since 2004) and GOME-2 aboard Metop-A (since 2007) and Metop-B 

(since 2012). Various UV total ozone algorithms are applied to these sensors: WFDOAS (ColdeweyEgbers et al., 2005), TOSOMI/TOGOMI (Antón et al., 2011), and GDP5/GODFIT (van Roozendael et 

al., 2012; Lerot et al., 2014). Generally, all algorithms show very good agreement (within 1%) with 

ground-based data and with other satellite data (e.g., Weber et al., 2005, 2013; Koukouli et al., 2012; 

Lerot et al., 2014). A variant of the TOSOMI/TOGOMI algorithm called OMI-DOAS (Kroon et al., 

2008) has routinely been used to retrieve total column ozone from OMI (since 2004).

3) Solar and Stellar Occultation Instruments

Solar and stellar occulation instruments provide the highest vertical resolution in ozone profile 

measurements from space, typically 2 km, and generally provide very accurate ozone profiles. However, 

their global sampling is rather sparse compared to limb-scattering and limb-emission instruments. These 

instruments are:

• The Stratospheric Aerosol and Gas Experiment II (SAGE II) provides one of the longest single 

instrument data sets (1984 to 2005) of ozone profile information. The ozone values in the new 

version (v7.0, see Table 2-2) are 1–2% lower than in the previous version (6.2) due to the change of 

the ozone absortion cross section used in the retrieval (Damadeo et al., 2013; Remsberg, 2014). 

• The Halogen Occultation Experiment (HALOE) aboard the Upper Atmosphere Research Satellite 

(UARS) has collected ozone profiles (cloud to mesosphere) from 1991 to 2005 with ~2 km 

resolution. Further information about profiles can be found at NASA Goddard Earth Sciences Data 

& Information Services Center (GES DISC): http://daac.gsfc.nasa.gov/. Although the HALOE 

record is not used directly in this Assessment, it is part of the Global OZone Chemistry And Related 

trace gas Data records for the Stratosphere (GOZCARDS) data set (R. Wang et al., 2013).

• The Global Ozone Monitoring by Occultation of Stars (GOMOS) on Envisat is a star-occultation 

instrument measuring in the UV, visible and near infrared spectrum. It provided global, nighttime 

ozone profiles in the altitude range 15–100 km with 2–3 km vertical resolution (e.g., Bertaux et al., 

2010; Kyrölä et al., 2010, 2013). 

• The Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS) was launched 

in 2004 aboard the SCISAT satellite. Although its record is short for trend analysis, it is used in the 

The HARMonized data set of OZone profiles (HARMOZ) database (Sofieva et al., 2013). 
Chapter 2

2.66

4) Limb-Scattering Instruments

Limb-scattering instruments have a typical vertical resolution of 3–4 km and provide very dense 

sampling of the daytime portion of the globe using backscattered solar radiation. These instruments are: 

• The Optical Spectrograph and Infrared Imager System (OSIRIS) instrument was launched in 2001 on 

the Odin satellite (McLinden et al., 2012). 

• The Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) 

was launched on Envisat in 2002 and operated until 2012 (Gottwald and Bovensmann, 2011).

• The OMPS (Ozone Mapping and Profiler Suite) is a mission providing limb scatter ozone profiles 

since 2012 (Kramarova et al., 2014). While its record is too short for ozone assessment, it is the only 

recently launched new limb sounder. OMPS may play an important role in extending the 

observational record beyond the lifetime of other existing satellite ozone profilers. 

5) Limb-Emission Instruments 

Limb emission instruments operate in the thermal infrared and microwave part of the spectrum, 

meaning they can provide measurements in both day and night, and they provide a much denser 

sampling than the occultation instruments. They have similar vertical resolution and sampling 

characteristics as the limb-scattering instruments. 

• Since 2001, the Sub-Millimetre Radiometer (SMR) aboard the Odin platform has provided twiceweekly measurements of global stratospheric ozone between 12 and 60 km altitude with random

uncertainty estimated at 20%. Retrieved ozone profiles have a vertical resolution of about 3 km in 

the stratosphere (Urban et al., 2005). 

• Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) is another emission 

instrument providing ozone profiles. SABER data are not used for trend analysis in this Ozone 

Assessment, but the orbital characteristics make the data useful for estimating the diurnal cycle 

(Studer et al., 2014; Section 2.3.2). Further information can be found at http://saber.gatsinc.com/overview.php. 

• The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board Envisat 

provided daily infrared sensing of global ozone profiles, and many other trace gases, from late 2002, 

and in a different mode, from late 2004 until April 2012, covering the ~10–70 km altitude range with 

resolution decreasing from 2 km at the bottom to 5 km at the top of the profile (von Clarmann et al., 

2009). Several processers for MIPAS exist. MIPAS data are included in the HARMOZ data set

(Sofieva et al., 2013). 

• Since 2004, the EOS-Aura Microwave Limb Sounder (Aura MLS) has provided near-global 

information on ozone profiles (and many other trace gases) between the upper troposphere and the

mesosphere. Ozone profiles are retrieved from microwave emissions (Waters et al., 2006; Livesey et 

al., 2006). The Upper Atmosphere Research Satellite (UARS) Microwave Limb Sounder (UARS 

MLS) is a predecessor to Aura MLS (Barath et al., 1993). Both MLS records are used in the 

GOZCARDS combined data set (Froidevaux et al., 2008; R. Wang et al., 2013).

6) Additional Combined Ozone Data Sets Not Used in the Assessment

• SBUV V8.6 NOAA merged data set, where bias corrections in overlapping periods have been 

applied (see http://larss.science.yorku.ca/QOS2012pdf/6071.pdf; data available at 

ftp://ftp.cpc.ncep.noaa.gov/SBUV_CDR/).

• SWOOSH (Stratospheric Water and Ozone Satellite Homogenized, http://www.esrl.noaa.gov/csd/

groups/csd8/swoosh/)

• BDBP (Binary Data Base of Profiles; Hassler et al., 2009, 2014; Bodeker et al., 2013). 

• The trajectory-mapped ozonesonde data set (Liu et al., 2013). 
CHAPTER 3

Update on Polar Ozone: Past, Present, and Future

Lead Authors:

M. Dameris

S. Godin-Beekmann

Coauthors:

S. Alexander

P. Braesicke

M. Chipperfield

A.T.J. de Laat

Y. Orsolini

M. Rex

M.L. Santee

Contributors:

R. van der A

I. Cionni

S. Dhomse

S. Diaz

I. Engel

P. von der Gathen

J.-U. Grooß

B. Hassler

L. Horowitz

K. Kreher

M. Kunze

U. Langematz

G.L. Manney

R. Müller

G. Pitari

M. Pitts

L. Poole

R. Schofield

S. Tilmes

M. Weber

Chapter Editors:

S. Bekki

J. Perlwitz
[Formatted for double-sided printing.]

From: 

WMO (World Meteorological Organization), Scientific Assessment of Ozone Depletion: 2014, Global 

Ozone Research and Monitoring Project – Report No. 55, 416 pp., Geneva, Switzerland, 2014.

This chapter should be cited as: 

Dameris, M., and S. Godin-Beekmann (Lead Authors), S. Alexander, P. Braesicke, M. Chipperfield, 

A.T.J. de Laat, Y. Orsolini, M. Rex, and M.L. Santee, Update on Polar ozone: Past, present, and future, 

Chapter 3 in Scientific Assessment of Ozone Depletion: 2014, Global Ozone Research and Monitoring 

Project – Report No. 55, World Meteorological Organization, Geneva, Switzerland, 2014.
CHAPTER 3

UPDATE ON POLAR OZONE: PAST, PRESENT, AND FUTURE

Contents

SCIENTIFIC SUMMARY ........................................................................................................................... 1

3.1 INTRODUCTION.............................................................................................................................. 3

3.1.1 State of Science in 2010......................................................................................................... 3

3.1.2 Scope of Chapter.................................................................................................................... 4

3.2 RECENT POLAR OZONE CHANGES ............................................................................................ 4

3.2.1 Measurements of Ozone and Related Constituents................................................................ 4

3.2.2 Recent Evolution of Polar Temperatures and Vortex Characteristics ................................... 5

3.2.2.1 Polar Temperatures ................................................................................................... 5

3.2.2.2 Polar Vortex Breakup Dates ..................................................................................... 6

3.2.2.3 Long-Term Evolution of PSC Volume ..................................................................... 7

3.2.3 Ozone Depletion in Recent Arctic Winters............................................................................ 8

3.2.3.1 Ozone Depletion in the Arctic Winters of 2009/2010, 2011/2012, 

and 2012/2013......................................................................................................... 10

3.2.3.2 Ozone Depletion in the Arctic Winter 2010/2011 .................................................. 11

3.2.3.3 Two Arctic Springs with Very Low Total Ozone: 1997 and 2011......................... 14

3.2.4 Recent Antarctic Winters..................................................................................................... 15

3.3 UNDERSTANDING OF POLAR OZONE PROCESSES .............................................................. 16

3.3.1 Polar Stratospheric Clouds................................................................................................... 16

3.3.1.1 Recent Observations ............................................................................................... 17

3.3.1.2 Revised Heterogeneous NAT and Ice Nucleation Scheme..................................... 18

3.3.1.3 Improved Understanding of PSC Composition ...................................................... 19

3.3.1.4 PSC Forcing Mechanisms....................................................................................... 20

3.3.2 Polar Chemistry.................................................................................................................... 21

3.3.2.1 Heterogeneous Chemistry ....................................................................................... 21

3.3.2.2 Gas-Phase Chemistry .............................................................................................. 22

3.3.2.3 Ozone Loss Processes............................................................................................. 23

3.3.3 Polar Dynamical Processes.................................................................................................. 25

3.3.3.1 Relation Between Wave Driving and Polar Ozone................................................. 25

3.3.3.2 The Role of Leading Modes of Dynamical Variability .......................................... 26

3.3.3.3 Meridional Mixing .................................................................................................. 27

3.4 RECOVERY OF POLAR OZONE.................................................................................................. 27

3.4.1 Polar Ozone Recovery in Previous Assessments................................................................. 27

3.4.2 Long-Term Antarctic Ozone Trends.................................................................................... 28

3.4.2.1 Vertically Resolved Ozone ..................................................................................... 28

3.4.2.2 Springtime Total Ozone .......................................................................................... 29

3.4.3 Long-Term Ozone Trend in the Arctic ................................................................................ 31

3.5 FUTURE CHANGES IN POLAR OZONE..................................................................................... 31

3.5.1 Factors Controlling Polar Ozone Amounts.......................................................................... 32

3.5.2 Long-Term Projection of Polar Ozone Amounts................................................................. 33

3.5.3 Uncertainties of Future Polar Ozone Changes..................................................................... 36

3.5.3.1 Internal Variability and Model Uncertainty .......................................................... 36
3.5.3.2 Scenario Uncertainty............................................................................................... 37

3.6 KEY MESSAGES OF CHAPTER 3 FOR THE DECISION-MAKING COMMUNITY............... 39

3.6.1 Recent Polar Ozone Changes............................................................................................... 39

3.6.2 Understanding of Polar Ozone Processes ............................................................................ 41

3.6.3 Recovery of Polar Ozone ..................................................................................................... 41

3.6.4 Future Changes in Polar Ozone............................................................................................ 42

REFERENCES............................................................................................................................................ 43

APPENDIX 3A: Satellite Measurements Useful for Polar Studies ........................................................... 60
Polar Ozone

3.1

SCIENTIFIC SUMMARY

Polar Ozone Changes

As stated in the previous Assessments, ozone-depleting substance (ODS) levels reached a maximum 

in the polar regions around the beginning of this century and have been slowly decreasing since 

then, consistent with the expectations based on compliance with the Montreal Protocol and its 

Amendments and adjustments. Considering the current elevated levels of ODSs, and their slow rate 

of decrease, changes in the size and depth of the Antarctic ozone hole and in the magnitude of the 

Arctic ozone depletion since 2000 have been mainly controlled by variations in temperature and 

dynamical processes. 

• Over the 2010–2013 period, the Antarctic ozone hole continued to appear each spring. The 

continued occurrence of an Antarctic ozone hole is expected because ODS levels have declined by 

only about 10% from the peak values reached at the beginning of this century. 

• Larger year-to-year variability of Antarctic springtime total ozone was observed over the last 

decade compared to the 1990s. The main driver of this pronounced variability has been variations 

in meteorological processes, notably the occurrence of dynamically induced disturbances of the 

Antarctic polar vortex. 

• A small increase of about 10–25 Dobson units (DU) in springtime Antarctic total ozone since 

2000 can be derived by subtracting an estimate of the natural variability from the total ozone 

time series. However, uncertainties in this estimate and in the total ozone measurements preclude 

definitive attribution of this increase to the reduction of ODSs over this period.

• Exceptionally low ozone abundances in the Arctic were observed in spring of 2011. These low 

ozone levels were due to anomalously persistent low temperatures and a strong, isolated polar 

vortex in the lower stratosphere that led to a large extent of halogen-induced chemical ozone 

depletion, and also to atypically weak transport of ozone-rich air into the vortex from lower 

latitudes. State-of-the-art chemical transport models (CTMs), which use observed winds and 

temperatures in the stratosphere together with known chemical processes, successfully reproduce 

the observed ozone concentrations.

Understanding of Polar Ozone Processes

Since the last Assessment, new laboratory measurements have strengthened our knowledge of polar 

ozone loss processes. Simulations using updated and improved models have been tested using the 

wealth of currently available measurements from satellites, ground-based networks, and dedicated 

campaigns.

• CTMs are generally able to reproduce the observed polar chlorine activation by stratospheric 

particles and the rate of the resulting photochemical ozone loss. Since the last Assessment,

better constraint of a key photochemical parameter based on recent laboratory measurements, i.e., 

the ClOOCl (ClO dimer) photolysis cross section, has increased confidence in our ability to 

quantitatively model polar ozone loss processes in CTMs.

• Chemistry-climate models (CCMs), which calculate their own temperature and wind fields, 

do not fully reproduce the range of polar ozone variability. Most CCMs have limitations in 

simulating the temperature variability in polar regions in winter and spring, as well as the temporal 

and spatial variation of the polar vortex.
Chapter 3

3.2

Future Changes in Polar Ozone

Projections of future ozone levels in this Assessment are mainly based on the CCM simulations used 

in the last Assessment. Individual studies using results from climate models provide new insights 

into the effects of carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) on future polar 

ozone levels by the end of this century.

• Arctic and Antarctic ozone abundances are predicted to increase as a result of the expected 

reduction of ODSs. A return to values of ozone in high latitudes similar to those of the 1980s is 

likely during this century, with polar ozone predicted by CCMs to recover about 20 years earlier in 

the Arctic (2025–2035) than in the Antarctic (2045–2060). Updated ODS lifetimes have no 

significant effect on these estimated return dates to 1980 values. 

• During the next few decades, while stratospheric halogens remain elevated, large Arctic ozone 

loss events similar to that observed in spring 2011 would occur again under similar longlasting cold stratospheric conditions. CCM simulations indicate that dynamic variability will lead 

to occasional cold Arctic winters in the stratosphere but show no indication for enhanced frequency 

of their occurrence. 

• Climate change will be an especially important driver for polar ozone change in the second 

half of the 21st century. Increases in CO2 concentrations will lead to a cooling of the stratosphere 

and increases in all greenhouse gases are projected to strengthen the transport of ozone-rich air to 

higher latitudes. Under conditions of low halogen loading both of these changes are anticipated to 

increase polar ozone amounts. The changes are expected to have a larger impact on ozone in the 

Arctic than in the Antarctic due to a larger sensitivity of dynamical processes in the Northern 

Hemisphere to climate change. Polar ozone levels at the end of the century might be affected by 

changing concentrations of N2O and CH4 through their direct impact on atmospheric chemistry. 

The atmospheric concentrations of both of these gases are projected to increase in most future 

scenarios, but these projections are very uncertain. 

• Substantial polar ozone depletion could result from enhancements of sulfuric aerosols in the 

stratosphere during the next few decades when stratospheric halogen levels remain high. 

Such enhancements could result from major volcanic eruptions in the tropics or deliberate 

“geoengineering” efforts. The surface area and number density of aerosol in polar regions are 

important parameters for heterogeneous chemistry and chlorine activation. The impact of sulfur 

dioxide (SO2) injection of either natural or anthropogenic origin on polar ozone depends on the 

halogen loading. In the next several decades, enhanced amounts of sulfuric acid aerosols would 

increase polar ozone depletion. 
Polar Ozone

3.3

3.1 INTRODUCTION

This chapter presents and assesses the latest results from the peer-reviewed literature about our 

knowledge and understanding of the past, present, and future of polar ozone, i.e., in the stratospheric 

region defined from 60° to 90° in both hemispheres. In the last WMO Scientific Assessment of Ozone 

Depletion: 2010 (WMO, 2011), information about polar ozone was distributed in both Chapter 2 

(Stratospheric Ozone and Surface Ultraviolet Radiation) and Chapter 3 (Future Ozone and its Impact on 

Surface UV). The chapter begins with a brief compilation of the main conclusions from the previous 

Assessment and a description of the aims and content of the chapter.

3.1.1 State of Science in 2010

As reported in WMO (2011), the Antarctic ozone hole had continued to appear each spring, in 

spite of a moderate decrease of ozone-depleting substances (ODSs) between 2005 and 2010 (WMO, 

2011). Since 1997 both the depth and magnitude of the Antarctic ozone hole were controlled primarily by 

variations in stratospheric temperature and dynamical processes. In comparison, ozone loss in the Arctic 

winter and spring remained highly variable but in a range comparable to values that have been determined

since the early 1990s. 

WMO (2011) reaffirmed the important role of halogen chemistry in polar ozone depletion. Some 

recent laboratory measurements of the chlorine monoxide dimer (ClOOCl) dissociation cross sections, 

together with analyses of chlorine partitioning from aircraft and satellite observations, had in part 

questioned the fundamental understanding of polar springtime ozone depletion. After further study, the 

earlier measurements of ClOOCl absorption cross section were confirmed and the then more recent study

(Pope et al., 2007) was shown to be incorrect. The dominant role of the catalytic ozone destruction cycle 

in polar springtime ozone depletion, initiated by the ClO + ClO reaction, coupled with a significant 

contribution from the catalytic destruction cycle initiated by the reaction BrO + ClO, was confirmed. The

climatology of polar stratospheric clouds (PSCs) in both polar regions was revisited, based on 

measurements from a new class of satellite instruments that provide daily vortex-wide information on 

PSC formation. The new climatology showed that PSCs over Antarctica occur more frequently in early 

June and less frequently in September than expected based on the previous PSC satellite climatology, 

which was developed from solar occultation instruments.

It was pointed out that numerical calculations constrained to match observed temperatures and 

halogen levels (e.g., with chemical transport models, CTMs) produced Antarctic ozone losses that were 

close to those derived from measured data. Free-running chemistry-climate models (CCMs) simulated

many aspects of the Antarctic ozone hole quite well. However, they did not uniformly reproduce the 

necessary very low temperatures at high southern latitudes, the isolation of polar air masses from middle 

latitudes, the dynamically isolated vortex characterized by strong vertical descent, and high amounts of 

halogens inside the polar vortex. Furthermore, most CCMs underestimated the mean Arctic ozone loss 

that had been derived from observations primarily because the simulated mean northern winter vortices 

were too dynamically disturbed, implying warmer conditions and larger mixing with lower-latitude air 

masses. 

CCM simulations predicted that Antarctic total column ozone values during spring would return 

to pre-1980 levels after the mid-21st century. This was later than estimated in any other region of the 

stratosphere, yet it was earlier than the expected return of stratospheric halogen loading to 1980 values.

The latter finding was explained by the global middle and upper stratospheric cooling due to enhanced 

greenhouse gas (GHG) concentrations (mainly due to carbon dioxide (CO2) increases). This cooling 

induces a slowing down of ozone-destroying gas-phase reactions and an increase in the rate of the 

production of ozone from the pressure-dependent reaction of oxygen atoms with oxygen molecules at 
Chapter 3

3.4

these stratospheric altitudes. Moreover, in most CCMs, GHG-induced changes (including corresponding 

changes of sea surface temperatures) accelerate the stratospheric meridional circulation (the so-called 

Brewer-Dobson circulation, BDC), resulting in a faster decrease in stratospheric halogen loading. 

Nevertheless, it was stated that Antarctic ozone holes could persist up to the end of the 21st century. 

Overall the confidence in the accuracy of our understanding of changes in Antarctic ozone was higher 

than that for other stratospheric regions.

Arctic total column ozone values during spring (March) were projected to return to pre-1980 

levels two to three decades before polar halogen loading returns to 1980 levels. Most CCMs did not

capture the extreme low stratospheric temperatures observed in some winters and, on average, 

underestimated Arctic ozone loss. In summary it was considered possible that this return date was biased 

early. In addition, a strengthening of the BDC through the 21st century leads to increases in springtime 

Arctic column ozone. As a consequence, by 2100, Arctic ozone was projected by models to lie well above 

1980 levels.

3.1.2 Scope of Chapter

This chapter updates the state of our knowledge about ozone in both polar regions from 

measurements and model studies. It focuses on the recent evolution of stratospheric ozone in the winter 

and springtime, compared to changes that occurred in the preceding decades. As about 10–15 years have 

passed since the peak of stratospheric content of ODSs in the polar regions, one important issue is 

whether a decrease of polar ozone depletion has been detected that can unambiguously be attributed to the 

decrease of ODSs in the stratosphere. Recent evolution in polar temperatures and PSC formation are 

discussed, together with improvements in our understanding of chemical and dynamical processes 

influencing polar ozone, especially in the winter and springtime. The most recent projections of 

stratospheric ozone in the polar regions are compiled from global model simulations, based on the 

Chemistry-Climate Model Validation-2 (CCMVal2) exercise (SPARC CCMVal, 2010) and some 

Coupled Model Intercomparison Project Phase 5 (CMIP5) investigations for the Fifth Assessment Report 

(AR5) of the Intergovernmental Panel on Climate Change (IPCC, 2013). The chapter closes with a 

discussion of uncertainties in future polar ozone due to climate change and potential effects of eruptions 

of large volcanoes as well as possible geoengineering activities. 

3.2 RECENT POLAR OZONE CHANGES

3.2.1 Measurements of Ozone and Related Constituents

Over the last three decades, an array of instruments on a number of satellite platforms has 

provided an expansive suite of measurements crucial for understanding the chemical and dynamical 

processes controlling ozone in the polar stratosphere. The last decade in particular was unique in its 

wealth of measurements of many atmospheric constituents of importance in studies of polar processes. 

Table 3A-1 in Appendix 3A summarizes the main satellite data sets of ozone, related trace gases, 

aerosols, and clouds of particular relevance for the polar regions.

It is worth noting that many of the instruments listed here are no longer operational, and others 

have exceeded their planned mission lifetimes. Table 3A-1 focuses exclusively on satellite measurements 

that have been or can be useful in polar studies; information about other available space-based ozone data 

sets can be found in Chapter 2 of this Assessment. Chapter 2 also includes discussion of long-term 

merged and/or homogenized ozone data records and climatologies, which are not covered here. General 

overviews of satellite ozone profile measurements are also given by Tegtmeier et al. (2013) and Hassler et 

al. (2013).

In addition to the satellite observing systems listed in Table 3A-1, several ground-based networks 

and other stations provide measurements of ozone and related constituents in the polar regions. 
Polar Ozone

3.5

Information on NDACC (Network for Detection of Atmospheric Composition Change, http://

www.ndsc.ncep.noaa.gov/) measurements and other data sets archived at the World Ozone and 

Ultraviolet Data Centre (WOUDC) is provided in Chapter 2.

3.2.2 Recent Evolution of Polar Temperatures and Vortex Characteristics

3.2.2.1 POLAR TEMPERATURES

The annual climatological cycle (1979–2012) of 50 hPa polar minimum temperature is illustrated 

for the Arctic and Antarctic in Figure 3-1. The 50 hPa polar minimum temperatures during recent winters 

are highlighted by the colored lines in Figure 3-1, along with the Arctic 1996–97 polar minimum 

temperature. 

Arctic minimum temperatures show considerable year-to-year variations. Recent Arctic winter 

variability has included new minimum temperatures during spring 2011, a time during which significant 

ozone depletion occurred (Manney et al., 2011; Pommereau et al., 2013). These low temperatures were 

associated with a small and strong polar 

vortex, low planetary wave activity, and weak 

meridional transport to high latitudes, as well 

as a relatively late final warming date 

(Hurwitz et al., 2011; Isaksen et al., 2012; 

Strahan et al., 2013). High stratospheric temperatures during some Arctic winters are due to 

the occurrence of sudden stratospheric warmings (SSWs), which are characterized by the 

reversal of the meridional temperature gradient.

Figure 3-1. The annual cycle and variability at 

50 hPa of minimum temperature for the Northern Hemisphere (50°N–90°N, top) and the 

Southern Hemisphere (50°S–90°S, bottom) from 

MERRA reanalysis data (Rienecker et al., 

2011). The thick black line shows the climatological mean annual cycle; the light and dark 

gray shading indicate the 30–70% and 10–

90% probabilities, respectively; and the thin 

black lines indicate the record maximum and 

minimum values, all for the period 1978/79–

2012/13 (Northern Hemisphere) and 1979–2012 

(Southern Hemisphere). The thresholds for 

chlorine activation (see Section 3.3, Box 3-1) 

and ice PSC formation are indicated by the 

green lines. Recent winters are highlighted by

the colored lines, along with Northern Hemisphere winter 1996–97. Updated from Figure 

4-1 in WMO (2007) with MERRA data sourced

from ozonewatch.gsfc.nasa.gov.
Chapter 3

3.6

For major SSWs, the 10 hPa zonal mean zonal wind at 60°N changes from westerly to easterly 

(Labitzke and Naujokat, 2000). Section 3.2.3.2 describes in detail the meteorological and chemical 

conditions leading to the severe ozone loss in the Arctic in 2011.

Recent 50 hPa Antarctic polar minimum temperatures have been lower than the climatological 

mean (1979–2012) during winter and September (Figure 3-1). In October and November 2012, the 

minimum temperatures at 50 hPa were higher than during other recent years. As emphasized in Section 

3.2.4, the 2012 ozone hole was significantly weaker than the 1990–2011 average due to the strong 

springtime planetary-wave forcing that year, which raised the polar mean temperature (Newman et al., 

2013). In contrast, 50 hPa minimum temperatures in 2011 were lower as a result of relatively weak winter 

and spring planetary wave forcing (Newman et al., 2012). Planetary wave activity also adiabatically 

warmed the stratosphere in July and September 2010 (Newman et al., 2011; de Laat and van Weele, 2011; 

Klekociuk et al., 2011).

3.2.2.2 POLAR VORTEX BREAKUP DATES

The polar vortex decays and then finally breaks up during spring due to the warming of the polar 

stratosphere by the returning sun and forcing by planetary waves, which decelerate the winds in the jet 

and further warm the polar stratosphere. The date on which the vortex breaks up is calculated from a wind 

average along the vortex edge (Nash et al., 1996). The first decade of the 21st century was characterized 

by major stratospheric sudden warmings during several Arctic winters (Manney et al., 2005; WMO, 2007; 

Manney et al., 2009; Ayarzagüena et al., 2011) and the date of final Arctic warming exhibited larger 

interannual variability in the 2000s than in the 1990s (Figure 3-2). Since the last Ozone Assessment in 

2010, the Antarctic vortex has continued to break up in November and December. The presence of the 

Antarctic ozone hole has resulted in a delay in the 

breakup date in recent decades, consistent with a 

vortex intensification following additional springtime 

radiative cooling (e.g., Waugh et al., 1999; 

Langematz and Kunze, 2006). However, interannual 

variability in the date of the Antarctic breakup is 

visible in Figure 3-2; for example, the 2012 vortex 

broke up several weeks earlier than in other recent 

years. The variability in the Antarctic breakup date is 

most likely due to meteorological variability rather 

than being a sign of a trend.

Figure 3-2. The Arctic (top) and Antarctic (bottom) 

vortex breakup dates on the 500 K isentropic surface 

following Nash et al. (1996). NCEP (Kalnay et al., 

1996); MERRA (Rienecker et al., 2011) and ERAInterim (Dee et al., 2011) reanalyses are used to 

calculate these dates. Updated from Figure 4-4 in 

WMO (2007).
Polar Ozone

3.7

3.2.2.3 LONG-TERM EVOLUTION OF PSC VOLUME

The volume of air inside the vortex at temperatures below the nitric acid trihydrate (NAT) polar 

stratospheric cloud (PSC) formation threshold, referred to as VPSC, is a commonly used diagnostic for 

multidecadal polar ozone depletion studies. This NAT PSC formation threshold is defined using a 

standard, non-denitrified profile of nitric acid (HNO3) (Rex et al., 2003). Thus VPSC is a temperature 

threshold (dependent on altitude) rather than a PSC threshold. The volume of air with temperature below 

this threshold, VPSC, is a proxy for ozone loss (Rex et al., 2003). VPSC is calculated using radiosonde data 

as well as reanalyses, thus investigation of the long-term evolution of Arctic PSC volumes must account 

for changes in the data sources with time. Radiosondes provide the longest data record, however, the use 

of their data for analyzing long-term evolution requires a careful account of the non-homogenized nature 

of the radiosondes. Non-homogenized radiosonde data overestimate stratospheric cooling trends when 

compared with homogenized data and furthermore there are large uncertainties between different 

homogenization approaches (Randel et al., 2009). Besides, the observational coverage of radiosondes has 

changed with time. The Freie University (FU-Berlin) analyses are based solely on radiosonde 

measurements over the period 1967–2001, although they are not objectively homogenized with respect to 

the station network. Radiosondes are more likely to capture temperature extremes than satellite 

radiometers due to the coarse vertical integration of the latter (e.g., Pawson et al., 1999). In the satellite 

era (post 1979), reanalyses incorporate observations in the lower stratosphere from the Microwave 

Sounding Unit (MSU), which make them more reliable in the stratosphere. There is some long-term drift 

of stratospheric temperatures in reanalyses but it is less severe in more recent reanalyses. Due to 

differences in data assimilation, individual reanalysis should not be combined with each other or with 

other observational data sets, in order to avoid inconsistencies in the records used for variability analysis. 

Using both FU-Berlin soundings and European Centre for Medium-Range Forecasts (ECMWF)

analyses, Rex et al. (2004, 2006) found that during the time period since 1965, recent decades showed

larger extreme values of VPSC than earlier decades, i.e., cold Arctic stratospheric winters have become 

colder. Cold winters were defined by Rex et al. (2004) as the coldest winter in each 5-year interval. This 

trend result was statistically significant at the 99% level. For the shorter period since 1979, Rieder and 

Polvani (2013) used three reanalyses (MERRA, NCEP, ERA-Interim) to calculate VPSC and demonstrated 

the high correlation among the three reanalysis. Using a different definition of extreme VPSC, they found 

that in these reanalyses, increases in maximum values of VPSC are not statistically significant at the 95% 

confidence level; however, they are significant at the 80–93% level (varying for each reanalysis). Using 

ERA-Interim data, Pommereau et al. (2013) reported high variability but no trend in total sunlit VPSC (i.e.,

PSC volume in sunlight) between 1994 and 2012. Thus, recent research has made conclusions of larger 

extreme VPSC values in the coldest Arctic winters in recent decades less certain than it was stated in the 

previous Assessment (WMO, 2011). Individual winters clearly exhibit extremely cold conditions, leading 

to large values of VPSC. This interannual variability is illustrated clearly in Figure 3-3, which combines 

results from several published time series of both Arctic VPSC and VPSC divided by the volume of the polar 

vortex, calculated using MERRA, NCEP, ERA-Interim reanalyses and FU-Berlin radiosondes (update 

from Rex et al., 2006, based on new reanalysis products). VPSC is an absolute measure of the area affected 

by polar ozone loss and thus related to the absolute amount of ozone destruction. The fraction of the 

vortex area below the VPSC temperature threshold, VPSC/Vvortex, is a proxy for chemical processing in the 

polar vortex, and thus particularly important for the Arctic, where a large interannual variability of the 

vortex is observed (Tilmes et al., 2006). Cold extreme conditions in the Arctic are likely related to the 

absence of sudden stratospheric warmings in some winters and are likely to continue to occur in the 

future. Whether there is a long-term trend in extreme values of the derived VPSC time series depends upon 

the specific definition of an extreme and, given the short observational record, further extreme-value 

analysis is warranted.
Chapter 3

3.8

Figure 3-3. Arctic VPSC (top) and VPSC

divided by the volume of the polar 

vortex (bottom), based on different 

meteorological reanalyses: ECMWF 

ERA-Interim (orange line), MERRA 

(green line), NCEP (black line), and 

FU-Berlin (red line). Update from Rex 

et al. (2006) based on new reanalysis 

products.

3.2.3 Ozone Depletion in Recent Arctic Winters

The recent evolution of polar ozone is shown in Figure 3-4, which represents the springtime 

average of total ozone poleward of 63° geographic latitude in the Arctic and Antarctic, derived from 

satellite measurements. The gray shading in the figure highlights the difference between the average total 

ozone values computed over the period 1970–1982 (represented by the horizontal black lines) and the 

ozone abundances observed in individual years. Such a figure has been featured in the last several 

WMO/UNEP Ozone Assessments. However, because the size, shape, position, and breakup date of the 

Arctic vortex are highly variable, the March polar-cap averages depicted in Figure 3-4 reflect differing 

amounts of extravortex air (which may have higher or lower total ozone abundances than those inside the 

vortex in any given year, depending primarily on the relationship between the vortex and the cold region, 

which are often not concentric). Alternatively, Figure 3-5 shows the minimum of the daily average total 

ozone within the 63° contour of equivalent latitude, which more closely follows the position of the polar 

vortex. Arctic winters with early final warmings, for which March mean total ozone values convey little 

information about ozone loss, are excluded from the time series (as indicated by the dotted segments of 

the line in the top panel of the figure). As for Figure 3-4, interpretation of Figure 3-5 is complicated by 

the fact that dynamically induced low total ozone abundances are strongly spatially correlated with the 

cold region in the lower stratosphere and not necessarily with the vortex (e.g., Petzoldt, 1999); thus in the 

Arctic, because dynamical effects almost always dominate over chemical destruction, both high and low 

column values are included in the means in Figures 3-4 and 3-5. Moreover, Figure 3-5 only partially 

alleviates the issue of mixing vortex and extravortex air, because the area encompassed within the 63° 

contour of equivalent latitude is a constant, whereas the size of the vortex varies over the course of the 

month and from year to year. The very low total ozone in the Arctic spring of 2011 stands out in both 

figures. However, as column ozone is strongly influenced by both chemical destruction and transport 

effects (e.g., Tegtmeier et al., 2008), it is not possible to diagnose the degree of chemical loss from 

inspection of the total ozone values in Figure 3-4 or Figure 3-5 alone. That the Arctic vortex was smaller 

than usual in March 2011 (Manney et al., 2011) further complicates interpretation of that average polar
Polar Ozone

3.9

Figure 3-4. Total ozone average 

(Dobson units) over 63°-90° latitude 

in March (Northern Hemisphere, NH) 

and October (Southern Hemisphere, 

SH). Symbols indicate the satellite 

data that have been used in different 

years. The horizontal gray lines 

represent the average total ozone for 

the years prior to 1983 in March for 

the NH and in October for the SH. 

Updated from Figure 2-8, WMO 

(2011).

Figure 3-5. Time series of the minimum of the 

daily average column ozone (Dobson units) 

within the 63° contour of equivalent latitude

(Φe) in March in the Arctic and October in the 

Antarctic. Arctic winters in which the polar 

vortex broke up before March (1987, 1999, 

2001, 2006, 2009, and 2013) are shown by 

open symbols; dotted lines connect surrounding years. Figure adapted from Müller et 

al. (2008) and WMO (2011), updated using the 

Bodeker Scientific combined total column 

ozone database (version 2.8; circles) through 

the Arctic winter of 2012, and Aura OMI 

measurements thereafter (diamonds).

cap total ozone value relative to those in other cold years. Ozone loss in the 2010/2011 Arctic 

winter/spring is discussed in detail in Section 3.2.3.2.

With the present availability of satellite stratospheric measurements, the extent of polar ozone 

destruction processes during the winter can be evaluated from the evolution of key species involved in 

those processes, such as hydrogen chloride (HCl), chlorine monoxide (ClO), and nitric acid (HNO3), in 

addition to ozone. Decreases in gas-phase HNO3 are indicative of the formation of PSCs, while decreases 

in HCl and increases in ClO signify the occurrence of chlorine activation through heterogeneous reactions 

on PSC particles and/or cold binary aerosols (see Section 3.3.1). Figure 3-6 (discussed in more detail 

below) shows the vortex-averaged evolution of these key constituents at a representative level in the 

lower stratosphere during the last four Arctic winters, as measured by the Microwave Limb Sounder 

(MLS) instrument onboard NASA’s Aura satellite. The envelope of behavior over the 2005–2009 period 

is also shown for comparison.
Chapter 3

3.10

3.2.3.1 OZONE DEPLETION IN THE ARCTIC WINTERS OF 2009/2010, 2011/2012, AND 2012/2013

The meteorology of the wintertime Arctic lower stratosphere is characterized by substantial 

interannual variability. Although all recent winters had at least brief intervals cold enough for chlorine 

activation, they were also, with the exception of 2010/2011, marked by considerable intraseasonal 

variations in temperature (Figure 3-1) and in the size, strength, and persistence of the polar vortex (Figure 

3-2), conditions that govern the cumulative amount of chemical ozone loss. The 2009/2010 early winter 

was extremely cold with unusually extensive PSC formation, including a rare outbreak of synoptic-scale 

ice PSCs in mid-January 2010 (Pitts et al., 2011; Dörnbrack et al., 2012). The vortex was shifted off the 

pole during the midwinter cold spell, allowing greater exposure to sunlight than usual and hence 

prompting intense chlorine activation (Figure 3-6), which induced a moderate degree of ozone loss 

(Kuttippurath et al., 2010b; Wohltmann et al., 2013) prior to the onset of a major SSW in February 2010

Figure 3-6. Time series of vortex-averaged HNO3, HCl, ClO, and O3 from Aura Microwave Limb Sounder 

(MLS) on the 485 K potential temperature surface (~18 km, ~50 hPa) for winters in the Arctic (left panels) 

and Antarctic (right panels). Gray shading shows the envelope of behavior observed by Aura MLS over 

the 2005–2009 period. The last four winters are highlighted by colored lines as indicated in the legend (for 

the Arctic, the year given refers to the spring). An instrument anomaly caused Aura MLS operations to be 

suspended from 27 March to 20 April 2011; dotted red lines have been used to fill the resulting data gap 

to guide the eye. Purple triangles on Arctic panels show 1996/1997 values from UARS MLS. Updated 

from Manney et al. (2011).

Arctic

2

4

6

8

10

12

14

HNO3 / ppbv

0.0

0.5

1.0

1.5

2.0

2.5

HCl / ppbv

0.0

0.2

0.4

0.6

0.8

1.0

1.2

ClO / ppbv

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

O3 / ppmv

1 Dec 1 Jan 1 Feb 1 Mar 1 Apr

Antarctic

2010

2011

2012

2013

1 Jun 1 Jul 1 Aug 1 Sep 1 Oct
Polar Ozone

3.11

(Kuttippurath and Nikulin, 2012). Similarly, the 2011/2012 and 2012/2013 winters were characterized by 

low minimum temperatures in December that triggered PSC formation and chlorine activation. In late 

January 2012, a strong SSW (Chandran et al., 2013) halted further chemical processing. In December 

2012 and January 2013, the vortex was again substantially shifted off the pole, ClO was strongly 

enhanced, and ozone abundances dropped (Figure 3-6). However, temperatures rose abruptly to nearrecord values in early January as a very strong and prolonged SSW began (Goncharenko et al., 2013). As 

a result, chlorine deactivation by early February 2013 precluded the exceptional loss that can occur when 

low temperatures persist into spring.

3.2.3.2 OZONE DEPLETION IN THE ARCTIC WINTER 2010/2011

The Arctic winter/spring of 2010/2011 has been widely studied. It was characterized by an 

unprecedented degree of chemical ozone loss, coupled with atypically weak transport of ozone to the 

lower stratospheric polar vortex, which led to exceptionally low values of springtime total ozone (Figures 

3-4, 3-5, and 3-8). It must be emphasized, however, that the occurrence of this extreme event has not 

challenged our fundamental understanding of the processes controlling polar ozone. Unusual (for the 

Arctic) meteorological conditions in 2010/2011 resulted in record-low ozone through known chemical 

and dynamical mechanisms. If similar conditions were to arise again in the Arctic while stratospheric 

chlorine loading remains high, similarly severe chemical ozone loss would take place. Uncertainties in 

current climate models preclude confident quantification of the likelihood of repeated episodes of 

extensive Arctic ozone depletion in the present or future climate (e.g., Charlton-Perez et al., 2010; Garcia, 

2011), as discussed in Section 3.5.

In spring 2011, the transport barrier at the edge of the lower stratospheric polar vortex was the 

strongest (in either hemisphere) in the previous 32 years (Manney et al., 2011). Unusually weak 

tropospheric planetary wave driving allowed the vortex to remain strong, stable, and cold for an extended 

period, with its mid-April breakup date one of the latest in the satellite era. The mechanisms responsible 

for the weak wave activity in 2011 have not been definitively determined but may be related to high sea 

surface temperatures in the North Pacific (Hurwitz et al., 2011; Section 3.3.3.2). Recent analyses suggest 

that the atypically high frequency of extreme total negative eddy heat flux events and the absence of 

extreme positive events at 50 hPa during spring 2011 may have contributed to weakened downward 

transport, cooling, and strengthening of the Arctic lower stratospheric vortex, and a delayed final 

warming (Shaw and Perlwitz, 2014). Daily minimum temperatures were only moderately low (i.e., rarely 

below ice PSC formation thresholds), but the cold region was uncommonly long lasting and vertically 

extensive, leading to a winter-mean vortex fractional volume of air with the potential for PSC formation 

that was the largest ever observed in the Arctic (Manney et al., 2011), and a March Arctic polar cap 

temperature at 50 hPa more than two standard deviations below the climatological mean (Hurwitz et al., 

2011). The persistence of a strong, cold vortex for more than three months (from December through the 

end of March) is typical in the Antarctic but unique in the observational record in the Arctic (Manney et 

al., 2011).

Consistent with the temperature distribution, ice PSCs were rare, but other PSCs types (see Box 

3-1, p. 3.17) were abundant until mid-March (Arnone et al., 2012; Lindenmaier et al., 2012). CALIPSO 

data show that not only were PSCs present far later in 2011 than is typical in the Arctic, but they also 

spanned a vertical range comparable to that in the Antarctic (Manney et al., 2011). Widespread and 

persistent PSCs led to severely depleted gas-phase HNO3 (Figure 3-6). That HNO3 mixing ratios remained 

much lower than observed in any previous Arctic winter well after the last PSCs had dissipated is evidence 

for the occurrence of considerable denitrification (Sinnhuber et al., 2011; Kuttippurath et al., 2012).

The persistent low temperatures supported extensive chlorine activation on the surfaces of PSC 

particles and/or cold binary aerosols. Although some chlorine activation has occurred in all recent Arctic 

winters, it has never been as prolonged or as intense as that in 2011, when vortex-averaged ClO values 

exceeded the range previously observed in the Arctic from late February through March (Manney et al., 
Chapter 3

3.12

2011). In addition, very low values of chlorine nitrate (ClONO2) (Sinnhuber et al., 2011; Arnone et al., 

2012; Lindenmaier et al., 2012) and HCl (Figure 3-6) were observed in the vortex in March. In contrast to 

previous cold Arctic winters, when chlorine deactivation had already been completed by mid-March, in 

2011 ClO began decreasing rapidly only about a week earlier than is typical in the corresponding season 

in the Antarctic (Figure 3-6). For the ozone and odd nitrogen abundances normally found in the Arctic, 

the primary chlorine deactivation mechanism is the reformation of ClONO2, whereas under the severely 

denitrified and ozone-depleted conditions characteristic of the Antarctic ozone hole, production of 

ClONO2 is suppressed and that of HCl favored. Figure 3-6 shows that chlorine was initially repartitioned 

into HCl to a greater (more Antarctic-like) extent than typical in the Arctic, suggesting that denitrification 

and low ozone abundances may have inhibited ClONO2 reformation to some extent (Manney et al., 2011; 

Arnone et al., 2012; Lindenmaier et al., 2012). Nevertheless, the steep rise in ClONO2 associated with the 

decline in ClO after mid-March indicates that deactivation did occur predominantly into that reservoir 

even in 2011 (Sinnhuber et al., 2011; Arnone et al., 2012).

The meteorological conditions (persistent low temperatures inside a strong, isolated polar vortex), 

consequent chlorine activation, and denitrification in the 2011 Arctic vortex led to severe chemical ozone 

destruction between 16 and 22 km altitude (Figure 3-7), with 60–80% of the vortex ozone at ~18–20 km 

removed by early April (Manney et al., 2011; Sinnhuber et al., 2011). Because of the delayed chlorine 

deactivation, lower stratospheric ozone loss rates in March 2011 reached over 4 parts per billion by 

volume (ppbv) per sunlit hour (Kuttippurath et al., 2012) or 0.7%/d (Pommereau et al., 2013), larger than 

previously observed in mid-March in the Arctic and similar to those routinely seen in September in the 

Antarctic. Peak chemical ozone loss had been as large in some previous cold Arctic winters (e.g., the 

winters of 2000 and 2005; Manney et al., 2011), but significant loss extended over a much broader 

altitude region in 2011 (Manney et al., 2011). In addition to chemical ozone destruction, unusually weak 

diabatic descent and wave-driven horizontal transport also played major roles in 2011, with the late final 

warming delaying influx of ozone-rich air into the polar lower stratosphere (Hurwitz et al., 2011; Isaksen 

et al., 2012; Strahan et al., 2013). Although CTM studies consistently show that the exceptionally low

Figure 3-7. Profiles of observed vortex-average 

chemical ozone loss from the cold Arctic winter/spring 

periods of 1997 and 2011 derived from ozonesondes. 

Note that significant differences (up to ~0.4 parts per 

million by volume (ppmv) at the end of March 2011) in 

ozone loss estimates for a given year derived from 

various methods and data sets imply some uncertainty 

in the chemical loss determination. However, year-toyear differences in the amount of ozone loss obtained 

from any given method/data set combination are very 

similar, indicating a high degree of precision in the 

relative amount of calculated loss between different 

years and hemispheres. Also shown is an indicative 

range of ozone loss for typical Antarctic winter/spring 

periods, illustrated by the loss that has been derived 

from ozone observations for a relatively weak early 

Antarctic ozone hole (1985, upper limit of the gray 

shading) and the loss in a strong Antarctic ozone hole 

(2003, lower limit of the gray shading). Error bars show 

uncertainty estimates of the derived ozone losses 

based on a methodology described in Harris et al. 

(2002). Figure adapted from Manney et al. (2011). 
Polar Ozone

3.13

ozone abundances in spring 2011 were brought about by both extreme chemical loss and weak 

dynamical resupply, they disagree on the relative contributions of the two factors, with Isaksen et al. 

(2012) attributing roughly 25% of the observed ozone column anomaly to chemistry and the rest to 

transport effects, whereas Strahan et al. (2013) found chemical and transport effects to contribute equally.

Together, the anomalous chemical and meteorological conditions induced record-low ozone in 

March 2011, as characterized by a variety of metrics. Sinnhuber et al. (2011) reported Michelson 

Interferometer for Passive Atmospheric Sounding (MIPAS) measurements showing that vortex-averaged 

ozone at 475 K decreased from ~3 parts per million by volume (ppmv) in early December to ~1.5 ppmv 

in early April, in good agreement with the MLS measurements shown at 485 K in Figure 3-6. Using 

Ozone Monitoring Instrument (OMI) data, Manney et al. (2011) calculated that the fraction of the Arctic 

vortex in March with total ozone less than 275 Dobson units (DU), typically near zero, reached nearly 

45% in 2011 (see also Figure 3-8); minimum vortex total ozone values were continuously below 250 DU 

for 27 days. Integrated over the column, the 2011 Arctic ozone “deficit” (the difference between the daily 

total ozone amount from OMI and a reference value minimally affected by chemical ozone loss) was 

comparable to that in the Antarctic vortex core in recent years (Figure 3-8; Manney et al., 2011). 

Similarly, column ozone measurements from UV-visible spectrometers located in eight Systèmes 

d’Analyse par Observation Zénithale (SAOZ)/NDACC stations distributed around the Arctic indicate a 

reduction in total ozone of ~38% (170 DU) by late March 2011, the largest in the SAOZ record dating 

back to 1994 and comparable to that in the 2002 Antarctic winter (Pommereau et al., 2013). Groundbased measurements at the Polar Environment Atmospheric Research Laboratory (PEARL) at Eureka, 

Canada, also registered the lowest ozone columns in their 11-year record, 237–247 DU, when the vortex 

was overhead in mid-March (Adams et al., 2012). On the basis of the long-term total ozone data set 

updated from Stolarski and Frith (2006), in 2011 March total ozone averaged over the 60–80°N region 

was the lowest of the satellite era (Hurwitz et al., 2011; see also Figure 3-4). Similarly, record-low zonal 

mean (60–90°N) column ozone values, reaching as low as ~310 DU in mid-March, were seen in Global 

Ozone Monitoring Experiment 2 (GOME-2) data (Balis et al., 2011; Isaksen et al., 2012).

It is important to emphasize that because downward transport in the winter polar vortex is stronger 

in the Arctic, background ozone levels are ~100 DU higher there than in the Antarctic (e.g., Tegtmeier et 

al., 2008). As a result, although the evolution of Arctic ozone and related constituents in spring 2011 more 

closely followed that characteristic of the Antarctic than ever before, the springtime total ozone values 

remained considerably higher than those reached in a typical year in the Antarctic (Figures 3-4, 3-5, and 3-

8). Moreover, ozone loss in cold and prolonged Antarctic winters is substantially greater throughout the 

profile (Figure 3-7). Finally, because the areal extent of the 2011 Arctic vortex was only ~60% the size of a 

typical Antarctic vortex, the low-ozone region was more spatially confined (Figure 3-8).

Figure 3-8. Maps of total column ozone from 

Aura Ozone Monitoring Instrument (OMI) (top 

row) and ozone “deficit” (bottom row) for the 

Arctic (left) and Antarctic (right). Total ozone 

deficit is defined as the difference between daily 

values and a reference total ozone field 

minimally affected by chemical loss. Overlaid 

black contours mark the size and shape of the 

polar vortex on the 460 K potential temperature 

surface. Adapted from Manney et al. (2011).

26 Mar 2011 26 Sep 2010

280

320

360

400

440

Column O3 (DU)

26 Mar 2011 26 Sep 2010

-110

-70

-30

10

50

Column Deficit (DU)
Chapter 3

3.14

3.2.3.3 TWO ARCTIC SPRINGS WITH VERY LOW TOTAL OZONE: 1997 AND 2011

Figure 3-4 shows that March polar-cap average total ozone abundances were comparably low in 

1997 and 2011, and much lower than those in any other year in the satellite record. Similarly, Figure 3-5

shows that the minimum daily mean ozone column amount reached in March was very low in both 1997 

and 2011, although in this view 2000 was also an exceptional year, and the 1997 value is not as striking. 

As discussed in Section 3.2.3.2, an unprecedented degree of chemical ozone loss took place in 2011, 

whereas only moderate chemical ozone loss occurred in 1997 (Manney et al., 1997; Tegtmeier et al., 

2008). In fact, chemical loss also was more severe in the Arctic springs of 1996 and 2005 than in 1997 

(WMO, 2007; Manney et al., 2011; Pommereau et al., 2013), yet those years show larger March average 

total ozone in both Figures 3-4 and 3-5. That the March total ozone values in these two years are so 

similar reflects how strongly Arctic column ozone is influenced by dynamical effects (e.g., Petzoldt, 

1999; Tegtmeier et al., 2008). Here, the chemical and dynamical conditions in the two years are compared 

and contrasted to underline the fact that total ozone abundances cannot by themselves be used as a proxy 

for quantifying chemical loss in the lower stratosphere.

Similarities between 1997 and 2011:

• The polar stratospheric chlorine burden peaked in the period 2000–2002 and has been declining 

slowly since then (WMO, 2011; see also Chapter 1); thus the amount of total inorganic chlorine 

available was approximately the same in the two years.

• Lower stratospheric temperatures below the threshold associated with chlorine activation on PSC 

particles and/or cold binary aerosols (see Section 3.3.1) persisted through March in both years (Coy et 

al., 1997; Manney et al., 2011; Figure 3-1), prolonging the potential for heterogeneous processing into 

a period of greater exposure to sunlight than in more typical years.

• The lower stratospheric vortices were unusually persistent into the spring, consistent with abnormal 

patterns of total eddy heat fluxes at 50 hPa (Shaw and Perlwitz, 2014); as a result, vortex breakup 

dates in both years were among the latest on record, delaying dynamical resupply of ozone to 

northern high latitudes and keeping March total ozone abundances anomalously low (Hurwitz et al., 

2011; Isaksen et al., 2012; Strahan et al., 2013).

Differences between 1997 and 2011:

• The transport barrier at the edge of the 2011 Arctic vortex was unusually strong throughout the winter 

(the strongest on record during February and March), whereas the 1997 vortex was among the 

weakest until February, and near average strength thereafter (Manney et al., 2011).

• Lower stratospheric minimum temperatures were continuously below the threshold for chlorine 

activation (through heterogeneous reactions on PSC particles and/or cold binary aerosol; see Section 

3.3.1) from mid-December through March in 2011 (Manney et al., 2011), whereas they did not drop 

significantly below that threshold until mid-January in 1997 (Coy et al., 1997; Figure 3-1)

• Temperatures persistently (for more than 100 days) below the chlorine activation threshold covered a 

larger vertical domain in 2011 than in 1997 (15–23 km vs. 20–23 km), with a consequently broader 

range of ClO enhancement as well as larger maximum ClO abundances, especially at lower altitudes 

(Manney et al., 2011).

• Early-winter cold conditions and chlorine activation prompted ozone destruction, resulting in ~0.7–

0.8 ppmv less O3 at lower stratospheric levels by March in 2011 than in 1997 (Figure 3-6).

• The persistent cold in 2011 led to extensive PSC formation and severe denitrification (Sinnhuber et 

al., 2011; Arnone et al., 2012; Lindenmaier et al., 2012), with ~4 ppbv less HNO3 at lower 

stratospheric levels by March in 2011 than in 1997 (Figure 3-6).

• Denitrification delayed chlorine deactivation in 2011, when ClO started to decline rapidly only in 

mid-March (Figure 3-6), compared to late February in 1997 (Santee et al., 1997); the late onset of 

chlorine deactivation allowed ozone loss rates in March 2011 to reach values typical in the Antarctic 
Polar Ozone

3.15

at an equivalent time but not observed previously in the Arctic at this period of time (Kuttippurath et 

al., 2012; Pommereau et al., 2013).

• Photochemical box model results suggest that by prolonging the period of rapid springtime ozone 

destruction, denitrification caused an additional 0.6 ppmv of loss in March and April 2011 (Manney 

et al., 2011).

• Together, the early-winter loss and greater springtime loss induced by denitrification roughly account 

for the ~1.5 ppmv lower ozone observed in the lower stratosphere in 2011 than in 1997 (Manney et 

al., 2011).

In summary, anomalous meteorological conditions played a large role in bringing about low total 

ozone in the Arctic springs of both 1997 and 2011. Chlorine-catalyzed ozone destruction was much 

greater in 2011 than in 1997. Although a cold polar vortex persisted into April in both years, chemical 

loss as severe as that in 2011 requires additional conditions that did not occur in 1997, namely: 

temperatures low enough to trigger chlorine activation early in winter, and cold regions extensive enough 

to allow widespread denitrification before March. Even in 2011, however, denitrification was not so 

severe and vertically extensive as to allow ozone destruction on the scale typically seen in Antarctica over 

a large altitude range (e.g., Manney et al., 2011; Arnone et al., 2012; Solomon et al., 2014).

3.2.4 Recent Antarctic Winters

The Antarctic winters of 2010, 2012, and 2013 were on average characterized by larger ozone 

columns than has been typical for the Antarctic stratosphere since the early 1990s (Figure 3-4). The ozone 

mass deficits (OMD) during those years were approximately one-third smaller than during most years of 

the 2000s, and losses were close to half of the maximum recorded OMD in 2006 (based on the Multi 

Sensor Reanalysis (MSR) total ozone data set, following de Laat and van Weele, 2011). In contrast, in 

2011 the reduction of springtime Antarctic ozone columns was more typical of that observed in the 2000s.

The 2010 Antarctic vortex was characterized by a midwinter (mid-July) minor SSW, which 

increased the descending motion within the polar vortex (a minor SSW is a warming not accompanied by 

a 10 hPa zonal wind reversal around 65oS). Correspondingly, VPSC, the potential NAT volume (see 

Section 3.2.2.3) based on MERRA reanalysis data remained well below the 1979–2012 average and less 

denitrification than typical occurred during the Antarctic winter of 2010. The SSW penetrated down to 50 

hPa. The average temperature between 60o-90oS around 30 hPa rose by approximately 5–10 K from 190 

K to 195–200 K and thus above the threshold temperature for efficient heterogeneous chlorine activation. 

As a result, in 2010 photochemical springtime ozone destruction around 30 hPa became less effective. 

Combined with a late onset of ozone depletion around 30 hPa within the vortex which occurred two to 

four weeks later than typical during the last decade (de Laat and van Weele, 2011; Klekociuk et al., 2011) 

ozone columns throughout the 2010 Antarctic spring remained larger than what has been typical for the 

2000s. Note that, as midlatitude wave activity remained weak during the rest of the winter and spring, the 

vortex remained stable into December.

The occurrence of an Antarctic ozone hole with much less ozone loss is not without precedent. 

Other years that have shown less than typical (for the period) Antarctic ozone loss are 1986, 1988, 2002, 

and 2004. It has long been established that the much lower ozone loss during these years compared to 

previous years is related to above-average wave activity (e.g., Schoeberl et al., 1989; Kanzawa and 

Kawaguchi, 1990; WMO, 2007). Furthermore, it is well documented that this reduction occurred at 

altitudes between approximately 20 and 25 km (Hofmann et al., 1997; Hoppel et al., 2005), above the 15–

20 km layer typically associated with complete ozone destruction.

Using trace gas measurements from Aura MLS, de Laat and van Weele (2011) showed that the 

primary cause of the smaller ozone loss in 2004 and 2010 was a change in chemistry triggered by vortex 

dynamics. Enhanced midlatitude wave activity induced SSWs during the Antarctic winter (July–August). 

Although the amplitude of these minor warmings is small in an absolute sense—only a few degrees 
Chapter 3

3.16

Kelvin at maximum and not comparable to the magnitude of sudden warmings seen in the Arctic—they 

nevertheless strongly inhibit the formation of PSCs at altitudes between 20 and 25 km where temperatures 

are close to PSC formation thresholds. The reduced PSC formation limits denitrification and dehydration 

as seen in water vapor and nitric acid measurements from MLS. Due to this pre-conditioning, once 

sunlight returns to the Antarctic stratosphere from mid-August onward, reduced availability of active 

halogen lessens the efficiency of catalytic ozone destruction.

In 2011, stratospheric temperatures during Austral winter and spring remained persistently lower 

than the long-term mean and on average close to the lowest stratospheric temperatures seen since 1979 

throughout, with only a single small warming period during midwinter. Estimates of the potential NAT 

volume in 2011 were well above its climatological mean, and ozone destruction was not reduced.

In 2012, meteorological conditions to some extent mimicked those in 2010, i.e., in early winter 

(late June) a minor SSW occurred, which reduced the potential NAT volume and preconditioned the 

Antarctic lower stratosphere for less ozone depletion. However, the 2012 winter SSW was not as 

pronounced as that in 2010. On the other hand, in contrast to 2010, springtime 2012 was characterized by 

several minor SSWs. As a result, stratospheric temperatures between 10 to 50 hPa remained above the 

long-term climatological mean. These minor warmings were indicative of a less stable vortex, which led 

to an early dissipation of the Antarctic vortex halfway through October (Kramarova et al., 2014). This 

explains the relatively large total ozone column values in October 2012 in Figures 3-4 and 3-5.

In 2013, no midwinter warming events occurred. Yet, from mid-August onward, the Antarctic 

vortex was disrupted by several minor SSWs, mimicking the year 2012 with stratospheric temperatures 

between 10 to 50 hPa remaining above the long-term climatological mean, and similar to 2013, an early 

dissipation of the vortex.

Note that detailed analyses of the 2012 and 2013 Antarctic ozone hole seasons have not been 

performed at the time of this Assessment. Hence, it is not known to what degree modified chemistry and 

changes in vortex dynamics and transport processes have contributed to the smaller than typical OMDs in 

2012 and 2013.

In summary, the Antarctic ozone hole has seen very different amounts of ozone loss over the 

period 2010–2013 due to variations in polar vortex dynamics. In particular, minor SSWs, as well as 

reduced vortex stability, have led to significantly reduced Antarctic springtime ozone depletion during 

several years.

3.3 UNDERSTANDING OF POLAR OZONE PROCESSES

Overall, there have been no major changes in our understanding of polar ozone loss processes 

since WMO (2011). Our knowledge of polar chemical and dynamical processes was already based on a 

large body of research, and models could reproduce observed chemical polar ozone depletion and its 

variability well (e.g., Chipperfield et al., 2005; Frieler et al., 2006). Recent work has improved our 

detailed understanding of polar ozone processes, such as the formation mechanism of nitric acid 

trihydrate (NAT) particles; validated previous assumptions; and reduced uncertainty. For example, 

uncertainty in the photolysis rate of the ClO dimer (Cl2O2 or ClOOCl), a key parameter in polar chemical 

ozone loss, has been reduced by a factor of three (see Section 3.3.2.2). The very cold winter of 2010/11 

increased the range of meteorological variability seen in the Arctic over the past few decades and 

provided a new extreme test case for models.

3.3.1 Polar Stratospheric Clouds

Polar stratospheric clouds (PSCs) play two major roles in stratospheric ozone depletion 

(Solomon, 1999). First, heterogeneous chemical reactions that convert chlorine from HCl and ClONO2

reservoirs to active, ozone-destroying species are catalyzed by PSC particles (primarily supercooled 

ternary solution (STS) droplets; see Box 3-1), as well as by cold binary aerosols (Portmann et al., 1996; 
Polar Ozone

3.17

Drdla and Müller, 2012). Second, the gravitational sedimentation of large nitric acid trihydrate (NAT) 

PSC particles irreversibly removes gaseous odd nitrogen (denitrification) (Salawitch et al., 1989), thereby 

slowing the reformation of the benign chlorine reservoirs and extending the ozone depletion process.

3.3.1.1 RECENT OBSERVATIONS

An extensive set of PSC observations was produced by the RECONCILE field campaign 

conducted in the Arctic during January–March 2010 (von Hobe et al., 2013). These include observations 

from in-situ particle probes, a HNO3 content probe, in situ backscatter probe, infrared limb-sounding 

instrumentation, and upward- and downward-looking lidar onboard the high-altitude M55-Geophysica 

aircraft; from ground-based lidars; and from the balloon-borne Compact Optical Backscatter and AerosoL 

Detector (COBALD) aerosol backscatter sondes. In addition, the spaceborne lidar (Cloud-Aerosol Lidar 

with Orthogonal Polarization, CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite

Observation (CALIPSO) satellite provided a view of PSC properties on nearly vortex-wide spatial scales 

and spanning the entire winter, complementing the more localized campaign measurements. Significant 

findings related to PSC processes include:

1) Extensive regions of NAT PSCs were observed by CALIOP during 15–30 December 2009 prior to 

the occurrence of ice PSCs (Pitts et al., 2011). This is the first time NAT PSCs have been observed 

on vortex-wide scales prior to the occurrence of ice PSCs and corroborates the conclusions of 

Pagan et al. (2004) and Voigt et al. (2005) that ice nuclei are not a prerequisite for NAT formation. 

A non-ice NAT nucleation mechanism operating on vortex-wide scales has important implications 

for denitrification and potential enhancement of ozone depletion.

Box 3-1. Stratospheric Particles and Their Roles in Ozone Depletion

• Stratospheric aerosols – liquid sulfuric acid/water (H2SO4/H2O) droplets: They are present at all 

latitudes in the lower stratosphere; typical mean radius ≈ 0.05–0.1 μm. Their background 

abundance can be greatly enhanced by volcanic eruptions that reach the stratosphere. These 

aerosols cause the conversion of gaseous nitrogen oxides (NOx: NO + NO2) species to nitric acid 

(HNO3) and can initiate chlorine activation at low temperatures (≈195 K).

• Supercooled ternary solution (STS) polar stratospheric clouds (PSCs) – liquid nitric acid/sulfuric 

acid/water (HNO3/H2SO4/H2O) droplets: They grow from stratospheric aerosols at low temperatures 

(≈195 K) without a phase change; maximum radius ≈0.3–0.5 μm. They are responsible for 

reversible removal of HNO3 by condensation and play a major role in chlorine activation.

• Solid nitric acid trihydrate (NAT) PSCs – HNO3•3 H2O particles: They can form at temperatures 

below the NAT existence temperature, typically around 195 K, but require significant supercooling to form readily from the gas or liquid phase. They are responsible for irreversible 

removal of HNO3 (denitrification) when they sediment and can play a role in chlorine activation, 

though their effect is likely masked by activation on STS particles. NAT particles have a typical 

radius of 1 μm, but can grow to 10 μm radius or larger. These larger particles have been referred 

to as “NAT-rocks.”

• Solid water ice PSCs – H2O particles: They can exist only at temperatures below the frost point, 

typically around 188 K; typical radii range from ~1 μm for mountain wave-induced ice PSCs to 

5–10 μm for synoptic-scale ice PSCs. They are responsible for irreversible removal of H2O 

(dehydration) but play a minor role in chlorine activation.
Chapter 3

3.18

2) Unusually large PSC particles (“NAT-rocks”) were detected during the 2010 winter and again in 

the winter of 2011 when synoptic scale PSCs formed in the Arctic (von Hobe et al., 2013). Visual 

evidence for particles with diameters as large as 35 μm was provided by shadow-cast images. 

However, if the particles are assumed to be NAT spheres, the total mass of all optically detected 

particles with diameters greater than 2 μm exceeds the available total reactive nitrogen (NOy) (as 

measured and also reconstructed from model calculations) beyond the measurement uncertainties. 

Thus, new theoretical concepts, e.g., that the particles are highly aspherical or consist mostly of ice 

with a NAT coating, must be explored.

3) In situ measurements of submicron background aerosols showed that up to 75% of the particles 

larger than 10 nm in diameter were non-volatile or contained non-volatile cores and thus could not 

consist solely of sulfuric acid (H2SO4) and H2O (von Hobe et al., 2013). This high refractory 

particle fraction was consistently found within the Arctic polar vortex during three measurement 

campaigns in 2003, 2010, and 2011, with the largest amount of refractory material occurring at the 

lowest nitrous oxide (N2O) mixing ratios. Thus, subsiding air masses in the vortices transported 

non-volatile particulate matter—possibly of meteoric origin—from the upper stratosphere and 

lower mesosphere into the upper troposphere/lower stratosphere (UT/LS) region. Especially in 

times of relative volcanic quiescence or low stratospheric background (H2SO4/H2O) aerosol, such 

particles may be involved in heterogeneous PSC nucleation (e.g., Hoyle et al., 2013; Engel et al., 

2013).

4) A rare outbreak of synoptic-scale Arctic ice PSCs was observed by CALIOP from 15–21 January 

2010. During this same period, unprecedented evidence of water redistribution and irreversible 

dehydration in the Arctic stratosphere was obtained (Engel et al., 2014). Simultaneous balloonborne measurements of water vapor and aerosol backscatter on 17 January provided a unique highresolution snapshot of repartitioning of water vapor into ice particles. For the first time, signatures 

of rehydration could be measured in the Arctic and attributed to the observed dehydration. The 

movement of the dehydrated air masses around the polar vortex was seen in the Aura MLS water 

vapor data. A modeling study by Engel et al. (2014) showed that the observed redistribution of 

water cannot be explained by homogeneous ice nucleation alone. A selective, heterogeneous 

nucleation mechanism is required that allows the ice particles to grow to larger sizes compared to 

homogeneously nucleated ice particles, which remain too small to cause the significant dehydration 

in the observed case. 

3.3.1.2 REVISED HETEROGENEOUS NAT AND ICE NUCLEATION SCHEME

The formation of NAT PSCs is a prerequisite for denitrification by sedimenting particles, which 

prolongs seasonal ozone loss. The extensive and deep denitrification in the Antarctic vortex helps to drive 

the almost complete O3 loss inside the Southern Hemisphere polar vortex (Solomon et al., 2014). In 

contrast, denitrification in the Arctic is smaller and more variable from year to year. A more accurate 

representation of NAT PSC nucleation and particle characteristics leads to better model simulations of 

denitrification and hence ozone loss. For example, a Single-Layer Isentropic Model of Chemisty and 

Transport (SLIMCAT) chemical transport model (CTM) simulation of the 2004/2005 Arctic winter using 

the microphysics-based Denitrification by Lagrangian Particle Sedimentation (DLAPSE) denitrification 

scheme showed much better agreement with observed HNO3 and column O3 loss than a simulation using 

the standard thermodynamic equilibrium PSC approach (Feng et al., 2011).

CALIOP observations of widespread NAT PSCs and synoptic-scale ice PSCs in the Arctic during 

the 2009/2010 winter (Pitts et al., 2011) have stimulated new microphysical modeling studies (Hoyle et 

al., 2013; Engel et al., 2013). PSC optical parameters computed using Mie and T-Matrix scattering codes 

were compared to selected CALIPSO PSC observations made in December 2009 and January 2010. The 

best agreement between model and observations was achieved by (1) allowing for NAT and ice to 
Polar Ozone

3.19

nucleate heterogeneously on pre-existing solid particles and (2) superimposing small-scale temperature 

fluctuations onto synoptic-scale parcel trajectories as suggested by Murphy and Gary (1995). The 

nucleation properties of NAT and ice can be approximated the same way as heterogeneous ice nucleation 

on Arizona test dust in the immersion mode as demonstrated in previous laboratory experiments (Marcolli 

et al., 2007). Whereas artificially produced Arizona test dust is composed of various mineral species with 

a composition similar to that of dust originating from desert, non-volatile solid inclusions were observed 

in 67% of the stratospheric background aerosols by Curtius et al. (2005) and up to 75% of the submicron 

aerosol measurements during the 2010 RECONCILE campaign (von Hobe et al., 2013). Coagulated 

meteoritic smoke particles or micrometeorites may be suitable nuclei for heterogeneous NAT and ice 

formation as speculated by the above mentioned authors and have also been used in early laboratory 

experiments by Biermann et al. (1996). It now appears that the upper limits of measured NAT nucleation 

rate coefficients on foreign material by Biermann et al. (1996) might be sufficient to explain the 

CALIPSO PSC observations of low number density NAT PSCs from December 2009.

The newly introduced heterogeneous nucleation pathways of NAT and ice are allowed to compete 

with the conventional accepted pathways of PSC formation, namely, the growth of liquid particles into 

supercooled ternary solution (STS) droplets due to uptake of HNO3 and H2O (Carslaw et al., 1995), the 

homogeneous ice nucleation at around 3 K below the ice frost point (Koop et al., 2000), and the 

subsequent nucleation of NAT on ice upon warming, which typically occurs in mountain-wave-driven 

localized cold pools (Carslaw et al., 1998).

Grooß et al. (2014) implemented a new saturation-dependent NAT nucleation parameterization 

into the Chemical Lagrangian Model of the Stratosphere (CLaMS) model based on the theory described 

in Hoyle et al. (2013) and found that the model reproduces the locations and extent of NAT PSCs 

observed by CALIOP somewhat better than when a constant nucleation rate is assumed (Grooß et al., 

2005).

3.3.1.3 IMPROVED UNDERSTANDING OF PSC COMPOSITION

Recent studies by Lambert et al. (2012) and Pitts et al. (2013) demonstrated the usefulness of 

combining nearly coincident data from the CALIOP lidar on CALIPSO and MLS on Aura to study the 

temperature-dependent uptake of HNO3 in PSCs; this procedure is very similar to the method of Spang 

and Remedios (2003), who combined Cryogenic Infrared Spectrometers and Telescopes for the 

Atmosphere (CRISTA) measurements of HNO3 and particle properties for a PSC type classification in the 

Southern Hemisphere. Comparing observations with theoretical HNO3 uptake for STS (Carslaw et al., 

1995) and NAT (Hanson and Mauersberger, 1988) allows one to judge how well PSCs can be assigned to 

the various composition classes by CALIOP and also offers insight into PSC growth kinetics. Pitts et al. 

(2013) showed that CALIOP PSCs in the STS, liquid-NAT mixture (external mixtures of NAT and 

stratospheric aerosols or STS), and ice classes conform well to their expected temperature existence 

regimes, providing more confidence in our understanding of PSC particle composition. Pitts et al. (2013) 

also found that liquid-NAT mixture PSCs exhibit two preferred modes of HNO3 uptake, one that is 

closely aligned with the theoretical HNO3 uptake curve for STS, and a second that is more closely aligned 

with the theoretical HNO3 uptake curve for NAT as shown in Figure 3-9a.

Analysis of temperature histories along parcel trajectories (Figure 3-9b) show that liquid-NAT 

mixture PSCs with HNO3 uptake more like that of STS had been below the NAT existence temperature 

TNAT for only short periods of time. Since the growth of large, low-number-density NAT particles is 

kinetically limited, HNO3 uptake in these mixtures of PSCs is dominated by STS droplets. On the other 

hand, liquid-NAT mixture PSCs with HNO3 uptake more like that of NAT had been below TNAT for much 

longer periods of time, allowing the thermodynamically favored NAT particles to approach equilibrium 

(Figure 3-9b). Wegner et al. (2013) showed that allowing the formation of non-equilibrium NAT mixtures 

in the Whole Atmosphere Community Climate Model (WACCM) global 3-D model significantly 

improves the agreement of the model with gas-phase HNO3 observations.
Chapter 3

3.20

Figure 3-9. (a) Uptake of nitric acid as a function of T − Tice for CALIOP Arctic NAT mixture PSC 

observations during 1 December 2009–31 January 2010. (b) Temperature histories along air parcel 

trajectories for CALIOP Arctic NAT mixture PSC observations during 1 December 2009–31 January 2010. 

The color scale for panel (b) indicates the average number of hours each air parcel associated with the 

NAT mixture observations falling within each bin was exposed to temperatures below TNAT. Black lines 

are reference equilibrium uptake curves for STS and NAT assuming 16 ppbv HNO3 and 5 ppbv H2O. The 

histogram bin size is 0.25 ppbv × 0.25 K. Adapted from Pitts et al. (2013).

3.3.1.4 PSC FORCING MECHANISMS

PSCs can form in the winter polar stratosphere once the synoptic-scale temperature drops below 

the NAT and ice PSC existence temperatures, but the formation of NAT particles requires significant 

supercooling below the NAT equilibrium temperature. Small-scale orographic gravity waves provide an 

additional forcing mechanism for PSC formation when synoptic-scale temperatures are close to the PSC 

formation thresholds (Godin et al., 1994; Carslaw et al., 1999). The PSCs formed by orographic gravity 

waves can cause the conversion of a large fraction of inactive chlorine species to reactive chlorine species 

(Carslaw et al., 1998), despite the limited spatial and temporal scales of the waves. Early-season PSC 

formation in the Antarctic winter has been linked to orographic wave forcing (Höpfner et al., 2006;

Eckermann et al., 2009), with quantifiable changes in the abundance of trace gas species (Lambert et al., 

2012). PSC formation due to orographic wave forcing occurs throughout winter near the polar vortex 

edge, where synoptic-scale temperatures remain close to the frost-point temperature (Alexander et al., 

2011; Kohma and Sato, 2011). Recent satellite data sets indicate the occurrence of midwinter PSCs linked 

to orographic wave forcing in both the Arctic and the Antarctic (Khosrawi et al., 2011; Noel and Pitts, 

2012; Alexander et al., 2013). Analyses of satellite observations indicate that the location and occurrence 

of resolved orographic gravity waves are well reproduced by meteorological analyses such as ECMWF, 

but the amplitudes can be significantly underestimated (e.g., Schroeder et al., 2009). Kohma and Sato 

(2013) demonstrated that the simultaneous occurrence of upper tropospheric clouds and PSCs is 

preferentially promoted by tropospheric blocking linked to high-pressure systems.
Polar Ozone

3.21

3.3.2 Polar Chemistry

3.3.2.1 HETEROGENEOUS CHEMISTRY

During polar winter, heterogeneous reactions can convert reservoir chlorine species (HCl and 

ClONO2) into more reactive species, together termed ClOx, that destroy ozone (Solomon et al., 1986). 

The seasonal evolution of the balance between the heterogeneous chlorine activation rates and mostly 

gas-phase chlorine deactivation rates (i.e., the reformation of HCl and/or ClONO2) largely controls the 

amount of ozone loss in a given polar winter.

Chlorine activation reactions occur on a variety of surface types such as liquid binary aerosol, 

STS, and NAT (Box 3-1), although with rates that, at a given temperature, vary with the surface type and 

increase substantially with decreasing temperature. All of these particles are included in typical models 

used to simulate stratospheric ozone. Drdla and Müller (2012) proposed that the temperature threshold for 

the onset of polar chlorine activation is controlled by the reactivity of liquid aerosols. They further report 

that different assumptions about the types of PSC and rates of heterogeneous reactions have only a minor 

impact on simulated polar chlorine activation rates, at least for the range of conditions studied (the Arctic 

winter 1999/2000 and the Antarctic winter 2000). Fast chlorine activation on liquid particles means that 

these particles control the onset of polar chlorine activation at temperatures just higher than TNAT, and 

Drdla and Müller (2012) argue they are sufficient to reproduce the morphology of chlorine activation and 

the evolution of ClOx levels throughout winter. They suggest that this is the case even for cold binary 

(H2SO4/H2O) stratospheric aerosols. In reality, these particles will take up HNO3 as temperatures 

decrease, turning them into STS and further increasing their reactivity. Wohltmann et al. (2013) found 

that the difference in simulated column ozone loss over the winter 2009/2010 caused by a variety of 

assumptions about heterogeneous activation rates is less than 10%. For other winters it remains to be 

studied how sensitive ozone loss calculations are to these assumptions. When temperatures remain low 

until later during the season compared to 2009/2010, these sensitivities can potentially be larger.

Vortex-averaged satellite observations by the MLS instrument for the Arctic winters 2004/2005 

to 2010/2011 (Figure 3-10) show that the initial removal of HCl and HNO3 from the gas-phase in 

December/January are not correlated (Wegner et al., 2012) and therefore there is no definite connection 

between the PSC particles that lead to chlorine activation and those that deplete gas-phase HNO3. HNO3

loss exhibits large interannual variability depending on prevailing temperatures while HCl loss is 

continuous through December with small inter- or intra-annual variability. Hence, the occurrence of 

HNO3-containing PSC particles does not seem to have a significant effect on the rate of initial chlorine 

activation on a vortex-wide scale.

Figure 3-10. HCl and HNO3

observations by MLS for the Arctic 

winters 2004/2005 to 2010/2011 on 

500 K potential temperature in the 

vortex core (equivalent latitude 

>75°N). Adapted from Wegner et 

al. (2012).
Chapter 3

3.22

Overall the body of work presented above corrobates the view that chlorine activation rates are 

mainly controlled by temperature (e.g., Kawa et al., 1997), with a limited dependence on the different 

particle types. Nonetheless, the formation of STS and NAT particles is important as these particles 

significantly alter gas-phase chemistry through the uptake of HNO3. Further, the formation of NAT 

particles is important as sedimentation and thus denitrification can only occur if large NAT particles form 

in the stratosphere (see Section 3.3.1).

Antarctic observations have shown that extremely low ozone mixing ratios below about 0.5 ppmv 

are reached (e.g., Solomon, 2005). The lower limit of these low ozone values has been investigated by 

Grooß et al. (2011), extending earlier work by Douglass et al. (1995). Grooß et al. showed that continuous 

rapid heterogeneous reactions on polar stratospheric clouds were required to produce the extreme low 

ozone values observed in the Antarctic. They show that under such low ozone conditions with continued 

PSC existence a balance is maintained by gas-phase production of both HCl and hypochlorous acid 

(HOCl) followed by heterogeneous reaction between these two compounds, which inhibits deactivation of 

chlorine via the formation of HCl and therefore allows the ozone loss to continue. Thereafter, a very 

rapid, irreversible chlorine deactivation into HCl occurs, either when ozone drops to values low enough 

for gas-phase HCl production to exceed chlorine activation processes or when temperatures increase 

above the polar stratospheric cloud formation threshold.

3.3.2.2 GAS-PHASE CHEMISTRY

Recent observational studies and laboratory investigations have largely confirmed our 

understanding of how chlorine and bromine compounds drive polar ozone losses. The major cause of gasphase chemical springtime polar ozone loss is due to the ClO + ClO and ClO + BrO cycles, for example:

ClO + ClO + M ↔ ClOOCl + M (R1)

ClOOCl + hν → Cl + ClOO (R2a)

ClOO + M → Cl + O2 + M (R3)

2{Cl + O3 → ClO + O2}

Net: 2 O3 → 3 O2

The efficiency of ozone loss via this cycle largely depends on the rate of ClOOCl photolysis 

(R2a). Pope et al. (2007) reported very low values for the ClOOCl photolysis cross section, but these are 

now attributed to an overcorrection of the molecular chlorine (Cl2) interference (von Hobe et al., 2009). 

Following Pope et al. (2007) a large number of new laboratory studies of the ClOOCl photolysis cross

sections and quantum yields were carried out. This additional body of work led to a comprehensive reevaluation of the absorption spectra (WMO, 2011) and to a new recommendation for the cross sections 

given in the Jet Propulsion Laboratory (JPL) 2011 report (Sander et al., 2011), which is now based on the 

study of Papanastasiou et al. (2009). These are larger than previously recommended values. At the same 

time the uncertainty range in the recommendation has been reduced compared to earlier JPL 

recommendations, based on the considerable amount of new laboratory data that was published after Pope 

et al. (2007). Recent experiments by Young et al. (2014) are consistent with the current JPL 

recommendation but their measurements extend to longer wavelengths and also directly quantify the Cl2

interference, further confirming our understanding of this photolysis process. The higher ClOOCl 

photolysis cross section in JPL 2011 (Sander et al., 2011), which is based only on laboratory 

measurements, is now also consistent with previous studies of the ClO dimer reaction that are based on 

atmospheric observations (e.g., Stimpfle et al., 2004; Frieler et al., 2006) and with more recent 

evaluations based on ClO observations from ground-based microwave measurements in the Antarctic 

(Kremser et al., 2011), and in situ (Sumińska-Ebersoldt et al., 2012) and remote-sensing (Kleinböhl et al., 

2014) aircraft observations in the Arctic.

The products of ClOOCl photolysis in (R2a) have been questioned by Huang et al. (2011). They 

argue that ClOOCl photolyzes directly into 2 Cl + O2. Under stratospheric conditions this mechanism 

would be slightly more rapid than the thermal decomposition of ClOO in (R3) but otherwise it has a 
Polar Ozone

3.23

limited impact on modeling the ozone loss process. More important, Huang et al. (2011) also support the 

findings of Moore et al. (1999) on the existence of a minor channel for (R2) that produces ClO via 

photolysis with a yield of 19%, compared to a value of 10 ± 10% in Moore et al. (1999), while previous 

JPL recommendations do not mention this channel. This minor channel has now been adopted in the JPL 

2011 recommendation (Sander et al., 2011). Plenge et al. (2005) estimated that the impact of a 10% yield 

decreases the ozone loss due to the dimer cycle by 5%.

Progress has also been made in understanding the forward (i.e., formation of ClOOCl) and 

backward (i.e., thermal decomposition of ClOOCl) reactions that determine the equilibrium described by 

process (R1). Recent atmospheric observations of nighttime ClO (Sumińska-Ebersoldt et al., 2012) are 

consistent with the Plenge et al. (2005) laboratory measurements of the thermal equilibrium constant 

given by (R1), which is considerably smaller than JPL 2006 recommendations (Sander et al., 2006). This 

agrees with previous atmospheric observations, which also support a thermal equilibrium constant smaller 

than laboratory-based recommendations (see WMO, 2011). The JPL 2011 recommendation, while smaller 

than the JPL 2006 recommendation, is still 2.5–3 times larger than the value derived by Plenge et al. 

(2005) for stratospherically relevant temperatures of 190–210K. While a quantitative understanding of the 

equilibrium constant is important for understanding the budget between ClO and ClOOCl in particular 

during night and twilight conditions, it does not significantly affect our understanding of ozone loss rates, 

which, in a chemical model, are not very sensitive to assumptions about this particular kinetic parameter.

The ClO + BrO catalytic cycles are responsible for about 50% of the ozone loss in the polar lower 

stratosphere, with the contribution being slightly larger in the Arctic where the overall ozone depletion is 

smaller (e.g., Frieler et al., 2006). Chapter 1 discusses recent work that has better quantified the 

contribution from very short-lived substances (VSLS) to the stratospheric bromine budget. Overall the 

result of Chapter 1 is that VSLS increase the stratospheric bromine burden to some extent, compared to 

what it would be in the absence of VSLS transport into the stratosphere. Considering the VSLS 

contribution to stratospheric bromine leads to larger ozone loss in chemical models and this VSLS 

contribution is necessary for models to reproduce observed ozone loss rate.

Atmospheric balloon observations of bromine monoxide (BrO) and ClO (Kreycy et al., 2013) 

support a larger photolysis rate for bromine nitrate (BrONO2) and a smaller reaction rate of BrO + NO2

affecting the BrO and NO2 cycles. This reduces the amount of total inorganic bromine (Bry) required to 

reconcile stratospheric BrO measurements with models, and reduces the inferred contribution of VSLS 

(see Chapter 1). The overall effect on stratospheric ozone of such changes in the photolysis and reaction 

rates is small to negligible (<1% ozone change everywhere), due to canceling effects of overestimating 

Bry (ozone loss suppressing) and underestimating BrO/Bry (ozone loss enhancing).

3.3.2.3 OZONE LOSS PROCESSES

We now discuss the effect of the progress presented in Section 3.3.2.2 on our ability to calculate 

ozone loss rates with chemical models. Figure 3-11 illustrates the progress in our quantitative 

understanding of chemical ozone loss rates since the last Assessment (WMO, 2011). It compares 

observed ClOx in the cold Arctic winter of 1999/2000 with chemical box model calculations, which are 

based on ozone loss rates that were diagnosed with the Match approach (Rex et al., 2002) from 

ozonesonde observations. With the updates in ClOOCl cross sections described in Section 3.3.2.2, and 

including a contribution from stratospheric Bry from VSLS (see Chapter 1 of this Assessment), the model 

reproduces observed ClOx much better than based on WMO (2011) assumptions, and uncertainties of the 

model calculations are largely reduced compared to the status in WMO (2011).

Since WMO (2011) a number of studies have quantified chemical ozone loss rates as vortex 

averages or at a single location and confirmed our understanding. Moreover, the cold Arctic winter of 

2010/11 provided a new, more extreme test case for ozone loss models. Kuttippurath et al. (2010a and 

2010b) examined the UV-visible SAOZ spectrometer network, Hassler et al. (2011b) examined ozonesondes
Chapter 3

3.24

Figure 3-11. Ozone loss per sunlit 

hour (lower panel) based on results 

of Match analysis for Arctic winter 

1999/2000. The upper panel shows 

the abundance of ClOx (ppbv) 

needed to reproduce the observed 

loss rates in a photochemical box 

model based on JPL 2006 (blue) and 

JPL 2011 (red) recommendations for 

JCl2O2 and their respective uncertainties. Observations of ClOx are 

also shown (gray diamonds). The 

diagram illustrates the progress in 

quantitative understanding of polar 

chemical ozone loss and the 

reduced uncertainty in modeling this process. Both calculations include a contribution to stratospheric Bry

from VSLS based on Chapter 1. Update of Frieler et al. (2006) and WMO (2011). 

at South Pole, and Sonkaew et al. (2013) examined the SCanning Imaging Absorption spectroMeter for 

Atmospheric CHartographY (SCIAMACHY) ozone profiles. Differences between the SCIAMACHY 

Antarctic loss rates of 45 ± 6 ppbv per day and South Pole sonde-derived rates of 70 ± 10 ppbv per day 

for the peak chemical ozone loss rates at 475 K over the 2002–2010 period are likely explained by the 

very different sampling of the polar vortex.

A number of studies have compared inferred chemical ozone loss rates with models for the cold 

Arctic winter 2010/2011. Figure 3-12 shows the results from a range of 3-D CTMs compared with ozone 

observations from MIPAS and from MLS. Overall all models shown in the figure were able to reproduce 

the observed ozone loss, clearly showing that the unprecedented loss during Arctic spring 2011 has been 

caused by well-known chemistry. Adams et al. (2012) also found that their 3-D CTM could reproduce the 

loss inferred from ground-based observations. Pommereau et al. (2013) found good agreement between 

observations and models for the diagnosed ozone column loss, when taking into account changes in partial 

ozone column at high altitudes (above ~550K, ~20km). Together, these studies indicate that the large loss 

seen in Arctic winter 2010/2011 is consistent with our current understanding of chemical processes and was 

driven by the very specific meteorological conditions, as described in Section 3.2.3.2. Overall the ability of 

3D-CTMs to reproduce the observed loss for 

such an event that has extended the previous 

range of variability increases confidence that the 

models are now mature and capture the processes that are relevant for Arctic ozone loss.

Figure 3-12. Evolution of ozone mixing ratio at 

475 K (~18km) observed by the MLS and 

MIPAS satellite instruments (open and solid 

black dots) and simulated by several chemical 

transport models (CTMs, solid color lines). 

Figure based on updated calculations with 

CTMs described in Feng et al. (2011; 

SLIMCAT), Kuttippurath et al., (2012; MIMOSA 

CHIM), Grooß et al. (2005, 2014; CLaMS), 

Wohltmann and Rex (2009; ATLAS), and

Sinnhuber et al. (2011).
Polar Ozone

3.25

3.3.3 Polar Dynamical Processes

3.3.3.1 RELATION BETWEEN WAVE DRIVING AND POLAR OZONE

Ozone inside the polar vortex and in the collar region surrounding the polar vortex experiences large yearto-year variations (WMO, 2011). The main driver for this variability is variations in atmospheric 

dynamics (Fusco and Salby, 1999; Randel et al., 2002; Weber et al., 2003, 2011; Hood and Soukharev, 

2005; Salby, 2008). Variability in the planetary wave activity driving the winter Brewer-Dobson 

circulation modulates both dynamical and chemical processes affecting polar ozone (e.g., Tegtmeier et al., 

2008). The links between planetary waves and polar ozone losses results from the temperature modulation 

(e.g., Newman et al., 2001). Mass circulations associated with momentum deposition by the planetary 

waves leads to adiabatic compression of polar air masses (and immediate warming, e.g., SSWs 

(Ayarzaguëna et al., 2011)) and expansion in the tropical lower stratosphere (cooling). The return toward 

radiative equilibrium (slow diabatic cooling) in the polar region then results in enhanced transport into the 

polar vortex and subsidence inside the vortex area. The combination of enhanced transport and warmer 

polar temperatures in a given winter is then responsible for higher polar ozone levels, reduced polar ozone 

losses, and leads to higher spring total ozone (e.g., Chipperfield and Jones, 1999; de Laat and van Weele, 

2011; Kuttipurath et al., 2010b; Kuttipurrath and Nikulin, 2012; Kramarova et al., 2014). Our 

understanding of the mechanisms that determine the degree of wave driving of the polar stratosphere is 

still incomplete, but some progress has been made.

Weber et al. (2011) showed a compact relationship between the mean winter eddy heat flux at 100 

hPa, a measure for the planetary wave activity and BDC strength, and spring-to-fall polar ozone ratio 

combining data from both hemispheres (Figure 3-13). The planetary wave activity is much lower in the 

Southern Hemisphere and, therefore, results in spring-to-fall ozone ratios smaller than 1 (polar ozone loss 

outweighs ozone transport). In the Northern Hemisphere this ratio is always above 1 (ozone transport 

outweighs polar ozone loss). The various extreme events like the split of the Antarctic vortex in 2002 (with an 

ozone ratio above 1), the record Antarctic 

ozone hole in 2006, the cold Arctic 

winters in 1996, 1997, and 2011 (e.g., 

Manney et al., 2011), and high Arctic 

ozone in 2010 (Steinbrecht et al., 2011) 

follow this compact linear relationship.

Figure 3-13. Spring-to-fall ratio of 

observed polar cap total ozone (>50°) 

as a function of the absolute extratropical winter mean eddy heat flux 

(September to March in the Northern 

Hemi-sphere and March to September 

in the Southern Hemisphere) derived 

from ECMWF ERA-Interim data. Data 

from the Southern Hemisphere are 

shown as triangles (September over 

March ozone ratios) and from the 

Northern Hemisphere as solid circles 

(March over September ratios). Selected 

polar total ozone distributions for 

selected years are shown at the top. 

Updated from Weber et al. (2011).
Chapter 3

3.26

This linear relationship between eddy heat flux and polar cap ozone was also found in two CCMs,

indicating that current models realistically describe the variability in stratospheric circulation and its 

effect on total ozone (Weber et al., 2011). Both models show a positive trend in the winter mean eddy 

heat flux (and winter BDC strength) in both hemispheres until year 2050, however, the interannual 

variability (peak-to-peak) is two to three times larger than the change in the decadal means between 1960 

and 2050 (Weber et al., 2011). Substantial polar ozone losses could occur in the case of particularly cold 

winters in the coming decades despite the ongoing decrease of ODS levels in the stratosphere.

3.3.3.2 THE ROLE OF LEADING MODES OF DYNAMICAL VARIABILITY

The respective influences of natural variability and anthropogenic climate change on polar 

stratospheric temperatures are difficult to disentangle given the short observational record in the satellite 

era. Using reanalyses and radiosonde data, Bohlinger et al. (2014) showed a wintertime positive trend in 

Arctic temperatures at 50 hPa over the past three decades, and a corresponding increase in planetary wave 

activity diagnosed as the meridional eddy heat fluxes at 100 hPa. In addition, they have identified a 

residual radiative cooling trend of about −0.5 K/decade. Nevertheless, the processes in the troposphere 

that govern the large interannual variability and the trend in these temperatures remain to be fully 

understood. It is particularly important to understand the origin of very strong vortex events that drive the 

ozone loss, either short-duration intense cooling episodes as observed in January 2010 (Dörnbrack et al., 

2012), or else prolonged coolings like that observed during the late winter and spring 2011 (Manney et 

al., 2011). Several recent observational studies have shown that tropospheric highs (e.g., blockings) can 

lead to either warming or cooling of the Northern Hemisphere polar stratosphere, depending upon their 

geographical location (Nishii et al., 2011; Woollings et al., 2010; Castanheira and Barriopedro, 2010). 

This dual effect arises from the potential interaction of transient waves with climatological planetary 

waves, thereby increasing or lowering the wave activity flux into the stratosphere. North Pacific blockings 

distinctly lead to polar stratospheric coolings (Nishii et al., 2010), and brief vortex cooling episodes 

observed during the 2009/10 (Dörnbrack et al., 2012). Also the 2010/2011 winter, described in Section 

3.2.3.2, was clearly associated with North Pacific highs and a precursory enhanced Western Pacific 

teleconnection pattern (Orsolini et al., 2009). The exact cause of the prolonged cold stratosphere in March 

and April 2011, which led to the record ozone loss, remains unclear, but may involve complex dynamical 

positive feedbacks between a small intense polar vortex and equatorward-deflected planetary waves. 

Recent observational and modeling studies emphasize the role of a warm anomaly in North Pacific sea 

surface temperatures in leading to the cold vortex in 2011 (Hurwitz et al., 2011, 2012). Hence, a better 

understanding of the variability of the coupled ocean-atmosphere circulation not only in the North 

Atlantic but also in the key Eastern Eurasia/North Pacific region where wave activity fluxes into the 

stratosphere are climatologically the strongest, may lead to a better understanding of polar stratospheric 

temperature variability.

Kiesewetter et al. (2010) showed that the stratospheric Northern Annular Mode (NAM) index is 

strongly correlated with Arctic ozone anomalies. The different phases of the NAM are driven by the 

variability in planetary wave driving. Extreme phases of the NAM index (strong and weak vortex events) 

are associated with negative and positive ozone anomalies that descend from the uppermost stratosphere 

and then rapidly cover the upper and middle stratosphere, from where they then slowly descend into the 

lowermost stratosphere within 5 months.

Another important factor in modulating the strength of the polar vortices is the equatorial quasibiennal oscillation (QBO). The QBO influences the propagation of waves, e.g., during QBO easterlies the 

waves are more directed toward the polar region, decelerating the polar night jet and perturbing the polar 

vortex (Holton and Tan, 1980; Baldwin et al., 2001; Naoe and Shibata, 2010; Anstey and Shepherd, 2014;

Watson et al., 2014). There is a close link between the QBO and the occurrence of SSWs and the date of 

the final warming (Thiéblemont et al., 2011). Similarly, planetary wave activity tends to be stronger 

during warm phases of the El Niño-Southern Oscillation (ENSO) (e.g., Garfinkel and Hartmann, 2008). 
Polar Ozone

3.27

Trends and changes in the amplitude of Southern Hemisphere stationary waves in reanalyses are 

associated with polar ozone depletion and changes in the strength of the subtropical jets driven by sea 

surface temperature (SST) forcing (Wang et al., 2013; Agosta and Canziani, 2011). Sonkaew et al. (2013) 

showed that the variable Arctic ozone loss as determined from SCIAMACHY limb ozone profiles during 

2002–2009 correlate with the QBO phase, meaning larger ozone losses were generally observed during 

QBO west phases, although the studied period is relatively short. Hurwitz et al. (2011) showed that the 

dynamical conditions prevailing during Arctic winter 2011 were characterized as expected by a QBO 

westerly phase and a concurrent La Niña phase. However, these features alone cannot explain the 

persistence of the low temperature anomaly into March 2011. As mentioned above, they identified the 

positive North Pacific SST anomaly as a potential driver for the cold Arctic vortex in late winter 2011.

3.3.3.3 MERIDIONAL MIXING

Blessmann et al. (2012a) showed that a larger fraction of ozone from lower latitudes is mixed into 

the Arctic vortex in early winter when the wave activity in late fall has been high. In the contrasting case 

of low wave activity, a larger fraction of early winter polar vortex ozone has subsided from the upper 

stratosphere during fall. The amount and variability (10%) of early winter Arctic ozone below 750 K (~30 

km) are largely determined by dynamical processes in the early vortex formation period (Blessmann et 

al., 2012b).

Using ozone observations above Antarctica in combination with a CTM model, Roscoe et al. 

(2012) confirmed earlier studies that the polar ozone depletion starts earlier for stations that are closer to 

the vortex edge than those in the core region. They also showed from dynamical considerations that air 

parcels from the core region and the vortex edge region mix only weakly. As the vortex edge region is 

more strongly exposed to sunlight and is generally warmer, a cooling trend in the stratosphere could 

extend the region where PSC formation is possible, potentially delaying ozone recovery. This contrasts to 

the core region where the formation of PSCs is saturated and is less impacted by additional cooling.

3.4 RECOVERY OF POLAR OZONE

Detection of polar ozone recovery is an important milestone in assessing the effectiveness of the 

Montreal Protocol. As indicated in Chapter 1 of this assessment, the stratospheric chlorine and bromine 

burden as expressed by the Equivalent Effective Stratospheric Chlorine (EESC) has decreased by about 

10% in the polar regions from its peak level reached in the beginning of this century. This section 

assesses whether an increase in ozone is observed in the polar regions that can be attributed to the 

decrease in ODSs. Recent changes in understanding of polar ozone trends are discussed in the context of 

what has been discussed in previous assessments. The focus is on observed polar ozone changes. Future 

polar ozone evolution is discussed in detail in Section 3.5.

3.4.1 Polar Ozone Recovery in Previous Assessments

The WMO/UNEP 2006 Ozone Assessment Report (WMO, 2007; see Section 6.2.2) outlined in 

detail the different stages of current and future ozone: slowdown of ozone decline, turn around and onset 

of ozone increases, and full recovery from ODSs. The latter will be discussed in the context of future 

polar ozone in Section 3.5. WMO (2007) established that slowing and cessation of ozone decline had 

already occurred and that 1997 was the most likely turnaround year. That report also included predictions 

of a slow recovery of Antarctic column ozone, with an increase in springtime ozone of 5–10% between 

2000 and 2020, or 0.25–0.5%/year over that period. 

The WMO/UNEP 2010 Ozone Assessment Report (WMO, 2011) firmly established that for 

detection of the second stage of ozone recovery—the occurrence of statistically significant increases in 

ozone above previous minimum values due to declining EESC—it is required to separate dynamical from 
Chapter 3

3.28

chemical influences on ozone (Newman et al., 2006; Yang et al., 2008). A standard approach for 

detection that was discussed in WMO (2011, see Section 2.1.2; Box 3-2) is to use a multivariate 

regression model that quantifies the relation between ozone and different dependent variables that 

simultaneously describe natural and anthropogenic forcings. The long-term trend can either be described 

by fitting a piece-wise linear trend function (PWLT) or the EESC. For the PWLT, the turning point is 

typically defined at the EESC maximum. Alternatively, the turning point can also be derived from a 

break-point analysis of the ozone record (Yang et al., 2005, 2008; Chehade et al., 2014).

WMO (2011) also discussed the available regression studies, which at that time had focused on 

tropical and midlatitude ozone. However, analyzing polar ozone for long-term trends and signs of onset of 

ozone increases had not been performed before WMO (2011), as it is more complicated due to the need to 

include polar vortex dynamics, which results in larger year-to-year variability in polar regions than at 

midlatitudes and in the tropics. In WMO (2011), Antarctic trends were only briefly discussed, as 

essentially only one regression study was available at the time (Yang et al., 2008). Furthermore, that study 

only considered temperature as a dependent variable and focused on the first stage of ozone recovery, the 

leveling off of Antarctic ozone loss and reversal of the EESC trend from increasing during the 1980s and 

1990s to a decrease after 2000. It was concluded that the leveling off of Antarctic ozone since the late 

1990s could be attributed to changes in Antarctic stratospheric halogen loading.

In addition, WMO (2011) noted based on model studies that increases in greenhouse gas (GHG)

concentrations do not have a significant direct effect (due to radiative processes) on springtime Antarctic 

polar temperatures and ozone for the period up to 2100. Indirect effects of GHG on ozone via changes in 

vortex dynamics were not reported in WMO (2011). Furthermore, there are large uncertainties associated 

with the ozone recovery path, and model uncertainties rather than those of GHG scenarios dominate 

uncertainties in ozone recovery. Hence, it is unlikely that recent Antarctic stratospheric ozone changes 

were affected by increases in GHGs. See further Section 3.5 on the impact of GHGs on future Antarctic 

ozone recovery.

For the Arctic, WMO (2007) already noted that compared to the Antarctic, the Arctic shows 

larger interannual variability in springtime ozone and smaller ozone depletion. As a result, detection of 

changes in ozone due to decreases in EESC will likely take longer than in the Antarctic. For the Arctic, no 

slowing of a decline in ozone had been found. WMO (2011) reported little progress in assessing Arctic 

ozone recovery since WMO (2007). 

3.4.2 Long-Term Antarctic Ozone Trends 

3.4.2.1 VERTICALLY RESOLVED OZONE

Hassler et al. (2011a) assessed 25 years of ozonesonde measurements made at the South Pole 

station and presented an update and expansion of earlier South Pole ozonesonde studies (Hofmann et al., 

1997; Solomon et al., 2005; Hofmann et al., 2009). The study analyzed the height dependence of ozone 

loss rates throughout Antarctic spring (late August to late September) for five-year periods, which reduces 

the effect of year-to-year variability in ozone (Figure 3-14). The study concluded that ozone loss rates 

changed little over the period 1996–2010, although a small but statistically insignificant reduction in 

ozone loss rates after 2000 was identified. The lack of clear reduction in ozone loss rates (Figure 3-14) 

could be partly related to saturation of loss at certain pressure levels which results in the near-complete 

ozone destruction at pressure levels around 70 hPa (typically 50–100 hPa; see also Yang et al. (2008)). It 

thus may take some time for air masses at certain pressure levels to become “desaturated” with regard to 

ozone loss. Furthermore, the decrease in EESC during the period 2000–2010 is approximately 5–10%, 

depending on the choice of age of air (Newman et al., 2007), suggesting that no large decrease in ozone 

destruction can be expected to have occurred yet. Assuming a future linear relation between the reduction 

in EESC and ozone loss rates and assuming that future dynamical variability of the Antarctic stratosphere 

will remain similar to the variability observed during the last two decades as well as assuming that no 
Polar Ozone

3.29

major volcanic eruption will occur, Hassler et al. (2011a) find that a statistically significant reduction in 

South Pole ozone loss rates for August–September as measured by ozonesondes is only expected to occur 

at the end of the 2010–2020 period if the current decline in EESC continues unabated. They also noted 

that there are uncertainties with this methodology, in particular how to account for changes in greenhouse 

gas concentrations, which likely will affect future Antarctic stratospheric dynamics. Another complicating 

factor for the detection of height-dependent ozone increases is changes in stratospheric temperatures 

(cooling), which lead to trends in air density and layer thickness (McLinden and Fioletov, 2011).

Miyagawa et al. (2014) assessed ground-based ozone profile Dobson Umkehr measurements at 

the Antarctic coastal station Syowa (69.0°S, 39.6°E). Based on a multivariate regression method to 

account for Antarctic polar vortex dynamics, and consistent with Hassler et al. (2011a), they report a 

small but statistically insignificant increase in springtime Antarctic stratospheric ozone after 2001 over 

Syowa that can be attributed to decreasing EESC. They find that Antarctic vortex dynamics have a large 

impact on stratospheric ozone at Syowa, and conclude that differences in lower, middle, and upper 

stratospheric transport processes have different effects on lower, middle, and upper stratospheric 

Antarctic stratospheric ozone. Furthermore, they point at possible delays in upper stratospheric ozone 

recovery by both effects of the solar cycle, as well as by longer transport time of air masses to reach the 

upper stratosphere.

In summary, in situ measurements of the vertical distribution of Antarctic ozone do not yet show 

a significant reduction in ozone loss rates, and this is not expected to become apparent until 

approximately 2020. 

Figure 3-14. Vertical profile of 

ozone loss rates for five time 

periods (1986–1990, 1991–1995, 

1996–2000, 2001–2005 without 

2002, 2006–2010) based on 25

years of ozonesonde measurements taken at the South Pole, as 

determined by a linear fit to all 

available data for each pressure 

level between day 235 and 270 

(late August to end of September). 

Ozone loss rates are given in 

[ppmv/day], error bars represent 1-

σ uncertainties. After Hassler et al. 

(2011b).

3.4.2.2 SPRINGTIME TOTAL OZONE

Hassler et al. (2011b) analyzed October mean total ozone columns from four surface stations 

around Antarctica for the period 1966 to 2008. While these stations show a similar emergence of the 

ozone hole from 1960 to 1980, their records diverge after 1980, with annual mean differences between 

stations as large as 50 DU. By screening measurements based on whether they are obtained within or 

outside the vortex, ozone behavior over the last two decades for the four stations was found to be very 

similar. Similar conclusions have been reached for the Arctic stratosphere based on satellite data and 

methodologies (e.g., Kiesewetter et al., 2010). 
Chapter 3

3.30

Salby et al. (2011, 2012) presented the first claim of detection of the second phase of recovery of 

Antarctic ozone, i.e., a statistically significant increase in ozone due to declining EESC. They applied a 

two-parameter regression model to analyze annual springtime (September–November) Total Ozone 

Mapping Spectrometer (TOMS)/OMI total ozone over Antarctica poleward of 70°S (vortex core). Total 

ozone measurements were regressed against the upward Eliassen-Palm (EP) flux at 70 hPa, averaged 

poleward of 40°S during the period August–September, and the QBO, represented by tropical 30 hPa 

winds. Salby et al. (2011) reported a correlation (R2) of springtime vortex core total ozone variations by 

their two-parameter regression model of 0.96. By applying these regressions, dynamical processes that 

determine year-to-year variability in Antarctic vortex strength and ozone destruction can be removed 

from the total ozone record, leaving an ozone residual that can be probed for the presence of trends. A 

positive linear trend for the period 1996–2008 was reported with a statistical significance of 99.5% using 

a two-tailed t-test. Note that the results from Salby et al. (2011, 2012) cannot directly be compared to 

those of Hassler et al. (2011a), in part because they look at different springtime periods, and also because 

Salby et al. (2011, 2012) investigate a vortex-average total ozone amount, whereas Hassler et al. (2011a) 

investigate ozone profiles taken at one specific location.

Kuttippurath et al. (2013) presented more extensive multivariate regression analyses of Antarctic 

polar vortex total ozone for the period 1979–2010. They analyzed two different satellite total ozone data

sets (TOMS/OMI and MSR), as well as averaged ground-based Antarctic measurements of total ozone. 

They further applied the multivariate regression to three total ozone time series based on three different 

Antarctic ozone records: average total ozone inside the vortex and the vortex core, both based on passive 

tracer transport model simulations, as well as average total ozone for equivalent latitudes between 65°

and 90°S. Finally, they applied two different trend estimates to the total ozone time series: either the 

EESC or PWLT were used as fit parameters in the multivariate regression. Trends were calculated for 

the periods both before and after 2000. The multivariate regression model includes effects of the solar 

flux, QBO, stratospheric aerosols, the heat flux (or Eliassen-Palm flux), and the Antarctic oscillation (or 

Southern Annular Mode). Taking these effects into account, the three types of measurements, the three 

vortex definitions, and the two linear trend methods all show a statistically significant positive trend in 

Antarctic total ozone for the period 2000–2010. The recovery rates based on the PWLT trend estimates 

are approximately 25 DU/decade or 8%/decade, while the EESC fit provides an estimate of 

approximately 10 DU/decade or 3%/decade. Both trend estimates are significant at the 95% confidence 

level. Differences between PWLT and EESC trend estimates indicate that vortex dynamics are important 

and should be considered, consistent with findings from Kiesewetter et al. (2010) and Hassler et al. 

(2011a).

The correlation of the multivariate regression in Kuttipurrath et al. (2013) does not exceed 0.90 

(R2), which appears inconsistent with the 0.96 (R2) correlation found by Salby et al. (2011), despite the 

latter study being based on only two dependent variables. The cause of this discrepancy is currently 

unclear, but it should be kept in mind that although both studies include the same dependent variables 

(QBO and heat flux), they use different underlying base data (40 hPa tropical wind speed QBO and 

ECMWF ERA Interim heat flux in Kuttippurath et al. (2013); 30 hPa wind speed QBO and NCEP heat 

flux in Salby et al. (2011, 2012)). The time period over which total ozone data are averaged is also 

different (between September and November in the former case, over October in the latter case), as well 

as the length of the period under consideration (1996–2008 for Salby et al. (2011, 2012), and 2000–2010 

for Kuttippurath et al. (2013)). In addition, these studies do not address several other sources of 

uncertainty, like regression parameter choices, regressor errors, and sensitivity to the time period over 

which the regressors are taken.

In summary, although findings of multivariate regression studies of springtime Antarctic total 

ozone are consistent with a beginning of ozone recovery, i.e., they report increases in ozone after 2000, 

uncertainties in measurements and regressors as well as uncertainties in statistical analyses preclude the 

definitive conclusion that Antarctic stratospheric ozone is increasing due to declining ODSs. 
Polar Ozone

3.31

3.4.3 Long-Term Ozone Trend in the Arctic

Previous WMO/UNEP Ozone Assessments have noted that the large degree of interannual 

variability in meteorological conditions, and the strong dependence on the start and end dates used for the 

analysis render robust determination of ozone trends in the Arctic extremely problematic. The picture 

remains largely unchanged for this Assessment. Although several studies have placed the exceptional 2011 

Arctic spring ozone values in context through comparisons with multiyear (in some cases multidecade) 

ozone data sets (Manney et al., 2011; Balis et al., 2011; Hurwitz et al., 2011; Arnone et al., 2012; Adams et 

al., 2012; Kuttippurath et al., 2012; Lindemaier et al., 2012; Isaksen et al., 2012; Pommereau et al., 2013; 

Strahan et al., 2013), few have specifically quantified long-term changes in Arctic lower stratospheric 

ozone. It is thus not possible to make a definitive statement about Arctic ozone trends at this time.

3.5 FUTURE CHANGES IN POLAR OZONE

Future changes in ozone can be assessed with models of varying complexity (parametric, twoand three-dimensional models). In recent years the state-of-the-art for assessing stratospheric ozone 

changes in a climate context has moved to comprehensive three-dimensional chemistry-climate models 

(CCMs). A major milestone for the CCM community was the CCMVal-2 model intercomparison report 

(SPARC CCMVal, 2010) that preceded the WMO/UNEP 2010 Ozone Assessment (WMO, 2011) and 

informed the conclusions therein. Progress with CCMs since has been continuous and new studies have 

either consolidated or added details to results from CCMVal-2. No recent study has challenged our 

fundamental understanding of how ozone will develop in the future, based on decreasing ODSs and 

continued evaluation of climate change sensitivities.

No intercomparison on the scale of CCMVal-2 has been carried out in time for this Ozone 

Assessment. The SPARC lifetime assessment (SPARC, 2013) has reassessed lifetimes of a number of 

ODSs using observations and models. The CCMs that contributed to the modeling part of the lifetime 

assessment have been updated since CCMVal-2 and will be used for future integrations and collaborative 

efforts, including the Chemistry-Climate Model Initiative (CCMI). Even though the modeling part of the 

lifetime assessment is extremely valuable for attributing past ozone changes by providing additional 

model integrations covering the recent past, it is investigating time-slice experiments for the future 

(Chipperfield et al., 2014), which are not directly comparable to the transient integrations projecting 2100 

ozone levels in CCMVal-2. However, changed lifetimes of ODSs can be used in an indicative way and in 

updated model integrations. If key lifetimes are significantly increased, projected ozone recovery will be 

delayed. Table 6.1 in SPARC (2013) summarizes the new lifetimes for CFC-11 and CFC-12, among 

others. The recommended lifetimes increased from 45 to 52 years for CFC-11 and from 100 to 102 years

for CFC-12. This lifetime adjustment does not suggest a major change of return and recovery dates 

reported in WMO (2011). Commonly the lifetime information of a species is used in conjunction with the 

assumed surface fluxes to calculate surface mixing ratios. The time-dependent surface mixing ratios are 

subsequently used as boundary conditions for CCM integrations. Four CCMs used in CCMVal-2 

(SPARC CCMVal, 2010) and subsequently presented in WMO (2011), i.e., CMAM, GEOSCCM, 

UMSLIMCAT, and WACCM, compared the impact of changing from the WMO (2011) mixing ratio 

time series of ODSs to the SPARC (2013) recommendations (Figure 3-15). In Figure 3-15 the thick black 

line is the multi-model mean (MMM) polar total ozone from the four CCMs as contributed to WMO 

(2011) using Special Report on Emissions Scenarios (SRES) A1B scenario for well-mixed GHG and the 

WMO (2011) recommended ODS concentrations. The thin colored lines are pairwise differences added to 

the MMM for each of the four models. The models used Representative Concentration Pathway (RCP)

6.0 (GEOSCCM, WACCM, and CMAM) or RCP 4.5 (UMSLIMCAT) scenarios for well-mixed GHG in 

the updated runs. The turquoise shading is the one standard deviation interannual variability for March or 

October respectively added/subtracted to the MMM. Note that the differences are small and that they lie
Chapter 3

3.32

Figure 3-15. The thick black line is showing multi-model mean (MMM) polar total ozone (60°-90°; left: 

Northern Hemisphere March, right: Southern Hemisphere October) from four CCMs (see legend) that 

contributed to WMO (2011) using SRES A1B for well-mixed GHG and the WMO (2011) recommended 

ODS concentrations. The thin colored lines are pairwise differences (“old-new” ODS scenarios; “old”: 

WMO, 2011; “new”: SPARC, 2013) added to the MMM for each of the four models. The “new” 

integrations used RCP 6.0 (CMAM, GEOSCCM, and WACCM) or RCP 4.5 (UMSLIMCAT) for well-mixed 

GHG. The turquoise shading is the one standard deviation interannual variability for March (left) and 

October (right) from GEOSCCM added/subtracted to the MMM. Horizontal dashed lines are 1980 values.

largely within the one standard deviation range, thus suggesting that the ODS lifetime change had no 

significant impact on the polar ozone recovery in either the Northern or Southern Hemisphere. However it 

should be noted that this “by chance ensemble” provides a MMM that is returning late to 1980s ozone 

values in the Southern Hemisphere, compared to the full WMO (2011) MMM. 

3.5.1 Factors Controlling Polar Ozone Amounts

Section 3.3 describes our level of understanding of processes influencing polar ozone changes. CCMs 

are an attempt to utilize this process understanding to simulate (in a comprehensive way) chemistry-climate 

interactions, allowing us to make projections into the future. Such models are of increasing complexity (e.g.,

consider more and more Earth system components with higher complexity). Like all models, CCMs have to 

compromise in terms of complexity and resolution, to provide the length of integrations required to evaluate 

interactions between composition and climate on longer timescales. Continuous validation of the model 

performance for the recent past is a key to our judgment of model projections, even though good model 

performance for the past does not necessarily guarantee reliable predictions.

Two main factors determine future ozone amounts: How fast are the stratospheric chlorine and 

bromine amounts changing, and what is the impact of increasing GHGs on ozone? Box 3-2 summarizes 

many important aspects relating to this issue. To illustrate the success of the Montreal Protocol, it is 

useful to consider so-called “world avoided” simulations. Since the last Assessment, Garcia et al. (2012) 

used an updated version of the Whole Atmosphere Community Climate Model (WACCM) model, 

illustrating the expected strong impact of heterogeneous chemistry on the ozone budget and quantifying 

the ozone loss avoided by the Montreal Protocol. Their results are in good agreement with earlier studies 

that have been reported in WMO (2011). 

For tracing the success of the Montreal Protocol, previous WMO/UNEP ozone assessments have 

introduced the concepts of ozone recovery and return. As emphasized in Section 3.4, ozone recovery 

relates to the physical effects ODSs have on stratospheric ozone. When ODSs no longer significantly 
Polar Ozone

3.33

affect ozone chemistry, full ozone recovery has been achieved. For this consideration, transport effects, 

e.g., the removal of chlorine-containing species from the stratosphere, are most important (indicated with 

a downward pointing arrow in Box 3-2). 

Return relates to the achievement of a threshold ozone amount that was observed in the past. 

When ODS abundances decline in the stratosphere, ozone will increase. In addition ozone will increase 

due to a cooling of the upper stratosphere that is caused by increasing GHGs (Box 3-2). Simultaneously,

changes in meridional transport would modify the high-latitude ozone budget, with current CCMs 

indicating a strengthening of the BDC for GHG increases. This has been extensively discussed in WMO 

(2011) and it was concluded that, “A stronger BDC would decrease the abundance of tropical lower 

stratospheric ozone, increase poleward transport of ozone, and could reduce the atmospheric lifetimes of 

long-lived ODSs and other trace gases.” A detailed discussion of the recent findings regarding the 

evolution of the BDC is presented in Chapter 4 of the present Assessment.

Baumgaertner et al. (2010) add a nuance to the general picture by pointing out that upper 

stratospheric NOx enhancement due to a stronger BDC would cause additional ozone loss, but that the 

ozone loss would be more or less canceled by more poleward ozone transport. The added effects of 

decreasing ODSs, increasing GHGs, and changing meridional transport will lead to polar ozone return 

dates that are earlier than the recovery dates. Arguably the evolution of return dates, in particular in total 

ozone, is more straightforward and easier to measure than the exact timing of recovery. 

Even though two important factors determining future ozone are well understood, namely, the 

ozone change due to decreasing ODSs and the stratospheric cooling due to GHGs, many mechanisms 

exist that are uncertain in their future development. One of the uncertainties lies with the PSCs (Box 3-2). 

How will they develop under climate change? Will there be more PSCs due to radiatively controlled 

cooling, or less due to dynamically induced warming? Hurwitz and Newman (2010) looked at the 

development of the PSC area in projections using the Goddard Chemistry-Climate Model (GEOSCCM). 

In their model, future trends in the PSC area in October over Antarctica were negative, thus “helping”

ozone return. In addition, Deushi and Shibata (2011) investigated the impact of GHGs on ozone recovery. 

In their model, resolved wave forcing is decreased in spring over Antarctica, due to an earlier breakdown 

of the polar vortex in the future. If this is a verifiable result, it would indicate a potential mechanism for 

earlier ozone return dates. More examples are discussed in Sections 3.3.3 and in 3.5.3.1. 

3.5.2 Long-Term Projection of Polar Ozone Amounts

A multi-model mean (MMM) total ozone time series relative to a particular year is a relatively 

robust representation of an “average” behavior for the future. An uncertainty range can be described by 

the inter-model standard deviation that is usually large. The large standard deviations arise because the 

models are potentially biased and their meteorology will differ in the same nominal year. However each 

individual model ozone time series is referenced to its own climatological base period. Therefore a large 

spread does not mean that models disagree on the general temporal development of ozone. The spread is 

merely highlighting that the models differ.

Following considerations in Austin et al. (2010a) and WMO (2011), Figure 3-16 presents a 

MMM anomaly total ozone time series. In Figure 3-16, 1980 ozone values are indicated with a dashed 

line. The thick red line indicates the MMM total ozone anomaly for the Arctic in March (Figure 3-16, top) 

and for Antarctica in October (Figure 3-16, bottom). The spread is indicated by a two standard deviation 

interval (gray shading). The MMM time series indicate an earlier return date with respect to 1980 values 

for the Arctic (near 2030) than for the Antarctic (near 2050). Note that the CCMVal-2 integrations have 

been performed with a particular Special Report on Emission Scenario (SRES) climate changes scenario 

(A1B). For the recent IPCC report (AR5; IPCC, 2013), SRES scenarios have been superseded by 

Representative Concentration Pathways (RCP) scenarios (van Vuuren et al., 2011). Both SRES and RCP 

are descriptions of the possible evolution of climate forcings that depend on assumptions, e.g., how 

energy consumption will develop in the future, and a range of possibilities is considered. This scenario
Chapter 3

3.34

Box 3-2. Factors Determining Future Polar Ozone

Ozone-depleting substances (ODSs) are the drivers of polar ozone loss. Due to the Montreal Protocol and 

its Amendments, ODS amounts are decreasing and ozone will recover. Here, we discuss factors that influence 

details of the recovery process. Factors influencing future ozone amounts in high latitudes at different heights are: 

changes in meridional transport (indicated by bold open arrows), temperature changes from increased long-lived 

GHGs (indicated by blue or red shaded areas), and chemical effects (the future potential to form PSCs that can 

activate available halogens, e.g., chlorine and to a lesser extent bromine, and changes in temperature-dependent 

reaction rates). Each effect is changing ozone at certain heights. A combination of all effects is manifested in the 

total ozone, the vertically integrated amount of ozone.

The sketch below shows polar latitudes (with the North or South Pole to the left) versus altitude. The 

altitude scale is roughly indicated by the position of the polar tropopause (black dashed line). Stratospheric cooling

and tropospheric warming are indicated with color-shaded areas. Poleward transport and generally descending 

motion, as well as air exchange between the stratosphere and the troposphere, are indicated with bold open arrows. 

The blue half ellipse shows the region where PSCs occur when temperatures are low enough. The green half ellipse 

denotes the ozone maximum in partial pressure or number density. 

Changes in transport under climate change: Models predict a strengthening of the Brewer-Dobson 

circulation (BDC) for increased long-lived GHG concentrations. Increased poleward transport would provide a gain 

in polar ozone. Increased downward transport and more efficient air exchange between the stratosphere and the 

troposphere would provide a more efficient removal mechanism for halogen-containing species, the main driver of 

ozone destruction.

Changes in temperature under climate change: The increase of long-lived GHGs has led to a warming 

in the troposphere and cooling in the stratosphere. Many processes and reactions that change ozone are temperature 

dependent. In colder conditions more PSCs could be formed, thus providing a greater potential for halogen 

activation and ozone destruction. Furthermore, PSC formation depends on the availability of water vapor; future 

trends in water vapor are uncertain. 

Chemical effects: They are closely coupled to the transport and temperature changes. In the lower 

stratosphere they depend on the availability of halogen-containing species and the occurrence, amount, and timing of 

PSCs. In the upper stratosphere, chlorine chemistry also plays a role. However, lower temperatures there slow down 

the gas-phase destruction of ozone, thus resulting in more ozone. In addition, changes in N2O and CH4

concentrations could affect ozone chemistry as well. 

Because all effects above contribute to changes in polar total ozone, it is more difficult to monitor total 

ozone recovery than return. Total ozone recovery relies on the concept that ozone amounts are no longer 

significantly affected by halogen chemistry and full recovery would imply that halogens of anthropogenic origin no 

longer play a role in determining ozone amounts. Total ozone return is a simpler milestone to monitor, answering 

the question “When do we reach a level of ozone that we had in the past?” Altitude
Polar Ozone

3.35

uncertainty will be discussed further in Section 3.5.3. The blue line in Figure 3-16 is derived from 

observations (see also Figure 3-4) indicating the overall qualitative agreement with model results (see also 

Chapter 2 of this Assessment).

Austin et al. (2010a) compared 1960 and 1980 baseline projections for CCMVal-2, highlighting 

the issue of a later return to 1960 values. One factor limiting our confidence in the timing of return date 

projections is the large inter-model spread, even though Austin et al. (2010a) presented some evidence 

that the situation had improved since CCMVal-1. Note however that this Assessment uses a recent 

climatological base period and indicates the 1980-return date separately (black dashed lines in Figure 3-16).

Certain aspects of the inter-model spread in return dates can be understood by investigating 

physical properties of the models. Note however that the spread in return dates is smaller than the 

envelope in Figure 3-16 (see WMO, 2011 for details). Strahan et al. (2011) evaluated CCMVal-2 model 

results by characterizing transport performance and the resulting vortex Cly (80°S, 50hPa) concentrations. 

Results showed that models with no diagnosable chlorine chemistry deficiencies showed a quasi-linear 

relationship between polar vortex Cly in 2005 and the projected return dates. As expected from our 

chemical understanding of ozone loss, models with high Cly in 2005 showed late return dates, with return 

dates to 1980 values ranging from around 2040 to 2070.

Figure 3-16. The solid red line is showing multi-model mean (MMM) polar total ozone anomalies in 

percent (60°-90°; top: Northern Hemisphere March, bottom: Southern Hemisphere October) relative to a 

1998 to 2008 base period. The MMM values predict a return date relative to the year 1980 in the Northern 

Hemisphere before the middle of the 21st century (near 2030, indicated with black dashed lines) and in 

the SH for around the middle of the 21st century (near 2050). The spread between the CCMs used for 

estimating the MMM values is indicated by the gray ranges (two standard deviations). Observations are 

indicated by the blue lines showing ozone anomalies derived from ozone values presented in Figure 3-4 

of this Assessment.

Observations
Chapter 3

3.36

3.5.3 Uncertainties of Future Polar Ozone Changes

We can distinguish three different contributors to uncertainty: internal variability of the 

atmosphere, model uncertainty, and scenario uncertainty. Depending on the quantity, internal variability 

can be a small or large source of uncertainty. In contrast model uncertainty is commonly significant. 

Scenario uncertainty is less problematic in the near future (e.g., for the next twenty years), because 

different RCPs diverge more for the far future than for the near future. Consequently scenario uncertainty 

increases rapidly for the later decades, because we do not know which path will be chosen in the far 

future. 

Charlton-Perez et al. (2010) estimated uncertainty contributions in multi-model mean projections 

of annual and global mean total ozone. They use global and annual mean data to keep the contribution of 

internal variability small. The spatial and temporal averaging mitigates the magnitude of internal 

variability that would be far more dominant for, e.g., seasonal or monthly mean data. Indications are that 

scenario uncertainties are increased in the late 21st century with RCP (used in Coupled Model 

Intercomparison Project Phase 5, CMIP5) compared to SRES A1B (used in Coupled Model Intercomparison Project Phase 3 (CMIP3) and WMO, 2011) scenarios. In the following subsections, we will 

discuss aspects of internal variability/model uncertainty and scenario uncertainty in more detail.

3.5.3.1 INTERNAL VARIABILITY AND MODEL UNCERTAINTY

Stratospheric cooling from increasing carbon dioxide levels will likely alter the forcing from 

upward-propagating tropospheric waves, which affect cold and warm winters, and thus internal variability

itself, in different ways. Overall increasing wave activity in the stratosphere, as predicted by some climate 

models, would make dynamically quiet periods less frequent. However, as already mentioned in Section 

3.3.3.2, amplified tropospheric wave activity does not necessarily imply enhanced wave fluxes into the 

stratosphere. Consequently the evolution of polar stratospheric temperatures over the next hundred years 

has a number of uncertainties. 

Chemistry-climate models (CCMs) do not reproduce the derived long-term changes in Arctic 

VPSC (Hitchcock et al., 2009). VPSC is an integrated measure of polar temperatures (see Section 3.2.2). 

Although there is a suggestion that multidecadal variability in VPSC extremes can happen through internal 

variability (Rieder and Polvani, 2013), the question remains open as to whether more extremely cold 

Arctic winters are projected in the future (e.g., Hitchcock et al., 2009). Langematz et al. (2014) analyzed 

future VPSC in transient and timeslice simulations, finding an increase in VPSC until the middle of the 21st

century and a drop afterwards.

One of the uncertainties in modeling polar ozone amounts arises from ongoing changes in the 

Northern Hemisphere land or ocean cryospheres, which might impact the high-latitude stratosphere. Both 

the Eurasian snow cover and the Arctic sea ice loss have the potential to modulate the upward 

propagation of planetary waves. Increased Eurasian snow cover during autumn amplifies wave trains 

propagating upward into the polar stratosphere (e.g., Fletcher et al., 2009; Orsolini and Kvamstø, 2009; 

Smith et al., 2010). Arctic sea ice loss first leads to a strong warming of the lower troposphere in autumn, 

when ocean heat loss is strong, but ultimately changes synoptic and global circulation patterns. An 

observational study contrasting recent decades with low or high sea ice extent (Jaiser et al., 2012) and a 

case study with a high-resolution coupled ocean-atmosphere model for the year 2007 characterized by a 

very large summer sea ice loss (Orsolini et al., 2012), have shown enhanced stratospheric planetary waves 

in early winter. The springtime response to observed or projected sea ice decrease was also investigated 

using models of various complexity, i.e., a coupled atmosphere-ocean model in Screen et al. (2013), a 

CCM in Cai et al. (2012), and a CCM coupled to an ocean in Scinocca et al. (2009), the three studies 

qualitatively agreeing on a springtime stratospheric cooling. 

Given the small number of studies with models of various complexity, the high internal 

atmospheric variability in winter, the different sea ice decrease scenarios, and the potential seasonality of 
Polar Ozone

3.37

the response, further studies are needed to determine whether there exists a real multi-model consensus on 

the impact on stratospheric variability.

Model biases pose an ongoing challenge for modelers and influence the estimate of model 

uncertainty. Biases can have far reaching consequences for model performance. For example a 

temperature bias will impact the formation of PSCs and thus influence chemical ozone destruction 

significantly. WMO (2011) and in more detail Austin et al. (2010b) showed that many models 

participating in CCMVal-2 underestimated the present-day ozone hole area in the projection runs and that 

the future development of the ozone hole area differed significantly between models. In a case study,

Brakebusch et al. (2013) showed an improvement in modeled ozone in their nudged CCM for the winter 

2004–2005 when temperatures for heterogeneous chemistry reactions were reduced by 1.5 K, indicating, 

for instance, less chlorine activation in the model under observed conditions. This indicates that 

underlying climate model biases affect the performance of a CCM regarding the simulation of future 

polar ozone.

3.5.3.2 SCENARIO UNCERTAINTY

As discussed in WMO (2011) and detailed in Eyring et al. (2010), the relative contributions of 

ODSs and GHGs on projected ozone changes can be estimated with CCM experiments in which different 

forcings are fixed, for example an integration from 1960 to 2100 with fixed ODSs. For instance, the role 

of increasing GHGs in speeding up ozone return was investigated by Oman et al. (2010). Using CCMVal2 model results, they showed that decreasing halogens and declining upper atmospheric temperatures (due 

to GHGs), contribute almost equally to increases in modeled upper stratospheric ozone (Box 3-2 and 

accompanying description). A similar conclusion is reached by Plummer et al. (2010) studying 

sensitivities in one particular model that is included in Oman et al. (2010).

The recent CMIP5 exercise focused on broader climate change issues in support of the IPCC AR5 

(IPCC, 2013). Models with and without interactive chemistry participated. Models without interactive 

chemistry had the option of using an ozone climatology derived from observations, CCMVal-2 data, and 

complementary data (Cionni et al., 2011). Eyring et al. (2013) compared the ozone evolution in CMIP5 

models with interactive ozone to the climatology constructed for non-interactive models (Cionni et al., 

2011), thus achieving some insight in the scenario uncertainty due to different climate change scenarios

(Figure 3-17). For the Northern Hemisphere (NH) polar region in March, the total ozone column for all RCP 

scenarios agrees well until ~2025. After the year 2025 ozone modeled with RCP6.0 agrees well with the 

CCMVal-2 data. This is expected, because RCP6.0 is close to the SRES A1B forcing used in CCMVal-2.

Figure 3-17. The 1980 

baseline-adjusted total ozone 

column time series from 1960 

to 2100 for the CMIP5 CHEM 

multi-model mean (colored 

lines) and CCMVal-2 multimodel mean ozone database

(black line) for Northern 

Hemisphere (left) and 

Southern Hemisphere (right) 

spring polar regions. All time 

series by construction go 

through 0 in 1980. The RCP 

2.6, RCP 4.5, RCP6.0, and 

RCP 8.5 are shown in blue, 

light blue, orange, and red, 

respectively. The corresponding color-coded stippled areas show the 95% confidence interval of the 

CHEM multi-model mean simulations. Derived from Figure 6 in Eyring et al. (2013). 
Chapter 3

3.38

For RCP8.5, ozone increases fastest and rises significantly above the 1980 amounts. For RCP2.6, ozone 

increases slower after ~2040 compared to RCP6.0 and the ozone enhancement relative to 1980 amounts is 

smaller. The situation is less clear in the Southern Hemisphere (SH). The RCP-driven models show 

higher ozone values compared to the CCMVal-2 multi-model mean during October in the SH polar 

region. All ozone trajectories stay close together until ~2030. After ~2040, distinct scenario differences 

are apparent, with RCP8.5 showing the largest ozone amounts in later years. Note that there are some 

clear differences between the different scenarios with respect to SRES A1B. Obviously many aspects 

influence scenario uncertainty. Revell et al. (2012) evaluated the ozone response to different nitrous oxide 

(N2O) and methane (CH4) scenarios in a number of model sensitivity studies. Large N2O concentrations 

were associated with smaller ozone increases, whereas larger CH4 concentrations were associated with 

larger ozone increases. All this highlights the importance of the chosen concentration pathway for the 

discussion of recovery dates.

In addition, scenario uncertainty includes events we cannot foresee and that can potentially affect 

stratospheric ozone: for example a major volcanic eruption or the decision to use stratospheric aerosol for 

solar radiation management (i.e., “geoengineering”). Details about possible geoengineering activities and 

the issue of potential impact to global stratospheric ozone and climate are also discussed in Chapters 2, 4,

and 5 of this Assessment.

Austin et al. (2013) discuss how past volcanic 

eruptions have changed ozone in the stratosphere using 

a version of the GFDL CCM. The more recent eruptions 

(El Chichón and Mt. Pinatubo) resulted in a globally 

averaged total ozone decrease (Figure 3-18, top) caused 

by severe ozone depletion in the lower stratosphere 

(confirmed by many earlier studies as well, including 

the CCMVal-2 Report). The earlier eruptions (Krakatau, 

Santa Maria, and Agung) resulted in globally averaged 

total ozone increases (Figure 3-18, top). The difference 

in ozone response is caused by the changed chemistry 

due to the increased availability of chlorine. However, 

changes in polar latitudes are more complex and depend 

on the meteorology as well (Figure 3-18, middle and 

bottom). Past volcanic aerosol episodes (only two events 

are well described based on a wealth of measurements) 

can be used as templates for assessing possible future 

impacts, highlighting that the impact on ozone at global 

scale will depend on stratospheric halogen loading and 

on many other factors in polar latitudes. 

Figure 3-18. Simulated total ozone anomalies for the 

global mean (top), the Arctic mean (middle), and the 

Antarctic mean (bottom) within two years of each of the 

five major volcanic eruptions since 1860. The results are 

plotted relative to the mean for the two-year period prior 

to the date that the aerosol surface area density 

significantly exceeded the background value at the 63-

hPa level. The mean annual cycle has been subtracted 

from the results. The error bars denote twice the 

standard deviation of the monthly values for the twoyear pre-volcanic period. Extension of Figure 11 in 

Austin et al. (2013).
Polar Ozone

3.39

Tilmes et al. (2008, 2009) investigated the relationship between ozone depletion and chlorine 

activation to estimate how sulfuric acid aerosol might affect polar ozone. In their model, an injection of 

sulphur large enough to compensate surface warming caused by the doubling of atmospheric CO2 would 

strongly enhance Arctic ozone depletion during the present century for cold winters and would cause a 

considerable delay in Antarctic ozone recovery. Pitari et al. (2014) presented results from two general 

circulation models (GCMs) and two CCMs. On average, the models simulate a decrease in globally 

averaged ozone up to about 2 DU during the middle of the century (2040–2049) due to an increase in 

sulfate aerosol surface area density similar to conditions a year after the Mt. Pinatubo eruption. Enhanced 

heterogeneous chemistry on sulfate aerosols leads to an ozone increase in low and middle latitudes, 

whereas enhanced heterogeneous reactions in polar regions and increased tropical upwelling lead to a 

reduction of stratospheric ozone.

A further uncertainty for polar ozone amounts is the change in natural halogen-containing source 

gases levels, and in particular in very short-lived substances (VSLS). Considerations include the 

characterization of VSLS sources in models (Hossaini et al., 2013) and how the sources will change under 

climate change, how VSLS and their breakdown products will be transported (Hossaini et al., 2012), and 

how efficient the brominated species originating from VSLS will be in depleting ozone (Tilmes et al., 

2012; Braesicke et al., 2013; Oman and Douglass, 2014). For example, Braesicke et al. (2013) diagnose in 

their model a possible sensitivity of total ozone to an increase in VSLS, with up to 20 DU ozone loss in 

the Southern Hemisphere polar region. Of course this sensitivity depends on the chlorine loading and will 

change in the future as well. 

In summary, while we have a sound understanding of processes determining future polar ozone 

(Box 3-2), there are significant uncertainties in determining recovery and return dates. Part of the 

uncertainty can be understood through physical considerations (for example transport and chemical 

lifetimes), and are expected to be reduced in the future. Other uncertainties, in particular in the scenarios, 

are beyond our direct control and we can only gauge possibilities.

3.6 KEY MESSAGES OF CHAPTER 3 FOR THE DECISION-MAKING COMMUNITY

3.6.1 Recent Polar Ozone Changes

An Antarctic ozone hole has continued to form each year during the period 2010–2013. The 

continued occurrence of an Antarctic ozone hole was expected because the amount of ozone-depleting 

substances in polar regions has decreased only moderately (by about 10%) over the last decade. The 

period was also characterized by enhanced variability in Antarctic polar vortex dynamics that had an 

impact on the year-to-year variations of vortex-averaged total ozone during the springtime. 

In the Arctic, exceptionally low ozone abundances were observed within the vortex during the 

spring of 2011. These low ozone values were due to an unprecedented degree of chemical ozone loss, 

coupled with very weak transport of ozone to the lower stratospheric polar vortex. This exceptional event 

was caused by unusual meteorological conditions in the Arctic during the winter 2010/2011, characterized 

by persistent low temperatures and a strong isolated polar vortex. With the present availability of 

stratospheric satellite measurements, the extent of polar ozone destruction processes throughout the 

winter could be evaluated from the evolution of key species involved in chemical ozone depletion, such 

as hydrogen chloride (HCl), chlorine monoxide (ClO), and nitric acid (HNO3). The persistence of low 

temperatures led to the formation of widespread and vertically extensive polar stratospheric clouds, which 

induced strong chlorine activation and denitrification in the 2011 Arctic vortex. These mechanisms led to 

severe chemical ozone destruction between 16 and 22 km altitude, with 60–80% of the vortex ozone at 

~18–20 km removed by early April (Figure 3-19). 

State-of-the-art chemical transport models (CTMs) reproduce the observed ozone values during 

spring 2011 well, confirming that the extremely low ozone values resulted from known processes, not 
Chapter 3

3.40

unusual or unexpected chemistry. The occurrence of this extreme event has thus not challenged our 

fundamental understanding of the processes controlling polar ozone.

The derived ozone loss in the Arctic spring 2011 was comparable to ozone losses observed in 

Antarctica in the 1980s (Figure 3-19). Because transport from low to high latitudes is more prominent in 

the Northern Hemisphere (NH) than in the Southern Hemisphere (SH), background ozone levels in the 

Arctic are ~100 DU higher than in the Antarctic. As a result, although the evolution of Arctic ozone and 

related constituents in spring 2011 more closely followed that characteristic of the Antarctic than ever 

before, the springtime total ozone values remained considerably higher than those reached in a typical 

year in the Antarctic. In addition, the areal extent of the 2011 Arctic vortex was only ~60% the size of a 

typical Antarctic vortex, thus the low-ozone region was more spatially confined (Figure 3-19).

Figure 3-19. Left: Representative spring profiles of observed vortex-average chemical ozone loss (in 

parts per million by volume, ppmv). The light gray curves indicate the results for individual Arctic spring 

periods (1992–2010). The red curve indicates the result in Arctic spring 2011. Also shown is an indicative 

range of ozone loss for typical Antarctic spring periods, illustrated by the loss that has been derived from 

ozone observations for a relatively weak early Antarctic ozone hole (1985, upper limit of the gray shading) 

and the loss in a strong Antarctic ozone hole (2003, lower limit of the gray shading). Right: Maps of total 

column ozone from the Aura satellite’s Ozone Monitoring Instrument (OMI) for the Antarctic (top; ozone 

hole situation 2010) and Arctic (bottom; strong ozone column reduction in March 2011). Overlaid black 

contours mark the size and shape of the polar vortex on the 460 K potential temperature surface. 

Different charts are adapted from Manney et al. (2011). The figure shows that the degree of chemical 

ozone loss in the Arctic in spring 2011 was in the range of observations from weak Antarctic ozone holes 

(within uncertainties; left panel), but that the abundance of ozone above the Arctic was still substantially 

larger than in Antarctic ozone holes, mainly because the undisturbed ozone layer is thicker in the Arctic 

compared to the Antarctic, due to natural differences in transport between the two hemispheres. 
Polar Ozone

3.41

If similar conditions were to arise again in the Arctic while stratospheric chlorine loading remains 

high, similarly severe chemical ozone loss would take place. Uncertainties in current climate models 

preclude confident quantification of the likelihood of repeated episodes of extensive Arctic ozone 

depletion in the present or future climate (a point also made in Section 3.5).

3.6.2 Understanding of Polar Ozone Processes

Generally, there have been no major changes in our understanding of polar ozone loss processes 

since WMO (2011). The scientific knowledge of polar chemical and dynamical processes was already 

based on a large body of research. As mentioned, numerical model studies of the atmosphere using CTMs 

reproduce observed chemical polar ozone depletion and its variability well. 

Recent work has improved the detailed understanding of polar ozone processes (such as the 

formation mechanism of polar stratospheric clouds (PSCs), in particular nitric acid trihydrate (NAT) 

particles), validated previous assumptions, and reduced uncertainty. The formation of NAT PSCs is a 

prerequisite for denitrification by sedimenting particles, which prolongs seasonal ozone loss. A more 

accurate representation of NAT PSC nucleation and particle characteristics leads to better model 

simulations of denitrification and hence ozone loss. 

The uncertainty range in the photolysis rate of dichlorine peroxide (ClOOCl, the ClO dimer), a 

key parameter in polar chemical ozone loss, has been reduced significantly, providing a better constraint 

for the simulation of polar ozone in late winter and spring. The overall understanding of chemical 

processes involved in polar ozone loss is well developed and remains unchanged. 

It is now clear that the ClO + BrO catalytic cycles are responsible for about 50% of the ozone loss 

in the polar lower stratosphere, with the contribution being slightly larger in the Arctic, where the overall 

depletion is less. Recent work has better quantified the contribution from very short-lived substances

(VSLS) to the overall stratospheric bromine budget. In the photochemically aged air masses of the polar 

lower stratosphere, both long-lived and short-lived brominated species will have decomposed to inorganic 

bromine. Therefore, the source of bromine is not important, but any contribution of VSLS to bromine will 

translate into a contribution to polar ozone loss, which is proportional to the fraction of overall bromine 

that comes from the breakdown of VSLS. 

Regarding polar stratospheric dynamics, the very cold Northern Hemisphere winter of 2010/2011 

expanded the range of stratospheric dynamical variability seen in the Arctic over the past decades and 

provided a new extreme test case for models (i.e., CTMs as well as chemistry-climate models, CCMs). 

The current understanding of the mechanisms that determine planetary wave driving (or the lack 

of it) of the polar stratosphere is still incomplete, but some progress has been made. It is particularly 

important to understand the origin of very strong polar vortex events that drive the ozone loss, either 

short-duration intense cooling episodes as observed in January 2010, or prolonged cooling like that 

observed during the late winter and spring 2011. Several recent observational studies have shown that 

tropospheric highs (e.g., blockings) can lead to either warming or cooling of the Northern Hemisphere 

polar stratosphere, depending upon their geographical location. 

3.6.3 Recovery of Polar Ozone

Recent WMO/UNEP ozone assessments (WMO, 2007, 2011) have firmly established that 

intensification of Antarctic springtime ozone depletion is no longer occurring. The stabilization of 

Antarctic polar ozone loss occurred most likely after 1997. The previous ozone assessment (WMO, 2011) 

concluded that it was not yet possible to confidently state that there had been increases in Antarctic 

springtime stratospheric ozone, nor that these could be attributed to decreasing ozone-depleting 

substances (ODSs). 
Chapter 3

3.42

Current investigations indicate a small increase of 10–25 DU (3–8%) after 2000 in springtime 

Antarctic ozone observations, after taking year-to-year variability into account. This slight rise in 

Antarctic springtime ozone content is consistent with expectations considering the decrease in ODSs. 

However, uncertainties in separating chemical from dynamical effects on Antarctic springtime 

ozone, combined with only a slow decline in ODSs and the strong dependence of results on the start and 

end dates used for the analyses, prevent—for now—unambiguously attributing the decrease in ozone 

depletion to decreasing ODSs. 

The expected continued slow decline in ODSs will make attribution of decreasing Antarctic 

springtime ozone depletion to decreasing ODSs possible as time progresses. 

3.6.4 Future Changes in Polar Ozone

A major milestone for the CCM community was the CCMVal-2 model intercomparison report 

(SPARC CCMVal, 2010) that preceded the WMO/UNEP 2010 assessment (WMO, 2011) and informed 

the conclusions therein. Progress with CCMs since has been continuous and new studies have either 

consolidated or added details to results from CCMVal-2. No recent study has challenged our fundamental 

understanding of how ozone will develop in the future, based on decreasing ODSs and continued 

evaluation of climate change sensitivities.

Arctic and Antarctic ozone is predicted to increase as a result of the expected reduction of ODSs 

due to regulations of the Montreal Protocol. A return to values of ozone in high latitudes similar to those 

of the 1980s is likely during this century, with Northern Hemisphere (NH) polar ozone predicted to 

recover earlier as compared to the Southern Hemisphere (SH) polar ozone (Figure 3-16). Uncertainties in 

the assessed return dates result in particular from incomplete knowledge of future greenhouse gas (GHG) 

levels and corresponding climate change consequences (Figure 3-17), and incomplete description of 

processes and their feedbacks in numerical prediction tools, including CCMs. 

Updated ODS lifetimes (SPARC, 2013) have only a minor effect on previously estimated dates of 

ozone return to 1980 values. Lifetimes of ODSs have been reassessed and some lifetimes have changed 

since the last Assessment. Our physical understanding and first CCM studies do not indicate any 

significant changes for ozone return dates due to the changed ODS lifetimes.

Climate change is an important driver for polar ozone amounts late this century. Due to a larger 

sensitivity of NH dynamical processes, climate change is expected to have a larger impact on ozone in the 

Arctic than in the Antarctic. However, we do not know how climate change forcings will develop in 

detail. The possibilities have been gauged by using four different “Representative Concentration 

Pathways (RCPs)” adopted by IPCC (5th Assessment Report, 2013) in climate model studies (Coupled 

Model Intercomparison Project Phase 5, CMIP5) (Figure 3-17). Conversely, it is now evident that 

considering ozone in a comprehensive way is important for climate projections. 

Another driver for the development of ozone are VSLS emissions, especially brominated species. 

There are large uncertainties about current-day VSLS emissions and the sensitivity of polar ozone loss to 

changes in Bry requires further characterization. Nevertheless, some model studies indicate a sensitivity of 

total ozone sensitivity to increased VSLS emissions, with up to 20 DU ozone loss in the Southern 

Hemisphere polar region. How VSLS sources will change in a changing climate is yet unknown. 

Major volcanic eruptions can perturb stratospheric ozone. Volcanic effects on stratospheric ozone 

have been simulated by several CCMs. Observations and model simulations show that recent major 

eruptions (e.g., El Chichón in 1982 and Mt. Pinatubo in 1991) resulted in globally averaged total ozone 

decreases caused by severe ozone destruction in the lower stratosphere. In contrast, model results suggest 

that earlier eruptions (e.g., Krakatau in 1883, Santa Maria in 1902, and Agung in 1963) resulted in 

globally averaged total ozone increases. The difference in the response of ozone to the earlier and later 

volcanos is attributable to catalytic ozone destruction enabled by the increased availability of 

stratospheric chlorine. Hence, in the next few decades while stratospheric chlorine content remains high, 

ozone depletion could worsen in the event of large volcanic eruptions. 
Polar Ozone

3.43

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Chapter 3

3.60

Appendix 3A

Satellite Measurements Useful for Polar Studies

Table 3A-1. Main satellite measurements of ozone and related constituents in polar regions.

Instrument Record Length Latitudinal 

Range

Constituents Vertical 

Resolution*

References

Total Column

TOMS on 

Nimbus-7, 

Meteor-3

TOMS on 

ADEOS, Earth 

Probe 

Nov 1978 – Dec 

1994

Jul 1996 – Dec 

2006

Near-global 

coverage 1

Ozone

SO2, aerosol

Total column Herman et al., 1991; 

Stolarski et al., 1991; 

Newman et al., 1991; 

Newman et al., 1997; 

Bodeker et al., 2001

AIRS on Aqua May 2002 –

present

Global 

coverage

Ozone

CH4

Total column Divakarla et al., 2008

TOU on 

Feng-Yun 3A

May 2008 –

present

Near-global 

coverage 1

Ozone Total column Dong et al., 2009; 

Bai et al., 2013

TANSO-FTS on 

GOSAT

Apr 2009 –

present

Near-global 

coverage 1

Ozone

CH4, NO2, 

HNO3, NO2, SO2

Total column Ohyama et al., 2012

OMPS-NM on 

Suomi-NPP

Nov 2011 –

present

Near-global 

coverage 1

Ozone

SO2, aerosol

Total column Kramarova et al., 2014; 

Seftor et al., 2014

Total Column and Profiles

SBUV on 

Nimbus 7

SBUV on 

NOAA-9, 

NOAA-11, 

NOAA-14, 

NOAA-16, 

NOAA-17, 

NOAA-18, 

NOAA-19

Nov 1978 – Jun 

1990

Feb 1985 –

present

Near-global 

coverage 1

Ozone Total column & 

profiles (nadir)

Between 16 hPa 

and 40 hPa – top 

of the atmosphere

Vertical resolution 

between 6 km and 

15 km

Bhartia et al., 2013; 

McPeters et al., 2013

SCIAMACHY on 

Envisat

Aug 2002 – Apr 

2012

Global 

coverage

Ozone

NO2, BrO, SO2, 

OClO, aerosol

Total column & 

profiles 

(nadir/limb)

~10 km – ~60 km

Vertical resolution 

3–5 km

Bovensmann et al., 

1999; 

Piters et al., 2006

OMI on 

EOS-Aura

Aug 2004 –

present

Near-global 

coverage 1

Ozone

NO2, BrO, SO2, 

OClO, aerosol

Total column & 

profiles (nadir)

Troposphere – top 

of atmosphere (18 

layers)

Vertical resolution 

6–15 km

Bhartia and 

Wellemeyer, 2002; 

Veefkind et al., 2006; 

Liu et al., 2010; 

Kroon et al., 2011
Polar Ozone

3.61

TES on 

EOS-Aura

Aug 2004 –

present

Global 

coverage

Ozone

CH4, HNO3

Total column & 

profiles 

(nadir/limb)

0 km – 33 km

Vertical resolution 

~6–7 km

Beer, 2006; 

Bowman et al., 2006; 

Nassar et al., 2008

IASI on 

Metop-A

IASI on 

Metop-B

Nov 2006 –

present

Nov 2012 –

present

Global 

coverage

Ozone

CH4, HNO3

Total column & 

profiles (nadir)

Tropospheric layer 

– top of 

atmosphere

Vertical resolution 

~7 km

Coheur et al., 2005; 

Wespes et al., 2009; 

August et al., 2012

GOME-2 on 

Metop-A

GOME-2 on 

Metop-B

Jan 2007 –

present

Dec 2012 –

present 

Near-global 

coverage 1

Ozone

NO2, BrO, SO2, 

OClO, aerosol

Total column & 

profiles (nadir)

Surface – top of 

atmosphere

Vertical resolution 

~7–15 km

van Roozendael et al., 

2012; 

van Peet et al., 2014

OMPS-NP on 

Suomi-NPP

Nov 2011 –

present

Near-global 

coverage 1

Ozone

SO2, aerosol

Total column & 

profiles (nadir)

Between 16 hPa 

and 40 hPa – top 

of the atmosphere

Vertical resolution 

6−15 km

Seftor et al., 2014

Profiles

LIMS on Nimbus 

7

Nov 1978 – May 

1979

64°S – 84°N Ozone

H2O, HNO3, NO2

Profiles (limb)

Cloud top – ~0.01 

hPa

Vertical resolution 

~3.7 km

Gille and Russell, 1984; 

Girard and Louisnard, 

1984; 

Remsberg et al., 2007; 

Remsberg et al., 2010

SAM II on 

Nimbus 7

Nov 1978 – Dec 

1993

64°S – 80°S 

and

64°N – 80°N 

2

(coverage 

changed over 

the lifetime of 

the 

instrument)

PSCs, aerosol Profiles (solar 

occultation)

Surface – ~160 km

Vertical resolution 

~0.5 km

Kent and McCormick, 

1984; 

McCormick et al., 1981; 

McCormick and Trepte, 

1986

SAGE I on AEMBFeb 1979 – Nov 

1981

79°S – 79°N 2 Ozone

NO2, aerosol

Profiles (solar 

occultation)

Tropopause – ~55 

km

Vertical resolution 

1 km

McCormick et al., 1984; 

Kent and McCormick, 

1984; 

McCormick et al., 1989

SAGE II on 

ERBS

Oct 1984 – Jul 

2005

80°S – 80°N 2 Ozone

NO2, H2O, 

aerosol

Profiles (solar 

occultation)

Tropopause – ~55 

km

Vertical resolution 

1 km

Cunnold et al., 1989; 

McCormick et al., 1989;

Damadeo et al., 2013

MLS on UARS Sep 1991 – Mar 

2000

From 34° on 

one side of 

the equator to 

80° on the 

other side –

alternating 

every ~36 

days

Ozone

ClO, HNO3, H2O

Profiles (limb)

100 hPa – 0.22 

hPa; 

Vertical resolution 

3.5–5 km in the

stratosphere, 

5–8 km in the 

mesosphere

Barath et al., 1993; 

Waters et al., 1993; 

Livesey et al., 2003
Chapter 3

3.62

CLAES on 

UARS

Oct 1991 – Apr 

1993

From 34° on 

one side of the 

equator to 80° 

on the other –

alternating 

every ~36 

days

Ozone

N2O, CFC-11, 

CFC-12, CH4, 

H2O, NO, NO2, 

HNO3, ClONO2, 

HCl, N2O5, 

PSCs, aerosol

Profiles (limb)

10 km – 60 km 

Vertical resolution 

~2.5 km

Roche et al., 1993; 

Kumer et al., 1996; 

Massie et al., 1996

HALOE on 

UARS

Oct 1991 – Nov 

2005

80°S – 80°N 2 Ozone

NO2, H2O, NO, 

CH4, HCl, HF, 

PSCs, aerosol

Profiles (solar 

occultation)

Cloud top –

~0.005 hPa

Vertical resolution 

~2.3 km

Russell et al., 1993; 

Schoeberl et al., 1995; 

Hervig et al., 1997

POAM II on 

SPOT-3

Sep 1993 – Nov 

1996

55°N – 73°N, 

63°S – 88°S 2

Ozone

NO2, H2O, PSCs, 

aerosol

Profiles (solar 

occultation)

~5 km – ~60 km

Vertical resolution 

~1.5 km

Glaccum et al., 1996; 

Lumpe et al., 1997 ; 

Bevilacqua et al., 1997 ; 

Fromm et al., 2003

ILAS on ADEOS Oct 1996 – Jun 

1997

57°N – 71°N, 

64°S – 88°S 2

Ozone

HNO3, NO2, 

N2O, CH4, H2O, 

PSCs, aerosol

Profiles (solar 

occultation)

~10 km – top of 

atmosphere

Vertical resolution 

~2 km

Sugita et al., 2002; 

Jucks et al., 2002; 

Nakajima et al., 2002; 

Yokota et al., 2002

POAM III on 

SPOT-4

Mar 1998 – Dec 

2005

55°N – 73°N, 

63°S – 88°S 2

Ozone

NO2, H2O, PSCs, 

aerosol

Profiles (solar 

occultation)

~5km – ~60km

Vertical resolution 

~1.5 km

Lucke et al., 1999; 

Lumpe et al., 2002; 

Fromm et al., 2003

OSIRIS on Odin Nov 2001 –

present

Near-global 

coverage 1

Ozone

NO2, BrO, 

aerosol

Profiles (limb)

Cloud tops – 55 

km

Vertical resolution 

1.5 km in UTLS, 2 

km higher up

Llewellyn et al., 2004; 

Brohede et al., 2007; 

McLinden et al., 2007

SMR on Odin Nov 2001 –

present

~83°S –

~83°N

Ozone

N2O, HNO3, 

H2O, ClO, NO, 

NOy

Profiles (limb)

Vertical resolution 

2.5–3.5 km

Urban et al., 2005; 

Barret et al., 2006

SAGE III on 

Meteor-3M 3

Feb 2002 – Dec 

2005

50°S – 30°S,

50°N – 80°N 2

Ozone,

NO2, H2O, 

OClO, aerosol

Profiles (solar 

occultation)

Tropopause – ~55

km

Vertical resolution 

1 km

Wang et al., 2006

MIPAS on 

Envisat

Jun 2002 – Apr 

2012

Global 

coverage

Ozone

N2O, NO, NO2, 

HNO3, N2O5, 

ClONO2, CFCs, 

HOCl, ClO, H2O, 

H2O2, CH4, CO

Profiles (limb)

~8 km (20/40 km; 

middle/upper 

atmosphere mode) 

– 72 km (100 km; 

middle/upper 

atmosphere mode)

Vertical resolution 

from ~2 km to ~8 

km (depending on 

altitude)

Fischer et al., 2008; 

von Clarmann et al., 

2009

GOMOS on 

Envisat

Aug 2002 – Apr 

2012

Global 

coverage

Ozone

NO2, H2O, PSCs, 

aerosol

Profiles (stellar 

occultation)

~15 km – ~100 km

Vertical resolution 

2–3 km

Kyrölä et al., 2004; 

Bertaux et al., 2010
Polar Ozone

3.63

ILAS II on 

ADEOS II

Apr 2003 – Oct 

2003

57°N – 71°N 

and 64°S –

88°S 2

Ozone

HNO3, NO2, 

N2O, CH4, H2O, 

ClONO2, N2O5, 

CFC-11, CFC12, PSCs, aerosol

Profiles (solar 

occultation)

~10 km – top of 

atmosphere

Vertical resolution 

~1.5 km

Sugita et al., 2006; 

Irie et al., 2006

ACE-MAESTRO 

on SCISAT

Feb 2004 –

present

Near-global 

coverage 2

Ozone

NO2, PSCs, 

aerosol

Profiles (solar 

occultation)

5 km – 35 km

Vertical resolution 

~1.2 km

McElroy et al., 2007; 

Nowlan et al., 2007

ACE-FTS on 

SCISAT

Feb 2004 –

present

Near-global 

coverage 2

Ozone

H2O, CH4, N2O, 

NO2, NO, NO3, 

HCl, HF, CO, 

CFC-11, CFC12, N2O5, 

ClONO2, CH3Cl, 

SF6, H2O2, CCl4, 

HCFCs, ClO, 

HOCl

Profiles (solar 

occultation)

~5 km – 95 km

Vertical resolution 

3–4 km

Bernath et al., 2005; 

Boone et al., 2005; 

Jones et al., 2012

MLS on 

EOS-Aura

Aug 2004 –

present

82°S – 82°N Ozone

BrO, CH3Cl, 

ClO, CO, H2O, 

HCl, HNO3, 

HO2, OH, OCl, 

N2O, SO2

Profiles (limb)

215 hPa – 0.02 

hPa

Vertical resolution 

~3 km in 

stratosphere, 

degrading to 4–6 

km for pressures 

of 0.1 hPa or less

Waters et al., 2006; 

Livesey et al., 2006; 

Froidevaux et al., 2008; 

Santee et al., 2008

HIRDLS on 

EOS-Aura

Jan 2005 – Mar 

2008

63°S – 80°N Ozone

HNO3, CFC-11, 

CFC-12, NO2, 

N2O5, H2O, N2O, 

NO2, ClONO2, 

aerosol

Profiles (limb)

10 km – 55 km

Vertical resolution 

~1 km

Gille et al., 2008; 

Kinnison et al., 2008; 

Nardi et al., 2008

CALIOP on 

CALIPSO

Apr 2005 –

present

82°S – 82°N PSCs, aerosol Profiles (nadir)

Surface – 40km

Vertical resolution 

30–60 m 

Winker et al., 2009; 

Pitts et al., 2009

OMPS-LP on 

Suomi-NPP

Nov 2011 –

present

Near-global 

coverage 1

Ozone Profiles (limb)

10 km – 60 km

Vertical resolution 

2 km

Rault and Loughman, 

2013

* Vertical resolution only applies to ozone.

1 Apart from polar night latitudes.

2 Because of their particular viewing geometry and measurement technique, solar occultation instruments do not provide global 

coverage on a daily basis.

3 A replica of the SAGE III Meteor-3M instrument is scheduled to be deployed on the International Space Station (ISS) in 2015. 

Although SAGE-III/ISS will measure ozone, water vapor, and a few other atmospheric constituents (NO2, NO3, and OClO, as 

well as aerosols and clouds), its coverage will be focused on middle and low latitudes.
CHAPTER 4

Stratospheric Ozone Changes and Climate

Lead Authors:

J.M. Arblaster

N.P. Gillett

Coauthors:

N. Calvo

P.M. Forster

L.M. Polvani

S.-W. Son

D.W. Waugh

P.J. Young

Contributors:

E.A. Barnes

I. Cionni

C.I. Garfinkel

E.P. Gerber

S.C. Hardiman

D.F. Hurst

J.-F. Lamarque

E.-P. Lim

M.P. Meredith

J. Perlwitz

R.W. Portmann

M. Previdi

M. Sigmond

N.C. Swart

J.-P. Vernier

Y. Wu

Chapter Editors:

L.J. Gray

D.W.J. Thompson
[Formatted for double-sided printing.]

From: 

WMO (World Meteorological Organization), Scientific Assessment of Ozone Depletion: 2014, Global 

Ozone Research and Monitoring Project – Report No. 55, 416 pp., Geneva, Switzerland, 2014.

This chapter should be cited as: 

Arblaster, J.M., and N.P Gillett (Lead Authors), N. Calvo, P.M. Forster, L.M. Polvani, S.-W. Son, D.W. 

Waugh, and P.J. Young, Stratospheric ozone changes and climate, Chapter 4 in Scientific Assessment of 

Ozone Depletion: 2014, Global Ozone Research and Monitoring Project – Report No. 55, World 

Meteorological Organization, Geneva, Switzerland, 2014.
CHAPTER 4

STRATOSPHERIC OZONE CHANGES AND CLIMATE

Contents

SCIENTIFIC SUMMARY ........................................................................................................................... 1

4.1 INTRODUCTION AND SCOPE ........................................................................................................... 3

4.1.1 Summary of the Previous Ozone Assessment............................................................................... 3

4.1.2 Scope of the Chapter ..................................................................................................................... 3

4.2 OBSERVED CHANGES IN STRATOSPHERIC CONSTITUENTS THAT RELATE 

TO CLIMATE ....................................................................................................................................... 4

4.2.1 Long-Lived Greenhouse Gases and Ozone-Depleting Substances ............................................... 4

4.2.2 Stratospheric Water Vapor ............................................................................................................ 4

4.2.3 Stratospheric Aerosols................................................................................................................... 6

4.2.4 Ozone............................................................................................................................................. 6

4.3 OBSERVED AND SIMULATED CHANGES IN STRATOSPHERIC CLIMATE............................. 6

4.3.1 Stratospheric Temperature............................................................................................................. 6

4.3.1.1 Observations..................................................................................................................... 6

4.3.1.2 Simulated Past and Future Changes ............................................................................... 11

4.3.2 Stratospheric Meridional Circulation .......................................................................................... 14

4.3.2.1 Observations................................................................................................................... 14

4.3.2.2 Simulated Past and Future Changes ............................................................................... 16

4.3.3 Stratospheric Zonal Flow ............................................................................................................ 18

4.4 EFFECTS OF PAST CHANGES IN STRATOSPHERIC OZONE ON THE TROPOSPHERE AND 

SURFACE ............................................................................................................................................ 19

4.4.1 Tropospheric Circulation Effects ................................................................................................ 19

4.4.1.1 Surface Impacts .............................................................................................................. 25

4.4.1.2 Ocean Impacts ................................................................................................................ 27

4.4.1.3 Sea Ice Impacts............................................................................................................... 29

4.4.2 Radiative Effects ......................................................................................................................... 30

4.4.3 Chemistry Effects........................................................................................................................ 32

4.5 EFFECTS OF FUTURE CHANGES IN STRATOSPHERIC OZONE ON THE TROPOSPHERE 

AND SURFACE .................................................................................................................................. 33

4.5.1 Tropospheric Circulation Effects ................................................................................................ 34

4.5.1.1 Surface Impacts .............................................................................................................. 38

4.5.1.2 Ocean Impacts ................................................................................................................ 38

4.5.1.3 Sea Ice Impacts............................................................................................................... 39

4.5.1.4 The World Avoided by the Montreal Protocol............................................................... 39

4.5.2 Radiative Effects ......................................................................................................................... 41

4.5.3 Chemistry Effects........................................................................................................................ 41

POLICY-RELEVANT INFORMATION................................................................................................... 43

REFERENCES............................................................................................................................................ 45

Stratospheric Ozone and Climate

4.1

SCIENTIFIC SUMMARY

Since the last Assessment, new research has better quantified the impact of stratospheric ozone changes 

on climate. Additional model and observational analyses are assessed which examine the influence of 

stratospheric ozone changes on stratospheric temperatures and circulation, Southern Hemisphere 

tropospheric circulation and composition, surface climate, oceans, and sea ice.

• Stratospheric ozone changes are the dominant driver of observed globally averaged long-term 

temperature changes in the lower stratosphere. Between 1979 and 1995 global mean lower stratospheric 

temperature decreased by about 1 K but has since remained approximately constant.

○ Models broadly reproduce the evolution of global mean lower stratospheric temperature change. 

Stratospheric ozone changes are the dominant driver of these changes, with volcanic aerosol driving 

episodic warming, and greenhouse gas increases having only a minor contribution.

○ Observed mid- and upper-stratospheric temperatures decreased from 1979 to 2005, but the magnitude of 

the cooling is uncertain. A newly reprocessed data set of satellite measurements exhibits substantially 

different cooling trends compared to the existing data set. Models indicate that increasing greenhouse 

gases, as well as ozone changes, both made comparable contributions to observed cooling in the mid and 

upper stratosphere.

○ There was little overall change in global lower stratospheric water vapor concentration between 2000 

and 2012, based on satellite measurements, which show a decrease between 2000 and 2004 followed by 

an increase to 2012.

○ The observed cooling of the Antarctic lower stratosphere since 1979 during austral spring is consistent 

with the average simulated cooling in models forced with observed ozone depletion. There is a large 

range in the magnitude of the simulated cooling, with models that underestimate the ozone depletion also 

underestimating the temperature trends.

• Climate models consistently predict a long-term increase in the strength of the Brewer-Dobson 

circulation due to greenhouse gas increases, with important impacts on stratospheric and tropospheric 

composition.

○ The predicted increase in the strength of the Brewer-Dobson circulation extends throughout the depth of 

the stratosphere.

○ Observations of changes in temperature, ozone, and trace gases over the past three to five decades are 

suggestive of increased upwelling in the tropical lower stratosphere, consistent with a strengthening of 

the shallow branch of the Brewer-Dobson circulation predicted by models. There is large uncertainty in 

changes in the deep branch of the Brewer-Dobson circulation inferred from observations in the mid and 

upper stratosphere.

○ Stratospheric ozone recovery and an acceleration of the Brewer-Dobson circulation in the future would 

both tend to increase the global tropospheric ozone burden. The projected net changes in tropospheric 

ozone and other compounds vary regionally and are scenario and model dependent.

• Stratospheric temperature changes due to Antarctic ozone depletion are very likely the dominant 

driver of the observed changes in Southern Hemisphere tropospheric circulation in summer over 

recent decades, with associated surface climate and ocean impacts.

○ The contribution of Antarctic ozone depletion to the observed increase in the Southern Annular Mode 

index in austral summer is substantially larger in most models than the contribution from greenhouse gas 

increases over the past three to five decades. An increase in this index corresponds to a decrease in 

atmospheric pressure at high latitudes, an increase at midlatitudes, and a poleward shift of the 

midlatitude jet. The role of ozone depletion is largest in summer. Observations and models suggest 

smaller Southern Annular Mode trends in other seasons.

○ Stratospheric ozone depletion has likely contributed to the observed expansion of the Southern 

Hemisphere Hadley Cell in austral summer.
Chapter 4

4.2

○ Climate models simulate a poleward shift of the Southern Hemisphere midlatitude maximum in 

precipitation and a moistening of the subtropics in response to stratospheric ozone depletion in austral 

summer. There is some evidence of a consistent pattern of trends in observations.

○ Observational and modeling studies present a broadly consistent picture of the ocean’s response to 

surface wind stress changes, which have likely been substantially caused by stratospheric ozone changes, 

with intensification of the subtropical ocean gyres and the meridional overturning circulations, and a 

subsurface warming. The impact of these wind stress changes on oceanic carbon uptake remains 

uncertain. The role of ocean eddies, which modify the ocean circulation and temperature response to 

wind stress changes, is better understood than at the time of the last Ozone Assessment, but remains a 

source of uncertainty.

○ The influence of stratospheric ozone depletion on Antarctic sea ice increases reported in the last Ozone 

Assessment is not supported by a number of new coupled modeling studies. These suggest that ozone 

depletion drives a decrease in Southern Hemisphere sea ice extent and thus did not lead to the small 

observed increase. However, there is low confidence in this model result because of large uncertainties 

in the simulation of Antarctic sea ice.

○ No robust link between stratospheric ozone changes and Northern Hemisphere tropospheric climate has 

been found, consistent with the conclusions of the previous Ozone Assessment.

• There is further evidence that in austral summer over the next 50 years, Antarctic stratospheric ozone 

recovery and increases in greenhouse gases will have opposite effects on the Southern Hemisphere 

tropospheric circulation, with associated surface climate and ocean impacts.

○ Ozone recovery is expected to drive a weakening and equatorward shift of the midlatitude jet, while 

increases in greenhouse gases are expected to drive a strengthening and poleward shift of the jet. Under a 

low greenhouse gas emissions scenario, ozone recovery is expected to dominate the effect of greenhouse 

gas increases on Southern Hemisphere tropospheric circulation in austral summer to give a weakening 

and equatorward shift of the midlatitude jet over the next 50 years, whereas in a high emissions scenario 

the jet is projected to continue to strengthen and shift poleward.

○ An equatorward shift in the Southern Hemisphere Hadley Cell boundary and extratropical rainfall in 

summer is simulated in response to ozone recovery. These changes offset a scenario-dependent fraction 

of projected greenhouse-gas induced changes in these variables.

○ Simulations from multiple models indicate that if the concentrations of ozone-depleting substances 

(ODSs) had continued to increase in the absence of the Montreal Protocol, the enhanced ozone depletion 

from uncontrolled ODSs would be expected to have led to substantial additional cooling in the Antarctic 

polar stratosphere, with associated changes in Southern Hemisphere circulation and rainfall patterns.

• New estimates of global mean ozone radiative forcing due to emissions of ozone-depleting substances, 

which account for stratospheric ozone change and its indirect effect on tropospheric ozone, indicate a 

stronger surface cooling effect than that due to stratospheric ozone changes alone.

○ The overall global mean ozone radiative forcing from the effects of ODS emissions on both tropospheric 

and stratospheric ozone is assessed to be −0.15 (−0.3 to 0) watts per square meter (W m-2) in 2011. 

Approximately three quarters of this results from ozone changes in the stratosphere.

○ Models indicate that ODS-induced stratospheric ozone depletion has acted to decrease tropospheric 

ozone. This ODS-driven decrease in tropospheric ozone contributes to the overall negative ozone 

radiative forcing, although the magnitude is uncertain.

○ The radiative forcing due to observed decreases in stratospheric ozone concentration alone is estimated 

to be −0.05 W m-2 (−0.15 to 0.05) W m-2 in 2011. A rapid adjustment to radiative forcing may also arise 

from cloud changes, resulting from the circulation changes driven by ODS-induced ozone depletion. The 

radiative effect of this cloud adjustment may be of a larger magnitude than the non-adjusted forcing.

○ Uncertainty in future lower stratospheric ozone trends in the tropics precludes a confident assessment of 

the sign of future stratospheric ozone radiative forcing. Current models give a range of stratospheric 

ozone radiative forcing of −0.05 to +0.25 W m-2 in 2100 under a high greenhouse gas emissions 

scenario, which is generally suggestive of a slight warming contribution relative to present.
Stratospheric Ozone and Climate

4.3

4.1 INTRODUCTION AND SCOPE

4.1.1 Summary of the Previous Ozone Assessment

Chapter 4 of the 2010 Ozone Assessment (Forster and Thompson et al., 2011) assessed 

stratospheric changes and their influence on climate. The chapter considered the tropospheric response to 

stratospheric change induced by greenhouse gases (GHGs), solar variability, and volcanic eruptions, as 

well as ozone. New data sets and improved simulations allowed an improved characterization of lower 

stratospheric temperature trends, and the influence of both natural and human factors was identified. The 

evolution of lower stratospheric temperature was described, with progressive cooling from 1960 to the 

late 1990s followed by a period with approximately constant temperature. Based on updated data sets the 

observed cooling was found to have occurred in the tropics as well as the extratropics and to have been 

similar at all latitudes in the annual mean. Ozone decreases were assessed to be the dominant driver of the 

observed long-term lower stratospheric cooling, with volcanic eruptions causing episodic warming. 

Temperature trends in the mid and upper stratosphere were assessed to be relatively uncertain, due to the 

existence of only a single reconstruction of satellite observed mid- and upper-stratospheric temperature 

available at the time.

The 2010 Ozone Assessment described an upward trend in stratospheric water vapor from 1980 

to around 2000, followed by an abrupt decrease that was assessed to be sustained through to 2009 based 

on measurements available at the time. An increase of stratospheric aerosol concentrations of 4–7% yr-1

between the late 1990s and 2009 was reported, though the causes of the trend were not clear, with both 

volcanic sources and increased coal burning cited as possible contributors.

The radiative impact of stratospheric ozone on climate was concluded to be smaller than had 

previously been thought. The chapter concluded that much of the observed southward shift of the Southern 

Hemisphere tropospheric midlatitude jet in summer was due to Antarctic ozone depletion, which in turn 

had driven trends in surface winds and temperature over Antarctica. It was concluded with somewhat less 

confidence that Antarctic ozone depletion had contributed to the observed increase in Antarctic sea ice 

extent, a southward shift of the Southern Hemisphere storm track and associated precipitation, a warming 

of the subsurface Southern Ocean, and decreases of carbon uptake over the Southern Ocean. No link 

between Arctic ozone depletion and tropospheric circulation had been established.

Projected changes in stratospheric temperature were discussed, with GHGs driving a cooling, 

moderated by ozone increases driven by this cooling itself and by decreasing concentrations of ozonedepleting substances (ODSs). The opposing effects of ozone recovery and GHG increases on the latitude 

of the Southern Hemisphere midlatitude jet in summer were discussed, and the net effect of these forcings 

was assessed to be uncertain. The chapter reported that climate models simulate an increase in the 

Brewer-Dobson circulation (BDC) in response to GHG increases, consistent with earlier assessments. It 

was concluded that stratospheric ozone recovery would increase the transport of ozone into the 

troposphere.

4.1.2 Scope of the Chapter

The previous chapters of this report have described and assessed past and projected future 

changes in stratospheric ozone. This chapter assesses new research since the 2010 Ozone Assessment on 

the impact of those changes on climate. To facilitate easy comparison with the 2010 Ozone Assessment, 

this chapter will follow a similar structure to Chapter 4 of that Assessment (Forster and Thompson et al., 

2011). Stratospheric ozone changes, together with changes in other stratospheric constituents, directly 

affect the radiative budget of the stratosphere, causing changes in stratospheric temperature and 
Chapter 4

4.4

circulation, which in turn influence tropospheric climate. Therefore after assessing observed variations in 

stratospheric constituents that relate to climate (Section 4.2), the chapter will continue to assess simulated 

and observed variations in stratospheric temperature and circulation, with a focus on attribution of 

observed changes to variations in ozone and other drivers (Section 4.3). The chapter will then assess the 

influence of stratospheric ozone changes on the troposphere, surface, and ocean, as requested by the 

Parties to the Montreal Protocol. In 1987 when the Montreal Protocol was signed, the impacts of 

stratospheric ozone depletion on tropospheric climate were not generally known, but over the past fifteen 

years an increasingly mature body of research on these impacts has developed. While the 2010 Ozone 

Assessment also considered the tropospheric response to other stratospheric changes, including changes 

in stratospheric water vapor, stratospheric aerosol, and solar irradiance variations, these topics were 

comprehensively assessed in the recently published Fifth Assessment Report of the Intergovernmental 

Panel on Climate Change (IPCC, 2013). For this reason this chapter will focus on the influence of 

stratospheric ozone change, with the influence of other stratospheric changes on climate discussed only 

briefly for context. Sections on the influence of stratospheric ozone on the troposphere in the past 

(Section 4.4) and future (Section 4.5) will start by considering ozone-induced effects on tropospheric 

circulation and resulting climate impacts, followed by sections considering radiative effects and chemical 

effects in turn.

4.2 OBSERVED CHANGES IN STRATOSPHERIC CONSTITUENTS THAT RELATE TO 

CLIMATE

The stratospheric constituents considered in this section impact climate directly through radiative 

effects and indirectly through their influence on stratospheric ozone. We review and assess observed 

variations in these constituents to inform our understanding and attribution of changes in stratospheric 

temperature and circulation.

4.2.1 Long-Lived Greenhouse Gases and Ozone-Depleting Substances

Carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and ODSs are all gases of 

tropospheric origin that impact climate both directly by absorbing and emitting long-wave radiation and 

indirectly by impacting stratospheric ozone. ODSs, N2O, and CH4 are source gases for compounds that 

deplete stratospheric ozone, whereas changes in CO2 impact ozone through changes in stratospheric 

temperature and circulation. 

Recent measurements and growth rates for ODSs and N2O are covered in Chapter 1 of this report, 

with a summary of recent growth rates shown in Tables 1-1 and 1-12. The measurements and growth rates 

for CO2 and CH4 are covered in detail in the IPCC Fifth Assessment Report (Hartmann et al., 2013) and 

are briefly summarized here. The tropospheric abundance of CO2 was around 390.5 parts per million 

(ppm) in 2011, which is around 40% greater than in 1750, and the average annual increase in globally

averaged CO2 concentration from 1980 to 2011 was 1.7 ppm yr-1 (2.0 ppm yr-1 since 2001) (Hartmann et 

al., 2013). There are large year-to-year variations (from an annual increase of around 0.7 ppm in 1992 to 

2.9 ppm in 1998) that are primarily due to small changes in the balance between carbon fluxes from 

photosynthesis and respiration on land. Tropospheric CH4 abundance was around 1803 ppb in 2011, 

which is 150% greater than before 1750. There have been substantial changes in the growth rate of CH4

since 1980: there was an increase in the global-average annual abundance from 1980 to 1998, little 

change from 1999 to 2006, and an increase in atmospheric burden since 2007 (Ciais et al., 2013). 

4.2.2 Stratospheric Water Vapor

Stratospheric water vapor is important for Earth’s radiative balance (influencing stratospheric and 

tropospheric temperatures) and for stratospheric chemistry. Changes in stratospheric water vapor can alter 
Stratospheric Ozone and Climate

4.5

stratospheric ozone chemistry in several different ways: Water vapor is the main source of reactive 

hydrogen oxide molecules (HOx) that destroy ozone, and changes in water vapor alter stratospheric 

temperatures (and hence rates of chemical reactions) and the formation of polar stratospheric clouds. 

Changes in stratospheric water vapor can also impact the stratospheric circulation, as well as the 

tropospheric midlatitude jets (Maycock et al., 2013).

As discussed in the previous Ozone Assessment (Forster and Thompson et al., 2011), satellite 

measurements of lower stratospheric H2O from the early 1990s to the present show substantial variability, 

with a large (~ 0.6 ppmv) step-like decrease after 2001 followed by roughly constant values. In more recent 

years these measurements show an increase in both tropical and midlatitude lower stratospheric water vapor, 

and there is only a small net change between 2000 and 2012 both in the midlatitudes and in the tropics 

(Randel and Jensen 2013; Fueglistaler et al., 2013). These changes are observed in both balloon-borne and 

satellite measurements. Figure 4-1 compares balloon-borne measurements at Boulder, Colorado, with 

corresponding zonal mean satellite observations (Hurst et al., 2011). There are unresolved discrepancies 

between the balloon and satellite measurements over the period 1992–1996. An updated trend analysis of 

the full (1980–2010) Boulder record shows sensitivity to the time period considered for the trends (due to 

the large decadal variability, Figure 4-1) and to the altitude (Hurst et al., 2011). For the full 30-year period 

there is a net increase of 1.0 ± 0.2 ppm between 16–26 kilometers (which corresponds to around 0.75% yr-1). 

The principal sources of water vapor in the bulk of the stratosphere are entry through the tropical 

tropopause and CH4 oxidation. There is a small additional source from oxidation of molecular hydrogen 

(H2). In the extratropical lowermost stratosphere, an additional source of water vapor is quasi-horizontal 

(isentropic) transport across the subtropical tropopause and deep convection, while dehydration in the 

polar lower stratosphere is a sink. Long-term H2O trends are due to trends in the flux of water vapor 

entering the stratosphere and increased production of H2O from CH4 oxidation (for example, around 30% 

of the 1980–2010 increase in water vapor over Boulder can be attributed to increases in CH4; Fujiwara et 

al., 2010; Hurst et al., 2011). Many of the year-to-year and longer variations in the observational H2O 

record can be linked to observed changes in tropical tropopause temperatures but some discrepancies still 

exist (e.g., Schoeberl et al., 2012; Fueglistaler et al., 2013; Randel and Jensen, 2013). For example, the 

long-term trends cannot be reproduced with trajectory-based models based on observed changes in tropical

Figure 4-1. Water vapor anomalies in the Northern Hemisphere lower stratosphere (~16–19 km) from 

satellite sensors and in situ measurements normalized to 2000–2011. Approximately monthly balloonborne measurements (FPH = frost point hygrometer) of stratospheric water vapor from Boulder, Colorado,

at 40°N (green dots; green curve is 15-point running mean) averaged over 16–18 km and monthly means 

at 83 hPa for 30°N–50°N (black) determined from Halogen Occultation Experiment (HALOE) and 

Microwave Limb Sounder (MLS) satellite sensors. Updated from Figure 2.5 of Hartmann et al. (2013), 

which is updated from Solomon et al. (2011).

-1.5

-1.0

-0.5

0.0

0.5

1.0

Anomaly (ppm)

1980 1985 1990 1995 2000 2005 2010

Year

-40

-30

-20

-10

0

10

20

30

Anomaly (%)

HALOE+MLS: 30°N-50°N

NOAA FPH: Boulder (40°N)
Chapter 4

4.6

tropopause temperatures. It is still unclear whether the inability to model the observed trends is due to the 

large uncertainties in the observed stratospheric water vapor and tropical tropopause temperatures (e.g., 

Wang et al., 2012), uncertainties in the models, or whether the models have missing mechanisms.

4.2.3 Stratospheric Aerosols

Stratospheric aerosols influence climate in many ways, including shortwave radiative forcing 

(with surface cooling following an increase in stratospheric aerosols), changes in circulation caused by 

differential (vertical or horizontal) heating, and by changing stratospheric ozone with its associated 

radiative and circulation impacts. Observed changes in stratospheric aerosols are discussed in Section 

2.3.4 of Chapter 2 of this Assessment. Briefly, the eruption of Mt. Pinatubo in 1991 was the last major 

volcanic eruption and the current stratospheric aerosol concentrations are much lower than in the years 

immediately following this eruption. However, as reported in the previous Ozone Assessment (Forster 

and Thompson et al., 2011), there has been an increase in stratospheric aerosol optical depth since the late

1990s, with an average increase of 4–10% per year from 2000–2010 (see Figure 2-18 of Chapter 2).

4.2.4 Ozone

As discussed in detail in this chapter, changes in stratospheric ozone influence climate both by 

direct radiative effects and by affecting stratospheric and tropospheric circulation. Past changes in global 

and polar stratospheric ozone are reviewed in Chapters 2 and 3, respectively, and only the key points are 

briefly summarized here.

There is substantial year-to-year variability in extratropical column ozone, but there have been 

only weak trends since 2000, especially compared to the large decreases observed from 1980 to the mid1990s. The differences between total column ozone in the recent past (circa 2008–2012) and pre-1980 

values are similar to those quoted for 2006–2008 in the previous Ozone Assessment (Forster and 

Thompson et al., 2011), i.e., near-global (60°N–60°S) column ozone is approximately 2% lower than pre1980 values. The Antarctic ozone hole has continued to form each year, with springtime Antarctic 

(October, 60–90oS) column ozone values substantially lower than pre-1980 values. There has, however, 

been large year-to-year variability in the ozone amount in the last few years, due to variability in 

stratospheric temperatures and dynamical processes. Large year-to-year variability is also evident in 

tropical lower stratospheric ozone concentrations, complicating the detection of long-term trends there. 

4.3 OBSERVED AND SIMULATED CHANGES IN STRATOSPHERIC CLIMATE

The previous section summarized the observed changes in long-lived GHGs and ODSs, as well as 

stratospheric water vapor, aerosols, and ozone (see also Chapters 1–3 of this Assessment). Changes in 

these constituents have a direct impact on stratospheric temperatures through their radiative effects, which 

in turn can affect the stratospheric circulation. In this section, we assess observed changes in stratospheric 

temperature and circulation and simulated changes in the past and future, as well as current understanding 

of the causes of these changes. In addition to influencing tropospheric climate, stratospheric temperature 

and circulation are also important drivers of stratospheric ozone change (Box 3-2 of Chapter 3).

4.3.1 Stratospheric Temperature

4.3.1.1 OBSERVATIONS

Identifying robust long-term trends in stratospheric temperature requires records of at least a few 

decades and global coverage. Observations of stratospheric temperatures are mainly derived from 
Stratospheric Ozone and Climate

4.7

balloon-borne radiosondes and satellite retrievals. Radiosondes provide measurements since 1957 over an 

irregular network with quasi-global coverage, although certain regions such as the oceans and the 

Antarctic are poorly sampled. Radiosondes have very good vertical resolution in the lower stratosphere, 

but coverage does not extend to the middle and upper stratosphere. Microwave Sounding Unit (MSU) and 

Stratospheric Sounding Unit (SSU) satellite instruments provided global coverage measurements from 

late 1978 to 2005. However, their vertical resolution is coarse as they measure over broad altitude ranges 

corresponding to the instrument weighting functions. The highest MSU channel (MSU channel 4) peaks 

in the lower stratosphere near 20 km, while SSU channels peak in the middle and upper stratosphere, at 

25–35 km (SSU channel 1), 35–45 km (SSU channel 2), and 40–50 km (SSU channel 3). SSU channels 1, 

2, and 3 are also referred in the literature as channels 25, 26, and 27, respectively. MSU and SSU 

instruments have now been replaced by the Advanced Microwave Sounding Unit (AMSU; in service 

since 1998), which has channels covering the domains of both the MSU and SSU instruments.

New trend estimates in the lower stratosphere, published since the last Ozone Assessment and

based on longer records of several radiosonde and satellite temperature data sets, agree with previous 

estimates of temperature trends in this region. The global mean temperature in the lower stratosphere 

decreased by around 1 K from 1979 to 2012, as shown in Figure 4-2 in MSU channel 4 data processed by 

three different institutions (RSS, UAH, and NOAA; see also Hartmann et al., 2013). Short-term warming 

periods appear after the volcanic eruptions of El Chichón (1982) and Mt. Pinatubo (1991), and a lack of 

any statistically significant trend in globally averaged lower stratospheric temperatures since the mid1990s continues to 2012 (Thompson et al., 2012; Seidel et al., 2011). Estimates of lower stratospheric 

temperature trends from radiosondes and the MSU instrument up to 2012 are listed in Table 2.8 from the 

IPCC AR5 (Hartmann et al., 2013).

Interest in temperature trends in the middle and upper stratosphere has grown recently. While the 

tropospheric climate response may be most sensitive to changes in stratospheric composition and 

temperature in the lower stratosphere (e.g., Forster and Shine, 1997), trends in the middle and upper 

stratosphere are potentially useful for understanding stratospheric circulation changes. The number of 

temperature data sets available in the middle and upper stratosphere is much smaller than in the lower 

stratosphere and as discussed below, the trend uncertainties are larger. SSU data from a series of 

instruments are available from 1979, SSU and AMSU data are available from 1998 to 2005, and only 

AMSU data are available after 2005. Like most satellite data, SSU data require several corrections before 

they can be used for climatic studies. These corrections are related to 1) the cell of CO2 that is used to 

calibrate the long-wave emissions, which leaks over time, changing the altitudes measured, and whose 

CO2 content also varies among SSU instruments (Kobayashi et al., 2009); 2) interactions between the 

large amplitudes of the diurnal and semidiurnal thermal tides in the middle and upper stratosphere and 

satellite orbital drift (Nash and Forrester, 1986), and 3) the long-term increase in CO2 in the atmosphere, 

which can change the weighting function of the instruments and thus the altitudes measured (Shine et al., 

2008). In addition, there is no overlap period between several pairs of consecutive satellites and thus, 

merging data from different satellites may produce inaccurate results. Comparison with radiosonde 

observations is also not possible since radiosonde data are not generally available at these altitudes.

Only two independent analyses of SSU data are available. Originally, SSU data were processed by 

scientists at the U.K. Met Office in the 1980s (Nash and Forrester, 1986; Nash, 1988) and this data set was 

subsequently updated by Shine et al. (2008) and Randel et al. (2009). Recently, an additional alternative 

analysis of SSU data has been generated by Wang et al. (2012), taking advantage of improvements in 

radiative transfer modeling. Figure 4-2 (left panels) shows the global mean stratospheric temperature 

anomalies since 1979 in the three SSU channels as produced by Wang et al. (NOAA STAR, red line) and 

Shine et al. (Met Office, blue line). Comparison of these data sets (Thompson et al., 2012) shows that global 

mean trends are similar in the upper stratosphere (SSU channel 3). However, in the middle stratosphere, the 

two data sets exhibit differences in SSU channels 1 and 2 of as large as 0.5 K decade-1, with the NOAA 

STAR data set showing a global mean cooling almost twice as large as the Met Office data set (Wang et al., 

2012; Thompson et al., 2012). The full reasons for these discrepancies remain unknown (e.g., Nash and 

Saunders, 2013), but planned updates to the data sets may resolve the discrepancies in part. 
Chapter 4

4.8

Thus, the agreement between satellite measurements and radiosonde observations over the longer 

record since the 2010 Ozone Assessment increases confidence in the robustness of the temperature trends 

in the lower stratosphere. Observed changes in global-mean temperature in the middle and upper 

stratosphere are considerably more uncertain. All data sets exhibit a cooling trend from 1979 to 2005 (to 

2012 for the lower stratosphere), which is stronger in the upper stratosphere than at lower levels, 

consistent with physical understanding.

Figure 4-2. Time series of global mean stratospheric temperature anomalies from 1979 to 2012 for SSU 

channels 1-3 (top three rows) and MSU channel 4 (bottom row) for the altitude ranges, data sets, and 

model output indicated. Colored lines indicate results based on observations processed by different 

research groups: the Met Office (blue in top three panels), Remote Sensing Systems (green), the 

University of Alabama-Huntsville (blue in bottom panel) and the National Oceanic Atmospheric 

Administration Center for Satellite Applications and Research (red). Gray lines indicate results from the 

Chemistry-Climate Model Validation-2 (CCMVal2) and Coupled Model Intercomparison Project Phase 5 

(CMIP5) models weighted by the appropriate satellite weighting function for easy comparison with 

observations. Time series are plotted so that their 1979–1982 mean anomalies are zero. Adapted from 

Thompson et al. (2012).

1985 1990 1995 2000 2005 2010

Year

1980 1985

−1.5

 −1

−0.5

−1.5

 −1

−0.5

−1.5

 −1

−0.5

−1.5

 −1

−0.5

Kelvin

1980 1985 1990 1995 2000 2005 2010

−1.5

 −1

−0.5

−1.5

 −1

−0.5

−1.5

 −1

−0.5

−1.5

 −1

−0.5

Year

Kelvin

 CCMVal2 models (gray) 

 Observed (colors)

SSU Ch. 3 (~40-50 km)

NOAA and Met Office

SSU Ch. 2 (~35-45 km)

NOAA and Met Office

SSU Ch. 1 (~25-35 km)

NOAA and Met Office

MSU Ch. 4 (~15-20 km)

NOAA, RSS, and UAH 

 CMIP5 models (gray) 

 Observed (colors)

Global mean stratospheric temperature anomalies
Stratospheric Ozone and Climate

4.9

Seasonal and spatial structure of trends

Changes in the seasonal and spatial patterns of stratospheric temperature trends can arise from the 

radiative response to homogeneous changes in long-lived GHGs (Fels et al., 1980; Forster and Shine, 1999),

constituents with a strong spatial and seasonal structure (such as ozone), as well as changes in the 

stratospheric mean meridional circulation (as will be discussed in Section 4.3.2). The pattern of zonal mean 

lower stratospheric temperature trends as a function of month over the period 1979–2012 (Figure 4-3a, b) is 

similar to that shown over the period 1979–2007 in the previous Ozone Assessment (Forster and Thompson 

et al., 2011). The largest trends in lower stratospheric temperatures occur over the Antarctic in November and 

December in satellite data (Figure 4-3a) and October–November in HadAT (Hadley Centre Atmospheric 

Temperature) radiosonde data (Figure 4-3b) following the maximum in ozone depletion in October. 

However, this feature is somewhat sensitive to the period over which the trend is calculated due partly to the 

Figure 4-3. Lower stratospheric temperature trends over the period 1979–2012 in 

K per decade as a function of latitude and 

month from (a) satellite MSU RSS v3.3 

(channel 4); (b) HadAT radiosonde (averaged with the MSU channel 4 weighting 

function), and (c) synthetic MSU channel 

4 temperatures from merged CMIP5 historical and RCP8.5 (Representative Concentration Pathway) simulations covering 

1979–2012 taken from Santer et al. 

(2013). The following volcano years are 

treated as missing data (1982, 1983, 

1991, 1992, 1993) and trends are calculated where at least 50% of monthly 

anomalies are present over the 1979–

2012 period. The hatching in a) and b) 

shows where the observed trend is within 

the 5–95% range of simulated internal 

variability and thus not significant, where 

internal variability is assessed from the 

spread of trends in the CMIP5 historical 

simulations. Hatching in c) shows where 

the observed MSU trend in (a) lies outside 

the 5–95% range of trends simulated in 

the 33 individual CMIP5 simulations, thus 

showing thus showing areas where the 

simulated and observed trends are 

inconsistent.

(a)

(b)

(c)
Chapter 4

4.10

large internal variability in this region (Figure 4-4). Anomalously warm conditions over Antarctica in 

2002–2006 were followed by anomalously low temperatures in the period 2007–2010. In the Arctic, both 

satellite and radiosonde observations agree on a large warming trend in January and February and large 

cooling trend in March and April (Figure 4-3a and b) although some of these trends are not statistically 

robust, likely because of the large interannual variability at high latitudes, particularly in the Northern 

Hemisphere, and decadal variability possibly associated with changes in the seasonal distribution of 

Sudden Stratospheric Warmings (Gómez-Escolar et al., 2012). In the tropics, the seasonal cycle is 

amplified through the significant cooling from June to October and December to February observed in 

satellite data (Figure 4-3a) as pointed out in the last Ozone Assessment (Forster and Thompson et al., 

2011) and confirmed in radiosonde observations (Figure 4-3b and Free et al., 2011). However, it is not 

clear whether the changes in the seasonal patterns in the tropical lowermost stratosphere represent a longterm trend or are related to decadal-scale variability (Free, 2011).

In the middle and upper stratosphere, there are large differences between the latitudinal structure 

of the trends in the NOAA STAR (Wang et al., 2012) and Met Office (Shine et al., 2008) SSU data sets 

(not shown; see Thompson et al., 2012). Large meridional variations are present in the NOAA STAR data 

set, with the largest cooling trend in the tropics, and decreasing trends toward the high latitudes, with 

smaller trends in the Antarctic than in the Arctic. In contrast, the Met Office data set shows a relatively 

uniform cooling at all latitudes in the middle stratosphere (channels 1 and 2). Near the stratopause 

(channel 3), the high-latitude differences between the data sets reverse and the Met Office data set

exhibits a larger cooling than the NOAA STAR data set (Thompson et al., 2012). 

In summary, in the lower stratosphere, there is high confidence in the observations of the global 

mean trends and good agreement across different data sets. This is not the case in the mid and upper 

stratosphere, where only satellite data are available and different satellite reconstructions exhibit different 

trends. Changes in mid- and upper-stratospheric temperature are relevant to the climate change signal 

detection problem and as explained in Section 4.3.2, they are used to characterize changes in the BDC, 

which in turn can affect the amount of ozone entering the troposphere. Uncertainties in the seasonal and 

spatial patterns of stratospheric temperature trends are larger than those in the global mean especially in 

the dynamically active season in each hemisphere, boreal winter and austral spring. 

Figure 4-4. Time series of MSU channel 4-weighted temperature anomalies for the October to January 

average for four different radiosonde data sets and the unadjusted radiosondes at the Antarctic locations 

examined by Thompson and Solomon (2002) (red), MSU channel 4 data (black), the CMIP5 ensemble 

mean (purple), and the CCMVal-2 models and ensemble mean (blue). Individual model results are shown 

with the thin blue and purple lines. Adapted from Young et al. (2013b). 
Stratospheric Ozone and Climate

4.11

4.3.1.2 SIMULATED PAST AND FUTURE CHANGES

Temperature changes in the stratosphere can have a natural or anthropogenic origin, and 

attribution of the past or projected changes to a given driver relies on using climate model simulations. 

Since the last Ozone Assessment, two types of models have been widely analyzed for climate purposes in 

the stratosphere: Chemistry-Climate Models (CCMs) and atmosphere-ocean general circulation models 

(AOGCMs). They are described in Box 2-2, along with details of the model intercomparison projects in 

which such models are compared. While the last Ozone Assessment (Forster and Thompson et al., 2011) 

relied principally on CCM simulations, this Assessment makes use of results from a more comprehensive 

set of CCM and AOGCM simulations. 

Figure 4-2 shows time series of global mean stratospheric temperatures simulated by CCMs 

(from the Chemistry-Climate Model Validation-2 (CCMVal-2) experiment) and AOGCMs (from the 

Coupled Model Intercomparison Project Phase 5 (CMIP5) experiment) together with the time evolution 

of satellite observations from different channels, corresponding to the different altitude ranges already 

discussed above. Model data have been weighted by the satellite weighting functions. The model 

simulations were forced with changes in well-mixed GHGs, anthropogenic aerosols, and stratospheric 

ozone or ODSs, as well as with changes in solar irradiance, volcanic aerosols, and in the case of most 

CMIP5 simulations, land use change. It is clear that both sets of models exhibit a global mean cooling 

trend at all levels, which is larger in the upper stratosphere in general agreement with the observations. 

Nevertheless, there are discrepancies in the magnitude of the long-term cooling. 

For the lower stratosphere, both sets of models underestimate the global mean cooling seen in the 

MSU channel 4 measurements (Thompson et al., 2012; Santer et al., 2013; Charlton-Perez et al., 2013). 

The cause (or causes) of the model-observation discrepancy remains unexplained at this time, but could 

relate to forcing errors related to ozone trends or prescribed stratospheric aerosol loadings (Free and 

Lanzante, 2009; Solomon et al., 2011; Santer et al., 2013), as well as errors in the evolution of the 

modeled stratospheric water vapor (Gettelman et al., 2010; Maycock et al., 2014), or even errors in the 

model radiation code (Forster et al., 2011). For example, the prescribed ozone data set used by most of the 

CMIP5 models without interactive chemistry (Cionni et al., 2011) has been shown to underestimate 

Antarctic ozone depletion relative to the 1979–2007 observations (Cionni et al., 2011; Hassler et al., 

2013), although only a subset of models in Figure 4-2 used this data set and the discrepancy shown here is 

for the global mean temperature. Stratospheric water vapor changes (Section 4.2.2) are estimated to have 

cooled the lower stratosphere by up to ~0.2 K decade-1 in the global and annual mean from 1980–2010, a 

substantial portion of the total trend (Maycock et al., 2014). However, stratospheric water vapor changes 

in this region are likely dominated by indirect climate feedbacks due to global warming (Dessler et al., 

2013), rather than forced by increases in methane.

In the middle stratosphere at around 30 km (SSU channel 1), both the CCMVal2 and CMIP5 

models exhibit cooling trends more in agreement with the Nash and Forrester (1986) Met Office SSU 

data set than the Wang et al. (2012) NOAA SSU data set. At altitudes centered around 40 km (SSU 

channel 2) the models lie in between both observational data sets. In the upper stratosphere, where the 

agreement between the two SSU data sets is better, the models show a smaller cooling than observed. 

Some of the model-observation differences were already highlighted in the previous Ozone Assessment 

based on the CCMVal2 models (Forster and Thompson et al., 2011). The fact that the differences remain 

in the CMIP5 AOGCMs (Thompson et al., 2012; Santer et al., 2013) suggests that they are not related to 

coupling to the ocean. The reasons for these model-observation differences or the discrepancy between 

SSU data sets remain unknown. 

When comparing the latitudinal and seasonal distribution of lower stratospheric zonal mean 

temperature trends (Figure 4-3) there is a tendency for models to overestimate the seasonal extent of the 

Southern Hemisphere polar cooling and underestimate the tropical cooling over the past three decades, 

compared to the observations (see also Thompson et al., 2012; Santer et al., 2013). Over the Antarctic, the 

simulated cooling trend over the 1979–2012 period is more consistent with observations than over the 

shorter 1979–2005 period (Charlton-Perez et al., 2013; Santer et al., 2013). At high latitudes, there are 
Chapter 4

4.12

large differences between the pattern of zonal mean trends in the models and satellite observations 

(Thompson et al., 2012), which may reflect trends in the circulation (see Section 4.3.2.1). 

For the high latitude Southern Hemisphere in particular, modeling studies have shown that 

stratospheric ozone depletion is the main driver of polar temperature trends in the lower stratosphere 

region during austral spring and summer (e.g., McLandress et al., 2011; Polvani et al., 2011b). The 

comparison of CCMs carried out as part of CCMVal-2 (SPARC CCMVal, 2010) concluded that the 

ensemble mean temperature showed too strong a cooling between 1969–1998, as compared with 

observations reported by Thompson and Solomon (2002), which has been used as a benchmark in this 

type of study. Recently, Young et al. (2013b) compared several different sets of radiosondes and found a 

cooling trend in November at 100 hPa in the range of −3.8 to −4.7 K decade-1 for the same period, around 

50% larger than that reported by Thompson and Solomon (2002). Comparing over different periods with 

several observational data sets, Calvo et al. (2012) and Young et al. (2013b) concluded that the ensemble 

mean of both CCMVal-2 and CMIP5 exhibits cooling trends for the Southern Hemisphere lower 

stratosphere polar cap that are not significantly different from observations, although there is a large 

spread for individual models (Figure 4-4), and those underestimating ozone depletion also underestimate 

the temperature trends (Young et al., 2013b). Lower stratosphere temperature trends for the Southern 

Hemisphere polar cap are also characterized by zonal asymmetries in September and October (e.g., Lin et 

al., 2009). However, while Wang and Waugh (2012) found that CCMs forced with observed sea surface 

temperatures (SSTs) can qualitatively reproduce the observed seasonal pattern of lower stratospheric 

temperature variations, there is a large contribution from internal variability, and the pattern of the trends 

can differ substantially between different realizations from the same model. This is consistent with a large 

role for internal variability in generating the observed seasonal and spatial pattern of trends. 

Over the recent past, global mean lower stratospheric temperatures calculated from simulations with 

individual forcings (Figure 4-5) suggest that ozone changes (or equivalently ODSs) are the dominant 

driver of lower stratospheric cooling, with greenhouse gas increases making a smaller cooling 

contribution, and volcanic aerosol driving episodic warming following large volcanic eruptions (Eyring et 

al., 2006; Ramaswamy et al., 2006; Dall'Amico et al., 2010; Gillett et al., 2011; Lott et al., 2013). An 

analysis of five CMIP5 model simulations of the combined response to all major anthropogenic and 

natural influences shows they are able to reproduce the observed evolution of global mean lower 

stratospheric temperature reasonably well, although with the caveats mentioned above (Figure 4-5). The

Figure 4-5. Time series of observed (black dots) and simulated global mean (82.5°S–82.5°N) synthetic 

MSU lower stratosphere temperature anomalies in a subset of CMIP5 simulations forced with 

anthropogenic and natural forcings (black), well mixed greenhouse gases (blue), natural forcings (green) 

and stratospheric and tropospheric ozone (red). Anomalies are calculated relative to 1996–2005. 

Ensemble means of the following models are shown: CCSM4, CESM1-CAM5, CanESM2, GISS-E2-H, 

GISS-E2-R. Adapted from Ramaswamy et al. (2006) and Bindoff et al. (2013). 

1980 1985 1990 1995 2000 2005

Year

0

0.5

1

1.5

2

2.5

Temperature anomaly [K]

GHG

Nat

Ozone

All

Observations
Stratospheric Ozone and Climate

4.13

models generally capture the step-like temperature reduction after episodic warming from major volcanic 

eruptions but the overall cooling trend (−0.29 ± 0.03 K decade-1) from 1979–2005 is slightly less than 

observed (–0.34 ± 0.05 K decade-1). Simulated changes in stratospheric and tropospheric ozone alone lead 

to much larger lower stratospheric temperature trends (–0.20 ± 0.04 K decade-1) than increases in GHGs 

(–0.01 ± 0.03 K decade-1). Simulations with individual forcings have also been used to examine the 

drivers of temperature trends in the tropical lower stratosphere. Polvani and Solomon (2012) suggested 

that the observed seasonal cycle of tropical lower stratospheric temperature trends correlates well with the 

seasonal cycle of tropical ozone trends, although these appear to be largely driven by trends in the BDC 

(Lamarque and Solomon, 2010; Mclandress et al., 2010) (see Section 4.3.2). 

Such individual forcing simulations may also be used to attribute observed changes in 

stratospheric temperature by regressing observed changes onto the patterns of response simulated by the 

models in an attribution analysis. Gillett et al. (2011) used output from the CCMVal-2 simulations to 

partition observed MSU lower stratospheric temperature trends into components attributable to changes in 

GHGs, ODSs, and natural forcings. They found that both natural forcings and ODSs contributed 

significantly to the observed lower stratospheric cooling over the 1979–2005 period, with the influence of 

ODSs dominating, whereas the influence of greenhouse gas changes was not detectable in the 

observations. In the mid and upper stratosphere, Gillett et al. (2011) could detect the response to 

combined anthropogenic forcing (ODSs + GHGs) and natural forcings in SSU measurements, but the 

GHG and ODS influences were not separately detectable. However, conclusions related to the SSU data 

should be treated as tentative due to the large uncertainties in these observations, as discussed above. The 

attribution of temperature trends using one model was found to be sensitive to the height of the model top 

(Mitchell et al., 2013), though Charlton-Perez et al. (2013) did not find significant differences between 

lower stratospheric temperature trends in high-top and low-top CMIP5 models.

An important driver of the future evolution of stratospheric temperatures is the relative rate of 

increase of GHGs and stratospheric ozone. Relative to present day, the recovery of the ozone layer will act 

to warm the stratosphere over future decades. Increasing GHGs both cool the stratosphere radiatively and 

induce changes in the stratospheric mean meridional circulation, as discussed in Section 4.3.2. Hence, the 

projected GHG and ozone changes oppose each other and their relative importance in future projections 

varies across scenarios and models (Figure 4-6). Projected temperature changes also vary both regionally 

and with altitude. In the tropics, models simulate a stratospheric cooling trend that is larger at higher 

altitudes (e.g., Oman et al., 2010) as a result of increasing GHGs. They also exhibit tropical cooling (Figure 

4-6) which increases with the magnitude of the GHG forcing. At high latitudes, the future response in the 

lower stratosphere exhibits seasonal structure. For the Southern Hemisphere high latitudes, warming is 

projected in late spring and early summer, and cooling in winter. The Northern Hemisphere high latitudes 

are projected to warm in winter and early spring although the trends are not statistically significant. 

Figure 4-6. CMIP5 multi-model mean zonal mean lower stratospheric temperature trends (K per decade) 

over the period 2006–2050 under the low emissions scenario, RCP2.6 (left) and the high emissions 

scenario, RCP8.5 (right). Multi-model mean trends significant at the 5% level are stippled.
Chapter 4

4.14

4.3.2 Stratospheric Meridional Circulation

4.3.2.1 OBSERVATIONS

Since the 2010 Ozone Assessment, many studies have advanced our understanding of the 

stratospheric meridional circulation (the so-called Brewer-Dobson circulation, BDC) and its changes. 

While before 2010 most of the focus of the investigations was on the changes in the tropical upwelling in 

the lower stratosphere, recent studies have highlighted the importance of differentiating two branches of 

the stratospheric circulation, the shallow and deep branches (Plumb 2002; Birner and Bönisch 2011; 

Bönisch et al., 2011). The shallow branch appears in the lowermost stratosphere with rising air in the 

tropics and descending air in the subtropics and middle latitudes, while the deep branch reaches the upper 

stratosphere and the descending branches extend to the mid and high latitudes, shown schematically in 

Figure 4-7. Birner and Bönisch (2011) compared these two branches of the Brewer-Dobson circulation 

and found that the deep branch was characterized by a much longer transit time (defined as the time an air 

parcel needs to be transported from the entry point at the tropical tropopause to a given arrival location), 

smaller integrated mass flux, and stratospheric entry latitudes closer to the equator. As the circulation is 

driven by wave dissipation, and different waves dissipate in different regions, the type of waves driving 

the shallow and deep branches differs. 

It is now well established across many different model simulations that a strengthening of the 

BDC is simulated in response to increasing GHG concentrations through changes in wave dissipation 

driven by climate change (e.g., Butchart, 2014). Ozone changes on regional and seasonal scales also 

modulate changes in the meridional circulation at these scales through changes in local radiative heating, 

temperature, and zonal wind patterns, impacting wave-mean flow interactions (e.g., Lin and Fu, 2013). As 

pointed out in the last Ozone Assessment (Forster and Thompson et al., 2011), trends in the BDC are not 

easy to detect in observations because trends are small and thus difficult to separate from natural 

variability, and the BDC cannot be measured directly with available observations, so needs to be inferred 

from changes in other variables such as the latitudinal distribution of temperature, the amplitude of the 

quasi-biennial oscillation (QBO), chemical constituents, and the estimated age of air. 

Based on the out-of-phase relationship between temperature changes in the tropics and high 

latitudes, the 2010 Ozone Assessment noted that observed changes in temperature are consistent with an 

acceleration of the BDC in the lower stratosphere (e.g., Thompson and Solomon, 2009; Fu et al., 2010). 

This has been corroborated recently by studies of radiosonde data sets (Free, 2011; Young et al., 2012) 

and satellite data (Young et al., 2012), although the role of decadal variability in the apparent trend 

and the possible role of changes in the seasonal cycle of the circulation are not clear yet. Kawatani and

Figure 4-7. Schematic illustration of the 

shallow and deep branches of the 

Brewer-Dobson circulation in the stratosphere at solstices. Also shown is the 

meridional cross section of Northern 

Hemisphere winter ozone density (color 

shading, with darker shades indicating 

larger ozone concentrations, based on 

the Bodeker et al. (2013) climatology), 

and the approximate location of the tropopause (dashed curve). Adapted from 

Plumb (2002) and IPCC/TEAP (2005).

TROPOSPHERE STRATOSPHERE

POLE EQUATOR POLE

DEEP

BRANCH

SHALLOW

BRANCH

SUMMER WINTER
Stratospheric Ozone and Climate

4.15

Hamilton (2013) found a significant decrease in the amplitude of the QBO at 70hPa between 1953 and 

2013 based on radiosonde zonal wind measurements at near-equatorial stations and attributed it to an 

increased upwelling in the lowermost stratosphere that hampered the downward penetration of the QBO 

into this region. At higher levels in the stratosphere, Young et al. (2012) used the Met Office SSU data to 

diagnose a strengthening of the Northern Hemisphere branch of the BDC in December and the Southern 

Hemisphere branch of the BDC in August over 1979–2005, but only after removing year-to-year 

variability. However, as noted in Section 4.3.1.1, the Met Office SSU temperature trends have a different 

latitudinal structure to the NOAA STAR data (Thompson et al., 2012), meaning that the BDC trend 

inferred from each data set would be different. Thus, there are large uncertainties in the changes in the 

upper branch of the BDC inferred from temperature observations. 

In addition to inferences made from observed temperature variations, changes in the BDC can 

also be inferred from measurements of chemical species. Decreasing ozone in the lowermost tropical 

stratosphere has been measured by satellite instruments and ozonesondes from 1985 to 2010 (Randel and 

Thompson, 2011; Sioris et al., 2014), consistent with an acceleration of the BDC in the lower 

stratosphere. However, the early years of the record are subject to substantial observational uncertainties 

(Solomon et al., 2012). Several recent studies using shorter records, subject to large interannual 

variability, are not long enough to corroborate such trends. More details on tropical ozone changes can be 

found in Chapter 2 (Section 2.3.5.3). 

Recently, Stiller et al. (2012) presented new age-of-air estimates derived from more than 106 SF6

profiles retrieved from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) limb 

emission mid-infrared spectrometer for 2002–2010, with almost global coverage and about 3 km vertical 

resolution. Stiller et al. (2012) show that trends of differing sign occur at different levels in the 

stratosphere. In the lower stratosphere, their results show a decrease in age of air consistent with an 

acceleration of the BDC. As discussed in the last Ozone Assessment, Engel et al. (2009) found no 

significant decrease in the mean age of air above 24 km based on measurements of CO2 and SF6. In the 

middle and upper stratosphere, the results of Stiller et al. (2012) corroborate those of Engel et al. (2009) 

for northern midlatitudes, showing a statistically robust increase in age of air in that region, consistent 

with a weakening of the deep branch of the BDC there, in contrast to the strengthening inferred from 

stratospheric temperatures (Young et al., 2012). 

As also discussed in the 2010 Ozone Assessment, inhomogeneities in observations and reanalysis 

products complicate the diagnosis of long-term trends in reanalysis data (e.g., Iwasaki et al., 2009). The 

new generation of reanalysis products, however, do show some improvements (e.g., for ERA-Interim 

reanalysis data as discussed by Dee et al. (2011) and Monge-Sanz et al. (2012)). Using ERA-Interim 

reanalysis data, changes in the BDC circulation were investigated based on the Transformed Eulerian 

Mean residual circulation (Sevior et al., 2011) and age of air with transport models of different 

complexity (Monge-Sanz et al., 2013; Diallo et al., 2012). Seviour et al. (2012) found that trends in the 

BDC inferred from tropical upwelling in the lower stratosphere were dependent on the altitude and 

tropical latitudes considered. Statistically significant trends in the lower stratosphere were found by 

Seviour et al. (2011) and Diallo et al. (2012) consistent with an enhancement of the BDC in this region,

while Monge-Sanz et al. found significant changes above 25 km in the Northern Hemisphere that were 

consistent with a weakening of the deep branch of the BDC in the Northern Hemisphere and in broad 

agreement with findings by Engel et al. (2009) and Stiller et al. (2012). However, Diallo et al. (2012) 

found little or no statistical significance in the changes in age of air above 20 km (in agreement with 

Bönisch et al., 2011). 

In summary, changes in temperature, ozone, and age of air all agree in showing an acceleration of 

the tropical upwelling in the lowermost stratosphere (shallow branch) and, as discussed in Section 4.3.2.2, 

this change is consistent with that simulated by climate models. However, the behavior of the trends in 

the BDC in the middle and upper stratosphere is not as clear, as temperature changes (albeit from only 

one data set) indicate a strengthening of the deep branch while BDC changes inferred from age of air 

point to no change or even weakening of the deep branch. 
Chapter 4

4.16

4.3.2.2 SIMULATED PAST AND FUTURE CHANGES

In the 2010 Ozone Assessment, it was assessed that chemistry-climate models consistently 

simulate an acceleration of the BDC in response to increasing GHG concentrations, although most studies 

had focused on the lower stratosphere. More recent modeling studies all consistently simulate an 

acceleration of the BDC in response to increasing GHG concentrations in past and future simulations 

(e.g., Butchart, 2014). The 2010 Ozone Assessment highlighted a primary caveat associated with the nonstatistically significant trend found in stratospheric age-of-air estimates from SF6 and CO2 measurements 

(Engel et al., 2009) and also noted difficulties in comparing the tropical upwelling and its forcings across 

different studies because of the different definitions used (e.g., fixed latitudes versus turnaround latitudes, 

where the residual vertical velocity changes sign), and in quantifying the role of parameterized gravity 

waves (versus resolved waves) in models, especially in the lower stratosphere. Since the last Ozone 

Assessment, new research has clarified some of these issues.

New studies demonstrated that observational results of Engel et al. (2009) may not be inconsistent 

with simulated stratospheric circulation changes and that BDC changes in climate models agree with new 

observational age-of-air measurements in the lower stratosphere (Stiller et al., 2012). Ray et al. (2010) 

were able to reproduce the observed age of air and ozone trends over the last 30 years in their simple 

model assuming a small strengthening of the mean circulation in the lower stratosphere and a moderate 

weakening of the mean circulation in the middle and upper stratosphere. Garcia et al. (2011) identified 

issues associated with using natural species, with non-uniform growth rates, as proxies for trends in the 

stratospheric circulation. Their CCM was able to simulate non-statistically significant trends in age of air, 

as observed by Engel et al. (2009), when it was sampled sparsely as in the observations, demonstrating 

the large uncertainty in trends determined from sparsely sampled data.

Recent studies have confirmed that the role of parameterized gravity waves in driving modeled 

changes in tropical upwelling is larger in the middle and upper stratosphere (Bunzel and Schmidt et al., 

2013; Oberländer et al., 2013; Palmeiro et al., 2014). This is in agreement with previous results from 

Garcia and Randel (2008) and McLandress and Shepherd (2009). In the lowermost stratosphere, 

orographic wave forcing dominates over non-orographic contributions and the trend in orographic gravity 

wave forcing is larger in the subtropics than in the deep tropics (McLandress and Shepherd, 2009). Thus 

the contribution of orographic gravity waves to the total trend in tropical upwelling is larger when the 

turnaround latitudes are used to compute the upwelling (e.g., McLandress and Shepherd, 2009) instead of 

using fixed latitudes encompassing the deep tropics (e.g., Calvo and Garcia, 2009).

Understanding of the role of resolved waves in driving the tropical upwelling has advanced. New 

individual modeling studies indicate that resolved waves are the main driver of the trend in tropical 

upwelling in the lower stratosphere (Bunzel and Schmidt, 2013; Oberländer et al., 2013; Palmeiro et al., 

2014; Okamoto et al., 2011) while the role of orographic gravity waves seems to be largely dependent on 

the model. Previous multi-model studies already highlighted the large spread in the contribution of both 

types of waves to the trend (e.g., Butchart et al., 2010), which could be in part explained by the 

compensation between resolved and parameterized orographic wave driving found in this region (Cohen 

et al., 2013; Sigmond and Shepherd, 2014 and references therein). The fact that representation of 

parameterized waves varies between models hampers a systematic multi-model comparison to assess the 

degree of consensus in the role of resolved versus parameterized waves.

The contribution of stationary and transient waves to the trend in the shallow branch tropical 

upwelling varies with latitude in models. The contribution of stationary waves dominates in the deep 

tropics, whereas transient waves are more important at higher latitudes in the subtropics (Garny et al., 

2011; Shepherd and McLandress, 2011). This explains discrepancies found in previous studies, because

the contribution of these waves is expected to be different depending on how the tropical upwelling is 

defined (in the deep tropics or between the turnaround latitudes). 

It is still difficult to attribute changes in wave forcing to changes in wave propagation or wave 

generation, because changes in both processes are hard to disentangle in a free-running climate model. 

Garny et al. (2011) found that warmer tropical SSTs under increasing GHGs cause a strengthening of the 
Stratospheric Ozone and Climate

4.17

subtropical jets and changes in deep convection affecting latent heat release, which modulate the wave 

propagation and wave generation, respectively, although the former dominates in their model. Shepherd 

and McLandress (2011) propose that critical-layer control of Rossby wave breaking (Randel and Held,

1991) is the mechanism that explains the simulated changes in wave drag that ultimately force the 

strengthened tropical upwelling in the lower stratosphere. The tropospheric warming in response to 

climate change leads to a strengthening and upward displacement of the upper flanks of the subtropical 

jets in the lower stratosphere (e.g., Garcia and Randel, 2008), which causes the critical layers on the 

equatorward side of the jets to move upward and the Rossby wave drag to occur at higher altitudes and 

further equatorward, allowing more Rossby wave activity to penetrate into the subtropical lower 

stratosphere. This mechanism can also explain the simulated increase in parameterized lowerstratospheric orographic gravity wave drag (e.g., Li et al., 2008; McLandress and Shepherd, 2009) as an 

upward shift of the wave-breaking levels due to the strengthened upper flank of the subtropical jets.

As discussed above, a few recent studies have been devoted to exploring the behavior of the deep 

branch of the circulation and understanding its driving mechanisms in future climates (Hardiman et al., 

2013; Palmeiro et al., 2014; Lin and Fu, 2013; Oberländer et al., 2013). A strengthening of the deep 

branch of the circulation has been found in response to increasing GHG concentrations in CCMs (Lin and 

Fu, 2013) and in “high top” CMIP5 models (i.e., those with their lid above 1 hPa; Hardiman et al., 2013; 

Palmeiro et al., 2014; Figure 4-8). In addition, changes in the width of the tropical upwelling region have 

been found to vary with height, so that the upwelling region narrows below 20 hPa and widens above 

20 hPa (Hardiman et al., 2013; also compare black and red lines in Figure 4-8). This indicates that different mechanisms might operate in forcing the changes in each branch of the circulation. Changes in the

Figure 4-8. Multi-model mean CMIP5 simulated differences in annual mean residual vertical velocity 

(mm/s) in RCP8.5, 2080–2099 climatology minus 2006–2025 climatology. Solid/Dashed contours show 

positive/negative values (increases/decreases in residual vertical velocity). Stippling denotes regions 

where 90% of models show a statistically significant change in residual vertical velocity at the 5% level. 

Red lines denote the position of the turnaround latitudes (where residual vertical velocity is zero) for the 

2006–2025 climatology. Adapted from Hardiman et al. (2013).
Chapter 4

4.18

dissipation of parameterized gravity waves appear to be the key to explaining the acceleration of the deep 

branch of the BDC under climate change (Oberländer et al., 2013; Palmeiro et al., 2014), although there is 

no consensus in the type of gravity waves involved. Thus, modeling evidence is currently too limited to 

assess the contribution of gravity waves to the deep branch of the circulation in the upper stratosphere. 

Overall, studies have found that the projected increase in the tropical upwelling in the upper 

stratosphere is robust across models and balanced by an increase in extratropical downwelling. In the 

Northern Hemisphere, a robust increase in downwelling is simulated at high latitudes throughout the 

entire stratosphere (Figure 4-8) while in the Southern Hemisphere, the increased downwelling mainly 

occurs at midlatitudes although the agreement across models is not as robust. Reduced downwelling is 

simulated over the Antarctic in austral spring and summer, driving the annual mean behavior in this 

region. Recent studies have shown that the reduced downwelling is in response to future ozone recovery 

(Hardiman et al., 2013; Palmeiro et al., 2014; Lin and Fu, 2013), in agreement with the enhanced 

downwelling in austral summer found in response to ozone depletion (e.g., Manzini et al., 2003; Li et al., 

2008) but in contrast with McLandress and Shepherd (2009), who found reduced downwelling in the 

future in Antarctic spring in response to increasing GHGs.

In summary, modeling studies show an acceleration of the shallow and deep branches of the BDC 

with climate change. In the lower stratosphere, these results are in agreement with observations from 

changes in temperature, trace gases, and age of air, which all agree in showing an intensification of the 

BDC in this region. In the middle and upper stratosphere, changes in the deep branch of the BDC inferred 

from changes in temperatures, trace gases, and age-of-air observations are uncertain. Further research is 

needed to assess the changes in the BDC in the middle and upper stratosphere and the underlying 

mechanisms.

4.3.3 Stratospheric Zonal Flow

The characteristics of the stratospheric zonal flow, and in particular the stratospheric polar 

vortices, play an important role in determining polar ozone concentrations and in the dynamical coupling 

between the stratosphere and troposphere. Changes in the zonal flow and vortices can have an impact on 

tropospheric climate. The observed changes in vortex characteristics, the cause of these changes, and 

projected future changes are discussed in Chapter 3 of this Assessment, and are only briefly reviewed here.

In general, there is larger interannual variability in the characteristics of the Arctic vortex than the 

Antarctic vortex. However, as discussed in Chapter 3, there has been an increase in the year-to-year 

variability in both hemispheres in recent years, with increased variability in lower stratospheric polar 

temperatures (Figure 3-1) and the breakup date of the vortices (Figure 3-2). Also, whereas there were few 

Arctic major sudden warmings during the 1990s, there were many during the first decade of the 21st

century (Chapter 3). In the Antarctic there has been a trend toward a stronger vortex (e.g., stronger zonal 

flow; see Figure 4-10) and later breakup dates since 1980 (Figure 3-2). In most recent years the vortex 

broke up in early to mid-December, although the 2012 vortex broke up in mid-November. 

The variability in the strength and lifetime of the polar vortices is connected to similar variability 

in planetary wave activity, since there is generally a stronger, longer-lasting vortex in winters with lower 

mean winter eddy heat flux (see Section 3.3.3). However, whether changes in wave activity and the 

resulting vortex strength are due to natural variability or the response to anthropogenic forcing is 

generally not known. An exception is the strengthening and delay in breakup date of the Antarctic vortex,

which is due primarily to diabatic cooling associated with the Antarctic ozone hole (see Section 4.3.1).

Climate model simulations also show a strengthening of the Antarctic vortex during the latter part 

of the 20th century in response to stratospheric ozone depletion, and a weakening in spring as ozone 

recovers (Figures 4-6, 4-10). The simulations show a shift to later breakup dates in the latter part of the 

20th century and then a return to earlier breakup dates (e.g., McLandress et al., 2010; Deushi and Shibata 

2011; Shaw et al., 2011; Wilcox et al., 2013; Orr et al., 2013). There is some indication of a shift toward 

later final warming dates in the latter half of the 21st century for a high GHG emission scenario (Wilcox et 
Stratospheric Ozone and Climate

4.19

al., 2013). However, Sheshadri et al. (2014) found that a delayed stratospheric final warming could not 

explain the trend in Southern Hemisphere tropospheric zonal mean zonal wind in recent decades (see 

Section 4.4).

In contrast to the clear trends in the Antarctic, models generally show small, insignificant trends 

in Arctic polar temperatures and vortex breakup dates over the 21st century (CCMVal 2010; Hitchcock et 

al., 2009; Langematz et al., 2014).

4.4 EFFECTS OF PAST CHANGES IN STRATOSPHERIC OZONE ON THE TROPOSPHERE 

AND SURFACE

The influence of stratospheric ozone change on Southern Hemisphere tropospheric and surface 

climate has been analyzed and investigated in an increasingly mature body of research, with its signature 

now well documented (e.g., recent reviews of Thompson et al., 2011; Previdi and Polvani, 2014; Canziani 

et al., 2014). We focus here on what has been learned since the 2010 Ozone Assessment (Forster and 

Thompson et al., 2011), notably, improved quantification of the relative roles of ozone and GHGs in 

driving observed Southern Hemisphere circulation changes. Consistent with the last Assessment, ozone 

depletion is assessed to be the dominant driver of austral summer (December-January-February, DJF) 

atmospheric circulation changes over the last several decades. We begin by assessing the effects of 

stratospheric ozone changes on the tropospheric circulation, followed by an assessment of the resultant 

impacts on surface climate, the ocean, and sea ice.

4.4.1 Tropospheric Circulation Effects

The Southern Hemisphere

As described in the previous section, the primary effect of stratospheric ozone depletion is to 

produce a strong cooling in the lower stratosphere over the Antarctic in austral spring. Simulations 

indicate that this cooling acts to strengthen and shift the Southern Hemisphere tropospheric midlatitude 

jet poleward in austral summer, and to drive an increase in the Southern Annular Mode (SAM) index 

corresponding to decreases in sea level pressure over high latitudes and increases over midlatitudes. We 

first evaluate the observed evidence for the impact of ozone depletion on the tropospheric circulation 

followed by an assessment of the current understanding of the mechanisms through which this shift 

occurs. We note that here and elsewhere in this chapter, we use the term “midlatitude jet” to refer to the 

band of strong westerly winds, climatologically centered around 50°S, which are associated with 

synoptic-scale eddies (i.e., typical storms in the midlatitudes). The latitude of the midlatitude jet is 

generally defined as the location of the maximum zonal mean westerly winds at 850 hPa. This definition 

is used because it distinguishes the Southern Hemisphere midlatitude jet from the upper-level subtropical 

jet that is present in some seasons.

The SAM is the leading mode of variability in the extratropical circulation and the SAM index 

gives an indication of changes in the characteristics of the midlatitude jet, though there is not necessarily a 

one-to-one relationship between SAM index anomalies and variations in the strength or location of the 

midlatitude jet. Whereas changes in the jet strength and location can only be determined from reanalysis 

data sets, the SAM index can be calculated from sea level pressure observations, which are available over 

a longer period. After 1979, there is generally good agreement between the SAM index calculated from 

station observations and that calculated from reanalyses, whereas prior to 1979 some reanalyses are 

known to have deficiencies (Marshall, 2003). Since a longer period is often used in model attribution 

studies, two periods are discussed here. Figure 4-9 shows trends in the SAM index from station 

observations of sea level pressure (based on an update of Marshall, 2003) for 1979–2012 (which 

encompasses the satellite era) and 1958–2012 (which begins at the International Geophysical Year). The 

largest seasonal trends are found in DJF over both periods and significant trends (shown in red) are observed
Chapter 4

4.20

Figure 4-9. SAM trends per decade 

calculated over 1979–2012 (open circles) 

and 1958–2012 (closed circles) from the 

seasonal and annual data of Marshall 

(2003; http://www.nerc-bas.ac.uk/icd/gjma/

sam.html). Error bars indicate the 95% 

confidence interval of the trends with the 

auto-correlation accounted for. Trends 

significant at the 5% level based on a twosided t-test are colored red. The SAM index 

is dimensionless (Marshall, 2003).

in the annual mean and DJF for 1979–2012 and in the annual mean, DJF, and March-April-May (MAM)

for 1958–2012.

The connection of these surface changes to the stratosphere is evident in Figure 4-10a, which shows 

the austral summer climatology and trends in the zonal mean zonal winds over the period 1979–2005 in one 

reanalysis data set (Eyring et al., 2013). There is a clear asymmetry between the Northern and Southern 

Hemisphere trends over this period, with the largest wind changes in the Southern Hemisphere stratosphere. 

These features lend support to ozone depletion being the dominant cause of the Southern Hemisphere 

trends, and these trends are well captured by the CMIP5 historical experiments (see Box 2-2 in Chapter 2 of 

this Assessment), driven by natural and anthropogenic forcings including ozone depletion (Figure 4-10b).

Swart and Fyfe (2012) analyzed recent trends in surface wind stress over the Southern Ocean in 

various reanalyses (Figure 4-11). They report no statistically significant trends in the annual mean 

midlatitude jet location (defined based on surface wind stress) over the 1979–2010 period, but note the 

existence of a significant poleward shift in austral summer (DJF), which is found consistently across six 

reanalysis data sets. They find that the Southern Hemisphere DJF midlatitude jet has shifted poleward by 

−0.7 ± 0.5 degrees latitude per decade, averaged across the different reanalyses (their Figure 3). Swart and 

Fyfe (2012) also report a strengthening of the midlatitude jet in the annual mean and in DJF, but the large 

spread across the reanalyses in Figure 4-11 precludes a confident assessment of this metric.

A recent study by Lee and Feldstein (2013) also found a dominant role for ozone depletion in 

summertime extratropical circulation trends in the ERA-Interim reanalyses in the last few decades. These 

authors applied a cluster analysis technique to zonal mean zonal wind data, identified trends in the 

occurrence frequency of two of the clusters, and by simply comparing the patterns of zonal mean wind 

anomalies associated with each cluster with the simulated response to GHGs and ozone from other 

studies, inferred that changes in occupation frequency of one cluster were due to GHG changes and 

changes in the occurrence frequency of the other were due to ozone depletion. Based on this, they inferred 

that ozone depletion has contributed about 50% more than increasing GHGs toward the jet shift in austral 

summer. Son et al. (2013) and Bandoro et al. (2014) further showed that stratospheric ozone variability 

can change the tropospheric circulation on interannual timescales.

Since the previous Ozone Assessment, several modeling studies have compared the influence of 

ozone depletion and GHGs on the tropospheric circulation. McLandress et al. (2011), performed transient 

simulations with a coupled-chemistry stratosphere-resolving model with a fully coupled (non-eddy 

resolving) ocean; Polvani et al. (2011b), performed time-slice integrations with a much simpler atmosphereonly (low-top) climate model, with prescribed ozone concentrations, sea surface temperatures, and sea 

ice; while Gillett et al. (2013) and Fyfe et al. (2012) compared sea level pressure trends in CMIP5 

simulations that included GHG changes only and ozone (stratospheric and tropospheric ) changes only. 

Considering spatio-temporal patterns of sea level pressure change over the whole globe and for all four
Stratospheric Ozone and Climate

4.21

Figure 4-10. Long-term mean (thin black contour) and linear trend (color) of zonal mean DJF zonal winds 

for (a) ERA-interim over 1979–2005; (b) the mean of the CMIP5 historical experiments over 1979–2005; 

(c) CMIP5 RCP2.6 multi-model mean over 2006–2050 and (d) CMIP5 RCP8.5 multi-model mean over 

2006–2050. Contour intervals of climatological wind are 10 m s

-1 starting from −20 m s-1

. Trends that are 

statistically significant at the 5% level are stippled. Adapted from Eyring et al. (2013).

seasons, Gillett et al. (2013) separately detected the influence of ozone changes and GHG changes in 

observations, using attribution techniques that employ the distinctive patterns of response to each forcing 

simulated by CMIP5 models. Gillett et al. (2013) also examined seasonal SAM trends across the CMIP5 

individual forcing simulations (see Figure 4-12). In all studies apart from Fyfe et al. (2012), simulations 

showed that the shift in the latitude of the midlatitude jet and the SAM index trend in DJF were considerably 

larger in response to stratospheric ozone depletion than in response to GHG changes over the last fifty years

or so (McLandress et al., 2011; Polvani et al., 2011b; Gillett et al., 2013). Fyfe et al. (2012) find a comparable contribution of GHGs and ozone to trends in their DJF sea level pressure index over 1957–2010, 

although they note that the prescribed ozone forcing used in their simulations may be weaker than observed. 

In seasons other than DJF, the relative amplitude of the circulation response to anthropogenic and 

natural forcings depends on the metric used and on the period over which trends are calculated. 

Observations and most models show smaller SAM trends in these seasons, and simulations show a 

relatively uniform response to GHGs in all months (e.g., Staten et al., 2012; Gillett et al., 2013). In MAM, 

when the observed SAM index trends are significant over longer timescales (Figure 4-9), Polvani et al. 

(2011b) and McLandress et al. (2011) find larger contributions from GHGs compared to ozone depletion, Pressure (hPa)

(a) ERA-Interim, 1979-2005 (b) CMIP5 historical, 1979-2005

(c) CMIP5 RCP2.6, 2006-2050 (d) CMIP5 RCP8.5, 2006-2050 Pressure (hPa)

Pressure (hPa)

Pressure (hPa)
Chapter 4

4.22

Figure 4-11. Historical trends in the 

Southern Hemisphere surface westerly 

wind-stress jet position (a) and strength (b). 

Trends are computed over the period 

1979–2010 from six reanalysis products:

NCEP-NCAR Reanalysis 1 (R1), NCEPDOE Reanalysis 2 (R2), ECMWF ERAInterim Reanalysis (ERA-I), NOAA-CIRES 

Twentieth Century Reanalysis Version 2 

(TCR), NASA Modern Era-Retrospective 

Analysis for Research and Applications 

(MERRA), and NCEP Climate Forecast 

System Reanalysis (CFSR); the analysis 

has been adapted from Swart and Fyfe 

(2012) to include the NASA MERRA and 

NCEP CFSR data sets that were not 

included in the main text. The error bars 

show the 95% confidence interval of the 

trends, where auto-correlation has been 

accounted for. Trends are computed for 

seasonal means and annual means of the 

zonal-mean zonal wind-stress. Adapted 

from Swart and Fyfe (2012).

Figure 4-12. Simulated and observed trends in 

the Northern Annular Mode and Southern 

Annular Mode indices. Observed trends in the (a) 

NAM and (b) SAM over the period 1951–2011 are 

shown for each season based on HadSLP2 /

HadSLP2r_lowvar (solid line), the 20th Century 

Reanalysis (dotted), and in the case of the SAM, 

the Marshall SAM index over the period 1958–

2011 (dashed). No normalization was used when 

computing the annular mode indices. Gray bars 

show the 5–95% centered range of trends in the 

control simulations. Colored boxes show the 

ensemble mean and its 5–95% confidence range 

for the simulated response to GHGs, aerosols 

(AER), tropospheric and stratospheric ozone 

changes (OZ), and natural forcings (NAT), based 

on available individual forcing simulations. Black 

boxes show the 5–95% range of trends simulated in response to ALL forcings. Note the 

different scales on (a) and (b). Adapted from 

Gillett et al. (2013).

DJF MAM JJA SON

Season

-0.5

0.0

0.5

1.0

1.5

SAM trend (hPa/decade)

DJF MAM JJA SON

Season

-0.4

-0.2

0.0

0.2

0.4

0.6

NAM trend (hPa/decade)

(a)

NAM

SAM

(b)
Stratospheric Ozone and Climate

4.23

while Staten et al. (2012) and Gillett et al. (2013) suggest comparable contributions from both (see Figure 

4-12). A comparable contribution of GHGs and ozone is also found in annual mean trends in the SAM in 

studies where it was diagnosed (Sigmond et al., 2011; Staten et al., 2012), consistent with earlier studies 

(e.g., Arblaster and Meehl, 2006; Shindell and Schmidt, 2004). Recent modeling studies suggest that the 

response to other forcings is weaker, though aerosol changes may have driven opposing, negative trends 

in the SAM (Gillett et al., 2013; Xie et al., 2013). 

In summary, the contribution of Antarctic ozone depletion to the observed increase in the 

Southern Annular Mode index in austral summer is substantially larger in most models than the 

contribution from greenhouse gas increases over the past three to five decades. The role of ozone 

depletion is largest in summer. Observations and models suggest smaller Southern Annular Mode trends 

in other seasons. In most models, GHGs drive consistently positive trends in the SAM across the seasonal 

cycle and likely contribute partially to the observed changes seen. 

In the Southern Hemisphere midlatitudes, in association with the shift of the jet, several 

additional impacts of stratospheric ozone depletion, beyond those already mentioned in the previous 

Ozone Assessment have now been documented. Ndarana et al. (2012) reported a large increase in 

summertime Rossby wave breaking events on the equatorward side of the tropospheric midlatitude jet in 

the Southern Hemisphere (and weak decreases on the poleward side), over the last 30 years in 

meteorological analyses. Such events are of interest because they are often linked to weather extremes 

and stratosphere-troposphere exchange of trace gases. Using model integrations with single forcings, 

Ndarana et al. (2012) showed that trends consistent with the reanalyses are simulated in response to 

stratospheric ozone depletion. Using the same model integrations, Grise et al. (2014) showed how ozone 

depletion can also cause a significant poleward shift in the position of midlatitude storms over the 

Southern Ocean, indicating that the storm tracks are tightly linked with the position of the midlatitude jet. 

Recent studies have shown that the impact of stratospheric ozone depletion is not confined to the 

mid to high latitudes but extends well into the low latitudes. Notably, new studies have shown that ozone 

depletion has likely contributed to a broadening of the Hadley Cell in austral summer (McLandress et al., 

2011; Polvani et al., 2011b; Min and Son, 2013), confirming the tentative conclusion of the last Ozone 

Assessment (Forster and Thompson et al., 2011; Son et al., 2010). This is illustrated in Figure 4-13, which 

shows a broad variety of simulated circulation metrics exhibit substantial trends in austral summer, in a 

model forced with stratospheric ozone changes alone (via changes in ODSs). Note, in particular, the 

Hadley cell width in panel (d), and how the ozone forcing yields a much stronger broadening than 

greenhouse gas forcing, over the period 1960–2005. The response of the Hadley Cell width to ozone 

depletion has also been detected in observations in austral summer by Min and Son (2013), using several 

reanalyses and CMIP3 and CMIP5 models. Nonetheless, large observational uncertainties remain and the 

observed trend in the Hadley Cell width is considerably larger than that simulated in response to ozone 

and GHG changes by climate models (Quan et al., 2013; Min and Son, 2013; Lucas et al., 2013, 2014).

Understanding of the influence of stratospheric ozone depletion on the low-latitude atmospheric 

circulation has also improved since the last Ozone Assessment. Although the direct response to polar 

ozone depletion is primarily a shift of the jet in the midlatitudes, the width of the tropical circulation is 

very tightly coupled to the position of the jet in austral summer (Kang and Polvani, 2011). 

In spite of the modeling and observational evidence that stratospheric ozone depletion affects the 

tropospheric circulation, a precise mechanism linking stratospheric ozone loss to the jet shift is still the subject 

of active research. Experiments with simplified atmospheric models (e.g., Polvani and Kushner, 2002, and 

Butler et al., 2010) have established that the impact of ozone depletion on the troposphere is effected through a 

cooling of the lower polar stratosphere, which is associated with anomalously strong westerly winds that alter 

the wave driving of the stratosphere, producing a positive anomaly in potential vorticity. It is well accepted that 

the balanced response of the troposphere to this positive potential vorticity anomaly is an acceleration of the 

zonal flow on the poleward flank of the storm track, consistent with the sign of the observed shift in the 

circulation (e.g., Hartley et al., 1998; Thompson et al., 2006). It is unlikely, however, that this balanced 

response is sufficiently large to explain the magnitude of the observed circulation shift. 
Chapter 4

4.24

Figure 4-13. Time series of (a) 100-hPa temperature for October–January area-averaged over 70° to 

90°S, (b) DJF tropopause pressure anomaly averaged over 45° to 90°S, (c) DJF jet-location anomaly 

defined by the latitude of 850-hPa zonal-mean zonal wind maximum, (d) DJF Hadley cell boundary 

anomaly defined as the zero-crossing latitude of 500-hPa mass streamfunction, and (e) DJF SAM-index 

anomaly derived from 850-hPa geopotential. The REF-B2 (black), ODS (red), and GHG (blue) 

simulations denote an experiment with time-varying ODS and GHG concentrations, an experiment with 

time-varying ODS concentration but GHG concentrations fixed at 2000 values, and an experiment with 

time-varying GHG concentration and ODS concentrations fixed at 2000 values, respectively. The sum of 

the GHG and ODS responses is denoted by purple dots. The straight lines are linear fits computed from 

1960 to 1999 and 2000 to 2099. The red and blue curves are shifted with respect to the black; their colorcoded axes are given on the right. In (b-d), anomalies are computed with respect to 1960 baselines; the 

average baseline (i.e., average of the REF-B2, ODS, and GHG baselines) is shown in the top-left corner 

of each panel. The 1960 baseline has not been removed from the SAM index time series. Adapted from 

McLandress et al. (2011).

Studies with idealized atmospheric models in particular suggest that tropospheric eddy feedbacks 

amplify the impact of stratospheric cooling, and so play a critical role in the mechanism (Kushner and 

Polvani, 2004; Song and Robinson, 2004); a number of pathways for the lower stratosphere to directly 

influence tropospheric eddies have been proposed. Several mechanisms focus on the direct influence of 

the lower stratosphere on tropospheric eddy momentum fluxes: linear theories consider the propagation 

and refraction of synoptic waves (Limpasuvan and Hartmann, 2000; Chen and Held, 2007; Simpson et al., 

2009), while nonlinear mechanisms focus on the wave breaking itself (Wittman et al., 2004; Kunz et al., 

2009). Other studies have focussed on the impact of stratospheric anomalies on the generation of wave 

activity through baroclinic instability, which in turn drives changes in the eddy momentum fluxes 

(Rivière, 2011; Thompson and Birner, 2012). 
Stratospheric Ozone and Climate

4.25

Crook et al. (2008) and Waugh et al. (2009) find that the zonal structure of ozone loss amplifies 

its impact on the troposphere, suggesting a role for planetary-scale wave interactions. The potential for 

constructive and destructive interferences between forced and climatological planetary waves has been 

shown to impact coupling between the stratosphere and troposphere in the Northern Hemisphere (Smith et 

al., 2010), and there is evidence that the ozone hole has modified planetary wave coupling in the Southern 

Hemisphere (Shaw et al., 2011). 

Tropospheric eddy feedbacks have been observed in the jet response in comprehensive model 

studies (McLandress et al., 2011; Orr et al., 2012), but Garfinkel et al. (2013) illustrate the difficulty in 

separating and confirming many of the proposed mechanisms, even in an idealized atmospheric model. 

Tropospheric eddy feedbacks overwhelm the initial perturbation generated by the stratosphere, controlling 

the ultimate amplitude of the response. Both comprehensive and idealized models tend to overestimate 

the strength of the tropospheric eddy feedbacks (e.g., Gerber et al., 2010), complicating the effort to 

connect model-based analysis to the real atmosphere. A number of studies have also noted the 

equatorward bias in the position of the Southern Hemisphere DJF midlatitude jet in the CMIP3 and 

CMIP5 models compared to the reanalyses (Wilcox et al., 2012, Swart and Fyfe, 2012), which may 

impact their response to stratospheric ozone changes (Sigmond and Fyfe, 2014). Swart and Fyfe (2012) 

find this bias has somewhat improved from CMIP3 to CMIP5. Despite these uncertainties and the lack of 

clarity on the mechanism, the influence of stratospheric ozone on the troposphere is robust across a range 

of comprehensive and idealized atmospheric models.

The Northern Hemisphere

The last Ozone Assessment assessed that no robust linkages between stratospheric ozone 

depletion and tropospheric circulation had been established in the Northern Hemisphere, consistent with 

the relatively weak ozone depletion observed in the Arctic (see, e.g., Figure 3-4). However, Morgenstern 

et al. (2010) find a weak but significant anticorrelation between Northern Hemisphere column ozone and 

the NAM index in spring (March-May, MAM) in the CCMVal-2 models, suggesting that in these models 

Arctic ozone depletion drives an increase in the NAM index in MAM. The CMIP5 models also exhibit an 

increase in the NAM index in MAM in response to combined changes in stratospheric and tropospheric 

ozone (Figure 4-12), though simulations with one model suggest that this response may be driven by 

tropospheric ozone changes (Gillett et al., 2013). No statistically significant trend in the NAM index has 

been observed in MAM (e.g., Gillett et al., 2013). Thus our assessment remains that no robust link 

between stratospheric ozone depletion and Northern Hemisphere circulation has been established.

4.4.1.1 SURFACE IMPACTS

An important development since the previous Ozone Assessment has been the improved 

understanding of the influence of ozone depletion on Southern Hemisphere precipitation. The effect of 

ozone depletion on midlatitude precipitation is directly related to the position of the midlatitude jet, and 

has been documented in a number of studies (e.g., Fyfe et al., 2012; Previdi and Polvani, 2014). What has 

become apparent more recently is that ozone depletion may also be impacting precipitation in the 

subtropics, notably the latitudinal band 15–35°S (Kang et al., 2011). Over this region a positive trend in 

precipitation has been observed over the last decades of the 20thcentury during austral summer (Kang et 

al., 2011; Previdi and Polvani, 2014). 

The connection between observed Southern Hemisphere precipitation changes and the SAM trends in 

austral summer is illustrated in Figure 4-14, which shows the DJF zonal mean observed GPCP (Global 

Precipitation Climatology Project) precipitation trend over both land and ocean points over the period 

1979–2000. Note how most of the observed precipitation changes (red) are linearly congruent with the 

SAM (blue; see caption for details). This is particularly the case for the midlatitude zone. The subtropical 

trends are less significant, with more year-to-year variability in that latitude band compared to higher
Chapter 4

4.26

Figure 4-14. Zonal-mean change in GPCP (Global 

Precipitation Climatology Project) DJF precipitation 

during 1979–2000. The total precipitation change is 

plotted in red, and is based on the linear trend in the 

seasonal-mean precipitation at each latitude. The 

component of the precipitation change that is 

linearly congruent with the SAM trend is plotted in 

blue. This is calculated by regressing the seasonal 

detrended precipitation onto the SAM index and 

multiplying by the trend in the SAM. Error bars show 

the plus and minus one standard deviation range of 

the detrended seasonal-mean data, providing an 

indication of the year-to-year precipitation variability. 

From Previdi and Polvani (2014).

latitudes, yet are also largely congruent with the observed positive trend in the SAM index. Attribution of 

precipitation trends to SAM trends on more regional scales is more difficult. For example, the observed 

summer rainfall increases in subtropical northern Australia are larger than can be explained by the SAM 

changes alone (Hendon et al., 2007; Thompson et al., 2011). 

Kang et al. (2011), using models forced with ozone depletion alone, showed that the precipitation

response in austral summer was consistent with that observed and resulted from an expansion of the tropical 

circulation in their simulations. This moves the downwelling branch of the tropical circulation poleward,

which results in enhanced upwelling in the subtropics and hence enhanced precipitation, in austral summer. 

A recent regional study by Gonzalez et al. (2013), contrasting models forced with ozone depletion and 

increasing GHGs, suggested that ozone depletion is a driver of observed precipitation increases in South 

East South America in austral summer, with its effect comparable to that due to increasing GHGs. Fyfe et al. 

(2012) identified a poleward shift in Southern Hemisphere extratropical austral summer precipitation from 

merged reanalysis and satellite-based observations that was inconsistent with simulated internal variability, 

but consistent with the simulated response to anthropogenic and natural forcings. In individual forcing 

simulations from one model, they found that both GHGs and ozone depletion contributed to a shift in 

precipitation consistent with that observed, with their influence partially opposed by the response to aerosols.

Previous Ozone Assessments have noted that the observed warming of the Antarctic Peninsula 

and cooling observed over the rest of continental Antarctica observed in austral summer are largely 

congruent with the positive trend in the SAM, suggesting that ozone depletion has contributed to these 

trends (e.g., Forster and Thompson et al., 2011). Since the last Ozone Assessment, several studies have 

directly examined the surface temperature trends simulated in response to ozone changes in coupled 

ocean-atmosphere models. Consistent with the last Ozone Assessment, McLandress et al. (2011) simulate 

cooling over eastern Antarctica and warming over western Antarctica in austral summer in response to 

ozone depletion. Sigmond and Fyfe (2010) also simulate a weak cooling over the Antarctic interior in 

austral summer in response to ozone depletion, but no significant response over the Antarctic Peninsula. 

They simulate a maximum surface temperature response to ozone depletion over the Southern Ocean at 

around 60°S in late winter where a pronounced warming is associated with the simulated decrease in sea 

ice extent (Section 4.4.1.3). In the annual mean, Bitz and Polvani (2012) also simulate the largest surface 

temperature response to ozone depletion over the high latitude Southern Ocean at around 60°S, in 

standard and high-resolution models. Over Antarctica itself, the simulated surface temperature response is 

small in the annual mean in their simulations. Thus recent studies find that in models at least, the largest 

annual mean surface temperature response to ozone depletion is not over Antarctica itself, but warming 

over the high latitude Southern Ocean. Other studies have noted the summertime contribution of the 

positive SAM trend to surface warming over southern Africa (Manatsa et al., 2013) and Patagonia 
Stratospheric Ozone and Climate

4.27

(Thompson et al., 2011) and the mitigation of warming in central-east Australia (Hendon et al., 2007), 

with a recent study suggesting springtime ozone losses can be directly implicated in these impacts 

(Bandoro et al., 2014).

4.4.1.2 OCEAN IMPACTS

As discussed above, observations show a strengthening and poleward shift of the band of 

maximum surface wind stress over the southern oceans since 1979 (Figure 4-11), largest in austral 

summer. Modeling evidence indicates that in summer, stratospheric ozone depletion has been the 

dominant driver of these changes, with greenhouse gas increases and stratospheric ozone making 

comparable contributions in the annual mean (see discussion above). The westerly wind stress plays a 

fundamental role in driving the oceanic circulation, including creating (via so-called Ekman transport) a 

region of divergence and upwelling on the poleward side of the surface wind maximum, and convergence 

and downwelling equatorward of the maximum. As discussed in the 2010 Ozone Assessment (Forster and 

Thompson et al., 2011), given the observed trends in the surface wind stress, one expects an enhancement 

of this Ekman response, causing increased upwelling of deep waters south of the Antarctic Circumpolar 

Current (ACC), increased northward surface flow at the latitude of the ACC, and increased downwelling 

north of the ACC. Recent observational and modeling studies have considerably improved our 

understanding of the response of the southern oceans to changing winds.

We first consider changes in the southern subtropical oceans (~15–45oS), where observations show 

increases in the horizontal circulation, and transport consistent with the increase in maximum wind stress 

(and wind stress curl). Analysis of satellite altimetry and ship and float hydrographic data shows an 

increase in the strength of the southern subtropical horizontal circulation (“gyres”) from the early 1990s to 

early 2000s that agrees with the expected response to the increase in the wind stress curl (Roemmich et al., 

2007; Cai, 2006). Model simulations indicate that at least half of the changes in DJF are induced by 

Antarctic ozone depletion (Cai and Cowan, 2007). This intensification of the subtropical gyres and 

associated changes in Ekman-driven downwelling north of the ACC would be expected to contribute to 

more rapid transport of surface waters into the interior (“ventilation”) of the upper southern subtropical 

oceans. Recent analysis of repeat measurements of chlorofluorocarbons (CFCs) in the southern oceans 

shows such an increase in ventilation, with a decrease in the mean age of water at the subtropical thermocline between the early 1990s and mid-late 2000s (Waugh et al., 2013; Figure 4-15). The mean age of 

ocean water is analogous to the mean age of stratospheric air, and is defined as the mean time for transport 

from the surface to the interior ocean. Further, there is quantitative agreement in observed changes in wind 

stress curl, gyre strength, and subtropical age, with all changing by around 20–30% (Waugh, 2014). 

The new analysis of ocean CFC measurements also indicates decadal changes in the ventilation of 

the subpolar southern oceans, but with an increase in the mean age between the early 1990s and mid-late 

2000s (Huhn et al., 2013; Waugh et al., 2013; Figure 4-15). This increase is consistent with theoretical 

considerations and modeling studies, which (as discussed in the last Assessment) indicate that an 

intensification of the surface winds will lead to an intensification in the meridional overturning 

circulation, with an increase of upwelling in subpolar waters and an increase in downwelling in 

subtropical waters. The increase in subpolar upwelling will bring up more deep, old waters that mix with 

surrounding waters and increase the ages in subpolar waters. The contrast between the decrease in age in 

subtropical waters and increase in subpolar waters inferred from CFC observations is also found in 

modeling studies (Bryan et al., 2006; Gnanadesikan et al., 2007; Waugh, 2013).

An intensification of surface winds is also expected to lead to changes in subsurface ocean 

temperatures. A subsurface warming is observed below and north of the ACC (around 40–60°S), and this 

is consistent with a poleward shift of the temperature structure (Böning et al., 2008; Gille, 2008; Cai et al., 

2010). However, the extent to which the Southern Ocean warming is caused by shifting of the ACC versus 

other processes, such as an acceleration of poleward heat flux caused by the increasing eddy intensity 

(Hogg et al., 2008), is currently unclear. A subsurface warming, extending deepest in the midlatitudes, is 
Chapter 4

4.28

also found in modeling studies examining the impact of ozone depletion on Antarctic sea ice (Sigmond and 

Fyfe, 2010; Bitz and Polvani, 2012; Smith et al., 2012), as described in Section 4.4.1.3 below.

The above observational and modeling studies present a consistent picture for the ocean’s 

response to increasing surface wind stress, with intensification of the subtropical horizontal (gyre) and the 

meridional overturning circulations, more rapid ventilation of the subtropical waters but older subpolar 

waters, and a subsurface warming. However, large uncertainties remain. This is in part due to limited 

historical oceanic data that prevents observational quantification of the (potentially large) natural decadal 

variability. An additional complication is the role of oceanic mesoscale (10–50 km scale) eddies. As 

discussed in the 2010 Ozone Assessment, these play an important role in the ocean response to changing 

forcing, but the climate models used to examine ozone impacts generally do not explicitly resolve these 

eddies and it is uncertain how much the effect of eddies oppose the direct wind-forced acceleration of the 

zonal flow (e.g., ACC transport) and overturning circulation. However, there has been recent progress in 

testing these ideas, and we now have a better understanding of the Southern Ocean eddy field and 

circulation response to changing winds. Theoretical arguments have been made that indicate that an 

invariant ACC transport (eddy saturation) is dynamically distinct from an invariant overturning 

circulation (eddy compensation), and one does not imply the other (Meredith et al., 2012). These 

arguments have been tested with various eddy permitting and eddy resolving models with different 

configurations, and it has been found that in the eddy saturated limit, only partial compensation of the 

overturning circulation is expected in response to decadally-changing winds (Meredith et al., 2012;

Morrison and Hogg, 2013; Farneti et al., 2010). Widely used parameterizations for the role of mesoscale 

eddies have typically failed to capture this response adequately, though recent improvements in their 

implementation have shown progress (Hofmann and Morales Maqueda, 2011; Gent and Danabasoglu, 

2011). Investigations are continuing, including into what sets the level of (incomplete) eddy 

compensation, and hence the magnitude of the overturning response to changing winds (Abernathey et al., 

2011). These advances in understanding imply that an increase in Southern Ocean overturning (and 

corresponding changes in the ventilation) in response to changing winds is a reasonable expectation.

Figure 4-15. (a) Depth-latitude cross-sections of the change in mean age of ocean water between 1991 

and 2005 based on CFC-12 measurements along 150°W. (b) Difference in mean age, expressed as 

percentage change per decade relative to age from original cruise, for circumpolar deep water (CDW) 

and Subantarctic Mode Water (SAMW) water masses for the repeat sampling of meridional sections at 

90°E, 150°W, 103°W, 20°W, and 0°E. Adapted from Waugh et al. (2013) and Huhn et al. (2013).

(A)

65S 55S 45S 35S 25S 15S

1500

1000

500

0

Depth (m)

 -80

 -40

 -30

 -20

 -10

 -5

 0

 5

 10

 20

 30

 40

 80

Age (%)

26.6

27.0

27.6

27.2

CDW

SAMW

I08 P16 P18 A16 ANT

Section

-40

-20

0

20

40

Age (%/decade)

CDW

SAMW

90E 150W 103W 20W 0

(B) 

Mean-Age (2005-1991)
Stratospheric Ozone and Climate

4.29

Ocean carbon

The southern oceans play a critical role in the oceanic uptake of atmospheric carbon dioxide, and, 

as discussed in the last Assessment, there is evidence that the intensification and poleward shift of the 

surface winds has led to a reduction in the CO2 uptake in Antarctic waters. This reduction is linked to 

more transport of carbon-rich deep waters to the surface, which decreases the surface air-sea gradients 

and oceanic uptake. An increase in the upwelling of carbon-rich deep waters is consistent with the 

increase in the age of subpolar water discussed above. However, the southern oceans are very poorly 

sampled (especially for carbon), and there are large uncertainties in the estimates of the carbon uptake.

In a recent study, Lenton et al. (2013) compared estimates of 1990–2009 Southern Ocean air-sea 

CO2 fluxes from several different methods, including a synthesis of surface ocean observations, five 

ocean biogeochemical models coupled to ocean general circulation models, eleven atmosphere inversions, 

and ten ocean inversions (the atmospheric inversions estimate carbon fluxes from atmospheric CO2

measurements, while the ocean inversions estimate fluxes from ocean measurements). They show large 

interannual variability in the air-sea fluxes (up to 25% of annual mean) and some substantial differences 

between fluxes inferred using different methods. In particular, there is a large spread in the 1990–2009 

trends, with atmospheric inversions generally showing a slowdown in the uptake (broadly consistent with 

Le Quéré et al., 2007), while the ocean biogeochemical models indicate an uptake consistent with the 

growth of atmospheric CO2 (i.e., no slow-down). Further complicating the picture, recent observational 

studies indicate large zonal variations in the ocean uptake of carbon (Sallée et al., 2012), and the changes 

in the efficiency of the Southern Ocean sink may not be zonally uniform (Lenton et al., 2013). Given the 

poor sampling in southern oceans, the zonal and interannual variability, and large uncertainties in all 

methods, longer data records will be needed to determine if there are any trends in the oceanic uptake of 

CO2 (and even then it may not be possible to determine if these trends are linked to stratospheric ozone 

depletion).

4.4.1.3 SEA ICE IMPACTS

Significant increases in Antarctic sea ice extent of 2.5 ± 2.0% have been observed in austral 

summer from 1979–2012 (Vaughan et al., 2013). The sea ice trends vary regionally, with large increases 

in the Ross Sea and decreases in the Bellingshausen and Amundsen seas (Vaughan et al., 2013). At the 

time of the 2010 Assessment, the influence of stratospheric ozone trends on Antarctic sea ice was unclear, 

with some studies arguing that ozone depletion might be responsible for the observed positive trends in 

Antarctic sea ice extent (e.g., Turner et al., 2009), leading the last Assessment to conclude that there was 

some evidence that the ozone-induced summer SAM trend had caused the summer increase in Antarctic 

sea ice extent (Forster and Thompson et al., 2011). However, the studies assessed in the last Assessment 

focused on the relationship between sea ice and the SAM on monthly timescales, instead of on how 

stratospheric ozone changes affect sea ice on decadal timescales. Since the last Ozone Assessment, 

Simpkins et al. (2012) argued, based on observations, that the increase in sea ice extent is not linked to the 

trend in the SAM and several studies have now explicitly addressed the question of how stratospheric 

ozone depletion affects Antarctic sea ice. 

The first of these studies is by Sigmond and Fyfe (2010); they contrasted time-slice model 

integrations before and after the formation of the ozone hole and concluded that ozone depletion would 

result in a reduction of Antarctic sea ice extent. The second is a study by Bitz and Polvani (2012), which 

also contrasted model runs with and without an ozone hole; they confirmed the results of Sigmond and 

Fyfe (2010) and corroborated them by using an eddy-resolving ocean model. This same result was further 

strengthened by the study of Smith et al. (2012), who used a fully coupled chemistry-climate model to 

study the effect of ozone recovery on sea ice. Finally, Sigmond and Fyfe (2014) found that a decrease in 

annual mean sea ice extent was simulated in response to ozone changes over the 1951–2005 period in all 

five CMIP5 models with ozone-only simulations available. The ozone-induced strengthening of the 
Chapter 4

4.30

Southern Ocean overturning circulation (Section 4.4.1.2) is found to enhance the upwelling of warm 

water beneath the mixed-layer and enhance convection, driving upper ocean warming (Section 4.4.1.2) 

and decreases in sea ice extent in all seasons (Bitz and Polvani, 2012). 

Thus, in all models that have isolated the impact of stratospheric ozone depletion, Antarctic sea ice 

extent declines in all seasons. However, confidence in the simulated response to ozone depletion is limited 

by the fact that even with all major forcings, climate models on average simulate a decrease in sea ice extent 

(Turner et al., 2013; Zunz et al., 2013), whereas observations show Antarctic sea ice extent to have 

increased (albeit at a rather small rate) over the observational period (Parkinson and Cavalieri, 2012; 

Vaughan et al., 2013). Some studies have found that the observed positive trend is within the range of 

simulated trends, perhaps just reflecting a multi-decadal natural variation (Polvani and Smith, 2013; Zunz et 

al., 2013; Mahlstein et al., 2013), though Turner et al. (2013) and Zunz et al. (2013) also note the difficulties 

the models have in reproducing both the climatological and interannual variability of the observed sea ice 

extent. Another hypothesis is that the observed sea ice growth is due to enhanced freshwater input from 

dynamic mass loss (Bintanja et al., 2013), which is not included in the models, though this effect may not 

be large enough to explain the discrepancy (Swart and Fyfe, 2013). Overall, as concluded in the IPCC Fifth 

Assessment Report, the fundamental cause for the observed sea ice increase remains unknown and there is 

low confidence in the scientific understanding of this trend (Bindoff et al., 2013).

4.4.2 Radiative Effects

Stratospheric ozone exerts an influence on the troposphere directly by affecting the longwave and 

shortwave irradiances in the troposphere. Since 2000, a limited number of studies have investigated the 

radiative effects of stratospheric ozone concentration change, as assessed in previous IPCC and Ozone 

Assessments. These assessments have all reached similar conclusions, that stratospheric ozone depletion 

since 1979 likely contributes a net negative radiative forcing of around −0.05 W m-2 ± 0.1 W m-2 (e.g., 

Myhre et al., 2013). For context the forcing from CO2 changes over 1979–2010 was 0.8 W m-2 (Myhre et 

al., 2013). The sign of the ozone forcing remains uncertain due to uncertainties from: i) quantifying ozone 

changes near the tropopause where the relative forcing is strongest; ii) cancellation between positive 

shortwave and negative longwave forcing, and iii) the dominant role of stratospheric adjustment in 

contributing a negative longwave forcing. Because of these factors considerable uncertainties remain 

when deriving forcing from observations and these uncertainties impact the testing of model-derived 

forcings. The radiative forcing from stratospheric ozone change is comparable in magnitude to that from

changes in stratospheric water vapor due to methane oxidation (discussed in Section 4.2.2), which is 

assessed to be 0.07 (0.02–0.12) W m-2 in the IPCC Fifth Assessment Report (Myhre et al., 2013). 

Changes in stratospheric water vapor due to changes in transport or circulation are considered to be a 

feedback rather than a forcing by Myhre et al. (2013).

Hassler et al. (2013) compared stratospheric ozone forcings derived from different observationbased data sets over 1979–1997 and found a factor of four difference in net globally averaged radiative 

forcing (−0.03 W m-2 to −0.12 W m-2; Figure 4-16). Uncertainties in derived ozone trends, corresponding 

to differences between data sets, at both high latitudes and over the equator lead to uncertainties in 

forcing, and to uncertainties in the simulated response to ozone changes. This uncertainty is illustrated in 

Figure 4-16 where the mean forcing derived from models (−0.04 ± 0.06 W m-2 ) is similar to the forcings 

derived using the SPARC (Stratosphere-troposphere Processes and their Role in Climate; Cionni et al., 

2011) data set but smaller than those derived from the BDBP (Binary Database of Profiles; Bodeker et al., 

2013) data set. There is also additional uncertainty introduced by the radiative transfer and stratospheric 

adjustment method (compare the two dashed lines in Figure 4-16). The weaker ozone and radiative 

forcing trends in the SPARC data set, used in many CMIP5 simulations (Eyring et al., 2013), could lead 

to an underestimate of the magnitude of the simulated response to ozone changes in many CMIP5 models, 

although it is not clear whether simulations forced with the BDBP data set could lead to overestimates in 

the response (e.g., Solomon et al., 2012).
Stratospheric Ozone and Climate

4.31

Figure 4-16. Top: Annual mean radiative forcing due to stratospheric ozone changes between 1979–

1981 and 1995–1997 averages for the BDBP (solid blue line), and the SPARC (dashed red lines) ozone 

data sets (reproduced from Hassler et al., 2013). Two different radiation and stratospheric adjustment 

schemes are used with the SPARC data to give a measure of methodological uncertainty. Model forcings 

are calculated using their ozone fields with a single radiation scheme (CAMRT- J.F. Lamarque). 

Calculations for CAM3.5, CCSRNIES, CMAM, E39CA, GEOSCCM, LMDZrepro, MRI, Niwa_SOCOL, 

ULAQ, UMETRAC, UMSLIMCAT, UMUKCA-METO, UMUKCA-UCAM, WACCM CCMVAL-2 models are 

shown, as well as the multi-model mean. Bottom: Same as above but for the global average.

Previous Ozone Assessments have considered the radiative forcing due to stratospheric ozone 

concentration changes, but this is not necessarily the same as the ozone forcing from ODS emissions, as 

both ODSs and stratospheric precursors such as methane can affect stratospheric ozone concentrations 

(see Section 4.4.3). Further, ODS emissions can induce changes in ozone in both the stratosphere and 

troposphere (see Section 4.4.3). Therefore, as discussed in the IPCC Fifth Assessment Report (Myhre et 

al., 2013), progress has been made toward merging observation and model results (e.g., Søvde et al., 

2011; Shindell et al., 2013a) to derive the radiative forcing from ozone changes due to ODS emissions, 

considering effects on both tropospheric and stratospheric ozone. There have also been ongoing multimodel intercomparison efforts (e.g., Shindell et al., 2013b; Conley et al., 2013; Stevenson et al., 2013) 

that help to assess the uncertainties in the ozone radiative forcing. The net radiative forcing due to 

stratospheric and tropospheric ozone changes induced by ODSs relative to preindustrial levels was 

calculated to be −0.26 W m-2 based on simulations of the Oslo CTM2 (Søvde et al., 2011) and −0.28 W

m-2 based on simulations of the GISS-E2-R model (Shindell et al., 2013a). Based on these two studies, 

Myhre et al. (2013) assess the radiative forcing from the effect of ODSs on ozone to be –0.15 (–0.3 to 

0.0) W m–2 from 1750 to 2010. The best estimate was assessed to be smaller than the estimates of Søvde 

et al. (2011) and Shindell et al. (2013a) because the models used in those studies had stronger 
Chapter 4

4.32

stratospheric ozone radiative forcing than the Atmospheric Chemistry and Climate Model 

Intercomparison Project (ACCMIP) multi-model mean (Myhre et al., 2013). About three-quarters of the 

ozone forcing from ODS emissions results from ozone changes in the stratosphere. The indirect changes 

in tropospheric ozone account for the other quarter (Shindell et al., 2013a).

The IPCC Fifth Assessment Report (Myhre et al., 2013) also uses effective radiative forcings to 

quantify the drivers of climate change. This effective radiative forcing goes beyond the traditional 

definition of radiative forcing and is defined to additionally account for the forcing from rapid cloud and 

circulation adjustments in the troposphere, not associated with global mean climate change. Myhre et al. 

(2013) assumed that any rapid adjustment associated with ozone was small and the effective radiative 

forcing matched the radiative forcing quoted above, i.e., any indirect forcings from cloud changes were 

small. However, some studies suggest otherwise. Grise et al. (2013) find a cloud radiative forcing due to 

the fact that the modeled poleward jet shift caused by the ozone hole moves the Southern Hemisphere 

clouds poleward, exposing the surface to higher insolation on average. In their model this effect 

contributed a positive indirect radiative forcing of +0.25 W m-2 averaged over the Southern Hemisphere 

in the annual mean (and around +0.2 W m-2 in the global mean). Their result is subject to considerable 

uncertainty and would likely be model dependent. A further possible effect relates to the modification of 

surface wind driven sea salt fluxes and thereby cloud condensation nuclei and clouds (Korhonen et al., 

2010; Struthers et al., 2013). Korhonen et al. (2010) show that this could be of a similar magnitude, but is 

a cooling effect (–0.7 W m-2 over the 50°S to 65°S latitude band in the summer, and around −0.1 W m-2 in 

the global mean). Therefore, it is expected that Southern Hemisphere effective forcings exist due to shifts 

in the midlatitude jet. These are of indeterminate sign, could exert a large local forcing, and could be of a 

comparable magnitude to the direct ODS-induced ozone radiative forcing in the global mean.

In summary ODS emissions likely contributed a small negative radiative forcing of −0.15 ± 0.15 

W m-2 in 2010 due to ozone. However, the possibility of a similarly sized adjusted forcing from 

circulation-driven cloud changes leads to an effective radiative forcing from ODSs of undetermined sign. 

The regional nature of this adjusted forcing could be important for Southern Hemisphere climate change. 

4.4.3 Chemistry Effects

Ozone levels in the troposphere are affected by natural and anthropogenic emissions of reactive 

compounds, the prevailing climate, and the influence of the stratosphere. At the global scale, the impact 

of these drivers on tropospheric ozone is assessed by examining its budget terms, with production from in 

situ photochemistry and a net influx from the stratosphere (via stratosphere-troposphere exchange, STE), 

and loss from in situ chemistry and deposition to surfaces (e.g., Wild, 2007). The role of stratospheric 

change for tropospheric ozone is both direct and indirect. The direct influence is via changes in the net 

influx of stratospheric ozone, mediated by increases or decreases in stratospheric ozone concentrations 

and changes in the patterns and strength of the stratospheric transport and circulation (e.g., the BDC) that 

bring ozone to the troposphere (e.g., Hegglin and Shepherd, 2009). The indirect influence is mainly 

through stratospheric ozone-modulated changes in UV radiation and the subsequent impacts on 

tropospheric photochemistry (e.g., Tang et al., 2011), although stratospherically driven tropospheric 

climate changes could have an additional small impact. Changes in tropospheric ozone and the UV flux 

are important because these have impacts on all chemically active tropospheric constituents, including 

impacting air quality (Tang et al., 2011; Lin et al., 2012) and the lifetimes of chemically active GHGs 

such as methane (Voulgarakis et al., 2013).

Global chemistry models remain the main tools for understanding the tropospheric ozone budget 

(see Box 2-2 in Chapter 2 of this Assessment). A major improvement to many chemistry-climate models 

since the last Assessment is the merging of tropospheric and stratospheric chemistry schemes (e.g., Naik 

et al., 2013; Shindell et al., 2013c), enabling studies that examine impacts and feedbacks between the two 

domains. Ten of the fifteen models used to assess preindustrial to projected future ozone changes in the 

Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) (Young et al., 2013a) 
Stratospheric Ozone and Climate

4.33

included a chemistry scheme appropriate for both stratospheric and tropospheric chemical processes, 

although there was a broad range in the complexity of the schemes (the number of species simulated 

ranged from 16 to 130). However, despite the overall increase in complexity of the models, simulations of 

present day tropospheric ozone do not differ markedly from those considered in the 2010 Ozone 

Assessment (see also Stevenson et al., 2006), including in their ability to reproduce the seasonal and 

geographical features in ozone observations (Myhre et al., 2013; Young et al., 2013a). 

Since the 2010 Ozone Assessment, there have been several model studies examining the drivers 

of past tropospheric composition that explicitly consider the influence of stratospheric ozone change 

caused by ODSs (John et al., 2012; Lang et al., 2012; Shindell et al., 2013c; Young et al., 2013a; Reader 

et al., 2013). Lang et al. (2012) examined the changes between 1960 and 2005, using sensitivity 

simulations to isolate the role of ODS changes between those periods. They found that, in the absence of 

other changes, the increase of ODSs between 1960 and 2005 reduced ozone concentrations globally, with 

the chemically induced reduction of stratospheric ozone resulting in a decreased net ozone influx to the 

troposphere of 5.4% in the Northern Hemisphere and 21.6% in the Southern Hemisphere. The decrease in 

STE ozone flux was slightly offset by an ODS-driven increase in the strength of the meridional 

circulation, which increases the STE mass flux (Oman et al., 2009) (see also Section 4.3.2.2). John et al. 

(2012) note the importance of decreased stratospheric ozone in decreasing methane lifetime in the last 

decades of the 20th century (through enhanced UV increasing the concentration of the hydroxyl radical, 

OH), but do not quantify the effect.

The main focus of the other studies is on the drivers of preindustrial (PI; ~1850) to present-day 

changes. All three studies (Shindell et al., 2013c; Young et al., 2013a; Reader et al., 2013) report a much 

lower tropospheric ozone column/burden in the PI (reduced 25–30% compared to present day), driven by 

the lower ozone precursor emissions in the past. Shindell et al. (2013c) found that the net stratospheric 

influx of ozone into the troposphere was ~25% greater in their PI simulation. Such an increase might 

indeed be expected, given the higher stratospheric ozone concentrations and the lower tropospheric ozone 

concentrations (meaning a higher net import of ozone into the troposphere), although the range of changes 

in the net stratospheric influx reported by Young et al. (2013a) (~0–50%) shows that there is little 

agreement on the magnitude of this impact. Reader et al. (2013) suggest that the combined increase in 

tropospheric ozone (through precursor emission increases) and decrease in stratospheric ozone since the 

PI means that the global total ozone column has changed little. 

Overall, the move by many groups toward combined troposphere-stratosphere chemistry-climate 

models allows better characterization of the links between the two domains, albeit with the caveat that it 

is hard to unambiguously assign magnitudes to individual drivers in such an interrelated system. While 

most models agree that ODS-driven ozone depletion has reduced the magnitude of the net stratospheric 

influx of ozone into the troposphere, our assessment of the magnitude of the effect is hampered by the 

range of stratospheric treatments in different models (i.e., fully interactive to passive/prescribed), which is 

likely one driver of inter-model variability in the results. Furthermore, improvements in measurement 

techniques will be needed to better constrain STE processes in models (Tang and Prather, 2012), although 

new observational analyses are providing insights into the main locations of STE events (Jin et al., 2013), 

which will be valuable for future validations. 

4.5 EFFECTS OF FUTURE CHANGES IN STRATOSPHERIC OZONE ON THE 

TROPOSPHERE AND SURFACE

This section assesses the climate impacts of future variations in stratospheric ozone over the next 

century. It follows an identical structure to Section 4.4, discussing the climate impacts from a radiative, 

dynamical, and chemistry perspective. Earlier chapters have outlined future projections of stratospheric 

ozone for the globe (Chapter 2) and polar regions (Chapter 3). These projections involve a complex 

interaction between projected changes in GHGs, ODSs, and the climate system. While a declining 

stratospheric halogen loading is expected to lead to an increase in stratospheric ozone, GHG changes will 
Chapter 4

4.34

also influence ozone concentrations through direct chemical effects, climate-induced changes in 

chemistry, and changes in the stratospheric circulation.

The studies assessed incorporate climate model results from a number of intercomparison 

projects. These include experiments run under new scenarios of future emissions named Representative 

Concentration Pathways (RCPs) that were developed in preparation for the IPCC Fifth Assessment 

Report. Box 4-1 gives a description of the RCPs and how they differ from the Special Report on 

Emissions Scenarios (SRES) scenarios considered in the 2010 Ozone Assessment.

4.5.1 Tropospheric Circulation Effects 

It is now well established that the Southern Hemisphere circulation response to the anticipated 

ozone recovery is largely opposite to that resulting from ozone depletion in the past (Section 4.4.1), 

offsetting GHG-induced circulation change in the austral summer. This offsetting effect may then result 

in a much weaker rate of Southern Hemisphere circulation change, and associated impacts, in the next 

few decades than in the recent past. In this section the possible effects of stratospheric ozone recovery on 

Southern Hemisphere climate are assessed, updating the 2010 Ozone Assessment by integrating recent 

findings. Since projected circulation changes are all assessed from climate models and many models 

exhibit biases, for example in the climatological jet location, projected circulation changes are subject to 

considerable uncertainty. In line with Section 4.4.1, overall assessments are focused on the Southern 

Hemisphere especially over austral summer, DJF, when ozone-related tropospheric climate changes are 

strongest. The potential impact of ozone recovery on the Northern Hemisphere climate is only briefly 

assessed. The benefit of the Montreal Protocol is also documented by considering recent simulations of 

the effects of unregulated ODS emissions.

The Southern Hemisphere

Since the 2010 Ozone Assessment significant progress has been made in our understanding of 

stratospheric ozone-related Southern Hemisphere climate change in the future. A number of studies have 

been conducted either by performing climate model sensitivity tests with and without stratospheric ozone 

recovery (Shindell and Schmidt, 2004; Perlwitz et al., 2008; Karpechko et al., 2010; McLandress et al., 

2011; Polvani et al., 2011a; Arblaster et al., 2011; Staten et al., 2012; Watson et al., 2012) or by 

examining multi-model projections of the CMIP3 (Miller et al., 2006; Son et al., 2009), CCMVal-2 (Son 

et al., 2010), and CMIP5 models where stratospheric ozone concentration is prescribed or predicted 

internally (Swart and Fyfe, 2012; Eyring et al., 2013; Barnes et al., 2014; Gerber and Son, 2013).

Figure 4-13 summarizes the overall climate effects of stratospheric ozone recovery as simulated 

by the Canadian CCM (CMAM) under the SRES A1B GHG emission scenario (McLandress et al., 2011). 

Although this is based on single model’s experiments, these experiments are qualitatively consistent with 

results that were reported by Polvani et al. (2011a) based on simulations from the CAM3 model. In the 

absence of other climate forcing, the increase in stratospheric ozone concentration since 2000 (red lines) 

warms the stratosphere, with a maximum warming in the Antarctic lower stratosphere during austral 

spring and summer (Figure 4-13a, Figure 4-6). This warming reduces the temperature lapse rate near the 

tropopause, lowering polar tropopause height and increasing tropopause pressure (Figure 4-13b). The 

polar warming also reduces the meridional temperature gradient in the upper troposphere and lower 

stratosphere that will likely lead to a weakening of the Antarctic polar vortex. As discussed in Section 

4.4.1 and shown in Figure 4-13c, the wind change is not limited to the upper troposphere and lower 

stratosphere. A significant response is also simulated near the surface. Specifically, the midlatitude jet is 

simulated to shift equatorward in response to ozone recovery. This change strongly projects onto the 

negative polarity of the SAM. Recent studies have shown that the latitudinal shift of the austral-summer jet 

is mostly eddy-driven (Lorenz and DeWeaver, 2007; Butler et al., 2010; McLandress et al., 2011) and 

highly correlated with the long-term trend of the southern edge of the Southern Hemisphere Hadley Cell
Stratospheric Ozone and Climate

4.35

Box 4-1. Representative Concentration Pathways

Future anthropogenic emission projections typically follow a scenario approach based on a set of assumed socioeconomic choices that may be expected over the next century. In the lead-up to the Intergovernmental Panel on 

Climate Change (IPCC) Fifth Assessment Report, the scientific community, for the first time in 12 years, developed 

new scenarios for climate change research. These Representative Concentration Pathways (RCPs) differ from the 

previous Special Report on Emissions Scenarios (SRES) scenarios in that they are concentration scenarios based 

around general characteristics of radiative forcing at 2100, rather than emissions scenarios (van Vuuren et al., 2011). 

This allowed both emission and socio-economic scenarios to be developed in parallel. 

Box 4-1: Figure 1. Historical and projected total anthropogenic radiative forcing (RF; W m-2

) relative to preindustrial 

(~1765) between 1950 and 2100 for the SRES A1B and 

RCP scenarios. Adapted from Cubasch et al. (2013).

For the Coupled Model Intercomparison Project-Phase 5 

(CMIP5), four pathways were chosen from the existing 

literature to span a range of radiative forcing in 2100 

which are outlined in Figure 1: RCP2.6 (peak and decline; 

2.6 W m-2), RCP4.5 (stabilization without over-shoot; 4.5 

W m-2), RCP6.0 (stabilization without over-shoot; 6.0 W

m-2), and RCP8.5 (rising; 8.5 W m-2). By 2100, the 

radiative forcing of the SRES A1B scenario, used in most 

of the chemistry-climate model simulations assessed in 

SPARC CCMVal (2010), is closest to RCP6.0. The RCPs 

explicitly define emissions and concentrations of GHGs 

(Figure 2), aerosols, tropospheric ozone precursors, and land-use change. They do not give specific guidance on 

variations in natural forcings, such as volcanic eruptions and solar input for the future, however most CMIP5 models 

included some form of the 11-year solar cycle in their RCP simulations while returning volcanic aerosols to zero or 

preindustrial background volcanic aerosol values (Collins et al., 2013). Emissions of most ozone-depleting 

substances follow the A1 scenario (WMO, 2003), which has a similar trajectory to the adjusted A1 halon scenario 

used in the 2010 Ozone Assessment, and is identical for all RCPs. See Meinshausen et al. (2011) for more details.

The main set of climate model simulations underlying the IPCC Fifth Assessment Report were those included in 

CMIP5. For models without interactive chemistry, the International Global Atmospheric Chemistry (IGAC) and 

Stratosphere-troposphere Processes and Their Role in Climate (SPARC) communities developed an ozone 

concentrations database covering the period 1850–2100 (Cionni et al., 2011). For the future period, zonal mean 

stratospheric ozone concentrations in this database were computed from the average of 13 CCMVal-2 models run 

under the SRES A1B scenario. Thus, the stratospheric ozone concentrations are identical for each RCP. 

Tropospheric ozone was based on the CAM3.5 chemistry-climate model (Lamarque et al., 2011). Eyring et al. 

(2013) document the implementation of ozone forcing in each model that participated in CMIP5. Of the 46 models 

assessed, a little over half prescribed ozone concentrations from the IGAC/SPARC database and the others used 

either semi-offline or interactive chemistry. For the latter, the ozone concentrations were simulated interactively 

under the four RCPs, providing some variation in stratospheric ozone across scenarios and models. The CMIP5 

ozone projections are within the spread of those from the CCMVal-2 models used in the 2010 Ozone Assessment.

Box 4-1: Figure 2. Concentrations of CO2, CH4, and N2O under the four RCPs and the SRES A1B scenario.

1950 1975 2000 2025 2050 2075 2100 0

1

2

3

4

5

6

7

8

9

Year

RF total [W/m2

]

RCP2.6

RCP4.5

RCP6.0

RCP8.5

SRES A1B

SRES A2

SRES B1

IS92a

CO2

2000 2020 2040 2060 2080 2100

200

400

600

800

1000

CH4

2000 2020 2040 2060 2080 2100

1000

1500

2000

2500

3000

3500

4000

N2O

2000 2020 2040 2060 2080 2100

300

320

340

360

380

400

420

440

RCP 8.0

RCP 6.0

RCP 4.5

RCP 2.6

SRES A1b

Parts per million (ppm)

Parts per billion (ppb)Parts per billion (ppb)
Chapter 4

4.36

(Son et al., 2009; Kang and Polvani, 2011; Gerber and Son, 2013). Although weak, this equatorward shift 

of the Hadley Cell edge is evident in Figure 4-13d. 

All of these projected changes are essentially opposite to those resulting from stratospheric ozone 

depletion in the past (compare 1960–2000 and 2001–2099 trends in Figure 4-13). More importantly, they 

oppose atmospheric circulation changes associated with ongoing GHG increases (blue lines in Figure 4-

13). As a result, Southern Hemisphere summer circulation changes in the next few decades are likely to 

be much weaker than those in the late 20th century (black lines in Figure 4-13).

The relative importance of GHG increases and ozone recovery for the simulated future 

midlatitude jet shift depends on the GHG emissions scenario and season. Multi-model analyses using the 

CMIP5 models (e.g., Swart and Fyfe, 2012; Eyring et al., 2013; Barnes et al., 2014) have shown that in 

austral summer the Southern Hemisphere circulation effects of stratospheric ozone recovery in the first 

half of 21st century likely overwhelm those of GHG increases under a low GHG emissions scenarios, e.g., 

RCP2.6 (Box 4-1), as shown in Figures 4-10c and 4-17a. In the RCP8.5 scenario, which has high GHG 

emissions, the influence of GHGs likely dominates (Figures 4-10d, 4-17a), whereas near cancellation is 

simulated under moderate emission scenarios such as RCP4.5 and RCP6.0 (Box 4-1). In austral winter 

(JJA), the jet shift is weaker and scales with the strength of the GHG emissions (Figure 4-17b). 

Differences in radiative forcing between RCP scenarios are small in the near term (Box 4-1), and hence 

the difference in projected jet trends between RCP scenarios may not be significant until the middle of 

21st century (Figure 4-17; Simpkins and Karpechko, 2012).

Projected changes in the Southern Hemisphere midlatitude jet are also dependent on the 

Antarctic lower stratosphere ozone trend itself. The CCMVal-2 and CMIP5 models with interactive 

chemistry exhibit a range in future 

projections of stratospheric ozone. For 

example, the dates when global-mean total 

column ozone returns to its 1980 values 

vary by about 20 years between CCMVal2 models (Eyring et al., 2010; see also 

Section 2.4 of Chapter 2 of this Assessment). Consideration of the effects of 

differing ODS emissions scenarios, and 

the effects of solar and volcanic forcing 

changes, would further increase this spread 

(see Sections 2.4 and 5.4 of Chapters 2 and 

5 of this Assessment). 

Figure 4-17. Time series of the CMIP5 

Southern Hemisphere DJF (panel a) and 

JJA (panel b) jet position anomalies 

relative to the 1900–1910 value in the 

historical simulations and three climate 

scenario simulations (RCP8.5, RCP4.5, 

and RCP2.6). Thick lines show the multimodel means and shading indicates the 

model spread. Time series have been 

smoothed using a 10-year moving average 

filter. Adapted from Barnes et al. (2014).

a)

b)
Stratospheric Ozone and Climate

4.37

The degree of simulated cancellation between ozone-related and GHG-related climate changes 

further depends on climate sensitivity (Arblaster et al., 2011; Watson et al., 2012). For the same GHG 

emissions scenario, upper tropospheric tropical temperature changes differ widely between models (bottom 

panel of Figure 4-18) partly because of uncertainties in physical parameterizations of atmospheric 

processes (e.g., Watson et al., 2012). Likewise the same ODS emissions scenario results in different 

Antarctic ozone and lower stratospheric temperature trends in different models (top panel of Figure 4-18). 

These uncertainties in tropical upper troposphere and polar lower stratosphere temperature changes, or 

uncertainties in equator-to-pole temperature gradient changes in the upper troposphere and lower 

stratosphere, contribute to the uncertainty in projections of future Southern Hemisphere climate change in 

austral summer (Lorenz and DeWeaver, 2007; Wilcox et al., 2012; Gerber and Son, 2013; Harvey et al., 

2013). In general a larger poleward shift of the midlatitude jet is associated with a larger temperature 

gradient change in the upper troposphere and lower stratosphere (e.g., Wilcox et al., 2012). Even for 

models with similar climate sensitivity, the atmospheric and surface climate response to external forcings 

can differ substantially, in part due to differing biases in the mean state (Kidston and Gerber, 2010; Son et 

al., 2010), since the mean state bias is correlated with the projected Southern Hemisphere midlatitude jet 

change (Kidson and Gerber, 2010; Son et al., 2010; Simpson et al., 2012; Sigmond and Fyfe, 2014). The 

projected circulation change is typically larger if the climatological jet is biased equatorward. However, 

the causal relationship is not clear as there are other deficiencies in climate models. For example, Simpson

Figure 4-18. The relationship between 

the trends of the latitudinal location of the 

DJF near-surface westerly maximum and 

(top) ONDJ polar lower-stratospheric 

temperature trends and (bottom) DJF 

tropical upper-tropospheric temperature 

trends. The trends are calculated over 

1979–2005 for the past (black or gray) 

and 2006–2050 for the future (different 

colors for various GHG emissions 

scenarios). Both CCMVal-2 (circles) and 

CMIP5 models (squares for the models 

with interactive chemistry and triangles 

for models without it) are used. The 

correlation between the two variables is 

computed for all CMIP5 models and for 

the subset of CMIP5 models with and 

without interactive chemistry for the past 

(first number) and for the future (second 

number). The correlation coefficients that 

are statistically significant at the 95% 

confidence level are indicated with an 

asterisk. Adapted from Eyring et al. (2013).
Chapter 4

4.38

et al. (2013) showed that the CMIP5 models do not have realistic planetary wave-zonal mean flow 

feedback, overestimating the time scale of SAM anomalies. This bias in eddy feedback can introduce 

more uncertainty in future Southern Hemisphere climate changes. 

The Northern Hemisphere

Hu et al. (2011) recently argued that the anticipated recovery of stratospheric ozone will 

substantially enhance tropospheric and surface warming in the first half of the 21st century. They 

examined CMIP3 models with and without ozone recovery and suggested that ozone-induced

tropospheric warming will be strongest during winter in the extratropical Northern Hemisphere, despite 

the fact that ozone recovery will be strongest in the Southern Hemisphere during springtime. This 

surprising result was shown by Previdi and Polvani (2012) and McLandress et al. (2012) to be caused not 

by stratospheric ozone forcing but by different responses of the climate models to GHG forcing. By 

examining the same two groups of models in GHG-only simulations, Previdi and Polvani (2012) found 

essentially the same result as Hu et al. (2011), clearly attributing the differences to climate sensitivity. 

McLandress et al. (2012) further confirmed that Northern Hemisphere surface temperature response to 

stratospheric ozone recovery is negligible in their coupled chemistry-climate model integrations.

4.5.1.1 SURFACE IMPACTS

Projected future tropospheric circulation changes are accompanied by surface climate changes, as 

were past changes (Section 4.4.1.1). These include changes in sea level pressure, surface air temperature, 

and precipitation (McLandress et al., 2011; Polvani et al., 2011a). In response to ozone recovery, sea level 

pressure is projected to increase in high latitudes and decrease in midlatitudes in austral summer, 

consistent with the negative SAM trend. This will likely change Antarctic surface temperature (Son et al., 

2009), but projected changes are relatively small (e.g., McLandress et al., 2011). Hydro-climate systems 

are also projected to change in response to ozone recovery in austral summer. Specifically the ozoneinduced equatorward shift of the surface wind and the associated storm track in summer is expected to

drive high-latitude drying and midlatitude moistening (Purich and Son, 2012; Polvani et al., 2011a) and 

potentially modify the frequency of extreme precipitation events (Purich and Son, 2012; Kang et al., 

2013). Projected ozone-induced precipitation and circulation changes approximately cancel GHG-induced 

changes in the mid and high latitudes of the Southern Hemisphere in summer under the SRES A1B 

scenario over the 2000–2060 period (Polvani et al., 2011a).

4.5.1.2 OCEAN IMPACTS

The possible influences of stratospheric ozone recovery on the southern oceans have been 

discussed in the literature, based mainly on past climate simulations (Forster and Thompson et al., 2011). 

However, a few recent studies have directly addressed this issue using CCMs coupled with coarseresolution ocean and sea-ice models (Sigmond et al., 2011; Smith et al., 2012).

The equatorward shift and weakening of surface westerlies, or negative SAM trend, simulated in 

response to ozone recovery will tend to reverse the changes in the southern oceans due to ozone depletion 

(discussed in Section 4.4.1.2). For example, ozone recovery is expected to reduce northward Ekman 

transport in the austral summer, weaken the meridional overturning circulation, and weaken the baroclinic 

component of the ACC (e.g., Figure 4-19). While this effect may be overestimated in some simulations 

because of unresolved mesoscale eddies, these circulation changes are expected to offset GHG-induced 

changes to some degree (Sigmond et al., 2011).

There is uncertainty in the timescales of response of different aspects of the ocean circulation to 

changes in the wind stress. The Ekman response to a change in winds will be almost instantaneous, but 

the contributions due to eddies will increase over time on a timescale of decades (Meredith and Hogg,
Stratospheric Ozone and Climate

4.39

2006; Screen et al., 2009). Changes due to advection of surface perturbations (due to the wind stress 

change) into the interior ocean will also take longer than the instantaneous Ekman response. Thus there 

will likely be a delay between changes in the wind stress and changes in the ocean circulation, with the 

delay depending on the relative role of Ekman and eddy responses in causing changes in a particular 

aspect of the circulation. For example, the simulations in Sigmond et al. (2011) showed a delay of around 

20 years in the response of the ACC to changes in the surface wind stress (see Figure 4-19). 

There have been no studies of the impact of ozone recovery on the oceanic uptake of CO2, but it 

is likely there will be a reversal of the impact of ozone depletion. 

Figure 4-19. Annual mean response to GHG (red) 

and ODS forcings (blue) of (a) the SAM index, (b) 

the zonal-mean meridional Ekman transport at 

50°S, and (c) the zonal transport through the Drake 

passage. The time series are smoothed with an 

11-year moving average. Three sets of CMAM 

experiments (GHG, ODS, and control simulations)

are used in this figure, each with three ensemble 

members simulating the 1960–2100 period. The 

GHG simulation is forced with time-varying GHGs 

and fixed ODSs at 1960 levels. Conversely, the 

ODS simulation is forced with time-varying ODSs 

and other GHGs at 1960 levels. The control 

simulation is forced with time-varying ODSs and 

GHGs. To account for model drift, the response to 

the ODS forcing is defined as the difference 

between the control and GHG simulations. 

Likewise GHG-related response is defined as the 

difference between the control and ODS 

simulations. Updated from Sigmond et al. (2011).

4.5.1.3 SEA ICE IMPACTS

Smith et al. (2012) showed that ozone recovery is projected to slow down the Antarctic sea ice 

decline that is projected in response to GHG increases. This compensation, which results from 

modulation of the Ekman transport and upper-ocean temperature near the Antarctic continent (Sigmond 

and Fyfe, 2010; Smith et al., 2012), is found to occur in all seasons because of the long-term memory of 

ocean temperature. However, this result, which is largely opposite to the simulated Antarctic sea ice 

response to ozone depletion (Section 4.4.1.3), is based on a single model experiment coupled with a 

coarse-resolution ocean model. Verification of this result will require further evaluations using highresolution ocean models. 

4.5.1.4 THE WORLD AVOIDED BY THE MONTREAL PROTOCOL

The ozone-related climate changes described above are all based on the successful regulation of 

ODS emissions in accordance with the Montreal Protocol (considered here together with its Amendments

and adjustments). However, it is pertinent to ask, what would have happened if the Montreal Protocol had 
Chapter 4

4.40

not been implemented? In other words, what is the benefit of the Montreal Protocol and actions taken so 

far? Climate models suggest that continued accumulation of ODSs in the absence of the Montreal 

Protocol would have led to a collapse of the global ozone layer by the mid-21st century. For example, 

recent studies suggest a decrease of global total ozone from about 315 DU in 1974 to about 110 DU in 

2065 in the absence of the Montreal Protocol (Newman et al., 2009; Garcia et al., 2012). Because ODSs 

are effective GHGs (e.g., Velders et al., 2007; WMO, 2011), increasing ODS concentrations would also 

enhance surface warming. The combined effects of lower-stratospheric cooling by continued ozone 

depletion and tropospheric warming by increased ODS emissions would then drive much stronger climate 

changes in both the Southern Hemisphere and Northern Hemisphere in the 21st century than those simulated in the latter half of the 20th century (Morgenstern et al., 2008; Newman et al., 2009; Wu et al., 2013).

A series of modeling studies, the so-called “world avoided” simulations, have recently been 

performed either by increasing the concentration of ODSs in CCMs (Morgenstern et al., 2008; Newman 

et al., 2009; Garcia et al., 2012) or by prescribing unregulated ODSs and corresponding ozone 

concentrations in an atmospheric general circulation model (AGCM) (Wu et al., 2013). Such simulations 

show significant stratospheric cooling in the next 20–50 years, with a maximum cooling in the Antarctic 

lower stratosphere in response to the increased ODS concentrations (e.g., Wu et al., 2013). This cooling 

would maintain the polar vortex year-round by the mid-21st century (Newman et al., 2009), resulting in no 

final warming in the Southern Hemisphere stratosphere. Simulated tropospheric warming due to the direct 

radiative effects of the ODSs would also be substantial. For example, Garcia et al. (2012) found surface 

warming of over 2 K in response to enhanced ODSs in the tropics, 6 K in the Arctic, and about 4 K in 

Antarctic from 2000 to 2070 (Figure 4-20). This is of comparable magnitude to GHG warming under the 

RCP4.5 scenario (Garcia et al., 2012), indicating that global warming over next few decades could have 

been doubled in the absence of the Montreal Protocol. 

Figure 4-20. Surface 

temperature change (K) 

between the decades of 

1990–2000 and 2060–

2070 in the (a) control 

and (b) world-avoided 

simulations. The former is 

driven by RCP 4.5 and an 

ODS emissions scenario 

that is based on the 

Montreal Protocol. However, in the latter, ODS 

emissions are not regulated until 2070. Changes 

in the stippled regions are 

not significant at the 95%

confidence level. From 

Garcia et al. (2012).
Stratospheric Ozone and Climate

4.41

Figure 4-21. The precipitation minus 

evaporation (P-E) change between a 

reference simulation (REF1960) and a 

simulation with increased ODSs but fixed 

GHGs (WA2025; red), a simulation with GHG 

increases only (GHG2025; blue), the sum of 

the two (gray dashed), and a simulation with 

both ODS and GHG increases (ALL202; gray 

solid line). In REF1960, CO2, CH4, N2O, CFC11, CFC-12, and O3 concentrations are 

prescribed at levels corresponding to the year 

1960. In WA2025, the concentrations of CFC11, CFC-12, and stratospheric O3 are 

increased from the reference level to the 

world-avoided levels, averaged over the 

decade 2020–29. In GHG2025 the concentrations of CO2, CH4, and N2O are 

increased by approximately 37%, 66%, and 

15%, respectively, relative to the reference 

level. Updated from Wu et al. (2013).

Focusing on near-future climate impacts, Wu et al. (2013) examined atmospheric and surface 

responses to unregulated ODS emissions in the 2020s. They showed that not only the Southern 

Hemisphere, but also the tropics and Northern Hemisphere would experience substantial hydro-climate 

changes in the absence of the Montreal Protocol (Figure 4-21; Wu et al., 2013). As the ODS concentration 

increases, tropical and extratropical wet regions become wetter, whereas subtropical dry regions become 

drier in both hemispheres (red line in Figure 4-21). These changes in global precipitation minus 

evaporation (P-E) are of comparable magnitude to those associated with the increase in other GHGs alone 

(blue line in Figure 4-21). This result suggests that hydro-climate change by 2025 would be almost 

doubled in the absence of the Montreal Protocol, highlighting the importance of the Montreal Protocol in 

mitigating future climate change.

4.5.2 Radiative Effects 

Stratospheric ozone forcing is very sensitive to the altitude of ozone change, and GHG increases 

as well as future circulation changes are expected to influence the distribution of ozone. Therefore, as 

stratospheric chlorine levels decline, stratospheric ozone is not expected to return to its 1970 or 

preindustrial spatial distribution or total column. As a result, the stratospheric ozone radiative forcing 

does not simply scale with stratospheric chlorine loading and would not be expected to return to zero in 

the future (Portmann et al., 2012). Bekki et al. (2013) found a large spread between CCMVal-2 models,

with radiative forcing due to stratospheric ozone staying negative in some models but increasing by up to 

+0.25 W m-2 by 2100 in others. On average the multi-model mean showed an increase in forcing to +0.06 

W m-2 by 2100 from a value of −0.05 W m-2 today. The spread is driven by differences in modeled ozone 

change near the tropopause. The expected high-altitude increase in ozone would have little effect on 

forcing.

4.5.3 Chemistry Effects 

Kawase et al. (2011), a single model study, and the ACCMIP multi-model study of Young et al. 

(2013a) present the most detailed account of the 21st century tropospheric ozone projections under the 

RCP scenarios (see Box 4-1), supported by complementary findings of Lamarque et al. (2011), Shindell 

−80 −60 −40 −20 0 20 40 60 80

−0.4

−0.2

0

0.2

0.4

0.6

0.8

latitude

P−E [mm/day]

Zonal Mean P−E

WA2025 − REF1960

GHG2025 − REF1960

sum of previous two

ALL2025 − REF1960
Chapter 4

4.42

et al. (2013b), and – for the CMIP5 models – Eyring et al. (2013). These model studies find that 

tropospheric ozone changes over the 21st century are dominated by changes in precursor emissions 

(oxides of nitrogen, carbon monoxide, and volatile organic compounds) (see Lamarque et al., 2011,

2013). A decrease in the tropospheric ozone burden is found for the RCP2.6, 4.5, and 6.0 simulations, 

driven by falling emissions of ozone precursors. RCP8.5 simulations project ozone increases throughout 

the troposphere, partially driven by the near doubling of methane concentrations by 2100 (compared to 

the present day), and occurring in spite of the decreasing emissions prescribed for the other ozone 

precursors. In these studies, the expected recovery of stratospheric ozone concentrations, due to reduced 

ODSs, combines with an enhanced STE, due to the projected strengthening of the BDC (Section 4.3.2.2), 

to somewhat negate the tropospheric ozone decrease in RCP2.6, 4.5, and 6.0, and enhance the increase in

RCP8.5.

Both Kawase et al. (2011) and Young et al. (2013a) quantify the increases in the net influx of 

stratospheric ozone to the troposphere for the RCPs. For 2100, Kawase et al. (2011) report net influx 

increases of 45%, 80%, 111%, and 109% compared to the present day for RCP2.6, 4.5, 6.0, and 8.5 

respectively (RCP8.5 has a lower net influx due to the large tropospheric ozone increases). The ACCMIP 

models (Young et al., 2013a) exhibit a wide range of net influx increases: 14–90% and 24–139% for 

RCP2.6 and 8.5, respectively. Using different climate and emissions scenarios (and neglecting changes in 

ozone precursor emissions), Zeng et al. (2010) separated the impacts on the net stratospheric ozone influx 

from increasing GHG concentrations (strengthening the BDC) and from ozone recovery, finding that 

approximately half their overall 43% increase in the influx by 2100 was attributable to each factor. 

Moreover, the combined impact of ozone recovery and a strengthened BDC was enough to cancel the 

reduction in tropospheric ozone due to climate change (from enhanced water vapor, leading to more 

ozone destruction; e.g., Johnson et al. (2001). Morgenstern et al. (2014) found a 33% increase in the net 

stratospheric influx by 2050, caused predominantly by ozone recovery.

The range of stratospheric influx changes between models is related to: different treatments of the 

stratosphere, such as whether the model explicitly calculates stratospheric ozone concentrations or uses an 

offline stratospheric ozone data set; what the vertical extent and resolution of the stratosphere is in the 

model, which may influence how the modeled circulation responds to GHG forcing; and the magnitude of 

the troposphere-stratosphere gradient in ozone concentrations, which is important since we are concerned 

with the net ozone influx from STE. Furthermore, different tropopause definitions can affect comparisons 

between studies. Despite the inter-model differences, there is general agreement in the spatial patterns of 

tropospheric ozone change that are qualitatively attributable to an increased stratospheric influx between 

models, such as enhanced ozone in the upper troposphere (at the flanks of the jets), and a quasi-zonal 

increase in the midlatitude tropospheric ozone column (Kawase et al., 2011; Eyring et al., 2013; 

Stevenson et al., 2013; Young et al., 2013a).

As with past changes (Section 4.4.3), the potential impacts of projected stratospheric ozone 

change through UV attenuation have received less attention. Model studies by Voulgarakis et al. (2013) 

and Morgenstern et al. (2014) (correcting Morgenstern et al., 2013) investigated OH and methane lifetime 

changes, finding a significant impact of the modeled stratospheric ozone column changes on the mean 

tropospheric OH concentration (mediated through ozone photolysis), suggesting that differences in 

stratospheric ozone could contribute to the model spread in methane lifetimes.

Overall, simulations are in agreement that stratospheric ozone recovery and climate change 

(through circulation impacts) mean that the net influx of stratospheric ozone could become a more 

important term in the tropospheric ozone budget. Simulations also agree on the broad spatial patterns of 

an enhanced stratospheric input, but there remains a large degree of uncertainty in the magnitude of the 

impact. Models are beginning to include more interactive processes relevant for understanding the role of 

stratospheric change on tropospheric composition (e.g., stratospheric chemistry, interactive photolysis 

calculations), but it remains to be seen whether an ensemble of models with more consistent processes 

will reduce or increase the inter-model spread. 
Stratospheric Ozone and Climate

4.43

POLICY-RELEVANT INFORMATION

There is further evidence that Antarctic ozone depletion has influenced the Southern Hemisphere 

surface climate and ocean.

The Antarctic ozone hole was first linked to changes in the tropospheric circulation in the early 

2000s. In the decade or so since, a strong case has been built for the dominance of ozone depletion in 

driving the Southern Hemisphere summertime circulation changes in recent decades. A poleward shift in 

the circulation, including the position of the midlatitude jet and storm tracks, has been observed in austral 

summer. Since the last Ozone Assessment, the contribution of ozone depletion to Southern Hemisphere 

summertime circulation changes over the past three to five decades has been better quantified and shown 

to be considerably larger than that from greenhouse gases, in most studies. No robust link between 

stratospheric ozone changes and Northern Hemisphere tropospheric climate has been found, consistent 

with the conclusions of the previous Ozone Assessment.

The ozone hole impacts the Southern Hemisphere tropospheric circulation by cooling the polar 

lower stratosphere in spring, which increases the gradient in temperature between the equator and pole. 

While the precise mechanism by which this then shifts the tropospheric midlatitude jet poleward is still 

unclear, such a response is robustly simulated in models. New research has found that ozone depletion has 

likely contributed to the observed expansion of the Southern Hemisphere Hadley Cell, with models 

simulating an associated pattern of increased summertime precipitation in the subtropics. An improved 

understanding of the role of ocean eddies in the response of the Southern Ocean to observed wind stress 

changes (partly due to ozone depletion) has also been gained, and models and observations provide 

evidence that these wind stress changes have strengthened the overturning circulation in the Southern 

Ocean. This may have led to a reduction in the amount of carbon uptake by the Southern Ocean, but large 

uncertainties remain in both observing and simulating this process. Additional research since the previous 

Ozone Assessment has shown that coupled models simulate a decrease in hemispheric-mean Antarctic 

sea-ice extent in response to ozone depletion. However, there is low confidence in this model result 

because these models also simulate a decrease in Antarctic sea-ice extent when driven by all major 

anthropogenic and natural forcings, in contrast to the small observed increase since 1979. Figure 4-22

schematically summarizes the impact of ozone depletion on the climate system.

Figure 4-22. Schematic 

illustration of Southern Hemisphere climate impacts in 

austral summer associated 

with Antarctic ozone depletion. Ozone depletion has 

cooled the Antarctic stratosphere, very likely shifting 

the region of strong westerly

winds and associated rainfall southward in the summer.

These changes in midlatitude winds have likely led 

to changes in the ocean circulation. Ozone depletion 

has also likely contributed to a southward expansion of the tropical circulation in summer, and may have 

increased subtropical rainfall. 
Chapter 4

4.44

With the ozone hole expected to recover over coming decades, the climate impacts of stratospheric 

ozone change in the future will be opposite to those of the past. Meanwhile, GHGs are projected to keep 

increasing, driving circulation effects that oppose those of ozone recovery. Hence, climate model 

simulations show that summer trends in the Southern Hemisphere tropospheric circulation over the next 

fifty years will likely be weaker than those over the past few decades. New simulations since the last Ozone 

Assessment have allowed an assessment of the impacts of ozone recovery under various scenarios of future 

emissions, compared to the single emissions scenario previously assessed. In all scenarios, ozone 

recovery acts to weaken the circulation changes induced by greenhouse gases alone. In a scenario with low 

greenhouse gas emissions, ozone recovery is found to dominate the Southern Hemisphere summer 

circulation changes, shifting the midlatitude jet equatorward.

Stratospheric ozone changes are the dominant driver of globally averaged cooling in the lower 

stratosphere. 

Stratospheric temperature changes are important indicators of the impact of anthropogenic 

emissions on climate. There is robust evidence that changes in composition in the stratosphere have 

resulted in radiative cooling of the stratosphere over the past three decades. Weather balloons have been 

providing vertically resolved temperatures since 1958 but are sparse geographically and only cover the 

lower stratosphere. Hence, most of the information about stratospheric temperature change comes from 

satellite measurements. Satellite observations provide good global coverage of the stratosphere since the 

late 1970s but have coarser vertical resolution than the balloon data. 

New research since the previous Ozone Assessment has led to a better understanding of the 

uncertainties in stratospheric temperature changes. Lower stratospheric temperature trends have been 

analyzed by numerous groups and, while some differences exist between data sets, a global cooling of 

approximately 1°C over the 1979–2012 period is found across these data sets. For the middle and upper 

stratosphere, however, only one data set was available at the time of the 2010 Ozone Assessment, making 

estimates of uncertainty difficult. An additional analysis of the Stratospheric Sounding Unit (SSU) 

satellite measurements published in 2012 tells quite a different story from the previous data set. While 

both data sets show global cooling, the new data set shows a cooling almost twice as large as the original 

analysis in the middle stratosphere. Comparison with modeled trends provided little insight into the cause 

of these differences, though planned updates to the data sets may help to resolve some of the 

discrepancies.

Since the previous Ozone Assessment, a number of carefully designed model experiments have 

been undertaken to quantify the contribution of ozone depletion to recent climate change. Based on these 

and earlier experiments, cooling in the lower stratosphere over Antarctica in spring and summer has been 

clearly attributed to Antarctic ozone depletion by multiple studies. In the tropics, one study suggests that 

ozone depletion is the main driver of lower stratospheric cooling there, though uncertainties in ozone 

concentrations used to force the models are tightly linked to uncertainties in the temperatures. Globally, 

several studies have shown that ozone changes are the dominant driver of lower stratospheric cooling.

New estimates of global mean ozone radiative forcing due to emissions of ozone-depleting 

substances, which account for stratospheric ozone change and its indirect effect on tropospheric 

ozone, indicate a stronger surface cooling effect than that due to stratospheric ozone changes 

alone. 

Radiative forcing — the net change in the energy balance at the tropopause due to an imposed 

perturbation — has been further developed within the IPCC Fifth Assessment Report. A new term 

“Effective Radiative Forcing” was defined to encompass rapid adjustments in the troposphere as well as 

the traditional stratospheric adjustment. This quantity is more closely associated with the resulting 

temperature changes. Radiative forcings are assessed at 2010.

This Assessment, for the first time, considers the radiative forcing from the effects of ODS 

emissions on ozone, including impacts on both tropospheric and stratospheric ozone, which is assessed to 
Stratospheric Ozone and Climate

4.45

be −0.15 [−0.3 to 0] W m-2. Approximately three-quarters of this radiative forcing results from ozone 

changes in the stratosphere. There is also the possibility of an induced forcing from rapid adjustment 

effects on clouds, associated with ozone-driven changes in the Southern Hemisphere tropospheric 

circulation, and a second possible effect due to ozone-induced wind changes increasing sea salt aerosol 

over the Southern Ocean. These rapid adjustments could be of a comparable size to the direct ozone 

radiative forcing and could be of either sign. Overall, this makes the sign of the Effective Radiative 

Forcing, which includes such adjustments, unknown at present. 

Estimates of radiative forcing are very sensitive to the latitudinal and vertical distribution of 

ozone. Observations and models suggest that increasing greenhouse gases have accelerated the shallow 

branch of the Brewer-Dobson circulation, leading to a decrease of lower stratospheric ozone in the tropics 

and an increase in midlatitudes, with additional impacts on tropospheric ozone. A further acceleration of 

the Brewer-Dobson circulation is projected due to future greenhouse gas increases. This implies that the 

distribution of ozone will not recover to its pre-depletion spatial state, which has implications for 

projections of radiative forcing. Model estimates for stratospheric ozone radiative forcing by 2100 are 

highly uncertain, ranging from slightly negative to exceeding +0.25 W m-2 under a high greenhouse gas 

emissions scenario. 

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CHAPTER 5

Scenarios and Information for Policymakers

Lead Authors:

N.R.P. Harris

D.J. Wuebbles

Coauthors:

J.S. Daniel

J. Hu

L.J.M. Kuijpers

K.S. Law

M.J. Prather

R. Schofield

Contributors:

J.B. Burkholder

E.L. Fleming

Ø. Hodnebrog

R. Hossaini

C.H. Jackman

D. Phoenix

Chapter Editors:

M. McFarland

G.J.M. Velders
[Formatted for double-sided printing.]

From: 

WMO (World Meteorological Organization), Scientific Assessment of Ozone Depletion: 2014, Global 

Ozone Research and Monitoring Project – Report No. 55, 416 pp., Geneva, Switzerland, 2014.

This chapter should be cited as: 

N.R.P. Harris and D.J.Wuebbles (Lead Authors), J.S. Daniel, J. Hu, L.J.M. Kuijpers, K.S. Law, M.J. 

Prather, and R. Schofield, Scenarios and information for policymakers, Chapter 5 in Scientific Assessment 

of Ozone Depletion: 2014, Global Ozone Research and Monitoring Project – Report No. 55, World 

Meteorological Organization, Geneva, Switzerland, 2014.
CHAPTER 5

SCENARIOS AND INFORMATION FOR POLICYMAKERS

Contents

SCIENTIFIC SUMMARY ........................................................................................................................... 1

5.1 INTRODUCTION.................................................................................................................................. 5

5.1.1 Main Issues from WMO-UNEP 2010 and Other Reports......................................................... 5

5.1.2 Objectives of This Assessment.................................................................................................. 6

5.2 ISSUES OF POTENTIAL IMPORTANCE TO STRATOSPHERIC OZONE AND CLIMATE ........ 7

5.2.1 Halocarbons Controlled Under the Montreal Protocol.............................................................. 7

5.2.2 Replacement Compounds.......................................................................................................... 8

5.2.3 HFC-23 9

5.2.4 Biogenically Produced Short-Lived Halocarbons..................................................................... 9

5.2.5 Breakdown Products................................................................................................................ 11

5.2.6 Nitrous Oxide, Methane, and Carbon Dioxide........................................................................ 11

5.2.7 Stratospheric Water Vapor ...................................................................................................... 11

5.2.8 Stratospheric Aerosols............................................................................................................. 12

5.2.9 Other Proposed Influences on Stratospheric Ozone................................................................ 12

5.3 METRICS FOR CHANGES IN OZONE AND CLIMATE................................................................ 15

5.3.1 Metrics for Changes in Ozone................................................................................................. 15

5.3.2 Metrics for Changes in Climate............................................................................................... 23

5.4 SCENARIOS AND SENSITIVITY ANALYSES............................................................................... 28

5.4.1 Tools Used in Analyses of Ozone and Climate Effects .......................................................... 28

5.4.2 Background Scenario(s) for Ozone and Climate..................................................................... 29

5.4.3 Alternative Future Scenarios................................................................................................... 31

5.4.4 Radiative Forcing on Climate.................................................................................................. 37

5.4.5 Replacements for High-GWP HFCs ....................................................................................... 38

REFERENCES ......................................................................................................................................... 41

APPENDIX 5A ......................................................................................................................................... 49

Table 5A-1: Analyses of GWPs and GTPs

Table 5A-2: Baseline Scenario Mixing Ratios

Scenarios and Information for Policymakers

5.1

SCIENTIFIC SUMMARY

A new baseline scenario for ozone-depleting substances (ODSs) is presented in Chapter 5 that 

reflects our current understanding of atmospheric mixing ratios, production levels, and bank sizes. 

Elimination of future emissions, from either production or existing banks of various ODSs, is applied to 

this scenario to evaluate the maximum impacts of various hypothetical policy options including phaseouts and destruction (see Table S5-1). Some specific findings corresponding to this table include:

• Emissions from the current banks (taking 2015 as being current) over the next 35 years are 

projected to lead to greater future ozone depletion and climate forcing than those caused by 

future ODS production. Capture and destruction of these banks could avoid 1.8 million Ozone 

Depletion Potential-tonnes (ODP-tonnes) of future emission through 2050; this compares with an 

estimated 1.6 million ODP-tonnes of emissions that have occurred over the last decade (from 

2005–2014).

• Of all of the ODS banks, the banks of halons in 2015 are projected to contribute most to 

ozone depletion over the next 35 years (as Equivalent Effective Stratospheric Chlorine, 

EESC), while chlorofluorocarbon (CFC) and hydrochlorofluorocarbons (HCFC) banks are 

expected to contribute most in terms of Global Warming Potential-weighted (GWPweighted) emissions.

• If future production and all ODS 2015 banks are considered, HCFCs represent the 

halocarbon group that contributes most to future GWP-weighted emissions. HCFCs can be 

reduced in the future by both bank recapture and destruction and by production 

elimination.

Table S5-1. Summary of mitigation options for accelerating the recovery of the ozone layer and 

reducing CO2-equivalent emissions. The table gives the reductions in integrated EESC (Equivalent 

Effective Stratospheric Chlorine) and integrated CO2-equivalent emissions relative to the baseline 

scenario that can be achieved for mitigation options beginning in 2015 or 2020. The integrated EESC is 

defined as the total EESC amount integrated from 2015 until the time EESC returns to the 1980 level 

(before 2050 for all scenarios). Bank recapture and destruction is assumed to be 100% effective and 

either applies to the bank existing in 2015 or the bank existing in 2020. Any potential contribution from 

very short-lived substances is neglected. These calculations use the lifetimes derived from SPARC, 

2013 (Stratosphere-troposphere Processes And their Role in Climate).

Substance or Group of 

Substances

Reductions (%) in Integrated 

Midlatitude EESC Integrated from 

2015 until EESC Returns to 1980 

Levels

Reduction in Cumulative GWPWeighted Emissions from 2015 

to 2050 (Gigatonnes of CO2-

equivalent)

Bank recapture and 

destruction in 2015 or 2020:

2015 bank 2020 bank 2015 bank 2020 bank

CFCs 8.9 5.3 4.7 3.3

halons 12 6.8 0.2 0.2

HCFCs 6.4 5.5 4.6 4.6

Production elimination from 2015 onward:

HCFCs 6.4 7.8

CH3Br 

(only quarantine and pre-shipment)

5.3 0.0

Total emissions elimination from 2015 onward:

CCl4 9.8 1.2

CH3CCl3 0.0 0.0

HFCs 0.0 Up to 165*

* Reduction relative to hypothetical future upper range scenario and would depend on actual growth rate of HFC use.
Chapter 5

5.2

• The impact on ozone-layer recovery of further policy actions on already controlled ozonedepleting substances is becoming smaller. Nonetheless, if all ODS emissions – including those 

emanating from many widely dispersed banks – were to be stopped in 2015, then the return to 1980 

midlatitude EESC values would be brought forward to 2036 compared with 2047 in the baseline 

scenario.

• Updated Ozone Depletion Potentials (ODPs) are almost all numerically smaller, ranging from 

no change (for carbon tetrachloride, CCl4) to more than a factor of two smaller (for CFC-115), 

with most of these smaller by 10–30% than the values reported in WMO (2011). These changes 

largely reflect the revised estimate for the atmospheric lifetime of CFC-11 (from 45 to 52 years) 

reported in SPARC (2013); CFC-11 is the reference gas in determining ODPs so this change affects 

all ODPs. Uncertainties in the atmospheric lifetimes, the fractional release values, and atmospheric 

chemistry generally result in overall uncertainties in ODPs on the order of 30% for the CFCs and 

CCl4, but are higher for HCFCs and halons (about 60% for the HCFCs and halon-1301, to over 80% 

for halon-1202 and halon-1211).

• New atmospheric model studies continue to emphasize that ODPs for very short-lived 

substances (VSLS) that contain bromine or chlorine are strongly dependent on the geographic 

location and season of emission. Impacts from VSLS are much larger (with ODPs approaching 

values of 1) if emissions occur in regions close to convective regions in the tropics. There is still 

insufficient research available to confidently compare the mitigation options of anthropogenic VSLS 

emissions with those of the longer-lived halogenated hydrocarbons; overall the VSLS have smaller 

ODPs than longer-lived ODS. However, if long-lived controlled halocarbons (and their banks) follow 

their projected decline, then chlorine- and bromine-containing anthropogenic VSLS emissions will 

play a relatively larger role in future ozone depletion, but the absolute effects are smaller than that of 

ODSs today while remaining uncertain.

• The projection of CCl4 remains more uncertain than projections for other ODSs due to our 

incomplete understanding of the current CCl4 budget (likely a missing source; see Chapter 1).

In the scenarios examined (see table above), CCl4 human-related emissions from 2015 through 2050 

are comparable to those of the HCFCs in terms of ODP-weighted emissions and are about 10% in 

terms of GWP-weighted emissions. It is expected that future emissions of CCl4 will remain an 

important factor in the evolution of EESC.

• The total anthropogenic emissions of methyl bromide (CH3Br) have declined in response to 

controls of the Montreal Protocol. Overall, reported consumption has gone down from ~70,000 

tonnes/yr in the late 1990s to ~13,000 tonnes/yr in 2012.

• Quarantine and pre-shipment (QPS) uses of CH3Br are exempted uses (not controlled) by the 

Montreal Protocol and in 2012 constitute an annual consumption of CH3Br (~9,000 tonnes) that 

is larger than the annual consumption for 2012 from uses controlled by the Protocol (~4,000 

tonnes). The elimination of future emissions from QPS uses could bring forward the date of EESC 

return to 1980 levels by 1.1 years, smaller than the 1.6 years estimated in the previous Assessment. 

Critical-use exemptions continue to be granted, but at levels significantly reduced compared with four 

years ago. A continuation of critical-use exemptions at the current level would delay the return of 

EESC to 1980 levels by 0.2 years.

• Carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) are each important to climate 

forcing and to the levels of stratospheric ozone (see Chapter 2). In terms of the globally averaged 

ozone column, additional N2O leads to lower ozone levels, whereas additional CO2 and CH4 lead to 

higher ozone levels. Ozone depletion to date would have been greater if not for the historical 

increases in CO2 and CH4. The net impact on ozone recovery and future levels of stratospheric ozone 

thus depends on the future abundances of these gases. For many of the scenarios used in the most 

recent Intergovernmental Panel on Climate Change (IPCC) Assessment (IPCC, 2013), global ozone 
Scenarios and Information for Policymakers

5.3

will increase to above pre-1980 levels due to future trends in the gases. Latitudinal and altitudinal 

responses are expected to vary. Note that scenarios used in IPCC consider a future with all three 

major greenhouse gases increasing and thus it is important to assess the net balance of these 

perturbations on stratospheric ozone.

• Global Warming Potentials (GWPs) for a range of halocarbons have been updated based on 

IPCC (2013) and SPARC (2013). The CO2 Absolute Global Warming Potential (AGWP; the 

denominator for the GWP of other greenhouse gases) has increased by 6% compared to the previous 

Assessment (WMO, 2011). As a result, GWP values for many non-CO2 greenhouse gases decreased 

slightly. GWPs also changed because of revised values for the lifetime and the radiative efficiency of 

the individual greenhouse gases. The revised SPARC-based lifetimes for a range of ODSs have been 

updated due to new analyses of observations and models and are included here; the largest differences 

in GWPs are found for CFC-11, CFC-115, halon-1301, halon-2402, and halon-1202. For 

hydrofluorocarbons (HFCs), some examples of the IPCC 100-year GWPs and the SPARC lifetime 

adjusted values are given below. The numbers in parentheses represent the effects of uncertainties in 

the SPARC lifetimes, radiative efficiency, and the AGWP for CO2 based on 90% confidence. In 

addition, the IPCC (2013) stated uncertainties in the 100-year GWP for HFC-134a is ±35% (90% 

confidence) as representative for similar gases. The IPCC and updated GWPs that use the SPARC 

lifetimes are consistent within their uncertainties. 

Substance IPCC AR5 100-yr 

GWP

Updated 100-yr GWP (90% 

uncertainty range)

HFC-23 12,400 12,500 (8880–16,300)

HFC-32 677 704 (453–1070)

HFC-125 3170 3450 (2230–5140)

HFC-134a 1300 1360 (857–2050)

HFC-143a 4800 5080 (3460–7310)

HFC-152a 138 148 (96–211)

• Global Temperature Potentials (GTPs) are discussed and values reported for the first time in a 

WMO-UNEP Ozone Assessment. The GTP metric gives the relative temperature increase at a 

specified time horizon due to emissions of a greenhouse gas, relative to that caused by the same 

weight of CO2 emissions. This metric may be useful as an alternative to GWPs. These metrics are 

different in construction and have both advantages and disadvantages. The revised SPARC-based

lifetimes affect GTPs (relative to IPCC, 2013) in the same way as GWPs. The table below shows 

updated GTPs for the same HFCs listed above.

Substance Updated 20-yr 

GTP

Updated 50-year 

GTP 

Updated 100-year 

GTP

HFC-23 11,500 13,000 12,800

HFC-32 1440 154 98

HFC-125 6040 3350 1180

HFC-134a 3170 771 214

HFC-143a 7110 5390 2830

HFC-152a 191 26 21

• The current direct radiative forcing (RF) from ODS halocarbons (CFCs, halons, and HCFCs) is 

about 0.33 W m-2 and is near its expected peak. The RF is projected to decrease to about 0.20 W 

m-2 by about 2050, depending on the particular emission scenario adopted. By 2100, the radiative 

forcing from these halocarbons is projected to be near 0.10 W m-2 independent of the specific 

emission scenarios considered here.
Chapter 5

5.4

• While HFCs currently constitute less than 1% of the radiative forcing on climate (0.02 W m-2), 

if the current mix of HFCs is unchanged, increasing demand could imply a radiative forcing for 

HFCs as high as 0.4 W m-2 by 2050. For all scenarios (Special Report on Emissions Scenarios 

(SRES) and Representative Concentration Pathway (RCP)) used in the recent IPCC Assessments, the 

HFC radiative forcing increases by 0.1 W m-2 or less by 2050; however, these scenarios did not 

consider recent market trends. Scenarios based on projections of HFC markets yield radiative forcings 

that range from 0.16 W m-2 to 0.4 W m-2 by 2050. 

• Replacements of the current mix of high-GWP HFCs with low- or zero-ODP, low-GWP 

compounds, could lead to a decrease in the radiative forcing on climate over the coming 

decades, possibly by as much as 0.07 W m-2 by 2030 relative to baseline scenarios assuming 

continued growth in high-GWP HFC production. Such reductions are comparable to possible 

reductions in radiative forcing for some other non-CO2 emissions (e.g., for black carbon emissions). 

Even by 2050, the RF from the low-GWP replacement compounds would be negligibly small. For the 

uses projected, such replacements are likely to have a negligible effect on stratospheric ozone, despite 

some replacements containing chlorine or bromine and having non-zero ODPs. 

• The impact of HFC mitigation on future climate change that only considers radiative forcing of 

HFCs through a particular year is underestimated if the future commitment to climate forcing 

in the HFC banks is neglected. This bank size represents a substantially larger fraction of the 

cumulative HFC production and emission than was the case for CFCs in the 1980s; this is because 

current and projected applications for HFCs emit those HFCs much more slowly than applications 

historically did for CFCs. 

• Unsaturated HFCs (also known as hydrofluoro-olefins, HFOs) are replacement compounds for 

long-lived HCFCs and HFCs. Unsaturated HFCs have short atmospheric lifetimes (days) and small 

GWPs (<10). Atmospheric degradation of one of these substances (HFC-1234yf) produces the 

persistent degradation product trifluoroacetic acid (TFA). While the environmental effects of TFA are 

considered negligible over the next decades, potential longer-term impacts could require future 

evaluations due to the environmental persistence of TFA and uncertainty in future uses of HFC1234yf.

• CFC-316c ((E)- and (Z)- isomers of cyclic 1,2-C4F6Cl2) are possible ODS replacement 

compounds, and have long lifetimes (75 and 114 years), with correspondingly high ODPs (0.46 

and 0.54) and GWPs (4160 and 5400).

• Emissions of biogenically produced bromocarbons will likely increase as a result of changes in 

the management of their human-related production (e.g., marine aquaculture). However, 

uncertainties in all natural emissions and in transport to the stratosphere are large, making it difficult 

to quantify their effects on ozone.

• Current emissions from aviation and rockets have only a small effect on total ozone (<1%). 

However, new technologies and potential market growth in aviation and rockets will require 

further assessment as they could potentially lead to effects on ozone.

• Geoengineering the climate system via anthropogenic increases of stratospheric sulfate aerosols 

within the next few decades would be expected to deplete stratospheric ozone, with the largest 

effects in the polar regions. The current level of understanding of how other possible geoengineering 

approaches would affect the stratosphere is limited.

• The proposed cosmic-ray-driven breakdown of CFCs in ice particles is of negligible importance 

in polar ozone loss.
Scenarios and Information for Policymakers

5.5

5.1 INTRODUCTION

The series of WMO Ozone Assessments have reported the success of the control measures 

introduced under the Montreal Protocol. These have included striking reductions first in the rate of increase 

in atmospheric ozone-depleting substances (ODSs) and subsequently in the total amount of ODSs in the 

atmosphere (see Chapter 1). Signs of an increase in stratospheric ozone amounts are emerging (Chapter 2),

pointing to the success of these measures in reducing ozone depletion and hence limiting the resulting 

increases in surface UV radiation. As successive Amendments and adjustments to the Montreal Protocol 

have been introduced, opportunities for further significant measures affecting stratospheric ozone have 

become scarcer. Accordingly, policy-relevant issues are now largely concentrated on (i) issues connected 

with new compounds with the potential to deplete ozone and (ii) the other atmospheric effects of ODSs and 

their replacements. In addition, the Montreal Protocol and its Amendments have at this point contributed 

more to climate change mitigation than any other existing international agreement.

In this section, the main points from the WMO Ozone Assessment (2011) are first summarized. 

Then, the objectives and the contents of this chapter are described.

5.1.1 Main Issues from WMO-UNEP 2010 and Other Reports

In several respects, this chapter is an update of Chapter 5 in WMO (2011). In that chapter, Ozone 

Depletion Potentials (ODPs) and Global Warming Potentials (GWPs) for ODSs and their replacements 

were updated. New scenarios were generated to explore the potential impacts of hypothetical ODS and 

nitrous oxide (N2O) emissions reductions on future ozone depletion and climate forcing. The WMO 

(2011) chapter additionally included assessments of some processes and activities (e.g., from rockets or 

from the possible uses of geoengineering as a response to climate change) that may affect future ozone 

levels through mechanisms that do not necessarily involve the emission of chlorine- and brominecontaining source gases. It was found that some of these processes could affect future ozone levels more 

than future emissions of controlled ODSs. The impact of the Montreal Protocol on climate forcing was 

discussed. Finally, the chapter showed how the Montreal Protocol and its Amendments and adjustments 

had averted many profound changes to Earth and its atmosphere. In particular, because many ODSs are 

potent greenhouse gases, the Montreal Protocol has successfully avoided larger potential changes to the 

Earth’s climate. Two specific issues raised there are worth mentioning as they are looked into again here. 

First, the effects of the accelerated phase-out of HCFCs (hydrochlorofluorocarbons) agreed to by 

the Parties to the Montreal Protocol in 2007 were projected as a reduction in cumulative HCFC emissions 

between 2011 and 2050 of 0.6–0.8 million ODP-tonnes, equivalent to bringing forward the year in which 

Equivalent Effective Stratospheric Chlorine (EESC) returns to 1980 levels by 4–5 years. In addition, the 

accelerated HCFC phase-out was projected to reduce emissions by 0.4–0.6 gigatonnes of carbon dioxideequivalents (GtCO2-eq) per year averaged over 2011–2050. The net climate benefit is determined, in part, 

by the climate impact of the compounds used to replace the HCFCs. If high GWP HFCs (hydrofluorocarbons) were to be used without mitigation, it was estimated that the HFC growth could result in 

GWP-weighted emissions up to 8.8 GtCO2-eq per year by 2050. This amount is comparable to the GWPweighted emissions of chlorofluorocarbons (CFCs) at their peak in 1988. The projected radiative forcing 

in 2050 from these compounds (up to 0.4 watts per square meter (W m-2)) could be reduced by using 

replacement compounds with lower GWP values that also have low ODPs. 

Second, the options available for further reductions in future halocarbon emissions were 

recognized as becoming more limited. However, for reducing the risk of future increases in atmospheric 

concentrations, the Assessment showed it would be important to minimize any leakage of CFCs and 

halons from banked storage (or “banks,” the largest source of current ODP-weighted emissions of ODSs). 

A delay of four years, from 2011 to 2015, in the capture and destruction of the estimated CFC and halon 

banks was estimated to reduce the potential ozone and climate benefits from these actions by about 30%.
Chapter 5

5.6

Since the last WMO Assessment, several reports have addressed topics of direct interest for this 

chapter:

1) The UNEP synthesis report, “HFCs: A Critical Link in Protecting Climate and the Ozone Layer”

(UNEP, 2011). It concluded that limiting the future growth of HFCs could result in unrealized emissions 

(emissions that would have otherwise occurred) corresponding to as much as 7–19% of the CO2

emissions that year. Alternative technological options exist that minimize the climate impact of HFCs. 

Issues related to future scenarios in HFC and other ODS alternatives are addressed in this chapter.

2) The SPARC report, “Lifetimes of Stratospheric Ozone-Depleting Substances, Their Replacements,

and Related Species” (SPARC, 2013). This report provides a thorough and consistent re-assessment 

of the lifetimes for a number of halocarbons as well as in-depth analysis of the associated 

uncertainties (Chapter 1, Box 1-1). These values are discussed in Chapter 1 and are used in the 

metric and scenario evaluations presented in this chapter. 

3) Reports produced by the UNEP Technology and Economic Assessment Panel (TEAP). These reports

continue to assess the technological and economic possibilities for phasing in commercially 

available replacements for ODSs (e.g., UNEP, 2013).

4) The Fifth Assessment Report of the Intergovernmental Panel on Climate Change, “Climate Change 

2013 – The Physical Science Basis” (IPCC, 2013). This report includes updated values of metrics such 

as Global Warming Potentials. These are updated in this chapter using the SPARC (2013) lifetimes. 

5.1.2 Objectives of This Assessment

The overall aim of this chapter is to present policy-relevant information. It includes an assessment 

of the possible options available to policymakers related to protection of stratospheric ozone (and effects 

on climate from halocarbons). In Section 5.2, recent developments in the understanding of the main 

ozone-depleting compounds, anthropogenic and natural, are summarized with emphasis on their 

importance for future stratospheric ozone depletion, other impacts such as the role of their breakdown 

products, and their influence on climate. The impacts of real and potential replacement products are 

similarly discussed. Special attention is given to the additional complexities associated with evaluating 

the effects from short-lived substances with spatially and temporally varying sources and sinks. Finally in 

Section 5.2, other potential influences on stratospheric ozone (e.g., other atmospheric changes, rockets, 

geoengineering) are considered.

Simple quantitative measures have been used to provide information about the effect of emissions 

from human activity on the atmosphere. These include Ozone Depletion Potentials (ODPs), Global 

Warming Potentials (GWPs), and radiative forcing (RF), which can be used to compare the relative effect 

of individual gases, as well as Equivalent Effective Stratospheric Chlorine (EESC) which is a measure of 

the combined impact of all chlorine- and bromine-containing gases. Estimates of these are discussed in 

Section 5.3, and updated values are presented based on the recently updated estimates of atmospheric

lifetimes (SPARC, 2013). In addition, newer measures, such as Global Temperature change Potentials 

(GTPs), are discussed here for the first time in a WMO Assessment.

Section 5.4 concludes the chapter with an examination of a range of scenarios. These are compared 

to a new baseline that is consistent with the existing observational record for atmospheric concentrations of 

halocarbons and the current limits on emissions contained in the Montreal Protocol. The scenarios 

investigate effects of hypothetical changes in emissions and are illustrative of potential mitigation actions

such as controls on banks (see Box 5-1). The halocarbon lifetimes used are those reported in SPARC 

(2013). The baseline emission scenario for CO2, methane (CH4), and N2O is taken as the RCP6.0 scenario

(van Vuuren et al., 2011; IPCC, 2013). The sensitivity of the calculated impact on the stratosphere is investigated by additionally using the RCP4.5 and RCP8.5 scenarios. (Representative Concentration Pathways 

are well established in the climate community and used as a basis for climate modeling experiments (van 

Vuuren et al., 2011; Chapter 4).) EESC is used where possible and additional calculations are performed 

using a two-dimensional (2-D) coupled chemistry-radiation-dynamics model (Fleming et al., 2011).
Scenarios and Information for Policymakers

5.7

Box 5-1. Halocarbon Banks

The bank of a manufactured compound is defined as the quantity of that compound stored in 

equipment and products and held as chemical inventory. The size of the bank will increase as long as the 

production of a compound is larger than the release into the atmosphere. Any compound produced and 

kept in equipment will either increase the size of the bank or be used to compensate for leakage. Leakage 

is the amount released to the environment by physical leakage or by accidental leakage occurring in 

regular use, accidents, and maintenance.

For ODS and their replacements, bottom-up estimates of the banks are calculated on the basis of 

the total amount of equipment and products manufactured per year per country (or per region), and their 

assumed charges (or contents in the case of products). These bottom-up estimates are generally less 

accurate than either the amount of a given compound produced or the amount in the atmosphere, which is 

accurately known from atmospheric measurements. An alternative way to estimate the bank is by taking 

the difference between the amount produced and the amount released to the atmosphere.

Banks tend to decrease when products and equipment are taken from the market or their use 

stops. In the absence of specific measures, there will be leakage of the contents of the products to the 

environment. This release can be avoided by recovery and capture. The captured material can either be 

used or destroyed. Reporting the amounts of ODSs recovered, recycled, or destroyed is not required under 

the Montreal Protocol, leading to uncertainty in the size of the bank. However, the success of this option 

can be limited as a result of either cost or logistical problems. TEAP report XX/8 2009 describes the 

options for destroying ODS chemicals for different regions and a range of scenarios (UNEP, 2009).

Scenarios of future banks and their composition are based on assumptions of economic 

development, patterns in society (e.g., number of coolers in supermarkets, air conditioners, etc.), and the 

expected market penetration of alternative compounds and technologies. Containment, recovery and 

recycling, and destruction at the end of product life can reduce emissions to the atmosphere. This can be 

achieved by reducing leakage during operation and use and/or by ensuring high rates of recovery and 

capture at the end of the useful lifetime of equipment. The potential impact of such controls on 

atmospheric concentrations of CFCs, halons, HCFCs, and HFCs are investigated in Section 5.4. 

5.2 ISSUES OF POTENTIAL IMPORTANCE TO STRATOSPHERIC OZONE AND CLIMATE

5.2.1 Halocarbons Controlled Under the Montreal Protocol

The success of the Montreal Protocol in limiting the atmospheric abundance of ODSs is now well 

documented. Implementation of its measures has resulted in significantly lower EESC than would 

otherwise have occurred (WMO, 2011 and preceding reports) as well as reductions in radiative forcing of 

climate change. Chapter 1 in this report finds that this success in limiting CFC and halon abundances has 

continued, though it notes large discrepancies between top-down and bottom-up emission estimates for 

halon-2402 and carbon tetrachloride (CCl4). In WMO (2011), leakage of CFCs and halons from their 

banks (see Box 5-1) was found to be the largest source to the atmosphere, and so the main policy option 

presented was to reduce the leakage. This issue is investigated further in Section 5.4. Revised ODPs and 

GWPs for the CFCs and halons are presented in Section 5.3 based on the recommendations for the 

lifetimes made in SPARC (2013).

Part of the decrease in CFC usage in the 1990s was achieved by finding chemical substitutes for

CFCs, including HCFCs and HFCs. Due to their lower, but non-zero ODPs, the HCFCs were defined by 

the Parties as transitional compounds and a first phase-out schedule for them was established in 1992. In 

order to accelerate the reduction in EESC, accelerated phase-out schedules for HCFCs were agreed under 

the Montreal Protocol in 2007. The implementation of these measures has been occurring gradually since 

that time, and it is expected that the overall effects will be observed as a decrease in first the growth rate 
Chapter 5

5.8

and then the atmospheric abundance of HCFCs. Chapter 1 reports that the increases over 2009–2012 for 

the main three HCFCs are smaller than those for 2006–2009. Presumably this has occurred in anticipation 

of the introduction of new measures following the accelerated phase-out agreement in 2007. Updated 

atmospheric measurements and lifetimes for HCFCs are used in the revised ODPs and GWPs presented 

and discussed in Section 5.3 and the scenarios presented in Section 5.4.

An inconsistency in the carbon tetrachloride (CCl4) budget was reported in WMO (2011), as the 

decline in atmospheric CCl4 concentrations was less than expected. Chapter 1 in this Assessment 

concludes that this discrepancy remains as there is a continued imbalance between the emissions of CCl4

inferred from the observed changes in global concentration and the bottom-up estimates of the

anthropogenic emissions. This difference cannot solely be explained by adjusting the atmospheric 

lifetime. Chapter 1 suggests that there may be ongoing anthropogenic emissions in the Northern 

Hemisphere. The implications of this uncertainty on future EESC are discussed further in Section 5.4.

Atmospheric methyl bromide (CH3Br) results from anthropogenic and natural emissions. The 

partitioning between them has been the subject of much debate in the past (WMO, 2003, 2007. 2011). 

The continued decline in tropospheric CH3Br amounts is caused by reductions in the controlled industrial 

production, consumption, and emission (see Chapter 1 for further analysis of the CH3Br emissions and 

budget). The anthropogenic uses fall into three categories: (1) the controlled applications (soil and 

postharvest fumigation and commodity disinfestation); (2) quarantine and pre-shipment (QPS) exempted 

applications, which are reported under the Montreal Protocol; and (3) feedstock uses exempted but 

reported under the Montreal Protocol. The annual global total consumption for non-QPS uses of CH3Br 

has decreased steadily as a result of the implementation of the Montreal Protocol, from over 50,000

tonnes/yr in the late 1990s to about 4,000 tonnes/yr in 2012 (Figure 1-6-6 of UNEP, 2013). This 

compares to a change in total consumption from about 70,000 tonnes/yr to about 20,000 tonnes/yr over 

the same period. Critical-use exemptions for the controlled uses are applied for by developed country 

(non-Article 5) Parties and have been granted annually since 2005. Fewer critical-use exemptions are 

being granted, as alternative approaches are more often available. The phase-out of controlled uses in 

Article 5 Parties by 1/1/2015 may result in additional applications for critical-use exemptions in the 

coming years (four Article 5 Parties have already applied for critical-use exemptions for 2015). The 

annual use for QPS is currently about 9,000 tonnes and is approximately steady (UNEP, 2013; Figure 1-

6-6). In general, use for QPS has decreased in non-Article 5 and increased in Article 5 Parties. Feedstock 

production is estimated at about 3,900 tonnes in 2012; however, this should not result in any significant 

emissions. Total global production in 2012 was 16,700 tonnes, down from 35,000 tonnes in 2006.

Scenarios for possible future emissions of CH3Br are discussed in Section 5.4. 

5.2.2 Replacement Compounds

The majority of the reduction in ODS emissions has occurred as a result of not-in-kind technology, 

such as containment, recovery and recycling, and non-fluorocarbon solutions. However, some of the

decrease in the use of CFCs, and now HCFCs, has resulted in increased HFC use, particularly in the 

refrigeration and air conditioning sectors and, to a lesser degree, in the foam and fire protection sectors. 

While most HFCs have GWPs similar to those of the HCFCs they are replacing, some have higher GWPs

(UNEP, 2011). The potential growth in the use of these high-GWP HFCs has given rise to concerns about 

the possible climate impact of the growth in HFC use (and emission) by the year 2050 (Velders et al., 

2009, 2012; WMO, 2011; UNEP, 2011; Wuebbles at al., 2013). To minimize the impact on the ozone layer 

and climate, HCFC replacements would ideally have low ODPs and GWPs, even if the replacements 

contain chlorine or bromine. Meeting such conditions implies that the replacement compounds have short 

lifetimes and/or weak IR absorptions. A number of possible compounds, many of which have low GWPs,

are now being considered. Technical aspects of new compounds are assessed by TEAP once their 

commercial potential has been shown (UNEP, 2013). Scenarios of future replacement compounds are 

considered in Section 5.4 and the possible impacts on ozone depletion and climate are assessed.
Scenarios and Information for Policymakers

5.9

1,2-dichlorohexafluorocyclobutane (C4Cl2F6, CFC-316c) is a proposed replacement substance, 

especially as a refrigerant. Papadimitriou (2013) evaluated the most likely atmospheric removal processes 

for the (E)- and (Z)- isomers of CFC-316c in a series of laboratory studies. 2-D model calculations 

included in their work show that stratospheric photolysis is the predominant loss process for both isomers,

with lifetimes of 75 and 114 years for the (E)- and (Z)- isomers, respectively (see Table 1-3). Ozone 

Depletion Potentials and Global Warming Potentials were also reported, demonstrating that both isomers 

are potent ozone-depleting substances and greenhouse gases (ODPs are 0.46 for (E)-R-316c and 0.54 for 

(Z)-R-316c; GWP100 are 4160 for (E)-R-316c and 5400 for (Z)-R-316c).

A number of short-lived compounds have been proposed as replacements for long-lived ODSs

and hydrofluorocarbons (HFCs) (see Table 1-11). Some of these substances are halogenated VSLS (i.e., 

lifetimes < 0.5 years) and were chosen due to their low ODPs and GWPs. An updated summary of the 

partial and total lifetimes of the proposed replacement substances is given in Table 1-11. Further 

discussion of the ODPs and GWPs for a number of these compounds is given in Section 5.3.

5.2.3 HFC-23

HFC-23 is an unwanted by-product in the manufacture of HCFC-22. A major and increasing use 

of HCFC-22 is as a feedstock in the production of other chemicals, the most important of which is 

polytetrafluoroethylene (PTFE). The amount of HFC-23 produced in HCFC-22 manufacturing is far 

larger than the small amounts currently required for its direct use in some low temperature refrigeration 

and fire protection equipment. HFC-23 emissions are sometimes not considered in the emissions total 

from the mix of HFCs used or predicted to be used. Global emissions of HFC-23 have risen since 2009 

after a period of decrease (Chapter 1). HFC-23 is a strong infrared absorber, and has a long lifetime of 

220 years and a high GWP (12,400 for a 100-year time horizon GWP) (IPCC, 2013). Its radiative forcing 

in 2012 was 0.005 W m-2, about 25% of the RF from all HFCs (Chapter 1). The annual emission of 12.8 

ktonne per year (Chapter 1) corresponds to 150 Gt CO2-eq per year.

The fraction produced in HCFC-22 manufacture depends on the details of the manufacturing 

process. It is assumed to be at most 3% of the amount of HCFC-22 produced, and in optimal 

manufacturing conditions (which are difficult to maintain) it can be brought down to 1.5%. Atmospheric 

emissions can be avoided if the HFC-23 is incinerated, which makes it possible to recover hydrofluoric 

acid (HF), the raw feedstock. Globally, a significant fraction of the HFC-23 produced in HCFC-22 

facilities has been incinerated since 2006, due to the fact that incineration projects in developing countries 

could be supported through the Kyoto Protocol Clean Development Mechanism (CDM). Future HFC-23 

emissions will depend on the amount of HCFC-22 produced, the efficiency of avoiding unwanted HFC23 byproducts, and whether the amount of residual HFC-23 incinerated increases or decreases. This is 

directly related to future policy choices including those related to the granting of new HFC-23 

incineration credits in the CDM (Miller and Kuijpers, 2011) and on other initiatives to avoid and destroy 

HFC-23. The impact of different emission scenarios is discussed in Section 5.4. More information can be 

found in Chapter 1 and references therein.

5.2.4 Biogenically Produced Short-Lived Halocarbons

Biogenically produced very short-lived substances (VSLS) are thought to contribute significantly to 

the stratospheric halogen budget, particularly for bromine (Chapter 1). The main processes affecting the 

effectiveness of these compounds (emissions, convective transport, and chemical processing) could all 

change in the coming decades as a result of changes in climate or in human activities. Bromoform (CHBr3)

and methylene bromide (CH2Br2) are expected to remain the two most important species. Their emissions 

could increase as a result of changes in managed production (e.g., algae farming for food, pharmaceuticals,

or carbon capture). Currently 99% of cultivation comes from 7 countries in Asia and the volume produced 

has grown by ~8%/yr since 1990 (FAO, 2012). A study in Malaysia found that while current bromocarbon 
Chapter 5

5.10

emissions from aquaculture are negligible, they could become significant in the next decade (>10% of 

regional seaweed emissions) (Leedham et al., 2013). With multiple ecosystem, dynamical, and chemical 

components contributing to oceanic VSLS emissions, predicting future emissions will be a major challenge.

Transport of these species into and across the tropical tropopause is the major way for them to 

enter the stratosphere. Tropical convection is thus a critical process in determining their flux into the 

stratosphere, and any changes in its strength or frequency as a result of a changing climate will affect their 

future stratospheric concentrations. These changes will happen in concert with any changes in the strength 

of the stratospheric circulation. The Coupled Model Intercomparison Project Phase 5 (CMIP5) climate 

models suggest that the flux of air into the stratosphere will increase at the same time as ozone depletion 

reduces and as greenhouse gas concentrations increase (see Figure 4-8 and related discussion). For shorterlived species, some features of the convection are particularly important in determining how much of any 

emitted substance (or their reaction products) reaches the stratosphere: these include the overall mass 

transport in convection, the altitudes where the air flows into and out of the convection, the frequency of 

strong events (particularly the high altitude outflow), and the location of the convection relative to the 

emissions. These all have significant uncertainties associated with them (e.g., Schofield et al., 2011). In 

addition, the boundary layer mixing and stratospheric advection processes have been shown to cause 

significant differences in simulated VSLS reaching the stratosphere (Hoyle et al., 2011). Differences are 

amplified for shorter-lived compounds. The implications for the contribution of short-lived species to 

stratospheric chlorine and bromine amounts and to the calculation of ODPs are discussed in Section 5.3.

Modeling studies have shown that climate-driven changes to tropospheric transport may affect

stratospheric VSLS loading (Dessens et al., 2009; Pyle et al., 2011). Hossaini et al. (2012a) calculate

increased injection of CHBr3 into the stratosphere for a 2100 simulation based on the Representative 

Concentration Pathways (RCPs) 4.5 and 8.5 scenarios (IPCC, 2013; also see Chapters 2 and 4). This 

increase was largest under RCP8.5, a scenario with stronger warming, and mostly attributed to an 

enhanced convective mass flux in the tropical troposphere, which agrees qualitatively with earlier model 

studies (Stevenson et al., 2005; Dessens et al., 2009). Overall, Hossaini et al. (2012a) project an increase 

in the direct injection of bromine into the stratosphere contained in the five major VSLS of 0.3 ppt and 

1.0 ppt Br under RCP4.5 and RCP8.5, respectively. These increases are attributed to both the dynamical 

and chemical perturbations, both of which carry large uncertainty, while climate-driven changes to 

emissions and changes in anthropogenic use were not considered. As discussed in Chapter 1, there 

remains significant uncertainty in the role of convection in determining the amount of bromine and 

chlorine reaching the lower stratosphere.

Changes in the tropospheric oxidizing capacity will impact the lifetimes of VSLS (SPARC, 

2013), particularly those whose primary sink is through hydroxyl radical (OH) oxidation (e.g., CH2Br2, 

CH2Cl2). Hossaini et al. (2012a) find significant variation in projected tropical tropospheric [OH] between 

the RCP scenarios. The local lifetime of CH2Br2 (against oxidation) varies significantly (±40%) (e.g., see 

Figure 1-14). Despite OH production being favored under warm and humid conditions, tropical [OH] in 

2100 is projected to decrease by 25% near the surface, due to a projected doubling of methane (CH4) 

under RCP8.5. Voulgarakis et al. (2013) find similar [OH] decreases of −22 ± 4.6% from a multi-model 

intercomparison. Under more moderate climate scenarios, such as RCP2.6 and RCP4.5, models project an 

increase in tropospheric [OH] of up to ~10% below 500 hectoPascals (hPa) (Hossaini et al., 2012a; John 

et al., 2012; Voulgarakis et al., 2013). These studies underline the sensitivity of future OH concentrations

and distribution to future CH4 emissions. Results also depend on responses to relative decreases in 

nitrogen oxides (NOx = NO + NO2) and carbon monoxide (CO) in the different scenarios over polluted 

regions. In addition sub-annual and regional variations, such as the low ozone concentrations found (and 

low OH concentration inferred) in the West Pacific (Rex et al., 2014), could affect VSLS.

The future impact of VSLS on ozone has yet to be fully assessed. While some studies suggest a 

potential increase in bromine from VSLS toward the end of the century, stratospheric chlorine will have 

decreased substantially by 2100 due to the phase-out of the long-lived chlorinated source gases under the 

Montreal Protocol. Therefore, bromine-mediated O3 destruction via the BrO + ClO catalytic cycle would 

be reduced. 
Scenarios and Information for Policymakers

5.11

5.2.5 Breakdown Products

Certain HCFCs, HFCs, HFEs (hydrofluoroethers), and HFOs (hydrofluoroolefins) can contribute to 

tropospheric ozone formation and degrade to produce toxic compounds. The atmospheric degradation of 

HCFCs, HFCs, HFEs, and HFOs is initiated by reaction with OH radicals leading to the formation of 

halogenated carbonyl compounds, which undergo further oxidation to yield HF, HCl, CO2, and, in some cases, 

trifluoroacetic acid (TFA, CF3C(O)OH) (e.g., see prior Assessments such as IPCC/TEAP 2005; WMO, 2011). 

There is a special concern regarding the production of TFA because of its possible effects on life in aquatic 

environments (see the discussion in WMO, 2011). The chlorine production is considered in the discussion of 

EESC in Section 5.4; the effects on HF and CO2 are likely to be extremely small. Examples of halocarbons 

that lead to the formation of TFA (and related compounds) include: HCFC-123, HCFC-124, HFC-125, HFC134a, HFC-227ea, and HFO-1234yf (Young and Mabury, 2010). While it is well established that TFA is a 

ubiquitous natural component in rivers, lakes, and other surface water bodies, uncertainties remain, as 

discussed in WMO (2011), regarding its natural and anthropogenic sources, long-term fate, and abundances. 

TFA formation depends on whether CF3CFO or CF3CClO are formed as intermediates in the parent compound 

degradation. The sole atmospheric fate of CF3CFO is hydrolysis to give TFA (Wallington, et al., 1994). The 

atmospheric fate of CF3CClO is hydrolysis, to give TFA, or photolysis. For halogenated propenes, HFOs, if 

there is a fluorine atom on the central carbon, the TFA yield is expected to be high; such as found with 

CF3CF=CH2 (HFO-1234yf) (Papadimitriou et al. 2011; Wallington et al., 2010). On the other hand, if there is 

a hydrogen on the central carbon atom there is no TFA formation, such as in CF3CH=CHF (HFO-1234ze) or 

CF3CH=CHCl (trans-1-chloro-3,3,3-trifluoropropylene or tCFP; also referred to as HFO-1233zd) or HFC152a. While some studies suggest that the extensive use of some TFA source compounds could dramatically 

increase the amount of TFA in wetlands (e.g., Luecken et al., 2010; Henne et al., 2012), the potential effects on 

associated ecosystems remains unclear and may not be as large a problem as initially envisioned (Boutonnet et 

al., 1999; Benesch et al., 2002; WMO, 2007, 2011). UNEP (2010) concluded that even when added to existing 

amounts from natural sources, risks from TFA (and the more toxic monofluoroacetic acid (MFA)) from 

halocarbons to humans and organisms in the aquatic environment are judged to be negligible. Nonetheless, 

there remains significant uncertainty about the potential effects of TFA in the future environment.

5.2.6 Nitrous Oxide, Methane, and Carbon Dioxide

Any future changes in halogen concentrations will be taking place against the backdrop of other 

atmospheric changes. From a stratospheric chemistry and circulation standpoint, the most important direct 

changes are likely to be those of CH4, N2O, and CO2 (also see Chapters 2 and 4). The concentrations of 

these gases have changed and are continuing to change as a result of human activities (IPCC, 2013). 

Continued changes in the stratospheric concentrations of these gases will lead to changing odd hydrogen 

(HOx) and NOx concentrations during the period that halogen levels are falling. At the same time, 

continued increases in the CO2 concentrations will lead to stratospheric cooling, which will slow the 

ozone chemical loss rates. Increases in CO2 also are projected to cause a strengthening of the stratospheric 

Brewer-Dobson circulation, which will redistribute ozone.

In general the chemical effects of these three gases occur in different locations in the stratosphere,

but overall the increases in CH4 and CO2 will have the opposite effect on stratospheric ozone as that of 

N2O. Future ozone levels will be strongly dependent on the actual future emissions and concentrations of 

these gases. How ozone will change as the future concentrations of these gases change is explored in 

Section 5.4 (see also Section 2.4).

5.2.7 Stratospheric Water Vapor

Stratospheric water vapor is critically important for the gas-phase chemistry, the particle 

distribution, and the radiative balance of the stratosphere. The large majority of stratospheric water vapor 
Chapter 5

5.12

enters the stratosphere in the tropics in the form of either CH4 or H2O. However, it can also enter the 

lowermost stratosphere through mixing processes around the extratropical tropopause. One such process is 

direct injection through midlatitude convection. Increased midlatitude convection could thus result in

increased injection of water vapor and a greater occurrence of ice crystals. While EESC remains high, there 

is thus a chance of enhanced chemical destruction of ozone by catalytic halogen chemistry on these 

additional surfaces (Anderson et al., 2012). The comprehensive measurements by the Aura Microwave 

Limb Sounder (MLS) satellite instrument (Schwartz et al., 2013) confirmed that the lower stratosphere over 

North America is episodically moist (as seen in the aircraft campaigns reported in Anderson et al., 2012). 

However, Schwartz et al. (2013) caution that chemical ozone depletion as a result of convectively enhanced 

H2O of the scale suggested by Anderson et al. (2012) does not seem readily apparent or likely in the current 

stratosphere; moreover, dilution effects from low O3 values lofted by tropospheric air would complicate the 

detection and attribution issues. Comparison of the Aura MLS observations with the CLaMS model

(Chemical Lagrangian Model of the Stratosphere) further suggest that the annual cycle in water above 360 

K at northern midlatitudes is dominated by horizontal transport of water vapor from low latitudes (Ploeger 

et al., 2013). The importance of northern midlatitude convection in the lower stratosphere is therefore 

unclear. Two points can be made with confidence: any chemical ozone depletion (i) is already included in 

the changes seen in the existing observational record; and (ii) will continue to reduce as EESC decreases.

Future stratospheric water vapor levels will be affected by any changes in the amount of water 

entering the stratosphere in the tropics. This could occur through changes in the large-scale structure of 

the tropical tropopause layer (Davis and Rosenlof, 2012; Randel and Jensen, 2013); and in the strength of 

the vertical transport of tropospheric air associated with features such as the Asian monsoon anticyclone 

(Ploeger et al., 2013). Such changes are included implicitly in the discussions in Sections 2.4 and 3.5. 

Given the uncertainties in possible future changes of stratospheric water vapor, the effect on ozone 

depletion is not investigated further with the simple models in this chapter.

Finally, it has been proposed that the observed correlation between stratospheric water levels and 

higher tropospheric temperatures implies a positive feedback of stratospheric water vapor on climate, with 

one-third of the feedback resulting from increases in water vapor entering the stratosphere in the tropics 

and the rest occurring from increases entering through the extratropical tropopause (Dessler et al., 2013). 

5.2.8 Stratospheric Aerosols

Stratospheric aerosols can have a significant influence on stratospheric ozone (e.g., Solomon et 

al., 1996; Chapter 2). The stratospheric aerosol layer has been increasing during the volcanically 

quiescent period of 2000–2009 by ~3.8% (Nagai et al., 2010). This has been shown to have a direct 

climate impact (Solomon et al., 2011). The increase is probably caused by the cumulative effect of minor 

volcanic eruptions with subsequent transport of sulfur dioxide (SO2) into the stratosphere (Vernier et al., 

2009; Neely et al., 2013). The impact of tropospheric pollution is now thought to be small (Siddaway and 

Petelina, 2011; Vernier et al., 2011; Section 8.4.2.2 in IPCC, 2013; Chapter 4). Changes in anthropogenic 

carbonyl sulfide (COS) emissions could also affect future background aerosol levels (Brühl et al., 2012). 

Other than in the discussion on geoengineering below, the effect on stratospheric ozone of possible

changes in the stratospheric aerosol layer is not considered further in this chapter and so represents a 

source of uncertainty in the results presented. 

5.2.9 Other Proposed Influences on Stratospheric Ozone

AVIATION

Since WMO (2011), studies have continued toward understanding the effects of emissions from 

commercial aviation on ozone in the upper troposphere and lower stratosphere (UTLS) and on climate 

(e.g., see Brasseur et al., 2013, Holmes et al., 2011; Lee et al., 2009). Aircraft emit gases and particles 

into the atmosphere, especially in the region of the UTLS. These emissions include carbon dioxide, 
Scenarios and Information for Policymakers

5.13

nitrogen oxides, water vapor, sulfates, and soot. The gases and soot tend to have a positive radiative 

forcing (RF), a surface warming effect, while other particles like sulfates produce a negative RF, a surface 

cooling effect. NOx produces ozone in the UTLS that then leads to additional OH production in the 

troposphere and a resulting decrease in methane. Current commercial aviation emissions are estimated to 

increase UTLS ozone at northern midlatitudes by 5–7% (2.3–9.1% in the range of models from recent 

studies: Olsen et al., 2013; Brasseur et al., 2013; Skowron et al., 2013). The net effect on the total ozone 

column, however, is small, an increase of less than 0.3% globally- and annually-averaged. By 2050, 

current studies using a scenario that includes technology advances in aviation efficiency suggest the effect 

of aviation on UTLS ozone could increase to as much as 11% (Olsen et al., 2013; Brasseur et al., 2013). 

The effect on the total ozone column remains small (<1%). 

Supersonic aircraft fly at higher altitudes, where they emit NOx and H2O into the stratosphere at 

altitudes where they can be mixed upwards and globally (instead of being flushed out of the lowermost 

stratosphere within a season as for subsonic aircraft). Thus high-flying supersonic aircraft can have 

potentially much greater impacts on ozone and climate forcing. There are no current plans for 

development of commercial supersonic aircraft, although the technology for supersonic business jets is 

continuing to be developed, and future growth should be monitored.

ROCKETS AND SUB-ORBITAL VEHICLES

WMO (2011) raised the potential importance of emissions from rockets. Cryogenic rocket 

engines using liquid oxygen and liquid hydrogen produce water and nitric oxide. Solid rocket motors 

(SRMs) have emissions of hydrochloric acid (HCl) and alumina (Al2O3) and so have more impact on 

ozone than the cryogenic engines. These SRM emissions can lead to destruction of the ozone in the 

rocket exhaust plumes (Ross et al., 2009; Voigt et al., 2013). The present-day loss in the globally 

averaged total ozone column due to these rockets is estimated at ~0.03%, insignificant compared to other 

processes (Ross et al., 2009). It would take a large increase in the frequency of launches for the impact 

on ozone to become significant compared to the impacts of other influences. A recent forecast for the

commercial sector (currently about 25% of the total) is an increase from about 20 to 30 launches per 

year (FAA, 2013). 

A number of suborbital, reusable vehicles (SRV) are being developed for use for satellite 

launches and/or for passengers. It is still early in the development of these technologies and so it is hard 

to predict future usage and growth in the number of launches. One study developed three scenarios 

(baseline, constrained, and growth) based on different assumptions about cost, level of consumer 

interest, and governmental/industrial demand (FAA, 2013). In these scenarios, the number of flights ten 

years after the first year of regular SRV operation ranged from about 250 to 1600. Newer propellants are 

being considered in the private space market, many of which are liquid oxygen (O2) with alcohol (FAA, 

2011). The effect on stratospheric ozone will depend on the number of launches, the propellant used, and 

the flight profiles. Few studies have addressed the effects of these vehicles and their potential 

environmental impacts. 

GEOENGINEERING OF CLIMATE

A variety of ideas have been proposed to mitigate the climate effects of rising greenhouse gases 

concentrations (geoengineering). One of these, the creation of additional particles in the stratosphere,

would directly impact stratospheric ozone (Tilmes et al., 2008, 2009). Other methods have indirect effects 

on stratospheric ozone and are not considered further here. 

Stratospheric particles reflect a small amount of the incoming solar radiation back to space, and 

so lead to a reduction in the incident solar energy reaching the Earth and a resultant surface cooling. An 

enhancement of the stratospheric particle layer, e.g., following volcanic eruptions, increases this cooling 

effect. The effect is well established, because the surface of the Earth is observed to cool as a result of the 

high sulfate aerosol loading in the years following major volcanic eruptions (WMO, 2011; Graf et al., 

1998; Free and Lanzante, 2009; IPCC, 2013), although it has recently been suggested that the volcanic 

response may have been overestimated by as much as a factor of two (Canty et al., 2013).
Chapter 5

5.14

Increases in stratospheric particles affect the radiative balance in the stratosphere, with 

consequent changes in the dynamics and in the chemistry (through changes in photolysis rates). In 

addition, stratospheric chemistry is perturbed by heterogeneous reactions that occur on particle surfaces,

with impacts on the HOx, NOx, ClOx, and BrOx chemical cycles. Three-dimensional models have 

individually simulated the stratospheric response following the Mt. Pinatubo eruption (the best observed) 

with some success (e.g., Heckendorn et al., 2009; see also Chapter 2, Section 2.3.4). However, the large 

inter-model variation in the dynamical response to forcings (SPARC CCMVal, 2010) limits our 

confidence in the predictive capability of the current models.

The main type of artificial perturbation that has been considered is an augmentation of the 

background sulfate aerosol layer through the injection of sulfur (Crutzen et al., 2006; Wigley, 2006; 

WMO, 2011). The observed changes with volcanic eruptions give confidence in our qualitative

understanding of the impacts of elevated sulfate aerosol. However, quantitative studies are limited to date.

Recent modeling studies of an artificially perturbed stratospheric aerosol layer have concentrated on 

scenarios defined in the Geoengineering Model Intercomparison Project (GeoMIP) (Kravitz et al., 2011), 

with nearly all GEOMIP studies to date focusing on impacts on climate rather than stratospheric ozone. 

Results from four models using the two GEOMIP scenarios that include stratospheric aerosol (Pitari et al., 

2014) indicate reductions in total column ozone of a few percent, with the larger losses at high latitudes,

consistent with earlier studies based on different scenarios (Heckendorn et al., 2009; Tilmes et al., 2009).

The chemical ozone loss is calculated to decrease as the availability of ClOx and BrOx decreases. This 

effect may be offset by any increase in the input of chlorine- and bromine-containing VSLS into the 

stratosphere (Tilmes et al., 2012; see Section 5.2.4).

Consideration is also being given to particles with different optical properties that could 

substantially increase the amount of light scattered back to space thereby reducing the mass required for 

injection (Katz, 2011) or that reduce the absorption of solar radiation by the particles hence leading to a 

reduced impact on the stratospheric circulation (Ferraro et al., 2011). Such particles could be more 

effective in producing a surface cooling than sulfate aerosol. The heterogeneous chemistry occurring on 

the surface of new particles is poorly known (Pope et al., 2012). The surface coating of a particle and how 

it evolves under stratospheric conditions will be important for the heterogeneous reaction rates. For 

example, a coating of sulfuric acid (H2SO4) on a particle’s surface would tend to make the heterogeneous 

chemistry that occurs more like that of sulfate aerosol. However, the effect on the optical properties 

would likely be small. If the particles became significantly larger, the sedimentation rate would in general 

increase and the stratospheric lifetime would shorten. 

In our discussion, we have not considered other potential effects of the stratospheric particle 

geoengineering approach on climate and other aspects of the environment. Overall the gaps in our current

understanding of the full impacts of possible geoengineering approaches on stratospheric ozone preclude 

us from making a full assessment with confidence. Thus, there is still the potential for significant risks to 

the ozone layer, both known and unknown, from solar radiation management through the use of

stratospheric particles.

POLAR OZONE DEPLETION BY COSMIC RAYS

A series of papers (most recently Lu (2013, 2014)) have repeated the hypothesis that cosmic rays 

can promote the breakdown of organic and inorganic halogenated compounds, including CFCs, on ice and 

other stratospheric particles in polar regions, with the resulting chlorine compounds playing the dominant 

role in polar ozone loss. The recent papers have been published despite a number of previous papers 

showing that this hypothesis is inconsistent with established knowledge of the stratosphere (Harris et al., 

2002; Patra and Santhanam, 2002; Grooß and Müller, 2011; Müller and Grooß, 2014 and references 

therein). Lu (2013) and his earlier papers rely principally on correlations of observed variables (e.g., 

ozone, temperature, cosmic ray flux) with no quantitative evidence that the proposed mechanism makes a 

significant difference to the well established understanding of polar ozone loss based on mechanisms 

demonstrated in laboratory and field measurements as well as model studies (e.g., see Chapter 3). Among 

other things there is no evidence that the hydrophobic CFC-11 or CFC-12 molecules are absorbed into the 
Scenarios and Information for Policymakers

5.15

particles in large enough amounts for cosmic-ray-produced electrons to dissociate them (Harris et al., 

2002). Nor can the mechanism explain the observed distributions and correlations of long-lived trace 

gases such as the CFCs, N2O, and CH4 which show that CFC depletion occurs in the middle and upper 

stratosphere at low and midlatitudes and not in the polar lower stratosphere (Grooß and Müller, 2011). 

The fundamental problem with the hypothesis is that it ignores most of the work that has been done over 

the last 30–40 years as reported in the series of WMO Assessments prepared in support of the Montreal 

Protocol. This hypothesis should be rejected.

5.3 METRICS FOR CHANGES IN OZONE AND CLIMATE

For the purpose of this Assessment, metrics are defined as tools used for quantifying and 

comparing impacts of emissions from human activity. Typically they aggregate and simplify complex 

information about different gases, placing them on a common scale to simplify comparison of impacts. 

Metrics such as Equivalent Effective Stratospheric Chlorine (EESC) and Ozone Depletion Potentials 

(ODPs) have proven to be important tools in policy considerations for stratospheric ozone (see Box 5-2),

while other metrics, including radiative forcing (RF) and Global Warming Potentials (GWPs), have 

proven to be useful tools in climate-policy-related studies (see Box 5-3). These metrics have all been used 

in past assessment of ozone and climate including the WMO Assessments. In addition, newer metrics, 

such as Global Temperature change Potentials (GTPs), are introduced in the discussion below.

One advantage of metrics is that they are straightforward to communicate. Some of these metrics 

express the integrated impact of a given gas relative to that for the release of the same mass of a reference 

compound (generally CFC-11 for ODPs and CO2 for GWPs and GTPs). For these metrics using such 

relative indices, some uncertainties in translating emissions into absolute environmental impacts tend to 

cancel, and the relative benefits of controlling emissions of different gases are highlighted. However, it 

should be recognized that the metrics discussed here do not represent the full complexity of the chemistry 

and physics of the atmosphere (e.g., where and when the ozone depletion occurs). Their simplicity means 

some caution is required when interpreting the values derived (e.g., how much are these values dependent 

on the background atmosphere assumed in their derivation). Nonetheless, ODPs and GWPs have found 

widespread use in national regulatory actions and in international agreements such as the Montreal 

Protocol and the Kyoto Protocol.

5.3.1 Metrics for Changes in Ozone

Box 5-2 (next page) summarizes the basics of metrics used for describing changes in ozone, 

namely, Equivalent Effective Stratospheric Chlorine (EESC) and Ozone Depletion Potentials (ODPs).

UPDATING THE EVALUATION OF ODPS

There have been only a few published updates on ODP values since the last Assessment, with most 

of those concerning VSLS as discussed below. Papanastasiou et al. (2013) provide analyses of updated semiempirical ODPs for several bromine-containing compounds (halon-1202, -1211, and -2402) using updated 

lifetimes computed with the NASA GSFC 2-D atmospheric model (Fleming et al., 2011). Their analyses 

produced somewhat different ODP values compared to WMO (2011): 1.95 for halon-1202 vs. 1.7 in WMO 

(2011), 8.1 for halon-1211 vs. 7.9 in WMO (2011), and 18.4 for halon-2402 vs. 13.0 in WMO (2011).

New scientific results affect the earlier ODPs, especially from the reanalysis of atmospheric 

lifetimes in SPARC (2013). The revised SPARC (2013) recommended lifetimes are based on calculations 

with atmospheric chemical transport models, analysis of observations at the surface and in the stratosphere,

laboratory analysis of chemical reactions and photolysis rates, and on inverse modeling. In addition, the

SPARC report provides uncertainties in the lifetimes of major halogenated ODSs. The uncertainties in the 

lifetimes are considerable, ranging from 3% to 33% (one standard deviation, 1σ; also see Velders and 

Daniel (2014) for further discussion on these uncertainties). The SPARC (2013) atmospheric lifetimes are
Chapter 5

5.16

Box 5-2. Metrics for Ozone: The Basics

Equivalent Effective Stratospheric Chlorine (EESC)

EESC is a sum of the time-dependent chlorine and bromine derived from ODS tropospheric 

abundances, weighted to reflect their potential influence on ozone. EESC has become a standard 

benchmark for estimating ozone depletion relative to a base period, usually taken as 1980 (a time before 

major ozone depletion). EESC relates surface mixing ratios of chlorine- and bromine-containing ODSs

to the stratospheric inorganic chlorine and bromine released from these gases in key regions of the 

stratosphere and thus to the amount of ozone they will destroy (Daniel et al., 1995; WMO, 1995, 1999, 

2003, 2007, 2011; also see Chapter 1). EESC also accounts for the larger efficiency of bromine to 

destroy stratospheric ozone compared to chlorine (on a per-atom basis) and that different source gases 

release their chlorine and bromine at different rates and geographic locations. EESC has been 

reformulated (Newman et al., 2007) to account for the age-of-air spectrum and the age-of-air dependent 

fractional release values. Not only does this increase its accuracy, but EESC can also then be derived for 

various latitudes, including effects at midlatitudes or in the Antarctic vortex (Newman et al., 2009;

WMO, 2011). The changes in integrated EESC and the date when EESC returns to 1980 levels have 

both been used in the previous WMO Assessments to quantify the relative impacts of future emissions of 

ODSs. In Section 5.4, EESC is used in the evaluation of scenarios for various assumptions about future 

emissions of halocarbons.

The EESC concept has been further revised (Daniel et al., 2010) to account for the effects of 

nitrous oxide (N2O), the primary source for nitrogen oxides (NOx = NO + NO2) in the stratosphere. If 

this can be done accurately, it is useful because N2O is increasing and is projected to continue to do so in 

the future. The NOx produced from N2O chemistry not only destroys ozone itself, it also reduces the 

efficiency of chlorine and bromine in destroying ozone by tying up these halogens in chlorine nitrate 

(ClONO2) and bromine nitrate (BrONO2) reservoir gases. Projected decreasing levels of reactive 

chlorine (Cly) similarly ties up less reactive nitrogen (NOy; note that reactive nitrogen does not include 

N2O, only the more reactive forms of atmospheric nitrogen) in ClONO2, especially in the lower 

stratosphere, increasing the efficiency of N2O to destroy ozone at those altitudes (Ravishankara et al., 

2009). However, there is also a decreasing efficiency of N2O in ozone depletion in the future climate due 

to the projected CO2-induced cooling of the stratosphere and enhancement of the stratospheric 

circulation (Rosenfield and Douglass, 1998; Plummer et al., 2010). The expected decrease, by 2100, in 

the effectiveness of a unit N2O emission to destroy ozone ranges from 10–20% (Daniel et al., 2010) to 

50% (Plummer et al., 2010). Although these interactions will potentially lead to a complicated 

relationship between EESC and ozone depletion, we investigate the usefulness of this effect in Section 

5.4. Future changes in emissions of methane, as well as potential emissions of other gases and particles, 

can further complicate the interpretation of EESC but are not considered in the EESC index at this time.

EESC is calculated as in previous Assessments. The only difference between the calculations in 

WMO (2011) and those here is that we now use an age spectrum for both midlatitude (3-year mean age) 

and Antarctic conditions (5.5-year mean age), while a full age spectrum was not used before. In both 

cases, we assume the width of the spectrum is equal to half of the average age (Newman et al., 2007). A 

complete discussion of the other aspects of the EESC calculation can be found in Chapter 5 of WMO 

(2011). As in that Assessment, we assume the relative impact of bromine compared to chlorine for ozone 

destruction, typically referred to as alpha (α), is 60 at midlatitudes and 65 in polar regions.

Ozone Depletion Potentials (ODPs)

The concept of Ozone Depletion Potentials (ODPs) (Wuebbles 1981, 1983; Solomon et al. 1992; 

the various WMO Assessments) arose as a means of determining the relative ability of a chemical to 

destroy ozone. Steady-state ODPs are defined as the change in global ozone for a sustained unit mass 

emission of a specific compound relative to the change in global ozone for the sustained unit mass 

emission of CFC-11 (CFCl3). This is equivalent to assuming an infinitesimal emission pulse and 

integrating over the entire decay of the compound. ODPs are an integral part of national and international 
Scenarios and Information for Policymakers

5.17

Box 5-2, continued.

considerations on ozone-protection policy, including the Montreal Protocol and its Amendments. ODPs 

provide an important and relatively straightforward way of analyzing the potential for a new chemical to 

affect ozone relative to the chlorofluorocarbons (CFCs) and other chlorine-, bromine- and iodinecontaining halocarbons. It is also now being applied to non-halogenated compounds like nitrous oxide 

(N2O) (Ravishankara et al., 2009; Fleming et al., 2011; WMO, 2011) and methane (CH4) (Fleming et al., 

2011). ODPs are currently determined by two different means: calculations from chemical transport 

models (CTMs) of the global atmosphere, and the semi-empirical approach that depends primarily on 

observations rather than models (Solomon et al., 1992; WMO, 2003, 2007, 2011). Both approaches have 

been shown to give very similar ODP values in previous Assessments.

Advantages and disadvantages of using ODPs have been discussed in the prior WMO 

Assessments. Because ODPs are defined relative to the ozone loss caused by CFC-11, it is generally 

thought that the ODP values demonstrate less sensitivity to photochemical modeling errors than do 

absolute ozone loss calculations, but this is only strictly true for other chlorine-containing compounds

with similar atmospheric lifetimes. Interpretation of non-halocarbon ODPs could be particularly 

problematic. For example, ODPs are normally derived relative to the current atmosphere, but there could 

potentially be some differences in values if they were calculated relative to a future atmosphere with 

different background composition, temperatures, or circulation. 

Originally, the evaluation of ODPs was conducted largely for chemicals with atmospheric 

lifetimes sufficiently long (> ~1 year) that they are well mixed throughout the troposphere after surface 

release, and a significant portion of the surface emissions can still reach the stratosphere. However, many 

of the compounds being considered either for new applications or as replacements for substances 

controlled under the Montreal Protocol are now designed to be very short lived, on the order of days to a 

few months, so as to reduce the impacts on ozone and climate. Many of these very short-lived substances 

(VSLS) still contain chlorine, bromine, or iodine, and can be vertically transported into the lower 

stratosphere particularly through the tropical troposphere. A major complication with VSLS is that the 

compounds can decompose into inorganic halogen compounds in the uppermost tropical troposphere, and 

hence an important uncertainty is the degree to which the inorganic halogens (e.g., HBr, HOBr) are 

scavenged during the removal of water vapor in ascent. Another issue is that basic assumptions of 

referencing to CFC-11 to cancel transport and other errors in the model clearly break down since the 

chemical removal processes are so different; nonetheless there is high value for policymakers in being 

able to use the modified form of the ODP concept for VSLS.

Due to the difficulties in calculating the dynamical and chemical processes affecting such shortlived compounds, three-dimensional (3-D) models fully representing the troposphere and stratosphere 

need to be used to predict the halogen loading and resulting effects on global ozone. As a result, the 

definition of ODPs has been revised for VSLS (Wuebbles et al., 2001; WMO, 2003, 2011; Pisso et al., 

2010). The ODPs derived for VSLS now account for variations that can occur in the ODP as a function of 

where and when (geographic location and time of year) the compound is emitted. The most important 

factor in evaluating the ODP of VSLS is shown to be geographical distribution, or latitude, of the surface 

emissions because gases emitted at higher latitudes are less likely to reach the stratosphere before 

destruction than gases emitted in the tropics (Bridgeman et al., 2000; Olsen et al., 2000; Wuebbles et al., 

2001). The discussion of updates to ODPs thus reflects this change in definition for VSLS.

compared to those from WMO (2011) in Table 5-1 (also see discussion of atmospheric lifetimes in Chapter 

1). There are a number of differences, but the most important one to the derivation of ODPs is the change in 

lifetime of CFC-11 from 45 years to 52 years (+15%); CFC-11 is in the denominator in ODP derivation, so 

this change in lifetime decreases the values of all ODPs in WMO (2011) by 15%. Revisions in the lifetimes 

for other gases produce the other differences found in ODP values for “This Assessment” found in Table 5-2.

The age-of-air spectrum from Newman et al. (2007) and the age-of-air dependent fractional

release factors (FRFs, defined as age of-air-dependent ODS decomposition rates; also see Chapter 1) from
Chapter 5

5.18

Table 5-1. Atmospheric lifetimes and fractional halogen release factors relative to WMO (2011) for 

long-lived halocarbons. In this Assessment, lifetimes are based on SPARC (2013). Fractional release 

factors (midlatitude conditions) used in this Assessment are based on the previous Assessment (WMO, 

2011), but we also show in the table those for the 10 compounds updated in Laube et al. (2013) using a 

mean age of air of 3 years. Lifetime uncertainties are based on SPARC (2013) lifetimes as evaluated by 

Velders and Daniel (2014). Also see Chapter 1 for further discussion on atmospheric lifetimes.

Halocarbon Atmospheric Lifetime 

(years)

Fractional Release Factors

WMO 

(2011)

This 

Assessment

Lifetime 

uncertainty (1σ)

c

This 

Assessment

Laube et al. 

(2013)

Annex A-I

CFC-11 45 52 ±22% 0.47 0.35

CFC-12 100 102 ±15% 0.23 0.19

CFC-113 85 93 ±17% 0.29 0.22

CFC-114 190 189 ±12% 0.12

CFC-115 1020 540 ±17% 0.04

Annex A-II

halon-1301 65 72 ±13% 0.28 0.26

halon-1211 16 16 ±29% 0.62 0.52

halon-2402 20 28 ±19% 0.65

Annex B-II

CCl4 26 a 26 a ±17% 0.56 0.42

Annex B-III

CH3CCl3 5.0 5.0 a ±3% 0.67 0.61

Annex C-I

HCFC-22 11.9 12 ±16% 0.13 0.07

HCFC-123 1.3

HCFC-124 5.9

HCFC-141b 9.2 9.4 ±15% 0.34 0.17

HCFC-142b 17.2 18 ±14% 0.17 0.05

HCFC-225ca 1.9

HCFC-225cb 5.9

Annex E

CH3Br 0.75 a,b 0.8 a ±17% 0.60

Others

halon-1202 2.9 2.5 ±33% 0.62

CH3Cl 1.0 a 0.9 a ±18% 0.44

a Losses due to oceanic and soil processes are taken into account using values from WMO (2011). The partial lifetime for CCl4

is 44 years for atmospheric loss (from SPARC, 2013) and is assumed to be 95 years for oceanic loss and 195 years for soil 

loss for a total lifetime of 26 years. The partial lifetime for CH3CCl3 is 5.0 years for atmospheric loss (from SPARC, 2013). 

The total lifetime for CH3Br is 1.5 years for atmospheric loss (from SPARC, 2013), 3.1 years for oceanic loss, and 3.3–3.4 

years for soil loss. The partial lifetime for CH3Cl is 1.3 years for atmospheric loss (from SPARC, 2013) and 3 years for 

oceanic and soil loss.

b In Table 5-1 a lifetime of 0.7 years is reported. In the scenarios calculations, however, a value of 0.75 years is used to be 

consistent with natural emission estimates from WMO (2011). c These are 1-σ lifetimes, taken from Velders and Daniel (2014), which are calculated when only the uncertainties in the 

atmospheric loss rates (inverse of the atmospheric lifetime) from SPARC (2013) are taken into account. A 1-σ uncertainty 

implies that there is an approximately 68% chance that the actual lifetime will fall within that range. The exclusion of other 

loss rate uncertainties is relevant for CCl4, for which the uncertainty could change if the uncertainty in the partial lifetime due 

to oceanic loss (82–191 years (WMO, 2011)) would be taken into account. 
Scenarios and Information for Policymakers

5.19

Newman et al. (2006) were used in WMO (2011) for discrete ages-of-air for midlatitude (3 year) and 

Antarctic (5.5 year) conditions. A new analysis of the FRF for ten ODS by Laube et al. (2013) gives 

values that are on average about 20% smaller than those derived by Newman et al. (2006) (see 

comparison in Table 5-1). These have not been adopted for this Assessment although their effect on ODP 

values is considered in the following discussion and in Chapter 1.

In Table 5-2, the steady-state semi-empirical ODPs for longer-lived halocarbons (those with an 

atmospheric lifetime greater than 0.5 year) are shown using the atmospheric lifetimes from WMO (2011)

and those derived using the lifetimes from SPARC (2013). In general the derived ODP values in Table 5-

2 are almost all smaller numerically (ranging from no change (for carbon tetrachloride, CCl4) to more 

than a factor of two smaller (for CFC-115), with most smaller by 10–30% than the values reported in 

WMO (2011), as expected given the longer lifetime for CFC-11. The one major exception is halon-2402,

for which the lifetime in SPARC (2013) is appreciably longer than in WMO (2011).

The use of the Laube et al. (2013) FRFs also affects the semi-empirical ODPs, as shown by the 

values in parentheses in Table 5-2 (based on Velders and Daniel, 2014). Using both the lifetimes from 

SPARC (2013) and the fractional release values from Laube et al. (2013) results in small changes in ODPs 

of most species compared with the values reported in WMO (2011). The ODPs of the HCFCs show larger 

changes: the ODP of HCFC-22 decreases by 37%; that of HCFC-141b, by 40%; and that of HCFC-142b,

by 64%. ODPs calculated from the fractional release values of Laube et al. (2013) and using the SPARC 

(2013) lifetimes are consistent with the assessed values in the Montreal Protocol and WMO (2011) except 

for HCFC-22, HCFC-141b, and HCFC-142b, all of which have much smaller values using the Laube et al. 

fractional release values. Uncertainties in the atmospheric lifetimes, the fractional release values, and 

atmospheric chemistry generally result in overall uncertainties on the order of 30% for the CFCs and CCl4, 

but are much higher for HCFCs and halons (roughly 55–58% for the HCFCs and halon-1301 to over 80% 

for halon-1202 and halon-1211), based on analyses by Velders and Daniel (2014). The 95th percentile 

confidence intervals are also shown in the table, as taken from Velders and Daniel (2014). They are shown 

when using the “most likely” and “possible” lifetime uncertainty ranges as presented in SPARC (2013).

Table 5-3 shows analyses of the spatial dependence in ODPs for VSLS primarily based on results 

using different versions of the National Center for Atmospheric Research (NCAR) global 3-D model 

(Wuebbles et al., 2009, 2011; Patten and Wuebbles, 2010; Youn et al., 2010; Patten et al., 2011). Note that 

this model calculates an atmospheric lifetime of 53.7 years for CFC-11, so the published ODPs would not 

be significantly affected by the revised SPARC (2013) lifetime for CFC-11. In these studies, the VSLS 

examined all have quite small ODPs based on emissions occurring primarily at midlatitudes. New 

approaches for estimating VSLS ODPs have been developed since WMO (2011) based on Lagrangian 

models (Tegtmeier et al., 2012; Pisso et al., 2010; Brioude et al., 2010), with findings similar to previous 

studies, except for emissions in the tropics, where a different treatment of convection may allow for more 

VSLS (and their products) to reach the stratosphere.

In addition to these lifetime estimates, Patten and Wuebbles (2010) evaluated the lifetimes and 

ODPs of (E)-1-chloro-3,3,3-trifluoropropylene ((E)-CHCl=CHCF3, HCFC-1233zd(E)) and (E)-1,2-

dichloroethylene ((E)-CHCl=CHCl), assuming industrial emissions were to occur over all land surfaces in 

the latitude range 30°N to 60°N. These compounds are proposed foam blowing agents and electronic 

cleaning substances. Based on 3-D chemical transport model (CTM) calculations, the atmospheric 

lifetime of HCFC-1233zd(E) was 40 days with an ODP of 0.00034. The model-calculated lifetime is 

shorter than the boundary layer local lifetime given in Table 1-11 (250 days) and longer than the 26-day 

lifetime reported in Sulbaek Andersen et al. (2008) that was calculated using a specific OH concentration. 

For (E)-CHCl=CHCl the calculated lifetime and ODP were 12.7 days (6.7-day local lifetime in Table 1-

11) and 0.00024, respectively. Patten et al. (2011) evaluated the lifetime and ODP of 2-bromo-3,3,3-

trifluoropropene (CH2=CBrCF3), a suggested halon replacement for use in fire extinguishers. They 

reported a global annually averaged lifetime of 7 days and an ODP of 0.0028, when emissions were 

distributed between 30°N to 60°N, compared to the 3.9-day local lifetime given in Table 1-11. The 

differences in the model-calculated and estimated local lifetimes given in Table 1-11 highlight the 

dependence on the OH climatology used for the lifetime estimate.
Chapter 5

5.20

Table 5-2. Ozone Depletion Potentials (ODPs) for long-lived halocarbons. Shown are the ODP values 

assumed in the Montreal Protocol, the ODPs updated in the previous Assessment (WMO, 2011), and the 

values determined in this Assessment based on the atmospheric lifetimes from SPARC (2013). Values 

shown as “This Assessment” are based on the fractional release factors from WMO (2011). The ODPs in 

parentheses are those using the fractional release factors from Laube et al. (2013). In general the derived 

ODP values in the Assessment are almost all smaller numerically (ranging from no change (for carbon 

tetrachloride, CCl4) to more than a factor of two smaller (for CFC-115), with most smaller by 10–30% than 

the values reported in WMO (2011), as expected given the longer lifetime for CFC-11. The one major 

exception is halon-2402, for which the lifetime in SPARC (2013) is appreciably longer than in WMO (2011). 

Halocarbon ODP in 

Montreal 

Protocol

Semi-Empirical ODP Uncertainties

(95% confidence interval)

(from Velders and Daniel, 2014)

WMO 

(2011)

This 

Assessment

Possible (±) Most Likely (±)

Annex A-I

CFC-11 1.0 1.0 1.0

CFC-12 1.0 0.82 0.73 (0.81) 34% 30%

CFC-113 0.8 0.85 0.81 (0.82) 34% 30%

CFC-114 1.0 0.58 0.50 37% 30%

CFC-115 0.6 0.57 0.26 34% 32%

Annex A-II

halon-1301 10.0 15.9 15.2 (19.0) 61% 57%

halon-1211 3.0 7.9 6.9 (7.7) 90% 82%

halon-2402 6.0 13.0 15.7 80% 71%

Annex B-II

CCl4 1.1 0.82 0.72 (0.72) 34% 30%

Annex B-III

CH3CCl3 0.1 0.16 0.14 (0.17) 52% 36%

Annex C-I

HCFC-22 0.055 0.04 0.034 (0.024) 69% 58%

HCFC-123 0.02 0.01

HCFC-124 0.022

HCFC-141b 0.11 0.12 0.102 (0.069) 68% 57%

HCFC-142b 0.065 0.06 0.057 (0.023) 67% 56%

HCFC-225ca 0.025

HCFC-225cb 0.033

Annex E

CH3Br 0.6 0.66 a 0.57 78% 69%

Others

halon-1202 * 1.7 96% 88%

CH3Cl 0.02 0.015

a This value was based on the lifetime of CH3Br of 0.8 year shown in the ODP table in WMO (2011).

* The value of 2.2 in Velders and Daniel (2014) is attributed to WMO (2011); the value was not in Table 5-1 of WMO 

(2011) but can be inferred from the fractional release and lifetimes shown in that table.
Scenarios and Information for Policymakers

5.21

Table 5-3. Ozone Depletion Potentials (ODPs) for emissions from given latitude bands over land 

for short-lived halocarbons (very short-lived substances, VSLS) based on analyses from 3-D 

models. ODPs are from the papers, but modeled lifetimes for CFC-11 were similar to the SPARC (2013) 

values, so no correction was necessary. See Chapter 1, Table 1-5, for local lifetimes of such VSLS.

VSLS Reference Latitudes of 

Emissions

Reported Annual 

Lifetimes (days)

ODPs

nPB 1 Wuebbles et al. (2009, 2011) 30°N – 60°N 24.7 0.0049

60°S – 70°N 19.6 0.011

TCE 2 Wuebbles et al. (2011) 30°N – 60°N 13.0 0.00037

PCE 3 Wuebbles et al. (2011) 30°N – 60°N 111 0.0050

BTP 4 Patten et al. (2011) 30°N – 60°N 7.0 0.0028

60°S – 60°N 4.3 0.0052

HFO-1233zd 5 Patten and Wuebbles (2010) 30°N – 60°N 40.4 0.00034

tDCE 6 Patten and Wuebbles (2010) 30°N – 60°N 12.7 0.00024

CF3I 7 Youn et al. (2010) 30°N – 60°N 5.0 0.008

20°S – 20°N 1.1 0.016

CH3I 8 Youn et al. (2010) 30°N – 60°N 13.6 0.017

CH2Br2

9 Tegtmeier et al. (2012) 20°S – 13°N 120 3 – 4

CHBr3

10 Tegtmeier et al. (2012) 20°S – 20°N 26 1 – 5 1 n-propyl bromide (C3H7Br) 2 trichloroethylene (C2HCl3) 3 perchloroethylene (C2Cl4) 4 2-bromo-3,3,3-trifluoropropene (CH2 = CBrCF3) 5 (E)-1-chloro-3,3,3-trifluoropropylene ((E)-CHCl=CHCF3) (also called tCFP) 6 (E)--1,2-dichloroethylene ((E)-CHCl=CHCl) 7 iodotrifluoromethane 8 methyl iodide 9 dibromomethane 10 tribromomethane

Earlier studies (Wuebbles et al., 1999, 2001; Olsen et al., 2000; Bridgeman et al., 2000) have 

shown that the ODPs for short-lived compounds depend greatly on when or where the emissions occur, 

with the largest ODPs being found for emissions in the tropics. Although it is generally expected that 

most emissions from anthropogenic emissions of VSLS will occur at northern midlatitudes, there is no 

guarantee of this and the locations of future emissions could change. ODPs for tropical emissions of two 

VSLS compounds from Tegtmeier et al. (2012) are also presented in Table 5-3. The compounds 

examined, CH2Br2 and CHBr3, are important contributors to lower stratospheric reactive bromine 

(especially through natural oceanic sources, see Chapter1), and have large ODPs for emissions occurring 

in the tropics. 

The recent modeling studies also re-emphasize the point that VSLS ODPs are very dependent on 

the location of emissions, and not just the latitude; for example, by co-location with efficient vertical 

transport by deep convection into the stratosphere (semi-empirical ODPs as a function of specific 

locations of emissions based on Brioude et al. (2010) are shown in Table 5-4). Brioude et al. (2010) 

showed that these factors are more important than regional variations in VSLS losses by OH or 

photolysis. Using CO-like emissions to represent anthropogenic VSLS, they estimated ODPs for various 

compounds and found maximum ODPs over the Indian sub-continent varying from 0.079 in winter to 

0.29 in summer for n-propyl bromide (C3H7Br or nPB) and from 0.13 in winter to 0.83 in summer for 
Chapter 5

5.22

CH3I. Pisso et al. (2010) applied their new methodology to an nPB-like tracer with a lifetime of 20 days. 

They also found higher ODPs over southeast Asia in the summer (and over western Pacific in winter). In 

July in the tropics (30°N–30°S), ODPs varied from 0.33 in runs with convection to 0.17 in runs with no 

convection. Locally, values over southeast Asia are as high as 1.00. In general the results from these 

Lagrangian studies predict higher ODPs regionally compared to the global model results. These 

differences highlight uncertainties in simulating the transport of VSLS, with boundary layer mixing, 

convection depth, and advection strength all possibly leading to local differences in VSLS delivery to the 

stratosphere (e.g., see Hossaini et al., 2012b; Feng et al., 2011; Hoyle et al. 2011). The global model 

studies (e.g., Wuebbles et al., 2011) used a full chemical treatment for VSLS and CFC-11 degradation in 

the stratosphere and more realistic degradation and wet deposition schemes for VSLS in the troposphere 

than the Lagrangian-based studies (e.g., Tegtmeier et al., 2012; Pisso et al., 2010), leading to less VSLS 

reaching the stratosphere. Overall, these results point to potentially more important impacts from VSLS if 

emissions occur in regions close to convective regions in the tropics.

Ravishankara et al. (1994) estimated that HFCs and other halocarbons with CF3 groups, such as 

HFC-23, -125, and -134a, could lead to ODPs of at most 0.0005 because of degradation product reactions. 

While the fluorine in HFCs is largely thought to be inert to ozone, it can destroy a small amount of ozone 

(Ravishankara et al., 1994). This can occur by (barely) catalytic cycles involving FOx = F + FO and 

CF3Ox = CF3O + CF3O2 + CF3O2NO2 families (e.g., Lary, 1997). Recent updates to relevant reaction rates 

suggest that the upper limits of the ODPs for such compounds are likely to be smaller (Sander et al., 

2011), indicating that these compounds (not containing chlorine, bromine, or iodine) are unlikely to have 

a significant effect on stratospheric ozone.

Table 5-4. Estimated annual-mean Ozone Depletion Potentials (ODPs) for short-lived halocarbons 

(very short-lived substances, VSLS) as a function of specific emissions location. The numbers in 

brackets show the seasonal variability. These semi-empirical ODP estimates are based on the Lagrangian 

model study of Brioude et al. (2010) (the numbers shown are from the Supplementary materials of the 

published paper). The ODP estimates for CHBr3 have been reduced by a factor of 3.1 compared with the 

Brioude et al. (2010) Supplement values owing to an error discovered after publication.

Species North America Europe East Asia Indian Subcontinent

C2H5Br 0.1300 

[0.0780 – 0.2000]

0.1100

[0.0610	– 0.1700]

0.2100

[0.1000	– 0.3100]

0.4600

[0.3400	– 0.6300]

CH2CBrCF3 0.0035

[0.0008 – 0.0077

0.0013

[0.0006	– 0.0024]

0.0052

[0.0011	– 0.0130]

0.0440

[0.0130	– 0.0830]

n-C3H7Br 0.0235 

[0.0150 – 0.0320]

0.0150

[0.0070	– 0.0260]

0.0420

[0.0190	– 0.0600]

0.1700

[0.0790	– 0.1300]

C2HCl3 0.0004 

[0.0001 – 0.0007]

0.0001

[0.0001	– 0.0002]

0.0006

[0.0002	– 0.0013]

0.0041

[0.0013	– 0.0079]

CCl3CHO 0.0008 

[0.0005 – 0.0010]

0.0004

[0.0002	– 0.0008]

0.0014

[0.0007	– 0.0022]

0.0062

[0.0026	– 0.0110]

CH3I 0.0360 

[0.0130 – 0.0650]

0.0140

[0.0072	– 0.0210]

0.0660

[0.0220	– 0.1500]

0.4200

[0.1300	– 0.8300]

CF3I 0.0068 

[0.0022 – 0.0120]

0.0034

[0.0013	– 0.0061]

0.0120

[0.0020	– 0.0310]

0.0940

[0.0290	– 0.1900]

C3F7I 0.0028 

[0.0007 – 0.0064]

0.0015

[0.0005	– 0.0031]

0.0033

[0.0006	– 0.0100]

0.0390

[0.0140	– 0.0670]

CH2ClI 0.0047 

[0.0011 – 0.0110]

0.0024

[0.0007	– 0.0050]

0.0051

[0.0009 – 0.0150]

0.0660

[0.0240	– 0.1100]

CHBr3 0.130

[0.094 – 0.201]

0.106 

[0.074 – 0.158]

0.216

[0.123	– 0.310]

0.581

[0.387	– 0.806]
Scenarios and Information for Policymakers

5.23

5.3.2 Metrics for Changes in Climate

Box 5-3 summarizes the basics of metrics used for describing changes in climate, namely, Global 

Warming Potentials (GWPs) and Global Temperature change Potentials (GTPs).

Box 5-3. Metrics for Climate: The Basics

Global Warming Potentials (GWPs)

Many metrics are based on the concept of radiative forcing (RF), which is itself a metric. RF has 

been commonly used to compare different forcing agents (e.g., emissions of gases and particles) affecting 

climate in assessments of climate change (e.g., IPCC, 1990, 1995, 1996, 1999, 2000, 2001, 2007, 2009,

2013). Traditionally, the use of radiative forcing as a metric has been based on there being a clear 

relationship between the globally averaged forcing and the globally averaged annual mean surface 

temperature response at equilibrium. IPCC reports now also use Effective Radiative Forcing (ERF) to 

compare different climate change mechanisms (Forster et al. in IPCC 2007; Myhre et al., 2013). Forcings 

can only be accurately compared in a global mean sense, and not all forcings necessarily have the same 

efficiency or “efficacy” in causing climate to change. The IPCC 5th Assessment Report accounts better for

the effects of efficacy by using the concept of ERF. For RF, all surface and tropospheric conditions are

assumed to be constant, while for ERF, all physical variables can respond to perturbations except for 

those concerning the sea surface temperatures and sea ice. The basis for ERF is to account for the rapid 

adjustments in the troposphere that occur in the climate system such as the effects on clouds. The 

inclusion of these adjustments makes ERF a better indicator of the eventual temperature response, 

especially from particles and other forcings on climate that have strong atmospheric responses on short 

timescales or have large spatial variations. By including many of the rapid adjustments that differ across 

forcing agents, the ERF concept includes much of their relative efficacy and therefore leads to more 

uniform climate sensitivity across agents than the traditional RF concept (Myhre et al., 2013). Because the 

rapid adjustments included in ERF differ in strength across climate models, the uncertainty range for ERF 

estimates tends to be larger than the range for RF estimates (Myhre et al., 2013). Nonetheless, for wellmixed gases, there is no significant difference between RF and ERF.

The Global Warming Potential (GWP) metric arose out of analyses done for the first IPCC 

Assessment and is still the most widely used emission metric and the general standard for metric 

discussion in Climate Assessments (IPCC 1990, 1996, 1999, 2007). It represents the radiative forcing for 

either pulse or sustained emissions above the current background levels by integrating the radiative 

forcing over a specific time interval and comparing that integral to the forcing from an equal mass 

emission of carbon dioxide. GWPs for different gases can be compared for evaluating their relative 

potential for affecting climate over a given timescale. The Kyoto Protocol and other climate-related 

policymaking also compares the effects of different emissions using GWPs with a 100-year time horizon, 

effectively mapping all greenhouse gas emissions into “CO2-equivalent emissions.” It has become 

common practice to use the 100-year time horizon for analyses of GWPs, but the choice of time horizon 

has no direct scientific basis (IPCC, 1990; Wuebbles, 1995; Myhre et al., 2013). Its choice is a value 

judgment since it depends on the relative weight assigned to effects at different times. Other important 

choices include the background atmosphere underlying the GWP calculations, and the way indirect 

effects and feedbacks are considered (Myhre et al., 2013).

Essentially, GWPs are a relative measure of the total energy added to the climate system by a 

component in question relative to that added by CO2. The GWP is approximately equal to the ratio 

(normalizing by the similar expression for CO2) of the equilibrium temperature response due to a 

sustained emission of the species or to the integrated temperature response for a pulse emission

(assuming efficacies are equal for the gases that are compared) (Myhre et al., 2013; also see O’Neill, 

2000; Prather, 2002; Peters et al., 2011; Azar and Johansson, 2012).
Chapter 5

5.24

Box 5-3, continued.

However, GWPs do not lead to equivalence with the temporal evolution of the temperature 

response or that of other climate variables. As a result, despite its existing use in policy considerations, 

there have been many critiques of the GWP concept. Metrics beyond radiative forcing and GWPs have 

been proposed but have not yet been used for policy decisions. The most prevalently discussed alternative 

metric is Global Temperature change Potential, also referred to as Global Temperature Potential (GTP).

Global Temperature change Potentials (GTPs)

The GTP metric (Shine et al., 2005; Shine et al., 2007) gives the relative temperature increase on 

a per unit mass of emissions basis due to emissions of a greenhouse gas relative to that due to CO2

emissions for the chosen time horizon. GTP takes into account the thermal inertia and response of the 

climate system, and provides a measure of the temperature responses of the different components for a 

specific time horizon. GTP is an end-point measure based on temperature change for a selected year. As 

with GWPs, the choice of time horizon has a strong effect on the metric. Like GWPs, GTPs can be used 

for weighting the emissions to obtain “CO2 equivalents.”

GWPs and GTPs are fundamentally different by construction (see Figure 5-1) and different 

numerical values can be expected. By accounting for the climate sensitivity and the exchange of heat 

between the atmosphere and the ocean, GTPs include physical processes that GWPs do not. GTPs 

account for the slow response of the (deep) ocean, thereby prolonging the response to emissions beyond 

what is controlled by the decay time of the atmospheric concentration. GTPs include both the atmospheric 

adjustment timescale of the component considered and the response timescale of the climate system. 

However, GTPs also incorporate extra uncertainties relative to GWPs from including the climate response 

in the analysis, e.g., GTP values can be significantly affected by assumptions about the climate sensitivity 

and heat-uptake by the ocean (also see discussion in Myhre et al., 2013). As such, GTPs are sensitive to 

the specific climate model used in their derivation (e.g., see Olivié and Peters, 2013) and to the 

background scenario used in the analyses. As a result, the relative uncertainty ranges are potentially much 

wider for GTPs compared to GWPs. 

Peters et al. (2011) provide additional useful insights to the GWP and GTP emissions metrics. 

They found that GWPs are a useful measure of the energy entering the climate system. GWPs and GTPs 

should be different as GTPs are an instantaneous measure while GWPs are an integrated measure of the 

system; that is, for the GTP the pathway of the forcing following a pulse emission is important, whereas 

the GWP depends only on the integral of the forcing. The ultimate choice of emission metric(s) and time

horizon(s) depends on policy objectives. To the extent that limiting integrated temperature change over a 

specific time horizon is consistent with the broader objectives of climate policy, the analysis by Peters et 

al. suggests that the GWP concept represents a relatively robust, transparent, and policy-relevant emission 

metric, except for the short-lived gases, but GWPs are quite small for such gases.

ANALYSES OF GWPS AND GTPS

Updated GWPs and GTPs for many compounds based on the analyses in IPCC (Myhre et al., 

2013) are shown in the Appendix in Table 5A-1. Also shown are the atmospheric lifetimes and radiative 

efficiencies used in these analyses. Hodnebrog et al. (2013) provide further descriptions of the analyses of 

radiative efficiencies for many halocarbons and related compounds (the IPCC values for the GWPs and 

GTPs are largely based on those in Hodnebrog et al.). Absolute GWP and GTP (AGWP and AGTP) are 

the absolute integral of RF (W m-2yr; using ERF if possible) and the absolute temperature change (°C) 

for a kilogram emission of the greenhouse gas. Climate-carbon feedbacks (i.e., feedbacks between climate 

change and the carbon cycle) are included in the AGWP and AGTP of CO2, but not for the AGWP of the 

non-CO2 gases; see discussion below. In the new IPCC analyses, there is an increase of approximately 1% 

and 6% relative to IPCC (2007) and WMO (2011) in the AGWP for CO2 for integrations of 20 and 100 
Scenarios and Information for Policymakers

5.25

years, respectively. As a result, many of the GWP values decrease slightly, but they also change because 

of changes in the lifetime and the radiative efficiency of the named greenhouse gas. This is the first time 

that values are provided for GTPs in the Ozone Assessment. The derivation of GTP in IPCC (2013) 

assumes a climate sensitivity of 1.06°C (W m-2)

-1

, equivalent to a +3.9°C equilibrium response to 2 × CO2, 

toward the higher end of the traditional range in climate sensitivity of 1.5 to 4.5°C for doubling of CO2.

The IPCC (2013) GWP and GTP values do not include the changes in atmospheric lifetimes 

recommended by SPARC (2013). Table 5-5 adjusts the IPCC GWPs and GTPs for the 24 halocarbons 

with recommended lifetimes from SPARC (2013). Halon-1211 and CCl4 were the only ODSs for which

the lifetime was unchanged. The changes in GWPs and GTPs are roughly proportional to the changes in 

atmospheric lifetimes. Although there are some differences for all of the gases (except halon-1211 and 

CCl4), the largest differences in GWPs and GTPs relative to Table 5A-1 are found for CFC-11, CFC-115, 

halon-1301, halon-2402, halon-1202, HFC-125, and HFC-143a.

Uncertainties in GWP values based on the uncertainties given for radiative efficiencies, 

perturbation lifetimes, and in the AGWP for the reference gas CO2 are estimated in IPCC AR5 Chapter 8 

(Myhre et al., 2013). The uncertainty in GWPs for gases with lifetimes of a few decades is estimated to be 

approximately ±25% and ±35% for 20 and 100 years, respectively. Velders and Daniel (2014) report 

uncertainties on a number of ODSs; their results suggest that the uncertainties differ substantially for 

different ODSs. Table 5-6 shows the estimated uncertainty ranges in 20-year and 100-year GWPs for 

several HFCs, first due to uncertainties in the SPARC (2013) lifetimes by themselves, and then in 

combination with other uncertainties in evaluation of the full range of uncertainties.

For shorter-lived gases, the uncertainties in GWPs will be larger but the GWP values are also 

smaller. For GTPs, few uncertainty estimates are currently available in the literature. In IPCC, the results 

from Joos et al. (2013), Reisinger et al. (2010, 

2011), and Boucher (2012) were used to assess an 

uncertainty for methane for a 100-year GTP of 

±75% (as compared to a range of 14 to +22% for 

100-year GWPs, based on Olivié and Peters 

(2013)). The uncertainty in GTPs for longer-lived 

gases is much smaller (e.g., −17 to +24% for N2O). 

We do not attempt to show the range of 

uncertainties for GTPs in this Assessment.

Figure 5-1. (a) The Absolute Global Warming 

Potential (AGWP) is calculated by integrating the 

RF due to emission pulses over a chosen time 

horizon; e.g., 20 and 100 years (vertical lines). The 

GWP is the ratio of AGWP for component i over 

AGWP for the reference gas CO2. The blue-hatched 

field represents the integrated RF from a pulse of 

CO2, while the green and red fields represent 

example gases with 1.5-year and 13-year lifetimes, 

respectively. (b) The Global Temperature change 

Potential (GTP) is based on the surface 

temperature response at a selected year after pulse 

emission of the same gases; e.g., 20 or 100 years 

(vertical lines). See IPCC (2013) Supplementary 

Material Section S8.11 for equations for calculations 

of GWP and GTP as used here.
Chapter 5

5.26

Table 5-5. GWPs and GTPs of various halocarbons based on the SPARC (2013) atmospheric 

lifetimes. Except for the HFCs, the lifetimes are also found in Table 5-1.

Halocarbon SPARC 

(2013)

Lifetime 

(years)

GWP

20-yr

GWP

100-yr

GTP

20-yr

GTP

50-yr

GTP

100-yr

Annex A-I

CFC-11 52 7090 5160 7160 5480 2920

CFC-12 102 10800 10300 11300 11000 8590

CFC-113 93 6560 6080 6830 6510 4860

CFC-114 189 7710 8580 8180 9010 8530

CFC-115 540 5780 7310 6210 7500 8290

Annex A-II

halon-1301 72 7930 6670 8160 7160 4700

halon-1211 16 4590 1750 3950 1130 297

halon-2402 28 3920 2030 3730 1900 615

Annex B-II

CCl4 26 3480 1730 3280 1570 479

Annex B-III

CH3CCl3 4.8 555 153 298 32 21

Annex C-I

HCFC-22 12 5310 1780 4230 847 265

HCFC-141b 9.4 2590 800 1900 285 114

HCFC-142b 18 5140 2070 4530 1490 387

Annex E

CH3Br 0.8 9 2 3 <1 <1

Others

halon-1202 2.5 719 196 285 35 27

CH3Cl 0.9 40 11 13 2 2

HFC-23 228 10800 12500 11500 13000 12800

HFC-32 5.4 2530 704 1440 154 98

HFC-125 31 6280 3450 6040 3350 1180

HFC-134a 14 3810 1360 3170 771 214

HFC-143a 51 7050 5080 7110 5390 2830

HFC-152a 1.6 545 148 191 26 21

HFC-227ea 36 5250 3140 5140 3180 1260

HFC-245fa 7.9 2980 882 2040 259 124

Values of the GWP and GTP metrics are dependent on what processes are included. Ideally all 

indirect effects should be taken into account. The indirect effects of CH4 on its own lifetime, tropospheric 

ozone, and stratospheric water have been traditionally included in its GWP (Prather, 1994; IPCC, 1995). 

The indirect effect of N2O on its own lifetime has been considered since the IPCC 3rd Assessment Report 

(Prather, 1998; IPCC, 2001; Prather and Hsu, 2010). The WMO Assessments (e.g., WMO, 2007, 2011) 

have considered the indirect effects on stratospheric ozone from various halocarbons. In Table 5-7, 

indirect GWPs based on IPCC (2013) for various halocarbons are updated using the approach for the 

ozone response first developed by Daniel et al. (1995). The resulting values are similar to those found in 

the previous Assessments.
Scenarios and Information for Policymakers

5.27

Table 5-6. For selected HFCs, lifetime and full uncertainty estimates of the 20- and 100-year GWPs 

using the SPARC (2013) lifetimes. The number ranges represent the effects of only considering 

uncertainties in the SPARC lifetimes, while the “full uncertainty” ranges include also uncertainties in the 

radiative efficiency (10%, from Myhre et al., 2013) and the AGWP for CO2 (from Joos et al., 2013). The 

GWP uncertainties are calculated as in Myhre et al. (2013) (see Supplementary Material Section 8.SM.12 

in IPCC (2013) for details), except that new information about lifetime uncertainties from SPARC (2013) is 

included here. The uncertainty estimates are representative of a 5 to 95% (90%) confidence interval. In 

addition, note that the IPCC (2013) stated uncertainties in the 100-year GWP for HFC-134a is ±35% (90% 

confidence) as representative for similar gases. The IPCC and updated GWPs that use the SPARC 

lifetimes are consistent within their uncertainties.

Halocarbon SPARC 

(2013)

GWP 20-yr GWP 100-yr

Lifetime 

(years)

Best 

Estimate 

Lifetime 

Uncertainty

Full 

Uncertainty

Best 

Estimate

Lifetime 

Uncertainty

Full 

Uncertainty

HFC-23 228 10800 10700–11100 8640–13100 12500 11800–14000 8880–16300

HFC-32 5.4 2530 2030–3530 1810–3650 704 551–1010 453–1070

HFC-125 31 6280 5840–7110 4930–7800 3450 2720–4830 2230–5140

HFC-134a 14 3810 3300–4690 2890–4980 1360 1040–1930 860–2050

HFC-143a 51 7050 6780–7690 5600–8620 5080 4340–6790 3460–7310

HFC-152a 1.6 545 431–718 386–750 148 117–195 96–211

Table 5-7. Indirect GWPs from ozone depletion (direct forcing from ODS, themselves, is not 

included) taken from IPCC (2013). Approach is taken from Daniel et al., 1995, assuming a radiative 

forcing due to ozone depletion in 2011 of −0.15 W m-2 (IPCC, 2013). Uncertainty in this radiative forcing 

leads to an uncertainty in these GWPs of ±100%. 

SUBSTANCE GWP 100-yr

CFC-11 –2640

CFC-12 –2100

CFC-113 –2150

CFC-114 –914

CFC-115 –223

HCFC-22 –98

HCFC-123 –37

HCFC-124 –46

HCFC-141b –261

HCFC-142b –152

CH3CCl3 –319

CCl4 –2110

CH3Br –1250

halon-1211 –19000

halon-1301 –44500

halon-2402 –32000

HCFC-225ca –40

HCFC-225cb –60
Chapter 5

5.28

It is also important to consider feedbacks between climate and the carbon cycle, effectively the 

additional amount of CO2 released from the warming caused by any greenhouse gas. Gillett and Matthews 

(2010) included climate-carbon feedbacks in calculations of the GWPs for CH4 and N2O and found that 

this increased the values by ~20% for the 100-year GWP. For GTPs they found an increase of ~80%. The 

AGWP for the CO2 reference gas has included the climate–carbon feedback in the analyses of GWP in 

recent Assessments (WMO, 2011; IPCC, 2007, 2013). For the first time, Myhre et al. (2013) include 

analyses of these indirect climate-carbon feedback effects on GWPs and GTPs for many halocarbons. For 

many gases, the correction is sizeable, increasing the values of the GWPs and GTPs. However, 

uncertainties remain large, so more analysis is likely needed before this additional effect is included in 

policy considerations. Also, the GWPs for the combination of indirect effects on ozone depletion and 

climate-carbon feedbacks have not been evaluated.

5.4 SCENARIOS AND SENSITIVITY ANALYSES

This section presents an analysis of a set of scenarios and hypothetical test cases that may be of 

use to decision-makers. The existing Montreal Protocol and its Amendments and adjustments provide the 

backdrop and a framework for these analyses. Options evaluated include the elimination of future 

production and future emissions in advance of current controls, and the recapture and destruction of banks

(see Box 5-1) in 2015 and 2020. Results are roughly linear, in that a decrease in 50% of future production 

will have about half the effect on ozone depletion and climate forcing as the scenario evaluated here in 

which all future production is eliminated. This Ozone Assessment does not evaluate the technical or 

economical feasibility of these options, but because of the linearity, these results can help guide 

policymakers in their environmental evaluation of feasible options.

5.4.1 Tools Used in Analyses of Ozone and Climate Effects

As in WMO (2011), both EESC and climate-chemistry modeling studies are used in the scenario 

analyses relating to ozone impacts. As discussed earlier, EESC is a metric that relates the tropospheric 

concentration of source gases to their chemically active stratospheric products that are available to destroy 

ozone. It has been shown (Daniel et al., 2010) that the halogenated ODS mitigation options have about the 

same percentage impact on integrated EESC as on integrated global stratospheric total column ozone. 

Because of the computational ease of calculating EESC, an EESC analysis allows for a fast and accurate 

method for comparing potential ODS mitigation options involving halogenated species without running a 

full atmospheric model. 

Typically, EESC has only been used for halocarbon source gases. However, surface N2O 

concentrations due to anthropogenic activity can also be included in EESC (Daniel et al., 2010). The 

calculation of N2O’s contribution to ozone depletion, and thus to EESC, is complicated by other chemical 

interactions, such as the concentration of atmospheric chlorine and stratospheric aerosols (Ravishankara 

et al., 2009), but these obstacles are similar to those encountered by the chlorine- and bromine-containing 

gases. In this chapter, we do not include N2O in our standard EESC calculations, but we do include a set 

of sensitivity runs to show the degree to which the two-dimensional (2-D) modeled ozone response 

compares with the N2O EESC response for an N2O mitigation option. 

The NASA/Goddard Space Flight Center (GSFC) 2-D coupled chemistry-radiation-dynamics 

model (Fleming et al., 2011) is used to evaluate the impact of various ODS and GHG scenarios on past 

and future ozone, including evaluation of the effects of changes of CO2 and CH4 that cannot readily be 

addressed by EESC as used here. While three-dimensional (3-D) climate-chemistry modeling studies 

would be ideal for these scenario/test analyses, the computational and time requirements make most of 

these studies prohibitive for this Assessment. The GSFC 2-D model provides realistic simulations of 

meridional transport in the stratosphere on timescales >30 days, as seen by good model agreement with a 

variety of observations in reproducing transport-sensitive features in the meridional plane (Fleming et al.,
Scenarios and Information for Policymakers

5.29

2011). Since the computational efficiency of a zonally averaged 2-D model makes it possible to perform 

multiple long-term simulations in a reasonable amount of time, this 2-D climate-chemistry model is optimal 

for addressing the ozone-change scenarios discussed here. To be consistent with the model results reported 

in other Chapters, the model simulations presented here use the recommended chemical rate constants from 

Sander et al. (2011). Sensitivity simulations revealed that using the updated rate constants from SPARC 

(2013) resulted in a very minor impact on global total ozone, with changes <±0.2 Dobson units (DU).

Radiative forcing is used to quantify the potential effects of the various scenarios on climate. The 

radiative forcing is calculated with a radiative transfer model using the spatial distribution of mixing 

ratios determined from observations or calculated in the given atmospheric chemistry-climate model. For 

the halocarbons, radiative forcing is determined by multiplying the surface mixing ratio by the 

appropriate radiative efficiency (see Appendix 5A, Table 5A-1). The radiative forcing of N2O is based on 

the analyses in Annex II of IPCC (2013).

In addition to the previously discussed ozone depletion and climate metrics, integrated ODP- and 

GWP-weighted quantities are also shown in Table 5-8 as another comparative tool.

5.4.2 Background Scenario(s) for Ozone and Climate

To evaluate the impact of potential policy decisions on ozone depletion and climate change, a 

background or baseline scenario of mixing ratios from 1950 through 2100 has been developed for ODS 

halocarbons and N2O (and CH4 and CO2 in the 2-D model), against which other scenarios are compared. 

These alternative scenarios are consistent with various mitigation options and are discussed in more detail 

in Section 5.4.3. The RCP6.0 scenario is used for the time evolution of CO2, CH4, and N2O abundances in 

the background scenario.

The baseline scenario for the halocarbon ODSs is consistent with the current upper limits 

prescribed by the Montreal Protocol on Substances that Deplete the Ozone Layer, and it has been 

developed to be consistent with mixing ratio observations through the beginning of 2013 (see Chapter 1). 

In the years before atmospheric observations were made, mixing ratios have been estimated from reported 

production values and are very similar to values in WMO (2011). Future projections are determined from 

global lifetime estimates that have been recently updated (SPARC, 2013), future production amounts set 

to be the maximum allowed under the Montreal Protocol, and bottom-up bank estimates for 2008 are the 

same as were used in WMO (2011). It is assumed that future releases of halocarbons from equipment and 

applications will continue at the same fractional rate as estimated over the period 2005 through 2011. 

Figure 5-2 compares the current baseline scenario and alternative scenarios (see Section 5.4.3 for 

a description of these scenarios) with the baseline scenario from WMO (2011). The most significant 

difference in terms of effects on EESC between the two baseline scenarios results from the longer 

estimated lifetimes for CFC-11 and CCl4. These lead to slower atmospheric decay and thus an increased 

contribution to EESC in the future. Lifetime estimate changes have no effect on historical mixing ratios 

since those are constrained by observations. Some of the largest relative mixing ratio changes occur for 

the HCFCs. These are primarily caused by the lower base level against which future HCFC production 

and consumption in Article 5 Parties are referenced to in the current baseline compared with the one from 

WMO (2011); they are also partly due to a higher assumed level of production between 2009 and 2012 in 

the previous Assessment, before the freeze went into effect in 2013. The Article 5 base production level is 

defined in the Montreal Protocol as the average of the 2009–2010 production. In WMO (2011), it was 

estimated that the Article 5 base level for the HCFCs would be slightly more than 36 ODP-ktonnes; it is 

now known to be about 33 ODP-ktonnes. This affects the current HCFC production as well as the 

production and emissions for decades to come since the future limits on production and consumption are 

prescribed by the Montreal Protocol to be a decreasing fraction of this base level over time.

Changing concentrations of CO2, CH4, and N2O also affect stratospheric ozone and should be 

considered in analyses of ozone. CO2 and CH4 have never been included in the EESC formalism, and 

N2O’s contribution to EESC has met with limited use. Therefore, in this chapter, we will consider the impact
Chapter 5

5.30

Table 5-8. Comparison of scenarios and casesa: the year when EESC drops below the 1980 value for both 

midlatitude and Antarctic vortex cases, and integrated EESC differences (midlatitude case) relative to the 

baseline (A1) scenariob. Also shown are changes in integrated ODP- and GWP-weighted emissions and, for selected 

cases, integrated global ozone depletion from 2015−2050. Future changes in CH4 and CO2 may also significantly alter 

ozone levels, perhaps by amounts larger than any of the cases considered in this table. However, their effects are not 

included here because policy choices that would lead to reduced global O3 depletion would require increased CH4 and 

CO2, which would increase climate forcing.

Scenario and 

Cases

Percent Difference in 

Integrated EESC Relative 

to Baseline Scenario for the 

Midlatitude Case

Year When EESC is Expected 

to Drop Below 1980 Value

Change in 

Cumulative 

ODPWeightedd

Emission: 

2015−2050

Change in 

Cumulative 

GWPWeightede

Emission: 

2015−2050

Percent 

Difference in 

Integrated

O3

Depletionf:

2015−2050

Midlatitude b,c

 

Antarctic 

vortex c

(Million

tonnes

CFC-11-

equivalent)

(Billion 

tonnes

CO2-

equivalent)

Scenarios

A1: Baseline scenario - - 2047.6 2073.3 0.0 0.0

Casesa of zero production from 2015 onward of:

P0: All ODS −5.9 −20 2042.8 2069.5 −0.91 −9.0 −0.30

CFCs 0.0 0.0 2047.6 2073.3 −0.00 −0.00 -

halons 0.0 0.0 2047.6 2073.3 −0.00 −0.00 -

HCFCs −1.8 −6.4 2046.3 2072.6 −0.22 −7.8 −0.12

CH3Br for QPS −1.6 −5.3 2046.5 2071.9 −0.13 −0.00 −0.07

CCl4 −2.8 −9.8 2045.3 2071.6 −0.56 −1.2 −0.11

Casesa of zero emissions from 2015 onward of:

E0: All ODS (does 

not include N2O)

−12 −40 2036.5 2061.4 −2.72 −18.5 −0.75

CFCs −2.6 −8.9 2045.0 2069.6 −0.86 −4.7 −0.20

halons −3.4 −12 2044.8 2070.1 −0.76 −0.24 −0.16

HCFCs −3.7 −13 2045.3 2072.2 −0.41 −12.4 −0.19

CCl4

g −2.8 −9.8 2045.3 2071.6 −0.56 −1.2 −0.11

CH3CCl3 0 0 2047.6 2073.3 −0.00 −0.00 -

CH3Br for QPS −1.6 −5.3 2046.5 2071.9 −0.13 −0.00 −0.07

Total anthropogenic N2O h- - - - −6.69 −104 −0.88

N2O mitigation −1.25 −19.5 −0.16

Casesa of full recovery of the 2015 banks of:

B0: All ODS −7.3 −25 2041.3 2065.7 −1.80 −9.6 −0.44

CFCs −2.6 −8.9 2045.0 2069.6 −0.86 −4.7 −0.20

halons −3.4 −12 2044.8 2070.1 −0.76 −0.24 −0.16

HCFCs −1.9 −6.4 2046.8 2072.9 −0.19 −4.6 −0.07

Casesa of full recovery of the 2020 banks of:

B0: All ODS −4.7 −16 2042.4 2066.8 −1.39 −8.1 −0.38

CFCs −1.5 −5.3 2045.6 2070.3 −0.64 −3.3 -

halons −2.0 −6.8 2045.4 2070.6 −0.56 −0.18 -

HCFCs −1.6 −5.5 2046.5 2072.7 −0.19 −4.6 -

CH3Br sensitivity: i

Same as A1, but 

CUEs continue at 

2012 levels

+0.2 +0.7 2047.8 2073.5 +0.02 +0.00 -

€

EESC dt

1980

x

∫ EESC dt

2015

x

∫
Scenarios and Information for Policymakers

5.31

Table 5-8, continued. a Significance of ozone-depleting substances for future EESC was calculated in the hypothetical “cases” by setting production or 

emission to zero in 2015 and subsequent years or the bank of the ODS to zero in the year 2015 or 2020. 

b EESC is integrated until it returns to 1980 levels, denoted as year “x.”

c For midlatitude conditions, an average age-of-air of 3 years, corresponding fractional release values, and a bromine efficiency 

factor (alpha) of 60 are assumed. For Antarctic vortex conditions, an average age-of-air of 5.5 years, corresponding fractional 

release values, and an alpha value of 65 are assumed. In all cases, age spectra are applied as in Newman et al. (2007).

d Semi-empirical ODPs from Table 5-2.

e GWPs with 100-year time horizon (see Appendix 5A, Table 5A-1).

f

Integrated globally averaged total column ozone changes are taken from 2-D model runs described in chapter.

g Banks are assumed to be zero. Emissions include uncertain sources such as possible fugitive emissions and unintended other 

emissions.

h The integrated ODP- and GWP-weighted emissions correspond to the reduction of anthropogenic N2O emissions from a 

business-as-usual case to a strong mitigation case (see text).

i

Same as A1 but critical-use exemptions continue at 2012 levels.

of these three gases in the 2-D model calculations, but not with the box model EESC analysis, except for 

a brief discussion of the estimated impact of N2O on EESC. The baseline scenario chosen for these 

compounds is taken to be the RCP6.0 scenario. While RCP6.0 is a mitigation scenario, it represents one 

choice of a central scenario around which we can explore the sensitivity of our results to a stronger 

mitigation scenario (RCP4.5) and a business-as-usual scenario (RCP8.5). This sensitivity analysis has 

been performed to explore the impact of this choice on the results, but in general, it has little effect on the 

impacts of the halocarbon mitigation scenarios in terms of either depletion of globally averaged total 

ozone or on climate forcing changes. However, the scenario choice could have local effects on the 

structure of ozone changes with altitude and latitude.

5.4.3 Alternative Future Scenarios

Future scenarios have been developed that reflect the impacts of various mitigation options to 

further reduce future ozone depletion. Because halocarbons and N2O are greenhouse gases, these scenarios 

will reduce climate forcing as well. For the ODS halocarbons, the mitigation options include capture and 

destruction of the banks (see Box 5-1), elimination of future production beginning in 2015, and elimination 

of future emissions beginning in 2015. Two sets of bank recapture scenarios have been performed, one for 

elimination of banks in 2015 and one for 2020. A comparison of these bank scenarios illustrates the 

reduced impact of the bank capture option on ozone and climate as the halocarbons are released into the 

atmosphere over this 5-year period and bank sizes are projected to decline for most ODSs. Because all 

post-2015 emission either originates from production after 2015 or from banks existing in 2015, the 

production elimination and bank capture and destruction scenarios can be approximately added together to 

reproduce the “no emission” scenario results. The reason that the results are not always perfectly additive 

is that some of the metrics quantified here are tied to the return of EESC to 1980 levels and this return time 

changes differently in each mitigation scenario. The production, bank, and emission scenarios are run for 

individual ODS groups to evaluate the impact of mitigation options for each group to the future ozone and 

climate metrics. These individual calculations allow for a straightforward evaluation of the relative 

importance of future production and bank sizes for each of the ODS groups considered.

Figure 5-2 shows future ODS concentration projections for the various mitigation options. The 

CFCs should have almost no additional production in the future scenarios and so all future emissions are 

assumed to originate from current equipment and applications. Thus, bank recapture and destruction is the 

only approach to reduce future mixing ratios of the CFCs. On the other hand, banks of CH3Br and CCl4
Chapter 5

5.32

Figure 5-2. Comparison of current baseline halocarbon mixing ratios compared with those from the 

baseline scenario of WMO (2011); also shown are future mixing ratio projections for “no emission from 

2015 onward,” “bank capture and destruction in 2015,” “bank capture and destruction in 2020,” and “no 

production from 2015 onward” scenarios. Curves are color coded in the same manner as in Figure 5-3 

(e.g., solid black is the baseline scenario). Shaded regions represent mixing ratios that are constrained to 

observational estimates (see Chapter 1; Chapter 5 Appendix 5A, Table 5A-2). The approximate natural 

concentration of CH3Br is noted by the dashed dark blue line in the lower right-hand panel (see Chapter 1).

CFC-11

1960 1990 2020 2050

0

100

200

300

ppt

1960 1990 2020 2050

CFC-12

1960 1990 2020 2050

0

200

400

600

1960 1990 2020 2050

CFC-113

1960 1990 2020 2050

0

20

40

60

80

100

ppt

1960 1990 2020 2050

CFC-114

1960 1990 2020 2050

0

5

10

15

20

1960 1990 2020 2050

CCl4

1960 1990 2020 2050

0

20

40

60

80

100

120

ppt

1960 1990 2020 2050

CH3CCl3

1960 1990 2020 2050

0

50

100

150

1960 1990 2020 2050

HCFC-22

1960 1990 2020 2050

0

100

200

300

400

ppt

1960 1990 2020 2050

HCFC-141b

1960 1990 2020 2050

0

10

20

30

40

1960 1990 2020 2050

HCFC-142b

1960 1990 2020 2050

0

10

20

30

40

ppt

1960 1990 2020 2050

Halon 1211

1960 1990 2020 2050

0

1

2

3

4

5

1960 1990 2020 2050

Halon 1301

1960 1990 2020 2050

0

1

2

3

4

ppt 1960 1990 2020 2050

CH3Br

1960 1990 2020 2050

0

2

4

6

8

10

12

1960 1990 2020 2050

Approximate Natural Level
Scenarios and Information for Policymakers

5.33

may be small compared with their annual production; for these compounds, eliminating production is the 

way to reduce their future mixing ratios. Of course, as discussed in Chapter 1, there is a discrepancy 

between top-down emissions estimates derived from CCl4 mixing ratio observations and reported 

production, with reported production too small to be able to account for the observed trend in abundances 

even if all production were emitted immediately. Thus, to the extent that there is additional unidentified 

emission that does not come from reported production, elimination of that emission could reduce future 

EESC and ozone depletion. In this Assessment we adopt current emissions of CCl4 from the top-down 

estimates and assume that future emissions will decline at 6% per year in the absence of additional 

controls. HCFCs can be noticeably reduced in the future by both bank recapture and destruction and by 

production elimination. It is important to recognize that only emissions resulting from QPS and criticaluse exemptions (CUE) applications are considered in our scenario calculations. While controlled uses are 

thought to lead to small emissions in comparison to QPS emissions (see Chapter 1), we also neglect 

emissions associated with other activities, such as biomass burning and gasoline and biofuel usage. The 

baseline scenario for WMO (2011) is shown for comparison in Figure 5-2. 

Figure 5-3 shows the impacts of the different mitigation options on total midlatitude EESC. The 

“No Future Emissions” curve represents the EESC levels to which we are committed even if no ODSs are 

emitted from 2015 on. This limiting case assumes no further production and no release from existing 

banks. Both future production and current banks contribute to the elevation of EESC above this level in 

our baseline scenario approximately equally as shown by the various curves. The difference between the 

“Zero 2015 Bank” and “Zero 2020 Bank” curves illustrates the impact on EESC of waiting 5 years to 

capture and destroy the banks; this difference is largest just after 2020 and shrinks over time. Velders and 

Daniel (2014) have quantified the EESC uncertainty in a scenario that is similar to the baseline scenario 

shown in Figure 5-3. That calculated uncertainty is determined from uncertainty estimates in all the terms 

that are used in the EESC calculation. It is found that the 2-σ fractional EESC uncertainty when 

considering the “most likely” lifetime ranges is comparable to the maximum difference between the 

baseline scenario and the zero emissions scenario. Overall, the most important single factor to future 

EESC uncertainty is the uncertainty in the lifetimes of the ODSs.

Table 5-8 shows, as in WMO (2011), how different specific mitigation options affect integrated 

EESC, ODP- and GWP-weighted emissions, and the return to 1980 EESC levels. In terms of future 

emissions, HCFCs, halons, CFCs, CCl4, and CH3Br all contribute noticeably to increasing future integrated

Figure 5-3. EESC for the current 

baseline scenario (midlatitude conditions) compared with EESC from 

the WMO (2011) baseline scenario; 

also shown are four alternative 

scenarios that reflect current mitigation alternatives considered in this 

Assessment. Velders and Daniel 

(2014) have quantified the uncertainty 

in a similar EESC scenario considering uncertainties in all contributing terms; they found that the 2-σ

uncertainty values in the future vary 

somewhat over time, but are less 

than 15% when the most likely 

lifetime ranges are considered and 

the curves are normalized at 1980 

EESC levels. 1960 1980 2000 2020 2040 2060 2080 2100

Year

0

500

1000

1500

2000

EESC

Current Baseline

No Future Emissions

Zero 2015 Bank

Zero 2020 Bank

No Future Production

WMO (2011)
Chapter 5

5.34

Figure 5-4. Model calculations of the 

globally averaged total column ozone 

difference relative to 1950. Upper panel: 

the baseline scenario, a scenario of no 

future ODS emissions (blue), no future 

human-related N2O emissions (green), and 

the N2O mitigation scenario from UNEP 

(2013) (red dashed-dotted). Bottom panel: 

the impact due to only the decreasing 

ODSs, with CO2, CH4, and N2O fixed at 

2000 levels (blue), and the separate 

impacts due to future increasing CO2 (red), 

CH4 (yellow), and N2O (green) in the 

presence of decreasing ODSs. The 

RCP6.0 scenario was used for the 

greenhouse gases. As stated in the text, 

these scenarios are different than those 

presented in Chapter 2.

EESC, where the integration is stopped once total EESC drops below 1980 levels. If all ODS emissions 

were to be eliminated beginning in 2015, EESC for midlatitudes would return to 1980 levels 11 years 

sooner than in the baseline scenario. The most significant projected emissions for determining the return 

time arise from current halon, CFC, and HCFC banks and future production of HCFCs, and CH3Br. 

Future emissions of CCl4 are also projected to be important, but as discussed in Chapter 1 and in this 

chapter, the sources of these emissions are uncertain. Production of CH3Br has been eliminated for many 

historical uses. However, production for quarantine and pre-shipment (QPS) applications is not controlled 

and is currently the largest remaining emissive anthropogenic component of CH3Br production. The 

elimination of future emissions from QPS uses could bring forward the date of EESC return to 1980 

levels by 1.1 years, smaller than the 1.6 years estimated in the previous Assessment. Critical-use 

exemptions for CH3Br also continue to be granted, but emissions arising from this production are 

substantially smaller than those from QPS activities. A continuation of critical-use exemptions at the 

current level would delay the return of EESC to 1980 levels by 0.2 years. For climate considerations, 

HCFCs play the largest role in future integrated GWP-weighted emissions, contributing almost two-thirds 

of the total by the ODS halocarbons. These emissions result primarily from future HCFC production, but 

current banks are also important. Future CFC emissions represent most of the remaining cumulative 

GWP-weighted emissions through 2050 and are due almost exclusively to current banks. 

Table 5-8 also shows the changes in integrated global ozone levels for selected scenarios run with 

the 2-D model. Figure 5-4 (top panel) shows the two most significant scenarios: 1) no future ODS 

emissions, and 2) no future human-related N2O emissions. Also shown is the effect of more modest N2O 

mitigation on future ozone. Unlike the ODS halocarbon scenarios, this N2O alternative mitigation 

scenario does not assume complete elimination of future production or emission. N2O has a number of 

sources but a major one results from the use of fertilizers, i.e., it is to a large degree a by-product of global 

food production, and because there are no replacements for this use, we have adopted the “concentrated 
Scenarios and Information for Policymakers

5.35

mitigation” scenario from UNEP (2013) for the alternative mitigation scenario here to compare with the 

baseline. Even though the reduction in N2O is only a fraction of the total anthropogenic emissions, the 

results here are qualitatively consistent with WMO (2011): the impact of all anthropogenic N2O emissions 

is very significant compared with the sum of all halocarbon emissions in terms of both ozone depletion 

and climate. When integrated through 2050, elimination of all anthropogenic N2O emissions leads to a 

slightly larger reduction in future CO2-equivalent emissions than would the elimination of all ODS 

halocarbon emissions. In terms of integrated ODP-weighted emissions, elimination of anthropogenic N2O 

has about half the effect of an elimination of all ODS halocarbon emissions. The alternative N2O 

mitigation scenario has an obviously smaller impact on global ozone by 2050. N2O’s impact becomes 

relatively more important over time because the halocarbon production and consumption is phased out by 

the Montreal Protocol, while N2O is projected to continue growing under many future scenarios, 

including those considered here. It must be recognized, however, that the quantitative impact of N2O 

emissions mitigation depends on the baseline scenario chosen (RCP6.0 here). A higher baseline scenario 

will increase the impact of N2O mitigation on future climate forcing and ozone depletion.

Figure 5-5 shows the relative importance of historical and future projected N2O abundances on 

EESC relative to that of the ODS halocarbons for the baseline scenario used in the chapter. This 

exemplifies the increasingly important role that N2O is expected play in the future if its emissions are not 

reduced. A similar response is seen in the 2-D model calculations of ozone with increasing N2O but CO2

and CH4 fixed at 2000 levels, with increasing ozone flattening and even starting to decrease in the later 

part of the 21st century (Figure 5-4, bottom, green line). The upper panel of Figure 5-4 shows the relative 

impact of reducing or eliminating future N2O emissions compared with that of eliminating future 

halocarbon ODS emissions on global average total ozone. While total future N2O emissions cause 

substantially more depletion in the future than do future halocarbon ODS emissions, many of the N2O 

emissions are expected to be very difficult to eliminate (UNEP, 2013). If the UNEP (2013) N2O 

mitigation scenario is adopted, which was only analyzed to 2050 (Figure 5-4, top, red dash-dotted line), 

there is little difference relative to the baseline scenario and much less change than if the no future ODS 

emissions scenario were adopted (blue line). Again, however, the impact of N2O mitigation is expect to 

grow past 2050, while that of ODS halocarbon mitigation will decrease.

It is important to recognize that any future increases in CO2 and CH4 not only will have a 

substantial impact on climate forcing, but also are expected to lead to higher levels of globally averaged 

total ozone than if these greenhouse gases remained constant. So while CO2 and CH4 are likely not 

considered candidates for altering future ozone depletion themselves, it is important to be aware that 

policy options for halocarbon ODSs and for N2O will be made against a backdrop of potentially large 

ozone changes due to CO2 and CH4. The effects on ozone due to increasing CO2 and CH4 are discussed in 

detail in Chapter 2; a summary of the important mechanisms and ozone responses is provided here.

Figure 5-5. Comparison of EESC calculated from 

halocarbons alone using the midlatitude baseline 

scenario (Halocarbon), and with the addition of the 

N2O contribution (Halocarbon+N2O) using the formula 

from Daniel et al. (2010) for including N2O in EESC.

1950 2000 2050 2100

Year

0

500

1000

1500

2000

EESC

Halocarbon+N2O

Halocarbon
Chapter 5

5.36

For most of the scenarios examined, increases in ozone arising from CO2 and CH4 increases may 

be comparable to or larger than the additional depletion caused by N2O increases. This behavior can be 

seen from the 2-D model calculations of global total ozone using the RCP6.0 scenario shown in Figure 5-

4 (bottom). This illustrates the individual effects of future increases in CO2 (red line), CH4 (yellow line), 

and N2O (green line) in the presence of decreasing ODSs, and can be compared with the impact due to 

only the decreasing ODSs (in which the GHGs are all fixed at 2000 levels, blue line). As shown by 

comparing the red, yellow, and green lines with the blue line in Figure 5-4, increasing CO2 leads to a 

substantial global ozone increase by 2100 (+2% relative to 1950) primarily due to stratospheric cooling,

which reduces the ozone chemical loss rates (Haigh and Pyle, 1979). Note that these results are for global 

ozone and that more localized changes may differ (see below and Chapter 2). Another factor is that future 

CO2-induced stratospheric changes will indirectly affect ozone by somewhat mitigating the ozone 

depletion caused by N2O (see Box 5-2 and Section 2.4.3.1).

Compared to CO2, methane loading leads to a smaller global total ozone increase (yellow line in 

Figure 5-4, bottom). CH4 causes ozone to increase by: 1) mitigation of the chlorine-ozone loss cycles in 

the stratosphere, and 2) enhanced NOx-induced ozone production in the troposphere and lowermost 

stratosphere following CH4 oxidation (Brasseur and Solomon, 2005, and see Section 2.4.3.1). For total 

column ozone, these processes dominate the ozone reductions caused by the CH4-enhanced HOx-ozone 

loss cycles that are important primarily in the upper stratosphere (Revell et al., 2012). The slight decline 

of the CH4-induced total ozone change during the late 21st century in Figure 5-4 is caused by the decrease 

in methane in the RCP6.0 scenario. As atmospheric chlorine levels decline through the 21st century, future 

methane-induced changes in total ozone will be increasingly determined by the NOx-ozone production 

cycle in the troposphere and lowermost stratosphere. The large range in CH4 among the RCP scenarios, 

mainly due to the very high methane of RCP8.5 (Section 2.4.3.2), is projected to produce a large range of 

future tropospheric ozone responses. For example, in 2100, CH4 increases of 1.9–2.0 ppm (approximately 

the increase from present day to 2100 in RCP8.5) are projected to increase tropospheric column ozone by 

3.5–5 DU (10–13%) (Brasseur et al., 2006; Kawase et al., 2011). 

The baseline scenario, with all ODS and GHG effects included, gives an ozone level in 2100 that 

is slightly less (by 1 DU) than in 1960 (Figure 5-4, black line). This is generally similar to the CMIP5 

CHEM multi-model mean for the RCP6.0 scenario, in which stratospheric column ozone is 4 DU less in 

2100 than 1960 (Eyring et al., 2013, see also Section 2.4.1). Scenarios with higher levels of CO2 and CH4

may cause ozone to obtain higher globally averaged levels than historically observed despite the fact that 

N2O levels contribute several DU of ozone depletion by 2100. This is seen in the CMIP5 multi-model 

mean for the RCP8.5 scenario, in which global stratospheric column ozone in 2100 is greater (by 2 DU) 

than in 1960 (Eyring et al., 2013). Also, the Special Report on Emissions Scenarios (SRES) A1B 

(medium) scenario used in the CCMVal-2 simulations (also used in WMO (2011) and Section 2.4.1 of 

this Assessment) had higher levels of CO2 and CH4, and lower N2O compared with RCP6.0; these factors 

all contribute to higher global ozone (by ~5 DU) in the A1B scenario during the mid to late 21st century 

(compare baseline simulations in Figure 2-24 (A1B) and Figure 5-4 (RCP6.0) which are from the same 

model). However, the ozone response to GHG forcing will likely differ in altitude and region. For 

example, the CO2-driven enhancement of the stratospheric circulation will increase lower stratospheric 

ozone at middle to high latitudes (Li et al., 2009). While global and midlatitude ozone may rise above 

historical levels, the CO2-driven circulation enhancement may lead to ozone decreases in the tropical 

lower stratosphere after 2050, as seen in the CCMVal-2 and CMIP5 simulations for different GHG 

scenarios (SPARC CCMVal, 2010; Eyring et al., 2013; see also Sections 2.3.5 and 2.4.1).

It is sometimes argued that the future projected “super-recovery” of stratospheric ozone, which 

can occur under certain scenarios of CO2 and CH4 future increased abundances, is a reason to not be 

concerned about increasing N2O. Scientifically however, it is clear that N2O increases in the future will 

lead to lower ozone levels (greater depletion) than if anthropogenic N2O emissions were mitigated. 

Depending on the particular CO2/CH4/N2O scenario, this may mean that levels of global total ozone 

before intervention from human emissions will never be attained again, or that there will be a delay in 

reaching those levels.
Scenarios and Information for Policymakers

5.37

5.4.4 Radiative Forcing on Climate

Figure 5-6 shows the impacts of the various mitigation scenarios on the radiative forcing on 

climate from the ODS halocarbons. These curves represent the same scenarios as were shown in Figure 5-

3 for their impacts on EESC. The relative shapes and positions of the various scenarios are similar to their 

EESC contributions. It is currently projected that ODS halocarbon climate forcing will decline from its 

current peak of 0.33 W m-2 to close to 0.1 W m-2 by 2100, with little dependence on the particular 

scenario because of controls already adopted under the Montreal Protocol. In the next few decades, the 

particular scenario can make a somewhat larger impact on radiative forcing reductions compared with the 

baseline scenario. One of the consequences of the controls on ODSs is that HFCs, climate forcing agents 

themselves, have become prevalent replacement compounds. These are discussed in the next section.

Velders and Daniel (2014) have quantified the RF uncertainties for a scenario very similar to the baseline 

scenario considered here. They considered uncertainties in a wide variety of factors that go into 

estimating past and future concentrations, as well 

as a 5% uncertainty in the radiative efficiency of 

each compound. That analysis suggests a 2-σ

uncertainty of about ±0.02 W m-2 from the present 

through 2100, when considering the “most likely” 

range of lifetimes. This uncertainty is controlled 

primarily by the radiative efficiency uncertainty in 

the past and current time, while lifetime uncertainties dominate further in the future.

Figure 5-6. Time series of historical and projected 

radiative forcing from long-lived ODS halocarbons. 

The radiative forcing projections for the primary 

mitigation scenarios considered in this Assessment are also shown.

Figure 5-7 shows the derived direct radiative forcing on climate from 2010 to 2050 due to ODSs

and other compounds (note that there would be additional indirect forcing due to effects on ozone). The 

top panel shows the RF due to CFCs and HCFCs to 2050 based on assuming the emissions follow the 

Montreal Protocol (RF values from Annex II of IPCC, 2013). 

The second panel shows the RF for HFCs under various assumptions and demonstrates that 

increasing RF from HFCs could essentially compensate (or more than compensate) for the decrease in RF 

from ODSs. The RF curves for HFCs for the RCP scenarios are based on IPCC (2013); these scenarios 

give lower RFs than those from Velders et al. (2009). Another scenario projecting HFCs growth is taken 

from Gschrey et al. (2011), which used various sources of information, including the Gross Domestic 

Product (GDP) and population data underlying the SRES scenarios (IPCC, 2000). Much larger RFs are 

given in the High and Low scenarios from Velders et al. (2009), which were also based on GDP and 

population data underlying the SRES scenarios, plus other information, including: the rapid observed 

growth in demand, substantiated by atmospheric observations; information about products and equipment 

using HCFCs and HFCs in developing countries; reported increases in consumption of HCFCs in 

developing countries; replacement patterns of HCFCs by HFCs as reported in developed countries; 

accelerated phase-out schedules of HCFCs in developed and developing countries; and increases in 

reported use of HFC-134a in mobile air conditioning in developed and developing countries. The Velders 

et al. (2009) High scenario describes what happens if the developing world follows the same path in 

transitioning from CFCs and HCFCs to HFCs (and not-in-kind alternatives) as we have seen in the 

developed world in the past decade (up to 2009). This in combination with large population and economic

1960 1980 2000 2020 2040 2060 2080 2100

Year

0.0

0.1

0.2

0.3

0.4

Radiative Forcing (W/m2

)

Current Baseline

No Future Emissions

Zero 2015 Bank

Zero 2020 Bank

No Future Production
Chapter 5

5.38

Figure 5-7. Radiative forcing (given 

as Effective RF) projections for CFCs 

and HCFCs (following the Montreal 

Protocol) and the degree to which 

these decreases might be offset by 

HFC and N2O increases. Except for 

some of the HFC scenarios, the 

values are based on the scenarios 

used in Annex II of IPCC (2013). The 

HFC scenarios represent a range of 

assumptions and calculations (e.g., 

see Velders et al. 2009; Gschrey et 

al., 2011). The Velders et al. A1 and 

A2 scenarios correspond to the high 

and low scenarios, respectively, used 

in Figure 5-8.

growth result in a larger RF for HFCs. 

If more alternative (low GWP) technologies get a larger market, share the 

contributions of HFCs to RF will be 

smaller than in this scenario. 

The bottom panel shows the 

projected growth in RF from N2O 

based on the RCP6.0 scenario from 

IPCC (2013). The increase in N2O 

concentration for this scenario results 

in a direct increase in RF of about 

0.09 W m-2 by 2050 relative to 2010

(from 0.17 to 0.26 W m-2). This is 

smaller than, but comparable to, the decrease in RF from ODSs over this time period. By comparison the RF 

changes for CO2 and CH4 for the same scenario over this time period are 1.1 (from 1.8 to 2.9) and 0.05 

(from 0.48 to 0.53) W m-2, respectively.

5.4.5 Replacements for High-GWP HFCs

The special report on HFCs by UNEP (2011) found that the climate benefits of the Montreal 

Protocol could be offset by future increases in the use of the HFCs with longer lifetimes and higher GWPs 

(those with GWP 100-year values greater than 1000, e.g., including HFC-134a, -143a, and -125). While 

HFCs are not currently a significant contributor to radiative forcing on climate, they could become 

important within the next few decades if no action is taken. Switching away from the use of such higherGWP HFCs to alternatives with much lower GWPs could effectively reduce the effects of halocarbons on 

climate by 2050. In WMO (2011), a set of different scenarios was considered based on Velders et al. (2009, 

2012) that show the phase-out of the higher-GWP HFCs could be an important contributor to reducing 

future radiative forcing. The analyses can be taken a step further (Wuebbles et al., 2013) by examining a 

realistic mix of compounds for replacing the uses of the higher-GWP HFCs. As stated in the previous section, 

the Velders et al. studies assumed growth in HFC use is much larger than in the IPCC (2013) analyses.

Various unsaturated halogenated hydrocarbons with very short atmospheric lifetimes have been 

recently proposed as substitutes for HCFCs (which are now being phased out under the Montreal 

Protocol) and longer-lived HFCs. These short-lived substances are expected to have extremely small

effects on tropospheric and stratospheric ozone and on climate. Among the possible replacement chemical 
Scenarios and Information for Policymakers

5.39

compounds are (E)-CHCl=CHCF3 (tCFP or HFO-1233zd; included in the ODP analyses in Table 5-3) and 

at least six possible HFOs: 2,3,3,3-tetrafluoropropene (CF3CF=CH2, HFO-1234yf); (E)-1,3,3,3-

tetrafluoropropene ((E)-CHF=CHCF3, HFO-1234ze(E)); (Z)-1,3,3,3-tetrafluoropropene ((Z)-CHF=CHCF3, 

HFO-1234ze(Z)); (Z)-1,2,3,3,3-pentafluoropropene ((Z)-CF3CF=CHF, HFO-1225ye(Z)); (E)-1,2,3,3,3-

pentafluoropropene ((E)-CF3CF=CHF, HFO-1225ye(E)); and (Z)-1,1,1,4,4,4-hexafluoro-2-butene ((Z)-

CF3CH=CHCF3, HFO-1336mzz-Z). In the possible uses, HFO-1234yf can serve as a mobile air 

conditioning refrigerant; HFO-1234ze(E) can be used as a blowing agent and propellant; HFO-1233zd

and HFO-1336mzz-Z can serve as blowing agents; HFO-1234ze(Z) has been suggested as a refrigerant 

(Brown et al., 2009); HFO-1225ye(Z) and -1225ye(E) have been also proposed as refrigerants (Hurley et 

al., 2007). The prospect of using HFO-1234yf and HFO-1234ze(E) has been discussed in the literature 

(UNEP, 2011; Velders et al., 2012). Three-dimensional modeling analyses by Wuebbles et al. (2013) 

show HFO-1233zd to have an atmospheric lifetime (for realistic locations of emissions) of 30.5 days, 

while the HFOs have lifetimes ranging from 9.2 days for HFO-1225ye to 17.3 days for HFO-1234ze. The 

100-year GWPs range from 0.9 to 4.7 for these six compounds, assuming emissions occur spatially 

corresponding to current uses of HFCs (Wuebbles et al., 2013).

Scenarios for replacing HFCs with the low-GWP alternatives are developed in Wuebbles et al. 

(2013) based on the demand for such compounds (e.g., see Velders et al., 2009) with the assumptions that 

(i) production and consumption of HFCs decrease linearly starting in 2015; (ii) production and 

consumption of HFC-32, -125, -143a, -245fa, and -365mfc decrease to zero in 2035; (iii) production and 

consumption of HFC-134a decrease to zero in 2025; (iv) the demand for refrigerants from use of HFC-32, 

-125, -134a, and -143a is replaced by HFO-1234yf, -1234ze(Z), -1225ye(Z), or -1225ye(E) on a per mass 

basis; (v) the demand for blowing agents from the use of HFC-152a, -245fa, and -365mfc is replaced by 

HFO-1234ze(E), or HFO-1233zd on a per mass basis. With these assumptions, the red lines in Figure 5-8

show the radiative forcing of the low-GWP alternatives in 2050 is between 0.00026 and 0.00080 W m-2. 

As a result, radiative forcing resulting from future requirements for refrigerants and blowing agents is 

significantly reduced. In contrast, the monotonically increasing radiative forcing of long-lived HFCs (the 

black lines in Figure 5-8 for low and high HFC growth scenarios from Velders et al., 2009) reaches 0.25 to 

0.40 W m-2 in 2050. The blue lines in Figure 5-8 show the radiative forcing of the long-lived HFCs for 

scenarios transitioning to low-GWP alternatives; the HFC radiative forcing for this assumption peaks at 

0.046 to 0.053 W m-2 near 2030 and decreases to 0.026 to 0.031 W m-2 in 2050. The resulting reduction in 

radiative forcing on climate in 2030 is significant, between 0.04 and 0.07 W m-2 (Wuebbles et al., 2013), 

comparable to the savings of the regulatory black carbon reduction measures, or a sizable fraction of the 

savings of the technological black carbon reduction measures and CH4 reduction measures recently 

suggested (Shindell et al., 2012). By 2050, Figure 5-8 shows that the savings could be as large as 0.37 W

m-2. Comparably, a recent study by Rigby et al. (2014) suggests that reducing HFC use under the Montreal 

Protocol could reduce radiative forcing in 

2050 by 0.05 to 0.24 W m-2. Some fraction 

of the replacements could possibly be not-inkind gases, leading to the possibility for even 

more reduction in radiative forcing (if those 

replacements are not greenhouse gases).

Figure 5-8. Radiative forcing (in W m-2) from 

2010–2050 for various scenarios of future HFC 

usage: high-GWP HFC scenario (Velders et 

al., 2009; black lines); scenarios for transitioning long-lived high-GWP HFCs to lowGWP alternatives (based on Wuebbles et al., 

2013; blue lines) and low-GWP replacement 

scenarios based on the use of low-GWP

alternative compounds (based on Wuebbles 

et al., 2013; red lines).
Chapter 5

5.40

Radiative forcing of HFCs would soon be less than that of today if the current mix of HFCs 

(mean lifetime ~15 yrs) were hypothetically to be entirely replaced within the next few years by a mix of 

replacements with lifetimes less than 1 month (Velders et al., 2012) but such a rapid transition may be 

difficult, if not unrealistic. Assuming the slower transition process, the blue lines in Figure 5-8, the 

radiative forcing due to long-lived HFCs emitted would essentially be the only remaining meaningful 

direct climate forcing contribution due to the chemicals used in refrigeration and blowing agents. 

Nonetheless, the quicker the long-lived HFCs are phased out, the less radiative forcing there would be.

Because the applications using HFCs are, in general, less emissive than were those of the CFCs at 

the same stage, the amount of HFCs stored in existing applications (banks) is projected to be a much larger 

fraction of annual production (or cumulative production) than was the case for CFCs. As a result, there is an 

additional future commitment to climate change from HFC banks that would not be apparent if only 

radiative forcing for a given period is analyzed (Velders et al., 2014). By 2050, HFC banks are estimated to 

grow to 40 and 65 GtCO2-eq in the high and low scenarios from Velders et al. (2009). In both cases, these 

bank sizes are approximately 25% of the cumulative production through 2050. Figure 5-9 shows the 

cumulative production and emissions and their comparisons with the bank sizes for the two scenarios from 

Velders et al. (2009). While the emissions and forcing from these scenarios are higher than for other 

published projections, the larger relative importance of the banks compared with the historical CFC situation 

should hold for all reasonable HFC scenarios. The implication is that earlier phase-outs of HFC production 

may play a somewhat larger role in mitigating climate forcing than previous estimates have suggested.

Figure 5-9. Projected growth of HFC 

production, emissions, and banks for two 

future scenarios (Velders et al., 2014). 

Figures show the magnitude of the 

future banks relative to cumulate 

emissions and production. For example, 

a phase-out of production in 2020 rather 

than 2030 would lead to a production 

decrease of 27–42 GtCO2-eq, of which 

8–15 GtCO2 would have remained in 

banks at the end of that decade and 19–

27 GtCO2-eq would have been emitted 

to the atmosphere during that decade.

higher scenario

lower scenario
Scenarios and Information for Policymakers

5.41

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Scenarios and Information for Policymakers

5.49

APPENDIX 5A

5A-1. ANALYSES OF GWPs AND GTPs

Table 5A-1. Atmospheric lifetimes / adjustment times, radiative efficiencies (RE), and GWP values for 20 and 100 years, and GTP values 

for 20, 50 and 100 years (from IPCC, 2013). Climate-carbon feedbacks are included for CO2 while no climate feedbacks are included for the 

other components (see IPCC (2013) for further details). The derivation of GTP assumes a climate sensitivity of 1.06 K (W m-2)

-1

, equivalent to a 

3.9 K equilibrium response to 2 x CO2, toward the higher end of the uncertainty in climate sensitivity. For a complete list of chemical names and 

Chemical Abstracts Service (CAS) numbers, and for accurate replications of metric values, plus further details on the specific values used, see 

Supplementary Material Section S8.13 and references therein in IPCC (2013). Also see Hodnebrog et al. (2013) for analyses of radiative 

efficiencies for the halocarbons and related compounds.

Industrial Designation or 

Chemical Name Chemical Formula Lifetime(years)

Radiative 

Efficiency

(W m-2 ppb-1)

GWP

20-yr

GWP

100-yr

GTP

20-yr

GTP

50-yr

GTP

100-yr

Carbon dioxide CO2 See * 1.37e-5 1 1 1 1 1

Methane CH4 12.4 + 3.63e-4 84 28 67 14 4

Fossil methane # CH4 12.4 + 3.63e-4 85 30 68 15 6

Nitrous oxide N2O 121 + 3.00e-3 264 265 277 282 234

Chlorofluorocarbons

CFC-11 CCl3F 45.0 0.26 6,900 4,660 6,890 4,890 2,340

CFC-12 CCl2F2 100.0 0.32 10,800 10,200 11,300 11,000 8,450

CFC-13 CClF3 640.0 0.25 10,900 13,900 11,700 14,200 15,900

CFC-113 CCl2FCClF2 85.0 0.30 6,490 5,820 6,730 6,250 4,470

CFC-114 CClF2CClF2 190.0 0.31 7,710 8,590 8,190 9,020 8,550

CFC-115 CClF2CF3 1,020.0 0.20 5,860 7,670 6,310 7,810 8,980

Hydrochlorofluorocarbons

HCFC-21 CHCl2F 1.7 0.15 543 148 192 26 20

HCFC-22 CHClF2 11.9 0.21 5,280 1,760 4,200 832 262

HCFC-122 CHCl2CF2Cl 1.0 0.17 218 59 70 10 8

HCFC-122a CHFClCFCl2 3.4 0.21 945 258 426 48 36

HCFC-123 CHCl2CF3 1.3 0.15 292 79 98 14 11

HCFC-123a CHClFCF2Cl 4.0 0.23 1,350 370 659 72 51

HCFC-124 CHClFCF3 5.9 0.20 1,870 527 1,120 121 74
Chapter 5

5.50

Industrial Designation or 

Chemical Name Chemical Formula Lifetime(years)

Radiative 

Efficiency

(W m-2 ppb-1)

GWP

20-yr

GWP

100-yr

GTP

20-yr

GTP

50-yr

GTP

100-yr

HCFC-132c CH2FCFCl2 4.3 0.17 1,230 338 624 67 47

HCFC-141b CH3CCl2F 9.2 0.16 2,550 782 1,850 271 111

HCFC-142b CH3CClF2 17.2 0.19 5,020 1,980 4,390 1,370 356

HCFC-225ca CHCl2CF2CF3 1.9 0.22 469 127 170 22 18

HCFC-225cb CHClFCF2CClF2 5.9 0.29 1,860 525 1,110 120 73

(E)-1-Chloro-3,3,3-trifluoroprop-1-

ene

trans-CF3CH=CHCl 26.0 days 0.04 5 1 2 <1 <1

Hydrofluorocarbons

HFC-23 CHF3 222.0 0.18 10,800 12,400 11,500 13,000 12,700

HFC-32 CH2F2 5.2 0.11 2,430 677 1,360 145 94

HFC-41 CH3F 2.8 0.02 427 116 177 21 16

HFC-125 CHF2CF3 28.2 0.23 6,090 3,170 5,800 2,980 967

HFC-134 CHF2CHF2 9.7 0.19 3,580 1,120 2,660 412 160

HFC-134a CH2FCF3 13.4 0.16 3,710 1,300 3,050 703 201

HFC-143 CH2FCHF2 3.5 0.13 1,200 328 549 62 46

HFC-143a CH3CF3 47.1 0.16 6,940 4,800 6,960 5,060 2,500

HFC-152 CH2FCH2F 0.4 0.04 60 16 18 3 2

HFC-152a CH3CHF2 1.5 0.10 506 138 174 24 19

HFC-161 CH3CH2F 66.0 days 0.02 13 4 4 <1 <1

HFC-227ca CF3CF2CHF2 28.2 0.27 5,080 2,640 4,830 2,480 806

HFC-227ea CF3CHFCF3 38.9 0.26 5,360 3,350 5,280 3,440 1,460

HFC-236cb CH2FCF2CF3 13.1 0.23 3,480 1,210 2,840 636 185

HFC-236ea CHF2CHFCF3 11.0 0.30 4,110 1,330 3,190 573 195

HFC-236fa CF3CH2CF3 242.0 0.24 6,940 8,060 7,400 8,400 8,380

HFC-245ca CH2FCF2CHF2 6.5 0.24 2,510 716 1,570 176 100

HFC-245cb CF3CF2CH3 47.1 0.24 6,680 4,620 6,690 4,870 2,410

HFC-245ea CHF2CHFCHF2 3.2 0.16 863 235 378 44 33

HFC-245eb CH2FCHFCF3 3.1 0.20 1,070 290 460 54 40

HFC-245fa CHF2CH2CF3 7.7 0.24 2,920 858 1,970 245 121

HFC-263fb CH3CH2CF3 1.2 0.10 278 76 92 13 10

HFC-272ca CH3CF2CH3 2.6 0.07 530 144 213 26 20

HFC-329p CHF2CF2CF2CF3 28.4 0.31 4,510 2,360 4,290 2,220 725

HFC-365mfc CH3CF2CH2CF3 8.7 0.22 2,660 804 1,890 262 114

HFC-43-10mee CF3CHFCHFCF2CF3 16.1 0.42 4,310 1,650 3,720 1,070 281

HFC-1132a CH2=CF2 4.0 days 0.004 <1 <1 <1 <1 <1

HFC-1141 CH2=CHF 2.1 days 0.002 <1 <1 <1 <1 <1

(Z)-HFC-1225ye CF3CF=CHF(Z) 8.5 days 0.02 <1 <1 <1 <1 <1
Scenarios and Information for Policymakers

5.51

Industrial Designation or 

Chemical Name Chemical Formula Lifetime(years)

Radiative 

Efficiency

(W m-2 ppb-1)

GWP

20-yr

GWP

100-yr

GTP

20-yr

GTP

50-yr

GTP

100-yr

(E)-HFC-1225ye CF3CF=CHF(E) 4.9 days 0.01 <1 <1 <1 <1 <1

(Z)-HFC-1234ze CF3CH=CHF(Z) 10.0 days 0.02 1 <1 <1 <1 <1

HFC-1234yf CF3CF=CH2 10.5 days 0.02 1 <1 <1 <1 <1

(E)-HFC-1234ze trans-CF3CH=CHF 16.4 days 0.04 4 <1 <1 <1 <1

(Z)-HFC-1336 CF3CH=CHCF3(Z) 22.0 days 0.07 6 2 2 <1 <1

HFC-1243zf CF3CH=CH2 7.0 days 0.01 <1 <1 <1 <1 <1

HFC-1345zfc C2F5CH=CH2 7.6 days 0.01 <1 <1 <1 <1 <1

3,3,4,4,5,5,6,6,6-Nonafluorohex-1-

ene

C4F9CH=CH2 7.6 days 0.03 <1 <1 <1 <1 <1

3,3,4,4,5,5,6,6,7,7,8,8,8-

Tridecafluorooct-1-ene

C6F13CH=CH2 7.6 days 0.03 <1 <1 <1 <1 <1

3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,10-

Heptadecafluorodec-1-ene

C8F17CH=CH2 7.6 days 0.03 <1 <1 <1 <1 <1

Chlorocarbons and 

Hydrochlorocarbons

Methyl chloroform CH3CCl3 5.0 0.07 578 160 317 34 22

Carbon tetrachloride CCl4 26.0 0.17 3,480 1,730 3,280 1,570 479

Methyl chloride CH3Cl 1.0 0.01 45 12 15 2 2

Methylene chloride CH2Cl2 0.4 0.03 33 9 10 2 1

Chloroform CHCl3 0.4 0.08 60 16 18 3 2

1,2-Dichloroethane CH2ClCH2Cl 65.0 days 0.01 3 <1 <1 <1 <1

Bromocarbons, 

Hydrobromocarbons and Halons

Methyl bromide CH3Br 0.8 0.004 9 2 3 <1 <1

Methylene bromide CH2Br2 0.3 0.01 4 1 1 <1 <1

Halon-1201 CHBrF2 5.2 0.15 1,350 376 756 80 52

Halon-1202 CBr2F2 2.9 0.27 848 231 356 42 32

Halon-1211 CBrClF2 16.0 0.29 4,590 1,750 3,950 1,130 297

Halon-1301 CBrF3 65.0 0.30 7,800 6,290 7,990 6,750 4,170

Halon-2301 CH2BrCF3 3.4 0.14 635 173 286 33 24

Halon-2311 / Halothane CHBrClCF3 1.0 0.13 151 41 49 7 6

Halon-2401 CHFBrCF3 2.9 0.19 674 184 283 34 25

Halon-2402 CBrF2CBrF2 20.0 0.31 3,440 1,470 3,100 1,150 304

Fully Fluorinated Species

Nitrogen trifluoride NF3 500.0 0.20 12,800 16,100 13,700 16,500 18,100

Sulphur hexafluoride SF6 3,200.0 0.57 17,500 23,500 18,900 23,800 28,200
Chapter 5

5.52

Industrial Designation or 

Chemical Name Chemical Formula Lifetime(years)

Radiative 

Efficiency

(W m-2 ppb-1)

GWP

20-yr

GWP

100-yr

GTP

20-yr

GTP

50-yr

GTP

100-yr

(Trifluoromethyl)sulfur 

pentafluoride SF5CF3 800.0 0.59 13,500 17,400 14,500 17,800 20,200

Sulfuryl fluoride SO2F2 36.0 0.20 6,840 4,090 6,690 4,140 1,650

PFC-14 CF4 50,000.0 0.09 4,880 6,630 5,270 6,690 8,040

PFC-116 C2F6 10,000.0 0.25 8,210 11,100 8,880 11,200 13,500

PFC-c216 c-C3F6 3,000.0 0.23 6,850 9,200 7,400 9,310 11,000

PFC-218 C3F8 2,600.0 0.28 6,640 8,900 7,180 9,010 10,700

PFC-318 c-C4F8 3,200.0 0.32 7,110 9,540 7,680 9,660 11,500

PFC-31-10 C4F10 2,600.0 0.36 6,870 9,200 7,420 9,320 11,000

Perfluorocyclopentene c-C5F8 31.0 days 0.08 7 2 2 <1 <1

PFC-41-12 n-C5F12 4,100.0 0.41 6,350 8,550 6,860 8,650 10,300

PFC-51-14 n-C6F14 3,100.0 0.44 5,890 7,910 6,370 8,010 9,490

PFC-61-16 n-C7F16 3,000.0 0.50 5,830 7,820 6,290 7,920 9,380

PFC-71-18 C8F18 3,000.0 0.55 5,680 7,620 6,130 7,710 9,140

PFC-91-18 C10F18 2,000.0 0.55 5,390 7,190 5,820 7,290 8,570

Perfluorodecalin (Z) (Z)-C10F18 2,000.0 0.56 5,430 7,240 5,860 7,340 8,630

Perfluorodecalin (E) (E)-C10F18 2,000.0 0.48 4,720 6,290 5,090 6,380 7,500

PFC-1114 CF2=CF2 1.1 days 0.002 <1 <1 <1 <1 <1

PFC-1216 CF3CF=CF2 4.9 days 0.01 <1 <1 <1 <1 <1

Perfluorobuta-1,3-diene CF2=CFCF=CF2 1.1 days 0.003 <1 <1 <1 <1 <1

Perfluorobut-1-ene CF3CF2CF=CF2 6.0 days 0.02 <1 <1 <1 <1 <1

Perfluorobut-2-ene CF3CF=CFCF3 31.0 days 0.07 6 2 2 <1 <1

Halogenated Alcohols and Ethers

HFE-125 CHF2OCF3 119.0 0.41 12,400 12,400 13,000 13,200 10,900

HFE-134 (HG-00) CHF2OCHF2 24.4 0.44 11,600 5,560 10,800 4,900 1,430

HFE-143a CH3OCF3 4.8 0.18 1,890 523 1,020 108 73

HFE-227ea CF3CHFOCF3 51.6 0.44 8,900 6,450 8,980 6,850 3,630

HCFE-235ca2 (enflurane) CHF2OCF2CHFCl 4.3 0.41 2,120 583 1,080 116 81

HCFE-235da2 (isoflurane) CHF2OCHClCF3 3.5 0.42 1,800 491 822 93 68

HFE-236ca CHF2OCF2CHF2 20.8 0.56 9,710 4,240 8,820 3,400 912

HFE-236ea2 (desflurane) CHF2OCHFCF3 10.8 0.45 5,550 1,790 4,280 753 260

HFE-236fa CF3CH2OCF3 7.5 0.36 3,350 979 2,240 273 138

HFE-245cb2 CF3CF2OCH3 4.9 0.33 2,360 654 1,280 136 91

HFE-245fa1 CHF2CH2OCF3 6.6 0.31 2,900 828 1,820 206 116

HFE-245fa2 CHF2OCH2CF3 5.5 0.36 2,910 812 1,670 179 114

2,2,3,3,3-Pentafluoropropan-1-ol CF3CF2CH2OH 0.3 0.14 69 19 21 3 3

HFE-254cb1 CH3OCF2CHF2 2.5 0.26 1,110 301 438 54 42
Scenarios and Information for Policymakers

5.53

Industrial Designation or 

Chemical Name Chemical Formula Lifetime(years)

Radiative 

Efficiency

(W m-2 ppb-1)

GWP

20-yr

GWP

100-yr

GTP

20-yr

GTP

50-yr

GTP

100-yr

HFE-263fb2 CF3CH2OCH3 23.0 days 0.04 5 1 1 0 0

HFE-263m1 CF3OCH2CH3 0.4 0.13 108 29 33 5 4

3,3,3-Trifluoropropan-1-ol CF3CH2CH2OH 12.0 days 0.02 1 0 0 0 0

HFE-329mcc2 CHF2CF2OCF2CF3 22.5 0.53 6,720 3,070 6,180 2,580 718

HFE-338mmz1 (CF3)2CHOCHF2 21.2 0.44 5,940 2,620 5,410 2,130 575

HFE-338mcf2 CF3CH2OCF2CF3 7.5 0.44 3,180 929 2,120 259 131

Sevoflurane (HFE-347mmz1) (CF3)2CHOCH2F 2.2 0.32 795 216 302 38 30

HFE-347mcc3 (HFE-7000) CH3OCF2CF2CF3 5.0 0.35 1,910 530 1,050 111 74

HFE-347mcf2 CHF2CH2OCF2CF3 6.6 0.42 2,990 854 1,880 212 120

HFE-347pcf2 CHF2CF2OCH2CF3 6.0 0.48 3,150 889 1,900 206 124

HFE-347mmy1 (CF3)2CFOCH3 3.7 0.32 1,330 363 624 69 51

HFE-356mec3 CH3OCF2CHFCF3 3.8 0.30 1,410 387 673 74 54

HFE-356mff2 CF3CH2OCH2CF3 105.0 days 0.17 62 17 18 3 2

HFE-356pcf2 CHF2CH2OCF2CHF2 5.7 0.37 2,560 719 1,500 162 101

HFE-356pcf3 CHF2OCH2CF2CHF2 3.5 0.38 1,640 446 747 84 62

HFE-356pcc3 CH3OCF2CF2CHF2 3.8 0.32 1,510 413 718 79 57

HFE-356mmz1 (CF3)2CHOCH3 97.1 days 0.15 50 14 15 2 2

HFE-365mcf3 CF3CF2CH2OCH3 19.3 days 0.05 3 <1 <1 <1 <1

HFE-365mcf2 CF3CF2OCH2CH3 0.6 0.26 215 58 66 10 8

HFE-374pc2 CHF2CF2OCH2CH3 5.0 0.30 2,260 627 1,240 132 88

4,4,4-Trifluorobutan-1-ol CF3(CH2)2CH2OH 4.0 days 0.01 <1 <1 <1 <1 <1

2,2,3,3,4,4,5,5-

Octafluorocyclopentanol -(CF2)4CH(OH)- 0.3 0.16 47 13 14 2 2

HFE-43-10pccc124 (H-Galden 

1040x, HG-11) CHF2OCF2OC2F4OCHF2 13.5 1.02 8,010 2,820 6,600 1,530 436

HFE-449s1 (HFE-7100) C4F9OCH3 4.7 0.36 1,530 421 809 86 59

n-HFE-7100 n-C4F9OCH3 4.7 0.42 1,760 486 934 99 68

i-HFE-7100 i-C4F9OCH3 4.7 0.35 1,480 407 783 83 57

HFE-569sf2 (HFE-7200) C4F9OC2H5 0.8 0.30 209 57 66 10 8

n-HFE-7200 n-C4F9OC2H5 0.8 0.35 237 65 75 11 9

i-HFE-7200 i-C4F9OC2H5 0.8 0.24 163 44 52 8 6

HFE-236ca12 (HG-10) CHF2OCF2OCHF2 25.0 0.65 11,000 5,350 10,300 4,770 1,420

HFE-338pcc13 (HG-01) CHF2OCF2CF2OCHF2 12.9 0.86 8,430 2,910 6,860 1,500 442

1,1,1,3,3,3-Hexafluoropropan-2-ol (CF3)2CHOH 1.9 0.26 668 182 243 32 25

HG-02 HF2C–(OCF2CF2)2–

OCF2H 12.9 1.24 7,900 2,730 6,430 1,410 415
Chapter 5

5.54

Industrial Designation or 

Chemical Name Chemical Formula Lifetime(years)

Radiative 

Efficiency

(W m-2 ppb-1)

GWP

20-yr

GWP

100-yr

GTP

20-yr

GTP

50-yr

GTP

100-yr

HG-03 HF2C–(OCF2CF2)3–

OCF2H 12.9 1.76 8,270 2,850 6,730 1,480 434

HG-20 HF2C–(OCF2)2–OCF2H 25.0 0.92 10,900 5,300 10,200 4,730 1,400

HG-21

HF2C–

OCF2CF2OCF2OCF2O–

CF2H

13.5 1.71 11,100 3,890 9,110 2,120 602

HG-30 HF2C–(OCF2)3–OCF2H 25.0 1.65 15,100 7,330 14,100 6,530 1,940

1-Ethoxy-1,1,2,2,3,3,3-

heptafluoropropane CF3CF2CF2OCH2CH3 0.8 0.28 223 61 70 10 8

Fluoroxene CF3CH2OCH=CH2 3.6 days 0.01 <1 <1 <1 <1 <1

1,1,2,2-Tetrafluoro-1-

(fluoromethoxy)ethane CH2FOCF2CF2H 6.2 0.34 3,080 871 1,880 207 122

2-Ethoxy-3,3,4,4,5-

pentafluorotetrahydro-2,5-

bis[1,2,2,2-tetrafluoro-1-

(trifluoromethyl)ethyl]-furan

C12H5F19O2 1.0 0.49 204 56 66 10 8

Fluoro(methoxy)methane CH3OCH2F 73.0 days 0.07 46 13 14 2 2

Difluoro(methoxy)methane CH3OCHF2 1.1 0.17 528 144 173 25 20

Fluoro(fluoromethoxy)methane CH2FOCH2F 0.9 0.19 479 130 153 22 18

Difluoro(fluoromethoxy)methane CH2FOCHF2 3.3 0.30 2,260 617 1,010 115 86

Trifluoro(fluoromethoxy)methane CH2FOCF3 4.4 0.33 2,730 751 1,400 150 105

HG'-01 CH3OCF2CF2OCH3 2.0 0.29 815 222 301 39 31

HG'-02 CH3O(CF2CF2O)2CH3 2.0 0.56 868 236 320 42 33

HG'-03 CH3O(CF2CF2O)3CH3 2.0 0.76 812 221 299 39 31

HFE-329me3 CF3CFHCF2OCF3 40.0 0.48 7,170 4,550 7,090 4,690 2,040

3,3,4,4,5,5,6,6,7,7,7-

Undecafluoroheptan-1-ol CF3(CF2)4CH2CH2OH 20.0 days 0.06 2 <1 <1 <1 <1

3,3,4,4,5,5,6,6,7,7,8,8,9,9,9-

Pentadecafluorononan-1-ol CF3(CF2)6CH2CH2OH 20.0 days 0.07 1 <1 <1 <1 <1

3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,

11,11-Nonadecafluoroundecan-1-ol CF3(CF2)8CH2CH2OH 20.0 days 0.05 <1 <1 <1 <1 <1

2-Chloro-1,1,2-trifluoro-1-

methoxyethane CH3OCF2CHFCl 1.4 0.21 449 122 153 21 17

PFPMIE 

(perfluoropolymethylisopropyl 

ether)

CF3OCF(CF3)CF2OCF2OCF3 800.0 0.65 7,500 9,710 8,070 9,910 11,300

HFE-216 CF3OCF=CF2 8.4 days 0.02 <1 <1 <1 <1 <1
Scenarios and Information for Policymakers

5.55

Industrial Designation or 

Chemical Name Chemical Formula Lifetime(years)

Radiative 

Efficiency

(W m-2 ppb-1)

GWP

20-yr

GWP

100-yr

GTP

20-yr

GTP

50-yr

GTP

100-yr

Trifluoromethyl formate HCOOCF3 3.5 0.31 2,150 588 984 111 82

Perfluoroethyl formate HCOOCF2CF3 3.5 0.44 2,130 580 971 110 81

Perfluoropropyl formate HCOOCF2CF2CF3 2.6 0.50 1,380 376 555 68 52

Perfluorobutyl formate HCOOCF2CF2CF2CF3 3.0 0.56 1,440 392 613 72 54

2,2,2-Trifluoroethyl formate HCOOCH2CF3 0.4 0.16 123 33 37 6 5

3,3,3-Trifluoropropyl formate HCOOCH2CH2CF3 0.3 0.13 64 17 19 3 2

1,2,2,2-Tetrafluoroethyl formate HCOOCHFCF3 3.2 0.35 1,720 470 755 87 65

1,1,1,3,3,3-Hexafluoropropan-2-yl

formate HCOOCH(CF3)2 3.2 0.33 1,220 333 535 62 46

Perfluorobutyl acetate CH3COOCF2CF2CF2CF3 21.9 days 0.12 6 2 2 <1 <1

Perfluoropropyl acetate CH3COOCF2CF2CF3 21.9 days 0.11 6 2 2 <1 <1

Perfluoroethyl acetate CH3COOCF2CF3 21.9 days 0.10 8 2 2 <1 <1

Trifluoromethyl acetate CH3COOCF3 21.9 days 0.07 8 2 2 <1 <1

Methyl carbonofluoridate FCOOCH3 1.8 0.07 350 95 126 17 13

1,1-Difluoroethyl carbonofluoridate FCOOCF2CH3 0.3 0.17 99 27 30 5 4

1,1-Difluoroethyl 2,2,2-

trifluoroacetate CF3COOCF2CH3 0.3 0.27 113 31 34 5 4

Ethyl 2,2,2-trifluoroacetate CF3COOCH2CH3 21.9 days 0.05 5 1 1 <1 <1

2,2,2-Trifluoroethyl 2,2,2-

trifluoroacetate CF3COOCH2CF3 54.8 days 0.15 25 7 7 1 <1

Methyl 2,2,2-trifluoroacetate CF3COOCH3 0.6 0.18 192 52 60 9 7

Methyl 2,2-difluoroacetate HCF2COOCH3 40.1 days 0.05 12 3 4 <1 <1

Difluoromethyl 2,2,2-

trifluoroacetate CF3COOCHF2 0.3 0.24 99 27 30 5 4

2,2,3,3,4,4,4-Heptafluorobutan-1-ol C3F7CH2OH 0.6 0.20 124 34 38 6 5

1,1,2-Trifluoro-2-

(trifluoromethoxy)-ethane CHF2CHFOCF3 9.8 0.35 3,970 1,240 2,960 467 178

1-Ethoxy-1,1,2,3,3,3-

hexafluoropropane CF3CHFCF2OCH2CH3 0.4 0.19 86 23 26 4 3

1,1,1,2,2,3,3-Heptafluoro-3-

(1,2,2,2-tetrafluoroethoxy)-propane

CF3CF2CF2OCHFCF3 67.0 0.58 7,940 6,490 8,140 6,960 4,380

2,2,3,3-Tetrafluoro-1-propanol CHF2CF2CH2OH 91.2 days 0.11 48 13 14 2 2

2,2,3,4,4,4-Hexafluoro-1-butanol CF3CHFCF2CH2OH 94.9 days 0.19 63 17 19 3 2

2,2,3,3,4,4,4-Heptafluoro-1-butanol CF3CF2CF2CH2OH 0.3 0.16 60 16 18 3 2

1,1,2,2-Tetrafluoro-3-methoxypropane

CHF2CF2CH2OCH3 14.2 days 0.03 2 <1 <1 <1 <1

Perfluoro-2-methyl-3-pentanone CF3CF2C(O)CF(CF3)2 7.0 days 0.03 <1 <1 <1 <1 <1
Chapter 5

5.56

Industrial Designation or 

Chemical Name Chemical Formula Lifetime(years)

Radiative 

Efficiency

(W m-2 ppb-1)

GWP

20-yr

GWP

100-yr

GTP

20-yr

GTP

50-yr

GTP

100-yr

3,3,3-Trifluoro-propanal CF3CH2CHO 2.0 days 0.004 <1 <1 <1 <1 <1

2-Fluoroethanol CH2FCH2OH 20.4 days 0.02 3 <1 <1 <1 <1

2,2-Difluoroethanol CHF2CH2OH 40.0 days 0.04 11 3 3 <1 <1

2,2,2-Trifluoroethanol CF3CH2OH 0.3 0.10 73 20 22 3 3

1,1'-Oxybis[2-(difluoromethoxy)-

1,1,2,2-tetrafluoroethane HCF2O(CF2CF2O)2-CF2H 26.0 1.15 9,910 4,920 9,320 4,460 1,360

1,1,3,3,4,4,6,6,7,7,9,9,10,10,12,12-

Hexadecafluoro-2,5,8,11-

tetraoxadodecane

HCF2O(CF2CF2O)3-CF2H 26.0 1.43 9,050 4,490 8,520 4,080 1,250

1,1,3,3,4,4,6,6,7,7,9,9,10,10,12,12,1

3,13,15,15-Eicosafluoro2,5,8,11,14-pentaoxapentadecaneHCF2O(CF2CF2O)4-CF2H 26.0 1.46 7,320 3,630 6,880 3,300 1,010

For CH4 we estimate an uncertainty of ±30% and ±40% for 20- and 100-year time horizons, respectively (for 90% uncertainty range). The uncertainty is dominated by AGWP for 

CO2 and indirect effects. The uncertainty in GWP for N2O is estimated to be ±20% and ±30% for 20- and 100-year time horizons, with the largest contributions from CO2. The 

uncertainty in GWP for HFC-134a is estimated to be ±25% and ±35% for 20- and 100-year time horizons while for CFC-11, the GWP corresponding uncertainties are 

approximately ±20% and ±35% (not accounting for the indirect effects). For CFC-12 the corresponding numbers are ±20 and ±30. The uncertainties estimated for HFC-134a and 

CFC-11 are assessed as representative for most other gases with similar or longer lifetimes. For shorter-lived gases, the uncertainties will be larger. For GTP, few estimates are 

available in the literature. The uncertainty is assessed to be of the order of ±75% for the methane 100-year GTP.

* No single lifetime can be given. The impulse response function for CO2 from Joos et al. (2013) has been used. See also Supplementary Material Section S8.11 in IPCC (2013).

+ Perturbation lifetime is used in calculation of metrics; not the lifetime of the atmospheric burden. 

# Metric values for CH4 of fossil origin include the oxidation to CO2 (based on Boucher et al. (2009)). In applications of these values, inclusion of the CO2 effect of fossil methane 

must be done with caution to avoid any double counting, since CO2 emissions numbers are often based on total carbon content. For non-fossil CH4 we assume balance between 

CO2 taken up by the biosphere and CO2 produced from CH4 oxidation. 
Scenarios and Information for Policymakers

5.57

5A-2. BASELINE SCENARIO MIXING RATIOS

Table 5A-2. Mixing ratios (ppt) of the ODSs considered in the baseline (A1) scenario. Values are for the beginning of the corresponding year

(see Chapter 1). Potentially important short-lived gases that may currently contribute 5 (2–8) ppt of stratospheric bromine and 95 (50–145) ppt of 

stratospheric chlorine (see Chapter 1) are not shown in the table. Note: Areas are shaded for compounds in years when mixing ratio values are 

forced to equal global average estimates inferred from observations (see Chapter 1, Figure 1-1).

Year CFC-11 CFC-12

CFC113CFC114CFC115 CCl4 CH3CCl3 HCFC-22HCFC141bHCFC142bhalon1211halon1202halon1301halon2402 CH3Br CH3Cl

1955 3.3 14.3 1.3 2.6 0.0 42.3 0.1 1.0 0.0 0.0 0.00 0.00 0.00 0.00 6.3 491.3

1960 9.5 29.5 1.9 3.8 0.0 52.1 1.5 2.1 0.0 0.0 0.00 0.00 0.00 0.00 6.5 510.3

1965 23.5 58.8 3.1 5.0 0.0 64.4 4.7 4.9 0.0 0.0 0.00 0.00 0.00 0.00 6.7 528.1

1970 52.8 114.3 5.5 6.5 0.2 75.9 16.3 12.1 0.0 0.0 0.02 0.00 0.00 0.02 7.0 539.9

1975 106.1 203.1 10.4 8.3 0.6 85.5 40.0 23.8 0.0 0.2 0.12 0.01 0.04 0.06 7.4 545.8

1980 161.9 297.1 19.0 10.7 1.5 92.9 82.0 42.5 0.0 0.4 0.69 0.01 0.36 0.15 7.8 548.4

1981 170.5 312.1 21.5 11.1 1.7 94.3 89.0 46.6 0.0 0.5 0.81 0.01 0.43 0.17 7.9 548.6

1982 179.2 330.5 24.5 11.6 2.0 95.7 94.1 50.7 0.0 0.6 0.95 0.01 0.51 0.19 8.0 548.9

1983 187.6 346.4 28.0 12.0 2.3 97.0 98.0 54.8 0.0 0.6 1.09 0.02 0.60 0.21 8.0 549.1

1984 196.4 363.7 32.2 12.4 2.7 98.5 102.0 58.8 0.0 0.7 1.23 0.02 0.71 0.23 8.1 549.3

1985 206.2 378.5 36.7 12.9 3.0 99.9 106.5 62.7 0.0 0.7 1.40 0.02 0.85 0.26 8.2 549.4

1986 216.2 397.9 41.8 13.4 3.4 101.3 110.3 66.9 0.0 0.8 1.59 0.02 1.03 0.27 8.3 549.5

1987 227.2 416.4 47.5 14.0 3.9 103.0 113.5 71.5 0.0 0.8 1.77 0.02 1.24 0.29 8.4 549.6

1988 238.7 439.0 54.0 14.5 4.3 104.0 118.7 76.7 0.0 0.9 1.96 0.02 1.45 0.31 8.5 549.7

1989 248.8 459.3 60.9 15.0 4.7 104.8 123.5 82.5 0.0 1.1 2.14 0.02 1.64 0.34 8.6 549.8

1990 256.4 476.4 67.6 15.4 5.2 105.6 127.3 88.2 0.0 1.2 2.32 0.03 1.80 0.37 8.7 549.8

1991 262.0 489.7 73.3 15.7 5.6 105.9 130.8 93.7 0.0 1.8 2.52 0.03 1.95 0.39 8.8 549.9

1992 265.4 500.7 78.2 15.8 6.0 105.8 133.6 99.8 0.1 2.8 2.72 0.03 2.09 0.42 8.9 549.9

1993 267.8 510.0 81.2 16.0 6.4 105.3 130.3 103.9 0.4 3.9 2.92 0.03 2.23 0.44 9.0 549.9

1994 268.1 516.5 83.0 16.1 6.8 104.4 121.9 109.1 1.5 5.1 3.11 0.03 2.35 0.46 9.2 550.0

1995 267.8 523.0 83.8 16.1 7.1 103.7 110.5 113.6 2.8 6.2 3.35 0.04 2.45 0.47 9.2 555.2

1996 267.0 528.7 84.0 16.2 7.4 102.6 98.2 119.4 4.5 7.2 3.53 0.04 2.53 0.48 9.2 539.3

1997 266.0 532.9 83.8 16.3 7.7 101.6 84.1 124.2 6.4 8.3 3.69 0.05 2.61 0.49 9.1 529.6

1998 264.6 536.4 83.4 16.4 7.9 100.7 71.0 128.9 8.2 9.4 3.82 0.05 2.69 0.49 9.3 554.3

1999 263.3 539.3 82.9 16.4 8.0 99.6 59.4 134.3 10.1 10.4 3.96 0.04 2.76 0.49 9.3 555.5

2000 261.6 541.4 82.3 16.5 8.1 98.5 49.7 139.2 11.8 11.4 4.08 0.04 2.84 0.49 9.0 542.8

2001 260.0 542.8 81.7 16.5 8.2 97.5 41.5 144.7 13.5 12.5 4.18 0.03 2.88 0.49 8.5 534.8

2002 258.2 543.6 81.1 16.6 8.3 96.5 34.5 150.5 14.8 13.3 4.24 0.02 2.91 0.49 8.3 533.6
Chapter 5

5.58

Year CFC-11 CFC-12

CFC113CFC114CFC115 CCl4 CH3CCl3 HCFC-22HCFC141bHCFC142bhalon1211halon1202halon1301halon2402 CH3Br CH3Cl

2003 256.0 543.6 80.4 16.6 8.3 95.5 28.8 155.4 16.1 13.9 4.28 0.02 2.97 0.49 8.2 539.6

2004 253.8 543.4 79.7 16.6 8.3 94.5 24.0 160.5 17.0 14.6 4.31 0.02 3.02 0.49 8.1 536.2

2005 251.5 542.5 79.0 16.6 8.4 93.5 20.0 165.7 17.5 15.2 4.34 0.01 3.05 0.49 7.9 539.9

2006 249.4 541.6 78.4 16.5 8.4 92.5 16.7 171.9 17.8 15.9 4.34 0.01 3.08 0.48 7.8 536.9

2007 247.2 539.6 77.7 16.5 8.4 91.4 14.0 179.1 18.5 16.9 4.32 0.01 3.11 0.48 7.6 543.7

2008 245.0 537.5 76.9 16.5 8.4 90.2 11.7 187.3 19.1 18.1 4.28 0.00 3.15 0.47 7.5 545.3

2009 243.0 535.3 76.2 16.5 8.4 88.9 9.8 195.2 19.6 19.3 4.22 0.00 3.17 0.47 7.3 541.0

2010 241.1 532.7 75.5 16.4 8.4 87.6 8.2 202.5 20.1 20.0 4.16 0.00 3.19 0.46 7.1 538.4

2011 239.0 530.1 74.8 16.4 8.4 86.5 6.9 210.0 20.9 20.8 4.08 0.00 3.22 0.45 7.1 533.5

2012 237.0 527.4 74.1 16.4 8.4 85.2 5.7 216.1 21.9 21.5 4.01 0.00 3.24 0.45 7.0 538.1

2013 234.7 525.0 73.4 16.3 8.4 84.1 4.8 221.5 22.9 21.9 3.91 0.00 3.26 0.44 7.0 539.5

2014 232.4 520.9 72.7 16.2 8.4 82.9 4.0 233.8 23.8 22.7 3.81 0.00 3.27 0.43 7.0 539.5

2015 229.9 516.7 71.9 16.1 8.4 81.6 3.3 244.8 24.6 23.5 3.71 0.00 3.28 0.43 7.0 539.5

2016 227.5 512.4 71.2 16.1 8.4 80.3 2.7 254.7 25.5 24.2 3.60 0.00 3.29 0.42 7.0 539.5

2017 224.9 508.0 70.5 16.0 8.4 78.9 2.2 262.9 26.4 24.8 3.49 0.00 3.30 0.41 7.0 539.5

2018 222.4 503.6 69.7 16.0 8.4 77.4 1.8 269.8 27.2 25.3 3.38 0.00 3.31 0.41 7.0 539.5

2019 219.9 499.1 69.0 15.9 8.4 75.9 1.5 275.5 28.0 25.8 3.27 0.00 3.31 0.40 7.0 539.5

2020 217.3 494.6 68.3 15.8 8.4 74.4 1.2 280.3 28.7 26.2 3.15 0.00 3.31 0.39 7.0 539.5

2025 204.2 472.0 64.7 15.5 8.4 66.6 0.4 282.2 31.5 27.0 2.60 0.00 3.29 0.35 7.0 539.5

2030 190.9 449.8 61.4 15.1 8.4 58.8 0.2 251.9 32.0 26.0 2.09 0.00 3.24 0.32 7.0 539.5

2035 177.8 428.5 58.2 14.7 8.3 51.3 0.1 198.8 29.8 23.3 1.66 0.00 3.16 0.28 7.0 539.5

2040 165.1 408.1 55.1 14.3 8.3 44.4 0.0 142.9 26.0 19.6 1.30 0.00 3.06 0.25 7.0 539.5

2045 152.8 388.6 52.3 14.0 8.3 38.1 0.0 98.7 21.7 16.0 1.01 0.00 2.95 0.22 7.0 539.5

2050 141.1 370.0 49.5 13.6 8.2 32.6 0.0 66.4 17.7 12.7 0.77 0.00 2.83 0.19 7.0 539.5

2055 130.0 352.3 46.9 13.3 8.2 27.7 0.0 44.2 14.1 9.9 0.59 0.00 2.71 0.17 7.0 539.5

2060 119.6 335.5 44.5 12.9 8.1 23.4 0.0 29.3 11.1 7.7 0.45 0.00 2.58 0.15 7.0 539.5

2065 109.8 319.4 42.1 12.6 8.0 19.8 0.0 19.3 8.6 5.9 0.34 0.00 2.45 0.13 7.0 539.5

2070 100.7 304.1 39.9 12.2 8.0 16.6 0.0 12.8 6.7 4.5 0.26 0.00 2.32 0.11 7.0 539.5

2075 92.3 289.6 37.9 11.9 7.9 14.0 0.0 8.4 5.1 3.4 0.19 0.00 2.20 0.10 7.0 539.5

2080 84.5 275.7 35.9 11.6 7.9 11.7 0.0 5.6 3.9 2.6 0.14 0.00 2.07 0.08 7.0 539.5

2085 77.2 262.5 34.0 11.3 7.8 9.8 0.0 3.7 3.0 2.0 0.11 0.00 1.96 0.07 7.0 539.5

2090 70.6 250.0 32.2 11.0 7.7 8.2 0.0 2.4 2.3 1.5 0.08 0.00 1.84 0.06 7.0 539.5

2095 64.4 238.0 30.5 10.7 7.7 6.8 0.0 1.6 1.7 1.2 0.06 0.00 1.73 0.05 7.0 539.5

2100 58.8 226.6 28.9 10.5 7.6 5.7 0.0 1.1 1.3 0.9 0.04 0.00 1.63 0.04 7.0 539.5
APPENDICES

APPENDIX A

LIST OF INTERNATIONAL AUTHORS, CONTRIBUTORS,

AND REVIEWERS

APPENDIX B

MAJOR ACRONYMS AND ABBREVIATIONS

APPENDIX C

CHEMICAL FORMULAE AND NOMENCLATURE

A.1

APPENDIX A

LIST OF INTERNATIONAL AUTHORS,

CONTRIBUTORS, AND REVIEWERS

COCHAIRS

Ayité-Lô Nohende Ajavon North-South Environment Togo

Paul A. Newman NASA Goddard Space Flight Center USA

John A. Pyle National Centre for Atmospheric Science, UK and 

University of Cambridge UK

A.R. Ravishankara Colorado State University and NOAA ESRL 

Chemical Sciences Division USA

SCIENTIFIC STEERING COMMITTEE

Ayité-Lô Nohende Ajavon North-South Environment Togo

David J. Karoly University of Melbourne Australia

Malcolm K. Ko NASA Langley Research Center USA

Paul A. Newman NASA Goddard Space Flight Center USA

John A. Pyle National Centre for Atmospheric Science, UK and 

University of Cambridge UK

A.R. Ravishankara Colorado State University and NOAA ESRL 

Chemical Sciences Division USA

Theodore G. Shepherd University of Reading, Department of Meteorology UK

Susan Solomon Massachusetts Institute of Technology, Department of 

Earth, Atmospheric, and Planetary Sciences USA

AUTHORS AND CONTRIBUTORS

CHAPTER 1

UPDATE ON OZONE-DEPLETING SUBSTANCES (ODSs) AND OTHER GASES OF 

INTEREST TO THE MONTREAL PROTOCOL

Lead Authors

Lucy J. Carpenter University of York USA

Stefan Reimann Empa, Swiss Federal Laboratories for Materials Science

and Technology Germany

Chapter Editors

Andreas Engel Goethe University Frankfurt, Institute for Atmospheric 

and Environmental Sciences Germany

Stephen A. Montzka NOAA ESRL Global Monitoring Division USA
Appendix A

A.2

Coauthors

James B. Burkholder NOAA ESRL Chemical Sciences Division USA

Cathy Clerbaux Sorbonne Universités, UPMC Univ. Paris 06; Université 

Versailles St-Quentin; CNRS / INSU; LATMOS-IPSL France

Bradley D. Hall NOAA ESRL Global Monitoring Division USA

Ryan Hossaini University of Leeds UK

Johannes C. Laube University of East Anglia UK

Shari A. Yvon-Lewis Texas A&M University USA

Contributors

Donald R. Blake University of California Irvine USA

Marcel Dorf Max-Planck-Institut für Chemie Germany

Geoffrey S. Dutton CIRES-University of Colorado / NOAA ESRL 

Global Monitoring Division USA

Paul J. Fraser CSIRO Marine and Atmospheric Research / Centre for 

Weather and Climate Research Australia

Lucien Froidevaux Jet Propulsion Laboratory, California Institute of Technology USA

François Hendrick Belgian Institute for Space Aeronomy Belgium

Jianxin Hu Peking University, College of Environmental Sciences 

and Engineering China

Ashley Jones University of Toronto Canada

Paul B. Krummel Centre for Australian Weather and Climate Research, 

CSIRO Marine and Atmospheric Research Australia

Lambert J.M. Kuijpers Technical University Eindhoven, Eindhoven Center 

for Sustainability The Netherlands

Michael J.Kurylo Universities Space Research Association / Goddard Earth 

Sciences, Technology, and Research USA

Qing Liang Universities Space Research Association / NASA Goddard 

Space Flight Center USA

Emmanuel Mahieu University of Liège Belgium

Jens Mühle Scripps Institution of Oceanography, University of California 

San Diego USA

Simon O’Doherty University of Bristol UK

Keiichi Ohnishi Asahi Glass Co., Ltd. Japan

Vladimir L. Orkin National Institute of Standards and Technology USA

Klaus Pfeilsticker University of Heidelberg Germany

Matt Rigby University of Bristol UK

Isobel J. Simpson University of California Irvine USA

Yoko Yokouchi National Institute for Environmental Studies Japan

Editorial Contributions 

Nada Derek University of York UK

Jenny Hudson Commonwealth Scientific and Industrial Research Organisation Australia
Authors, Contributors, and Reviewers

A.3

CHAPTER 2

UPDATE ON GLOBAL OZONE: PAST, PRESENT, AND FUTURE

Lead Authors

Steven Pawson NASA Goddard Space Flight Center USA

Wolfgang Steinbrecht Deutscher Wetterdienst, Hohenpeissenberg Germany

Chapter Editors

Vitali E. Fioletov Environment Canada, Measurements and Analysis 

Research Section Canada

Ulrike Langematz Freie Universität Berlin, Institut für Meteorologie Germany

Coauthors

Andrew Charlton-Perez University of Reading UK

Masatomo Fujiwara Hokkaido University Japan

Alexey Yu. Karpechko Finnish Meteorological Institute Finland

Irina Petropavlovskikh CIRES-University of Colorado / NOAA ESRL 

Global Monitoring Division USA

Joachim Urban Chalmers University of Technology Sweden

Mark Weber University of Bremen, Institute of Environmental Physics Germany

Contributors

Valentina Aquila GESTAR / The Johns Hopkins University USA

Wissam Chehade University of Bremen, Institute of Environmental Physics Germany

Irene Cionni Technical Unit for Energy and Environmental Modeling, ENEA Italy

Melanie Coldewey-Egbers Deutsches Zentrum für Luft- und Raumfahrt (DLR), 

Institut für Methodik der Fernerkundung Germany

Andy Delcloo Royal Meteorological Institute Belgium

Sandip Dhomse University of Leeds, School of Earth and Environment UK

Veronika Eyring Deutsches Zentrum für Luft- und Raumfahrt (DLR), 

Institut für Physik der Atmosphäre Germany

Eric L. Fleming Science Systems and Applications, Inc. USA

Stacey M. Frith Science Systems and Applications, Inc. USA

Lucien Froidevaux Jet Propulsion Laboratory, California Institute of Technology USA

Nathan P. Gillett Environment Canada Canada

Birgit Hassler CIRES-University of Colorado / NOAA ESRL 

Chemical Sciences Division USA

Michaela I. Hegglin University of Reading, Department of Meteorology UK

Doug Kinnison National Center for Atmospheric Research, Atmospheric 

Chemistry Division USA

Diego Loyola Deutsches Zentrum für Luft- und Raumfahrt (DLR), 

Institut für Methodik der Fernerkundung Germany

Chris McLinden Environment Canada, Air Quality Research Division Canada

Luke D. Oman NASA Goddard Space Flight Center USA

David Plummer Environment Canada Canada

Laura Revell Swiss Federal Institute of Technology Zürich Switzerland

Takatoshi Sakazaki Kyoto University Japan

William Seviour Oxford University UK
Appendix A

A.4

Susann Tegtmeier GEOMAR Helmholtz Centre for Ocean Research Kiel Germany

Ronald van der A Royal Netherlands Meteorological Institute (KNMI) The Netherlands

Jeannette Wild Innovim and NOAA / NWS / NCEP Climate Prediction Center USA

CHAPTER 3

UPDATE ON POLAR OZONE: PAST, PRESENT, AND FUTURE

Lead Authors

Martin Dameris Deutsches Zentrum für Luft- und Raumfahrt (DLR), 

Institut für Physik der Atmosphäre Germany

Sophie Godin-Beekmann Université de Versailles Saint-Quentin; Sorbonne Universités, 

UPMC Univ. Paris 06; CNRS / INSU; OVSQ-LATMOS France

Chapter Editors

Slimane Bekki Sorbonne Universités, UPMC Univ. Paris 06; Université

Versailles St-Quentin; CNRS / INSU; LATMOS-IPSL France

Judith Perlwitz CIRES-University of Colorado / NOAA ESRL 

Physical Sciences Division USA

Coauthors

Simon Alexander Australian Antarctic Division Australia

Peter Braesicke Karlsruhe Institute of Technology, Institute for 

Meteorology and Climate Research Germany

Martyn P. Chipperfield University of Leeds, School of Earth and Environment UK

A.T. Jos de Laat Royal Netherlands Meteorological Institute (KNMI) The Netherlands

Yvan J. Orsolini Norwegian Institute for Air Research (NILU) Norway

Markus Rex Alfred Wegener Institute – Helmholtz Centre for Polar and 

Marine Research Germany

Michelle L. Santee Jet Propulsion Laboratory, California Institute of Technology USA

Contributors

Ronald van der A Royal Netherlands Meteorological Institute (KNMI) The Netherlands

Irene Cionni Technical Unit for Energy and Environmental Modeling, ENEA Italy

Sandip Dhomse University of Leeds, School of Earth and Environment UK

Susana B. Diaz Instituto de Investigaciones en Ingenieria Genetica y Biologia 

molecular (INGEBI), Consejo Nacional de Investigaciones

Cientificas y Tecnologicas (CONICET) Argentina

Ines Engel Forschungszentrum Jülich, Institute of Energy and 

Climate Research – Stratosphere Germany

Peter von der Gathen Alfred Wegener Institute – Helmholtz Centre for Polar and 

Marine Research Germany

Jens-Uwe Grooß Forschungszentrum Jülich Germany

Birgit Hassler CIRES-University of Colorado / NOAA ESRL 

Chemical Sciences Division USA

Larry Horowitz NOAA Geophysical Fluid Dynamics Laboratory USA

Karin Kreher Bodeker Scientific and NIWA New Zealand

Markus Kunze Freie Universität Berlin, Institut für Meteorologie Germany
Authors, Contributors, and Reviewers

A.5

Ulrike Langematz Freie Universität Berlin, Institut für Meteorologie Germany

Gloria L. Manney NorthWest Research Associates USA

Rolf Müller Forschungszentrum Jülich GmbH Germany

Giovanni Pitari Università degli Studi de L'Aquila, Dipartimento di 

Scienze Fisiche e Chimiche Italy

Michael C. Pitts NASA Langley Research Center, Atmospheric

Composition Branch USA

Lamont R. Poole Science Systems and Applications, Inc. USA

Robyn Schofield University of Melbourne, ARC Centre of Excellence for 

Climate System Science Australia

Simone Tilmes National Center for Atmospheric Research USA

Mark Weber University of Bremen, Institute of Environmental Physics Germany

CHAPTER 4

STRATOSPHERIC OZONE CHANGES AND CLIMATE

Lead Authors

Julie M. Arblaster Australian Bureau of Meteorology and 

National Center for Atmospheric Research Australia /USA

Nathan P. Gillett Environment Canada Canada

Chapter Editors

Lesley J. Gray National Centre for Atmospheric Science, UK and 

University of Oxford UK

David W.J. Thompson Colorado State University USA

Coauthors

Natalia Calvo Complutense University of Madrid Spain

Piers M. Forster University of Leeds UK

Lorenzo M. Polvani Columbia University USA

Seok-Woo Son Seoul National University Korea

Darryn W. Waugh The Johns Hopkins University USA

Paul J. Young Lancaster University UK

Contributors

Elizabeth A. Barnes Colorado State University USA

Irene Cionni Technical Unit for Energy and Environmental Modeling, ENEA Italy

Chaim I. Garfinkel Hebrew University Israel

Edwin P. Gerber New York University USA

Steven C. Hardiman Met Office Hadley Centre UK

Dale F. Hurst CIRES-University of Colorado / NOAA ESRL 

Global Monitoring Division USA

Jean-François Lamarque National Center for Atmospheric Research USA

Eun-Pa Lim Australian Bureau of Meteorology Australia

Michael P. Meredith British Antarctic Survey UK

Judith Perlwitz CIRES-University of Colorado / NOAA ESRL 

Physical Sciences Division USA
Appendix A

A.6

Robert W. Portmann NOAA ESRL Chemical Sciences Division USA

Michael Previdi Columbia University, Lamont-Doherty Earth Observatory USA

Michael Sigmond Environment Canada Canada

Neil C. Swart Environment Canada Canada

Jean-Paul Vernier NASA Langley Research Center USA

Yutian Wu Purdue University USA

CHAPTER 5

SCENARIOS AND INFORMATION FOR POLICYMAKERS

Lead Authors

Neil R.P. Harris University of Cambridge UK

Donald J. Wuebbles University of Illinois USA

Chapter Editors

Mack McFarland DuPont Chemicals & Fluoroproducts USA

Guus J.M. Velders National Institute for Public Health and the Environment (RIVM) The Netherlands

Coauthors

John S. Daniel NOAA ESRL Chemical Sciences Division USA

Jianxin Hu Peking University, College of Environmental Sciences 

and Engineering China

Lambert J.M. Kuijpers Technical University Eindhoven, Eindhoven Center 

for Sustainability The Netherlands

Katharine S. Law Sorbonne Universités, UPMC Univ. Paris 06; Université 

Versailles St-Quentin; CNRS / INSU; LATMOS-IPSL France

Michael J. Prather University of California Irvine /Earth System Science DepartmentUSA

Robyn Schofield University of Melbourne, ARC Centre of Excellence for 

Climate System Science Australia

Contributors

James B. Burkholder NOAA ESRL Chemical Sciences Division USA

Eric L. Fleming Science Systems and Applications, Inc. USA

Øivind Hodnebrog Center for International Climate and Environmental 

Research – Oslo (CICERO) Norway

Ryan Hossaini University of Leeds UK

Charles H. Jackman NASA Goddard Space Flight Center USA

Daniel Phoenix University of Illinois USA

TWENTY QUESTIONS AND ANSWERS ABOUT THE OZONE LAYER: 2014 UPDATE

Lead Author

Michaela I. Hegglin University of Reading, Department of Meteorology UK
Authors, Contributors, and Reviewers

A.7

REVIEWERS

Jon Abbatt University of Toronto Canada

Ayité-Lô Nohende Ajavon North-South Environment Togo

Hideharu Akiyoshi National Institute for Environmental Studies Japan

Joan M. Alexander NorthWest Research Associates USA

Simon Alexander Australian Antarctic Division Australia

Stephen O. Andersen Institute for Governance & Sustainable Development USA

Julie M. Arblaster Australian Bureau of Meteorology and 

National Center for Atmospheric Research Australia /USA

Matthew Ashfold University of Nottingham Malaysia Campus Malaysia

Ghassem Asrar Joint Global Change Research Institute (PNNL/UMD) USA

Pieter J. Aucamp Ptersa Environmental Management Consultants, South Africa South Africa

Alkiviadis F. Bais Aristotle University of Thessaloniki Greece

Mark P. Baldwin University of Exeter UK

Steven L. Baughcum Boeing Company USA

Gufran Beig Indian Institute of Tropical Meteorology India

Slimane Bekki Sorbonne Universités, UPMC Univ. Paris 06; Université

Versailles St-Quentin; CNRS / INSU; LATMOS-IPSL France

Peter Bernath Old Dominion University USA

Thomas Birner Colorado State University, Department of Atmospheric Science USA

Greg Bodeker Bodeker Scientific New Zealand

Rumen D. Bojkov Consultant on ozone and climate change Germany

Geir O. Braathen World Meteorological Organization Switzerland

Stefan Brönnimann University of Bern, Institute of Geography Switzerland

Dominik Brunner Empa, Swiss Federal Laboratories for Materials Science 

and Technology Switzerland

John P. Burrows University of Bremen, Institute of Environmental Physics /

Institute of Remote Sensing Germany

Neal Butchart Met Office Hadley Centre UK

Amy H. Butler CIRES-University of Colorado / NOAA ESRL 

Chemical Sciences Division USA

Wenju Cai Commonwealth Scientific and Industrial Research 

Organization, Division of Marine and Atmospheric Research Australia

Francesco Cairo National Research Council – Institute of Atmospheric 

Sciences and Climate Italy

Pablo O. Canziani Pontificia Universidad Católica Argentina / Consejo Nacional

de Investigaciones Científicas y Técnicas) / PEPACG Argentina

Lucy J. Carpenter University of York UK

Kenneth S. Carslaw University of Leeds, School of Earth and Environment UK

Andrew Charlton-Perez University of Reading UK

Martyn P. Chipperfield University of Leeds, School of Earth and Environment UK

Bo Christiansen Danish Meteorological Institute Denmark

Cathy Clerbaux Sorbonne Universités, UPMC Univ. Paris 06; Université 

Versailles St-Quentin; CNRS / INSU; LATMOS-IPSL France

Martin Dameris Deutsches Zentrum für Luft- und Raumfahrt (DLR), 

Institut für Physik der Atmosphäre Germany

John S. Daniel NOAA ESRL Chemical Sciences Division USA

Sandip Dhomse University of Leeds, School of Earth and Environment UK
Appendix A

A.8

Susana B. Diaz Instituto de Investigaciones en Ingenieria Genetica y Biologia 

molecular (INGEBI), Consejo Nacional de Investigaciones

Cientificas y Tecnologicas (CONICET) Argentina

Anne R. Douglass NASA Goddard Space Flight Center USA

Richard S. Eckman NASA Headquarters USA

Nawo Eguchi Kyushu University, Research Institute for Applied Mechanics Japan

James William Elkins NOAA ESRL Global Monitoring Division USA

Andreas Engel Goethe University Frankfurt, Institute for Atmospheric and 

Environmental Sciences Germany

Christine A. Ennis CIRES-University of Colorado / NOAA ESRL 

Chemical Sciences Division USA

Veronika Eyring Deutsches Zentrum für Luft- und Raumfahrt (DLR), 

Institut für Physik der Atmosphäre Germany

David W. Fahey NOAA ESRL Chemical Sciences Division USA

Vitali E. Fioletov Environment Canada, Measurements and Analysis 

Research Section Canada

Piers M. Forster University of Leeds UK

Paul J. Fraser CSIRO Marine and Atmospheric Research / Centre for 

Weather and Climate Research Australia

Lucien Froidevaux Jet Propulsion Laboratory, California Institute of Technology USA

Jan Fuglestvedt Center for International Climate and Environmental 

Research – Oslo (CICERO) Norway

John C. Fyfe Environment Canada, Canadian Centre for Climate 

Modeling and Analysis Canada

Annie Gabriel Department of the Environment Australia

Lenah Gaoetswe Department of Meteorological Services Botswana

Hella Garny Deutsches Zentrum für Luft- und Raumfahrt (DLR), 

Institut für Physik der Atmosphäre Germany

Marvin A. Geller Stony Brook University USA

Edwin P. Gerber New York University USA

Andrew Gettelman National Center for Atmospheric Research USA

Tomasz Gierczak Warsaw University Poland

Manuel Gil-Ojeda Área de Investigación e Instrumentación Atmosférica, 

Instituto Nacional de Técnica Aeroespacial-INTA Spain

Nathan P. Gillett Environment Canada Canada

Sophie Godin-Beekmann Université de Versailles Saint-Quentin; Sorbonne Universités, 

UPMC Univ. Paris 06; CNRS / INSU; OVSQ-LATMOS France

Marco González Sistemas de Energia Costa Rica

Lesley J. Gray National Centre for Atmospheric Science, UK and 

University of Oxford UK

Kevin M. Grise Columbia University, Lamont-Doherty Earth Observatory USA

Jens-Uwe Grooß Forschungszentrum Jülich Germany

Serge Guillas University College London UK

Joanna D. Haigh Imperial College London UK

Bradley D. Hall NOAA ESRL Global Monitoring Division USA

Neil R.P. Harris University of Cambridge UK

Birgit Hassler CIRES-University of Colorado / NOAA ESRL 

Chemical Sciences Division USA

Alain Hauchecorne Université Versailles St-Quentin; Sorbonne Universités, 

UPMC Univ. Paris 06; CNRS / INSU; LATMOS-IPSL France

Peter Haynes University of Cambridge, Centre for Mathematical Sciences UK
Authors, Contributors, and Reviewers

A.9

Michaela I. Hegglin University of Reading, Department of Meteorology UK

Peter Hitchcock University of Cambridge, Department of Applied 

Mathematics and Theoretical Physics UK

Øivind Hodnebrog Center for International Climate and Environmental 

Research – Oslo (CICERO) Norway

Jianxin Hu Peking University, College of Environmental Sciences 

and Engineering China

Nathalie Huret Université d’Orléans / OSUC, CNRS / Laboratoire de Physique 

et Chimie de l'Environnement et de l'Espace France

Iolanda Ialongo Finnish Meteorological Institute, Earth Observation unit Finland

Mohammad Ilyas University of Malaysia Perlis Malaysia

Franz Immler European Commission Belgium

Ivar S.A. Isaksen University of Oslo Norway

Michal Janouch Czech Hydrometeorological Institute, Solar and Ozone 

Observatory Czech Republic

Julie M. Jones University of Sheffield, Department of Geography UK

Kenneth W. Jucks NASA Headquarters USA

David J. Karoly University of Melbourne Australia

Alexey Yu. Karpechko Finnish Meteorological Institute Finland

Yasuko Kasai National Institute of Information and Communications 

Technology Japan

Philippe Keckhut Université Versailles St-Quentin; Sorbonne Universités, 

UPMC Univ. Paris 06; CNRS / INSU, LATMOS-IPSL France

Sergey Khaykin Central Aerological Observatory of Roshydromet Russia

Andrew R. Klekociuk Australian Antarctic Division Australia

Jeff R. Knight Met Office Hadley Centre UK

Malcolm K. Ko NASA Langley Research Center USA

Yutaka Kondo Department of Earth and Planetary Science, Graduate School 

of Science, The University of Tokyo Japan

Karin Kreher Bodeker Scientific and NIWA New Zealand

Kirstin Krüger University of Oslo, Department of Geosciences Norway

Paul B. Krummel Centre for Australian Weather and Climate Research, 

CSIRO Marine and Atmospheric Research Australia

Lambert J.M. Kuijpers Technical University Eindhoven, Eindhoven Center 

for Sustainability The Netherlands

Michael J.Kurylo Universities Space Research Association / Goddard Earth 

Sciences, Technology, and Research USA

Paul J. Kushner University of Toronto, Department of Physics Canada

Erkki Kyrölä Finnish Meteorological Institute, Earth Observation Finland

Gabriela Lakkis Pontificia Universidad Católica Argentina, PEPACG Argentina

Shyam Lal Physical Research Laboratory India

Jean-François Lamarque National Center for Atmospheric Research, 

Earth System Laboratory USA

Tom Land U.S. Environmental Protection Agency, Office of 

Atmospheric Programs, Stratospheric Protection Division USA

Ulrike Langematz Freie Universität Berlin, Institut für Meteorologie Germany

Franck Lefèvre Sorbonne Universités, UPMC Univ. Paris 06; Université 

Versailles St-Quentin; CNRS / INSU; LATMOS-IPSL France

Bernard Legras Laboratoire de Météorologie Dynamique, CNRS / Ecole 

Normale Supérieure / UPMC / Ecole Polytechnique / IPSL France

Jos Lelieveld Max Planck Institute for Chemistry – Mainz Germany
Appendix A

A.10

Jintai Lin Peking University, Department of Atmospheric and 

Oceanic Sciences China

Nathaniel Livesey Jet Propulsion Laboratory, California Institute of Technology USA

Desmond Manatsa Bindura University of Science Zimbabwe

Gloria L. Manney NorthWest Research Associates USA

Martin R. Manning New Zealand Climate Change Research Institute New Zealand

Elisa Manzini Max-Planck-Institut für Meteorologie – Hamburg Germany

Bella Maranion U.S. Environmental Protection Agency USA

Daniel R. Marsh National Center for Atmospheric Research USA

Amanda C. Maycock University of Cambridge, Centre for Atmospheric Science UK

Mack McFarland DuPont Chemicals & Fluoroproducts USA

Charles McLandress University of Toronto, Department of Physics Canada

Johan Mellqvist Chalmers University of Technology Sweden

Pauline M. Midgley University of Bern Switzerland

Daniel M. Mitchell University of Oxford, Department of Physics UK

Mario J. Molina University of California San Diego, Department of Chemistry 

and Biochemistry USA

Stephen A. Montzka NOAA ESRL Global Monitoring Division USA

Olaf Morgenstern National Institute of Water and Atmospheric 

Research (NIWA) Lauder New Zealand

Rolf Müller Forschungszentrum Jülich GmbH Germany

Hiroaki Naoe Japan Meteorological Agency Japan

Thando Ndarana South African Weather Service South Africa

Paul A. Newman NASA Goddard Space Flight Center USA

Ole John Nielsen Copenhagen Center for Atmospheric Research (CCAR), 

Department of Chemistry, University of Copenhagen Denmark

Luke D. Oman NASA Goddard Space Flight Center USA

Vladimir L. Orkin National Institute of Standards and Technology USA

Andrew Orr British Antarctic Survey UK

Steven Pawson NASA Goddard Space Flight Center USA

Juan Carlos Peláez Centro de Física de la Atmósfera, Instituto de 

Meteorología de Cuba Cuba

Stuart A. Penkett University of East Anglia UK

Judith Perlwitz CIRES-University of Colorado / NOAA ESRL 

Physical Sciences Division USA

Thomas Peter Swiss Federal Institute of Technology Zürich, Institute for 

Atmospheric and Climate Science Switzerland

Damaris K. Pinheiro Federal University of Santa Maria Brazil

Giovanni Pitari Università degli Studi de L'Aquila, Dipartimento di 

Scienze Fisiche e Chimiche Italy

David Plummer Environment Canada Canada

Lorenzo M. Polvani Columbia University USA

Jean-Pierre Pommereau Université Versailles St-Quentin; Sorbonne Universités, 

UPMC Univ. Paris 06; CNRS / INSU; LATMOS-IPSL France

Ronald G. Prinn Massachusetts Institute of Technology, Center for Global 

Change Science USA

John A. Pyle National Centre for Atmospheric Science, UK and 

University of Cambridge UK

Birgit Quack GEOMAR Helmholtz Centre for Ocean Research Kiel Germany

B. Rajakumar Indian Institute of Technology Madras, Department 

of Chemistry India
Authors, Contributors, and Reviewers

A.11

S. Ramachandran Physical Research Laboratory India

V. Ramaswamy NOAA Geophysical Fluid Dynamics Laboratory USA

Cora Randall University of Colorado / Laboratory for Atmospheric 

and Space Physics USA

William Randel National Center for Atmospheric Research USA

Marilyn Raphael University of California Los Angeles, Department of 

Geography USA

A.R. Ravishankara NOAA ESRL Chemical Sciences Division and 

Colorado State University, Department of Chemistry and 

Department of Atmospheric Science USA

Stefan Reimann Empa, Swiss Federal Laboratories for Materials Science 

and Technology Switzerland

James Renwick Victoria University of Wellington New Zealand

Markus Rex Alfred Wegener Institute – Helmholtz Centre for Polar and 

Marine Research Germany

Robert C. Rhew University of California Berkeley USA

Harald E. Rieder University of Graz, Austria Austria

Martin Riese Forschungszentrum Jülich, Institute of Energy and Climate 

Research – Stratosphere Germany

Vincenzo Rizi CETEMPS, Dipartimento di Scienze Fisiche e Chimiche, 

Università Degli Studi dell'Aquila Italy

Alan Robock Rutgers University, Department of Environmental Sciences USA

Jose M. Rodriguez NASA Goddard Space Flight Center USA

Eugene Rozanov World Radiation Center / Swiss Federal Institute of 

Technology Zürich Switzerland

Vladimir Ryabinin World Climate Research Programme Switzerland

Alfonso Saiz-Lopez Consejo Superior de Investigaciones Cientificas, Institute 

of Physical Chemistry Rocasolano Spain

Ross J. Salawitch University of Maryland, College Park USA

Michelle L. Santee Jet Propulsion Laboratory, California Institute of Technology USA

Robert Sausen Deutsches Zentrum für Luft- und Raumfahrt (DLR), 

Institut für Physik der Atmosphäre Germany

Sue Schauffler National Center for Atmospheric Research USA

Robyn Schofield University of Melbourne, ARC Centre of Excellence for 

Climate System Science Australia

Dian J. Seidel NOAA Air Resources Laboratory USA

Megumi Seki United Nations Environment Programme, Ozone Secretariat Kenya

Jonathan Shanklin British Antarctic Survey UK

Tiffany A. Shaw Columbia University, Lamont-Doherty Earth Observatory USA

Rajendra Shende TERRE Policy Centre India

Theodore G. Shepherd University of Reading, Department of Meteorology UK

Kiyotaka Shibata Meteorological Research Institute Japan

Keith Shine University of Reading, Department of Meteorology UK

Masato Shiotani Kyoto University, Research Institute for Sustainable 

Humanosphere Japan

Peter Simmonds University of Bristol (retired) UK

Isla R. Simpson Columbia University, Lamont-Doherty Earth Observatory USA

Rajiv R. Singh Honeywell International USA

Björn-Martin Sinnhuber Karlsruhe Institute of Technology Germany

Karen L. Smith Columbia University, Lamont-Doherty Earth Observatory USA
Appendix A

A.12

Susan Solomon Massachusetts Institute of Technology, Department of 

Earth, Atmospheric, and Planetary Sciences USA

Johannes Staehelin Swiss Federal Institute of Technology Zürich, Institute for 

Atmospheric and Climate Science Switzerland

Wolfgang Steinbrecht Deutscher Wetterdienst, Hohenpeissenberg Germany

Gabriele P. Stiller Karlsruhe Institute of Technology, Institute for Meteorology 

and Climate Research Germany

Richard S. Stolarski The Johns Hopkins University USA

William T. Sturges University of East Anglia UK

Tove M. Svendby Norwegian Institute for Air Research (NILU) Norway

Neil C. Swart Environment Canada Canada

David W. Tarasick Environment Canada Canada

Susann Tegtmeier GEOMAR Helmholtz Centre for Ocean Research Kiel Germany

Said Ali Thaoubane Université des Comores Comoros

Larry W. Thomason NASA Langley Research Center USA

David W.J. Thompson Colorado State University USA

Simone Tilmes National Center for Atmospheric Research USA

Owen Brian Toon University of Colorado, Laboratory for Atmospheric and Space 

Physics, Department of Atmospheric and Oceanic Sciences USA

Matthew B. Tully Australian Bureau of Meteorology Australia

John Turner British Antarctic Survey UK

Guus J.M. Velders National Institute for Public Health and the Environment (RIVM) The Netherlands

Daniel P. Verdonik Hughes Associates, Inc. USA

Martin K. Vollmer Empa, Swiss Federal Laboratories for Materials Science 

and Technology Switzerland

Christian von Savigny Ernst-Moritz-Arndt-University of Greifswald, 

Institute of Physics Germany

Timothy J. Wallington Ford Motor Company USA

Darryn W. Waugh The Johns Hopkins University USA

Ann R. Webb University of Manchester UK

Debra K. Weisenstein Harvard University, School of Engineering and Applied ScienceUSA

Ray F. Weiss University of California San Diego, Scripps Institution 

of Oceanography USA

Laura J. Wilcox University of Reading, Department of Meteorology UK

Elian Augusto Wolfram Laser Research Center and Applications, CEILAP 

(CITEDEF-CONICET) Argentina

Donald J. Wuebbles University of Illinois USA

Shi-Keng Yang NOAA / NWS / NCEP Climate Prediction Center USA

Shigeo Yoden Kyoto University Japan

Durwood Zaelke Institute for Governance and Sustainable Development USA

Christos S. Zerefos Academy of Athens Greece

Lingxi Zhou Chinese Meteorological Administration, Chinese Academy 

of Meteorological Sciences China

Jerry Ziemke NASA Goddard Space Flight Center USA
Authors, Contributors, and Reviewers

A.13

OZONE PEER-REVIEW MEETING

Les Diablerets, Switzerland

23-27 June 2014

 by Maria Montzka, Fall 2006

Ayité-Lô Nohende Ajavon North-South Environment Togo

Stephen O. Andersen Institute for Governance & Sustainable Development USA

Julie M. Arblaster (remote) Australian Bureau of Meteorology and 

National Center for Atmospheric Research Australia/USA

Pieter J. Aucamp Ptersa Environmental Management Consultants, South Africa South Africa

Gufran Beig Indian Institute of Tropical Meteorology India

Geir O. Braathen World Meteorological Organization Switzerland

John P. Burrows University of Bremen, Institute of Environmental Physics /

Institute of Remote Sensing Germany

Pablo O. Canziani Pontificia Universidad Católica Argentina / Consejo Nacional

de Investigaciones Científicas y Técnicas) / PEPACG Argentina

Lucy J. Carpenter University of York UK

Martyn P. Chipperfield University of Leeds, School of Earth and Environment UK

Martin Dameris Deutsches Zentrum für Luft- und Raumfahrt (DLR), 

Institut für Physik der Atmosphäre Germany

John S. Daniel NOAA ESRL Chemical Sciences Division USA

Christine A. Ennis CIRES-University of Colorado / NOAA ESRL 

Chemical Sciences Division USA

David W. Fahey NOAA ESRL Chemical Sciences Division USA

Vitali E. Fioletov Environment Canada, Measurements and Analysis 

Research Section Canada

Lucien Froidevaux Jet Propulsion Laboratory, California Institute of Technology USA

Nathan P. Gillett Environment Canada Canada

Sophie Godin-Beekmann Université de Versailles Saint-Quentin; Sorbonne Universités, 

UPMC Univ. Paris 06; CNRS / INSU; OVSQ-LATMOS France

Marco González Sistemas de Energia Costa Rica

Neil R.P. Harris University of Cambridge UK

Michaela I. Hegglin University of Reading, Department of Meteorology UK

Kenneth W. Jucks NASA Headquarters USA
Appendix A

A.14

David J. Karoly University of Melbourne Australia

Malcolm K. Ko NASA Langley Research Center USA

Lambert J.M. Kuijpers Technical University Eindhoven, Eindhoven Center 

for Sustainability The Netherlands

Michael J.Kurylo Universities Space Research Association / Goddard Earth 

Sciences, Technology, and Research USA

Ulrike Langematz Freie Universität Berlin, Institut für Meteorologie Germany

Martin R. Manning New Zealand Climate Change Research Institute New Zealand

Amanda C. Maycock University of Cambridge, Centre for Atmospheric Science UK

Mack McFarland DuPont Chemicals & Fluoroproducts USA

Pauline M. Midgley University of Bern Switzerland

Stephen A. Montzka NOAA ESRL Global Monitoring Division USA

Olaf Morgenstern National Institute of Water and Atmospheric 

Research (NIWA) Lauder New Zealand

Rolf Müller Forschungszentrum Jülich GmbH Germany

Hiroaki Naoe Japan Meteorological Agency Japan

Paul A. Newman NASA Goddard Space Flight Center USA

Steven Pawson NASA Goddard Space Flight Center USA

Thomas Peter Swiss Federal Institute of Technology Zürich, Institute for 

Atmospheric and Climate Science Switzerland

David Plummer Environment Canada Canada

Lorenzo M. Polvani Columbia University USA

Ronald G. Prinn Massachusetts Institute of Technology, Center for Global 

Change Science USA

John A. Pyle National Centre for Atmospheric Science, UK and 

University of Cambridge UK

A.R. Ravishankara NOAA ESRL Chemical Sciences Division and 

Colorado State University, Department of Chemistry and 

Department of Atmospheric Science USA

Stefan Reimann Empa, Swiss Federal Laboratories for Materials Science 

and Technology Switzerland

Jose M. Rodriguez NASA Goddard Space Flight Center USA

Ross J. Salawitch University of Maryland, College Park USA

Megumi Seki United Nations Environment Programme, Ozone Secretariat Kenya

Rajendra Shende TERRE Policy Centre India

Theodore G. Shepherd University of Reading, Department of Meteorology UK

Susan Solomon Massachusetts Institute of Technology, Department of 

Earth, Atmospheric, and Planetary Sciences USA

Wolfgang Steinbrecht Deutscher Wetterdienst, Hohenpeissenberg Germany

William T. Sturges University of East Anglia UK

David W.J. Thompson Colorado State University USA

Guus J.M. Velders National Institute for Public Health and the Environment (RIVM) The Netherlands

Timothy J. Wallington Ford Motor Company USA

Darryn W. Waugh The Johns Hopkins University USA

Ray F. Weiss University of California San Diego, Scripps Institution 

of Oceanography USA

Donald J. Wuebbles University of Illinois USA

Shigeo Yoden Kyoto University Japan

Lingxi Zhou Chinese Meteorological Administration, Chinese Academy 

of Meteorological Sciences China
Authors, Contributors, and Reviewers

A.15

Liaisons of Sponsoring Organizations

Geir O. Braathen World Meteorological Organization Switzerland

Tina Birmpili United Nations Environment Programme Kenya

A.R. Ravishankara National Oceanic and Atmospheric Administration USA

Kenneth Jucks National Aeronautics and Space Administration USA

Claus Brüning European Commission Belgium

Assessment Coordinator and Technical Editor

Christine A. Ennis CIRES/NOAA ESRL Chemical Sciences Division USA

Publication/Graphics Design and Layout

Full Report: Christine A. Ennis CIRES/NOAA ESRL Chemical Sciences Division USA

ADM: Debra A. Dailey-Fisher NOAA ESRL Chemical Sciences Division USA

Conference Coordination and Documentation

Christine A. Ennis CIRES/NOAA ESRL Chemical Sciences Division USA

Geir O. Braathen World Meteorological Organization Switzerland

Debra A. Dailey-Fisher NOAA ESRL Chemical Sciences Division USA

John A. Pyle University of Cambridge UK

Conference Support

Debra Dailey-Fisher NOAA ESRL Chemical Sciences Division USA

Jennifer Fox NOAA ESRL Chemical Sciences Division USA 

Jeanne S. Waters NOAA ESRL Chemical Sciences Division USA

Kathy A. Thompson CSC USA

Chantal Renaudot World Meteorological Organization Switzerland

Alice Wood University of Cambridge UK

Megumi Seki UNEP Ozone Secretariat Kenya

James S. Curlin UNEP Division of Technology, Industry, and Economics France

Benedictine Desbois UNEP Division of Technology, Industry, and Economics France

Computing and Networking Support

Richard J. Tisinai CIRES/NOAA ESRL Chemical Sciences Division USA

Jennifer Fox NOAA ESRL Chemical Sciences Division USA

Document Distribution

Jeanne S. Waters NOAA ESRL Chemical Sciences Division USA

Debra A. Dailey-Fisher NOAA ESRL Chemical Sciences Division USA

Suzette M. Milano-Schoser NOAA ESRL Chemical Sciences Division USA

Geir O. Braathen /Chantal Renaudot World Meteorological Organization Switzerland

Megumi Seki UNEP Ozone Secretariat Kenya

Kathleen Creavalle UNEP Ozone Secretariat Kenya

Reference Research and Editing

Scout D. Ennis CIRES/NOAA ESRL Chemical Sciences Division USA

Zita N. Toth STC and NOAA ESRL Chemical Sciences Division USA

B.1

APPENDIX B

MAJOR ACRONYMS AND ABBREVIATIONS

A1 baseline (or most likely) halocarbon scenario of the Ozone Assessment

A1-2006 baseline (or most likely) halocarbon scenario of the 2006 Ozone Assessment

A1-2010 baseline (or most likely) halocarbon scenario of the 2010 Ozone Assessment

A1B scenario of the IPCC Special Report on Emissions Scenarios (SRES)

A5 Article 5 countries of the Montreal Protocol

AAO Antarctic Oscillation

ACC Antarctic Circumpolar Current

ACCMIP Atmospheric Chemistry and Climate Model Intercomparison Project

ACE-FTS Atmospheric Chemistry Experiment Fourier Transform Spectrometer

ADEOS Advanced Earth Observing Satellite

ADM Assessment for Decision-Makers (of the 2014 WMO/UNEP Ozone Assessment)

AGAGE Advanced Global Atmospheric Gases Experiment

AGTP Absolute Global Temperature Potential

AGWP Absolute Global Warming Potential

AIRS Atmospheric Infrared Sounder

AMSU Advanced Microwave Sounding Unit

AO Arctic Oscillation

AOGCM atmosphere-ocean general circulation model

AR4 IPCC Fourth Assessment Report

AR5 IPCC Fifth Assessment Report

ARC Australian Research Council (Australia)

ARCTAS Arctic Research of the Composition of the Troposphere from Aircraft and Satellites

ARCPAC Aerosol, Radiation, and Cloud Processes affecting Arctic Climate

ATLAS Atmospheric Laboratory for Applications and Science

ATTREX Airborne Tropical TRopopause Experiment

AVE Aura Validation Experiment

B1 a lower-emissions scenario of the IPCC Special Report on Emissions Scenarios (SRES)

B2 scenario of the IPCC Special Report on Emissions Scenarios (SRES)

BDBP Binary Database of Profiles

BDC Brewer-Dobson circulation

BL boundary layer

BUV Backscatter (or Backscattered) Ultraviolet (spectrometer)

C Celsius (unit of temperature)

CALIOP Cloud-Aerosol Lidar with Orthogonal Polarization

CALIPSO Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation

CAM Community Atmosphere Model

CanESM Canadian Earth System Model
Appendix B

B.2

CARIBIC Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument 

Container

CAS Chemical Abstracts Service 

CBL Convective boundary layer

CCM chemistry-climate model

CCMI Chemistry-Climate Model Initiative

CCMVal Chemistry-Climate Model (CCM) Validation Activity (SPARC)

CCMVal-2 Chemistry-Climate Model (CCM) Validation Activity-2 (SPARC)

CCSM Community Climate System Model

CCSRNIES Center for Climate-Systems Research–National Institute for Environmental Studies CCM

CDIAC Carbon Dioxide Information Analysis Center

CDM Clean Development Mechanism

CDW circumpolar deep water

CESM Community Earth System Model

CFC chlorofluorocarbon

CFSR Climate Forecast System Reanalysis

CICERO Center for International Climate and Environmental Research-Oslo (Norway)

CIRES Cooperative Institute for Research in Environmental Sciences (United States)

CLAES Cryogenic Limb Array Etalon Spectrometer

CLaMS Chemical Lagrangian Model of the Stratosphere

cm centimeters (unit of length)

CMAM Canadian Middle Atmosphere Model

CMIP3 Couples Model Intercomparison Project Phase 3

CMIP5 Coupled Model Intercomparison Project Phase 5

CMIP5-CHEM CMIP5 models with chemistry

CNRM Centre National de Recherches Météorologiques (France)

CNRM-CMM CNRM Centre de Meteorologie Marine

CNRS Centre National de la Recherche Scientifique (France)

COBALD Compact Optical Backscatter Aerosol Detector

CONICET Consejo de Investigaciones Cientificas y Técnicas (Argentina)

CO2-eq carbon dioxide equivalents

COSI COde for Solar Irradiance

CPT cold point tropopause

CR-AVE Costa Rica-Aura Validation Experiment

CRISTA Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere

CSIRO Commonwealth Scientific and Industrial Research Organisation (Australia)

CTM chemical transport model

CUE critical-use exemption

DJF December-January-February

DLAPSE Denitrification by Lagrangian Particle Sedimentation

DLR Deutschen Zentrum für Luft- und Raumfahrt (Germany)

DMS dimethyl sulfide

DOAS Differential Optical Absorption Spectroscopy

DU Dobson unit

E39CA a coupled chemistry-climate model of DLR

ECl Equivalent Chlorine

ECMWF European Centre for Medium-Range Weather Forecasts (United Kingdom)
Acronyms and Abbreviations

B.3

EEAP Environmental Effects Assessment Panel

EESC Equivalent Effective Stratospheric Chlorine

ENEA Italian National Agency for New Technologies, Energy (Italy)

ENSO El Niño-Southern Oscillation

Envisat Environmental Satellite

EOS Earth Observing System 

EP Eliassen-Palm

eq equivalent

ERA ECMWF Re-Analysis

ERA-40 ECMWF 40-year Re-Analysis

ERA-Interim ECMWF Interim Re-Analysis

ERF Effective Radiative Forcing

ESA European Space Agency

ESA O3-CCI European Space Agency Ozone Climate Change Initiative

ESRL Earth System Research Laboratory (NOAA)

FAA Federal Aviation Administration

FPH Frost Point Hygrometers

FRF fractional release factors

FTIR Fourier transform infrared

FU-Berlin Freie Universität Berlin (Germany)

GAW Global Atmosphere Watch

GCM general circulation model

GDP Gross Domestic Product

GES DISC Goddard Earth Sciences Data and Information Services Center

GeoMIP Geoengineering Model Intercomparison Project

GEOS CHEM Goddard Earth Observing System global 3-D chemical transport model

GEOSCCM Goddard Earth Observing System Chemistry-Climate Model (Table 3-1)

GFDL Geophysical Fluid Dynamics Laboratory (NOAA)

Gg gigagrams (109 grams) (unit of mass)

GHG greenhouse gas

GISS Goddard Institute for Space Studies (NASA)

GMD Global Monitoring Division (NOAA/ESRL)

GODFIT GOME Direct-FITing

GOME Global Ozone Monitoring Experiment

GOME-2 Global Ozone Monitoring Experiment-2

GOMOS Global Ozone Monitoring by Occultation of Stars 

GOSAT Greenhouse gases Observing SATellite

GOZCARDS Global Ozone Chemistry and Related Trace Gas Data Records for the Stratosphere

GPCP Global Precipitation Climatology Project

GROMOS Ground-Based Millimeter-Wave Ozone Spectrometer

GSFC Goddard Space Flight Center (NASA)

GSG GOME, SCIAMACY, and GOME-2

Gt gigatonnes

GtCO2-eq gigatonnes of carbon dioxide equivalents

GTO Global Total Ozone

GTP Global Temperature Potential; Global Temperature change Potential

GWP Global Warming Potential
Appendix B

B.4

HadAT Hadley Centre radiosonde temperature product

HALOE Halogen Occultation Experiment

HARMOZ HARMonized dataset of OZone profiles 

HCFC hydrochlorofluorocarbon

HF hydrogen fluoride

HFC hydrofluorocarbon

HFE hydrofluorinated ether or hydrofluoroether

HFO hydrofluoro-olefin

HIAPER High-performance Instrumented Airborne Platform for Environmental Research

HIPPO HIAPER Pole-to-Pole Observations

HIRDLS High Resolution Dynamics Limb Sounder

hPa hectoPascal (102 Pascal) (unit of pressure)

HTOC Halons Technical Options Committee (TEAP)

IAM Integrated Assessment Models

IASI Infrared Atmospheric Sounding Interferometer

IGAC International Global Atmospheric Chemistry

IGACO-O3 Integrated Global Atmospheric Chemistry Observations-Ozone

IHALACE International Halocarbons in Air Comparison Experiment

INGEBI Instituto de Investigaciones en Ingeniería Genética y Biología Molecular (Argentina)

INSU Institut National des Sciences de l’Univers (France)

IO3C International Ozone Commission

IPCC Intergovernmental Panel on Climate Change

IPSL Institut Pierre-Simon Laplace (France)

IR infrared

IUP Institute of Environmental Physics, University of Bremen (Germany)

JJA June-July-August

JMA Japan Meteorological Agency (Japan)

JPL Jet Propulsion Laboratory (NASA)

K Kelvin (unit of temperature)

kg kilogram (103 grams) (unit of mass)

km kilometer (103 meters) (unit of length)

KNMI Royal Netherlands Meteorological Institute (The Netherlands)

Kt kilotons (103 tons) (unit of mass)

LATMOS Laboratoire Atmosphères, Milieux, Observations Spatiales (France)

LIMS Limb Infrared Monitor of the Stratosphere 

LMDZrepro general circulation model of the Laboratory of Dynamic Meteorology (IPSL)

LS lower stratosphere

LT local time

LZRH level of zero radiative heating
Acronyms and Abbreviations

B.5

m meter (unit of length)

MAESTRO Measurements of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by 

Occultation

MAM March-April-May

MATCH Model for Atmospheric Transport and Chemistry

MBL marine boundary layer

MEaSUREs Making Earth System Data Records for Use in Research Environments

MERRA Modern-Era Retrospective Analysis for Research and Applications

MetOp Meteorological Operational satellite

MFA monofluoroacetic acid

MIPAS Michelson Interferometer for Passive Atmospheric Sounding

MLR multiple linear regression

MLS Microwave Limb Sounder

mm millimeters (10-3 meters) (unit of length)

μm micrometer; micron (10-6 meters) (unit of length)

MMBtu million British thermal units (1MMBtu = 1.055 gigajoules)

MMM multi-model mean

MOD merged ozone data set

mol mole (unit, amount of substance)

MRI Meteorological Research Institute (Japan)

MSR Multi Sensor Reanalysis 

MSU Microwave Sounding Unit

mW milliWatt (10-3 Watts)

NAM Northern Annular Mode

NAO North Atlantic Oscillation

NASA National Aeronautics and Space Administration (United States)

NAT nitric acid trihydrate

NCAR National Center for Atmospheric Research (United States)

NCEP National Centers for Environmental Prediction (NOAA) (United States)

NDACC Network for the Detection of Atmospheric Composition Change

NH Northern Hemisphere

NIES National Institute for Environmental Studies (Japan)

NIWA National Institute of Water and Atmospheric Research (New Zealand)

nm nanometers (10-9 meters) (unit of length)

NOAA National Oceanic and Atmospheric Administration (United States)

nPB n-propyl bromide

NPLS nonparametric least-squares fit

NPP net primary production

NRL Naval Research Laboratory

NRLSSI Naval Research Laboratory Solar Spectral Irradiance model

NWS National Weather Service (NOAA) (United States)

OCS carbonyl sulfide (also COS)

ODP Ozone Depletion Potential

ODS ozone-depleting substance

OMI Ozone Monitoring Instrument

OMPS Ozone Mapping and Profiler Suite
Appendix B

B.6

OMPS-LP Ozone Mapping and Profiler Suite-Limb Profiler

OMPS-NM Ozone Mapping and Profiler Suite-Nadir Mapper

OMPS-NP Ozone Mapping and Profiler Suite-Nadir Profiler

OSIRIS Optical Spectrograph and InfraRed Imager System

OSUC Observatoire des Sciences de l'Univers en région Centre (France)

PCE perchloroethylene, also known as tetrachloroethylene

PDO Pacific Decadal Oscillation

PEARL Polar Environment Atmospheric Research Laboratory

PEM Pacific Exploratory Mission

PEPACG Programa para el Estudio de Procesos Atmosféricos en el Cambio Global (Argentina)

PFC perfluorocarbon

PFOS perfluorooctanyl sulfonate

PG product gas

PGI product gas injection

PI pre-industrial

PNNL Pacific Northwest National Laboratory (United States)

POAM Polar Ozone and Aerosol Measurement

ppb parts per billion

ppbv parts per billion by volume

ppm parts per million

ppmv parts per million by volume

ppt parts per trillion

pptv part per trillion by volume

PSC polar stratospheric cloud

PTFE polytetrafluoroethylene

PWLT piecewise linear trend

QBO quasi-biennial oscillation

QPS quarantine and pre-shipment

RCP Representative Concentration Pathway

RE radiative efficiencies

REF-B1 reference “future” simulation of SPARC CCMVal-2

REF-B2 reference “future” simulation of SPARC CCMVal-2

RF radiative forcing

RICH Radiosonde Innovation Composite Homogenization

RSS Remote Sensing Systems Inc.

s second (unit of time)

SABER Sounding of the Atmosphere using Broadband Emission Radiometry

SAGE Stratospheric Aerosol and Gas Experiment

SAM Southern Annular Mode

SAM II Stratospheric Aerosol Measurement II

SAMW Subantarctic Mode Water

SAOZ Système d’Analyse par Observation Zénithale

SAP Scientific Assessment Panel (Montreal Protocol)
Acronyms and Abbreviations

B.7

SATIRE Spectral and Total Irradiance REconstruction

SBUV/SBUV2 Solar Backscatter (or Backscattered) Ultraviolet (spectrometer)

SCIAMACHY Scanning Imaging Absorption Spectrometer for Atmospheric Chartography

SCISAT a Canadian satellite also known as Atmospheric Chemistry Experiment (ACE)

SD-WACCM Specified Dynamics version of the Whole Atmosphere Community Climate Model

SG source gas

SGI source gas injection

SH Southern Hemisphere

SHADOZ Southern Hemisphere Additional Ozonesondes

SHIVA Stratospheric Ozone: Halogen Impacts in a Varying Atmosphere

SI2N SPARC/IO3C/IGACO-O3/NDACC initiative

SLIMCAT Single-Layer Isentropic Model of Chemistry and Transport

SLS Submillimeterwave Heterodyne Limb Sounder

SMILES Superconducting Submillimeter-Wave Limb-Emission Sounder

SMR Sub-Millimetre Radiometer (Odin satellite)

SOCOL modeling tool for studies of Solar-Climate-Ozone Links

SON September-October-November

SORCE Solar Radiation and Climate Experiment

SPARC Stratosphere-troposphere Processes and Their Role in Climate (WCRP)

SRES Special Report on Emissions Scenarios (IPCC)

SRM solid rocket motor

SRV suborbital, reusable vehicles

SSA stratospheric sulfate aerosol

SSA single scattering albedo

SSI spectral solar irradiance

SST sea surface temperature

SSU Stratospheric Sounding Unit

SSW sudden stratospheric warming

STAR System for Transfer of Atmospheric Radiation

STE stratosphere-troposphere exchange

STRAT Stratospheric Tracers of Atmospheric Transport 

STS supercooled ternary solution

Suomi-NPP Suomi National Polar-orbiting Partnership

SUSIM Solar Ultraviolet Spectral Irradiance Monitor

SWOOSH Stratospheric Water and Ozone Satellite Homogenized

SZA solar zenith angle

2-D two-dimensional

3-D three-dimensional

TANSO-FTS Thermal And Near infrared Sensor for carbon Observation-Fourier Transform 

Spectrometer

TC4 Tropical Composition, Cloud and Climate Coupling mission

TCE trichloroethene, trichloroethylene

TEAP Technology and Economic Assessment Panel (Montreal Protocol)

TES Tropospheric Emission Spectrometer

TFA trifluoroacetic acid

Tg teragrams (1012 grams) (unit of mass; equivalent to megatonne)

TOMCAT Toulouse Off-line Model of Chemistry and Transport

TOMS Total Ozone Mapping Spectrometer

TOSOMI SCIAMACHY total ozone retrieval algorithm
Appendix B

B.8

TOGOMI GOME total ozone retrieval algorithm

TOU Total Ozone Unit

TSAM time series additive model

TTL tropical tropopause layer

UAH University of Alabama–Huntsville

UARS Upper Atmosphere Research Satellite

UCI University of California, Irvine

UEA University of East Anglia (United Kingdom)

UK United Kingdom

UKCA United Kingdom Chemistry and Aerosols chemistry-climate model

ULAQ University of L’Aquila chemistry-climate model (Italy)

UMD University of Maryland (United States)

UMETRAC Unified Model with Eulerian Transport and Chemistry

UMSLIMCAT Unified Model Single-Layer Isentropic Model of Chemistry and Transport CCM

UMUKCA Unified Model of the UK – Chemistry and Aerosol

UNEP United Nations Environment Programme

UNFCCC United Nations Framework Convention on Climate Change

UPMC Université Pierre et Marie Curie (France)

US, USA United States of America

UT upper troposphere

UTLS upper troposphere/lower stratosphere

UV ultraviolet

VIRGO Variability of solar IRadiance and Gravity Oscillations

VSL very short-lived

VSLS very short-lived substance(s)

W watt (unit of energy)

WACCM Whole-Atmosphere Community Climate Model

WCRP World Climate Research Programme

WFDOAS Weighting Function Differential Optical Absorption Spectroscopy

WOUDC World Ozone and Ultraviolet Data Centre

W/m2

, W m-2watts per square meter

WMO World Meteorological Organization
C.1

APPENDIX C

CHEMICAL FORMULAE AND NOMENCLATURE

HALOGEN-CONTAINING SPECIES

Cl atomic chlorine Br atomic bromine

Cly total inorganic chlorine Bry total inorganic bromine

CCly organic chlorine CBry organic bromine

Cl2 molecular chlorine Br2 molecular bromine

ClO chlorine monoxide BrO bromine monoxide

Cl2O dichlorine monoxide Br2O dibromine monoxide

ClOx chlorine radicals ([ClO] + 2×[ClOOCl]) BrOx bromine radicals

OClO chlorine dioxide

ClOO chloroperoxy radical

Cl2O2, ClOOCl dichlorine peroxide (ClO dimer)

ClONO2, ClNO3 chlorine nitrate BrONO2, BrNO3 bromine nitrate

HCl hydrogen chloride (hydrochloric acid) HBr hydrogen bromide

HOCl hypochlorous acid HOBr hypobromous acid

F atomic fluorine I atomic iodine

F2 molecular fluorine I2 molecular iodine

Fy total inorganic fluorine Iy total inorganic iodine

HF hydrogen fluoride (hydrofluoric acid) IO iodine monoxide

FOx fluorine radicals, F + FO IOx iodine radicals

OIO iodine dioxide

HOI hypoiodous acid

SF6 sulfur hexafluoride NF3 nitrogen trifluoride

SO2F2 sulfuryl fluoride PBr3 phosphorus tribromide
Appendix C

C.2

HALOCARBONS

CHLOROFLUOROCARBONS (CFCS) HYDROCHLOROFLUOROCARBONS (HCFCS)

CFC-11 CCl3F HCFC-21 CHCl2F

CFC-12 CCl2F2 HCFC-22 CHClF2

CFC-13 CClF3 HCFC-31 CH2ClF

CFC-112 CCl2FCCl2F HCFC-123 CHCl2CF3

CFC-112a CClF2CCl3 HCFC-123a CHClFCF2Cl

CFC-113 CCl2FCClF2 HCFC-123b CHF2CCl2F

CFC-113a CCl3CF3 HCFC-124 CHClFCF3

CFC-114 CClF2CClF2 HCFC-124a CHF2CClF2

CFC-114a CCl2FCF3 HCFC-133a CH2ClCF3

CFC-115 CClF2CF3 HCFC-141b CH3CCl2F

CFC-316c cyclic C4Cl2F6 HCFC-142b CH3CClF2

HCFC-225ca CHCl2CF2CF3

HALONS HCFC-225cb CHClFCF2CClF2

halon-1202 CBr2F2 HCFC-234fb CF3CH2CCl2F

halon-1211 CBrClF2 HCFC-243cc CH3CF2CCl2F

halon-1301 CBrF3 HCFC-1233zd(E) (E)-CHClCHCF3

halon-2402 CBrF2CBrF2

halon-2311(Halothane) CHBrClCF3

HYDROFLUOROCARBONS (HFCS)

HFC-23 CHF3 HFC-245cb CH3CF2CF3

HFC-32 CH2F2 HFC-245ca CH2FCF2CHF2

HFC-41 CH3F HFC-245ea CHF2CHFCHF2

HFC-125 CHF2CF3 HFC-245eb CH2FCHFCF3

HFC-134 CHF2CHF2 HFC-245fa CHF2CH2CF3

HFC-134a CH2FCF3 HFC-263fb CH3CH2CF3

HFC-143 CH2FCHF2 HFC-272ca CH3CF2CH3

HFC-143a CH3CF3 HFC-281ea CH3CHFCH3

HFC-152 CH2FCH2F HFC-365mfc CH3CF2CH2CF3

HFC-152a CH3CHF2 HFC-356mcf CH2FCH2CF2CF3

HFC-161 CH3CH2F HFC-356mff CF3CH2CH2CF3

HFC-227ea CF3CHFCF3 HFC-338pcc CHF2CF2CF2CHF2

HFC-236cb CH2FCF2CF3 HFC-43-10mee CF3CHFCHFCF2CF3

HFC-236ea CHF2CHFCF3 HFC-458mfcf CF3CH2CF2CH2CF3

HFC-236fa CF3CH2CF3 HFC-55-10mcff CF3CF2CH2CH2CF2CF3

CHLOROCARBONS BROMOCARBONS

CH3Cl methyl chloride, chloromethane CH3Br methyl bromide, bromomethane

CH2Cl2 dichloromethane, methylene chloride CH2Br2 dibromomethane, methylene bromide

CHCl3 chloroform, trichloromethane CHBr3 bromoform, tribromomethane

CCl4 carbon tetrachloride, CTC CH3CH2Br, C2H5Br ethyl bromide, bromoethane

CHClCCl2 trichloroethylene, trichloroethene, TCE CH2BrCH2Br 1,2 dibromoethane

CCl2CCl2 tetrachloroethene, perchloroethene, PCE CH3CH2CH2Br, n-propyl bromide, n-PB, 

CH3CH2Cl, C2H5Cl ethyl chloride, chloroethane n-C3H7Br, 1-bromopropane

CH2ClCH2Cl 1,2 dichloroethane COBr2 carbonyl bromide

CH3CCl3 methyl chloroform

CH3CHClCH3 isopropylchloride, 2-chloropropane

CH3CH2CH2Cl n-propyl chloride, 1-chloropropane

COCl2, Cl2C(O) phosgene, carbonyl chloride
Chemical Formulae

C.3

IODOCARBONS FLUOROCARBONS

CH3I methyl iodide, iodomethane CF4 (PFC-14) perfluoromethane, 

CH2I2 diiodomethane carbon tetrafluoride

CH3CH2I, C2H5I ethyl iodide, iodoethane C2F6, CF3CF3 (PFC-116) perfluoroethane

CH3CHICH3 isopropyl iodide, 2-iodopropane C3F8, CF3CF2CF3 (PFC-218) perfluoropropane

CH3CH2CH2I (n-C3H7I) n-propyl iodide, 1-iodopropane c-C3F6 (PFC-C216) perfluorocyclopropane

C4F10 (PFC-31-10) perfluorobutane

OTHERS c-C4F8 (PFC-C318) perfluorocyclobutane

CHBr2Cl dibromochloromethane C5F12 (PFC-41-12) perfluoropentane

CH2BrCl bromochloromethane C6F14 (PFC-51-14) perfluorohexane

CHBrCl2 bromodichloromethane C7H16 (PFC-61-16) perflouoroheptane

CH2BrI bromoiodomethane C10F18 perfluorodecalin

CHBrF2 bromodifluoromethane COF2 carbonyl fluoride

CH2ClI chloroiodomethane CH2FC(O)OH monofluoroacetic acid (MFA)

CF3I trifluoroiodomethane CHF2C(O)OH difluoroacetic acid (DFA)

CH2CBrCF3 bromotrifluoropropene CF3C(O)OH trifluoroacetic acid (TFA)

CF3CF2CF2I, C3F7I 1-iodo-heptafluoropropane CF3Ox CF3O + CF3O2 + CF3O2NO2

COClF chlorofluorocarbonyl

CCl3CHO trichloroacetaldehyde, chloral HYDROFLUORO-OLEFINS

SF5CF3 trifluoromethylsulfurpentafluoride CH2CFCF3 HFO-1234yf

OTHER CHEMICAL SPECIES

O atomic oxygen H atomic hydrogen

O(3

P) atomic oxygen (ground state) H2 molecular hydrogen

O(1

D) atomic oxygen (first excited state) OH hydroxyl radical

O2 molecular oxygen HO2 hydroperoxyl radical

O3 ozone H2O water

Ox odd oxygen (O, O(1

D), O3) or HOx odd hydrogen (H, OH, HO2, H2O2)

oxidant (O3 + NO2)

N atomic nitrogen HNO2, HONO nitrous acid

N2 molecular nitrogen HOONO pernitrous acid

N2O nitrous oxide HNO3 nitric acid

NO nitric oxide NH3 ammonia

NO2 nitrogen dioxide NH4NO3 ammonium nitrate

NO3 nitrogen trioxide, nitrate radical 

N2O5 dinitrogen pentoxide

NOx nitrogen oxides (NO + NO2)

NOy total reactive nitrogen 

 (usually includes NO, NO2, NO3,

 N2O5, ClONO2, HNO4, HNO3)

S atomic sulfur H2S hydrogen sulfide

SO2 sulfur dioxide CS2 carbon disulfide

H2SO4 sulfuric acid COS, OCS carbonyl sulfide

CH3SCH3 DMS, dimethyl sulfide

C carbon atom CO2 carbon dioxide

CO carbon monoxide

CH4 methane CH3OH methyl alcohol, methanol

CH3CH3 ethane

CH3CH2CH3 propane

World Meteorological Organization

Global Ozone Research and Monitoring Project—Report No. 55

SCIENTIFIC ASSESSMENT OF

OZONE DEPLETION: 2014