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Confidence shows the level of coni dence that the research team attributes to the indicator, based on a multi-point assessment. Judgements are made in relation to the set of indicators that make up the Monitor assessment only; so, for example, the research team has more coni dence in indicators labelled "Robust" than in indicators labelled "Speculative". Some experts may however consider the robust indicators to still possess inadequate coni dence, or speculative indicators to exceed simple speculation. A 3-point scale is used to evaluate whether each criterion reviewed contributes or detracts from the overall level of coni dence. Confidence shows the level of coni dence that the research team attributes to the indicator, based on a multi-point assessment. Judgements are made in relation to the set of indicators that make up the Monitor assessment only; so, for example, the research team has more coni dence in indicators labelled "Robust" than in indicators labelled "Speculative". Some experts may however consider the robust indicators to still possess inadequate coni dence, or speculative indicators to exceed simple speculation. A 3-point scale is used to evaluate whether each criterion reviewed contributes or detracts from the overall level of coni dence. Severity shows the scale of the overall or absolute global impact of a given indicator and the breadth of effects internationally. "Major" impacts might involve, for example, tens of billions of dollars of economic damage or over 100,000 deaths on average per year. Other indicators estimate 
much lower levels of damage or even positive net impacts, in which case the severity may be assessed as "Minimal"

Affected Groups indicates the specific population segments or communities particularly affected or susceptible to the impacts of a given indicator. The groups may be socially, economically, geographically or otherwise dei ned depending on the impacts under examination. Injustice shows how unjust or not a given effect is on the global scale. It denotes the level of injustice of a specific effect or set of effects as they are assessed by one of the Monitor's indicators. Injustice is highest when the affected countries have least responsibility for climate change and at its lowest when impacts are shared the most among countries with high responsibility. The four-point score is dei ned by statistical quartiles, so the level of injustice is also relative only to the Monitor's Climate section indicators themselves. Responsibility for climate change is based on total country GHG emissions from 1990-2005 (Mueller et al, 2007). Priority shows the amount of support a specific effect area has received through international climate funding. It denotes the level of priority that the effect or set of effects assessed by one Monitor indicator has, as rel ected in international climate i nance expenditures for adaptation."High priority" denotes higher levels of funding from developed countries, targeting the issue in affected developing countries."Low" or"no priority" is given to concerns for which i nancial support has been marginal or virtually absent. The OECD Creditor Reporting System sub-sector l ows for 2010 have been used as the basis for the analysis (OECD CRS, 2012). High priority Low priority Not a priority The Millennium Development Goals (MDGs) represent the international community's eight primary objectives for poverty reduction to be achieved by 2015. The MDG Effect indicates an impact for specific MDGs. One of the eight goals relates to an international partnership for development and is not relevant to the Monitor's impact analysis. Any of the other seven goals are highlighted whenever an indicator assesses a Climate or Carbon effect that is understood to specifically undermine one or another of these goals. (For more information on the MDGs visit: www.un.org/millenniumgoals) Millenium Development Goal (MDG): End Poverty and Hunger Millenium Development Goal (MDG): Achieve Universal Primary Education Millenium Development Goal (MDG): Promote Gender Equality Millenium Development Goal (MDG): Reduce Child Mortality Millenium Development Goal (MDG): Improve Maternal Health Millenium Development Goal (MDG): Combat HIV/AIDS & Infectious Diseases Millenium Development Goal (MDG): Ensure Environmental Sustainability
Severity shows the scale of the overall or absolute global impact of a given indicator and the breadth of effects internationally. "Major" impacts might involve, for example, tens of billions of dollars of economic damage or over 100,000 deaths on average per year. Other indicators estimate 
much lower levels of damage or even positive net impacts, in which case the severity may be assessed as "Minimal"

Affected Groups indicates the specific population segments or communities particularly affected or susceptible to the impacts of a given indicator. The groups may be socially, economically, geographically or otherwise dei ned depending on the impacts under examination. The Millennium Development Goals (MDGs) represent the international community's eight primary objectives for poverty reduction to be achieved by 2015. The MDG Effect indicates an impact for specific MDGs. One of the eight goals relates to an international partnership for development and is not relevant to the Monitor's impact analysis. Any of the other seven goals are highlighted whenever an indicator assesses a Climate or Carbon effect that is understood to specifically undermine one or another of these goals. (For more information on the MDGs visit: www.un.org/millenniumgoals)
ADDITIONAL ECONOMIC COSTS (MILLION USD PPP) ADDITIONAL AFFECTED POPULATION (1000s) NET LOSS OF LAND (km²) (CUMULATIVE)
 COUNTRY     2010 2030 2010 2030 2010 2030
Afghanistan 99
Albania 77 402000055
Algeria 77 95550004070
Angola 77 10065000400950
Antigua and Barbuda 75- 10700011
Argentina 75- 4,50025,00000150300
Armenia 99
Australia 77 8001,500222,5007,250
Austria 99
Azerbaijan 99
Bahamas 4+0+ 3004,0000090200
Bahrain 66 3595001
Bangladesh 65- 1,25020,0004045200450
Barbados 77 10350011
Belarus 99
Belgium 77 35025221015
Belize 4+3- 70400002540
Benin 77 251506085
Bhutan 99
Bolivia 99
Bosnia and Herzegovina 77 15
Botswana 99
Brazil 77 3,25020,000688502,500
Brunei 77 5010000510
Bulgaria 77 3015000
Burkina Faso 99
Burundi 99
Cambodia 75- 2501,750002045
Cameroon 77 1008501145100
Canada 77 1,5003,500017003,000
Cape Verde 4+3- 402000011
Central African Republic 99
Chad 99
Chile 77 5502,750002,0004,500
China 77 15,000150,0004045250350
Colombia 77 3502,25000350600
Comoros 4+2+ 2515000
Congo 66 301500055
Costa Rica 66 906500055100
Cote d'Ivoire 66 1507501025
Croatia 66 150700002535
Cuba 66 5503,000001,5003,500
Cyprus 66 2045001
Czech Republic 88
Denmark 66 5501,00011100250
Djibouti 5-5- 25150001
Dominica 5-4+ 1595001
Dominican Republic 66 10070000150300
DR Congo 66 1575002050
Ecuador 66 1501,00000400900
Egypt 66 1,50010,00023200450
El Salvador 66 5530000515
Equatorial Guinea 66 502502560
Eritrea 3-1- 150650002055
Estonia 75- 2501,2500060200
Ethiopia 99
Fiji 3-2+ 150800001025
Finland 66 85150001550
France 66 7001,25022100150
Gabon 5-4+ 4002,00000150200
Gambia 3-0+ 1507500040100
Georgia 66 603000050100
Germany 66 1,0001,7502385150
Ghana 66 2008501535
Greece 66 250500003050
Grenada 65- 15800011
Guatemala 77 60400001020
Guinea 4+2+ 2501,5000045100
Guinea-Bissau 0+0+ 4002,2500050150
Guyana 3-1- 2001,000001540
Haiti 75- 10065000515
Honduras 75- 2501,50000200500
Hungary 99
Iceland 4+3- 3507000040150
India 77 4,50030,00030354501,000
Indonesia 77 2,75015,00015152,0004,500
Iran 77 3502,00000200400
Iraq 77 201500011
Ireland 77 25050000510
Israel 77 10400011
Italy 77 250550113050
Jamaica 77 75450007595
Japan 77 9502,000665080
Jordan 77 15
Kazakhstan 99
Kenya 77 200900002060
Kiribati 0+0+ 9055000100250
Kuwait 66 5550000515
Kyrgyzstan 88
Laos 88
Latvia 66 904000015
Lebanon 66 159500
Lesotho 88
Liberia 2+0+ 804003075
Libya 66 2001,0000090250
Lithuania 66 4020000110
Luxembourg 88
Macedonia 88
Madagascar 2+0+ 8504,0000045100
Malawi 88
Malaysia 66 9005,75022250450
Maldives 1-0+ 15090000
Mali 88
Malta 66 1500
Marshall Islands 0+0+ 905500011
Mauritania 3-0+ 2501,50000350900
Mauritius 66 2010011
Mexico 66 2,25015,000111,0002,000
Micronesia 2+0+ 3020000
Moldova 88
Mongolia 88
Morocco 66 2501,750111530
Mozambique 2+0+ 1,0005,25034100300
Myanmar 4+3- 1,7509,500223501,250
Namibia 70+ 105,250008502,000
Nepal 88
Netherlands 66 1,2501,25015152025
New Zealand 66 200400004501,250
Nicaragua 4+3- 4002,2500040100
Niger 99
Nigeria 77 5002,500007502,000
North Korea 2+2+ 1,75010,000111030
Norway 66 5001,250002575
Oman 66 100600001020
Pakistan 66 5002,75011100250
Palau 1-0+ 10600011
Panama 65- 3002,00000150400
Papua New Guinea 3-1- 5503,250005501,500
Paraguay 99
Peru 77 1501,000006080
Philippines 77 8504,75034350850
Poland 77 200850001535
Portugal 77 100200002540
Qatar 77 45250001
Romania 77 804000090200
Russia 77 3,00010,000114001,000
Rwanda 99
Saint Lucia 77 106000
Saint Vincent 75- 107000
Samoa 4+3- 2015000
Sao Tome and Principe 2+0+ 1580
Saudi Arabia 66 3001,500004090
Senegal 65- 2001,250003575
Seychelles 77 1560001025
Sierra Leone 3-0+ 2001,000003585
Singapore 66 105500
Slovakia 88
Slovenia 66 1500
Solomon Islands 0+0+ 3001,750001020
Somalia 0+0+ 7503,7500045150
South Africa 66 6003,0000065200
South Korea 66 2,50010,000221015
Spain 66 200450113565
Sri Lanka 66 1501,000014575
Sudan-South Sudan 66 50300001030
Suriname 5-4+ 704000040100
Swaziland 88
Sweden 66 15030000510
Switzerland 88
Syria 66 106500
Tajikistan 88
Tanzania 66 2001,250122570
Thailand 66 1,5006,7505665150
Timor-Leste 3-2+ 9560001
Togo 66 10551025
Tonga 4+3- 201000011
Trinidad and Tobago 77 503000011
Tunisia 77 5002,750002045
Turkey 77 300750015585
Turkmenistan 99
Tuvalu 2+0+ 11000
Uganda 88
Ukraine 66 1,0005,250224595
United Arab Emirates 66 502500015
United Kingdom 66 1,5002,75055100300
United States 66 4,2509,000101510,00025,000
Uruguay 5-5- 5003,25000510
Uzbekistan 99
Vanuatu 0+0+ 1007000011
Venezuela 66 8505,00011200400
Vietnam 5-4+ 4,00040,0002025150300
Yemen 66 1501,2500045150
Zambia 88
Zimbabwe 88
TOTAL85,799525,090249,773288,80431,31377,523