Data Portal
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 MORTALITY ADDITIONAL AFFECTED POPULATION (1000s)
 COUNTRY     2010 2030 2010 2030
Afghanistan 5-5- 801002030
Albania 77 5511
Algeria 4+4+ 1001503555
Angola 66 25401015
Antigua and Barbuda 66 00
Argentina 5-5- 801001010
Armenia 0+0+ 303044
Australia 0+0+ 3505504565
Austria 1-1- 6065910
Azerbaijan 77 5533
Bahamas 77 100
Bahrain 77 1100
Bangladesh 1-0+ 1,0002,000150200
Barbados 5-5- 1100
Belarus 2+1- 65703030
Belgium 0+0+ 1501502020
Belize 66 1100
Benin 66 101523
Bhutan 4+3- 1500
Bolivia 77 101534
Bosnia and Herzegovina 2+2+ 252533
Botswana 4+3- 51012
Brazil 5-5- 5006005565
Brunei 5-4+ 1100
Bulgaria 0+0+ 908533
Burkina Faso 66 152035
Burundi 5-5- 152558
Cambodia 77 1100
Cameroon 5-5- 3555815
Canada 0+0+ 3004003540
Cape Verde 65- 1100
Central African Republic 5-4+ 101535
Chad 5-5- 152536
Chile 4+4+ 557056
China 0+0+ 15,00025,000500650
Colombia 2+1- 3004502020
Comoros 5-5- 1100
Congo 5-5- 101523
Costa Rica 4+4+ 151511
Cote d'Ivoire 5-5- 4060815
Croatia 0+0+ 404022
Cuba 1-0+ 8510078
Cyprus 5-5- 1511
Czech Republic 0+0+ 10010066
Denmark 0+0+ 757578
Djibouti 66 1100
Dominica 3-3- 100
Dominican Republic 4+4+ 30351515
DR Congo 66 851502030
Ecuador 66 202522
Egypt 5-5- 1502004055
El Salvador 77 101023
Equatorial Guinea 5-5- 1100
Eritrea 77 51023
Estonia 4+3- 5511
Ethiopia 77 254059
Fiji 4+4+ 1522
Finland 2+2+ 303066
France 4+4+ 2502506060
Gabon 5-5- 1511
Gambia 75- 1501
Georgia 77 5533
Germany 0+0+ 700750100100
Ghana 65- 3050610
Greece 1-1- 909055
Grenada 77 00
Guatemala 77 101022
Guinea 5-5- 152535
Guinea-Bissau 5-5- 5511
Guyana 5-5- 1100
Haiti 77 101044
Honduras 5-5- 152056
Hungary 1-0+ 808566
Iceland 2+2+ 1100
India 0+0+ 15,00025,0009001,500
Indonesia 1-0+ 1,7503,250300400
Iran 4+3- 300450150200
Iraq 5-5- 701001015
Ireland 2+2+ 303044
Israel 4+4+ 253055
Italy 1-0+ 5005505555
Jamaica 2+2+ 202511
Japan 4+3- 450650150200
Jordan 5-5- 101523
Kazakhstan 0+0+ 3003504545
Kenya 66 4570915
Kiribati 5-5- 00
Kuwait 77 1111
Kyrgyzstan 2+3- 353511
Laos 3-3- 304522
Latvia 4+4+ 5511
Lebanon 5-5- 101501
Lesotho 5-5- 5511
Liberia 77 51012
Libya 5-5- 101523
Lithuania 4+4+ 151511
Luxembourg 2+3- 5500
Macedonia 0+0+ 252533
Madagascar 66 254058
Malawi 65- 203557
Malaysia 5-5- 50751515
Maldives 5-4+ 1100
Mali 66 102024
Malta 0+0+ 5500
Marshall Islands 2+2+ 100
Mauritania 66 5512
Mauritius 4+3- 5523
Mexico 5-5- 2503502530
Micronesia 5-5- 100
Moldova 2+2+ 202511
Mongolia 1-1- 202500
Morocco 5-5- 5070610
Mozambique 5-5- 45701020
Myanmar 3-2+ 2004003545
Namibia 5-5- 5523
Nepal 77 254045
Netherlands 0+0+ 1501501515
New Zealand 0+0+ 405546
Nicaragua 5-7 101011
Niger 77 101523
Nigeria 5-5- 30050065100
North Korea 1-0+ 2003003040
Norway 0+0+ 555588
Oman 66 1501
Pakistan 3-3- 9001,25075100
Palau 5-5- 00
Panama 5-5- 101011
Papua New Guinea 77 5501
Paraguay 77 5500
Peru 77 35401010
Philippines 3-3- 450650250300
Poland 2+2+ 2002002020
Portugal 3-3- 505577
Qatar 77 00
Romania 1-1- 15015088
Russia 0+0+ 1,5001,500350350
Rwanda 66 102024
Saint Lucia 5-5- 1100
Saint Vincent 5-5- 00
Samoa 4+4+ 1100
Sao Tome and Principe 5-5- 100
Saudi Arabia 77 20251520
Senegal 77 101523
Seychelles 75- 00
Sierra Leone 77 1500
Singapore 4+3- 152545
Slovakia 5-5- 151511
Slovenia 2+2+ 101511
Solomon Islands 5-7 1100
Somalia 77 101512
South Africa 0+0+ 8001,250150200
South Korea 4+3- 200250150250
Spain 1-1- 3503505555
Sri Lanka 1-0+ 1502504555
Sudan-South Sudan 5-4+ 1002001520
Suriname 65- 1100
Swaziland 4+3- 5523
Sweden 2+1- 65701010
Switzerland 3-3- 404066
Syria 5-5- 40601520
Tajikistan 77 5500
Tanzania 77 3050610
Thailand 4+2+ 2504502025
Timor-Leste 5-5- 1500
Togo 5-5- 101524
Tonga 4+4+ 1100
Trinidad and Tobago 5-5- 1501
Tunisia 5-5- 152512
Turkey 3-3- 3504004040
Turkmenistan 5-5- 101066
Tuvalu 3-3- 00
Uganda 77 3050710
Ukraine 1-0+ 3503504545
United Arab Emirates 66 1111
United Kingdom 0+0+ 850900100100
United States 0+0+ 3,2504,000300400
Uruguay 5-4+ 101011
Uzbekistan 5-5- 556099
Vanuatu 5-5- 1100
Venezuela 5-5- 557556
Vietnam 3-3- 4005505065
Yemen 77 203035
Zambia 5-5- 35501015
Zimbabwe 5-5- 203535
TOTAL51,32878,8355,043,4206,686,035