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
 COUNTRY     2010 2030
Afghanistan 0+0+ 2,0004,0002
Albania 66 110
Algeria 5-5- 3505002
Angola 0+0+ 1,2501,7507
Antigua and Barbuda 88 000
Argentina 88 000
Armenia 66 110
Australia 88 000
Austria 88 000
Azerbaijan 66 15100
Bahamas 88 000
Bahrain 68 000
Bangladesh 5-5- 1,2502,2501
Barbados 99 000
Belarus 79 000
Belgium 99 000
Belize 99 000
Benin 1-1- 3504500
Bhutan 5-3- 10200
Bolivia 5-7 80700
Bosnia and Herzegovina 77 000
Botswana 5-5- 15250
Brazil 99 000
Brunei 99 000
Bulgaria 77 100
Burkina Faso 0+0+ 9001,2501
Burundi 0+0+ 4007500
Cambodia 5-9 10000
Cameroon 0+0+ 9001,2501
Canada 88 000
Cape Verde 5-5- 550
Central African Republic 1-0+ 1502500
Chad 0+0+ 9001,2501
Chile 88 000
China 68 55003
Colombia 88 000
Comoros 2+2+ 20300
Congo 3-3- 801500
Costa Rica 99 000
Cote d'Ivoire 2+1- 5509500
Croatia 99 000
Cuba 99 000
Cyprus 79 000
Czech Republic 99 000
Denmark 99 000
Djibouti 4+3- 15250
Dominica 99 000
Dominican Republic 99 000
DR Congo 0+0+ 3,5006,5004
Ecuador 66 15150
Egypt 66 951500
El Salvador 88 000
Equatorial Guinea 1-1- 25350
Eritrea 4+3- 851500
Estonia 99 000
Ethiopia 0+0+ 3,5006,5004
Fiji 68 100
Finland 88 000
France 88 000
Gabon 4+4+ 20300
Gambia 2+2+ 45650
Georgia 66 110
Germany 88 000
Ghana 1-1- 9001,2501
Greece 99 000
Grenada 99 000
Guatemala 5-5- 1501500
Guinea 0+0+ 4005500
Guinea-Bissau 0+0+ 1001500
Guyana 88 000
Haiti 4+5- 1501000
Honduras 99 000
Hungary 79 000
Iceland 99 000
India 1-0+ 40,00085,00050
Indonesia 88 000
Iran 68 10000
Iraq 5-4+ 3008501
Ireland 88 000
Israel 88 000
Italy 88 000
Jamaica 88 000
Japan 88 000
Jordan 68 500
Kazakhstan 68 100
Kenya 3-2+ 8001,5001
Kiribati 68 100
Kuwait 68 000
Kyrgyzstan 66 1550
Laos 68 3500
Latvia 68 000
Lebanon 68 100
Lesotho 5-3- 25450
Liberia 1-2+ 1502000
Libya 68 500
Lithuania 68 000
Luxembourg 88 000
Macedonia 66 000
Madagascar 3-3- 5007000
Malawi 2+1- 4508000
Malaysia 79 500
Maldives 77 010
Mali 0+0+ 9501,2501
Malta 88 000
Marshall Islands 68 000
Mauritania 1-2+ 1001500
Mauritius 66 110
Mexico 88 000
Micronesia 68 000
Moldova 68 000
Mongolia 68 500
Morocco 66 1502500
Mozambique 3-2+ 5509500
Myanmar 5-4+ 5501,0000
Namibia 65- 15250
Nepal 5-5- 3005500
Netherlands 99 000
New Zealand 99 000
Nicaragua 77 15150
Niger 0+0+ 1,0001,5001
Nigeria 0+0+ 6,7509,2508
North Korea 66 601000
Norway 88 000
Oman 68 100
Pakistan 4+1- 3,2509,2504
Palau 79 000
Panama 99 000
Papua New Guinea 79 3000
Paraguay 99 000
Peru 77 45350
Philippines 79 20001
Poland 77 110
Portugal 99 000
Qatar 79 000
Romania 77 110
Russia 79 500
Rwanda 1-0+ 3506500
Saint Lucia 88 000
Saint Vincent 88 000
Samoa 68 000
Sao Tome and Principe 4+5- 150
Saudi Arabia 79 1500
Senegal 3-3- 3004000
Seychelles 77 000
Sierra Leone 0+0+ 3504500
Singapore 88 000
Slovakia 66 000
Slovenia 88 000
Solomon Islands 68 100
Somalia 0+0+ 5501,0000
South Africa 3-0+ 1,0002,0009
South Korea 68 500
Spain 88 000
Sri Lanka 88 000
Sudan-South Sudan 3-3- 8501,5001
Suriname 99 000
Swaziland 4+3- 15300
Sweden 99 000
Switzerland 99 000
Syria 79 1500
Tajikistan 5-7 45250
Tanzania 3-2+ 1,0002,0001
Thailand 88 000
Timor-Leste 88 000
Togo 2+2+ 1502500
Tonga 68 000
Trinidad and Tobago 88 000
Tunisia 68 1000
Turkey 66 25150
Turkmenistan 66 20150
Tuvalu 68 000
Uganda 1-1- 1,0002,0001
Ukraine 79 100
United Arab Emirates 79 000
United Kingdom 99 000
United States 99 000
Uruguay 99 000
Uzbekistan 77 55350
Vanuatu 79 000
Venezuela 99 000
Vietnam 79 9000
Yemen 4+4+ 4008500
Zambia 2+1- 4007500
Zimbabwe 5-4+ 1502500
TOTAL82,050156,285127,303