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 0+0+ 5,7507,50056
Albania 88
Algeria 5-5- 55060000
Angola 0+2+ 1,7502,00000
Antigua and Barbuda 66 1100
Argentina 66 30050001
Armenia 88
Australia 88
Austria 88
Azerbaijan 88
Bahamas 66 1100
Bahrain 66 1100
Bangladesh 1-1- 9,75015,0001015
Barbados 77 1100
Belarus 99
Belgium 99
Belize 77 1500
Benin 1-2+ 60065000
Bhutan 0+0+ 6015000
Bolivia 4+2+ 30065000
Bosnia and Herzegovina 88
Botswana 66 152500
Brazil 66 1,2502,50035
Brunei 88
Bulgaria 88
Burkina Faso 0+1- 1,7501,75000
Burundi 3-2+ 40060000
Cambodia 5-5- 20030001
Cameroon 0+1- 1,5001,75000
Canada 99
Cape Verde 5-7 5500
Central African Republic 2+1- 25040000
Chad 0+0+ 1,2501,50000
Chile 66 8515000
China 66 1,7502,750710
Colombia 66 25045000
Comoros 3-4+ 353500
Congo 4+4+ 15020000
Costa Rica 66 51000
Cote d'Ivoire 3-2+ 8501,25000
Croatia 88
Cuba 88
Cyprus 66 1100
Czech Republic 88
Denmark 88
Djibouti 3-3- 405000
Dominica 77 1100
Dominican Republic 75- 10020000
DR Congo 1-1- 4,7507,50034
Ecuador 5-5- 20035000
Egypt 77 60075000
El Salvador 5-5- 7515000
Equatorial Guinea 1-3- 505000
Eritrea 5-5- 8515000
Estonia 99
Ethiopia 3-3- 3,2505,25023
Fiji 77 5500
Finland 99
France 99
Gabon 4+5- 404500
Gambia 2+3- 859000
Georgia 99
Germany 99
Ghana 3-4+ 90095000
Greece 88
Grenada 66 1100
Guatemala 4+2+ 5001,00001
Guinea 0+2+ 80085000
Guinea-Bissau 0+0+ 20020000
Guyana 5-5- 101500
Haiti 2+1- 60080001
Honduras 75- 8015000
Hungary 99
Iceland 99
India 0+0+ 100,000250,000150250
Indonesia 4+3- 7,50010,000915
Iran 77 20040001
Iraq 4+3- 8502,00001
Ireland 99
Israel 99
Italy 99
Jamaica 5-5- 356500
Japan 99
Jordan 77 204500
Kazakhstan 99
Kenya 5-4+ 8001,25000
Kiribati 66 1100
Kuwait 66 1500
Kyrgyzstan 88
Laos 5-5- 8510000
Latvia 99
Lebanon 77 51500
Lesotho 5-5- 305000
Liberia 1-3- 25025000
Libya 77 152000
Lithuania 99
Luxembourg 99
Macedonia 99
Madagascar 4+5- 60065000
Malawi 3-3- 6501,00000
Malaysia 77 7510000
Maldives 75- 51000
Mali 0+2+ 1,2501,50000
Malta 88
Marshall Islands 65- 1100
Mauritania 3-4+ 15015000
Mauritius 66 5500
Mexico 65- 1,0001,75024
Micronesia 77 1100
Moldova 99
Mongolia 77 51500
Morocco 5-5- 50060000
Mozambique 3-2+ 1,0001,75001
Myanmar 0+0+ 5,2507,75058
Namibia 5-5- 304500
Nepal 1-1- 2,0002,50022
Netherlands 99
New Zealand 99
Nicaragua 75- 7015000
Niger 0+2+ 1,5001,75000
Nigeria 1-2+ 10,00010,00055
North Korea 0+0+ 1,7502,50022
Norway 88
Oman 66 1500
Pakistan 1-0+ 10,00025,000920
Palau 66 0
Panama 66 203500
Papua New Guinea 5-5- 9520000
Paraguay 77 409000
Peru 5-4+ 6501,25001
Philippines 66 55070023
Poland 88
Portugal 88
Qatar 66 100
Romania 88
Russia 88
Rwanda 4+4+ 35055000
Saint Lucia 66 1100
Saint Vincent 66 1100
Samoa 66 1100
Sao Tome and Principe 4+5- 5500
Saudi Arabia 77 5515000
Senegal 3-4+ 55055000
Seychelles 66 1100
Sierra Leone 0+0+ 65070000
Singapore 88
Slovakia 88
Slovenia 88
Solomon Islands 66 5500
Somalia 0+0+ 1,7502,00011
South Africa 5-3- 1,2501,75001
South Korea 77 559000
Spain 99
Sri Lanka 75- 20035000
Sudan-South Sudan 0+1- 3,2504,00023
Suriname 77 1500
Swaziland 5-5- 203500
Sweden 99
Switzerland 99
Syria 77 5010000
Tajikistan 99
Tanzania 4+3- 1,5002,50001
Thailand 5-5- 1,0001,50012
Timor-Leste 4+3- 355000
Togo 3-4+ 25030000
Tonga 66 1100
Trinidad and Tobago 66 51000
Tunisia 66 758500
Turkey 88
Turkmenistan 88
Tuvalu 66 0
Uganda 3-3- 1,5002,25001
Ukraine 99
United Arab Emirates 77 51000
United Kingdom 99
United States 99
Uruguay 77 254000
Uzbekistan 99
Vanuatu 77 1100
Venezuela 77 9015000
Vietnam 77 20025001
Yemen 2+4+ 1,2501,50011
Zambia 3-3- 60090000
Zimbabwe 5-4+ 25040000
TOTAL203,151403,241251,571404,828