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 1-1- 50085001
Albania 99
Algeria 5-5- 15020000
Angola 0+0+ 50090012
Antigua and Barbuda 66
Argentina 66 405500
Armenia 65- 101000
Australia 99
Austria 99
Azerbaijan 77 202500
Bahamas 77 00
Bahrain 77 1100
Bangladesh 5-5- 60080001
Barbados 77 00
Belarus 99
Belgium 99
Belize 77 00
Benin 0+0+ 25035000
Bhutan 4+3- 51000
Bolivia 5-5- 457500
Bosnia and Herzegovina 99
Botswana 4+4+ 151500
Brazil 66 20030000
Brunei 66 00
Bulgaria 88
Burkina Faso 0+0+ 30060000
Burundi 0+0+ 20030000
Cambodia 4+4+ 10015000
Cameroon 0+0+ 50070001
Canada 88
Cape Verde 5-5- 1500
Central African Republic 0+0+ 9015000
Chad 0+0+ 30055000
Chile 66 101500
China 66 80085022
Colombia 66 557500
Comoros 0+0+ 152500
Congo 3-3- 407500
Costa Rica 77 5500
Cote d'Ivoire 0+0+ 45060001
Croatia 88
Cuba 66 5500
Cyprus 66 00
Czech Republic 88
Denmark 88
Djibouti 5-5- 5500
Dominica 77
Dominican Republic 77 152000
DR Congo 0+0+ 2,0003,75036
Ecuador 66 203000
Egypt 66 20030000
El Salvador 66 101500
Equatorial Guinea 0+0+ 152500
Eritrea 5-5- 253500
Estonia 99
Ethiopia 0+0+ 2,0003,00035
Fiji 88
Finland 88
France 88
Gabon 4+4+ 101500
Gambia 3-3- 152500
Georgia 77 5500
Germany 99
Ghana 5-5- 9515000
Greece 99
Grenada 77 0
Guatemala 5-5- 509000
Guinea 0+0+ 25040000
Guinea-Bissau 0+0+ 6510000
Guyana 66 1100
Haiti 0+0+ 20030000
Honduras 65- 203500
Hungary 99
Iceland 99
India 5-5- 6,5008,0001015
Indonesia 77 55065011
Iran 77 659000
Iraq 5-5- 15025000
Ireland 99
Israel 77 1500
Italy 99
Jamaica 77 51000
Japan 77 252500
Jordan 77 101500
Kazakhstan 77 404500
Kenya 5-5- 20030000
Kiribati 99
Kuwait 77 1100
Kyrgyzstan 5-5- 203000
Laos 4+4+ 506500
Latvia 88
Lebanon 66 5500
Lesotho 4+4+ 152000
Liberia 0+0+ 9015000
Libya 66 51000
Lithuania 88
Luxembourg 88
Macedonia 88
Madagascar 4+3- 20030000
Malawi 0+0+ 40065001
Malaysia 66 101500
Maldives 66 1100
Mali 1-1- 25040000
Malta 99
Marshall Islands 99
Mauritania 2+2+ 457500
Mauritius 66 1100
Mexico 66 304500
Micronesia 88
Moldova 88
Mongolia 5-5- 101000
Morocco 77 405500
Mozambique 1-1- 40055000
Myanmar 5-5- 25030000
Namibia 5-5- 101500
Nepal 5-5- 10020000
Netherlands 99
New Zealand 99
Nicaragua 77 152000
Niger 0+0+ 45080001
Nigeria 0+0+ 3,5005,25058
North Korea 5-5- 9010000
Norway 99
Oman 77 1100
Pakistan 5-5- 7001,00011
Palau 99
Panama 77 5500
Papua New Guinea 99
Paraguay 77 152500
Peru 77 557500
Philippines 77 20025000
Poland 99
Portugal 99
Qatar 77 00
Romania 99
Russia 77 20020000
Rwanda 1-1- 15025000
Saint Lucia 77 00
Saint Vincent 77
Samoa 99
Sao Tome and Principe 3-3- 1100
Saudi Arabia 77 152500
Senegal 4+4+ 10015000
Seychelles 66 00
Sierra Leone 0+0+ 15030000
Singapore 66 1100
Slovakia 88
Slovenia 88
Solomon Islands 88
Somalia 1-1- 15025000
South Africa 2+1- 70070022
South Korea 77 5500
Spain 99
Sri Lanka 77 252500
Sudan-South Sudan 4+4+ 35055000
Suriname 66 1100
Swaziland 4+3- 101000
Sweden 99
Switzerland 99
Syria 77 305000
Tajikistan 4+4+ 558000
Tanzania 0+0+ 8001,25012
Thailand 66 405000
Timor-Leste 5-5- 5500
Togo 3-2+ 6510000
Tonga 88
Trinidad and Tobago 66 1100
Tunisia 5-5- 456000
Turkey 77 10015000
Turkmenistan 5-5- 253500
Tuvalu 99
Uganda 2+1- 50090001
Ukraine 99
United Arab Emirates 77 5500
United Kingdom 99
United States 99
Uruguay 77 1500
Uzbekistan 5-5- 9015000
Vanuatu 99
Venezuela 77 254000
Vietnam 77 708500
Yemen 5-4+ 15030000
Zambia 1-0+ 25040000
Zimbabwe 4+4+ 8510000
TOTAL28,91542,04451,83578,009