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 ECONOMIC COSTS (MILLION USD PPP)
 COUNTRY     2010 2030
Afghanistan 4+1- 85700
Albania 75- 15100
Algeria 5-4+ 3002,250
Angola 5-4+ 1501,000
Antigua and Barbuda 4+0+ 545
Argentina 65- 5504,500
Armenia 77 545
Australia 77 4501,000
Austria 77 1535
Azerbaijan 77 25200
Bahamas 3-0+ 45350
Bahrain 65- 25200
Bangladesh 4+2+ 6505,500
Barbados 65- 545
Belarus 77 55400
Belgium 77 3585
Belize 3-0+ 1075
Benin 1-0+ 90600
Bhutan 4+1- 10100
Bolivia 3-0+ 1501,250
Bosnia and Herzegovina 66 1090
Botswana 66 110
Brazil 66 9006,750
Brunei 3-0+ 75650
Bulgaria 66 40250
Burkina Faso 3-0+ 70450
Burundi 0+0+ 60400
Cambodia 3-0+ 1001,500
Cameroon 2+0+ 2001,250
Canada 66 3580
Cape Verde 3-0+ 545
Central African Republic 0+0+ 50350
Chad 4+0+ 60400
Chile 66 150800
China 66 5,50055,000
Colombia 65- 3002,500
Comoros 74+ 15
Congo 4+1- 50350
Costa Rica 5-3- 100850
Cote d'Ivoire 3-0+ 150900
Croatia 66 25150
Cuba 4+2+ 2502,000
Cyprus 66 11
Czech Republic 66 25100
Denmark 88 -25-60
Djibouti 2+0+ 1070
Dominica 3-0+ 525
Dominican Republic 5-4+ 1501,000
DR Congo 4+2+ 60400
Ecuador 5-3- 2001,500
Egypt 99 -350-2,750
El Salvador 5-4+ 60500
Equatorial Guinea 66 550
Eritrea 3-0+ 1585
Estonia 66 520
Ethiopia 2+0+ 4503,000
Fiji 4+2+ 1075
Finland 88 -15-35
France 66 300700
Gabon 0+0+ 3002,000
Gambia 2+0+ 15100
Georgia 65- 15100
Germany 77 90200
Ghana 3-0+ 2001,500
Greece 66 200450
Grenada 4+0+ 535
Guatemala 5-4+ 100850
Guinea 0+0+ 150900
Guinea-Bissau 0+0+ 15100
Guyana 5-4+ 555
Haiti 4+1- 35300
Honduras 4+2+ 75600
Hungary 66 30150
Iceland 88 -1
India 3-0+ 15,000100,000
Indonesia 64+ 1,2509,500
Iran 5-4+ 1,2508,750
Iraq 5-4+ 1501,000
Ireland 66 15
Israel 66 80450
Italy 66 300650
Jamaica 0+0+ 2502,000
Japan 66 4501,000
Jordan 65- 20150
Kazakhstan 99 -55-400
Kenya 75- 60400
Kiribati 3-0+ 120
Kuwait 65- 95750
Kyrgyzstan 5-4+ 15100
Laos 1-0+ 901,000
Latvia 66 530
Lebanon 5-4+ 70550
Lesotho 4+2+ 1055
Liberia 0+0+ 15100
Libya 5-4+ 1501,000
Lithuania 66 15100
Luxembourg 66 1
Macedonia 65- 15100
Madagascar 1-0+ 100800
Malawi 0+0+ 1501,000
Malaysia 5-4+ 5004,000
Maldives 5-4+ 125
Mali 0+0+ 1501,000
Malta 66 1
Marshall Islands 1-0+ 115
Mauritania 1-0+ 40250
Mauritius 5-4+ 25200
Mexico 65- 1,2507,750
Micronesia 1-0+ 530
Moldova 5-4+ 1590
Mongolia 66 115
Morocco 4+2+ 4003,000
Mozambique 2+0+ 100800
Myanmar 4+2+ 2001,500
Namibia 65- 1080
Nepal 3-0+ 1501,250
Netherlands 66 50100
New Zealand 88 -5-10
Nicaragua 4+1- 55450
Niger 1-0+ 65450
Nigeria 4+2+ 9006,250
North Korea 66 10100
Norway 88 -5-15
Oman 65- 60500
Pakistan 3-0+ 1,50015,000
Palau 1-0+ 110
Panama 66 20150
Papua New Guinea 4+1- 45350
Paraguay 2+0+ 1501,250
Peru 65- 2502,000
Philippines 5-4+ 5504,500
Poland 66 90500
Portugal 66 65150
Qatar 66 110
Romania 66 100800
Russia 66 4002,750
Rwanda 0+0+ 100750
Saint Lucia 4+1- 550
Saint Vincent 4+1- 530
Samoa 4+0+ 530
Sao Tome and Principe 1-0+ 115
Saudi Arabia 66 100950
Senegal 0+0+ 2501,750
Seychelles 5-3- 530
Sierra Leone 1-0+ 30200
Singapore 88
Slovakia 66 1050
Slovenia 66 530
Solomon Islands 3-0+ 560
Somalia 1-0+ 35250
South Africa 65- 5503,750
South Korea 77 5503,250
Spain 77 350850
Sri Lanka 75- 100900
Sudan-South Sudan 0+0+ 6505,000
Suriname 65- 535
Swaziland 4+1- 15100
Sweden 99 -20-40
Switzerland 77 1025
Syria 75- 90700
Tajikistan 75- 15100
Tanzania 1-0+ 3502,500
Thailand 4+2+ 1,25010,000
Timor-Leste 4+1- 1080
Togo 0+0+ 55400
Tonga 3-0+ 525
Trinidad and Tobago 66 1075
Tunisia 5-4+ 1501,000
Turkey 5-5- 1,2503,000
Turkmenistan 75- 40300
Tuvalu 3-0+ 1
Uganda 3-0+ 1501,000
Ukraine 66 1501,250
United Arab Emirates 65- 2001,500
United Kingdom 77 60150
United States 77 1,0002,500
Uruguay 75- 30250
Uzbekistan 4+2+ 2001,500
Vanuatu 3-0+ 540
Venezuela 65- 3502,750
Vietnam 5-3- 5506,000
Yemen 5-3- 100800
Zambia 3-0+ 85600
Zimbabwe 1-0+ 75500
TOTAL48,531344,777