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) LOSS IN WATER RUNOFF (km³)
 COUNTRY     2010 2030 2010 2030
Afghanistan 5-4+ 3525015
Albania 5-3- 3525001
Algeria 77 15950
Angola 75- 7045011
Antigua and Barbuda 5-3- 120
Argentina 99 -150-1,250-0-1
Armenia 2+0+ 7050001
Australia 65- 7502,00011
Austria 0+0+ 2,0006,00011
Azerbaijan 5-4+ 10080001
Bahamas 5-3- 15100
Bahrain 99 -1-5
Bangladesh 99 -25-200-1-1
Barbados 5-3- 1070
Belarus 3-0+ 4002,50011
Belgium 5-4+ 3501,00001
Belize 0+0+ 352500
Benin 65- 107501
Bhutan 99 -85-700-1-1
Bolivia 0+0+ 3502,50011
Bosnia and Herzegovina 5-3- 403000
Botswana 75- 201000
Brazil 99 -1,250-10,000-5-10
Brunei 99 -55-450-0
Bulgaria 0+0+ 6004,00011
Burkina Faso 66 1150
Burundi 88 -1-10-0-0
Cambodia 88 -15-150-0-1
Cameroon 88 -35-250-1-1
Canada 88 -2,500-7,250-1-1
Cape Verde 66 15
Central African Republic 88 -5-25-0-1
Chad 88 -25-150-1-1
Chile 5-3- 4003,25015
China 99 -5,750-60,000-30-55
Colombia 99 -250-2,000-1-5
Comoros 99 -1-1
Congo 99 -5-50-0
Costa Rica 3-0+ 1501,00011
Cote d'Ivoire 5-3- 4530015
Croatia 0+0+ 7004,75011
Cuba 5-3- 1501,250
Cyprus 77 515
Czech Republic 1-0+ 1,2509,00011
Denmark 88 -65-200
Djibouti 88 -1-5
Dominica 5-3- 110
Dominican Republic 5-3- 100950
DR Congo 99 -20-100-1-5
Ecuador 99 -750-5,500-1-5
Egypt 77 115
El Salvador 3-0+ 1501,0000
Equatorial Guinea 88 -5-35
Eritrea 88
Estonia 88 -100-800-0-1
Ethiopia 88 -100-650-5-5
Fiji 65- 120
Finland 99 -1,000-3,000-1-1
France 1-0+ 9,00025,000510
Gabon 88 -1-10
Gambia 66 15
Georgia 0+0+ 2001,25011
Germany 4+2+ 5,00015,00015
Ghana 66 105500
Greece 3-0+ 9002,75011
Grenada 5-3- 115
Guatemala 4+1- 1501,25011
Guinea 5-4+ 106001
Guinea-Bissau 88 -1
Guyana 4+1- 15100
Haiti 5-3- 15100
Honduras 4+1- 8065011
Hungary 3-0+ 5003,50011
Iceland 88 -25-70
India 88 -2,000-15,000-15-35
Indonesia 88 -950-7,500-10-20
Iran 66 3002,25011
Iraq 66 55500
Ireland 88 -250-700-0-0
Israel 66 1065
Italy 5-4+ 2,2506,75015
Jamaica 5-3- 35250
Japan 99 -4,250-10,000-1-5
Jordan 77 110
Kazakhstan 99 -50-350-0-0
Kenya 99 -65-400-1-5
Kiribati 75- 1
Kuwait 99 -1
Kyrgyzstan 3-0+ 4030011
Laos 88 -70-750-1-1
Latvia 88 -55-350-0
Lebanon 66 110
Lesotho 3-0+ 106511
Liberia 66 11
Libya 66 15
Lithuania 88 -20-150
Luxembourg 5-4+ 50150
Macedonia 0+0+ 10085001
Madagascar 88 -1-5
Malawi 88 -1-15-0
Malaysia 88 -800-6,000-1-5
Maldives 88 -10-60
Mali 5-4+ 159511
Malta 2+0+ 40100
Marshall Islands 65- 1
Mauritania 5-4+ 54000
Mauritius 88 -10-65
Mexico 4+1- 4,00030,0002035
Micronesia 75- 1
Moldova 3-0+ 3020001
Mongolia 88 -1-10
Morocco 66 10700
Mozambique 88 -1-5
Myanmar 88 -75-600-1-5
Namibia 65- 10550
Nepal 99 -25-200-1-1
Netherlands 77 1505000
New Zealand 99 -90-250-0
Nicaragua 1-0+ 7560011
Niger 88 -10-55-1-1
Nigeria 88 -65-400-1-1
North Korea 88 -20-200-1-1
Norway 88 -1,250-4,000-1-1
Oman 88 -25-200-0
Pakistan 88 -10-60-0
Palau 65- 1
Panama 2+0+ 2001,25011
Papua New Guinea 88 -100-850-5-5
Paraguay 88 -25-200-0-1
Peru 88 -200-1,500-1-1
Philippines 88 -45-350-1-1
Poland 5-4+ 9006,25011
Portugal 5-4+ 25070000
Qatar 88 -10-55
Romania 2+0+ 1,0006,75015
Russia 88 -2,500-15,000-5-10
Rwanda 88 -5-40-0-1
Saint Lucia 5-3- 120
Saint Vincent 5-3- 115
Samoa 75- 15
Sao Tome and Principe 99 -1
Saudi Arabia 77 201500
Senegal 77 15
Seychelles 99 -1-5
Sierra Leone 99 -1
Singapore 99 -250-2,000
Slovakia 0+0+ 7005,00011
Slovenia 0+0+ 4002,75001
Solomon Islands 65- 15
Somalia 99 -5-40-1-1
South Africa 5-4+ 5503,50055
South Korea 88 -85-650-0-1
Spain 2+0+ 4,75015,00055
Sri Lanka 88 -1-20
Sudan-South Sudan 88 -40-300-1-1
Suriname 65- 115
Swaziland 4+2+ 10700
Sweden 88 -1,500-4,500-1-1
Switzerland 4+1- 8002,25011
Syria 77 10650
Tajikistan 3-0+ 4530011
Tanzania 88 -200-1,250-5-10
Thailand 88 -300-2,250-1-5
Timor-Leste 88 -5-35
Togo 65- 53001
Tonga 75- 15
Trinidad and Tobago 75- 151500
Tunisia 77 115
Turkey 4+2+ 1,7505,5001020
Turkmenistan 66 10750
Tuvalu 65-
Uganda 99 -70-450-1-5
Ukraine 3-0+ 1,0007,00015
United Arab Emirates 88 -15-150
United Kingdom 88 -1,250-4,000-1-1
United States 88 -1,250-4,000-1-1
Uruguay 88 -10-70
Uzbekistan 65- 4030011
Vanuatu 75- 15
Venezuela 5-4+ 3502,75015
Vietnam 88 -100-1,000-1-1
Yemen 88 -10-60-0-0
Zambia 88 -1-5
Zimbabwe 4+1- 3020015
TOTAL13,42316,160-31-67