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) ADDITIONAL AFFECTED POPULATION (1000s) ADDITIONAL LAND DEGRADED (km²) (CUMULATIVE)
 COUNTRY     2010 2030 2010 2030 2010 2030
Afghanistan 5-5- 53025805001,000
Albania 0+0+ 201003580300600
Algeria 5-4+ 45350
Angola 5-3- 2515020651,2502,500
Antigua and Barbuda 5-4+ 10155
Argentina 88 -250-2,000-55-150-3,750-7,500
Armenia 88
Australia 2+0+ 5001,50020457,00015,000
Austria 88
Azerbaijan 88 -10-1-5-10
Bahamas 66 10015
Bahrain 65- 525
Bangladesh 77 520150400150300
Barbados 99
Belarus 99
Belgium 99
Belize 4+2+ 15002040
Benin 0+0+ 151001003501,5003,000
Bhutan 88
Bolivia 88
Bosnia and Herzegovina 0+0+ 654501002501,7503,250
Botswana 88 -5-25
Brazil 66 70550501002,2504,500
Brunei 88
Bulgaria 65- 10801020150350
Burkina Faso 4+1- 1050
Burundi 99 -1-1
Cambodia 99
Cameroon 77 110
Canada 99 -5-1000-35-70
Cape Verde 4+2+ 1561550100
Central African Republic 66 1
Chad 66 15
Chile 5-4+ 4030015407001,500
China 66 757503006002,0004,000
Colombia 66 110133575
Comoros 88 -1-30-90-75-150
Congo 66 15
Costa Rica 3-0+ 25200501505501,250
Cote d'Ivoire 4+1- 1595
Croatia 0+0+ 1008001503002,0003,750
Cuba 3-0+ 654501502501,2502,500
Cyprus 65- 5105104085
Czech Republic 99
Denmark 99
Djibouti 99 -1
Dominica 0+0+ 110132035
Dominican Republic 4+2+ 302001503006501,250
DR Congo 66 15
Ecuador 5-4+ 201502560400850
Egypt 3-2+ 2501,2501504002,0004,000
El Salvador 88
Equatorial Guinea 66 15
Eritrea 88 -1-1
Estonia 88
Ethiopia 88 -10-65
Fiji 88
Finland 88
France 5-4+ 4001,2506001,5005,25010,000
Gabon 66 15
Gambia 4+1- 110
Georgia 99
Germany 99
Ghana 5-4+ 1065752007501,500
Greece 4+2+ 1003501002501,5002,750
Grenada 88
Guatemala 88
Guinea 4+1- 530
Guinea-Bissau 4+1- 15
Guyana 99
Haiti 99
Honduras 4+2+ 10752565350750
Hungary 88
Iceland 88
India 88 -40-300-650-1,500-1,750-3,500
Indonesia 88 -5-50-50-100-400-750
Iran 66 120143570
Iraq 65- 15100
Ireland 99
Israel 75- 25200
Italy 5-3- 4501,2501,0002,5006,25010,000
Jamaica 75- 120154065150
Japan 77 40100150300500950
Jordan 75- 530
Kazakhstan 99 -5-450-2-150-300
Kenya 99 -10-50
Kiribati 99
Kuwait 99
Kyrgyzstan 99
Laos 99 -10-1-15-30
Latvia 99
Lebanon 75- 550
Lesotho 99 -1-1-2-15-30
Liberia 4+1- 15
Libya 5-4+ 15100
Lithuania 88
Luxembourg 88
Macedonia 88
Madagascar 4+2+ 1045351001,0002,000
Malawi 88 -1-10
Malaysia 88
Maldives 88
Mali 4+1- 545
Malta 5-5- 1520451530
Marshall Islands 99
Mauritania 77 1002550
Mauritius 99 -5-40-55-150-90-200
Mexico 4+1- 6004,5006001,50010,00020,000
Micronesia 99
Moldova 99
Mongolia 99
Morocco 5-4+ 30200852001,2502,500
Mozambique 88 00-5-10
Myanmar 88 -5-35-50-100-650-1,250
Namibia 66 1001525
Nepal 88
Netherlands 88
New Zealand 0+0+ 150500451002,7505,750
Nicaragua 0+0+ 1510025655501,000
Niger 4+1- 530
Nigeria 5-4+ 603507502,0004,2508,500
North Korea 88 -1-10-20-45-100-200
Norway 66 11001020
Oman 66 0
Pakistan 5-5- 704003501,0001,5003,250
Palau 99
Panama 0+0+ 90700752001,5003,250
Papua New Guinea 88
Paraguay 88
Peru 5-4+ 5540025651,2502,250
Philippines 88
Poland 88
Portugal 65- 309055100450900
Qatar 99
Romania 99
Russia 75- 2001,25025503,2506,250
Rwanda 99 -1-10
Saint Lucia 99
Saint Vincent 99
Samoa 99
Sao Tome and Principe 77
Saudi Arabia 75- 75550
Senegal 4+2+ 1050501507501,500
Seychelles 88 -1
Sierra Leone 4+1- 110
Singapore 99
Slovakia 99
Slovenia 5-4+ 10751025100250
Solomon Islands 88
Somalia 88 00-1-5
South Africa 88 -5-25-3-7-90-200
South Korea 88 -250-1,750-1,000-2,000-2,000-4,000
Spain 5-4+ 2006002504502,7505,500
Sri Lanka 88
Sudan-South Sudan 5-4+ 20150
Suriname 88
Swaziland 88 -5-20-10-25-150-300
Sweden 88
Switzerland 88
Syria 65- 1595
Tajikistan 99
Tanzania 99 00-1-5
Thailand 99 -80-650-250-600-2,000-4,000
Timor-Leste 0+0+ 25200501006501,250
Togo 0+0+ 10451504001,2502,500
Tonga 88
Trinidad and Tobago 88
Tunisia 5-3- 302003075450950
Turkey 4+2+ 3509506001,5006,25015,000
Turkmenistan 88 00-1
Tuvalu 88
Uganda 88 -5-30
Ukraine 0+0+ 4502,7507001,0009,00020,000
United Arab Emirates 65- 30200
United Kingdom 99
United States 77 200700551501,7503,500
Uruguay 4+1- 20150715400800
Uzbekistan 99
Vanuatu 99
Venezuela 99
Vietnam 99 -80-850-950-2,000-3,500-7,250
Yemen 99 -1-1-1-5-30-55
Zambia 99 -1-15
Zimbabwe 99 -1-10
TOTAL4,49020,6724,346,46910,894,91075,624153,324