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) SHARE OF WORKFORCE PARTICULARLY AFFECTED (%)
 COUNTRY     2010 2030 2010 2030
Afghanistan 4+1- 3503,0002923
Albania 77 1555
Algeria 77 1007501812
Angola 2+0+ 2,50015,0005243
Antigua and Barbuda 4+1- 252004938
Argentina 99 -150-1,0003829
Armenia 77 5402519
Australia 77 4510066
Austria 99 66
Azerbaijan 77 352003627
Bahamas 4+1- 1501,2504435
Bahrain 77 10603121
Bangladesh 4+1- 3,50030,0004434
Barbados 4+1- 907004535
Belarus 77 159555
Belgium 99 55
Belize 4+1- 403004132
Benin 1-0+ 4002,7505948
Bhutan 4+1- 554004434
Bolivia 75- 2001,7504636
Bosnia and Herzegovina 77 1544
Botswana 77 604005343
Brazil 75- 6,00045,0004334
Brunei 77 11566
Bulgaria 77 11555
Burkina Faso 1-0+ 6004,0006754
Burundi 4+2+ 352506150
Cambodia 1-0+ 9009,2505240
Cameroon 1-0+ 1,2508,7505545
Canada 66 30095077
Cape Verde 1-0+ 604005041
Central African Republic 2+0+ 755005948
Chad 1-0+ 5503,7505545
Chile 88 -50-4003729
China 65- 40,000450,0003625
Colombia 2+0+ 9,75075,0004031
Comoros 4+2+ 10554335
Congo 2+0+ 3502,5005343
Costa Rica 2+0+ 1,2509,0004031
Cote d'Ivoire 1-0+ 1,0007,2505343
Croatia 66 11555
Cuba 4+1- 1,75015,0003830
Cyprus 99 66
Czech Republic 77 54055
Denmark 99 66
Djibouti 4+2+ 201505646
Dominica 4+1- 151004938
Dominican Republic 4+1- 1,2509,5003830
DR Congo 2+0+ 5003,2505444
Ecuador 65- 5004,0004333
Egypt 77 2001,0002114
El Salvador 2+0+ 9507,5003830
Equatorial Guinea 2+0+ 5003,2506553
Eritrea 4+2+ 402506251
Estonia 66 52055
Ethiopia 4+2+ 9506,0006452
Fiji 3-0+ 756002718
Finland 88 -150-50066
France 88 55
Gabon 2+0+ 5003,2504133
Gambia 1-0+ 1007005948
Georgia 66 10603224
Germany 88 66
Ghana 1-0+ 2,00015,0005545
Greece 88 55
Grenada 4+1- 201504938
Guatemala 2+0+ 1,50010,0004434
Guinea 1-0+ 3502,0005747
Guinea-Bissau 1-0+ 553505545
Guyana 4+1- 806003729
Haiti 4+1- 1501,2504132
Honduras 2+0+ 7505,7504031
Hungary 66 53055
Iceland 88 -10-2577
India 4+1- 55,000450,0003527
Indonesia 1-0+ 30,000250,0004031
Iran 66 4002,7501913
Iraq 66 302501611
Ireland 88 55
Israel 88 55
Italy 88 44
Jamaica 4+1- 3502,5003930
Japan 77 4001,00066
Jordan 77 10701712
Kazakhstan 99 -250-1,7504030
Kenya 4+2+ 7004,7504839
Kiribati 3-0+ 10903323
Kuwait 66 553503121
Kyrgyzstan 66 5253627
Laos 1-0+ 4504,7504938
Latvia 66 52555
Lebanon 66 251502013
Lesotho 66 5503932
Liberia 1-0+ 503504839
Libya 66 402502316
Lithuania 66 54555
Luxembourg 88 55
Macedonia 66 1544
Madagascar 4+2+ 2001,2506755
Malawi 4+2+ 1509006150
Malaysia 1-0+ 10,00095,0003729
Maldives 1-0+ 755503728
Mali 1-0+ 5003,2504032
Malta 88 55
Marshall Islands 3-0+ 5453323
Mauritania 1-0+ 2001,2503024
Mauritius 1-0+ 5503,5003527
Mexico 2+0+ 35,000250,0003930
Micronesia 3-0+ 10903323
Moldova 66 11044
Mongolia 88 -15-1503426
Morocco 66 654502114
Mozambique 4+2+ 2501,5006351
Myanmar 1-0+ 2,25015,0004837
Namibia 66 302003327
Nepal 4+1- 5003,7505341
Netherlands 99 66
New Zealand 77 51566
Nicaragua 2+0+ 4003,0004031
Niger 1-0+ 3502,2505041
Nigeria 1-0+ 10,00075,0004234
North Korea 66 909003726
Norway 88 -200-65066
Oman 66 251502618
Pakistan 4+1- 6,50050,0003325
Palau 3-0+ 5253323
Panama 2+0+ 1,0007,7504132
Papua New Guinea 3-0+ 3002,2503323
Paraguay 65- 907004636
Peru 75- 1,2509,5004837
Philippines 1-0+ 10,00085,0003829
Poland 66 1510055
Portugal 88 66
Qatar 66 654504027
Romania 66 54055
Russia 88 -2,000-15,00066
Rwanda 4+2+ 1508506855
Saint Lucia 4+1- 302504938
Saint Vincent 4+1- 201504938
Samoa 3-0+ 201503323
Sao Tome and Principe 1-0+ 10605847
Saudi Arabia 66 2001,2502215
Senegal 1-0+ 7004,7505746
Seychelles 1-0+ 604004535
Sierra Leone 1-0+ 1509005444
Singapore 66 2520066
Slovakia 66 12055
Slovenia 66 11055
Solomon Islands 3-0+ 302503021
Somalia 4+2+ 654004234
South Africa 66 1,2507,2503227
South Korea 66 1501,00066
Spain 88 55
Sri Lanka 1-0+ 3,00025,0003326
Sudan-South Sudan 4+2+ 1,0007,5003932
Suriname 4+1- 705003325
Swaziland 77 15853630
Sweden 99 -300-95066
Switzerland 99 66
Syria 77 352001812
Tajikistan 77 5253526
Tanzania 4+2+ 6504,0006351
Thailand 1-0+ 15,000150,0004535
Timor-Leste 1-0+ 907503527
Togo 1-0+ 2001,2506150
Tonga 3-0+ 151003323
Trinidad and Tobago 4+1- 4003,0004334
Tunisia 77 402501913
Turkey 77 4001,2502014
Turkmenistan 77 15903224
Tuvalu 3-0+ 153323
Uganda 4+2+ 4503,0006048
Ukraine 66 3020055
United Arab Emirates 66 956003624
United Kingdom 88 66
United States 66 15,00050,00066
Uruguay 66 10754132
Uzbekistan 66 251503224
Vanuatu 3-0+ 201503323
Venezuela 2+0+ 8,00060,0004132
Vietnam 1-0+ 8,00085,0004837
Yemen 66 201502013
Zambia 4+2+ 2001,5005443
Zimbabwe 66 251506956
TOTAL301,9682,487,2355,9734,699