Questionnaire Pathways Guidance Note
1. Introduction
1.1 Overview
- The 2023 CDP-ICLEI Track Questionnaire is divided into three distinct pathways. These three pathways streamline reporting, allowing local jurisdictions to find the most appropriate questionnaire for their local context.
- Respondents will be recommended a pathway during the questionnaire activation process based upon their response to three jurisdictional attributes. Jurisdictions are provided the flexibility to change their pathway if required. They can also return to their dashboard and change the pathway selected prior to submitting the response.
- An increase in the pathways is accompanied by an increase in the number of questions.
- The pathway selected does not affect meeting the reporting requirements of the projects and initiatives the jurisdiction is participating in and it does not affect CDP scoring or Global Covenant of Mayors badging.
1.2 Questions by Pathway
- An increase in the pathways is accompanied by a gradual increase in the number of questions. A high-level breakdown is provided in the table below and the complete breakdown can be viewed in the Questionnaire Mapping Document.
Pathway | Number of Questions | View Questionnaire by Pathway |
---|---|---|
1 | 27 | View the Pathway 1 Questionnaire |
2 | 34 | View the Pathway 2 Questionnaire |
3 | 43 | View the Pathway 3 Questionnaire |
2. Process
2.1 Questionnaire Activation Process
- Respondents will be recommended a pathway during the questionnaire activation process based upon their response to three jurisdictional attributes, however flexibility is provided so that any pathway can be selected.
- Respondents are required to activate their response each year, with this five-step process (as outlined in the table below) including a step titled 'Questionnaire Pathway Selection'.
Activation Process |
---|
Step 1: Get Started Step 2: Confirm Main User Step 3: Opt-in to Projects Step 4: Questionnaire Pathway Selection Step 5: Start Questionnaire |
2.2 Questionnaire Pathway Selection
- The Questionnaire Pathway Selection is a 2-step process. In the first step 'Jurisdiction Details' the respondent responds to three jurisdictional attributes and in the second step 'My Questionnaire Pathway' the respondent selects their pathway.
- Respondents will be presented with three questions in the Questionnaire Pathway Selection screen. The purpose of these questions is to inform the pathway that the responding jurisdiction will be recommended to report against. The questions request the respondent to select the options that most accurately reflect the jurisdictions population, emissions per capita and human development index.
- The options for both the emissions per capita and human development index are prepopulated based on the country/area/region of the responding jurisdiction. These selections can be changed by the jurisdiction should local and/or regional data be available and different to the prepopulated selection. Once the three attributes have a response the recommended pathway can then be selected.
- The respondent can then proceed to the questionnaire using the recommended pathway by clicking the 'Enter questionnaire' button to the bottom right of the screen or the respondent can select any of the other two pathways by clicking on the link in the presented sentence 'To change your pathway, click here.' Once this link is clicked the other pathway options will be presented
- The questions and applicable responses are outlined in the table below while further information on the methodology for the recommendation is provided in Section 2.3.
Attributes that inform pathway recommendation |
---|
Jurisdiction Population
Per Capita Emissions1
Human Development Index (per UN classification)2
|
1 Global Carbon Project. 2021. Supplemental data of Global Carbon Budget 2021 (Version 1.0) [Data set]. Global Carbon Project. https://doi.org/10.18160/gcp-2021
2 UNDP (United Nations Development Programme). 2022. Human Development Report 2021-22: Uncertain Times, Unsettled Lives: Shaping our Future in a Transforming World. New York.
2.3 Pathway Recommendation Calculation
The questionnaire pathway recommendation is based on the questionnaire pathway index value. The questionnaire pathway index is a summary measure related to the dimensions of population, emissions per capita and human development. In order to transform the indicators expressed in different units into indices between 0 and 1 each indicator is subdivided into three ranges and each range is assigned an index value. The geometric mean of these three indices is then used to generate the questionnaire pathway index value, as detailed in the tables below.
Dimension 1: Population
Range | Index Value |
---|---|
<500,000 | 0.33333 |
500,000 - 1,500,000 | 0.66666 |
>1,500,000 | 1 |
Indicator 2: Emissions per capita
Range | Index Value |
---|---|
<3 tonnes per capita | 0.33333 |
3-5 tonnes per capita | 0.66666 |
>5 tonnes per capita | 1 |
Indicator 3: Human Development Index
Range | Index Value |
---|---|
Low or Medium | 0.33333 |
High | 0.66666 |
Very high | 1 |
Relationship of Index Value Geometric Mean and Recommended Questionnaire Pathway
Index Value Geometric Mean | Recommended Questionnaire Pathway |
---|---|
<0.65 | Pathway 1 |
0.65-0.8 | Pathway 2 |
>0.8 | Pathway 3 |
3. Human Development Index (HDI) and Emissions Per Capita Prepopulated Responses
The response options for both the emissions per capita and human development index (HDI) are prepopulated based on the country/area/region of the responding jurisdiction. The jurisdiction can change these selections should local and/or regional data be available and different from the prepopulated selection. The table below indicates the response options prepopulated based on the country/area/region. The data for HDI is sourced from the United Nations Human Development Report 2021/222 while emissions data is sourced from the Global Carbon Project1 and is based upon the average of national emissions from the years 2018, 2019 and 2020.
ISO Code | Country/Area/Region Name | Human Development Index (HDI) - Populated Response | Emissions Per Capita - Populated Response |
---|---|---|---|
AF | Afghanistan | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
AX | Åland Islands | Very High (> 0.8) |
No prepopulation possible |
AL | Albania | High (0.7-0.8) |
< 3 metric tonnes CO2e per capita |
DZ | Algeria | High (0.7-0.8) | 3-5 metric tonnes CO2e per capita |
AS | American Samoa | Low, Medium (< 0.7) | No prepopulation possible |
AD | Andorra | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
AO | Angola | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
AI | Anguilla | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
AQ | Antarctica | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
AG | Antigua and Barbuda | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
AR | Argentina | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
AM | Armenia | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
AW | Aruba | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
AU | Australia | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
AT | Austria | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
AZ | Azerbaijan | High (0.7-0.8) | 3-5 metric tonnes CO2e per capita |
BS | Bahamas | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
BH | Bahrain | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
BD | Bangladesh | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
BB | Barbados | High (0.7-0.8) | 3-5 metric tonnes CO2e per capita |
BY | Belarus | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
BE | Belgium | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
BZ | Belize | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
BJ | Benin | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
BM | Bermuda | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
BT | Bhutan | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
BO | Bolivia (Plurinational State of) | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
BQ | Bonaire, Sint Eustatius and Saba | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
BA | Bosnia & Herzegovina | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
BW | Botswana | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
BV | Bouvet Island | Low, Medium (< 0.7) | No prepopulation possible |
BR | Brazil | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
IO | British Indian Ocean Territory | Low, Medium (< 0.7) | No prepopulation possible |
VG | British Virgin Islands | High (0.7-0.8) | 3-5 metric tonnes CO2e per capita |
BN | Brunei Darussalam | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
BG | Bulgaria | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
BF | Burkina Faso | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
BI | Burundi | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
CV | Cabo Verde | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
KH | Cambodia | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
CM | Cameroon | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
CA | Canada | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
KY | Cayman Islands | Very High (> 0.8) | No prepopulation possible |
CF | Central African Republic | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
TD | Chad | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
CL | Chile | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
CN | China | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
HK | China, Hong Kong Special Administrative Region | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
MO | China, Macao Special Administrative Region | Very High (> 0.8) | < 3 metric tonnes CO2e per capita |
CX | Christmas Island | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
CC | Cocos (Keeling) Islands | Low, Medium .(< 0.7) | No prepopulation possible |
CO | Colombia | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
KM | Comoros | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
CG | Congo | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
CK | Cook Islands | Low, Medium (< 0.7) | 3-5 metric tonnes CO2e per capita |
CR | Costa Rica | Very High (> 0.8) | < 3 metric tonnes CO2e per capita |
CI | Côte d'Ivoire | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
HR | Croatia | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
CU | Cuba | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
CW | Curaçao | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
CY | Cyprus | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
CZ | Czechia | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
KP | Democratic People's Republic of Korea | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
CD | Democratic Republic of the Congo | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
DK | Denmark | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
DJ | Djibouti | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
DM | Dominica | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
DO | Dominican Republic | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
EC | Ecuador | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
EG | Egypt | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
SV | El Salvador | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
GQ | Equatorial Guinea | Low, Medium (< 0.7) | > 5 metric tonnes CO2e per capita |
ER | Eritrea | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
EE | Estonia | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
SZ | Eswatini | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
ET | Ethiopia | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
FK | Falkland Islands (Malvinas) | Low, Medium (< 0.7) | No prepopulation possible |
FO | Faroe Islands | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
FJ | Fiji | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
FI | Finland | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
FR | France | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
GF | French Guiana | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
PF | French Polynesia | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
TF | French Southern Territories | Low, Medium (< 0.7) | No prepopulation possible |
GA | Gabon | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
GM | Gambia | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
GE | Georgia | Very High (> 0.8) | < 3 metric tonnes CO2e per capita |
DE | Germany | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
GH | Ghana | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
GI | Gibraltar | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
GR | Greece | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
GL | Greenland | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
GD | Grenada | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
GP | Guadeloupe | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
GU | Guam | High (0.7-0.8) | No prepopulation possible |
GT | Guatemala | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
GG | Guernsey | Very High (> 0.8) | No prepopulation possible |
GN | Guinea | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
GW | Guinea-Bissau | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
GY | Guyana | High (0.7-0.8) | 3-5 metric tonnes CO2e per capita |
HT | Haiti | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
HM | Heard Island and McDonald Islands | Low, Medium (< 0.7) | No prepopulation possible |
VA | Holy See | Low, Medium (< 0.7) | No prepopulation possible |
HN | Honduras | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
HU | Hungary | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
IS | Iceland | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
IN | India | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
ID | Indonesia | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
IR | Iran (Islamic Republic of) | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
IQ | Iraq | Low, Medium (< 0.7) | > 5 metric tonnes CO2e per capita |
IE | Ireland | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
IM | Isle of Man | Very High (> 0..8) | No prepopulation possible |
IL | Israel | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
IT | Italy | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
JM | Jamaica | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
JP | Japan | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
JE | Jersey | Very High (> 0.8) | No prepopulation possible |
JO | Jordan | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
KZ | Kazakhstan | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
KE | Kenya | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
KI | Kiribati | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
KW | Kuwait | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
KG | Kyrgyzstan | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
LA | Lao People's Democratic Republic | Low, Medium (< 0.7) | 3-5 metric tonnes CO2e per capita |
LV | Latvia | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
LB | Lebanon | High (0.7-0.8) | 3-5 metric tonnes CO2e per capita |
LS | Lesotho | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
LR | Liberia | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
LY | Libya | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
LI | Liechtenstein | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
LT | Lithuania | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
LU | Luxembourg | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
MG | Madagascar | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
MW | Malawi | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
MY | Malaysia | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
MV | Maldives | High (0.7-0.8) | 3-5 metric tonnes CO2e per capita |
ML | Mali | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
MT | Malta | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
MH | Marshall Islands | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
MQ | Martinique | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
MR | Mauritania | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
MU | Mauritius | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
YT | Mayotte | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
MX | Mexico | High (0.7-0.8) | 3-5 metric tonnes CO2e per capita |
FM | Micronesia (Federated States of) | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
MC | Monaco | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
MN | Mongolia | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
ME | Montenegro | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
MS | Montserrat | Low, Medium (< 0.7) | > 5 metric tonnes CO2e per capita |
MA | Morocco | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
MZ | Mozambique | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
MM | Myanmar | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
NA | Namibia | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
NR | Nauru | Low, Medium (< 0.7) | > 5 metric tonnes CO2e per capita |
NP | Nepal | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
NL | Netherlands | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
NC | New Caledonia | Low, Medium (< 0.7) | > 5 metric tonnes CO2e per capita |
NZ | New Zealand | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
NI | Nicaragua | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
NE | Niger | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
NG | Nigeria | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
NU | Niue | Low, Medium (< 0.7) | > 5 metric tonnes CO2e per capita |
NF | Norfolk Island | Low, Medium (< 0.7) | No prepopulation possible |
MK | North Macedonia | High (0.7-0.8) | 3-5 metric tonnes CO2e per capita |
MP | Northern Mariana Islands | High (0.7-0.8) | No prepopulation possible |
NO | Norway | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
OM | Oman | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
PK | Pakistan | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
PW | Palau | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
PA | Panama | Very High (> 0.8) | < 3 metric tonnes CO2e per capita |
PG | Papua New Guinea | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
PY | Paraguay | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
PE | Peru | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
PH | Philippines | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
PN | Pitcairn | Low, Medium (< 0.7) | No prepopulation possible |
PL | Poland | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
PT | Portugal | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
PR | Puerto Rico | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
QA | Qatar | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
KR | Republic of Korea | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
MD | Republic of Moldova | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
RE | Réunion | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
RO | Romania | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
RU | Russian Federation | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
RW | Rwanda | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
BL | Saint Barthélemy | High (0.7-0.8) | No prepopulation possible |
SH | Saint Helena | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
KN | Saint Kitts and Nevis | High (0.7-0.8) | 3-5 metric tonnes CO2e per capita |
LC | Saint Lucia | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
MF | Saint Martin (French Part) | Low, Medium (< 0.7) | No prepopulation possible |
PM | Saint Pierre and Miquelon | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
VC | Saint Vincent and the Grenadines | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
WS | Samoa | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
SM | San Marino | Very High (> 0.8) | No prepopulation possible |
ST | Sao Tome and Principe | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
SA | Saudi Arabia | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
SN | Senegal | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
RS | Serbia | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
SC | Seychelles | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
SL | Sierra Leone | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
SG | Singapore | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
SX | Sint Maarten (Dutch part) | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
SK | Slovakia | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
SI | Slovenia | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
SB | Solomon Islands | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
SO | Somalia | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
ZA | South Africa | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
GS | South Georgia and the South Sandwich Islands | Low, Medium (< 0.7) | No prepopulation possible |
SS | South Sudan | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
ES | Spain | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
LK | Sri Lanka | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
PS | State of Palestine | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
SD | Sudan | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
SR | Suriname | High (0.7-0.8) | 3-5 metric tonnes CO2e per capita |
SJ | Svalbard and Jan Mayen Islands | Low, Medium (< 0.7) | No prepopulation possible |
SE | Sweden | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
CH | Switzerland | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
SY | Syrian Arab Republic | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
TJ | Tajikistan | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
TH | Thailand | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
TL | Timor-Leste | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
TG | Togo | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
TK | Tokelau | Low, Medium (< 0.7) | No prepopulation possible |
TO | Tonga | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
TT | Trinidad and Tobago | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
TN | Tunisia | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
TR | Turkey | Very High (> 0.8) | 3-5 metric tonnes CO2e per capita |
TM | Turkmenistan | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
TC | Turks and Caicos Islands | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
TV | Tuvalu | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
UG | Uganda | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
UA | Ukraine | High (0.7-0.8) | > 5 metric tonnes CO2e per capita |
AE | United Arab Emirates | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
GB | United Kingdom of Great Britain and Northern Ireland | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
TZ | United Republic of Tanzania | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
UM | United States Minor Outlying Islands | Low, Medium (< 0.7) | No prepopulation possible |
US | United States of America | Very High (> 0.8) | > 5 metric tonnes CO2e per capita |
VI | United States Virgin Islands | High (0.7-0.8) | No prepopulation possible |
UY | Uruguay | Very High (> 0.8) | < 3 metric tonnes CO2e per capita |
UZ | Uzbekistan | High (0.7-0.8) | 3-5 metric tonnes CO2e per capita |
VU | Vanuatu | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
VE | Venezuela (Bolivarian Republic of) | Low, Medium (< 0.7) | 3-5 metric tonnes CO2e per capita |
VN | Viet Nam | High (0.7-0.8) | < 3 metric tonnes CO2e per capita |
WF | Wallis and Futuna Islands | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
EH | Western Sahara | Low, Medium (< 0.7) | No prepopulation possible |
YE | Yemen | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
ZM | Zambia | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
ZW | Zimbabwe | Low, Medium (< 0.7) | < 3 metric tonnes CO2e per capita |
1 Global Carbon Project. 2021. Supplemental data of Global Carbon Budget 2021 (Version 1.0) [Data set]. Global Carbon Project. https://doi.org/10.18160/gcp-2021
2 UNDP (United Nations Development Programme). 2022. Human Development Report 2021-22: Uncertain Times, Unsettled Lives: Shaping our Future in a Transforming World. New York.