This article is for disclosing cities and details the 3 different pathways and pathway maps in CDP-ICLEI Track.
Contents
- Introduction
- Section 1: Questionnaire pathways
- Section 2: Pathways Map
- Pathway 1
- Pathway 2 - Additional Questions (7) and/or Columns/Rows
- Pathway 3 - Additional Questions (10)
- Projects and Initiatives - Additional Questions
The 2025 Cities 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.
Responders will be recommended a pathway during the questionnaire activation process based on 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 at any point prior to submitting their 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. A high-level breakdown is provided in the table below, in section 1, and a complete breakdown can be viewed in section 2.
Section 1: Questionnaire Pathways
| Pathway | Number of Questions |
| 1 | 28 |
| 2 | 35 |
| 3 | 45 |
During the questionnaire activation process, responders will be presented with three questions that inform the recommendation of a pathway. These questions request the responder to select the options that most accurately reflect three attributes: the jurisdiction’s 1) population; 2) emissions per capita; and 3) human development index (HDI).
The options for both the emissions per capita and HDI are prepopulated based on the country/area/region of the responding jurisdiction. The pre-population is based on national-level data and can be changed should local and/or regional data be available and different to the prepopulated selection, or when the jurisdiction’s total emissions per capita (at least scope 1 and 2 or GPC-aligned BASIC) is different.
The responder can then proceed to the questionnaire using the recommended pathway, or they can select either of the other two pathways. ICLEI Network Cities are encouraged to report to Pathway 3.
The questions and applicable responses are outlined in the table below while further information on the methodology for the recommendation is provided in Section 3.
| Jurisdictional Attribute | Options | Source for pre-populated option |
| Population | < 500,000 500,000 – 1,500,000 > 1,500,000 | N/A |
| Per Capita Emissions | < 3 metric tonnes CO2e/capita 3-5 metric tonnes CO2e/capita > 5 metric tonnes CO2e/capita | 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 |
| Human Development Index | Low or Medium (< 0.7) High (0.7 - 0.799) Very high (> 0.8) | UNDP (United Nations Development Programme). 2022. Human Development Report 2021-22: Uncertain Times, Unsettled Lives: Shaping our Future in a Transforming World. New York. |
Pathway Recommendation Methodology
The Cities 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. 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.
Attribute 1: Population
| Range | Index Value |
| <500,000 | 0.33333 |
| 500,000 - 1,500,000 | 0.66666 |
| >1,500,000 | 1 |
Attribute 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 |
Attribute 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 |
| <0.62 | Pathway 1 |
| 0.62-0.8 | Pathway 2 |
| >0.8 | Pathway 3 |
Emissions Per Capita and Human Development Index (HDI) Prepopulated Responses
The response options for both the emissions per capita and 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 2021/22 while emissions data is sourced from the Global Carbon Project and is based upon the average of national emissions from the years 2018, 2019 and 2020.
| ISO Code | Country/Area/Region Name | Emissions Per Capita - Populated Response | Human Development Index (HDI) - Populated Response |
| AF | Afghanistan | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| AX | Åland Islands | No prepopulation possible | Very High (> 0.8) |
| AL | Albania | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| DZ | Algeria | 3-5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| AS | American Samoa | No prepopulation possible | Low, Medium (< 0.7) |
| AD | Andorra | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| AO | Angola | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| AI | Anguilla | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| AQ | Antarctica | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| AG | Antigua and Barbuda | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| AR | Argentina | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| AM | Armenia | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| AW | Aruba | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| AU | Australia | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| AT | Austria | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| AZ | Azerbaijan | 3-5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| BS | Bahamas | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| BH | Bahrain | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| BD | Bangladesh | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| BB | Barbados | 3-5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| BY | Belarus | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| BE | Belgium | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| BZ | Belize | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| BJ | Benin | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| BM | Bermuda | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| BT | Bhutan | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| BO | Bolivia (Plurinational State of) | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| BQ | Bonaire, Sint Eustatius and Saba | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| BA | Bosnia & Herzegovina | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| BW | Botswana | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| BV | Bouvet Island | No prepopulation possible | Low, Medium (< 0.7) |
| BR | Brazil | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| IO | British Indian Ocean Territory | No prepopulation possible | Low, Medium (< 0.7) |
| VG | British Virgin Islands | 3-5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| BN | Brunei Darussalam | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| BG | Bulgaria | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| BF | Burkina Faso | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| BI | Burundi | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| CV | Cabo Verde | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| KH | Cambodia | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| CM | Cameroon | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| CA | Canada | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| KY | Cayman Islands | No prepopulation possible | Very High (> 0.8) |
| CF | Central African Republic | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| TD | Chad | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| CL | Chile | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| CN | China | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| HK | China, Hong Kong Special Administrative Region | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| MO | China, Macao Special Administrative Region | < 3 metric tonnes CO2e per capita | Very High (> 0.8) |
| CX | Christmas Island | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| CC | Cocos (Keeling) Islands | No prepopulation possible | Low, Medium (< 0.7) |
| CO | Colombia | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| KM | Comoros | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| CG | Congo | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| CK | Cook Islands | 3-5 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| CR | Costa Rica | < 3 metric tonnes CO2e per capita | Very High (> 0.8) |
| CI | Côte d'Ivoire | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| HR | Croatia | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| CU | Cuba | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| CW | Curaçao | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| CY | Cyprus | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| CZ | Czechia | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| KP | Democratic People's Republic of Korea | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| CD | Democratic Republic of the Congo | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| DK | Denmark | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| DJ | Djibouti | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| DM | Dominica | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| DO | Dominican Republic | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| EC | Ecuador | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| EG | Egypt | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| SV | El Salvador | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| GQ | Equatorial Guinea | > 5 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| ER | Eritrea | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| EE | Estonia | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| SZ | Eswatini | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| ET | Ethiopia | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| FK | Falkland Islands (Malvinas) | No prepopulation possible | Low, Medium (< 0.7) |
| FO | Faroe Islands | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| FJ | Fiji | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| FI | Finland | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| FR | France | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| GF | French Guiana | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| PF | French Polynesia | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| TF | French Southern Territories | No prepopulation possible | Low, Medium (< 0.7) |
| GA | Gabon | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| GM | Gambia | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| GE | Georgia | < 3 metric tonnes CO2e per capita | Very High (> 0.8) |
| DE | Germany | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| GH | Ghana | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| GI | Gibraltar | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| GR | Greece | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| GL | Greenland | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| GD | Grenada | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| GP | Guadeloupe | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| GU | Guam | No prepopulation possible | High (0.7 - 0.8) |
| GT | Guatemala | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| GG | Guernsey | No prepopulation possible | Very High (> 0.8) |
| GN | Guinea | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| GW | Guinea-Bissau | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| GY | Guyana | 3-5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| HT | Haiti | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| HM | Heard Island and McDonald Islands | No prepopulation possible | Low, Medium (< 0.7) |
| VA | Holy See | No prepopulation possible | Low, Medium (< 0.7) |
| HN | Honduras | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| HU | Hungary | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| IS | Iceland | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| IN | India | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| ID | Indonesia | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| IR | Iran (Islamic Republic of) | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| IQ | Iraq | > 5 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| IE | Ireland | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| IM | Isle of Man | No prepopulation possible | Very High (> 0.8) |
| IL | Israel | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| IT | Italy | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| JM | Jamaica | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| JP | Japan | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| JE | Jersey | No prepopulation possible | Very High (> 0.8) |
| JO | Jordan | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| KZ | Kazakhstan | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| KE | Kenya | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| KI | Kiribati | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| KW | Kuwait | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| KG | Kyrgyzstan | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| LA | Lao People's Democratic Republic | 3-5 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| LV | Latvia | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| LB | Lebanon | 3-5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| LS | Lesotho | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| LR | Liberia | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| LY | Libya | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| LI | Liechtenstein | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| LT | Lithuania | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| LU | Luxembourg | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| MG | Madagascar | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| MW | Malawi | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| MY | Malaysia | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| MV | Maldives | 3-5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| ML | Mali | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| MT | Malta | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| MH | Marshall Islands | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| MQ | Martinique | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| MR | Mauritania | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| MU | Mauritius | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| YT | Mayotte | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| MX | Mexico | 3-5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| FM | Micronesia (Federated States of) | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| MC | Monaco | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| MN | Mongolia | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| ME | Montenegro | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| MS | Montserrat | > 5 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| MA | Morocco | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| MZ | Mozambique | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| MM | Myanmar | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| NA | Namibia | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| NR | Nauru | > 5 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| NP | Nepal | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| NL | Netherlands | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| NC | New Caledonia | > 5 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| NZ | New Zealand | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| NI | Nicaragua | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| NE | Niger | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| NG | Nigeria | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| NU | Niue | > 5 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| NF | Norfolk Island | No prepopulation possible | Low, Medium (< 0.7) |
| MK | North Macedonia | 3-5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| MP | Northern Mariana Islands | No prepopulation possible | High (0.7 - 0.8) |
| NO | Norway | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| OM | Oman | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| PK | Pakistan | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| PW | Palau | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| PA | Panama | < 3 metric tonnes CO2e per capita | Very High (> 0.8) |
| PG | Papua New Guinea | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| PY | Paraguay | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| PE | Peru | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| PH | Philippines | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| PN | Pitcairn | No prepopulation possible | Low, Medium (< 0.7) |
| PL | Poland | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| PT | Portugal | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| PR | Puerto Rico | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| QA | Qatar | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| KR | Republic of Korea | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| MD | Republic of Moldova | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| RE | Réunion | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| RO | Romania | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| RU | Russian Federation | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| RW | Rwanda | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| BL | Saint Barthélemy | No prepopulation possible | High (0.7 - 0.8) |
| SH | Saint Helena | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| KN | Saint Kitts and Nevis | 3-5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| LC | Saint Lucia | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| MF | Saint Martin (French Part) | No prepopulation possible | Low, Medium (< 0.7) |
| PM | Saint Pierre and Miquelon | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| VC | Saint Vincent and the Grenadines | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| WS | Samoa | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| SM | San Marino | No prepopulation possible | Very High (> 0.8) |
| ST | Sao Tome and Principe | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| SA | Saudi Arabia | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| SN | Senegal | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| RS | Serbia | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| SC | Seychelles | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| SL | Sierra Leone | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| SG | Singapore | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| SX | Sint Maarten (Dutch part) | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| SK | Slovakia | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| SI | Slovenia | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| SB | Solomon Islands | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| SO | Somalia | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| ZA | South Africa | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| GS | South Georgia and the South Sandwich Islands | No prepopulation possible | Low, Medium (< 0.7) |
| SS | South Sudan | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| ES | Spain | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| LK | Sri Lanka | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| PS | State of Palestine | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| SD | Sudan | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| SR | Suriname | 3-5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| SJ | Svalbard and Jan Mayen Islands | No prepopulation possible | Low, Medium (< 0.7) |
| SE | Sweden | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| CH | Switzerland | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| SY | Syrian Arab Republic | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| TJ | Tajikistan | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| TH | Thailand | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| TL | Timor-Leste | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| TG | Togo | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| TK | Tokelau | No prepopulation possible | Low, Medium (< 0.7) |
| TO | Tonga | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| TT | Trinidad and Tobago | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| TN | Tunisia | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| TR | Turkey | 3-5 metric tonnes CO2e per capita | Very High (> 0.8) |
| TM | Turkmenistan | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| TC | Turks and Caicos Islands | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| TV | Tuvalu | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| UG | Uganda | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| UA | Ukraine | > 5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| AE | United Arab Emirates | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| GB | United Kingdom of Great Britain and Northern Ireland | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| TZ | United Republic of Tanzania | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| UM | United States Minor Outlying Islands | No prepopulation possible | Low, Medium (< 0.7) |
| US | United States of America | > 5 metric tonnes CO2e per capita | Very High (> 0.8) |
| VI | United States Virgin Islands | No prepopulation possible | High (0.7 - 0.8) |
| UY | Uruguay | < 3 metric tonnes CO2e per capita | Very High (> 0.8) |
| UZ | Uzbekistan | 3-5 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| VU | Vanuatu | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| VE | Venezuela (Bolivarian Republic of) | 3-5 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| VN | Viet Nam | < 3 metric tonnes CO2e per capita | High (0.7 - 0.8) |
| WF | Wallis and Futuna Islands | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| EH | Western Sahara | No prepopulation possible | Low, Medium (< 0.7) |
| YE | Yemen | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| ZM | Zambia | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
| ZW | Zimbabwe | < 3 metric tonnes CO2e per capita | Low, Medium (< 0.7) |
The Pathways Map below outlines the questions, and where relevant the columns/rows, that are presented on each pathway.
If your jurisdiction participates in certain projects or initiatives, there may be additional questions and/or columns/rows presented to ensure your questionnaire aligns with their reporting requirements. More information on projects and initiatives may be found in our Frameworks, Projects and Initiatives knowledge article. Please see the 'Column/Row Modifications' in the tables below to view potential additional columns/rows and the table 'Projects and Initiatives - Additional Questions' to view potential additional questions.
Pathway 1
2025 Question Number | Question Text | Column/Row Modifications |
| 1.1 | What language are you submitting your response in? | N/A |
| 1.2 | Provide details of your jurisdiction in the table below. | Pathway 1: Columns 1-10 Column 11: GCoM cities only. |
| 2.1 | Has a climate risk and vulnerability assessment been undertaken for your jurisdiction? If not, please indicate why. | N/A |
| 2.1.1 | Provide details on your climate risk and vulnerability assessment. | Pathway 1: Columns 1-6 Column 7: Cities disclosing to C40; GCoM; ICLEI GreenClimateCities; ICLEI Ukrainian Cities; UBC Sustainable Cities Commission; EU Mission on Adaptation to Climate Change . |
| 2.2 | Provide details on the most significant climate hazards faced by your jurisdiction. | Pathway 1: Columns 1-5 Columns 6-10: Cities disclosing to C40; GCoM; ICLEI GreenClimateCities; ICLEI Ukrainian Cities; UBC Sustainable Cities Commission; EU Mission on Adaptation to Climate Change . |
| 2.3 | Identify and describe the most significant factors impacting on your jurisdiction’s ability to adapt to climate change and indicate how those factors either support or challenge this ability. | N/A |
| 3.1 | Does your jurisdiction have a community-wide emissions inventory to report? | N/A |
| 3.1.1 | Provide information on and an attachment (in spreadsheet format)/direct link to your main community-wide GHG emissions inventory. | Pathway 1: Columns 1-12 and 17 Columns 13-16: Cities disclosing to C40; GCoM; ICLEI GreenClimateCities; ICLEI Ukrainian Cities; UBC Sustainable Cities Commission; NetZeroCities – Mission Cities. |
| 3.1.2 | Provide a breakdown of your community-wide emissions by scope. If the inventory has been developed using the Global Protocol for Community Greenhouse Gas Emissions Inventories (GPC) you will also be requested to provide a breakdown by sector. | Pathway 1: Rows 1-4 (Total emissions only) Rows 5-17: C40; ICLEI GreenClimateCities; ICLEI Ukrainian Cities; NetZeroCities – Mission Cities. |
| 3.1.3 | Provide a breakdown of your community-wide emissions in the format of the Common Reporting Framework. | Pathway 1: Rows 30 and 31 (Total emissions only) Rows 1-29: C40; GCoM; ICLEI GreenClimateCities; ICLEI Ukrainian Cities; UBC Sustainable Cities Commission; NetZeroCities – Mission Cities. |
| 4.1 | Report the following information regarding your jurisdiction-wide energy consumption. | Pathway 1: Columns 2, 3, 5 and 6 Column 4: C40; GCoM; ICLEI GreenClimateCities; 100% Renewable Energy Campaign; UBC Sustainable Cities Commission; NetZeroCities – Mission Cities. Column 1: GCoM cities only. |
| 4.5 | Report your jurisdiction's passenger and/or freight mode share data. | Pathway 1: Rows 1-13, 24 (Passenger mode share only) Rows 14-23: C40; ICLEI Ukrainian Cities; UBC Sustainable Cities Commission; NetZeroCities – Mission Cities. |
| 4.7 | Report the following waste-related data for your jurisdiction. | Pathway 1: Row 1 (Total solid waste only) Rows 2-9: C40; ICLEI Ukrainian Cities; UBC Sustainable Cities Commission; NetZeroCities – Mission Cities. |
| 4.8 | Report on how climate change impacts health outcomes and health services in your jurisdiction. | Pathway 1: Columns 1-3, 7 Columns 4-6: C40; ICLEI Ukrainian Cities; EU Mission on Adaptation to Climate Change. |
| 4.10 | Provide details of the household access to water, sanitation services and water consumption in your jurisdiction. | N/A |
| 4.11 | What percentage of your population is food insecure and/or lives in a food desert? | N/A |
| 5.1 | Does your jurisdiction have an adaptation goal(s) in place? If no adaptation goal is in place, please indicate the primary reason why. | N/A |
| 5.1.1 | Report your jurisdiction’s main adaptation goals. | N/A |
| 6.1 | Does your jurisdiction have an active greenhouse gas emissions reduction target(s) in place? Please include long-term and/or mid-term targets. If no active GHG emissions reduction target is in place, please indicate the primary reason why. | N/A |
| 6.1.1 | Provide details of your emissions reduction target(s). Please report both long-term and mid-term targets, if applicable. | N/A |
| 6.1.2 | If you are using or plan to use carbon credits sold to or purchased from outside the jurisdiction or target boundary, provide details. | N/A |
| 7.1 | Provide details of your jurisdiction's energy-related and other environment-related targets active in the reporting year. | N/A |
| 8.1 | Does your jurisdiction have a climate action plan or strategy that addresses mitigation, adaptation (resilience) and/or energy? | N/A |
| 8.1.1 | Report details on the climate action plan or strategy that addresses mitigation, adaptation (resilience) and/or energy-related issues in your jurisdiction. | Pathway 1: Columns 1-10, 17 Columns 11-16: C40; GCoM, ICLEI GreenClimateCities; ICLEI Ukrainian Cities; UBC Sustainable Cities Commission; EU Mission on Adaptation to Climate Change; NetZeroCities – Mission Cities. |
| 9.1 | Describe the outcomes of the most significant adaptation actions your jurisdiction is currently undertaking. Note that this can include those in the planning and/or implementation phase. | Pathway 1: Columns 1-11 Columns 12-14: C40; GCoM; ICLEI GreenClimateCities; 100% Renewable Energy Campaign; ICLEI Ukrainian Cities; Transformative Actions Program; UBC Sustainable Cities Commission; EU Mission on Adaptation to Climate Change. Columns 15-16: GCoM cities only. |
| 9.2 | Describe the outcomes of the most significant mitigation actions your jurisdiction is currently undertaking. Note that this can include those in the planning and/or implementation phases. | Pathway 1: Column 1-11 Columns 12-14: C40; GCoM; ICLEI GreenClimateCities; Ecomobility Alliance; 100% Renewable Energy Campaign; ICLEI Ukrainian Cities; Transformative Actions Program; UBC Sustainable Cities Commission. Columns 15-16: GCoM cities only. |
| 9.3 | Describe any planned climate-related projects within your jurisdiction for which you hope to attract financing. | N/A |
Pathway 2 - Additional Questions (7) and/or Columns/Rows
Responding jurisdictions who select Pathway 2 will be presented with the questions as outlined in Pathway 1 in addition to the questions and columns/row as outlined in the table below.
2025 Question Number | Question Text | Column/Row Modifications |
| 1.3 | Provide information on your jurisdiction’s oversight of climate-related risks and opportunities and how these issues have impacted your jurisdiction's planning. | N/A |
| 1.4 | Report how your jurisdiction assesses the wider environmental, social, and economic opportunities and benefits of climate action. | N/A |
| 1.5 | Report on your engagement with other levels of government regarding your jurisdiction's climate action. | N/A |
| 1.6 | Report your jurisdiction's most significant examples of collaboration with government, business, and/or civil society on climate-related issues. | N/A |
| 2.1.1 | Provide details on your climate risk and vulnerability assessment. | Pathway 2: Columns 1-7 (Complete question) |
| 2.2 | Provide details on the most significant climate hazards faced by your jurisdiction. | Pathway 2: Columns 1-10 (Complete question) |
| 3.1.1 | Provide information on and an attachment (in spreadsheet format)/direct link to your main community-wide GHG emissions inventory. | Pathway 2: Columns 1-17 (Complete question) |
| 3.1.2 | Provide a breakdown of your community-wide emissions by scope. If the inventory has been developed using the Global Protocol for Community Greenhouse Gas Emissions Inventories (GPC) you will also be requested to provide a breakdown by sector. | Pathway 2: Rows 1-17 (Complete question) |
| 3.1.3 | Provide a breakdown of your community-wide emissions in the format of the Common Reporting Framework. | Pathway 2: Rows 1-31 (Complete question) |
| 3.1.4 | Provide a breakdown of your community-wide emissions by sector. | N/A |
| 4.3 | How many households within the jurisdiction boundary face energy poverty? Select the threshold used for energy poverty in your jurisdiction. | N/A |
| 4.5 | Report your jurisdiction's passenger and/or freight mode share data. | Pathway 2: Rows 1-24 (Complete question) |
| 4.7 | Report the following waste-related data for your jurisdiction. | Pathway 2: Row 1-9 (Complete question) |
| 4.8 | Report on how climate change impacts health outcomes and health services in your jurisdiction. | Pathway 2: Columns 1-7 (Complete question) |
| 8.1.1 | Report details on the climate action plan or strategy that addresses mitigation, adaptation (resilience) and/or energy-related issues in your jurisdiction. | Pathway 2: Columns 1-15 (Complete question) |
| 8.2 | Report details on the other environment-related plans, policies and/or strategies in your jurisdiction. | N/A |
| 9.1 | Describe the outcomes of the most significant adaptation actions your jurisdiction is currently undertaking. Note that this can include those in the planning and/or implementation phase. | Pathway 2: Columns 1-14 Columns 15-16: GCoM cities only. |
| 9.2 | Describe the outcomes of the most significant mitigation actions your jurisdiction is currently undertaking. Note that this can include those in the planning and/or implementation phases. | Pathway 2: Column 1-14 Columns 15-16: GCoM cities only. |
Pathway 3 - Additional Questions (10)
Responding jurisdictions who select Pathway 3 will be presented with the questions as outlined in Pathway 1 and 2 in addition to the questions as outlined in the table below.
| 2025 Question Number | Question Text | Column/Row Modifications |
| 3.2 | Does your jurisdiction have a consumption-based emissions inventory to measure emissions from consumption of goods and services? The consumption-based approach captures direct and lifecycle GHG emissions of goods and services and allocates GHG emissions to the final consumers, rather than to the producers. | N/A |
| 4.1 | Report the following information regarding your jurisdiction-wide energy consumption. | Pathway 3: Columns 2-6 Column 1: GCoM cities only. |
| 4.1.1 | Report the total electricity consumption in MWh and the energy mix used for electricity consumption in your jurisdiction. | N/A |
| 4.1.2 | Report the total thermal (heating/cooling) energy consumption in MWh and the energy mix used for thermal (heating/cooling) source mix breakdown for energy consumption in your jurisdiction. | N/A |
| 4.1.3 | For each type of renewable energy within the jurisdiction boundary, report the installed capacity (MW) and annual generation (MWh). | N/A |
| 4.9 | Report the following air pollution data for the jurisdiction. | N/A |
| 4.12 | Report the total quantity of food that is procured (in tonnes) for government-owned and/or operated facilities (including municipal facilities, schools, hospitals, youth centers, shelters, public canteens, prisons etc.). If available, please provide a breakdown per food group. | N/A |
| 4.13 | Report the sources of your jurisdiction’s water supply, volumes withdrawn per source, and the projected change. | N/A |
| 8.3 | Does your jurisdiction have a strategy for reducing emissions from consumption of the jurisdiction's most relevant goods and services? | N/A |
| 8.4 | Does your jurisdiction have a strategy or standard for reducing emissions from the jurisdiction’s procurement and purchases of goods and services? | N/A |
| 9.4 | Report the factors that support climate-related investment and financial planning in your jurisdiction. | N/A |
Projects and Initiatives - Additional Questions
Responding jurisdictions who participate in certain initiatives will be presented some of the additional questions below.
| 2025 Question Number | Question Text | Applicable Projects and Initiatives |
| 3.3 | Do you have an emissions inventory for your government operations to report? | C40; ICLEI GreenClimateCities; ICLEI Ukrainian Cities; |
| 3.3.1 | Attach your government operations emissions inventory and report the following information regarding this inventory. | C40; ICLEI GreenClimateCities; ICLEI Ukrainian Cities |
| 3.3.2 | Report your government operations emissions in metric tonnes CO2e. | C40; ICLEI GreenClimateCities; ICLEI Ukrainian Cities |
| 4.1.4 | Report the total jurisdiction-wide annual electricity and heating and cooling consumption for each sector listed and for your government operations. | C40; 100% Renewable Energy Campaign; ICLEI Ukrainian Cities; UBC Sustainable Cities Commission |
| 4.2 | Report the percentage of households within the jurisdiction with access to clean cooking fuels and technologies. | C40; GCoM; 100% Renewable Energy Campaign; ICLEI Ukrainian Cities; |
| 4.4 | Report the following information on access to secure energy for your jurisdiction. | C40; GCoM; 100% Renewable Energy Campaign; ICLEI Ukrainian Cities; UBC Sustainable Cities Commission |
| 4.6 | Report the total emissions, fleet size and number of vehicle types for the following modes of transport. | C40; Ecomobility Alliance; ICLEI Ukrainian Cities |
| 11.2 | Where available, please provide the following documentation relevant to your membership in the Green Climate Cities program. | ICLEI GreenClimateCities |
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