Climate Co-benefit Methodologies
Climate co-benefit approach supports local governments in measuring and reporting the climate mitigation and adaptation impacts of initiatives that are not primarily climate-focused but generate significant climate benefits. These methodologies enable governments and project implementers to demonstrate the climate value of interventions of urban forestry and Single-Use Plastic (SUP) ban policy. Governments can report on climate co-benefits under State Action Plans and National Missions on climate change, while companies can highlight these co-benefits under their sustainability reporting.
Approach to development of Methodology
These methodologies are developed under the project “Indo-German Support for Climate Action in India and the IKI Interface Project” (CAP)” supported by the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Climate Action, and Nature Conservation (BMUKN). The project is implemented by GIZ India under the overall guidance of the Ministry of Environment, Forest and Climate Change (MoEFCC). The consortia of Oxford Policy Management, the Council on Energy, Environment and Water (CEEW) and the Perspectives Climate Group (PCG) provided technical support for the development of these methodologies.
The methodologies are developed and piloted with Maharashtra as one of the pilot states. State Climate Action Cell under the Department of Environment and Climate Change of Government of Maharashtra anchored the state level engagement in the Maharashtra.
The methodology was developed through a structured, evidence-based process combining research, field experience, and stakeholder validation. An extensive literature review identified relevant global and national frameworks and data parameters for assessing mitigation and adaptation co-benefits. These frameworks were then contextualised for local conditions. This was followed by stakeholder consultations in Maharashtra with various government departments, research institutions, corporates to further contextualize the framework. Semi-structured interviews and field visits strengthened practical relevance. The methodology was presented regularly to MoEFCC for its review and feedback. Post the development of Co-benefit assessment tool state-level validation workshops with forest officials, municipal authorities, and other stakeholders helped finalize the tool. All the insights gathered from detailed consultations and validations were synthesized to ensure the methodology is scientifically robust, operationally feasible, and aligned with national and state climate policy objectives.
Urban Foresty CCOB Methodology
The Urban Forestry Climate Co-benefit (CCOB) methodology estimates mitigation and adaptation co-benefits from urban forestry projects in India. Mitigation benefits are calculated through carbon removals in above-ground and below-ground biomass using a planting unit (PU) approach, with annual CO₂ accounting. The methodology considers carbon sequestration as well as losses from harvest, fuelwood collection, and natural disturbances, while accommodating varying levels of data availability without adding burden on stakeholders. Adaptation co-benefits include urban heat island reduction, changes in groundwater recharge, flood and stormwater management, and biodiversity improvement. Click here to access the tool
SUP Ban Policy CCOB Methodology
The SUP Ban Policy Climate Co-benefit methodology estimates mitigation and adaptation benefits from implementing SUP bans and increasing the adoption of alternatives to SUP. For mitigation calculations, users may select Tier 1–3 approaches depending on data availability. Adaptation benefits are quantified across three parameters: reduced blockage of storm drains (lower urban flood risk), reduced plastic leakage into water bodies (improved environmental health and resilience), and employment generation in alternative industries (enhanced socioeconomic resilience). Click here to access the tool
The above tools took in account the challenges of data availability and complexity of their use. The tools are designed in way that data availability is not a limiting factor to generate required results. They are also designed for ease of use.
