PolicyandGovernanceAdvisory

Our Work in India

Subnational Engagement and Presence

High-Resolution Source Apportionment
12x12km district-level modeling to identify precise emission hotspots and sector-specific contributors across the state. This granular data allows for the development of targeted, localized mitigation strategies that address the unique atmospheric profiles of individual districts rather than relying on broad state averages.
Socio-Economic Policy Forecasting
Advanced scenario analysis to model the impact of clean energy transitions, such as accelerated EV adoption and Green Hydrogen integration. These forecasts integrate state-specific socio-economic variables, including population growth and industrial development, to calculate the sensitivity of emission reductions to specific subnational policy interventions.
Machine Learnt Spatiotemporal Mapping
Integration of Sentinel-1 (SAR) and Sentinel-2 (Multispectral) data streams into automated Machine Learning (ML) pipelines to classify paddy field extent and flooding dynamics. This geospatial framework provides the high-resolution layer necessary to scale methane emission factors and validate the efficacy of subnational mitigation strategies, such as Alternate Wetting and Drying (AWD).