Energy Systems & Storage

  • Form Energy — Developing iron-air batteries that can store energy for 100+ hours at a fraction of the cost of lithium-ion. Long-duration storage is critical for renewable integration, and it’s a systems engineering challenge involving materials science, electrochemistry, and grid-scale deployment.

  • Antora Energy — Building thermal energy storage systems using heated carbon blocks and thermophotovoltaics to convert stored heat back to electricity. A novel approach to long-duration storage that could complement renewables, with interesting thermodynamics and materials engineering problems.

  • Heliogen — Using AI and computer vision to optimize solar concentration and achieve extremely high temperatures for industrial processes. Combines computer vision, control systems, and renewable energy to decarbonize hard-to-abate sectors like cement and steel.

Carbon Removal & Utilization

  • Charm Industrial — Converting agricultural waste into stable bio-oil that can be permanently stored underground to remove CO2 from the atmosphere. One of the few carbon removal approaches already operating at scale, with process engineering and logistics challenges.

  • Susterre Farms — Implementing regenerative agriculture practices and biochar application to sequester carbon in soils while improving yields. Engineers can contribute to measurement protocols, supply chain optimization, and soil carbon monitoring technologies.

Building Efficiency & Heat Pumps

  • BlocPower — Retrofitting buildings with electric heat pumps, smart controls, and financing solutions to decarbonize urban heating and cooling. Combines building systems engineering with data analytics and financing models to scale electrification.

Transportation Electrification

  • Revel — Electric vehicle sharing and charging infrastructure operating in dense urban areas. Fleet electrification and charging network optimization present interesting software, hardware, and grid integration challenges.

Agricultural Technology

  • Climate Corporation (Bayer) — Digital farming platform that uses satellite data, weather modeling, and field sensors to optimize crop inputs and practices. Precision agriculture combines geospatial analysis, predictive modeling, and farm systems integration.

Climate Data & Modeling

  • Climate TRACE — Independent emissions tracking using satellite imagery, AI, and public data to create granular, real-time greenhouse gas maps. Direct application of computer vision, remote sensing, and large-scale data processing to climate accountability.

Policy & Market Mechanisms

  • Regional Greenhouse Gas Initiative (RGGI) — Cap-and-trade program covering 11 Northeastern US states that has successfully reduced power sector emissions while generating economic benefits. Demonstrates how market-based mechanisms can drive real emissions reductions at scale.

Today’s Synthesis

The convergence of Climate TRACE ’s emissions monitoring with RGGI ’s cap-and-trade framework presents a concrete engineering opportunity: building real-time verification systems for existing carbon markets. Software engineers can contribute by developing computer vision pipelines that automatically detect and quantify emissions from power plants using satellite imagery, then feed verified data directly into market trading platforms. This solves a critical problem: current emissions reporting relies heavily on self-reported data that’s often delayed or inaccurate. By combining remote sensing, machine learning, and API integrations with existing policy infrastructure like RGGI, engineers can create tools that make carbon markets more transparent and effective. The technical stack involves geospatial data processing, time-series analysis, and building regulatory-compliant reporting systems—directly applicable skills for engineers looking to work on climate impact at scale. The convergence of Climate TRACE ’s emissions monitoring with RGGI ’s cap-and-trade framework presents a concrete engineering opportunity: building real-time verification systems for existing carbon markets. Software engineers can contribute by developing computer vision pipelines that automatically detect and quantify emissions from power plants using satellite imagery, then feed verified data directly into market trading platforms. This solves a critical problem: current emissions reporting relies heavily on self-reported data that’s often delayed or inaccurate. By combining remote sensing, machine learning, and API integrations with existing policy infrastructure like RGGI, engineers can create tools that make carbon markets more transparent and effective. The technical stack involves geospatial data processing, time-series analysis, and building regulatory-compliant reporting systems—directly applicable skills for engineers looking to work on climate impact at scale.