The adaptation and mitigation framework for analyzing Climate-tech
Not every low-carbon tech should be called Climate-tech
I haven’t come across a standardized definition of what qualifies as climate-tech. It’s important to arrive at a common definition of climate-tech as it has a policy and financial implications for stakeholders working in this space as well as for millennials opting to forge their careers in this field. Humans and mother-nature comprising Land, Oceans, Atmosphere, and Forests create a dynamic yet interconnected cycle of interactions. Any external disturbance to these cycles such as additional flux of greenhouse gases being pumped into the atmosphere, or plastics/ rare earth metals being discharged in oceans/rivers causes extreme consequences many of which are still unknown and will be felt over a long time. Going by that framework, a climate-tech could try to restore this balance by reducing those fluxes while not impacting our productivity or a climate tech could help us adapt to the consequences -both of which are the need of the hour. In this blog, I am going to focus on tech that helps us mitigate or adapt to the impacts of additional GHG related fluxes into the atmosphere. However, the qualification of that tech as climate-tech should aim at a system level and long term land, water, vegetation, and air impact assessment.
Battery tech is one such example of a low carbon tech that should not be called Climate-tech yet till all environmental externalities are accounted for. We all know that advancements in batteries are accelerating the adoption of EVs, and transforming electric grids from being high emission, centralized to decentralized, distributed, and clean sources of power. However, such a transformation might come at the cost of an environmental externality such as intensive mining of rare-earth metals, and the problems of water contamination that comes with dumping used batteries near river sites the likes of which we are currently observing in China. We have committed the mistakes of not the long-term system-level consequences of new technology on mother nature in the past many times.
As an example, going by today’s standards- internal combustion engines were also called Climate tech in the early 20th century. Their invention and affordable scale-up by Henry Ford, pumped by the Texas oil boom immediately provided relief from the great horse manure crisis of 1894. Today, 60% of the U.S GHG emissions come from internal combustion engines.
That said, I have taken an attempt to take a holistic yet deeper level classification of Climate-tech understanding across each of the industries. I have intentionally left out battery tech from my analysis until we have a better understanding of its long-term consequences. Not all of it could be covered in this post, I will go deeper into each of the industrial sectors in further blog posts. The most relevant categorization for the tech solving climate problems would be Mitigation tech as well as Adaptation tech.
Mitigation Tech: We are currently pumping 37 Gigatons of GHGs into the atmosphere, increasing at almost 2% every year, treating our atmosphere as an open sewer. We continue on this pathway, we will consume our carbon budget in the next 10–15 years. We need to be net zero emissions by 2030, in order to give us a 66% chance of limiting the global temperature rise to 2 degrees. Of the current emissions, Energy, Food & Agriculture, Transport, Industry, Transportation, and Buildings contribute to 35%, 24%, 21%, 14%, and 6% respectively. The net-zero pathway can be realized either by substituting emission-intensive technologies in each of the contributing sectors with clean ones(replace), making the existing one more efficient(clean), or by sequestering(store) carbon using other sectors such as forestry, land use, and agriculture as carbon sinks. According to the emission pathways calculator of the Department of UK, there is an opportunity to limit it to 40GT as opposed to 60 GT in 2050 in the business as usual scenario. Assuming a conservative market price of $15/ton, that alone presents a $300 Billion market opportunity for start-ups globally. This is a back-of-the-envelope calculation, and some sector-specific adjustments need to be done in order to assess the right market opportunity. However, the scale of the opportunity is undebatable. Every one of those themes is worth writing a book about but I would limit myself to giving a brief description of each of those here:
Replace- Substituting less emission-intensive technologies: Most of the renewable tech, EV-tech(jury is still out), and alternate protein markets, qualify in this category and have seen big home runs in the last decade such as Sunrun, SolarCity, Impossible foods, Tesla and this space continues to see new investments in exciting companies and new venture capital and PE/infrastructure funds raising capital to help scale technologies in this space. A few examples of recent additions in this space are Mortal, DSM, IndigoAg, Fervo Energy, and certainly not an exhaustive list. Sub Sectors that are yet to see major innovations on this front are cement, and broader manufacturing space.
Reduce- Making existing tech more efficient: Recent research published by Nicholas Stern, and Montek Ahluwalia concluded that 75% of the emissions reduction in India-(the third largest emitter of GHG) is possible from efficient city planning, efficient buildings, and efficient industrial technologies alone. Modeling done by other nonprofits and governments has arrived at a similar scale of numbers for energy efficiency around the world. This is clearly a low-hanging fruit with the shortest NPV and highest ROI for all the players involved in capturing value. This space also has seen home runs such as EnerNOC, and Opower, however, surprisingly hasn’t seen the same level of investments and innovations. Breakthrough ventures recently funded 75F.
Sequester- Generating carbon sinks: This sector is at an inflection point now. For years, carbon capture and storage have tried to disrupt this space and make inroads by working with Oil & Gas companies, Chemical companies for a decade. A handful of them survived- such as Carbon Clean Solutions started by my friend-Anirudha Sharma. Suddenly, the revival of interest in forestry and agriculture emissions has reinvigorated this space and we are seeing a rush of start-up and investment activity with players such as Nori, IndigoAg, Pachama. One estimate says that soils today hold 1% organic carbon which if increased to the earlier levels of 3% could help sequester one-third to half of the current GHG emissions however, the jury is still out on this claim without a lack of long-term data. Theoretically, soil-based carbon sequestration could enable the transition to a net-zero emissions world, however, without any global acceptable standards of quantifying sequestration, I will be cautiously optimistic of the initial buzz around this space.
Adaptation tech: Last three years alone, climate-related disasters cost the world close to $650 Billion. This figure doesn’t include the impact due to slowly changing weather variability that impacts the production of food and fiber. As an example, weather variability causes annual losses of more than $0.5 billion/year in the U.S Corn belt- this doesn’t include the economic costs of extreme disasters. The adaptation pathway for any industry will consist of three steps- changing infrastructure/design to reduce long term risk, respond better to the changing weather variability and transfer the rest of the risk to the new class of climate insurance and financing products. It’s unfair to describe each of those strategies in a few lines but I will demonstrate using a specific example of the buildings sector
Reduce-Enabling Infrastructure Changes: This will entail designing new material for infrastructure as well as changing engineering designs- for roads, bridges, buildings, and farm infrastructure that can withstand new intensity and frequency of extremes every year. Resilience to extreme wind speeds from category 4–5 hurricanes on the coastal infrastructure on the Atlantic coast of the U.S is one such example. The State of New Jersey has already rolled out regulations mandating building codes to comply with the new climate normal. This is quite an unmet need in the industry and has not seen many start-ups in this space. Even if there are a few climate prediction start-ups-hardly any of them go into integrating those predictions for producing actionable insights. Most of the government centers such as Environment Canada have done the majority of the work in this space.
Respond- Responding better to in-season extreme risk: Industries and businesses are not new to this pain point. Weather Channel now IBM has been providing warning to the rail-road companies about the Tornado risks in the midwest for the last thirty years. However, most of the progress done in this space is in the weather time frames(min out to a week out). Depending on the industry, the insights would only be actionable if it is provided with sufficient lead time. A construction manager can reschedule his crane movements only if they know at least 2 weeks in advance. Unfortunately, not many innovations have happened in weather/climate space in those lead times and above with the exceptions of a few government centers such as NOAA and ECMWF. ClimateAi has made some inroads on that front with the use of transparent AI and if scaled would be a cheaper, faster and more useful way of running weather/climate forecasts. Other groups such as Tapio Schneider’s group have done path-breaking stuff in this space. Jupiter too is also trying to make inroads in this space.
Transfer- Risk Transfer: The third and in many cases the last step would be to transfer risks that can’t be managed or reduced through climate insurance and financing products. These products underwrite risk from a long-term horizon- time frames in which climate risk could be measured reasonably rather than historical looking underwriting It’s a very nascent industry as the lending and insurance industry still relies on historical information to underwrite next year's policies. We have seen some signs of it when Nephilla Capital launched drought insurance for Africa. The resurety-Boston-based start-up has been one of the successful entrants in long-term insurance with their proxy revenue swaps for Wind Industry. I believe this is an area ripe for disruption with advances in climate science, imagery-based claims processing, and a need for pricing climate risk specific to a location, and customer profile both for B2B and B2C markets.
However, successful businesses are not built on looking at the macro trends or dollar amounts of the opportunities available. Every sector has its own dynamics, readiness, willingness of the companies to pay, budget cycles, and regulations that provide push and pull for climate solutions in that space. We have seen that in France as an example for the financial services sector- where Climate risk reporting is mandatory at the regulatory level for all the funds. This along with an anticipation of more regulators adopting such policies has allowed companies such as 427mt.com, Carbon Delta, Sustainalytics, and Trucost to get traction and eventually get acquired. I have tried compiling the above framework in the chart above. This is not an exhaustive list of companies by any measure and is based on my understanding of their product offerings. However, as we can see from the diagram above, the sector is just beginning to see the investment in this space. Before interpreting this chart- it’s important to read the following caveats:
- This is not the exhaustive list of companies/start-ups in every sector but an indicative list intended to convey the framework.
- The list consists of both mature companies as well as start-ups.
- White-space means that I have not known any start-ups working in that space.
- For finance and insurance, it's difficult to segment that into the “replace, reduce, and transfer framework”.
I am grateful to my colleagues and friends- Sudarshan Bhatija and Anshuman Bapna for their review and contributions to this article
