Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. In this edition, we are exploring the emerging market for climate technology, exploring their significance, and addressing why a successful path forward lies in embracing clean, green, and planet-friendly solutions for both startups and established companies. Let’s dive right in.

What is climate technology?

Climate technology leverages a range of dynamic technologies and systems to address the challenges posed by climate change. This collaborative effort draws on diverse areas of expertise, incorporating engineering, materials science, environmental science, economics, and policy development. It unites these disciplines to forge innovative solutions for mitigating and adapting to the impacts of a changing climate.

Climate tech startups, on the other hand, are companies that are developing new technologies and products to help mitigate climate change and adapt to its devastating impacts on the environment and society. In recent years, investment in climate tech startups has surged, and many of these companies are now scaling up their operations to unprecedented heights. 

In 2023, the total enterprise value of climate tech startups worldwide soared to a whopping $2.6 trillion, a 60-fold increase in its value over the past decade. This remarkable growth trajectory underscores the burgeoning significance of climate tech in the global business landscape. These companies also witnessed an impressive milestone in 2022, with over 240 climate tech startups individually commanding valuations exceeding $1 billion. Notably, as of January 2023, the number of climate tech unicorns–startups valued at over a billion dollars–reached 83, collectively contributing to a market capitalization surpassing $180 billion.

Let’s take a look at five interesting reads that explore the exciting world of climate technology, how it is thriving (and how it might not be) and most importantly, how this technology is helping to solve our climate crisis.

  1. Microsoft teamed up with a nonprofit using autonomous ‘interceptor’ boats to clean up the ocean and is helping it identify trash with machine learning

The Ocean Cleanup, a nonprofit focused on combating plastic pollution in the oceans, is using innovative technology to address the problem on multiple fronts. The organization uses solar-powered catamarans called interceptors to autonomously collect plastic from rivers before it reaches the ocean. They plan to deploy interceptors in 1,000 of the most polluted rivers across the globe within five years. The Ocean Cleanup also deployed machine learning models to help identify plastic in rivers and remove them before it reaches the oceans.

  1. Using open source AI to map global pollution through imagery

Deep learning is making strides in addressing societal issues through technology. One such area is the potential use of deep learning for social good, including tasks like estimating natural disaster damage and mapping illegal fishing. With concerns about environmental impacts, AI could play a huge role in shedding light on how our societies affect the natural world, such as automatically mapping and addressing the growing problem of litter and illegal waste dumping.

  1. Emerging tech, like AI, is poised to make healthcare more accurate, accessible and sustainable

Emerging technologies like AI and ML are reshaping the healthcare sector, contributing to more sustainable and planet-friendly practices. These technologies enhance healthcare efficiency, precision, and diagnostics, leading to reduced resource wastage. AI automates diet recording, promoting sustainable dietary habits, while digital biomarkers and genomics improve preventive health. However, this transformation must be accompanied by a commitment to privacy and security, ensuring that patient data remains protected.

  1. The future of disaster planning: How AI & ML models could protect communities from natural disasters

Guessing the weather is hard enough. Predicting when the next natural disaster is going to happen is almost impossible. However, AI and ML models are changing the game, emerging as trailblazers in predicting and responding to natural disasters. This data can be used to improve disaster planning and amp up response efforts. The ML models can be used to analyze large amounts of data to identify patterns that can help predict when and where the next disaster will occur. This information can then be used to warn people and prepare for evacuations, survey disaster areas, and identify survivors.

  1. Feeding the world by AI, machine learning, and the cloud

World population and climate change present significant challenges to agriculture. These challenges—including the overuse of freshwater, droughts, and heatwaves—threaten crops. This article suggests that a planet-friendly agriculture approach requires a leap beyond traditional farming practices, and sees AI as a key driver in this agricultural revolution. AI and ML can enhance scientific research and accelerate the development of innovative solutions. The shift to the cloud and greater digitalization enable greater collaboration and innovation in agricultural science. Researchers believe the next three years will see a transformation in agriculture, driven by smarter data utilization.

Wrapping up

The climate tech ecosystem has identified a remarkable 1,642 venture capital-backed climate tech companies by 2022. These companies are categorized into seven distinct verticals, each targeting specific sectors, ranging from food and land use, to energy, and transportation. All of these sectors collectively contribute to a more sustainable and climate-resilient future.The goal of climate tech startups is to combat climate change, promote environmental sustainability, and create a more sustainable and resilient future for our planet. Ambitious, bold, and daring, climate action plays a crucial role in developing and implementing innovative solutions that can contribute to a greener and more environmentally responsible world.