AI has been proposed as an important tool to support several efforts related to nature-based climate solutions such as the detection of wildfires that affect forests and vegetation-based offsets. While this and other use-cases provide important demonstrative value of the power of AI in climate change mitigation, such efforts have typically been undertaken in silos, without awareness of the integrative nature of real-world climate policy-making. In this paper, we propose a novel overarching framework for AI-aided integrated and comprehensive decision support for various aspects of nature-based climate decision-making. Focusing on vegetation-based solutions such as forests, we demonstrate how different AI-aided decision support models such as AI-aided wildfire detection, AI-aided vegetation carbon stock assessment, reversal risk mitigation, and disaster response planning can be integrated into a comprehensive framework. Rather than being disparate elements, we posit that the exchange of data and analytical results across elements of the framework, and careful mitigation of uncertainty propagation will provide tremendous value relative to the status-quo for real-world climate policy-making.

"No-till" and cover cropping are often identified as the leading simple, best management practices for carbon sequestration in agriculture. However, the root of the problem is more complex, with the potential benefits of these approaches depending on numerous factors including a field's soil type(s), topography, and management history. Instead of using computer vision approaches to simply classify a field as till vs. no-till, we instead seek to identify the degree of residue coverage across a field through a probabilistic deep learning segmentation approach to enable more accurate analysis of carbon holding potential and realization. This approach will not only provide more precise insights into currently implemented practices, but also enable a more accurate identification process of fields with the greatest potential for adopting new practices to significantly impact carbon sequestration in agriculture.

Algae, that green scum often seen on the surface of ponds, and credited with harmful ocean algal blooms that kill ocean life might just hold an important key to addressing climate change. Algae, much like trees, uses carbon dioxide to conduct photosynthesis, sequestering CO2 as it grows. Hypergiant, an AI products and solutions company, is harnessing this unique power of algae in its latest technology, the EOS bio-reactor which uses AI to optimize algae growth and carbon sequestration. Its bio-reactor is built to hook up to HVAC systems found in large industrial buildings, skyscrapers and apartment buildings which are some of the biggest contributors to global warming from the CO2 emitted through their energy usage and air conditioning systems. The science is clear that we must not only cut our carbon emissions as a means to stop the irreversible harm of climate change and limit global warming but that we also need to take carbon out of the atmosphere to stay within the stated target 1.5 C of the Paris Climate Agreement.

For good reason, plenty of people are worried about the quantities of carbon dioxide (CO2) that are being pumped into the atmosphere. Since the early 1800s, scientists have known that greenhouse gases in the atmosphere trap heat, causing the effect we now know as global warming. CO2 is a particularly big contributor to this problem. Created as a result of the burning of fuels like oil and natural gas, CO2 makes up the overwhelming majority of greenhouse gas emissions. It represents around 72% of the total, compared to 18% methane and 9% nitrous oxide.