Emerging Technologies / Green tech

The current AgTech transformation is driven by data platforms (e.g., digital agribusiness platforms and farm management systems), climate resilience tools (including carbon sequestration technologies and soil genomics), and thermal intelligence applications. These technologies optimize resource use, improve decision-making through predictive analytics, and create new revenue streams like carbon credits, directly addressing global food security challenges by increasing agricultural efficiency and sustainability.

Private equity is increasingly focusing on mature AgTech solutions with proven scalability, particularly data platforms and climate adaptation tools, rather than early-stage innovations. This contrasts with traditional venture capital's historical emphasis on experimental technologies, reflecting a market shift toward solutions that demonstrate immediate impact on food system resilience and measurable sustainability outcomes.

The main purpose of GPM Hybrid PPC is to manage hybrid power plants effectively by ensuring grid compliance and optimizing the distribution of active power between PV plants and Battery Energy Storage Systems (BESS), thus promoting grid stability and meeting stringent grid code requirements.

GreenPowerMonitor's energy management solutions, such as the Hybrid Energy Management System, facilitate the transition by optimizing coordination between PV and battery storage. This optimization enhances grid stability and supports the integration of renewable energy sources into the grid, thereby reducing reliance on fossil fuels.

The AI boom has increased demand for energy-intensive data centers, which now account for 1-2% of global electricity use and could reach 3-4% by 2030. This surge creates opportunities for climate tech startups to develop solutions like grid optimization hardware, renewable energy integration, and efficiency technologies to reduce data centers' carbon footprints while meeting rising power demands.

Innovative energy credit frameworks could incentivize data centers to adopt cleaner energy sources and efficiency technologies. These financial mechanisms may help bridge the gap between rising AI-driven energy demands and sustainability goals by rewarding investments in renewable energy integration and carbon reduction initiatives.

Greenwashing refers to the practice of making false or misleading claims about the environmental benefits of a product or service. In tech, this can involve exaggerated claims about energy efficiency, recyclability, or carbon neutrality. For instance, companies like Keurig have faced lawsuits for misleading recycling claims, highlighting the need for consumers to critically evaluate environmental claims (Husson, 2024; TechTarget, 2024)[2].

Technology can play a crucial role in combating greenwashing by providing accurate data and verification tools. Innovations in carbon accounting and AI can help ensure that environmental claims are backed by reliable data, reducing the risk of greenwashing. This approach emphasizes transparency and accountability in sustainability claims (Mightybytes, 2024; Pivit Global, 2024)[4][5].

Lean manufacturing reduces environmental impact by systematically eliminating waste (overproduction, defects, excess inventory) and optimizing resource use through tools like Value Stream Mapping, which identifies energy-intensive processes and material inefficiencies. This minimizes raw material consumption, energy use, and carbon emissions while maintaining production efficiency.

Lean principles bridge operational efficiency and environmental stewardship by creating a culture of continuous improvement (Kaizen) that simultaneously addresses production waste and ecological impacts. Many companies focus solely on end-product sustainability without addressing process inefficiencies, making lean methodologies critical for reducing hidden waste streams in manufacturing.

A circular economy for smartphones is a sustainable model that moves away from the traditional linear 'take-make-dispose' approach. Instead, it focuses on repairing, reusing, refurbishing, and recycling devices to reduce waste, conserve natural resources, and minimize environmental impact. This approach extends the lifecycle of smartphones by managing returns, recovering valuable materials, and reintroducing refurbished devices into the market.

Strategic partnerships in the smartphone industry facilitate collaboration across manufacturers, recyclers, and service providers to implement circular economy practices effectively. These partnerships enable efficient collection of used devices, refurbishment, recycling of valuable materials, and development of modular designs that simplify repairs. Such collaboration reduces electronic waste, lowers carbon emissions, and creates new business opportunities while improving profitability and environmental outcomes.

The circular economy is an economic model focused on designing out waste and pollution, keeping products and materials in use for as long as possible, and regenerating natural systems. Unlike the traditional linear economy, which follows a 'take-make-dispose' pattern, the circular economy aims to create closed-loop systems where resources are reused, repaired, refurbished, and recycled to minimize environmental impact and resource consumption.

AI supports the circular economy by optimizing resource efficiency and waste reduction through predictive maintenance, improving waste sorting with computer vision, and enhancing supply chain transparency and demand forecasting. It also aids in designing products for circularity by enabling better material selection, modularity, and lifecycle tracking via digital twins or material passports. Additionally, AI optimizes reverse logistics for efficient collection and refurbishment of used products, thereby reducing waste and improving sustainability.

Africa's vulnerability stems from high economic dependence on climate-sensitive sectors like rain-fed agriculture, weak adaptive capacity due to limited financial resources and governance challenges, and exposure to extreme weather events. The continent accounts for 35% of global climate-related fatalities (1970-2021) and faces annual economic losses of $7-$15 billion, projected to reach $50 billion by 2030.

Green finance enables investments in renewable energy infrastructure, climate-smart agriculture, and resilience-building projects. These sectors offer high growth potential as Africa transitions to low-carbon economies, with opportunities in solar/hydropower development, sustainable food systems, and adaptation technologies that mitigate climate risks.

Young forests excel at carbon capture because their rapidly growing trees absorb CO2 quickly through photosynthesis. Mature forests reach equilibrium where carbon intake from growth balances carbon released through decomposition, limiting net sequestration.

Reforestation costs $1-50 per ton of CO2 removed through natural regrowth or planting, while industrial carbon capture plants cost ~$1,000 per ton. Trees also provide additional benefits like biodiversity support and air filtration.

When purchasing eco-friendly electronics, consider factors such as durability, repairability, and the use of sustainable materials. Opting for devices made from recycled materials or those with modular designs can significantly reduce electronic waste. Additionally, choosing brands that prioritize sustainability and offer recycling programs can contribute to a more environmentally responsible tech industry.

Consumers can support ethical practices by choosing products from companies that use fairly sourced materials and prioritize labor rights. For example, Fairphone uses fairly mined materials and promotes modular designs for easier repair and recycling. Additionally, buying refurbished electronics from platforms like Back Market can help reduce electronic waste and support sustainable consumption.

GreenOps is a practice focused on minimizing the carbon footprint of cloud environments by efficiently using cloud resources. It involves monitoring and reducing emissions through tools and strategies like optimized code, serverless architecture, and automation (Forrester, 2024; NRG, 2025)[2][4].

Tools like the Free GreenOps tool provide insights into cloud carbon emissions, enabling users to understand their environmental impact. By offering visibility into emissions, these tools empower users to make informed decisions about optimizing their cloud usage, such as using more efficient infrastructure or offsetting emissions (Cloud Carbon Footprint, n.d.; Greenpixie, n.d.)[1][3].

A digital twin is a virtual replica of a physical data center that mirrors its behavior and conditions in real-time. It uses sensor data and software to simulate scenarios, predict performance, and optimize operations for better efficiency and sustainability.

Digital twins help data centers achieve sustainability by optimizing energy consumption through predictive analysis and simulation. They identify inefficiencies, predict peak usage times, and adjust settings to reduce waste, thereby enhancing overall energy efficiency and supporting carbon-neutral operations.

The phrase 'taking the training wheels off clean energy' refers to the need for green technologies to become competitive with fossil fuels without relying on subsidies or support. It emphasizes the necessity for a level playing field where clean energy technologies can stand on their own merit, driven by market forces rather than government incentives.

Collaboration among academia, industry, and government is essential for advancing clean energy technologies because it facilitates the sharing of resources, expertise, and risk. This collaboration helps in addressing large-scale challenges such as grid modernization and infrastructure development, which are critical for the widespread adoption of clean energy.

Laser-based steel production, such as Limelight Steel's technology, uses laser light to process iron ore into iron metal, achieving significant energy savings by eliminating the need for chemical reducing agents and allowing the use of low-grade ores. This method can reduce energy consumption by up to 20% and potentially cut emissions by 70% if powered by zero-carbon electricity[2][5].

Laser welding, particularly the laser multi-pass narrow-gap welding process, offers several advantages over traditional methods like metal active gas welding. It reduces energy input by up to 80%, decreases filler material consumption by up to 85%, and minimizes distortion, eliminating the need for post-weld straightening. This results in faster production times and lower costs[1].

Molten oxide electrolysis (MOE) is a process developed by Boston Metal that uses electricity to produce steel, eliminating the need for fossil fuels like coal. In this process, iron ore is dissolved in an electrolyte and heated to high temperatures, allowing electrons to split the bonds in iron oxide, producing pure liquid metal without generating CO₂ emissions[1][5].

Boston Metal plans to scale up its green steel production by licensing its MOE technology to existing steelmakers. The company aims to build larger demonstration plants and commercial facilities, with the goal of reaching commercialization by 2026. This involves creating modular cells that can be scaled up to produce millions of tons of steel annually[1][5].

In 2025, AI is expected to play a crucial role in IT sustainability by focusing on computational efficiency and energy use. Companies will measure AI deployments not just by performance but also by their environmental impact, prioritizing intelligent workload management and precise resource allocation to reduce energy consumption.

In 2025, data centers will prioritize energy efficiency and sustainability due to environmental regulations and climate challenges. Novel solutions like building data centers in space or using modular fission reactors will be explored to address energy constraints while ensuring continuous operations.

AI can help by optimizing energy use, enhancing renewable energy deployment, and improving waste management. The metaverse, by reducing the need for physical travel, could lower emissions by up to 10 gigatons by 2050. However, both technologies require careful management to mitigate potential environmental downsides, such as increased energy consumption from data centers and e-waste generation.

Successful implementation of AI and the metaverse in reducing emissions requires extensive data and professional oversight. Challenges include ensuring data accuracy, managing the energy consumption of data centers, and mitigating e-waste from technology upgrades. Additionally, transitioning to cleaner energy sources is crucial for these technologies to have a net-positive environmental impact.