As the COP28 World Climate Summit, scheduled for November 28 to December 12, 2023, in Dubai draws near, the challenges faced by developing countries in the context of climate change are gaining increased attention. These nations are often at the forefront of the climate crisis due to several key reasons. Geographical and climatic vulnerabilities are prominent, especially in island nations like the Maldives and countries with extensive coastlines such as Bangladesh, which face significant risks including flooding and coastal erosion. Additionally, constraints in resources such as infrastructure, technology, and finance impede their ability to effectively adapt and mitigate the impacts of climate change, as seen in Kenya where climate change repercussions on agriculture profoundly affect food security and the economy.
Furthermore, these countries often encounter the complex task of balancing compliance with international Environmental, Social, and Governance (ESG) standards and the necessity of economic growth. This is evident in nations like India, heavily reliant on fossil fuels for industrial and economic development, and Indonesia, facing similar challenges in aligning its nickel industry with ESG norms. The reliance on fossil fuels and less environmentally friendly technologies, often due to their affordability and accessibility, compounds these challenges. This is juxtaposed with the high initial costs involved in transitioning to green technologies and sustainable solutions.
The role of Artificial Intelligence (AI) in addressing these challenges is increasingly pertinent, especially in the lead-up to the COP28 summit. AI can assist in optimizing the use of resources, forecasting and responding to the impacts of climate change, and in the development and implementation of renewable energy solutions. However, harnessing the potential of AI requires significant investments in infrastructure, training, and technology. To strike an effective balance between ESG compliance, economic growth, and adaptation to climate change, developing countries need international cooperation, strategic investments, and the utilization of technological innovations, including AI. This approach is crucial for these nations as they navigate the path towards a sustainable future, a central theme that will undoubtedly be a focus of discussions at the COP28 World Climate Summit in Dubai later this year.
AI in Climate Prediction and Management
AI plays a crucial role in helping developing countries tackle climate change, particularly in extreme weather prediction and long-term climate impact modeling. With its capability to process large datasets, AI enables deeper and more accurate analysis of weather patterns and climate trends, aiding in the prediction of events like floods, droughts, and storms. This is vital for developing countries, which often face limited resource challenges and are vulnerable to climate change impacts.
For instance, India has utilized AI to improve predictions of monsoon seasons and floods. These more accurate predictions allow governments and communities to prepare more effectively, reducing disaster impacts and saving lives. In East Africa, AI is used to predict and manage drought impacts, improving food security and access to water for affected populations.
With the aid of AI, these countries have made significant progress in climate risk management. More accurate early warnings lead to more efficient resource management and reduced disaster impacts. Such initiatives demonstrate how AI can be an essential tool for developing countries in addressing climate change, helping them not only to respond to current challenges but also to contribute to global understanding of climate change.
Optimizing Renewable Energy Use
Artificial Intelligence (AI) is increasingly crucial in enhancing renewable energy efficiency, particularly for developing countries striving to reduce their dependency on fossil fuels. AI enables the optimization of production and distribution of renewable energies such as solar and wind by predicting weather patterns to optimize energy output. This is essential in ensuring that renewable energy can be efficiently and effectively integrated into the power grid.
For instance, countries like Morocco have made significant progress in this area. Home to one of the world’s largest solar power plants, the Noor Ouarzazate Solar Complex, Morocco has utilized AI to enhance its operational efficiency. AI is used to predict solar irradiation and optimize the angle of solar panels, significantly improving electricity generation efficiency. This not only helps in meeting domestic energy needs but also reduces carbon emissions.
In India, the government has used AI to manage the integration of renewable energy into the national power grid. With an energy system heavily reliant on renewable sources, particularly wind and solar, AI is used to predict the energy output from these sources, manage distribution, and balance the load on the grid. This ensures the stability of the electricity grid and reduces the need for fossil fuel-based backup power plants.
The use of AI in renewable energy sectors in developing countries shows great potential in reducing reliance on fossil fuels, reducing emissions, and advancing sustainability goals. Successes in countries like Morocco and India serve as examples for other developing nations in implementing advanced technology to further their renewable energy initiatives.
Natural Resource and Agricultural Management
Artificial Intelligence (AI) offers innovative solutions to enhance food security and the welfare of farmers in developing countries, who typically manage small-scale agriculture. With AI technology, resource management, such as water, can be optimized. AI can predict irrigation needs based on weather conditions and crop types, reducing water wastage and ensuring adequate hydration for crops.
In agriculture, AI also plays a crucial role in predicting pest attacks and efficient fertilizer use. With data from field sensors and satellite imagery, AI can provide early warnings of pest infestations, allowing farmers to take preventive measures. Fertilizer use becomes more effective with AI recommendations based on analytical data, reducing waste and improving crop quality.
Real-world examples of AI use in agriculture can be seen in Kenya, where AI-based applications help small farmers diagnose plant diseases. In India, the Digital Agriculture program uses AI to advise farmers on the optimal planting times and ways to improve crop yields. Such initiatives not only increase productivity and income for farmers but also contribute to reducing greenhouse gas emissions, supporting sustainable and environmentally friendly agricultural practices.
Enhancing Industrial Efficiency
The mining industry plays a crucial role in the economies of many developing countries, contributing significantly to the Gross Domestic Product (GDP), exports, and job creation. Rich mineral and energy resources in countries like Indonesia, Zambia, the Democratic Republic of Congo, and Chile are major drivers of their economic growth. However, this industry also faces challenges in terms of environmental and social impacts, prompting the need for more sustainable practices.
AI in the mining industry offers opportunities to improve operational efficiency, workplace safety, and environmental impact reduction. AI can be used to optimize mining processes, including excavation and mineral processing, reducing waste, and increasing mineral recovery rates. AI-based systems also play a role in monitoring work conditions, such as air quality and structural stability, as well as in reducing energy consumption and carbon emissions.
In countries like Chile and Peru, which have large mining industries, the implementation of AI has brought about significant changes. With AI, these companies have successfully improved efficiency, reduced waste, and enhanced worker safety. This step is not only economically beneficial but also crucial in the global effort to reduce the environmental impact of industrial activities, making it an important step towards more sustainable and responsible industrial practices.
Artificial intelligence offers unique opportunities for developing countries to leapfrog technological barriers on their journey towards zero carbon emission targets. Through strategic implementation of AI, these countries can not only strengthen their efforts in climate change mitigation but also pave the way for more sustainable and inclusive economic growth. However, realizing this requires close global collaboration, continuous innovation, and a commitment to local capacity building.