Climate Change and Artificial intelligence

What is climate change?

Climate change refers to permanent changes in world weather and temperature patterns that occur gradually and periodically. Such changes can be caused by natural factors, such as volcanic eruptions and human activities. Industrialization in the early 19th century was the starting point for climate change, which mainly came from the use of fossil energy such as oil, gas and coal.

Climate change is triggered by an increase in greenhouse gases, especially the concentration of carbon dioxide (CO2) and methane (CH4) in the Earth’s atmosphere. Both of these gases absorb heat and trigger global warming that causes impacts, such as: an increase in the earth’s temperature; climate and weather uncertainty; melting polar ice caps that drive sea level rise; increased extreme weather events (droughts, floods and tornadoes), loss of biodiversity and changes in human habitation conditions. To deal with this terrible impact, for more than 4 decades the global community has begun to find the best way to cope and adapt to the impact.

The initiative to address this issue began in 1979 and is known as the first world conference on climate or World Climate Conference (WCC). Then in 1992, the United Nations together with world countries built an international agreement called the United Nations Framework Convention on Climate Change (UNFCCC). This initiative was formed as an international collaboration framework in tackling climate change by reducing the rate of world temperature rise that triggers climate change and finding ways out of the effects of climate change. Furthermore, in 1995 the first COP was held in Berlin, until this year the 28th COP will be held on November 30 to December 12, 2013 in Dubai (UAE) (UNFCCC, 2023).

Various forms of programs in mitigation and adaptation have been carried out, mainly pro-environmental policy making by the government and emphasizing environmental impacts in business activities. There are 5 sectors that are the focus as emission sources, consisting of; forestry, agriculture, energy, waste (Bappenas, 2021), and industrial sectors. Some of the policies made related to the 5 sectors are:

  1. Increasing the proportion of renewable energy use, by limiting the use of increasingly extracted and used fossil fuels that will cause climate change to worsen. Thus, changing to clean and renewable energy sources is the best way to stop using fossil energy.
  2. increased energy efficiency, which has a central role in tackling climate change. Energy efficiency, can be done in several forms, for example: reducing product weight while still providing the same service (light-weighting); reduce yield losses in the production process; find alternative uses for second-hand goods without remelting; reuse and recycle components; making more durable components of products; and use the product more intensively or with higher capacity
  3. transformation towards sustainable transportation. Transport is one of the sectors targeted for effective interventions to reduce CO2 emissions, so adaptation measures are needed to reduce vulnerability to climate change. Improving fuel efficiency in the transportation sector, especially through: the use of sustainable biofuels, mass transportation use campaigns, and the implementation of emission taxes from the use of private vehicles (UNECE 2023).
  4. Forest protection and ecosystem restoration to sequester more carbon. Reducing pressure on land clearing, especially land for consumption such as agriculture and plantations, can help avoid large carbon losses. Forests are nature’s most important object in tackling climate change, and forest protection is key to climate issues.

Benefits of AI in climate change mitigation efforts

Another aspect that is currently starting to attract attention in handling climate issues is the use of AI (Artificial Intelligence) technology. AI is nothing new, but it has grown rapidly in recent years, and today its potential is getting better and bigger in shaping our world than ever before. AI is a transformative shortcut that may solve the world’s biggest problems, including climate change.

This technology can be a driving force and change the way we deal with climate change. The following are examples of AI practices in revolutionizing our fight to drive climate change action solutions;

  1. Renewable Energy: AI helps optimize the efficiency of solar panels, wind turbines, and other renewable energy systems and minimize their costs. Machine learning algorithms can predict weather patterns to adjust energy production, thus ensuring a constant power supply. In addition, AI is helping to develop advanced materials for energy storage, such as high-capacity batteries, so that renewable energy becomes more reliable.
  2. Energy Efficiency: One of the most significant contributors to climate change is excessive energy consumption. Smart grids and AI-driven energy management systems can optimize energy distribution, reduce waste, and encourage the integration of renewable sources. Machine learning algorithms can predict demand patterns and adjust energy production accordingly, thereby minimizing dependence on fossil fuels. (Ipswich A 2023).
  3. Emission Reduction: AI can revolutionize industries by optimizing processes and reducing emissions. For example, in manufacturing, AI-based predictive maintenance can minimize equipment damage, preventing the release of pollutants. In agriculture, AI can minimize the use of pesticides and fertilizers, monitor soil moisture levels to identify appropriate irrigation efficiency, increase crop yields while reducing the environmental impact of agricultural activities and improving the livelihoods of rural communities. (World 101, 2023)
  4. Climate Modeling and Prediction: AI enables more accurate climate models by analyzing very large data sets and predicting climate trends. This information is critical to making the right decisions and policies. Predictive analytics can help anticipate extreme weather events, enabling better disaster preparedness and response. In addition, AI can be used as a carbon counting tool in tracking and reporting accurate emissions so as to help a business’s sustainability target.

Double-edged sword?

AI does have enormous potential in accelerating climate change resolution by optimizing programs or reducing inefficiencies. But on the other hand, there is a price to pay regarding the use of this revolutionary technology. AI requires supercomputers and servers that must be supplied with large amounts of electricity.  As a simulation example, the ChatGPT application will be used as a prototype in quantifying the relationship of AI in general with energy needs. Calculated data available to date, the number of ChatGPT users is around 180.5 million, with an average monthly visit of 1.5 billion visits. Based on statistics (Duarte, 2023), visits on ChatGPT have increased by 150% since February 2023 which is only 1 billion visits. In fact, the use of this site increased by 6 times more than the visit data in December 2022 which only had 266 million visits. Thus, it is not impossible that in the first semester of 2024 the number will continue to soar. This is related to the provision of electrification of this application.

The results of the study in 2023, as ChatGPT grows in popularity, the use of AI can increase global electricity consumption needs by 85-134 Terawatt-hours (TWh) per year by 2027 [de Vries, 2023]. In another study, algorithms in the training phase of AI models used such as ChatGPT’s GPT-3, Gopher, and Open Pre-trained Transformer (OPT) can consume electricity of 1,287, 1,066 and 324 MWh, respectively. So the scientists concluded, the energy requirement to turn on ChatGPT is 564  MWh  per day, assuming an estimated 1,287 MWh used in the training model  phase (Krishnamurthy,  2023).

Emissions from electricity use of 1 Mega Watt per Hour (MWh) are equivalent to 0.4765 tCO2e. Meanwhile, the total use of electrical energy for ChatGPT per day is 564 MWh. Thus, the total emissions resulting from the use of ChatGPT are 268.7 tCO2e/day (EPA, 2021).

To reduce emissions, forests composed of natural trees are one source to neutralize them. Based on research from Encon (2023), that every single tree in a natural forest has the ability to absorb CO2 of 21.77 kgCO2 – 31.5 kgCO2. To neutralize the emissions produced from ChatGPT of 268.7 tCO2, 8,331 – 12,362 trees are needed. Forestry research shows that tropical rainforests in Indonesia have a tree density per hectare of 531 – 638 individual trees (Wilkie 2004). So it takes 16.1 – 22.5 hectares of forest to neutralize emissions from using ChatGPT for 1 day around the world.


AI has the potential to play an important role in driving climate action solutions around the world. With the ability to monitor, analyze, and respond to environmental changes. In addition, AI can help reduce carbon emissions, improve environmental outcomes, and create a more sustainable future for the people of the world. Therefore, governments, businesses, and societies must seize this opportunity and use AI as a tool to create a more sustainable future.


Bappenas (2021). UPDATED NDC INDONESIA FOR A CLIMATE-RESILIENT FUTURE. Available at: (Accessed: November 20, 2023).

Encon 2023. Calculation of CO2 offsetting. Available at:,by%2031%20to%2046%20trees (Accessed: November 20, 2023).

de Vries, A. (2023) ‘The growing energy footprint of Artificial Intelligence’, Joule, 7(10), pp. 2191–2194. DOI:10.1016/J.Joule.2023.09.004.

Duarte, F. (2023) Number of CHATGPT users (Nov 2023), Exploding Topics. Available at: (Accessed: November 20, 2023).

EPA (2021). eGRID. U.S. annual national emission factor, year 2019 data. U.S. Environmental Protection Agency, Washington, DC.

Ipswitch A (2023). AI and Climate Change: Pioneering Technologies for a Sustainable Future. Available at: (Accessed: November 20, 2023).

Krishnamurthy, R. (2023) Projected increase in AI’s electricity use comparable to annual consumption of Netherlands, Argentina: Report, Down To Earth. Available at: (Accessed: November 20, 2023).

UNECE (2023). Climate Change and Sustainable Transport. Available at: (Accessed: November 20, 2023).

UNFCCC, (2023). History of the Convention. Available at: (Accessed: November 20, 2023).

Wilkie P., Argent G, Campbell E, Saridan A (2004). The diversity of 15 ha of lowland mixed dipterocarp forest, Central Kalimantan. Biodiversity & Conservation (13), 00. 695-708. doi: :10.1023/b:BIOC.0000011721.04879.79

World 101 (2023). How Can Artificial Intelligence Combat Climate Change?. Available at: (Accessed: November 20, 2023).


Writer: Irwan Budiarto (ENS)

EcoNusantara brings expert knowledge and linked engagement approach to support clients and stakeholders in developing innovative solutions committed to environmental and social responsibility. This section presents the latest dynamics of works and activities that we do.
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