AI and its Application in Green Tech: Europe and China's Common Ground
- Alessia Mazza
- 6 days ago
- 10 min read
Introduction
The application of artificial intelligence (AI) in the European Union and China demonstrates how the two global actors share a common interest in discovering ways in which AI development can help accelerate eco-sustainable objectives. Is the impact of AI on environmental protection, and as a tool to support green technology, superior in terms of benefit or harm? Analysing actions undertaken by the European Union and China and explaining critical issues and emerging challenges underscores different approaches among the two, but similar efforts to furnish an answer on this matter.
Weighting the Impact of AI on the Environment
A crucial issue in AI usage transcends beyond the recent dispute between DeepSeek and ChatGPT. The dispute saw the emergence of Chinese AI app DeepSeek upset the financial markets by establishing itself as the most downloaded app in the U.S. in one week. The Chinese artificial intelligence model DeepSeek-R1 was claimed to have been made with a total sum of 5.6 million USD, in contrast to the 100 million USD it took to develop ChatGPT. Regardless of each system’s computing capabilities, how much energy these tools consume directly impacts sustainability.
Consumption varies depending on the complexity of the AI model and how it is used, but in general, these technologies require massive amounts of electricity to process and analyse data efficiently, and an increasing quantity of water is needed to cool data centers. According to the World Economic Forum (WEF), a single response on ChatGPT consumes ten times the energy required for a Google search. When multiplied by all the platform’s users, the demand for energy grows exponentially. This increase in energy consumption is one of the many factors contributing to a rise in global greenhouse gas emissions. The WEF report also highlights that Microsoft, which has invested 13 billion in ChatGPT, declared a 30% increase in its CO2 emissions due to the use of data centers. This increase is attributed to energy consumption of its data centers, which are facilities where large amounts of data are stored and processed, and they require a large amount of energy to run servers and cooling systems. If the energy used to power data comes from non-renewable sources (like coal), it increases the emissions of CO2. This alarming situation is an emblematic example of how the growing energy demand related to AI is impacting the environment.
While AI helps the energy transition in certain ways, like optimizing energy demand with supply, forecasting renewable energy production more accurately, introducing Smart Grids, or environmental monitoring reducing emissions, it can be argued whether its consumption outweighs the benefits. Specifically, training AI models requires enormous computational power on servers that consume significant energy. Additionally, the production of AI hardware, such as chips and accelerators, requires the use of natural resources and raw materials such as tungsten and tantalum. The extraction of these minerals has in fact negative ecological and social impacts. During the processing procedure of minerals, soil and water can be contaminated by the release of materials and chemical substances, resulting in a consequent toxicity for ecosystems, plants and microorganisms. Furthermore, exposure to tungsten, inhalation, or contact with it can be harmful to human health. After exposure, the bloodstream can carry tungsten to organs, allowing the element to accumulate in human tissues, causing leukemia, lung toxicity and tumors.
Coined "conflict minerals", the extraction of these minerals in some countries fuels conflicts between armed groups involved in their illegal trade. On the other hand, because of the large amount of electronics involved, challenges are emerging in recycling waste. Researchers are working on the development of more eco-sustainable technologies, such as new cooling techniques for chips, creating ‘Superchips’ that use less energy, while adopting alternative energy sources like nuclear energy to power data centers.
Therefore, it becomes essential to adopt a responsible approach to these technologies by carefully evaluating potential risks and benefits. Despite currently being unable to avoid environmental damages brought by AI usage, in many cases, it is contributing to the UN 17 Sustainable Development Goals (SDGs). The UN 2030 Agenda is a program that aims to end poverty, face climate change, and ensure human rights. AI solutions, accompanied by ethical, inclusive, and sustainable principles, can help advance the agenda.
In poverty eradication, or SDG 1, AI boosts agricultural productivity by empowering advanced agricultural systems. In China, Alibaba Cloud launched ET Agricultural Brain in 2018, which tracks the growing conditions of crops and farm animals, detects disease in them, and reduces the risk of accidents and errors in breeding and harvesting. ET Agricultural Brain collects data with facial recognition and real-time monitoring of environmental parameters, and uses algorithms to transform them into information for farmers. In China, the population that relies on breeding and agriculture is large, and increasing the efficiency of this activity translates into an important support for a large part of the population, reducing poverty. For Climate forecasting and disaster management, the thirteenth point of the sustainability goals, it has been launched in Europe the Copernicus Emergency Management Service (CEMS), which is directly managed by the European Commission. It supports the management of natural or manmade disasters by monitoring in real time and identifying anomalies in order to provide immediate action.
In the context of global technological competition, China adopts a pragmatic, results-oriented approach aimed at dominating sectors such as blockchain, semiconductors, automotive, and AI. The PRC is now a central player in Green Tech, due to its position as one of the largest producers of essential materials for this industry, making countries reliant on its resources. Additionally, its long-established expertise, developed over years of early investment in this technology, further strengthens its know-how and influence. In contrast, the European Union stands out for its anthropocentric and sustainable model of technological competition. Human rights, privacy, and ethical issues are the core around which European policies in this competition are generated.
Green Tech in the EU
The European Union has adopted its flagship Green Deal, launched in 2019 by Ursula Von Der Leyen, with the goal to make the EU the first continent to achieve net-zero greenhouse gas emissions by 2050. Key aspects of the Green Deal include promoting renewable energy, sustainable industry, and green mobility. The EU is increasingly focusing on the role of AI in promoting sustainability and protecting the environment. AI is viewed as a critical tool for advancing the green transition, particularly in efforts to mitigate climate change and preserve biodiversity. The EU AI Act, which came into effect in 2024, ensures that AI technologies are developed and implemented with the primary goal of serving humanity while preserving the environment. It encourages interdisciplinary collaboration between social and environmental scientists and AI developers to create solutions that support sustainable practices. Through AI, the EU is not only working to reduce emissions and improve energy efficiency, but also seeking ways to optimise resource use and protect ecosystems across various sectors.
AI can be a positive force in minimising carbon emissions in the economy, creating a net positive impact on the environment and society. For example, Smart Grid is an advanced energy distribution and management system employed by the EU that uses digital technologies, including AI, to monitor, control and optimise the production, distribution, and consumption of electricity. By analysing a large amount of data, AI can predict the user's energy demand and optimise its usage. It can alternate the use of renewable energy with traditional energy and predict impending failures or infrastructure problems, planning maintenance needs before failure occurs. Sensors can monitor carbon emissions in real time from industries, so that they can intervene instantly if limits are exceeded. Meanwhile, AI could also help increase the use of sustainable means of transport with low carbon emissions. Through the Single European Sky project, the EU advances the use of AI to analyse weather data, air traffic patterns and flight plans, which could help suggest more fuel-efficient routes and reduce fuel consumption and emissions.
Another important relevant aspect is sustainable urban development. In the construction sector, the plan promotes the creation of "climate-proof buildings". These buildings are designed to address and mitigate the damage caused by climate change, such as rising sea levels, extreme weather events, and rising temperatures. These structures use advanced technologies such as sensors, automation, and smart systems to reduce energy consumption. Artificial intelligence plays a key role in optimising these systems, analyzing real-time data on temperatures, humidity, and energy consumption to improve efficiency and predict future behavior. Additionally, some buildings employ bioclimatic tools, which integrate natural solutions, such as sustainable drainage systems, to manage heat and rainwater. AI can support these systems through predictive models and intelligent algorithms, improving natural resource management and resilience to the impacts of climate change.
But how far has the application of AI come today in the context of the European Green Deal? The project currently faces a few major controversies. The adoption of AI in the Green Deal often entails high upfront costs for the implementation of technological solutions, research and development, and staff training. For many European small and medium-sized enterprises (SMEs), these financial barriers could represent a significant obstacle. The European Structural and Investment Funds, with a budget of 392 billion euros for the 2021-2027 period, are investments from member states in projects aligned with the EU’s priorities to support the ecological transition. Unfortunately, not all EU countries are equally ready for this transformation.
Countries with a strong dependence on carbon-intensive sectors, like coal, may find it difficult to meet the Green Deal's goals. Climate justice, therefore, remains a delicate issue. Furthermore, the production of electronic devices necessary for AI has a significant environmental impact and damages ecosystems, conflicting with the sustainability objectives of the Green Deal. This is why the EU is investing in technologies to improve the energy efficiency of data centers, and pushing for the transition of the latter to renewable energy sources. Besides, the AI Act, approved and entered into force in August 2024, comes to support human rights to ensure that the use of these technologies does not compromise safety, fundamental rights, and the environment.
Green Tech in China
In the context of Green Tech, the European Union's goals converge with those of China in terms of investments and efforts. China has made enormous progress, becoming a global leader in renewable energy investments. Since 2006, it has passed Renewable Energy Laws and reduced solar energy costs by 80%, playing a crucial role in the global ecological transition. Major green tech sectors in China include electric vehicles, lithium-ion batteries, and solar photovoltaics. Moreover, it is massively exporting renewable energy technologies to emerging economies like Indonesia, Chile, and Morocco.
Currently, green technology is rapidly evolving. China has launched further policies for the implementation and development of low-emission hydrogen technology, confirming Beijing’s role as a key player in the ecological transition. As stated by the International Renewable Energy Agency in 2019, no country is better positioned to become a superpower in renewable energy than China, which remains the largest producer, exporter, and installer of solar panels.
The U.S., on the other hand, has taken several actions to limit China’s dominance on AI tools in Green Tech, such as imposing tariffs on Chinese imports. However, this choice has concerned environmental activists, raising doubts about the real interests at play. For these activists, such actions do nothing but slow global ecological transition, forsaking the well-being of the planet and humanity. After all, China’s investments in green technologies – such as in solar, wind, and electric vehicles – have the potential to expedite the achievement of several SDGs, particularly those related to clean energy and climate action.
Regarding ecological urban development, which aligns with the interests of the EU, China is home to some of the most famous examples of smart cities. The focus of the smart city model is to merge technological progress, notably digitalisation and informatisation, with urban developmental needs to improve the quality of life, save energy, and reduce carbon emissions. Governing Beijing, Guangzhou, and Chongqing, China is in charge of some of the most competitive smart city projects. Smart cities in China integrate sensors and automation to optimise transportation, security, and environmental resources and maximise their usage, also saving costs.
In these cities, real-time data are collected and analysed to provide timely information and solutions. For example, the Internet of Things allows urban management personnel to monitor the status of everyday objects like vehicles and internet-connected appliances to communicate and exchange data. In Guangzhou, for instance, soil moisture is monitored through sensors and sent to an intelligent irrigation management system to properly care for trees. The main concern is the exposure of resident data to cyberattacks. But as some studies have reported, smart city technologies are more likely to collect data on local infrastructure status than on residents' behavior or activities. In other cases, data are collected regarding residents’ behavior in the community, not on an individual level. Sensors that monitor resource use, smart water management, and intelligent trash bins should not, in fact, pose a significant threat to privacy, as the data collected is generally aggregated and anonymised. These systems focus on optimising efficiency rather than tracking individuals. They improve energy efficiency by monitoring real-time consumption, reducing emissions in smart cities by up to 5% while saving money. Water management prevents issues like flooding, while smart traffic signs help cut down hours spent in traffic.
These measures helped improve living standards and sustainability. Before implementing smart measures, Hangzhou was ranked 30th in the world in traffic congestion. In 2015, the local government decided to work with Alibaba and its cloud computing platform to solve this problem, monitoring traffic using data from the transportation department and a map app. Traffic speed in that area increased by 15% in the first year of operation, allowing a more effective use of energy. Furthermore, the data collected to make this happen are merely about bins’ condition and traffic conditions on the road and where vehicles are located. If the data is only used to manage traffic, the risk of infringing upon individual privacy is low. That being said, there is a concern that poor management of population data may result in information leaks. Whether such data would be used commercially without prior notice is another issue of distress.
Conclusion
In both PRC and the EU, despite varying policies, approaches, and timelines, there is a shared commitment to a common goal. The efforts made by both to integrate AI into green technologies, along with new investments aimed at researching methods to reduce the environmental impact of data centers, unite them in pursuit. While Beijing has long invested in renewable energy sources and established itself as a global leader, the EU, through the Green Deal objectives, investments, and emission reduction programs, aims to become the first continent to achieve net-zero greenhouse gas emissions by 2050. This is being pursued by focusing on renewable energy and green mobility, while integrating intelligent technology systems. AI plays a crucial role in this process by optimising resource usage, improving energy efficiency, and monitoring emissions. Chinese and European smart cities alike use sensors and AI to enhance energy efficiency, monitor traffic, and manage urban resources, improving quality of life. However, both regions continue to face new challenges, including concerns about high costs and the environmental impact of electronic device production.
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ABOUT THE AUTHOR
Alessia Mazza studied Languages and Cultures of Asia and Africa at L’Università degli Studi di Napoli “L’Orientale.” With a growing interest in digital marketing, she has taken on roles as a writer, translator, and content creator, focusing on China–Europe and China–Italy relations. She is passionate about global languages and cross-cultural communication.
This article was edited by Stefano Bertoli and Marina Ferrero.
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