Hanoi Declared World's Most Polluted City, Authorities Seek Action

Residential buildings are shrouded behind heavy air pollution in Hanoi on January 3, 2025. (Photo by Nhac NGUYEN / AFP)
Residential buildings are shrouded behind heavy air pollution in Hanoi on January 3, 2025. (Photo by Nhac NGUYEN / AFP)
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Hanoi Declared World's Most Polluted City, Authorities Seek Action

Residential buildings are shrouded behind heavy air pollution in Hanoi on January 3, 2025. (Photo by Nhac NGUYEN / AFP)
Residential buildings are shrouded behind heavy air pollution in Hanoi on January 3, 2025. (Photo by Nhac NGUYEN / AFP)

Vietnam's capital Hanoi has been covered in thick smog over recent weeks, putting it at the top of a list of the world's most polluted cities, as the government said it would push for more electric vehicles (EVs) to alleviate the problem.
Levels of hazardous small particles, known as PM2.5, were measured at 266 micrograms per cubic meter in Hanoi early on Friday, the highest reading among a list of most-polluted cities, according to AirVisual, which provides independent global air pollution information via a phone app.
The Southeast Asian country, a regional manufacturing hub with one of the fastest-growing economies in Asia, has reported severe air pollution in its major cities for years, particularly in Hanoi, Reuters said.
The thick smog is mostly caused by heavy traffic, trash burning and industrial activities.
"We the elderly can feel it very clearly when we suffer from respiratory problems that lead to breathing difficulties," Luu Minh Duc, a 64-year-old resident of the city, said. "The situation seems to get worse recently."
Young people are also complaining.
"At first I thought it was foggy ... but later I found out that it is actually fine dusts that reduce my vision and make me feel like it is not healthy to breathe," said 21-year-old student Nguyen Ninh Huong.
Speaking at a meeting with the transport ministry on Thursday, Deputy Prime Minister Tran Hong Ha called for an accelerated transition to electric vehicles (EVs) as part of the efforts to reduce pollution, state media reported.
So far Hanoi has a target for at least 50% of buses and 100% of taxis to be EVs by 2030.
"This is the responsibility of the state to the people, and there must be specific and timely actions," Ha was quoted as saying by the Tien Phong newspaper.
The ministries of natural resources, environment and health did not immediately respond to Reuters' requests for comment.



Gulf States Unveil Efforts to Develop AI Tools to Combat Fake News

Dr. Preslav Nakov (LinkedIn)
Dr. Preslav Nakov (LinkedIn)
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Gulf States Unveil Efforts to Develop AI Tools to Combat Fake News

Dr. Preslav Nakov (LinkedIn)
Dr. Preslav Nakov (LinkedIn)

One of the significant challenges facing researchers in artificial intelligence (AI) development is ensuring objectivity amid the rapid and ever-increasing flow of information online. With numerous tools now available to disseminate diverse data and information, it has become increasingly difficult for audiences to distinguish between truth and propaganda on one hand and between objective journalism and biased framing on the other.
This has underscored the growing importance of technologies designed to analyze, detect, and filter vast amounts of data. These tools aim to curb the spread of misinformation, combat rumors and fake news, and make the internet a safer space for sharing and accessing accurate information.
Fake news is defined as media content created and published with the intent to mislead or manipulate public opinion, often for political, economic, or social purposes. The methods for creating fake news range from simple manipulation of facts to sophisticated techniques like deepfakes, further complicating efforts to identify them.
In Abu Dhabi, Dr. Preslav Nakov, a professor and chair of Natural Language Processing at Mohamed bin Zayed University of Artificial Intelligence, is leading innovative efforts to develop AI technologies, particularly in analyzing the methods used in media to influence public opinion.
Among his most notable contributions is the development of FRAPPE, an interactive tool for global news analysis. FRAPPE provides comprehensive insights into the persuasive and rhetorical techniques employed in news articles, enabling users to gain a deeper understanding of diverse media contexts. According to Nakov, FRAPPE helps users identify how news is framed and presented in different countries, offering a clearer perspective on divergent media narratives.
FRAPPE’s capabilities also extend to analyzing media framing methods. Nakov explains that the tool allows users to compare how different media outlets address specific issues. For instance, one outlet in a particular country might emphasize the economic implications of climate change, while another focuses on its political or social dimensions.
AI is the cornerstone of FRAPPE’s functionality, enabling the tool to analyze complex linguistic patterns that influence readers’ opinions.
In a discussion with Asharq Al-Awsat, Nakov highlighted the tool’s capabilities, noting that AI in FRAPPE is fundamental to analyzing, classifying, and detecting intricate linguistic patterns that shape readers’ perceptions and emotions. He explained that the application uses AI to identify propaganda and persuasion techniques such as insults, fear-based language, bullying, exaggeration, and repetition. The system has been trained to recognize 23 subtle techniques often embedded in real-world media content.
Ensuring objectivity and reducing bias are among the main challenges in developing AI tools like FRAPPE. Nakov explains that FRAPPE focuses on analyzing the language used in articles rather than evaluating their accuracy or political stance.
To date, FRAPPE has analyzed over two million articles on topics such as the Russia-Ukraine war and climate change. The tool currently supports content analysis in 100 languages, with plans to expand its capabilities to additional languages and enhance the accuracy of its analyses, further strengthening its ability to comprehend global media patterns.